From 2b998486d89ab5bf2889e3be407f01c65a4f35bc Mon Sep 17 00:00:00 2001 From: Max Jones <14077947+maxrjones@users.noreply.github.com> Date: Wed, 7 Aug 2024 17:17:23 -0400 Subject: [PATCH 001/152] Fix link in global reanalysis data page --- datasets/global-reanalysis-da.data.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/datasets/global-reanalysis-da.data.mdx b/datasets/global-reanalysis-da.data.mdx index f8d3e6625..02c51803a 100644 --- a/datasets/global-reanalysis-da.data.mdx +++ b/datasets/global-reanalysis-da.data.mdx @@ -416,7 +416,7 @@ The output variables available on VEDA include evapotranspiration (ET), gross pr ## Explore the Data -The global reanalysis is a large dataset with nearly two decades of daily output. Here we show a comparison of two dates for a single variable. We encourage users to Explore the Data to look at different dates and to compare variables. +The global reanalysis is a large dataset with nearly two decades of daily output. Here we show a comparison of two dates for a single variable. We encourage users to [Explore the data](https://www.earthdata.nasa.gov/dashboard/exploration?search=global-reanalysis-da) to look at different dates and to compare variables. An example of how trends calculated from the global reanalysis model output can be used to understand changes in TWS, GPP, and ET, can be seen in the corresponding data story. From 42a801c43e86cf7cdd5508dd650b8a2ff11f518c Mon Sep 17 00:00:00 2001 From: Max Jones <14077947+maxrjones@users.noreply.github.com> Date: Thu, 8 Aug 2024 11:05:29 -0400 Subject: [PATCH 002/152] Update datasets/global-reanalysis-da.data.mdx Co-authored-by: Slesa Adhikari --- datasets/global-reanalysis-da.data.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/datasets/global-reanalysis-da.data.mdx b/datasets/global-reanalysis-da.data.mdx index 02c51803a..6600f0974 100644 --- a/datasets/global-reanalysis-da.data.mdx +++ b/datasets/global-reanalysis-da.data.mdx @@ -416,7 +416,7 @@ The output variables available on VEDA include evapotranspiration (ET), gross pr ## Explore the Data -The global reanalysis is a large dataset with nearly two decades of daily output. Here we show a comparison of two dates for a single variable. We encourage users to [Explore the data](https://www.earthdata.nasa.gov/dashboard/exploration?search=global-reanalysis-da) to look at different dates and to compare variables. +The global reanalysis is a large dataset with nearly two decades of daily output. Here we show a comparison of two dates for a single variable. We encourage users to Explore the Data to look at different dates and to compare variables. An example of how trends calculated from the global reanalysis model output can be used to understand changes in TWS, GPP, and ET, can be seen in the corresponding data story. From 717d4ff14c2ae19c5e431445882d2b098ba10b0a Mon Sep 17 00:00:00 2001 From: Andrew Blackford <62357205+acblackford@users.noreply.github.com> Date: Mon, 19 Aug 2024 09:23:35 -0500 Subject: [PATCH 003/152] initial black belt climate/EJ story push --- stories/black-belt-climate-ej.stories.mdx | 81 ++++++++++++++++++++++ stories/black-belt-cover.png | Bin 0 -> 746904 bytes 2 files changed, 81 insertions(+) create mode 100644 stories/black-belt-climate-ej.stories.mdx create mode 100644 stories/black-belt-cover.png diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx new file mode 100644 index 000000000..bc7de679d --- /dev/null +++ b/stories/black-belt-climate-ej.stories.mdx @@ -0,0 +1,81 @@ +--- +id: black-belt-climate +name: Climate Extremes Aggrevate Social Vulnerabilities in Alabama's Black Belt +description: "Fill In" +media: + src: ::file ./black-belt-cover.jpg + alt: Black Belt Prairie via NLCD data. + author: + name: NASA + url: https://earthobservatory.nasa.gov/images/92321/black-belt-prairie +pubDate: 2024-08-19 +taxonomy: + - name: Topics + values: + - Environmental Justice + - Disasters +--- + + + + + Authors: Maheshwari Neelam [1], Udaysankar Nair [2] + [1] USRA and National Aeronautics and Space Administration (NASA) + [2] The University of Alabama in Huntsville + + ## The Black Belt Region + + 🚧 This Discovery presents work in progress and not peer-reviewed results! 🚧 + + x + + + + + + ## Climate Extremes + + x + + + + + + ## Employment Patterns in the Black Belt + + x + + + + + + ## Demographic Shifts + + x + + + + + + + ## Heat-Related Risks + + x + + + + + + ### Data Access : UPDATE + + * [National Weather Service Damage Assessment Toolkit](https://apps.dat.noaa.gov/stormdamage/damageviewer/) + * [National Weather Service Text Product Archive](https://mesonet.agron.iastate.edu/wx/afos/#) + * [Storm Prediction Center Event Archive](https://www.spc.noaa.gov/exper/archive/) + * [PlanetScope](https://www.planet.com/explorer/) + + ### Additional Resources : UPDATE + + * [FILL OUT](https://www.earthdata.nasa.gov/learn/pathfinders/air-quality-data-pathfinder) + + + \ No newline at end of file diff --git a/stories/black-belt-cover.png b/stories/black-belt-cover.png new file mode 100644 index 0000000000000000000000000000000000000000..7fa53b295861c3288e5df273d5259cbb004618d9 GIT binary patch literal 746904 zcmbTdWmFtN*Dg9}@F2l`aDuzLXK)QJgKJ=L5AF~=xI4k!-QC?acyPPC-}%0C?~k+2 zk2`D4n(pc?RlBRYYwzcoFeL?PR3ri<004k0Dr-x6tzqDR%oZ#e`oUQ^rAPNeQN-IqXEz$}wRQFe5fbQx6WS5HonP9srq5Qr# zut`JvwZj2iqP1c_ix>j@QpFg?0AxJS0C5tmaTqcXOg76*=T?b&vYj@|_-=YB3{RI&?F{Jz#or8U>cjAq;2&1ppv;obG<(5sp1P*xNoZ zJG8m@*Pr`leQ6IABEQ;vYm0=21)wWTUaT1G?=QeO3_?{ocUqU|09G^r7MqWH?5l{` z+DKC#j}h)XFCrwFIZ8tU#6(EQ$Y)f>IqfXF5kl|m+xA-#K6f8i-&Q>?0Y83=q*iq0 z1-$++vU90ai9Q^K6=Su#KcsjY4Dx-Arkmd3sMck`4!_b0Yf=Kr54tz2#7U43C+=V# z`?6h;CcPrYyP^WhgB80J8a~yJ+I0DxLqSKNY0bC*M0{=-BMFe>0O;l%Z0`2}Kz!$8 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Subject: [PATCH 004/152] added cover photo --- stories/black-belt-climate-ej.stories.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index bc7de679d..e306e2613 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -3,7 +3,7 @@ id: black-belt-climate name: Climate Extremes Aggrevate Social Vulnerabilities in Alabama's Black Belt description: "Fill In" media: - src: ::file ./black-belt-cover.jpg + src: ::file ./black-belt-cover.png alt: Black Belt Prairie via NLCD data. author: name: NASA From af771287971f24aa27e48937ea96c5f68718b583 Mon Sep 17 00:00:00 2001 From: Andrew Blackford <62357205+acblackford@users.noreply.github.com> Date: Mon, 19 Aug 2024 09:29:03 -0500 Subject: [PATCH 005/152] added authors --- stories/black-belt-climate-ej.stories.mdx | 2 ++ 1 file changed, 2 insertions(+) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index e306e2613..5abd1f0bd 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -20,7 +20,9 @@ taxonomy: Authors: Maheshwari Neelam [1], Udaysankar Nair [2] + [1] USRA and National Aeronautics and Space Administration (NASA) + [2] The University of Alabama in Huntsville ## The Black Belt Region From 339772c07945ab8bc7f9b48c7b4c6dcd3c57277f Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 09:34:43 -0500 Subject: [PATCH 006/152] content1 --- stories/black-belt-climate-ej.stories.mdx | 11 ++++++----- 1 file changed, 6 insertions(+), 5 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 5abd1f0bd..8d800fdeb 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -8,7 +8,7 @@ media: author: name: NASA url: https://earthobservatory.nasa.gov/images/92321/black-belt-prairie -pubDate: 2024-08-19 +pubDate: 2024-09-01 taxonomy: - name: Topics values: @@ -25,11 +25,12 @@ taxonomy: [2] The University of Alabama in Huntsville - ## The Black Belt Region + **Mission**: [NASA Earth Action](https://science.nasa.gov/earth/in-action/): A thriving world, driven by trusted, actionable Earth science + + **Disclaimer**: This study demonstrates innovative and practical applications of NASA Earth science data to highlight existing environmental inequities. Please note that the results have not undergone peer review. + + The Black Belt is a region in the Southern United States. The term "Black Belt" originally referred to the region's fertile black soil, ideal for agriculture, particularly cotton plantations. 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HcmV?d00001 diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 8d800fdeb..f6be51fa5 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -36,10 +36,16 @@ taxonomy: - ## Climate Extremes - - x + During the 19th century, the Black Belt became synonymous with large-scale cotton production, heavily reliant on enslaved African American labor. After the Civil War, many freed African Americans continued to work in agriculture as sharecroppers or tenant farmers. +

+ + + Black cotton farming family. + +

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From 5c47220211184ebb26d23c41c6a149845c86d175 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 10:52:24 -0500 Subject: [PATCH 008/152] CA --- stories/black-belt-climate-ej.stories.mdx | 27 +++++++++++++++++++++- stories/blackbelt_tmo_2015-2018_lrg.jpg | Bin 0 -> 1706887 bytes stories/soilmap_Alabama.png | Bin 0 -> 763080 bytes 3 files changed, 26 insertions(+), 1 deletion(-) create mode 100644 stories/blackbelt_tmo_2015-2018_lrg.jpg create mode 100644 stories/soilmap_Alabama.png diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index f6be51fa5..5fdd690c0 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -28,10 +28,35 @@ taxonomy: **Mission**: [NASA Earth Action](https://science.nasa.gov/earth/in-action/): A thriving world, driven by trusted, actionable Earth science **Disclaimer**: This study demonstrates innovative and practical applications of NASA Earth science data to highlight existing environmental inequities. Please note that the results have not undergone peer review. + + - The Black Belt is a region in the Southern United States. The term "Black Belt" originally referred to the region's fertile black soil, ideal for agriculture, particularly cotton plantations. This soil resulted from the weathering of limestone bases in the Selma Chalk region. + + + The Black Belt is a region in the Southern United States. The term "Black Belt" originally referred to the region's fertile black soil, ideal for agriculture, particularly cotton plantations. The fertile soil of the Black Belt is intricately connected to the weathering of limestone bases in the Selma Chalk region, which dates back to the Cretaceous Period when the Gulf of Mexico's shoreline was much further inland. Over millions of years, plankton deposited exoskeletons rich in calcium carbonate, leading to the formation of soft limestone known as Selma Chalk. This geological process resulted in a chalky subsoil that, due to its high calcium content, provides exceptional fertility, making the Black Belt particularly suitable for agriculture. + +
+ + + General Soil Map of Alabama, highlights the distinct soils found in the prairie regions, particularly focusing on the Black Belt area. + +
+
+ + + The Black Belt's crescent shape is captured in a natural-color image by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite. This image is a composition of segments from several images taken between 2015 and 2018, allowing for the removal of clouds and haze. +
+ + + The crescent-shaped area of fertile, cultivated land stretches through parts of Mississippi and Alabama. + +
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Date: Tue, 20 Aug 2024 11:23:18 -0500 Subject: [PATCH 010/152] text_align --- stories/black-belt-climate-ej.stories.mdx | 13 +++++++------ 1 file changed, 7 insertions(+), 6 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 8a689fa83..6e70d2422 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -59,16 +59,17 @@ taxonomy:
- - + + During the 19th century, the Black Belt became synonymous with large-scale cotton production, heavily reliant on enslaved African American labor. After the Civil War, many freed African Americans continued to work in agriculture as sharecroppers or tenant farmers. -
- + - - Black cotton farming family. + + Black cotton farming family.
From 09a6228999b69ecdc127d26bd3da67cecfc2e2c4 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 11:26:49 -0500 Subject: [PATCH 011/152] correct_align --- stories/black-belt-climate-ej.stories.mdx | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 6e70d2422..e10d2d620 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -59,14 +59,14 @@ taxonomy:
- - + + During the 19th century, the Black Belt became synonymous with large-scale cotton production, heavily reliant on enslaved African American labor. After the Civil War, many freed African Americans continued to work in agriculture as sharecroppers or tenant farmers. -
+
Black cotton farming family. From 0c2871366c281579592364f36ef01a2e497a1c7e Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 11:33:37 -0500 Subject: [PATCH 012/152] align_v1 --- stories/black-belt-climate-ej.stories.mdx | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index e10d2d620..cd3f026dc 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -61,12 +61,14 @@ taxonomy: - During the 19th century, the Black Belt became synonymous with large-scale cotton production, heavily reliant on enslaved African American labor. After the Civil War, many freed African Americans continued to work in agriculture as sharecroppers or tenant farmers. +

+ During the 19th century, the Black Belt became synonymous with large-scale cotton production, heavily reliant on enslaved African American labor. After the Civil War, many freed African Americans continued to work in agriculture as sharecroppers or tenant farmers. +

-
+
Black cotton farming family. From 29184c3bb806b792803ffc756cdedb0b8c9ab737 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 11:53:50 -0500 Subject: [PATCH 013/152] changes --- stories/black-belt-climate-ej.stories.mdx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index cd3f026dc..938bb1554 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -60,7 +60,7 @@ taxonomy: - +

During the 19th century, the Black Belt became synonymous with large-scale cotton production, heavily reliant on enslaved African American labor. After the Civil War, many freed African Americans continued to work in agriculture as sharecroppers or tenant farmers.

@@ -68,7 +68,7 @@ taxonomy:
Black cotton farming family. From cde158fb7993d9120bc0555b500bd8f68f3822ea Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 12:31:05 -0500 Subject: [PATCH 014/152] changes --- stories/black-belt-climate-ej.stories.mdx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 938bb1554..8a9b53a6c 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -60,7 +60,7 @@ taxonomy: - +

During the 19th century, the Black Belt became synonymous with large-scale cotton production, heavily reliant on enslaved African American labor. After the Civil War, many freed African Americans continued to work in agriculture as sharecroppers or tenant farmers.

@@ -68,7 +68,7 @@ taxonomy:
Black cotton farming family. From f14096626bc56ea7fac5ab65cbfb9ec291707660 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 14:40:34 -0500 Subject: [PATCH 015/152] changes to justify --- stories/black-belt-climate-ej.stories.mdx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 8a9b53a6c..6537cb4cd 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -60,7 +60,7 @@ taxonomy: - +

During the 19th century, the Black Belt became synonymous with large-scale cotton production, heavily reliant on enslaved African American labor. After the Civil War, many freed African Americans continued to work in agriculture as sharecroppers or tenant farmers.

@@ -68,7 +68,7 @@ taxonomy:
Black cotton farming family. From 6736a5978dc476005547dea2414faa570e56c1a0 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 14:47:49 -0500 Subject: [PATCH 016/152] changes --- stories/black-belt-climate-ej.stories.mdx | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 6537cb4cd..89cf4f031 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -35,9 +35,10 @@ taxonomy: The Black Belt is a region in the Southern United States OF America. The term "Black Belt" originally referred to the region's fertile black soil, ideal for agriculture, particularly cotton plantations. The fertile soil of the Black Belt is intricately connected to the weathering of limestone bases in the Selma Chalk region, which dates back to the Cretaceous Period when the Gulf of Mexico's shoreline was much further inland. Over millions of years, plankton deposited exoskeletons rich in calcium carbonate, leading to the formation of soft limestone known as Selma Chalk. This geological process resulted in a chalky subsoil that, due to its high calcium content, provides exceptional fertility, making the Black Belt particularly suitable for agriculture. -
+
General Soil Map of Alabama, highlights the distinct soils found in the prairie regions, particularly focusing on the Black Belt area. @@ -49,9 +50,10 @@ taxonomy: The Black Belt's crescent shape is captured in a natural-color image by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite. This image is a composition of segments from several images taken between 2015 and 2018, allowing for the removal of clouds and haze. -
+
The crescent-shaped area of fertile, cultivated land stretches through parts of Mississippi and Alabama. @@ -60,7 +62,7 @@ taxonomy: - +

During the 19th century, the Black Belt became synonymous with large-scale cotton production, heavily reliant on enslaved African American labor. After the Civil War, many freed African Americans continued to work in agriculture as sharecroppers or tenant farmers.

From af7650bcab9485861892e9e519cdc72fabac345f Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 14:54:55 -0500 Subject: [PATCH 017/152] edits to cc --- stories/black-belt-climate-ej.stories.mdx | 10 +++++----- stories/black_belt_cover.jpg | Bin 0 -> 80586 bytes 2 files changed, 5 insertions(+), 5 deletions(-) create mode 100644 stories/black_belt_cover.jpg diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 89cf4f031..2502ba52c 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -3,8 +3,8 @@ id: black-belt-climate name: Climate Extremes Aggrevate Social Vulnerabilities in Alabama's Black Belt description: "Fill In" media: - src: ::file ./black-belt-cover.png - alt: Black Belt Prairie via NLCD data. + src: ::file ./black_belt_cover.jpg + alt: Farmer in the fields. author: name: NASA url: https://earthobservatory.nasa.gov/images/92321/black-belt-prairie @@ -61,13 +61,13 @@ taxonomy:
- - + +

During the 19th century, the Black Belt became synonymous with large-scale cotton production, heavily reliant on enslaved African American labor. After the Civil War, many freed African Americans continued to work in agriculture as sharecroppers or tenant farmers.

-
+
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zwpaS^s2OOpNNpKG3hl_0i|1DC_IXnp zT4J0 Date: Tue, 20 Aug 2024 15:05:30 -0500 Subject: [PATCH 018/152] changes --- stories/black-belt-climate-ej.stories.mdx | 28 +++++++++++++---------- 1 file changed, 16 insertions(+), 12 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 2502ba52c..6f44f1b30 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -1,13 +1,13 @@ --- id: black-belt-climate name: Climate Extremes Aggrevate Social Vulnerabilities in Alabama's Black Belt -description: "Fill In" +description: "Rising temperatures worsen social vulnerabilities for older adults by increasing their heat-related health risks." media: src: ::file ./black_belt_cover.jpg alt: Farmer in the fields. author: name: NASA - url: https://earthobservatory.nasa.gov/images/92321/black-belt-prairie + url: https://widerimage.reuters.com/photographer/lucy-nicholson.html pubDate: 2024-09-01 taxonomy: - name: Topics @@ -31,12 +31,14 @@ taxonomy: - - + + +

The Black Belt is a region in the Southern United States OF America. The term "Black Belt" originally referred to the region's fertile black soil, ideal for agriculture, particularly cotton plantations. The fertile soil of the Black Belt is intricately connected to the weathering of limestone bases in the Selma Chalk region, which dates back to the Cretaceous Period when the Gulf of Mexico's shoreline was much further inland. Over millions of years, plankton deposited exoskeletons rich in calcium carbonate, leading to the formation of soft limestone known as Selma Chalk. This geological process resulted in a chalky subsoil that, due to its high calcium content, provides exceptional fertility, making the Black Belt particularly suitable for agriculture. +

-
- + @@ -46,17 +48,19 @@ taxonomy:
- - + + +

The Black Belt's crescent shape is captured in a natural-color image by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite. This image is a composition of segments from several images taken between 2015 and 2018, allowing for the removal of clouds and haze. +

-
- + - - The crescent-shaped area of fertile, cultivated land stretches through parts of Mississippi and Alabama. + + Black Belt Prairie from MODIS.
From 54e4e03c94f58d7498d3662b363eea6c900e68c8 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 15:15:00 -0500 Subject: [PATCH 019/152] changes to fig --- stories/black-belt-climate-ej.stories.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 6f44f1b30..2c314afc1 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -57,7 +57,7 @@ taxonomy:
Black Belt Prairie from MODIS. 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z>A$}3SQ|7@DV2+JIsMG^^IyFPb3B|p3YhtN)KHZb!{jn1)c+-7{?KwMoX1P83@0lN==>@ zJ74lTjIrYsxz^HE+bt~PhHIqC31cbzPJNDR6MS)X`&~qe>tUhU;DIx1JdqY2+2|2Y z*&agcc+AH&tapwvdO|0fa6OX;x3+HY^wRd!>2A;;H6J91N@&8lD&gcXGkui4M(C^T z{OOR2(YiiD^h@21Y~|T+jm(VfBQfFtD`J~7Hl_n8j)VaL888sQ0r_R|yWwX&-V4&v zlxYq6FGV?iWPTq4p8kUS-vW?90t2H}RsS@F{9hgI%3Fv2N||al<^OO5NBiq`jW(Ff Fe*tdoe&+xH literal 0 HcmV?d00001 diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 2c314afc1..73e2adfed 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -34,7 +34,7 @@ taxonomy:

- The Black Belt is a region in the Southern United States OF America. The term "Black Belt" originally referred to the region's fertile black soil, ideal for agriculture, particularly cotton plantations. The fertile soil of the Black Belt is intricately connected to the weathering of limestone bases in the Selma Chalk region, which dates back to the Cretaceous Period when the Gulf of Mexico's shoreline was much further inland. Over millions of years, plankton deposited exoskeletons rich in calcium carbonate, leading to the formation of soft limestone known as Selma Chalk. This geological process resulted in a chalky subsoil that, due to its high calcium content, provides exceptional fertility, making the Black Belt particularly suitable for agriculture. + The Black Belt is a region in the Southern United States OF America. The term "Black Belt" originally referred to the region's fertile black soil, ideal for agriculture, particularly cotton plantations. The fertile soil of the Black Belt is intricately connected to the weathering of limestone bases in the Selma Chalk region, which dates back to the Cretaceous Period when the Gulf of Mexico's shoreline was much further inland. Over millions of years, plankton deposited exoskeletons rich in calcium carbonate, leading to the formation of soft limestone known as Selma Chalk. This geological process resulted in a chalky subsoil that, due to its high calcium content, provides exceptional fertility, making the Black Belt particularly suitable for agriculture.

@@ -48,16 +48,13 @@ taxonomy:
- - -

+ + The Black Belt's crescent shape is captured in a natural-color image by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite. This image is a composition of segments from several images taken between 2015 and 2018, allowing for the removal of clouds and haze. -

-
- + Black Belt Prairie from MODIS. @@ -68,7 +65,7 @@ taxonomy:

- During the 19th century, the Black Belt became synonymous with large-scale cotton production, heavily reliant on enslaved African American labor. After the Civil War, many freed African Americans continued to work in agriculture as sharecroppers or tenant farmers. + Historically, the Alabama Black Belt was a cornerstone of the cotton economy, heavily reliant on enslaved African American labor. After the Civil War, many African Americans remained in the area, working as sharecroppers and tenant farmers. The region became a significant cultural and political area, particularly noted for its role in the civil rights movement. Despite its agricultural legacy, the Black Belt has faced economic and social challenges, including poverty and limited access to education and healthcare, which continue to impact its predominantly African American population.

@@ -79,17 +76,36 @@ taxonomy: Black cotton farming family. -
+
- - - ## Employment Patterns in the Black Belt - - x + +
+ + + Left Image Caption. + +
+ +

+ Anthropogenic climate change is causing extreme events, such as heatwaves, to become more frequent and severe. This trend is particularly alarming for the Black Belt, where many residents, especially the older population, depend on outdoor agricultural work. The MERRA-2 climate extreme indices dataset offers valuable insights into the rising extreme day and night temperatures affecting this region. As an advanced climate modeling system, MERRA-2 integrates extensive observational data to analyze climate patterns since 1980. It reveals a concerning increase in temperatures, which heightens the vulnerabilities of those working outdoors in the Black Belt. +

+
+ + + Right Image Caption. + +
+ ## Demographic Shifts From 617dffb7ea9cef9136354169de1f3c2a2295b075 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 15:50:29 -0500 Subject: [PATCH 021/152] changes --- stories/black-belt-climate-ej.stories.mdx | 26 ++++++++--------------- 1 file changed, 9 insertions(+), 17 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 73e2adfed..e0e23d1f5 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -80,29 +80,21 @@ taxonomy: -
+ Left Image Caption - - Left Image Caption. - -
- -

+

Anthropogenic climate change is causing extreme events, such as heatwaves, to become more frequent and severe. This trend is particularly alarming for the Black Belt, where many residents, especially the older population, depend on outdoor agricultural work. The MERRA-2 climate extreme indices dataset offers valuable insights into the rising extreme day and night temperatures affecting this region. As an advanced climate modeling system, MERRA-2 integrates extensive observational data to analyze climate patterns since 1980. It reveals a concerning increase in temperatures, which heightens the vulnerabilities of those working outdoors in the Black Belt.

-
-
Right Image Caption - - Right Image Caption. - -
+
From d06c5306ab47cc11cee2b6b17bacaf1edc9a0568 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 15:55:56 -0500 Subject: [PATCH 022/152] changes --- stories/black-belt-climate-ej.stories.mdx | 26 +++++++++++++++-------- 1 file changed, 17 insertions(+), 9 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index e0e23d1f5..4393c1019 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -80,21 +80,29 @@ taxonomy: - +
Left Image Caption -

+

Left Image Caption
+
+ + +

Anthropogenic climate change is causing extreme events, such as heatwaves, to become more frequent and severe. This trend is particularly alarming for the Black Belt, where many residents, especially the older population, depend on outdoor agricultural work. The MERRA-2 climate extreme indices dataset offers valuable insights into the rising extreme day and night temperatures affecting this region. As an advanced climate modeling system, MERRA-2 integrates extensive observational data to analyze climate patterns since 1980. It reveals a concerning increase in temperatures, which heightens the vulnerabilities of those working outdoors in the Black Belt.

+
+ +
Right Image Caption - +
Right Image Caption
+
From ee719aa2b4e4ee486597a1e4341868a853646461 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 16:00:17 -0500 Subject: [PATCH 023/152] changes --- stories/black-belt-climate-ej.stories.mdx | 22 +++++++--------------- 1 file changed, 7 insertions(+), 15 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 4393c1019..87bd3f63d 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -80,29 +80,21 @@ taxonomy: -
+ Left Image -
Left Image Caption
-
- - -

+

Anthropogenic climate change is causing extreme events, such as heatwaves, to become more frequent and severe. This trend is particularly alarming for the Black Belt, where many residents, especially the older population, depend on outdoor agricultural work. The MERRA-2 climate extreme indices dataset offers valuable insights into the rising extreme day and night temperatures affecting this region. As an advanced climate modeling system, MERRA-2 integrates extensive observational data to analyze climate patterns since 1980. It reveals a concerning increase in temperatures, which heightens the vulnerabilities of those working outdoors in the Black Belt.

-
- -
Right Image -
Right Image Caption
-
+
From c5710c85b1b2f2e8608e82af98d18d558dae27b3 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 16:02:17 -0500 Subject: [PATCH 024/152] modified justify --- stories/black-belt-climate-ej.stories.mdx | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 87bd3f63d..f9a629ece 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -83,15 +83,15 @@ taxonomy: Left Image Caption -

+

Anthropogenic climate change is causing extreme events, such as heatwaves, to become more frequent and severe. This trend is particularly alarming for the Black Belt, where many residents, especially the older population, depend on outdoor agricultural work. The MERRA-2 climate extreme indices dataset offers valuable insights into the rising extreme day and night temperatures affecting this region. As an advanced climate modeling system, MERRA-2 integrates extensive observational data to analyze climate patterns since 1980. It reveals a concerning increase in temperatures, which heightens the vulnerabilities of those working outdoors in the Black Belt.

Right Image Caption
From 004b17e2efaa923c57e8c40b266514d803957356 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 16:04:36 -0500 Subject: [PATCH 025/152] added figures --- stories/black-belt-climate-ej.stories.mdx | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index f9a629ece..fc97282e4 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -82,16 +82,16 @@ taxonomy: Left Image Caption

Anthropogenic climate change is causing extreme events, such as heatwaves, to become more frequent and severe. This trend is particularly alarming for the Black Belt, where many residents, especially the older population, depend on outdoor agricultural work. The MERRA-2 climate extreme indices dataset offers valuable insights into the rising extreme day and night temperatures affecting this region. As an advanced climate modeling system, MERRA-2 integrates extensive observational data to analyze climate patterns since 1980. It reveals a concerning increase in temperatures, which heightens the vulnerabilities of those working outdoors in the Black Belt.

Right Image Caption
From d3f2ae9d4107a4c9ca9774596f0586ecedfdee20 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 16:11:51 -0500 Subject: [PATCH 026/152] more images --- stories/black-belt-climate-ej.stories.mdx | 32 +++++++++++++++++++++-- 1 file changed, 30 insertions(+), 2 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index fc97282e4..ed47b09ac 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -83,7 +83,7 @@ taxonomy: Left Image Caption

@@ -91,12 +91,40 @@ taxonomy:

Right Image Caption
+ +
+ Left Image +
Increasing Warm Days
+
+ + +

+ Anthropogenic climate change is causing extreme events, such as heatwaves, to become more frequent and severe. This trend is particularly alarming for the Black Belt, where many residents, especially the older population, depend on outdoor agricultural work. The MERRA-2 climate extreme indices dataset offers valuable insights into the rising extreme day and night temperatures affecting this region. As an advanced climate modeling system, MERRA-2 integrates extensive observational data to analyze climate patterns since 1980. It reveals a concerning increase in temperatures, which heightens the vulnerabilities of those working outdoors in the Black Belt. +

+
+ +
+ Right Image +
Increasing Warm Nights
+
+
+ + + From 09329f7582cee8115a7d28d7e0956b57797cdbea Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 16:14:18 -0500 Subject: [PATCH 027/152] added captions --- stories/black-belt-climate-ej.stories.mdx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index ed47b09ac..e689a0c66 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -100,7 +100,7 @@ taxonomy:
Left Image @@ -115,7 +115,7 @@ taxonomy:
Right Image From e0a67496678fef461bf978f216bf99ff1e5c03d3 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 16:16:25 -0500 Subject: [PATCH 028/152] correct images --- stories/black-belt-climate-ej.stories.mdx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index e689a0c66..a69957a64 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -100,7 +100,7 @@ taxonomy:
Left Image @@ -115,7 +115,7 @@ taxonomy:
Right Image From 1da628a9ac451aea646a8f007de6f270b9130093 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 16:21:25 -0500 Subject: [PATCH 029/152] changes to text --- stories/black-belt-climate-ej.stories.mdx | 38 +++++++++++------------ 1 file changed, 18 insertions(+), 20 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index a69957a64..b8d372ffd 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -98,29 +98,27 @@ taxonomy: -
- Left Image -
Increasing Warm Days
-
- - -

+ +

+ Left Image + Left Image Caption +
+

Anthropogenic climate change is causing extreme events, such as heatwaves, to become more frequent and severe. This trend is particularly alarming for the Black Belt, where many residents, especially the older population, depend on outdoor agricultural work. The MERRA-2 climate extreme indices dataset offers valuable insights into the rising extreme day and night temperatures affecting this region. As an advanced climate modeling system, MERRA-2 integrates extensive observational data to analyze climate patterns since 1980. It reveals a concerning increase in temperatures, which heightens the vulnerabilities of those working outdoors in the Black Belt.

+
+ Right Image + Here is the cold nights +
- -
- Right Image -
Increasing Warm Nights
-
From 6df2c8fbdcd92eba45787b2bc2ec60ff68dc173d Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 16:34:41 -0500 Subject: [PATCH 030/152] content added --- stories/black-belt-climate-ej.stories.mdx | 20 ++++++++++++++------ 1 file changed, 14 insertions(+), 6 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index b8d372ffd..ba1ae60ce 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -79,6 +79,14 @@ taxonomy:
+ + +

+ Anthropogenic climate change is causing extreme events, such as heatwaves, to become more frequent and severe. This trend is particularly alarming for the Black Belt, where many residents, especially the older population, depend on outdoor agricultural work. The MERRA-2 climate extreme indices dataset offers valuable insights into the rising extreme day and night temperatures affecting this region. As an advanced climate modeling system, MERRA-2 integrates extensive observational data to analyze climate patterns since 1980. It reveals a concerning increase in temperatures, which heightens the vulnerabilities of those working outdoors in the Black Belt. +

+
+
+ Left Image Caption

- Anthropogenic climate change is causing extreme events, such as heatwaves, to become more frequent and severe. This trend is particularly alarming for the Black Belt, where many residents, especially the older population, depend on outdoor agricultural work. The MERRA-2 climate extreme indices dataset offers valuable insights into the rising extreme day and night temperatures affecting this region. As an advanced climate modeling system, MERRA-2 integrates extensive observational data to analyze climate patterns since 1980. It reveals a concerning increase in temperatures, which heightens the vulnerabilities of those working outdoors in the Black Belt. + Anthropogenic climate change is causing extreme events, such as heatwaves, to become more frequent and severe. This trend is particularly alarming for the Black Belt, where many residents, especially the older population, depend on outdoor agricultural work.

Left Image - Left Image Caption + Increasing Warm Nights (day/month) -

- Anthropogenic climate change is causing extreme events, such as heatwaves, to become more frequent and severe. This trend is particularly alarming for the Black Belt, where many residents, especially the older population, depend on outdoor agricultural work. The MERRA-2 climate extreme indices dataset offers valuable insights into the rising extreme day and night temperatures affecting this region. As an advanced climate modeling system, MERRA-2 integrates extensive observational data to analyze climate patterns since 1980. It reveals a concerning increase in temperatures, which heightens the vulnerabilities of those working outdoors in the Black Belt. +

+ The MERRA-2 climate extreme indices dataset offers valuable insights into the rising extreme day and night temperatures affecting the Alabama Black Belt region. This dataset includes indices such as Cool Nights (TN10P), which represent the percentage of days when the daily minimum temperature falls below the 10th percentile, and Warm Nights (TN90P), indicating when the daily minimum temperature exceeds the 90th percentile. Similarly, Cool Days (TX10P) and Warm Days (TX90P) track the percentage of days when daily maximum temperatures are below the 10th percentile or above the 90th percentile, respectively. These indices are analyzed for linear trends (p<0.1) in the data from 1980 to 2023, providing a comprehensive view of temperature extremes over time.

Right Image - Here is the cold nights + Increasing Warm Days (day/month)
From f40d6ef4f83e66536266b2a9c9c1d525b91e5755 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 16:39:16 -0500 Subject: [PATCH 031/152] changed --- stories/black-belt-climate-ej.stories.mdx | 42 ++++++++++++++--------- 1 file changed, 25 insertions(+), 17 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index ba1ae60ce..3fbf6f8fb 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -1,7 +1,7 @@ --- id: black-belt-climate name: Climate Extremes Aggrevate Social Vulnerabilities in Alabama's Black Belt -description: "Rising temperatures worsen social vulnerabilities for older adults by increasing their heat-related health risks." +description: "Rising temperatures worsen social vulnerabilities for elder population adults by increasing their heat-related health risks." media: src: ::file ./black_belt_cover.jpg alt: Farmer in the fields. @@ -107,24 +107,24 @@ taxonomy: -
+
Left Image Increasing Warm Nights (day/month)
-

- The MERRA-2 climate extreme indices dataset offers valuable insights into the rising extreme day and night temperatures affecting the Alabama Black Belt region. This dataset includes indices such as Cool Nights (TN10P), which represent the percentage of days when the daily minimum temperature falls below the 10th percentile, and Warm Nights (TN90P), indicating when the daily minimum temperature exceeds the 90th percentile. Similarly, Cool Days (TX10P) and Warm Days (TX90P) track the percentage of days when daily maximum temperatures are below the 10th percentile or above the 90th percentile, respectively. These indices are analyzed for linear trends (p<0.1) in the data from 1980 to 2023, providing a comprehensive view of temperature extremes over time. +

+ The MERRA-2 climate extreme indices dataset offers valuable insights into the rising extreme day and night temperatures affecting the Alabama Black Belt region. This dataset includes indices such as Cool Nights (TN10P), which represent the percentage of days when the daily minimum temperature falls below the 10th percentile, and Warm Nights (TN90P), indicating when the daily minimum temperature exceeds the 90th percentile. Similarly, Cool Days (TX10P) and Warm Days (TX90P) track the percentage of days when daily maximum temperatures are below the 10th percentile or above the 90th percentile, respectively. These indices are analyzed for linear trends (p<0.1) in the data from 1980 to 2023, providing a comprehensive view of temperature extremes over time.

-
+
Right Image - Increasing Warm Days (day/month) + Increasing Warm Days (day/month)
@@ -151,16 +151,24 @@ taxonomy: - ### Data Access : UPDATE + ### Data Access - * [National Weather Service Damage Assessment Toolkit](https://apps.dat.noaa.gov/stormdamage/damageviewer/) - * [National Weather Service Text Product Archive](https://mesonet.agron.iastate.edu/wx/afos/#) - * [Storm Prediction Center Event Archive](https://www.spc.noaa.gov/exper/archive/) - * [PlanetScope](https://www.planet.com/explorer/) + * [NASA Description for EMIT](https://lpdaac.usgs.gov/products/emitl2bch4plmv001/) + * [CDC/ATSDR SVI Data and Documentation Download | Place and Health | ATSDR](https://www.atsdr.cdc.gov/placeandhealth/svi/data_documentation_download.html) + + **Authors**: Maheshwari Neelam and Udaysankar Nair + + **Editor**: Maheshwari Neelam; + **Developers**: Andrew Blackford, Trent Cowan, and Jerika Christman ; + **Acknowledgements**: All individuals dedicated to Environmental Justice ; + **Questions / Feedback (email address)**: maheshwari.neelam@nasa.gov - ### Additional Resources : UPDATE + #### Additional Resources - * [FILL OUT](https://www.earthdata.nasa.gov/learn/pathfinders/air-quality-data-pathfinder) + 1. https://dtsc.ca.gov/2020/09/23/water-treatment-chemical-company-in-stockton-pays-32k-penalty-for-hazardous-waste-accumulation/ + 2. https://www.keranews.org/news/2022-08-23/dallas-lets-polluters-build-in-black-and-latino-neighborhoods-complaint-alleges + 3. https://www.americanbar.org/groups/crsj/publications/human_rights_magazine_home/vol--44--no-2--housing/environmental-injustice-in-uniontown--alabama--decades-after-the/ + 4. https://sites.uab.edu/humanrights/2018/09/05/the-plastic-problem/ \ No newline at end of file From 41bac3207f030893f23c67fbd425780bcfddc169 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 16:41:43 -0500 Subject: [PATCH 032/152] corrected --- stories/black-belt-climate-ej.stories.mdx | 3 --- 1 file changed, 3 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 3fbf6f8fb..c8606017b 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -152,9 +152,6 @@ taxonomy: ### Data Access - - * [NASA Description for EMIT](https://lpdaac.usgs.gov/products/emitl2bch4plmv001/) - * [CDC/ATSDR SVI Data and Documentation Download | Place and Health | ATSDR](https://www.atsdr.cdc.gov/placeandhealth/svi/data_documentation_download.html) **Authors**: Maheshwari Neelam and Udaysankar Nair From b7cc692c6f3e23677cb667773bae2b4b733bc031 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 16:50:02 -0500 Subject: [PATCH 033/152] changes --- stories/black-belt-climate-ej.stories.mdx | 44 ++--------------------- 1 file changed, 2 insertions(+), 42 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index c8606017b..0a2b61b43 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -80,28 +80,10 @@ taxonomy: - -

- Anthropogenic climate change is causing extreme events, such as heatwaves, to become more frequent and severe. This trend is particularly alarming for the Black Belt, where many residents, especially the older population, depend on outdoor agricultural work. The MERRA-2 climate extreme indices dataset offers valuable insights into the rising extreme day and night temperatures affecting this region. As an advanced climate modeling system, MERRA-2 integrates extensive observational data to analyze climate patterns since 1980. It reveals a concerning increase in temperatures, which heightens the vulnerabilities of those working outdoors in the Black Belt. -

-
-
- - - - Left Image Caption +

- Anthropogenic climate change is causing extreme events, such as heatwaves, to become more frequent and severe. This trend is particularly alarming for the Black Belt, where many residents, especially the older population, depend on outdoor agricultural work. + Anthropogenic climate change is causing extreme events, such as heatwaves, to become more frequent and severe. This trend is particularly alarming for the Black Belt, where many residents, especially the older population, depend on outdoor agricultural work.

- Right Image Caption
@@ -131,7 +113,6 @@ taxonomy: - ## Demographic Shifts @@ -148,24 +129,3 @@ taxonomy: x - - - - ### Data Access - - **Authors**: Maheshwari Neelam and Udaysankar Nair - - **Editor**: Maheshwari Neelam; - **Developers**: Andrew Blackford, Trent Cowan, and Jerika Christman ; - **Acknowledgements**: All individuals dedicated to Environmental Justice ; - **Questions / Feedback (email address)**: maheshwari.neelam@nasa.gov - - #### Additional Resources - - 1. https://dtsc.ca.gov/2020/09/23/water-treatment-chemical-company-in-stockton-pays-32k-penalty-for-hazardous-waste-accumulation/ - 2. https://www.keranews.org/news/2022-08-23/dallas-lets-polluters-build-in-black-and-latino-neighborhoods-complaint-alleges - 3. https://www.americanbar.org/groups/crsj/publications/human_rights_magazine_home/vol--44--no-2--housing/environmental-injustice-in-uniontown--alabama--decades-after-the/ - 4. https://sites.uab.edu/humanrights/2018/09/05/the-plastic-problem/ - - - \ No newline at end of file From bed74b298e14272a19d961b1029361298b86283f Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 16:56:19 -0500 Subject: [PATCH 034/152] comment it out to check --- stories/black-belt-climate-ej.stories.mdx | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 0a2b61b43..facd653e6 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -62,6 +62,7 @@ taxonomy:
+/*

@@ -110,7 +111,7 @@ taxonomy: - +*/ From 91d361901b69a3b6eaa2b11153d33116f50b9561 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 16:58:35 -0500 Subject: [PATCH 035/152] v1 --- stories/black-belt-climate-ej.stories.mdx | 100 ---------------------- 1 file changed, 100 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index facd653e6..906958a00 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -30,103 +30,3 @@ taxonomy: **Disclaimer**: This study demonstrates innovative and practical applications of NASA Earth science data to highlight existing environmental inequities. Please note that the results have not undergone peer review. - - - -

- The Black Belt is a region in the Southern United States OF America. The term "Black Belt" originally referred to the region's fertile black soil, ideal for agriculture, particularly cotton plantations. The fertile soil of the Black Belt is intricately connected to the weathering of limestone bases in the Selma Chalk region, which dates back to the Cretaceous Period when the Gulf of Mexico's shoreline was much further inland. Over millions of years, plankton deposited exoskeletons rich in calcium carbonate, leading to the formation of soft limestone known as Selma Chalk. This geological process resulted in a chalky subsoil that, due to its high calcium content, provides exceptional fertility, making the Black Belt particularly suitable for agriculture. -

-
-
- - - General Soil Map of Alabama, highlights the distinct soils found in the prairie regions, particularly focusing on the Black Belt area. - -
-
- - - - The Black Belt's crescent shape is captured in a natural-color image by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite. This image is a composition of segments from several images taken between 2015 and 2018, allowing for the removal of clouds and haze. - -
- - - Black Belt Prairie from MODIS. - -
-
- -/* - - -

- Historically, the Alabama Black Belt was a cornerstone of the cotton economy, heavily reliant on enslaved African American labor. After the Civil War, many African Americans remained in the area, working as sharecroppers and tenant farmers. The region became a significant cultural and political area, particularly noted for its role in the civil rights movement. Despite its agricultural legacy, the Black Belt has faced economic and social challenges, including poverty and limited access to education and healthcare, which continue to impact its predominantly African American population. -

-
-
- - - Black cotton farming family. - -
-
- - - -

- Anthropogenic climate change is causing extreme events, such as heatwaves, to become more frequent and severe. This trend is particularly alarming for the Black Belt, where many residents, especially the older population, depend on outdoor agricultural work. -

-
-
- - - -
- Increasing Warm Nights - Increasing Warm Nights (day/month) -
-

- The MERRA-2 climate extreme indices dataset offers valuable insights into the rising extreme day and night temperatures affecting the Alabama Black Belt region. This dataset includes indices such as Cool Nights (TN10P), which represent the percentage of days when the daily minimum temperature falls below the 10th percentile, and Warm Nights (TN90P), indicating when the daily minimum temperature exceeds the 90th percentile. Similarly, Cool Days (TX10P) and Warm Days (TX90P) track the percentage of days when daily maximum temperatures are below the 10th percentile or above the 90th percentile, respectively. These indices are analyzed for linear trends (p<0.1) in the data from 1980 to 2023, providing a comprehensive view of temperature extremes over time. -

-
- Increasing Warm Days - Increasing Warm Days (day/month) -
-
-
-*/ - - - - - ## Demographic Shifts - - x - - - - - - - ## Heat-Related Risks - - x - - From c72472540fc6ffd30980ffac45bc4c23782ec02d Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 17:01:34 -0500 Subject: [PATCH 036/152] v2 --- stories/black-belt-climate-ej.stories.mdx | 31 +++++++++++++++++++++++ 1 file changed, 31 insertions(+) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 906958a00..ac32572aa 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -30,3 +30,34 @@ taxonomy: **Disclaimer**: This study demonstrates innovative and practical applications of NASA Earth science data to highlight existing environmental inequities. Please note that the results have not undergone peer review. + + + +

+ The Black Belt is a region in the Southern United States OF America. The term "Black Belt" originally referred to the region's fertile black soil, ideal for agriculture, particularly cotton plantations. The fertile soil of the Black Belt is intricately connected to the weathering of limestone bases in the Selma Chalk region, which dates back to the Cretaceous Period when the Gulf of Mexico's shoreline was much further inland. Over millions of years, plankton deposited exoskeletons rich in calcium carbonate, leading to the formation of soft limestone known as Selma Chalk. This geological process resulted in a chalky subsoil that, due to its high calcium content, provides exceptional fertility, making the Black Belt particularly suitable for agriculture. +

+
+
+ + + General Soil Map of Alabama, highlights the distinct soils found in the prairie regions, particularly focusing on the Black Belt area. + +
+
+ + + + The Black Belt's crescent shape is captured in a natural-color image by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite. This image is a composition of segments from several images taken between 2015 and 2018, allowing for the removal of clouds and haze. + +
+ + + Black Belt Prairie from MODIS. + +
+
From a5100a48b09cc31fcc99bd94c396c7b12080db08 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 17:05:18 -0500 Subject: [PATCH 037/152] v3 --- stories/black-belt-climate-ej.stories.mdx | 21 +++++++++++++++++++-- 1 file changed, 19 insertions(+), 2 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index ac32572aa..aa1f50fb8 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -1,7 +1,7 @@ --- id: black-belt-climate name: Climate Extremes Aggrevate Social Vulnerabilities in Alabama's Black Belt -description: "Rising temperatures worsen social vulnerabilities for elder population adults by increasing their heat-related health risks." +description: "Rising temperatures worsen social vulnerabilities for elder population by increasing their heat-related health risks." media: src: ::file ./black_belt_cover.jpg alt: Farmer in the fields. @@ -40,7 +40,7 @@ taxonomy:
General Soil Map of Alabama, highlights the distinct soils found in the prairie regions, particularly focusing on the Black Belt area. @@ -61,3 +61,20 @@ taxonomy:
+ + + +

+ Historically, the Alabama Black Belt was a cornerstone of the cotton economy, heavily reliant on enslaved African American labor. After the Civil War, many African Americans remained in the area, working as sharecroppers and tenant farmers. The region became a significant cultural and political area, particularly noted for its role in the civil rights movement. Despite its agricultural legacy, the Black Belt has faced economic and social challenges, including poverty and limited access to education and healthcare, which continue to impact its predominantly African American population. +

+
+
+ + + Black cotton farming family. + +
+
From 64a17029bc7a6595a1413fa6462b8552bcdebcd7 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 17:11:00 -0500 Subject: [PATCH 038/152] v4 --- stories/black-belt-climate-ej.stories.mdx | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index aa1f50fb8..4139779d7 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -78,3 +78,11 @@ taxonomy:
+ + + +

+ Anthropogenic climate change is causing extreme events, such as heatwaves, to become more frequent and severe. This trend is particularly alarming for the Black Belt, where many residents, especially the older population, depend on outdoor agricultural work. +

+
+
From e6aa797456dadc00d8760da17291e9fbae613cb0 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 17:15:37 -0500 Subject: [PATCH 039/152] v5 --- stories/black-belt-climate-ej.stories.mdx | 33 ++++++++++++++++++++--- 1 file changed, 30 insertions(+), 3 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 4139779d7..d72858eb5 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -49,10 +49,12 @@ taxonomy: - + +

The Black Belt's crescent shape is captured in a natural-color image by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite. This image is a composition of segments from several images taken between 2015 and 2018, allowing for the removal of clouds and haze. +

-
+
@@ -80,9 +82,34 @@ taxonomy: - +

Anthropogenic climate change is causing extreme events, such as heatwaves, to become more frequent and severe. This trend is particularly alarming for the Black Belt, where many residents, especially the older population, depend on outdoor agricultural work.

+ + + +
+ Increasing Warm Nights + Increasing Warm Nights (day/month) +
+

+ The MERRA-2 climate extreme indices dataset offers valuable insights into the rising extreme day and night temperatures affecting the Alabama Black Belt region. This dataset includes indices such as Cool Nights (TN10P), which represent the percentage of days when the daily minimum temperature falls below the 10th percentile, and Warm Nights (TN90P), indicating when the daily minimum temperature exceeds the 90th percentile. Similarly, Cool Days (TX10P) and Warm Days (TX90P) track the percentage of days when daily maximum temperatures are below the 10th percentile or above the 90th percentile, respectively. These indices are analyzed for linear trends (p<0.1) in the data from 1980 to 2023, providing a comprehensive view of temperature extremes over time. +

+
+ Increasing Warm Days + Increasing Warm Days (day/month) +
+
+
+ From 8cca6253fcc813db70bff1038872992c697119ff Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 17:16:45 -0500 Subject: [PATCH 040/152] v5 --- stories/black-belt-climate-ej.stories.mdx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index d72858eb5..2ea9fcca2 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -97,7 +97,7 @@ taxonomy: style={{ width: '100%', height: 'auto' }} alt="Increasing Warm Nights" /> - Increasing Warm Nights (day/month) + Increasing Warm Nights

The MERRA-2 climate extreme indices dataset offers valuable insights into the rising extreme day and night temperatures affecting the Alabama Black Belt region. This dataset includes indices such as Cool Nights (TN10P), which represent the percentage of days when the daily minimum temperature falls below the 10th percentile, and Warm Nights (TN90P), indicating when the daily minimum temperature exceeds the 90th percentile. Similarly, Cool Days (TX10P) and Warm Days (TX90P) track the percentage of days when daily maximum temperatures are below the 10th percentile or above the 90th percentile, respectively. These indices are analyzed for linear trends (p<0.1) in the data from 1980 to 2023, providing a comprehensive view of temperature extremes over time. @@ -108,7 +108,7 @@ taxonomy: style={{ width: '100%', height: 'auto' }} alt="Increasing Warm Days" /> - Increasing Warm Days (day/month) + Increasing Warm Days From f505c8a4a06500cc2eb69066f43d80a6161e6c0f Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 17:20:27 -0500 Subject: [PATCH 041/152] v6 --- stories/black-belt-climate-ej.stories.mdx | 30 +++++++++-------------- 1 file changed, 12 insertions(+), 18 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 2ea9fcca2..71abc2050 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -91,25 +91,19 @@ taxonomy: -

- Increasing Warm Nights - Increasing Warm Nights -
-

- The MERRA-2 climate extreme indices dataset offers valuable insights into the rising extreme day and night temperatures affecting the Alabama Black Belt region. This dataset includes indices such as Cool Nights (TN10P), which represent the percentage of days when the daily minimum temperature falls below the 10th percentile, and Warm Nights (TN90P), indicating when the daily minimum temperature exceeds the 90th percentile. Similarly, Cool Days (TX10P) and Warm Days (TX90P) track the percentage of days when daily maximum temperatures are below the 10th percentile or above the 90th percentile, respectively. These indices are analyzed for linear trends (p<0.1) in the data from 1980 to 2023, providing a comprehensive view of temperature extremes over time. + Increasing Warm Nights +

+ The MERRA-2 climate extreme indices dataset offers valuable insights into the rising extreme day and night temperatures affecting the Alabama Black Belt region. This dataset includes indices such as Cool Nights (TN10P), which represent the percentage of days when the daily minimum temperature falls below the 10th percentile, and Warm Nights (TN90P), indicating when the daily minimum temperature exceeds the 90th percentile. Similarly, Cool Days (TX10P) and Warm Days (TX90P) track the percentage of days when daily maximum temperatures are below the 10th percentile or above the 90th percentile, respectively. These indices are analyzed for linear trends in the data from 1980 to 2023, providing a comprehensive view of temperature extremes over time.

-
- Increasing Warm Days - Increasing Warm Days -
+ Increasing Warm Days From bd0cf2d794f9b0a98f3949d8ce474dfe9c054c9e Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 20 Aug 2024 17:27:37 -0500 Subject: [PATCH 042/152] v7 --- stories/black-belt-climate-ej.stories.mdx | 26 ++++++++++++++++++++++- 1 file changed, 25 insertions(+), 1 deletion(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 71abc2050..d51b53a5d 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -57,6 +57,7 @@ taxonomy:
Black Belt Prairie from MODIS. @@ -82,7 +83,7 @@ taxonomy: - +

Anthropogenic climate change is causing extreme events, such as heatwaves, to become more frequent and severe. This trend is particularly alarming for the Black Belt, where many residents, especially the older population, depend on outdoor agricultural work.

@@ -107,3 +108,26 @@ taxonomy:
+ + +
+ Increasing Warm Nights + Increasing Warm Nights +
+

+ The MERRA-2 climate extreme indices dataset offers valuable insights into the rising extreme day and night temperatures affecting the Alabama Black Belt region. This dataset includes indices such as Cool Nights (TN10P), which represent the percentage of days when the daily minimum temperature falls below the 10th percentile, and Warm Nights (TN90P), indicating when the daily minimum temperature exceeds the 90th percentile. Similarly, Cool Days (TX10P) and Warm Days (TX90P) track the percentage of days when daily maximum temperatures are below the 10th percentile or above the 90th percentile, respectively. These indices are analyzed for linear trends in the data from 1980 to 2023, providing a comprehensive view of temperature extremes over time. +

+
+ Increasing Warm Days + Increasing Warm Days +
+
+
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z;~20Z-Sp)1o*8!{Y=S$cy88!hNy*?m|El{+^`)~CQd*pa^#>Vd=J=%~^t@0sKU-9) zt;td)*;voB!$_VdxD)kbk?>3>twsv8&>5(jR#UCZa}T+F{`#9bpGOLR5Go-mKb^$ z;f)tPK&|I?gk&OgevxEy&HAbP0l+XkK DO=64w literal 0 HcmV?d00001 diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index d51b53a5d..1897654b8 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -37,7 +37,7 @@ taxonomy: The Black Belt is a region in the Southern United States OF America. The term "Black Belt" originally referred to the region's fertile black soil, ideal for agriculture, particularly cotton plantations. The fertile soil of the Black Belt is intricately connected to the weathering of limestone bases in the Selma Chalk region, which dates back to the Cretaceous Period when the Gulf of Mexico's shoreline was much further inland. Over millions of years, plankton deposited exoskeletons rich in calcium carbonate, leading to the formation of soft limestone known as Selma Chalk. This geological process resulted in a chalky subsoil that, due to its high calcium content, provides exceptional fertility, making the Black Belt particularly suitable for agriculture.

-
+
-
+
Black Belt Prairie from MODIS. @@ -71,7 +71,7 @@ taxonomy: Historically, the Alabama Black Belt was a cornerstone of the cotton economy, heavily reliant on enslaved African American labor. After the Civil War, many African Americans remained in the area, working as sharecroppers and tenant farmers. The region became a significant cultural and political area, particularly noted for its role in the civil rights movement. Despite its agricultural legacy, the Black Belt has faced economic and social challenges, including poverty and limited access to education and healthcare, which continue to impact its predominantly African American population.

-
+
- +

- Anthropogenic climate change is causing extreme events, such as heatwaves, to become more frequent and severe. This trend is particularly alarming for the Black Belt, where many residents, especially the older population, depend on outdoor agricultural work. + Anthropogenic climate change is leading to more frequent and severe extreme events, such as heatwaves. This trend is particularly concerning for the Alabama Black Belt region, where many residents, especially the older population, depend on outdoor agricultural work. The MERRA-2 climate extreme indices dataset provides valuable insights into the increasing extreme temperatures affecting this area. It includes indices like Cool Nights (TN10P), which represent the percentage of days when the daily minimum temperature falls below the 10th percentile, and Warm Nights (TN90P), indicating when the daily minimum temperature exceeds the 90th percentile. Similarly, Cool Days (TX10P) and Warm Days (TX90P) track the percentage of days when daily maximum temperatures are below the 10th percentile or above the 90th percentile, respectively. By analyzing these indices for linear trends from 1980 to 2023, we can better understand the rising temperatures over time in this region. +

+ +
+ + + + Increasing Warm Nights +

+ The increasing occurrences of warm days and warm nights are significantly affecting the counties within Alabama's Black Belt region. The colorbar illustrates the slope of the linear trend.

+ Increasing Warm Days
Increasing Warm Nights

- The MERRA-2 climate extreme indices dataset offers valuable insights into the rising extreme day and night temperatures affecting the Alabama Black Belt region. This dataset includes indices such as Cool Nights (TN10P), which represent the percentage of days when the daily minimum temperature falls below the 10th percentile, and Warm Nights (TN90P), indicating when the daily minimum temperature exceeds the 90th percentile. Similarly, Cool Days (TX10P) and Warm Days (TX90P) track the percentage of days when daily maximum temperatures are below the 10th percentile or above the 90th percentile, respectively. These indices are analyzed for linear trends in the data from 1980 to 2023, providing a comprehensive view of temperature extremes over time. + The decreasing occurrences of cool days and cool nights are also significantly affecting the counties within Alabama's Black Belt region. The colorbar illustrates the slope of the linear trend.

Increasing Warm Days
+ + + Increasing Warm Nights +

+ Compounding these environmental challenges are significant demographic and socio-economic shifts within the Black Belt. The region is socio-economically disadvantaged, with limited access to education, healthcare, and employment opportunities. As a result, many young residents are leaving in search of better prospects, leading to a noticeable increase in the proportion of older adults. This demographic shift presents additional challenges, as older adults are generally more susceptible to the adverse effects of extreme heat, including heat-related illnesses. With fewer younger individuals to support them, the community's resilience to climate change is further weakened. +

+ Increasing Warm Days +
+
+ + + + + + + + + + + + +*/
Increasing Warm Nights Increasing Warm Nights

- The MERRA-2 climate extreme indices dataset offers valuable insights into the rising extreme day and night temperatures affecting the Alabama Black Belt region. This dataset includes indices such as Cool Nights (TN10P), which represent the percentage of days when the daily minimum temperature falls below the 10th percentile, and Warm Nights (TN90P), indicating when the daily minimum temperature exceeds the 90th percentile. Similarly, Cool Days (TX10P) and Warm Days (TX90P) track the percentage of days when daily maximum temperatures are below the 10th percentile or above the 90th percentile, respectively. These indices are analyzed for linear trends in the data from 1980 to 2023, providing a comprehensive view of temperature extremes over time. + The increasing occurrences of warm days (depicted on the right) and warm nights (depicted on the left) are significantly affecting the counties within Alabama's Black Belt region. The colorbar illustrates the slope of the linear trend.

Increasing Warm Days - Increasing Warm Days + Increasing Warm Days
+*/ \ No newline at end of file From 6a1323f6f53ecdf26431e28a17a61424f83b1bcc Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 09:23:08 -0500 Subject: [PATCH 044/152] error_corrected --- stories/black-belt-climate-ej.stories.mdx | 35 ----------------------- 1 file changed, 35 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 1897654b8..f3e0fe26c 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -145,38 +145,3 @@ taxonomy: - - - - - - - - - - -*/ - - -
- Increasing Warm Nights - Increasing Warm Nights -
-

- The increasing occurrences of warm days (depicted on the right) and warm nights (depicted on the left) are significantly affecting the counties within Alabama's Black Belt region. The colorbar illustrates the slope of the linear trend. -

-
- Increasing Warm Days - Increasing Warm Days -
-
-
-*/ \ No newline at end of file From 79df84cef8ecdd4201ce95b7c7155dbe811bd87d Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 09:25:33 -0500 Subject: [PATCH 045/152] v1 --- stories/black-belt-climate-ej.stories.mdx | 56 ----------------------- 1 file changed, 56 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index f3e0fe26c..b8e78862a 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -89,59 +89,3 @@ taxonomy:

- - - - Increasing Warm Nights -

- The increasing occurrences of warm days and warm nights are significantly affecting the counties within Alabama's Black Belt region. The colorbar illustrates the slope of the linear trend. -

- Increasing Warm Days -
-
- - - - Increasing Warm Nights -

- The decreasing occurrences of cool days and cool nights are also significantly affecting the counties within Alabama's Black Belt region. The colorbar illustrates the slope of the linear trend. -

- Increasing Warm Days -
-
- - - - Increasing Warm Nights -

- Compounding these environmental challenges are significant demographic and socio-economic shifts within the Black Belt. The region is socio-economically disadvantaged, with limited access to education, healthcare, and employment opportunities. As a result, many young residents are leaving in search of better prospects, leading to a noticeable increase in the proportion of older adults. This demographic shift presents additional challenges, as older adults are generally more susceptible to the adverse effects of extreme heat, including heat-related illnesses. With fewer younger individuals to support them, the community's resilience to climate change is further weakened. -

- Increasing Warm Days -
-
- - From 2c861ad14bb2e8023f2b52775a2f5f37d87faafb Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 09:28:37 -0500 Subject: [PATCH 046/152] v2 --- stories/black-belt-climate-ej.stories.mdx | 7 ------- 1 file changed, 7 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index b8e78862a..304f91dc5 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -82,10 +82,3 @@ taxonomy:
- - -

- Anthropogenic climate change is leading to more frequent and severe extreme events, such as heatwaves. This trend is particularly concerning for the Alabama Black Belt region, where many residents, especially the older population, depend on outdoor agricultural work. The MERRA-2 climate extreme indices dataset provides valuable insights into the increasing extreme temperatures affecting this area. It includes indices like Cool Nights (TN10P), which represent the percentage of days when the daily minimum temperature falls below the 10th percentile, and Warm Nights (TN90P), indicating when the daily minimum temperature exceeds the 90th percentile. Similarly, Cool Days (TX10P) and Warm Days (TX90P) track the percentage of days when daily maximum temperatures are below the 10th percentile or above the 90th percentile, respectively. By analyzing these indices for linear trends from 1980 to 2023, we can better understand the rising temperatures over time in this region. -

- -
From b2f004ee5e2844f226df00f98fafffe8020197be Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 09:35:29 -0500 Subject: [PATCH 047/152] content_Added --- stories/black-belt-climate-ej.stories.mdx | 49 +++++++++++++++++++++-- 1 file changed, 46 insertions(+), 3 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 304f91dc5..1c3056be6 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -32,15 +32,15 @@ taxonomy: - +

The Black Belt is a region in the Southern United States OF America. The term "Black Belt" originally referred to the region's fertile black soil, ideal for agriculture, particularly cotton plantations. The fertile soil of the Black Belt is intricately connected to the weathering of limestone bases in the Selma Chalk region, which dates back to the Cretaceous Period when the Gulf of Mexico's shoreline was much further inland. Over millions of years, plankton deposited exoskeletons rich in calcium carbonate, leading to the formation of soft limestone known as Selma Chalk. This geological process resulted in a chalky subsoil that, due to its high calcium content, provides exceptional fertility, making the Black Belt particularly suitable for agriculture.

-
+
General Soil Map of Alabama, highlights the distinct soils found in the prairie regions, particularly focusing on the Black Belt area. @@ -82,3 +82,46 @@ taxonomy:
+ + +

+ Anthropogenic climate change is leading to more frequent and severe extreme events, such as heatwaves. This trend is particularly concerning for the Alabama Black Belt region, where many residents, especially the older population, depend on outdoor agricultural work. The MERRA-2 climate extreme indices dataset provides valuable insights into the increasing extreme temperatures affecting this area. It includes indices like Cool Nights (TN10P), which represent the percentage of days when the daily minimum temperature falls below the 10th percentile, and Warm Nights (TN90P), indicating when the daily minimum temperature exceeds the 90th percentile. Similarly, Cool Days (TX10P) and Warm Days (TX90P) track the percentage of days when daily maximum temperatures are below the 10th percentile or above the 90th percentile, respectively. By analyzing these indices for linear trends from 1980 to 2023, we can better understand the rising temperatures over time in this region. +

+
+
+ + + + Increasing Warm Nights +

+ The increasing occurrences of warm days and warm nights are significantly affecting the counties within Alabama's Black Belt region. The colorbar illustrates the slope of the linear trend. +

+ Increasing Warm Days +
+
+ + + + Increasing Warm Nights +

+ The decreasing occurrences of cool days and cool nights are also significantly affecting the counties within Alabama's Black Belt region. The colorbar illustrates the slope of the linear trend. +

+ Increasing Warm Days +
+
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The Black Belt is a region in the Southern United States OF America. The term "Black Belt" originally referred to the region's fertile black soil, ideal for agriculture, particularly cotton plantations. The fertile soil of the Black Belt is intricately connected to the weathering of limestone bases in the Selma Chalk region, which dates back to the Cretaceous Period when the Gulf of Mexico's shoreline was much further inland. Over millions of years, plankton deposited exoskeletons rich in calcium carbonate, leading to the formation of soft limestone known as Selma Chalk. This geological process resulted in a chalky subsoil that, due to its high calcium content, provides exceptional fertility, making the Black Belt particularly suitable for agriculture.

@@ -49,15 +49,15 @@ taxonomy: - +

- The Black Belt's crescent shape is captured in a natural-color image by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite. This image is a composition of segments from several images taken between 2015 and 2018, allowing for the removal of clouds and haze. + The Black Belt's crescent shape is captured in a natural-color image by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite. This image is a composition of segments from several images taken between 2015 and 2018, allowing for the removal of clouds and haze.

-
+
Black Belt Prairie from MODIS. @@ -84,9 +84,7 @@ taxonomy: -

- Anthropogenic climate change is leading to more frequent and severe extreme events, such as heatwaves. This trend is particularly concerning for the Alabama Black Belt region, where many residents, especially the older population, depend on outdoor agricultural work. The MERRA-2 climate extreme indices dataset provides valuable insights into the increasing extreme temperatures affecting this area. It includes indices like Cool Nights (TN10P), which represent the percentage of days when the daily minimum temperature falls below the 10th percentile, and Warm Nights (TN90P), indicating when the daily minimum temperature exceeds the 90th percentile. Similarly, Cool Days (TX10P) and Warm Days (TX90P) track the percentage of days when daily maximum temperatures are below the 10th percentile or above the 90th percentile, respectively. By analyzing these indices for linear trends from 1980 to 2023, we can better understand the rising temperatures over time in this region. -

+ Anthropogenic climate change is leading to more frequent and severe extreme events, such as heatwaves. This trend is particularly concerning for the Alabama Black Belt region, where many residents, especially the older population, depend on outdoor agricultural work. The MERRA-2 climate extreme indices dataset provides valuable insights into the increasing extreme temperatures affecting this area. It includes indices like Cool Nights (TN10P), which represent the percentage of days when the daily minimum temperature falls below the 10th percentile, and Warm Nights (TN90P), indicating when the daily minimum temperature exceeds the 90th percentile. Similarly, Cool Days (TX10P) and Warm Days (TX90P) track the percentage of days when daily maximum temperatures are below the 10th percentile or above the 90th percentile, respectively. By analyzing these indices for linear trends from 1980 to 2023, we can better understand the rising temperatures over time in this region.
@@ -94,7 +92,7 @@ taxonomy: Increasing Warm Nights

@@ -102,7 +100,7 @@ taxonomy:

Increasing Warm Days
@@ -112,7 +110,7 @@ taxonomy: Increasing Warm Nights

@@ -120,8 +118,53 @@ taxonomy:

Increasing Warm Days
+ + + +

+ Agriculture continues to be the backbone of the Black Belt's economy, with many older adults working in the fields. This reliance on an aging workforce is concerning, particularly as the physical demands of farming are intensified by rising temperatures. In Sumter County, the number of farm operators aged 55 and above is increasing, mirroring a broader national trend where the average age of U.S. farm producers has risen to 58.1 years by 2022. This demographic shift poses challenges for the sustainability of the agricultural sector, as younger generations increasingly seek opportunities outside traditional farming roles. +

+
+
+ + + Age Distribution of Farm Operators. + +
+
+ + + +

+ Additionally, outdoor occupations like transportation and construction have remained crucial sources of income and have been increasing over the past few years, as analyzed by data from the U.S. Census Bureau. This data, specifically examining the number of establishments by employment category in counties such as Choctaw and Butler, highlights the economic importance of these sectors. +

+
+
+ + + Black cotton farming family. + +
+
+ + + + The combination of rising temperatures and an older workforce underscores the urgent need for adaptive strategies to protect both the health of the population and the viability of these economic sectors.Addressing these intertwined challenges requires targeted policies and investments in climate resilience measures. By enhancing education, healthcare, and job opportunities, along with adopting sustainable agricultural practices, the Black Belt can work towards a more resilient and prosperous future in the face of climate change. + To mitigate heat-related risks, several safeguards can be implemented: + ### Improved Access to Cooling Centers: Establishing more cooling centers in rural areas can provide relief during extreme heat events. + ### Health Monitoring Programs: Implementing regular health check-ups for older adults working in agriculture can help prevent heat-related illnesses. + ### Education and Training: Providing training on heat safety and recognizing symptoms of heat stress can empower workers to take preventive actions. + ### Flexible Work Schedules: Adjusting work hours to cooler parts of the day can reduce exposure to extreme heat. + + \ No newline at end of file From 4c217bd7653c64dcc6174a1f02b2091723b834f9 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 10:28:28 -0500 Subject: [PATCH 049/152] mod_v1 --- stories/black-belt-climate-ej.stories.mdx | 39 +++++++++++------------ 1 file changed, 18 insertions(+), 21 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index b632d315c..63e4f6194 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -82,9 +82,11 @@ taxonomy:
- - + + +

Anthropogenic climate change is leading to more frequent and severe extreme events, such as heatwaves. This trend is particularly concerning for the Alabama Black Belt region, where many residents, especially the older population, depend on outdoor agricultural work. The MERRA-2 climate extreme indices dataset provides valuable insights into the increasing extreme temperatures affecting this area. It includes indices like Cool Nights (TN10P), which represent the percentage of days when the daily minimum temperature falls below the 10th percentile, and Warm Nights (TN90P), indicating when the daily minimum temperature exceeds the 90th percentile. Similarly, Cool Days (TX10P) and Warm Days (TX90P) track the percentage of days when daily maximum temperatures are below the 10th percentile or above the 90th percentile, respectively. By analyzing these indices for linear trends from 1980 to 2023, we can better understand the rising temperatures over time in this region. +

@@ -92,15 +94,15 @@ taxonomy: Increasing Warm Nights

- The increasing occurrences of warm days and warm nights are significantly affecting the counties within Alabama's Black Belt region. The colorbar illustrates the slope of the linear trend. + The increasing occurrences of warm days and warm nights are significantly impacting the counties within Alabama's Black Belt. The colorbar illustrates the slope of the linear trend.

Increasing Warm Days
@@ -110,15 +112,15 @@ taxonomy: Increasing Warm Nights

- The decreasing occurrences of cool days and cool nights are also significantly affecting the counties within Alabama's Black Belt region. The colorbar illustrates the slope of the linear trend. + Concurrently, the decreasing occurrences of cool days and cool nights are also affecting the region.

Increasing Warm Days
@@ -127,8 +129,7 @@ taxonomy:

- Agriculture continues to be the backbone of the Black Belt's economy, with many older adults working in the fields. This reliance on an aging workforce is concerning, particularly as the physical demands of farming are intensified by rising temperatures. In Sumter County, the number of farm operators aged 55 and above is increasing, mirroring a broader national trend where the average age of U.S. farm producers has risen to 58.1 years by 2022. This demographic shift poses challenges for the sustainability of the agricultural sector, as younger generations increasingly seek opportunities outside traditional farming roles. -

+ Agriculture remains the backbone of the Black Belt's economy, with many older adults working in the fields. This reliance on an aging workforce is concerning, particularly as the physical demands of farming intensify with rising temperatures. In Sumter County, the number of farm operators aged 55 and above is increasing, reflecting a broader national trend where the average age of U.S. farm producers has risen to 58.1 years by 2022.

- Additionally, outdoor occupations like transportation and construction have remained crucial sources of income and have been increasing over the past few years, as analyzed by data from the U.S. Census Bureau. This data, specifically examining the number of establishments by employment category in counties such as Choctaw and Butler, highlights the economic importance of these sectors. -

+ Additionally, outdoor occupations such as transportation and construction have become crucial sources of income and have shown growth over the past few years. Data from the U.S. Census Bureau, which examines the number of establishments by employment category in counties like Choctaw and Butler, underscores the economic importance of these sectors.

- - Black cotton farming family. -
The combination of rising temperatures and an older workforce underscores the urgent need for adaptive strategies to protect both the health of the population and the viability of these economic sectors.Addressing these intertwined challenges requires targeted policies and investments in climate resilience measures. By enhancing education, healthcare, and job opportunities, along with adopting sustainable agricultural practices, the Black Belt can work towards a more resilient and prosperous future in the face of climate change. - To mitigate heat-related risks, several safeguards can be implemented: - ### Improved Access to Cooling Centers: Establishing more cooling centers in rural areas can provide relief during extreme heat events. - ### Health Monitoring Programs: Implementing regular health check-ups for older adults working in agriculture can help prevent heat-related illnesses. - ### Education and Training: Providing training on heat safety and recognizing symptoms of heat stress can empower workers to take preventive actions. - ### Flexible Work Schedules: Adjusting work hours to cooler parts of the day can reduce exposure to extreme heat. + ### To mitigate heat-related risks, several safeguards can be implemented: + - Improved Access to Cooling Centers: Establishing more cooling centers in rural areas can provide relief during extreme heat events. + - Health Monitoring Programs: Implementing regular health check-ups for older adults working in agriculture can help prevent heat-related illnesses. + - Education and Training: Providing training on heat safety and recognizing symptoms of heat stress can empower workers to take preventive actions. + - Flexible Work Schedules: Adjusting work hours to cooler parts of the day can reduce exposure to extreme heat. \ No newline at end of file From 19bcf30dbfa60ebd8c614cc2f94d7e442e00804a Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 10:31:19 -0500 Subject: [PATCH 050/152] mod_v2 --- stories/black-belt-climate-ej.stories.mdx | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 63e4f6194..d29d9bdce 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -129,7 +129,8 @@ taxonomy:

- Agriculture remains the backbone of the Black Belt's economy, with many older adults working in the fields. This reliance on an aging workforce is concerning, particularly as the physical demands of farming intensify with rising temperatures. In Sumter County, the number of farm operators aged 55 and above is increasing, reflecting a broader national trend where the average age of U.S. farm producers has risen to 58.1 years by 2022.

+ Agriculture remains the backbone of the Black Belt's economy, with many older adults working in the fields. This reliance on an aging workforce is concerning, particularly as the physical demands of farming intensify with rising temperatures. In Sumter County, the number of farm operators aged 55 and above is increasing, reflecting a broader national trend where the average age of U.S. farm producers has risen to 58.1 years by 2022. +

- Additionally, outdoor occupations such as transportation and construction have become crucial sources of income and have shown growth over the past few years. Data from the U.S. Census Bureau, which examines the number of establishments by employment category in counties like Choctaw and Butler, underscores the economic importance of these sectors.

+ Additionally, outdoor occupations such as transportation and construction have become crucial sources of income and have shown growth over the past few years. Data from the U.S. Census Bureau, which examines the number of establishments by employment category in counties like Choctaw and Butler, underscores the economic importance of these sectors. +

Date: Wed, 21 Aug 2024 10:40:50 -0500 Subject: [PATCH 051/152] mod_v3 --- stories/black-belt-climate-ej.stories.mdx | 74 ++++++++++++++++++----- 1 file changed, 59 insertions(+), 15 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index d29d9bdce..1047bcbc0 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -94,7 +94,7 @@ taxonomy: Increasing Warm Nights

@@ -102,7 +102,7 @@ taxonomy:

Increasing Warm Days
@@ -112,7 +112,7 @@ taxonomy: Increasing Warm Nights

@@ -120,7 +120,7 @@ taxonomy:

Increasing Warm Days
@@ -135,7 +135,7 @@ taxonomy:
Age Distribution of Farm Operators. @@ -152,18 +152,62 @@ taxonomy:
- - - The combination of rising temperatures and an older workforce underscores the urgent need for adaptive strategies to protect both the health of the population and the viability of these economic sectors.Addressing these intertwined challenges requires targeted policies and investments in climate resilience measures. By enhancing education, healthcare, and job opportunities, along with adopting sustainable agricultural practices, the Black Belt can work towards a more resilient and prosperous future in the face of climate change. - ### To mitigate heat-related risks, several safeguards can be implemented: - - Improved Access to Cooling Centers: Establishing more cooling centers in rural areas can provide relief during extreme heat events. - - Health Monitoring Programs: Implementing regular health check-ups for older adults working in agriculture can help prevent heat-related illnesses. - - Education and Training: Providing training on heat safety and recognizing symptoms of heat stress can empower workers to take preventive actions. - - Flexible Work Schedules: Adjusting work hours to cooler parts of the day can reduce exposure to extreme heat. + + +

+ The combination of rising temperatures and an older workforce underscores the urgent need for adaptive strategies to protect both the health of the population and the viability of these economic sectors.Addressing these intertwined challenges requires targeted policies and investments in climate resilience measures. By enhancing education, healthcare, and job opportunities, along with adopting sustainable agricultural practices, the Black Belt can work towards a more resilient and prosperous future in the face of climate change. + ### To mitigate heat-related risks, several safeguards can be implemented: + - Improved Access to Cooling Centers: Establishing more cooling centers in rural areas can provide relief during extreme heat events. + - Health Monitoring Programs: Implementing regular health check-ups for older adults working in agriculture can help prevent heat-related illnesses. + - Education and Training: Providing training on heat safety and recognizing symptoms of heat stress can empower workers to take preventive actions. + - Flexible Work Schedules: Adjusting work hours to cooler parts of the day can reduce exposure to extreme heat. +

-
\ No newline at end of file +
+ + + +

+ ### References + 1. Christine Todd Whitman. (2001). Environmental Protection Agency, EPA’s Commitment to Environmental Justice, Memorandum. + 2. https://www.washingtonpost.com/climate-environment/2020/11/16/environmental-racism-dallas-shingle-mountain/ + 3. Piper, I. (2023). The Inequitable Placement of Hazardous Waste Facilities: How Underserved Communities are Disproportionately Impacted. + 4. Siddiqua, A., Hahladakis, J. N., & Al-Attiya, W. A. K. (2022). An overview of the environmental pollution and health effects associated with waste landfilling and open dumping. Environmental Science and Pollution Research, 29(39), 58514-58536. + 5. US General Accounting Office. (1983). Siting of hazardous waste landfills and their correlation with racial and economic status of surrounding communities. RCED-83-168. +

+
+
+ + + +

+ ### Data Access + * [NASA Description for EMIT](https://lpdaac.usgs.gov/products/emitl2bch4plmv001/) + * [CDC/ATSDR SVI Data and Documentation Download | Place and Health | ATSDR](https://www.atsdr.cdc.gov/placeandhealth/svi/data_documentation_download.html) + + **Authors**: Maheshwari Neelam + + **Editor**: Maheshwari Neelam and Ashley Riddle ; + **Developers**: Trent Cowan, Andrew Blackford, and Jerika Christman ; + **Science and Content Contributors**: Maheshwari Neelam and Brian Frietag ; + **Acknowledgements**: All individuals dedicated to Environmental Justice ; + **Questions / Feedback (email address)**: maheshwari.neelam@nasa.gov + + #### Additional Resources + + 1. https://dtsc.ca.gov/2020/09/23/water-treatment-chemical-company-in-stockton-pays-32k-penalty-for-hazardous-waste-accumulation/ + 2. https://www.keranews.org/news/2022-08-23/dallas-lets-polluters-build-in-black-and-latino-neighborhoods-complaint-alleges + 3. https://www.americanbar.org/groups/crsj/publications/human_rights_magazine_home/vol--44--no-2--housing/environmental-injustice-in-uniontown--alabama--decades-after-the/ + 4. https://sites.uab.edu/humanrights/2018/09/05/the-plastic-problem/ +

+
+
+ + + + From afe396f973811e3849fabe7073f11d6568556548 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 10:47:21 -0500 Subject: [PATCH 052/152] v4 --- stories/black-belt-climate-ej.stories.mdx | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 1047bcbc0..949aed7ff 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -48,8 +48,8 @@ taxonomy:
- - + +

The Black Belt's crescent shape is captured in a natural-color image by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite. This image is a composition of segments from several images taken between 2015 and 2018, allowing for the removal of clouds and haze.

@@ -127,7 +127,7 @@ taxonomy:
- +

Agriculture remains the backbone of the Black Belt's economy, with many older adults working in the fields. This reliance on an aging workforce is concerning, particularly as the physical demands of farming intensify with rising temperatures. In Sumter County, the number of farm operators aged 55 and above is increasing, reflecting a broader national trend where the average age of U.S. farm producers has risen to 58.1 years by 2022.

@@ -135,7 +135,7 @@ taxonomy:
Age Distribution of Farm Operators. @@ -152,7 +152,7 @@ taxonomy:
From 76eacc07b122cfc96f127b57f125d35e903d3840 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 11:07:09 -0500 Subject: [PATCH 053/152] v4 --- stories/black-belt-climate-ej.stories.mdx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 949aed7ff..81fb0f82a 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -40,7 +40,7 @@ taxonomy:
General Soil Map of Alabama, highlights the distinct soils found in the prairie regions, particularly focusing on the Black Belt area. @@ -57,7 +57,7 @@ taxonomy:
Black Belt Prairie from MODIS. From 65f1926c7cb28aa04ed33c7dd0118a50640963e5 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 11:21:00 -0500 Subject: [PATCH 054/152] v4 --- stories/black-belt-climate-ej.stories.mdx | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 81fb0f82a..2b430fea5 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -32,7 +32,7 @@ taxonomy: - +

The Black Belt is a region in the Southern United States OF America. The term "Black Belt" originally referred to the region's fertile black soil, ideal for agriculture, particularly cotton plantations. The fertile soil of the Black Belt is intricately connected to the weathering of limestone bases in the Selma Chalk region, which dates back to the Cretaceous Period when the Gulf of Mexico's shoreline was much further inland. Over millions of years, plankton deposited exoskeletons rich in calcium carbonate, leading to the formation of soft limestone known as Selma Chalk. This geological process resulted in a chalky subsoil that, due to its high calcium content, provides exceptional fertility, making the Black Belt particularly suitable for agriculture.

@@ -49,7 +49,7 @@ taxonomy:
- +

The Black Belt's crescent shape is captured in a natural-color image by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite. This image is a composition of segments from several images taken between 2015 and 2018, allowing for the removal of clouds and haze.

@@ -57,7 +57,7 @@ taxonomy:
Black Belt Prairie from MODIS. From ea3f5cbe9f4e5a925424e52e4d09b151821fc7ce Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 11:41:31 -0500 Subject: [PATCH 055/152] v6 --- stories/black-belt-climate-ej.stories.mdx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 2b430fea5..f0bd84704 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -37,7 +37,7 @@ taxonomy: The Black Belt is a region in the Southern United States OF America. The term "Black Belt" originally referred to the region's fertile black soil, ideal for agriculture, particularly cotton plantations. The fertile soil of the Black Belt is intricately connected to the weathering of limestone bases in the Selma Chalk region, which dates back to the Cretaceous Period when the Gulf of Mexico's shoreline was much further inland. Over millions of years, plankton deposited exoskeletons rich in calcium carbonate, leading to the formation of soft limestone known as Selma Chalk. This geological process resulted in a chalky subsoil that, due to its high calcium content, provides exceptional fertility, making the Black Belt particularly suitable for agriculture.

-
+
-
+
Date: Wed, 21 Aug 2024 12:04:45 -0500 Subject: [PATCH 056/152] v6 --- stories/black-belt-climate-ej.stories.mdx | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index f0bd84704..3c0df769f 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -49,7 +49,7 @@ taxonomy: - +

The Black Belt's crescent shape is captured in a natural-color image by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite. This image is a composition of segments from several images taken between 2015 and 2018, allowing for the removal of clouds and haze.

@@ -66,7 +66,7 @@ taxonomy:
- +

Historically, the Alabama Black Belt was a cornerstone of the cotton economy, heavily reliant on enslaved African American labor. After the Civil War, many African Americans remained in the area, working as sharecroppers and tenant farmers. The region became a significant cultural and political area, particularly noted for its role in the civil rights movement. Despite its agricultural legacy, the Black Belt has faced economic and social challenges, including poverty and limited access to education and healthcare, which continue to impact its predominantly African American population.

@@ -83,7 +83,7 @@ taxonomy:
- +

Anthropogenic climate change is leading to more frequent and severe extreme events, such as heatwaves. This trend is particularly concerning for the Alabama Black Belt region, where many residents, especially the older population, depend on outdoor agricultural work. The MERRA-2 climate extreme indices dataset provides valuable insights into the increasing extreme temperatures affecting this area. It includes indices like Cool Nights (TN10P), which represent the percentage of days when the daily minimum temperature falls below the 10th percentile, and Warm Nights (TN90P), indicating when the daily minimum temperature exceeds the 90th percentile. Similarly, Cool Days (TX10P) and Warm Days (TX90P) track the percentage of days when daily maximum temperatures are below the 10th percentile or above the 90th percentile, respectively. By analyzing these indices for linear trends from 1980 to 2023, we can better understand the rising temperatures over time in this region.

From d89050f0889924d56d6ea2b8d7be0f6fef78822e Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 12:10:26 -0500 Subject: [PATCH 057/152] v7 --- stories/black-belt-climate-ej.stories.mdx | 15 ++++++--------- 1 file changed, 6 insertions(+), 9 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 3c0df769f..2a3560f46 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -32,7 +32,7 @@ taxonomy:
- +

The Black Belt is a region in the Southern United States OF America. The term "Black Belt" originally referred to the region's fertile black soil, ideal for agriculture, particularly cotton plantations. The fertile soil of the Black Belt is intricately connected to the weathering of limestone bases in the Selma Chalk region, which dates back to the Cretaceous Period when the Gulf of Mexico's shoreline was much further inland. Over millions of years, plankton deposited exoskeletons rich in calcium carbonate, leading to the formation of soft limestone known as Selma Chalk. This geological process resulted in a chalky subsoil that, due to its high calcium content, provides exceptional fertility, making the Black Belt particularly suitable for agriculture.

@@ -54,10 +54,10 @@ taxonomy: The Black Belt's crescent shape is captured in a natural-color image by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite. This image is a composition of segments from several images taken between 2015 and 2018, allowing for the removal of clouds and haze.

-
+
Black Belt Prairie from MODIS. @@ -127,7 +127,7 @@ taxonomy: - +

Agriculture remains the backbone of the Black Belt's economy, with many older adults working in the fields. This reliance on an aging workforce is concerning, particularly as the physical demands of farming intensify with rising temperatures. In Sumter County, the number of farm operators aged 55 and above is increasing, reflecting a broader national trend where the average age of U.S. farm producers has risen to 58.1 years by 2022.

@@ -137,14 +137,11 @@ taxonomy: src={new URL('./BB_AgeOperators_Sumter.png', import.meta.url).href} style={{ maxWidth: '50%', height: 'auto' }} /> - - Age Distribution of Farm Operators. -
- +

Additionally, outdoor occupations such as transportation and construction have become crucial sources of income and have shown growth over the past few years. Data from the U.S. Census Bureau, which examines the number of establishments by employment category in counties like Choctaw and Butler, underscores the economic importance of these sectors.

@@ -158,7 +155,7 @@ taxonomy:
- +

The combination of rising temperatures and an older workforce underscores the urgent need for adaptive strategies to protect both the health of the population and the viability of these economic sectors.Addressing these intertwined challenges requires targeted policies and investments in climate resilience measures. By enhancing education, healthcare, and job opportunities, along with adopting sustainable agricultural practices, the Black Belt can work towards a more resilient and prosperous future in the face of climate change. ### To mitigate heat-related risks, several safeguards can be implemented: From 35587f6b8ea1fdfcb1bd2487fc0eff8c229fc157 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 13:06:21 -0500 Subject: [PATCH 058/152] v7 --- stories/black-belt-climate-ej.stories.mdx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 2a3560f46..3a6223df9 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -57,7 +57,7 @@ taxonomy:

Black Belt Prairie from MODIS. @@ -135,7 +135,7 @@ taxonomy:
From ed5ab807f5febc3d181edd45533d714f0c9d9d35 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 13:24:07 -0500 Subject: [PATCH 059/152] V7 --- stories/black-belt-climate-ej.stories.mdx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 3a6223df9..d3592a00b 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -135,7 +135,7 @@ taxonomy:
@@ -184,7 +184,7 @@ taxonomy:

### Data Access - * [NASA Description for EMIT](https://lpdaac.usgs.gov/products/emitl2bch4plmv001/) + * [NASA Description for MERRA-2 Climate Indices ](https://lpdaac.usgs.gov/products/emitl2bch4plmv001/) * [CDC/ATSDR SVI Data and Documentation Download | Place and Health | ATSDR](https://www.atsdr.cdc.gov/placeandhealth/svi/data_documentation_download.html) **Authors**: Maheshwari Neelam From f8aac6066d74fbc2ddb43c253471e7060acdda98 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 13:40:03 -0500 Subject: [PATCH 060/152] v8 --- stories/black-belt-climate-ej.stories.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index d3592a00b..53764ea02 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -135,7 +135,7 @@ taxonomy:

From f697f4d51fde0e03046934cfae8b75ee7f5ac993 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 13:45:52 -0500 Subject: [PATCH 061/152] v8 --- stories/black-belt-climate-ej.stories.mdx | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 53764ea02..3bd75d729 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -184,19 +184,19 @@ taxonomy:

### Data Access - * [NASA Description for MERRA-2 Climate Indices ](https://lpdaac.usgs.gov/products/emitl2bch4plmv001/) + * [NASA Description for MERRA-2 Climate Indices ](https://search.earthdata.nasa.gov/search/granules?p=C1949649168-GES_DISC&pg[0][v]=f&pg[0][gsk]=-start_date&q=MERRA-2%20extremes&tl=1724265744.288!3!!/) * [CDC/ATSDR SVI Data and Documentation Download | Place and Health | ATSDR](https://www.atsdr.cdc.gov/placeandhealth/svi/data_documentation_download.html) - + * [United States Department of Agriculture (USDA) National Agricultural Statistics Service (NASS)](https://www.nass.usda.gov/) **Authors**: Maheshwari Neelam - **Editor**: Maheshwari Neelam and Ashley Riddle ; - **Developers**: Trent Cowan, Andrew Blackford, and Jerika Christman ; - **Science and Content Contributors**: Maheshwari Neelam and Brian Frietag ; + **Editor**: Maheshwari Neelam and Derek ; + **Developers**: Andrew Blackford, Trent Cowan, and Jerika Christman ; + **Science and Content Contributors**: Maheshwari Neelam and Udaysankar Nair; **Acknowledgements**: All individuals dedicated to Environmental Justice ; **Questions / Feedback (email address)**: maheshwari.neelam@nasa.gov #### Additional Resources - + 1. https://dtsc.ca.gov/2020/09/23/water-treatment-chemical-company-in-stockton-pays-32k-penalty-for-hazardous-waste-accumulation/ 2. https://www.keranews.org/news/2022-08-23/dallas-lets-polluters-build-in-black-and-latino-neighborhoods-complaint-alleges 3. https://www.americanbar.org/groups/crsj/publications/human_rights_magazine_home/vol--44--no-2--housing/environmental-injustice-in-uniontown--alabama--decades-after-the/ From f872ee7248b52b58c381dae0fcacaee3925cadbf Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 13:49:57 -0500 Subject: [PATCH 062/152] v9 --- stories/black-belt-climate-ej.stories.mdx | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 3bd75d729..f3effc7ab 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -57,7 +57,7 @@ taxonomy:

Black Belt Prairie from MODIS. @@ -135,7 +135,7 @@ taxonomy:
@@ -196,7 +196,7 @@ taxonomy: **Questions / Feedback (email address)**: maheshwari.neelam@nasa.gov #### Additional Resources - + 1. https://dtsc.ca.gov/2020/09/23/water-treatment-chemical-company-in-stockton-pays-32k-penalty-for-hazardous-waste-accumulation/ 2. https://www.keranews.org/news/2022-08-23/dallas-lets-polluters-build-in-black-and-latino-neighborhoods-complaint-alleges 3. https://www.americanbar.org/groups/crsj/publications/human_rights_magazine_home/vol--44--no-2--housing/environmental-injustice-in-uniontown--alabama--decades-after-the/ From c522196698255de4bf17fe122b90b4d155920781 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 13:54:16 -0500 Subject: [PATCH 063/152] V9 --- stories/black-belt-climate-ej.stories.mdx | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index f3effc7ab..dc0dfb0e6 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -37,7 +37,7 @@ taxonomy: The Black Belt is a region in the Southern United States OF America. The term "Black Belt" originally referred to the region's fertile black soil, ideal for agriculture, particularly cotton plantations. The fertile soil of the Black Belt is intricately connected to the weathering of limestone bases in the Selma Chalk region, which dates back to the Cretaceous Period when the Gulf of Mexico's shoreline was much further inland. Over millions of years, plankton deposited exoskeletons rich in calcium carbonate, leading to the formation of soft limestone known as Selma Chalk. This geological process resulted in a chalky subsoil that, due to its high calcium content, provides exceptional fertility, making the Black Belt particularly suitable for agriculture.

-
+
Black Belt Prairie from MODIS. @@ -135,7 +135,7 @@ taxonomy:
From d0838062356d8bb5e28d526462a9e74a8f0307cb Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 14:05:58 -0500 Subject: [PATCH 064/152] v10 --- stories/black-belt-climate-ej.stories.mdx | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index dc0dfb0e6..f13b0749c 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -40,7 +40,7 @@ taxonomy:
General Soil Map of Alabama, highlights the distinct soils found in the prairie regions, particularly focusing on the Black Belt area. @@ -57,7 +57,7 @@ taxonomy:
Black Belt Prairie from MODIS. @@ -149,7 +149,7 @@ taxonomy:
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d154cdde2..63e117321 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -16,21 +16,35 @@ taxonomy: - Disasters --- - - + + - Authors: Maheshwari Neelam [1], Udaysankar Nair [2] + Authors: Maheshwari Neelam [1], Udaysankar Nair [2] and Natalie P.Thomas [3] [1] USRA and National Aeronautics and Space Administration (NASA) [2] The University of Alabama in Huntsville + [3] University of Maryland and Global Modeling and Assimilation Office, NASA + **Mission**: [NASA Earth Action](https://science.nasa.gov/earth/in-action/): A thriving world, driven by trusted, actionable Earth science **Disclaimer**: This study demonstrates innovative and practical applications of NASA Earth science data to highlight existing environmental inequities. Please note that the results have not undergone peer review. + + +

+ Authors: Maheshwari Neelam [1], Udaysankar Nair [2] + [1] USRA and National Aeronautics and Space Administration (NASA) + [2] The University of Alabama in Huntsville + **Mission**: [NASA Earth Action](https://science.nasa.gov/earth/in-action/): A thriving world, driven by trusted, actionable Earth science + **Disclaimer**: This study demonstrates innovative and practical applications of NASA Earth science data to highlight existing environmental inequities. Please note that the results have not undergone peer review. +

+
+
+

@@ -55,7 +69,7 @@ taxonomy:

- @@ -190,7 +204,7 @@ taxonomy: **Authors**: Maheshwari Neelam **Editor**: Maheshwari Neelam and Derek ; - **Developers**: Andrew Blackford, Trent Cowan, and Jerika Christman ; + **Developers**: Andrew Blackford, Trent Cowan, Jerika Christman, Brian Freitag and Aaron Kaulfus ; **Science and Content Contributors**: Maheshwari Neelam and Udaysankar Nair; **Acknowledgements**: All individuals dedicated to Environmental Justice ; **Questions / Feedback (email address)**: maheshwari.neelam@nasa.gov From 45c90cd2927ce8ffd77fbca209185ebff1b087c0 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 15:09:23 -0500 Subject: [PATCH 067/152] V12 --- stories/black-belt-climate-ej.stories.mdx | 47 +++++++++-------------- 1 file changed, 19 insertions(+), 28 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 63e117321..4916f2a13 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -16,31 +16,25 @@ taxonomy: - Disasters --- - - - - Authors: Maheshwari Neelam [1], Udaysankar Nair [2] and Natalie P.Thomas [3] - - [1] USRA and National Aeronautics and Space Administration (NASA) - - [2] The University of Alabama in Huntsville - - [3] University of Maryland and Global Modeling and Assimilation Office, NASA - - **Mission**: [NASA Earth Action](https://science.nasa.gov/earth/in-action/): A thriving world, driven by trusted, actionable Earth science - - **Disclaimer**: This study demonstrates innovative and practical applications of NASA Earth science data to highlight existing environmental inequities. Please note that the results have not undergone peer review. - - - - - -

- Authors: Maheshwari Neelam [1], Udaysankar Nair [2] - [1] USRA and National Aeronautics and Space Administration (NASA) - [2] The University of Alabama in Huntsville - **Mission**: [NASA Earth Action](https://science.nasa.gov/earth/in-action/): A thriving world, driven by trusted, actionable Earth science - **Disclaimer**: This study demonstrates innovative and practical applications of NASA Earth science data to highlight existing environmental inequities. Please note that the results have not undergone peer review. + + +

+ Authors: Maheshwari Neelam [1], Udaysankar Nair [2] and Natalie P.Thomas [3] +

+

+ [1] USRA and National Aeronautics and Space Administration (NASA) +

+

+ [2] The University of Alabama in Huntsville +

+

+ [3] University of Maryland and Global Modeling and Assimilation Office, NASA +

+

+ Mission: NASA Earth Action: A thriving world, driven by trusted, actionable Earth science +

+

+ Disclaimer: This study demonstrates innovative and practical applications of NASA Earth science data to highlight existing environmental inequities. Please note that the results have not undergone peer review.

@@ -90,9 +84,6 @@ taxonomy: src={new URL('./Black_cotton_farming_family.jpg', import.meta.url).href} style={{ maxWidth: '100%', height: 'auto' }} /> - - Black cotton farming family. -
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zKsi|5T(2P`RFMj1eYjpU;lR^a$ABJ^!9R<{CszfQj`Yz>Ao+skWLkl@Xt*m*!I^`z}3V`crO^9vQ!(JKOI{3DP8EsTFl zc}08)r~gBd`3RM!QUS-HQLc`U&crou1tsrnl1d!hs|D|-Eekf9E7h@%hOy&^J*&S< zRT^}YL|`xarrARUn>82biPov(C94oNeFDpscgHTlnobpQyN46#<7-{@H=84BrBl|;J+bE9T3S$XoKADs z-HW38UG;A;@t-Js;*w7S^k1Ox|M0Q!LbxQVUGgWR)d{dL^rBoW(Ez2a-e`XRRUR_~ ztHfL1#Q3ZK>(1gy8^G`uWJByF6_KDixPrM&fRo%P=wmf9Kg#{Dyc{XiE4P+UYDrzmvZOK;z&7WH|>4gU-n`i~q_R%;7Yx}2*oLkO$;J;bt)|#Fps_@{y zOVGH`c)zU5g;>y+Pp^V*2+KcGsAk@;N3`ohUW7bc3;~};gXfTr`Yq_GYB}7W)(dAGbANHKZdH}<)~j>5DOI0(W&bp!wBf%pJN;i; l&A))<|LQSZ=-S5dsfb(Bu4eDnuag0PcQy2Hm#f)C{0|_ZY>5B> diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 4916f2a13..362a39310 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -50,9 +50,6 @@ taxonomy: src={new URL('./soilmap_Alabama.png', import.meta.url).href} style={{maxWidth: '600px', height: 'auto' }} /> - - General Soil Map of Alabama, highlights the distinct soils found in the prairie regions, particularly focusing on the Black Belt area. -
@@ -153,7 +150,7 @@ taxonomy:
@@ -192,21 +189,23 @@ taxonomy: * [NASA Description for MERRA-2 Climate Indices ](https://search.earthdata.nasa.gov/search/granules?p=C1949649168-GES_DISC&pg[0][v]=f&pg[0][gsk]=-start_date&q=MERRA-2%20extremes&tl=1724265744.288!3!!/) * [CDC/ATSDR SVI Data and Documentation Download | Place and Health | ATSDR](https://www.atsdr.cdc.gov/placeandhealth/svi/data_documentation_download.html) * [United States Department of Agriculture (USDA) National Agricultural Statistics Service (NASS)](https://www.nass.usda.gov/) +

+

**Authors**: Maheshwari Neelam - **Editor**: Maheshwari Neelam and Derek ; **Developers**: Andrew Blackford, Trent Cowan, Jerika Christman, Brian Freitag and Aaron Kaulfus ; **Science and Content Contributors**: Maheshwari Neelam and Udaysankar Nair; **Acknowledgements**: All individuals dedicated to Environmental Justice ; **Questions / Feedback (email address)**: maheshwari.neelam@nasa.gov - +

+

#### Additional Resources - 1. https://dtsc.ca.gov/2020/09/23/water-treatment-chemical-company-in-stockton-pays-32k-penalty-for-hazardous-waste-accumulation/ 2. https://www.keranews.org/news/2022-08-23/dallas-lets-polluters-build-in-black-and-latino-neighborhoods-complaint-alleges 3. https://www.americanbar.org/groups/crsj/publications/human_rights_magazine_home/vol--44--no-2--housing/environmental-injustice-in-uniontown--alabama--decades-after-the/ 4. https://sites.uab.edu/humanrights/2018/09/05/the-plastic-problem/

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@@ -137,7 +137,7 @@ taxonomy:
@@ -200,10 +200,10 @@ taxonomy:

#### Additional Resources - 1. https://dtsc.ca.gov/2020/09/23/water-treatment-chemical-company-in-stockton-pays-32k-penalty-for-hazardous-waste-accumulation/ - 2. https://www.keranews.org/news/2022-08-23/dallas-lets-polluters-build-in-black-and-latino-neighborhoods-complaint-alleges - 3. https://www.americanbar.org/groups/crsj/publications/human_rights_magazine_home/vol--44--no-2--housing/environmental-injustice-in-uniontown--alabama--decades-after-the/ - 4. https://sites.uab.edu/humanrights/2018/09/05/the-plastic-problem/ + 1.https://blogs.edf.org/growingreturns/2023/08/02/heat-threat-for-farmworkers/ + 2. https://www.thenation.com/article/society/black-farmers-pigford-debt/ + 3. https://foodprint.org/issues/black-land-loss-in-the-united-states/ + 4. https://inthesetimes.com/article/black-farmers-stress-debt-land-loss-racism-mental-health-crisis

From 729f3f48aff8ad89c7f769e18ddf415ea46840e0 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 15:42:18 -0500 Subject: [PATCH 070/152] v15 --- stories/black-belt-climate-ej.stories.mdx | 15 +++++++++------ 1 file changed, 9 insertions(+), 6 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 8b38f30fe..ccc5608d3 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -42,14 +42,17 @@ taxonomy:

- The Black Belt is a region in the Southern United States OF America. The term "Black Belt" originally referred to the region's fertile black soil, ideal for agriculture, particularly cotton plantations. The fertile soil of the Black Belt is intricately connected to the weathering of limestone bases in the Selma Chalk region, which dates back to the Cretaceous Period when the Gulf of Mexico's shoreline was much further inland. Over millions of years, plankton deposited exoskeletons rich in calcium carbonate, leading to the formation of soft limestone known as Selma Chalk. This geological process resulted in a chalky subsoil that, due to its high calcium content, provides exceptional fertility, making the Black Belt particularly suitable for agriculture. + The Alabama Black Belt, a region steeped in history and rich in natural resources, has long been an integral part of the Southern United States. The name "Black Belt" originally referred to the area's dark, fertile soil, ideal for agriculture, especially cotton plantations. This fertile land owes its richness to a unique geological history. Millions of years ago, when the shoreline of the Gulf of Mexico extended much farther inland, plankton deposited calcium carbonate-rich exoskeletons, eventually forming soft limestone known as Selma Chalk. Over time, this limestone weathered, giving rise to the chalky subsoil that characterizes the Black Belt. The high calcium content of this soil made it exceptionally fertile, transforming the region into a powerhouse of agricultural production.

+ + General Soil Map of Alabama. +
@@ -87,7 +90,7 @@ taxonomy:

- Anthropogenic climate change is leading to more frequent and severe extreme events, such as heatwaves. This trend is particularly concerning for the Alabama Black Belt region, where many residents, especially the older population, depend on outdoor agricultural work. The MERRA-2 climate extreme indices dataset provides valuable insights into the increasing extreme temperatures affecting this area. It includes indices like Cool Nights (TN10P), which represent the percentage of days when the daily minimum temperature falls below the 10th percentile, and Warm Nights (TN90P), indicating when the daily minimum temperature exceeds the 90th percentile. Similarly, Cool Days (TX10P) and Warm Days (TX90P) track the percentage of days when daily maximum temperatures are below the 10th percentile or above the 90th percentile, respectively. By analyzing these indices for linear trends from 1980 to 2023, we can better understand the rising temperatures over time in this region. + Data from the MERRA-2 climate extreme indices dataset reveal alarming trends. The indices track various temperature extremes, such as Cool Nights (TN10P), which represent the percentage of days when nighttime temperatures fall below the 10th percentile, and Warm Nights (TN90P), indicating when nighttime temperatures exceed the 90th percentile. Similarly, Cool Days (TX10P) and Warm Days (TX90P) monitor daytime temperature extremes. Analyzing these indices from 1980 to 2023 reveals a clear pattern of rising temperatures in the Black Belt, with an increasing number of warm days and nights.

@@ -201,9 +204,9 @@ taxonomy:

#### Additional Resources 1.https://blogs.edf.org/growingreturns/2023/08/02/heat-threat-for-farmworkers/ - 2. https://www.thenation.com/article/society/black-farmers-pigford-debt/ - 3. https://foodprint.org/issues/black-land-loss-in-the-united-states/ - 4. https://inthesetimes.com/article/black-farmers-stress-debt-land-loss-racism-mental-health-crisis + 2.https://www.thenation.com/article/society/black-farmers-pigford-debt/ + 3.https://foodprint.org/issues/black-land-loss-in-the-united-states/ + 4.https://inthesetimes.com/article/black-farmers-stress-debt-land-loss-racism-mental-health-crisis

From 0059a48731e799c5766c9d5be9a543e86b3d69da Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 16:08:46 -0500 Subject: [PATCH 071/152] v18 --- stories/black-belt-climate-ej.stories.mdx | 23 +++++++++++++++++++++-- 1 file changed, 21 insertions(+), 2 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index ccc5608d3..cbebccda7 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -87,10 +87,28 @@ taxonomy:
+ + + Increasing Warm Nights +

+ Analyzing Social Vulnerability Index (SVI) data from the CDC between 2000 and 2022 shows a concerning demographic shift: the younger generation, including those as young as 17, is increasingly moving out of the region, leaving behind an aging population, particularly those aged 65 and above. A linear trend is observed, with color coding representing the slope of this shift. This trend exacerbates the region's vulnerabilities, as the older population becomes more isolated and dependent. +

+ Increasing Warm Days +
+
+

- Data from the MERRA-2 climate extreme indices dataset reveal alarming trends. The indices track various temperature extremes, such as Cool Nights (TN10P), which represent the percentage of days when nighttime temperatures fall below the 10th percentile, and Warm Nights (TN90P), indicating when nighttime temperatures exceed the 90th percentile. Similarly, Cool Days (TX10P) and Warm Days (TX90P) monitor daytime temperature extremes. Analyzing these indices from 1980 to 2023 reveals a clear pattern of rising temperatures in the Black Belt, with an increasing number of warm days and nights. + The region is now facing a significant new challenge: climate change. As global temperatures rise, extreme weather events like heatwaves are becoming increasingly frequent and severe. This is particularly concerning for areas where many residents, especially older adults, rely on outdoor agricultural work. Data from the MERRA-2 climate extreme indices dataset reveal troubling trends, showing changes in temperature extremes. Indices such as Cool Nights (TN10P) and Warm Nights (TN90P) track the frequency of days with nighttime temperatures falling below the 10th percentile or exceeding the 90th percentile. Similarly, Cool Days (TX10P) and Warm Days (TX90P) monitor daytime temperature extremes. Analyzing these indices from 1980 to 2023 uncovers a clear pattern of rising temperatures, with an increasing number of warm days and nights, highlighting the escalating climate challenges facing the region.

@@ -191,7 +209,8 @@ taxonomy: ### Data Access * [NASA Description for MERRA-2 Climate Indices ](https://search.earthdata.nasa.gov/search/granules?p=C1949649168-GES_DISC&pg[0][v]=f&pg[0][gsk]=-start_date&q=MERRA-2%20extremes&tl=1724265744.288!3!!/) * [CDC/ATSDR SVI Data and Documentation Download | Place and Health | ATSDR](https://www.atsdr.cdc.gov/placeandhealth/svi/data_documentation_download.html) - * [United States Department of Agriculture (USDA) National Agricultural Statistics Service (NASS)](https://www.nass.usda.gov/) + * [United States Department of Agriculture (USDA) | National Agricultural Statistics Service (NASS) | Census](https://www.nass.usda.gov/) + * [Census Bureau Data | Occupation](https://www.census.gov/topics/employment/industry-occupation.html)]

**Authors**: Maheshwari Neelam From 1ea8de8be738a93779f8d3cafcbdcfec8ceeae51 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 16:12:08 -0500 Subject: [PATCH 072/152] v20 --- stories/black-belt-climate-ej.stories.mdx | 17 +---------------- 1 file changed, 1 insertion(+), 16 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index cbebccda7..3389949aa 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -92,15 +92,13 @@ taxonomy: Increasing Warm Nights

Analyzing Social Vulnerability Index (SVI) data from the CDC between 2000 and 2022 shows a concerning demographic shift: the younger generation, including those as young as 17, is increasingly moving out of the region, leaving behind an aging population, particularly those aged 65 and above. A linear trend is observed, with color coding representing the slope of this shift. This trend exacerbates the region's vulnerabilities, as the older population becomes more isolated and dependent.

Increasing Warm Days @@ -190,19 +188,6 @@ taxonomy: - - -

- ### References - 1. Christine Todd Whitman. (2001). Environmental Protection Agency, EPA’s Commitment to Environmental Justice, Memorandum. - 2. https://www.washingtonpost.com/climate-environment/2020/11/16/environmental-racism-dallas-shingle-mountain/ - 3. Piper, I. (2023). The Inequitable Placement of Hazardous Waste Facilities: How Underserved Communities are Disproportionately Impacted. - 4. Siddiqua, A., Hahladakis, J. N., & Al-Attiya, W. A. K. (2022). An overview of the environmental pollution and health effects associated with waste landfilling and open dumping. Environmental Science and Pollution Research, 29(39), 58514-58536. - 5. US General Accounting Office. (1983). Siting of hazardous waste landfills and their correlation with racial and economic status of surrounding communities. RCED-83-168. -

-
-
-

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- + General Soil Map of Alabama.
From b3141e29645bff049e62a3aaa235ebadbeb94447 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 16:26:38 -0500 Subject: [PATCH 074/152] V21 --- stories/black-belt-climate-ej.stories.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 153980353..3c9c3bf96 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -48,7 +48,7 @@ taxonomy:
General Soil Map of Alabama. From 3e9fd2b2236b6c34ae499fce1fd9983c4185c460 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 16:29:28 -0500 Subject: [PATCH 075/152] v22 --- stories/black-belt-climate-ej.stories.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 3c9c3bf96..19021b976 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -48,7 +48,7 @@ taxonomy:
General Soil Map of Alabama. From 18e4b35cdf8715cef8a855e827383c2bb78e98dd Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 16:32:31 -0500 Subject: [PATCH 076/152] v23 --- stories/black-belt-climate-ej.stories.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 19021b976..eee6885b7 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -48,7 +48,7 @@ taxonomy:
General Soil Map of Alabama. From 2195b3a4319e831936381b4662e20bb196007951 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 16:37:09 -0500 Subject: [PATCH 077/152] v22 --- stories/black-belt-climate-ej.stories.mdx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index eee6885b7..328e0ca53 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -45,10 +45,10 @@ taxonomy: The Alabama Black Belt, a region steeped in history and rich in natural resources, has long been an integral part of the Southern United States. The name "Black Belt" originally referred to the area's dark, fertile soil, ideal for agriculture, especially cotton plantations. This fertile land owes its richness to a unique geological history. Millions of years ago, when the shoreline of the Gulf of Mexico extended much farther inland, plankton deposited calcium carbonate-rich exoskeletons, eventually forming soft limestone known as Selma Chalk. Over time, this limestone weathered, giving rise to the chalky subsoil that characterizes the Black Belt. The high calcium content of this soil made it exceptionally fertile, transforming the region into a powerhouse of agricultural production.

-
+
General Soil Map of Alabama. From b304dbd393fa6d14f8df950a56218c2d4f8c2af8 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 16:39:38 -0500 Subject: [PATCH 078/152] v26 --- stories/black-belt-climate-ej.stories.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 328e0ca53..e0ce995b7 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -48,7 +48,7 @@ taxonomy:
General Soil Map of Alabama. From 227814674d4cbbf688513ad5f3f43779a4512b38 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 16:42:49 -0500 Subject: [PATCH 079/152] v28 --- stories/black-belt-climate-ej.stories.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index e0ce995b7..5338a4e2d 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -48,7 +48,7 @@ taxonomy:
General Soil Map of Alabama. From c763bdfe0047cc339351749049aa7ca3c4429925 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 16:47:09 -0500 Subject: [PATCH 080/152] v28 --- stories/black-belt-climate-ej.stories.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 5338a4e2d..a580dd970 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -40,7 +40,7 @@ taxonomy: - +

The Alabama Black Belt, a region steeped in history and rich in natural resources, has long been an integral part of the Southern United States. The name "Black Belt" originally referred to the area's dark, fertile soil, ideal for agriculture, especially cotton plantations. This fertile land owes its richness to a unique geological history. Millions of years ago, when the shoreline of the Gulf of Mexico extended much farther inland, plankton deposited calcium carbonate-rich exoskeletons, eventually forming soft limestone known as Selma Chalk. Over time, this limestone weathered, giving rise to the chalky subsoil that characterizes the Black Belt. The high calcium content of this soil made it exceptionally fertile, transforming the region into a powerhouse of agricultural production.

From 68069f3c69e762d18d6439ff73dae80f285a4a0b Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 16:50:18 -0500 Subject: [PATCH 081/152] v28 --- stories/black-belt-climate-ej.stories.mdx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index a580dd970..abd017eb9 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -45,10 +45,10 @@ taxonomy: The Alabama Black Belt, a region steeped in history and rich in natural resources, has long been an integral part of the Southern United States. The name "Black Belt" originally referred to the area's dark, fertile soil, ideal for agriculture, especially cotton plantations. This fertile land owes its richness to a unique geological history. Millions of years ago, when the shoreline of the Gulf of Mexico extended much farther inland, plankton deposited calcium carbonate-rich exoskeletons, eventually forming soft limestone known as Selma Chalk. Over time, this limestone weathered, giving rise to the chalky subsoil that characterizes the Black Belt. The high calcium content of this soil made it exceptionally fertile, transforming the region into a powerhouse of agricultural production.

-
+
General Soil Map of Alabama. From ff6e8837bb0e60fb0ffc9abe7975f77507e9c97b Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 16:54:32 -0500 Subject: [PATCH 082/152] v29 --- stories/black-belt-climate-ej.stories.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index abd017eb9..693f9c908 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -48,7 +48,7 @@ taxonomy:
General Soil Map of Alabama. From 6c16f1f5c02b50179b8bee13caff8736f6fc4d20 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 21 Aug 2024 16:57:16 -0500 Subject: [PATCH 083/152] v30 --- stories/black-belt-climate-ej.stories.mdx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 693f9c908..be9335b53 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -45,10 +45,10 @@ taxonomy: The Alabama Black Belt, a region steeped in history and rich in natural resources, has long been an integral part of the Southern United States. The name "Black Belt" originally referred to the area's dark, fertile soil, ideal for agriculture, especially cotton plantations. This fertile land owes its richness to a unique geological history. Millions of years ago, when the shoreline of the Gulf of Mexico extended much farther inland, plankton deposited calcium carbonate-rich exoskeletons, eventually forming soft limestone known as Selma Chalk. Over time, this limestone weathered, giving rise to the chalky subsoil that characterizes the Black Belt. The high calcium content of this soil made it exceptionally fertile, transforming the region into a powerhouse of agricultural production.

-
+
General Soil Map of Alabama. From f5d0d8362dc720daf64c90cfc3f6df30a09e6bb5 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Thu, 22 Aug 2024 08:56:30 -0500 Subject: [PATCH 084/152] v31 --- stories/black-belt-climate-ej.stories.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index be9335b53..a3a49a324 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -45,7 +45,7 @@ taxonomy: The Alabama Black Belt, a region steeped in history and rich in natural resources, has long been an integral part of the Southern United States. The name "Black Belt" originally referred to the area's dark, fertile soil, ideal for agriculture, especially cotton plantations. This fertile land owes its richness to a unique geological history. Millions of years ago, when the shoreline of the Gulf of Mexico extended much farther inland, plankton deposited calcium carbonate-rich exoskeletons, eventually forming soft limestone known as Selma Chalk. Over time, this limestone weathered, giving rise to the chalky subsoil that characterizes the Black Belt. The high calcium content of this soil made it exceptionally fertile, transforming the region into a powerhouse of agricultural production.

-
+
Date: Thu, 22 Aug 2024 09:12:11 -0500 Subject: [PATCH 085/152] V33 --- stories/black-belt-climate-ej.stories.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index a3a49a324..4346b5f5e 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -48,7 +48,7 @@ taxonomy:
General Soil Map of Alabama. From c046548792b72b2d5ab704aba92f9ccdcad460f2 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Thu, 22 Aug 2024 09:17:28 -0500 Subject: [PATCH 086/152] v34 --- stories/black-belt-climate-ej.stories.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 4346b5f5e..18a597521 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -48,7 +48,7 @@ taxonomy:
General Soil Map of Alabama. From e563048465b1ac7e7c46a0b697780991c0598987 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Thu, 22 Aug 2024 09:23:55 -0500 Subject: [PATCH 087/152] v34 --- stories/black-belt-climate-ej.stories.mdx | 12 +++++------- 1 file changed, 5 insertions(+), 7 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 18a597521..e939b5646 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -40,7 +40,7 @@ taxonomy: - +

The Alabama Black Belt, a region steeped in history and rich in natural resources, has long been an integral part of the Southern United States. The name "Black Belt" originally referred to the area's dark, fertile soil, ideal for agriculture, especially cotton plantations. This fertile land owes its richness to a unique geological history. Millions of years ago, when the shoreline of the Gulf of Mexico extended much farther inland, plankton deposited calcium carbonate-rich exoskeletons, eventually forming soft limestone known as Selma Chalk. Over time, this limestone weathered, giving rise to the chalky subsoil that characterizes the Black Belt. The high calcium content of this soil made it exceptionally fertile, transforming the region into a powerhouse of agricultural production.

@@ -198,7 +198,6 @@ taxonomy: * [Census Bureau Data | Occupation](https://www.census.gov/topics/employment/industry-occupation.html)]

- **Authors**: Maheshwari Neelam **Editor**: Maheshwari Neelam and Derek ; **Developers**: Andrew Blackford, Trent Cowan, Jerika Christman, Brian Freitag and Aaron Kaulfus ; **Science and Content Contributors**: Maheshwari Neelam and Udaysankar Nair; @@ -207,12 +206,11 @@ taxonomy:

#### Additional Resources - 1.https://blogs.edf.org/growingreturns/2023/08/02/heat-threat-for-farmworkers/ - 2.https://www.thenation.com/article/society/black-farmers-pigford-debt/ - 3.https://foodprint.org/issues/black-land-loss-in-the-united-states/ - 4.https://inthesetimes.com/article/black-farmers-stress-debt-land-loss-racism-mental-health-crisis + * https://blogs.edf.org/growingreturns/2023/08/02/heat-threat-for-farmworkers/ + * https://www.thenation.com/article/society/black-farmers-pigford-debt/ + * https://foodprint.org/issues/black-land-loss-in-the-united-states/ + * https://inthesetimes.com/article/black-farmers-stress-debt-land-loss-racism-mental-health-crisis

-
From 17994ac701ed766e72e8abe7c19ea553932ffe5c Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Thu, 22 Aug 2024 09:51:00 -0500 Subject: [PATCH 088/152] v34 --- stories/black-belt-climate-ej.stories.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index e939b5646..3ac35f1ea 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -48,7 +48,7 @@ taxonomy:
General Soil Map of Alabama. From 0b6e57c0a8b91eff9b61e3a1f099971fa0976053 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Thu, 22 Aug 2024 09:59:07 -0500 Subject: [PATCH 089/152] V35 --- stories/black-belt-climate-ej.stories.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 3ac35f1ea..5afc34605 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -48,7 +48,7 @@ taxonomy:
General Soil Map of Alabama. From 678177f9f59e80cd1dc066796962ba52caa10a3a Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Fri, 23 Aug 2024 11:52:31 -0500 Subject: [PATCH 090/152] v37 --- stories/black-belt-climate-ej.stories.mdx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 5afc34605..2cf645b26 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -42,7 +42,7 @@ taxonomy:

- The Alabama Black Belt, a region steeped in history and rich in natural resources, has long been an integral part of the Southern United States. The name "Black Belt" originally referred to the area's dark, fertile soil, ideal for agriculture, especially cotton plantations. This fertile land owes its richness to a unique geological history. Millions of years ago, when the shoreline of the Gulf of Mexico extended much farther inland, plankton deposited calcium carbonate-rich exoskeletons, eventually forming soft limestone known as Selma Chalk. Over time, this limestone weathered, giving rise to the chalky subsoil that characterizes the Black Belt. The high calcium content of this soil made it exceptionally fertile, transforming the region into a powerhouse of agricultural production. + The Alabama Black Belt, a region integral to the Southern United States, derives its name from its dark, fertile soil. This rich land, ideal for agriculture, especially cotton, owes its fertility to a unique geological history. Millions of years ago, when the Gulf of Mexico extended further inland, plankton deposits formed soft limestone called Selma Chalk. Over time, this limestone weathered, creating the calcium-rich, chalky subsoil that characterizes the Black Belt, transforming it into an agricultural powerhouse.

@@ -76,7 +76,7 @@ taxonomy:

- Historically, the Alabama Black Belt was a cornerstone of the cotton economy, heavily reliant on enslaved African American labor. After the Civil War, many African Americans remained in the area, working as sharecroppers and tenant farmers. The region became a significant cultural and political area, particularly noted for its role in the civil rights movement. Despite its agricultural legacy, the Black Belt has faced economic and social challenges, including poverty and limited access to education and healthcare, which continue to impact its predominantly African American population. + The region's rich soil played a pivotal role in shaping the region's history and demographics. This fertile land transformed the area into an agricultural powerhouse, making it a cornerstone of the cotton economy, heavily reliant on enslaved African American labor. After the Civil War, many African Americans remained in the area, working as sharecroppers and tenant farmers. The region became a significant cultural and political area, particularly noted for its role in the civil rights movement. Despite its agricultural legacy, the Black Belt has faced economic and social challenges, including poverty and limited access to education and healthcare, which continue to impact its predominantly African American population.

From ba8d44a064d1538b568c57084e1ad052b2fc7975 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Fri, 23 Aug 2024 12:04:45 -0500 Subject: [PATCH 091/152] v38 --- stories/black-belt-climate-ej.stories.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 2cf645b26..704356ca3 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -1,7 +1,7 @@ --- id: black-belt-climate name: Climate Extremes Aggravate Social Vulnerabilities in Alabama's Black Belt -description: "Rising temperatures worsen social vulnerabilities for elder population by increasing their heat-related health risks." +description: "Rising temperatures worsen social vulnerabilities for the elderly population by increasing their heat-related health risks." media: src: ::file ./black_belt_cover.jpg alt: Farmer in the fields. From 68077c5f19ccd1f9ea161d37d1eb04f162182019 Mon Sep 17 00:00:00 2001 From: Andrew Blackford <62357205+acblackford@users.noreply.github.com> Date: Fri, 23 Aug 2024 15:45:11 -0500 Subject: [PATCH 092/152] edited author and editor lists --- stories/black-belt-climate-ej.stories.mdx | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 704356ca3..d41566a72 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -19,7 +19,7 @@ taxonomy:

- Authors: Maheshwari Neelam [1], Udaysankar Nair [2] and Natalie P.Thomas [3] + Authors: Maheshwari Neelam [1], Udaysankar Nair [2], Andrew Blackford [2], and Natalie P.Thomas [3]

[1] USRA and National Aeronautics and Space Administration (NASA) @@ -198,8 +198,8 @@ taxonomy: * [Census Bureau Data | Occupation](https://www.census.gov/topics/employment/industry-occupation.html)]

- **Editor**: Maheshwari Neelam and Derek ; - **Developers**: Andrew Blackford, Trent Cowan, Jerika Christman, Brian Freitag and Aaron Kaulfus ; + **Editor**: Maheshwari Neelam and Derek Koehl; + **Developers**: Andrew Blackford, Trent Cowan, Jerika Christman, Brian Freitag, and Aaron Kaulfus ; **Science and Content Contributors**: Maheshwari Neelam and Udaysankar Nair; **Acknowledgements**: All individuals dedicated to Environmental Justice ; **Questions / Feedback (email address)**: maheshwari.neelam@nasa.gov From 32e1dff6ed6e6304474e41ca7f850bba8f94086a Mon Sep 17 00:00:00 2001 From: siddharth0248 Date: Tue, 27 Aug 2024 14:52:37 -0500 Subject: [PATCH 093/152] nldas3 story added --- datasets/nldas-cover.png | Bin 0 -> 604907 bytes datasets/nldas2.data.mdx | 88 +++++++++ datasets/nldas3.data.mdx | 105 +++++++++++ stories/nldas-cover.png | Bin 0 -> 604907 bytes stories/nldas-fig1.png | Bin 0 -> 410999 bytes stories/nldas-fig4.png | Bin 0 -> 257001 bytes stories/nldas-fig5.png | Bin 0 -> 376409 bytes stories/nldas-fig7.png | Bin 0 -> 823682 bytes stories/nldas3-fig1b.png | Bin 0 -> 2574734 bytes stories/nldas3.stories.mdx | 372 +++++++++++++++++++++++++++++++++++++ 10 files changed, 565 insertions(+) create mode 100644 datasets/nldas-cover.png create mode 100644 datasets/nldas2.data.mdx create mode 100644 datasets/nldas3.data.mdx create mode 100644 stories/nldas-cover.png create mode 100644 stories/nldas-fig1.png create mode 100644 stories/nldas-fig4.png create mode 100644 stories/nldas-fig5.png create mode 100644 stories/nldas-fig7.png create mode 100644 stories/nldas3-fig1b.png create mode 100644 stories/nldas3.stories.mdx diff --git a/datasets/nldas-cover.png b/datasets/nldas-cover.png new file mode 100644 index 0000000000000000000000000000000000000000..8e3e63467136234e726fd809409eee1417b9a6c4 GIT binary patch literal 604907 zcmZ_0Wl$YX@GXeDLvVKp?(XjH?yeUP?ykYz9fG?Df?wPr=)Jf@@cr%o?R!WDPD%p;0v-qf0S!ig{?GF(QcrPEQC^ar zmsDw@)92?WaH9KUd!`OzbPxi9970}7T+4U!Lf^5qjt?y%6rT=`CwuzkOVn${f1P%+ zUsF)~-n?TO0}cH!dRb>We=C?6EqZj{?fu-{6PxdU?651h|1n^9_W#E~?)fkNp9c@{ ze*^i9fF%FJ=qeWcUsQ3Q{}=E711Dwy{}25C@cuvWLo%!f)BlC|e02MNg8x5D|L?ip zgOOh6{Td@QJFsPYg&utiMM)fTyt4L!R@ZvrjV>~#o^^Dd0(UOa6h7bIYgfKnbn2Z) zH(i#a{4YL|N{yr2rUOj%de-;bELP{muJ5P<_Dm2T;ueifE?~VPa@N^SQ;B9ggr%fTE2wePi8g4 z(-(8N_Tfiv&OuFt2Wvs{MuJ~<`GNg2pSZKkqIqG%!CLqu!3#+TAG|9i!%d^=>oIKq`Fx?Fq@r^R@*?GDL6YMbg1CDr0Vgipl zu88<)EmW2tgdw4`j_g6iYd7sp2mb;qj7+hBi}aMnOPYj`EwiS*sn;>utfq_GZ{nc2 zDnMrF6ZUAk;UMavODY}iCEz&B13}cwwIGV=*0ANmo-ljwprfUDl7c{CXZTh#%31oi zAuxR)h5HW{U?!UIjRqsVh(z9dnY0}9aeaWBcq_=swc42Df>s8UoLb*>R3>zhu812< z^Ew*zT_3I6M_O{9clp#R-mh@~DaXkoGx}SD7kB#$NHG%GdHtRq)WHCc%QE7kvjw;| zklf4AYcl0B`U=v zCfJXm4o5Bhn+`Wl_~V<=kZ1I1#$yg>yJkH=*y=hAEP(m>tRI-Bu8r#%x|-d*=wCoQ zCCx2-t4UnF+}UkU+k%Ei^mEn#YI=GKK<^7Leqe!x%(5bF(3B&Il5W0a#X5R+0qG8} z`gewl#e$}`J))pc0_%Nu=o%0lO9}*gZru zJvK%|yi@EihhBj2)DsR{uTD3wbkQ<+t(~1G{(Y zP-085{m#aIOWjV`gF76N&rNb*d*ED~jAzi-UA6KMp@C@BoAo~nBA0AB8QzVyUs{M* z20tjtykFjN9lm&z;0l_EHom9tGsLL~-Aj$oOK9tY9M8p-Uo^i-zWUHCFlg)F(a)Gv`3IlzCv0OevISxDm;&?ZvRHGk=e|DF~i zKk_H>txomYfF-JM4K1`drI#h7|JE}0H9<2cTAn02BHrJ0?U6w*F)&TM!H0g+S46yj zzeveEe1!YnH@#8l^{4zSo1bu-XS(Ds5e&tuX70Naqqa8xzSS7+0eM{{aiYLq$rq?D zcIBgAbO9NvV78JPd=Os+LV~(UQKcMF_{9eV+$U;lcA>;cHZukYNDFp?l5L0Op-E40 ztfER+nRAZUiXoJ_<>GJLA5{LWmGEU!&zEtVrb903GL?7&Tp z0oM6&!-+pJ;N>G!aqk!AzxhKMQGc@ZbkaSt*PA)-68IV1HtwPI48aO}Buz%H2nKS5 zvc;+>;yYYE-nflQy@-jloiY70$)ENaM!!$6V6)gY1jjxqfL^KmDc0{=tn+5bNEE`+ zwwqdWli1y_N|N{o*j2tq_-&+I5v8|QD$2%vaVc{rj%oY8$v=}A+9?y)jO7t-P;jL??)%kYm zZHaqZBhu|&Vt_$h1~-E=)wlJ*Zfnp&fkj>xSR-TU=anGoeCU2X^tgK^xqBRd^zkH3 z)qLr}Py;O%IAEFm2O8}tJ$F#^h?H#_4ies`6q(=qFRJHFEII$QrQ8JDx*Od6+2!Z1 zIFar7JH$zv8k!I+`%jxtn6qf&?))P=1VUD2tJr0H&R5m#<3^=i3Z!o@4!K&`bV)ko zP_xZg#}2*---_^Whu+iZ*~>5Q{E~BLI0akLr1{^wP@LWv!81H(dN`-0!0ZG1mNDuu zfER}+etRjR!2IqXb>bb`x2ivjRRU(7k{J-6L-?EJld@kGR}l)N)9YK9UCaeA8z`Tp3RvLTlKQm9h8A3iHZ%E@#!~oMw zVb0uU7z{@eXflIl4jp>0@ycje_8#&PtNl%QbsjLp!8z^UaOjPxr5JvW3fR^h(#sN( zlNBe;F5=wIkxwU9_mCXcw-}gD!}Z57fheyR;lBm@|0K!Gn&tp#a?d-P_qRbz4X7|4 zFve5PbCj$bmV$dEvfAPFeWl3p`VZEa8x_j?cbM)RJcd$JT}8Nb@ySh{&bT6Z_ko1` z)qk)uqZ$a%wIW#m`Wl@4*2f{?4jY};c>DorcsTPsZFk>ir;(HZ9AI*@AWcbB?$N4J z0BsKdH~izKu%$72u+b2^iUTfkLUs`5X6R}`-wepXQ! zs#s#9D2KswTz|Xm~*}~jb}BdP#dVL zU(VaWtt>rZ8)0k1QkB!AAnCzjYztR#2NiKUWRwU?_V^au@4nic&@!dO z?At(QpOk~fj$(xw7GFHb3dBR`ks>LnM-)H_B6g15{g`mu+kB?`c#y2%dU!jC5Biix$#etRJ3-TB>6?lbXY;l4*Ci**^^ zd76iX+iNMp3s<>z+9pvDy?>JIw&x4xZcQ)3?IR^7hhn;TD;TjG_j1gg2LFX(68*=p zNblEIO-ua_lL4b(X70@ zGMHow{9_!k`SLa7$mM^o#P03pmg%*#^lG}5EayV)`(F?{er*FcZ#r>?pz>DBnVEnvCfn=ZJGPS-vw&ql(SIO2LdZ6;@0-voB%=O^gSWgg%lyIx#?K?kb%nx zPb27gcb8@kj<@d(Y=2}O-o6)FPBNVh-}$mKP$}xuk_L)5RY-QeAOkU(KWqh?|Df!%HR}*EnzID$lZY17gum2+%e{V(_LVY8JDXNT4JCp6_h@!m zTF@Pd8V~k1L!Sv7PGqqV(RCj?gRiYQ^)(oqm1M-3cui7?wO8Gb+w+MsDU6Z(-R~BY zty2QuhktPAby!L{N$JT>R|Z+Jhi(RbKvbpj8}xz9%`tbb6?7PSg9D{KK3A>dywrNT zz<6Qn^h1jqXelVD0wmC-=-lC|=z^#9bTQ?01I&b~=zEYMd815BVd80uTt;aVd(B

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z(fg(B?32B+NhhvM`PY*7U7D3;vvN!K?pqv@_PQ+fzHXm|n)lhepPOQ2>fGIFOR~C3 z>#Np%N;ZpiZv$EEPuYE@%JOL^t0hy-D$56b*$oCwjo!L4y+?|DA9!jRV(NaSWftK$ z?y32 { + return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + unit: + label: mm/month + type: gradient + min: "0" + max: "200" + stops: + - "#000004" + - "#3B0F70" + - "#8C2981" + - "#F37C21" + - "#FCFFA4" + - "#fc8d59" +--- + + + **Temporal Extent:** Jan 2003 to Dec 2021 (January 1979 to present available from the NASA GES DISC) + **Temporal Resolution:** Monthly-averaged (Hourly data available from the NASA GES DISC) + **Spatial Extent:** CONUS (25 to 53 North and -125 to -67 West) + **Spatial Resolution:** 0.125° x 0.125° + **Data type:** Research
+ + The precipitation from NLDAS-2 over CONUS is derived from a daily gridded precipitation analysis at 0.125-degrees from NOAA CPC. The data is temporally disaggregated to hourly using a variety of data sources, primarily radar-estimated precipitation amounts from Doppler Stage II data. Outside of CONUS, but still in the 25 to 53 North domain, different datasets are used to generate NLDAS-2 precipitation. See https://ldas.gsfc.nasa.gov/nldas/v2/forcing for details. + + ## Source Data Product Citation + - https://doi.org/10.5067/THUF4J1RLSYG NLDAS Primary Forcing Data L4 Monthly 0.125 x 0.125 degree V2.0, Edited by David M. Mocko, NASA/GSFC/HSL, Greenbelt, Maryland, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed:[Data Access Date], 10.5067/2DPKB5B5N14O + + ## Version History + V2.0 + +
+
+ + + ## Key Publications + Xia, Y., Mitchell, K., Ek, M., Sheffield, J., Cosgrove, B., Wood, E., Luo, L., Alonge, C., Wei, H., Meng, J., Livneh, B., Lettenmaier, D., Koren, V., Duan, Q., Mo, K., Fan, Y., Mocko, D., 2012. Continental-scale water and energy flux analysis and validation for the North American Land Data Assimilation System project phase 2 (NLDAS-2): 1. Intercomparison and application of model products: WATER AND ENERGY FLUX ANALYSIS. Journal of Geophysical Research: Atmospheres. Vol. 117, No. D3. https://doi.org/10.1029/2011JD016048 + + ## Learn More + - https://ldas.gsfc.nasa.gov/nldas/v2/forcing + - [Data Story: Mapping Water Availability over North America](https://deploy-preview-403--visex.netlify.app/stories/nldas) + + ## License + [Creative Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/legalcode) (CC BY 4.0) + + + diff --git a/datasets/nldas3.data.mdx b/datasets/nldas3.data.mdx new file mode 100644 index 000000000..9972451a5 --- /dev/null +++ b/datasets/nldas3.data.mdx @@ -0,0 +1,105 @@ +--- +id: nldas3 +name: "NLDAS-3 Precipitation Forcing Dataset" +description: "NASA is co-developing high-resolution retrospective and real-time data for water resources and agricultural applications" +media: + src: ::file ./nldas-cover.png + alt: Landsat 8 — OLI image of the Mississippi River below Memphis, Tennessee on September 16, 2023 at near record low water levels, limiting barge shipments, threatening drinking water supplies, agriculture, and ecosystems.y. + author: + name: LDAS-NASA + url: https://eoimages.gsfc.nasa.gov/images/imagerecords/151000/151897/mississippi_oli_2023259_lrg.jpg +taxonomy: + - name: Topics + values: + - Water Resources + - Hydrology + - Precipitation + - Surface Meteorology + - Drought + - Agriculture + - Disasters +layers: + - id: nldas3 + stacCol: nldas3 + name: Precipitation + type: raster + description: "Precipitation Dataset" + initialDatetime: newest + zoomExtent: + - 0 + - 20 + sourceParams: + colormap_name: magma + rescale: + - 0 + - 200 + nodata: 0 + compare: + datasetId: nldas3 + layerId: nldas3 + mapLabel: | + ::js ({dateFns, datetime, compareDatetime}) => { + return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + unit: + label: mm/month + type: gradient + min: "0" + max: "200" + stops: + - "#000004" + - "#3B0F70" + - "#8C2981" + - "#F37C21" + - "#FCFFA4" + - "#fc8d59" +--- + + + **Temporal Extent of sample NLDAS-3 data:** Jan 2001 to Dec 2021 + **Temporal Resolution of sample NLDAS-3 data:** Monthly + **Spatial Extent:** North and Central America (7-72 North, 169-52 West) + **Spatial Resolution:** 0.01° x 0.01° + **Data type:** Research
+ + This sample dataset presents a fine scale precipitation analysis from the development of NLDAS-3. NLDAS-3 is currently under development and the final product will include precipitation fields (included here) as well as other surface meteorology such as temperature, radiation, surface pressure, and wind speed. NLDAS-3 represents the next generation (i.e., phase 3) of the North American Land Data Assimilation System phase 2 (NLDAS-2). NLDAS-3 precipitation has been derived by assimilating daily precipitation amounts at 4 km of the NASA Integrated Multi-SatellitE Retrievals for Global Precipitation Measurements GPM (IMERG) and the Environment and Climate Change Canada (ECCC) Canadian Precipitation Analysis (CaPA) into the NASA’s Modern-Era Retrospective analysis for Research and Application, Version 2 (MERRA-2). NLDAS-3 precipitation at 4 km and daily time steps was then downscaled to 1 km using a cloud-cover based algorithm based on datasets from the Moderate Resolution Imaging Spectroradiometer (MODIS) then converted to hourly using a temporal disaggregation which employs MERRA-2 and IMERG datasets. NLDAS-3 covers North and Central America (from latitude 7 to 72 North and longitude 169 to 52 West) at a resolution of 0.01. The sample data available from this page are monthly-averages and an initial version of the still-in-development of the NLDAS-3 precipitation. + + ## Source Data Product Citation + Maina et al., (2024), NLDAS-3 surface meteorology 0.01 degree x 0.01 degree V1, Greenbelt, MD, USA, NASA Center for Climate Simulation (NCCS) DataPortal, Accessed: [Data Access Date] + + ## Version History + V2.0 + +
+
+ + + ## Key Publications + Maina et al., (2024), NLDAS-3 surface meteorology 0.01 degree x 0.01 degree V1, Greenbelt, MD, USA, NASA Center for Climate Simulation (NCCS) DataPortal, Accessed: July 24, 2024. + + Bratseth. (1986). Statistical interpolation by means of successive corrections - BRATSETH - 1986 - Tellus A - Wiley Online Library. Retrieved October 12, 2022, from https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1600-0870.1986.tb00476.x + + Cosgrove, B. A., Lohmann, D., Mitchell, K. E., Houser, P. R., Wood, E. F., Schaake, J. C., et al. (2003). Real-time and retrospective forcing in the North American Land Data Assimilation System (NLDAS) project. Journal of Geophysical Research: Atmospheres, 108(D22). https://doi.org/10.1029/2002JD003118 + + Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs, L., et al. (2017). The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). Journal of Climate, 30(14), 5419–5454. https://doi.org/10.1175/JCLI-D-16-0758.1 + + Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz‐Sabater, J., et al. (2020). The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146(730), 1999–2049. https://doi.org/10.1002/qj.3803 + + Huffman, G. J., Bolvin, D. T., & Nelkin, E. J. (2015). Integrated Multi-satellitE Retrievals for GPM (IMERG) technical documentation. NASA/GSFC Code, 612(2015), 47. + + Kemp, E. M., Wegiel, J. W., Kumar, S. V., Geiger, J. V., Mocko, D. M., Jacob, J. P., & Peters-Lidard, C. D. (2022). A NASA–Air Force Precipitation Analysis for Near-Real-Time Operations. Journal of Hydrometeorology, 23(6), 965–989. https://doi.org/10.1175/JHM-D-21-0228.1 + + Lespinas, F., Fortin, V., Roy, G., Rasmussen, P., & Stadnyk, T. (2015). Performance Evaluation of the Canadian Precipitation Analysis (CaPA). Journal of Hydrometeorology, 16(5), 2045–2064. https://doi.org/10.1175/JHM-D-14-0191.1 + + Maina et al., (2024), NLDAS-3 surface meteorology 0.01 degree x 0.01 degree V1, Greenbelt, MD, USA, NASA Center for Climate Simulation (NCCS) DataPortal, Accessed: July 24, 2024. + + ## Learn More + - https://ldas.gsfc.nasa.gov/nldas/v3 + - [Data Story: Mapping Water Availability over North America](https://deploy-preview-403--visex.netlify.app/stories/nldas) + + ## License + [Creative Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/legalcode) (CC BY 4.0) + + + diff --git a/stories/nldas-cover.png b/stories/nldas-cover.png new file mode 100644 index 0000000000000000000000000000000000000000..8e3e63467136234e726fd809409eee1417b9a6c4 GIT binary patch literal 604907 zcmZ_0Wl$YX@GXeDLvVKp?(XjH?yeUP?ykYz9fG?Df?wPr=)Jf@@cr%o?R!WDPD%p;0v-qf0S!ig{?GF(QcrPEQC^ar zmsDw@)92?WaH9KUd!`OzbPxi9970}7T+4U!Lf^5qjt?y%6rT=`CwuzkOVn${f1P%+ zUsF)~-n?TO0}cH!dRb>We=C?6EqZj{?fu-{6PxdU?651h|1n^9_W#E~?)fkNp9c@{ ze*^i9fF%FJ=qeWcUsQ3Q{}=E711Dwy{}25C@cuvWLo%!f)BlC|e02MNg8x5D|L?ip zgOOh6{Td@QJFsPYg&utiMM)fTyt4L!R@ZvrjV>~#o^^Dd0(UOa6h7bIYgfKnbn2Z) zH(i#a{4YL|N{yr2rUOj%de-;bELP{muJ5P<_Dm2T;ueifE?~VPa@N^SQ;B9ggr%fTE2wePi8g4 z(-(8N_Tfiv&OuFt2Wvs{MuJ~<`GNg2pSZKkqIqG%!CLqu!3#+TAG|9i!%d^=>oIKq`Fx?Fq@r^R@*?GDL6YMbg1CDr0Vgipl zu88<)EmW2tgdw4`j_g6iYd7sp2mb;qj7+hBi}aMnOPYj`EwiS*sn;>utfq_GZ{nc2 zDnMrF6ZUAk;UMavODY}iCEz&B13}cwwIGV=*0ANmo-ljwprfUDl7c{CXZTh#%31oi zAuxR)h5HW{U?!UIjRqsVh(z9dnY0}9aeaWBcq_=swc42Df>s8UoLb*>R3>zhu812< z^Ew*zT_3I6M_O{9clp#R-mh@~DaXkoGx}SD7kB#$NHG%GdHtRq)WHCc%QE7kvjw;| zklf4AYcl0B`U=v zCfJXm4o5Bhn+`Wl_~V<=kZ1I1#$yg>yJkH=*y=hAEP(m>tRI-Bu8r#%x|-d*=wCoQ zCCx2-t4UnF+}UkU+k%Ei^mEn#YI=GKK<^7Leqe!x%(5bF(3B&Il5W0a#X5R+0qG8} z`gewl#e$}`J))pc0_%Nu=o%0lO9}*gZru zJvK%|yi@EihhBj2)DsR{uTD3wbkQ<+t(~1G{(Y zP-085{m#aIOWjV`gF76N&rNb*d*ED~jAzi-UA6KMp@C@BoAo~nBA0AB8QzVyUs{M* z20tjtykFjN9lm&z;0l_EHom9tGsLL~-Aj$oOK9tY9M8p-Uo^i-zWUHCFlg)F(a)Gv`3IlzCv0OevISxDm;&?ZvRHGk=e|DF~i zKk_H>txomYfF-JM4K1`drI#h7|JE}0H9<2cTAn02BHrJ0?U6w*F)&TM!H0g+S46yj zzeveEe1!YnH@#8l^{4zSo1bu-XS(Ds5e&tuX70Naqqa8xzSS7+0eM{{aiYLq$rq?D zcIBgAbO9NvV78JPd=Os+LV~(UQKcMF_{9eV+$U;lcA>;cHZukYNDFp?l5L0Op-E40 ztfER+nRAZUiXoJ_<>GJLA5{LWmGEU!&zEtVrb903GL?7&Tp z0oM6&!-+pJ;N>G!aqk!AzxhKMQGc@ZbkaSt*PA)-68IV1HtwPI48aO}Buz%H2nKS5 zvc;+>;yYYE-nflQy@-jloiY70$)ENaM!!$6V6)gY1jjxqfL^KmDc0{=tn+5bNEE`+ zwwqdWli1y_N|N{o*j2tq_-&+I5v8|QD$2%vaVc{rj%oY8$v=}A+9?y)jO7t-P;jL??)%kYm zZHaqZBhu|&Vt_$h1~-E=)wlJ*Zfnp&fkj>xSR-TU=anGoeCU2X^tgK^xqBRd^zkH3 z)qLr}Py;O%IAEFm2O8}tJ$F#^h?H#_4ies`6q(=qFRJHFEII$QrQ8JDx*Od6+2!Z1 zIFar7JH$zv8k!I+`%jxtn6qf&?))P=1VUD2tJr0H&R5m#<3^=i3Z!o@4!K&`bV)ko zP_xZg#}2*---_^Whu+iZ*~>5Q{E~BLI0akLr1{^wP@LWv!81H(dN`-0!0ZG1mNDuu zfER}+etRjR!2IqXb>bb`x2ivjRRU(7k{J-6L-?EJld@kGR}l)N)9YK9UCaeA8z`Tp3RvLTlKQm9h8A3iHZ%E@#!~oMw zVb0uU7z{@eXflIl4jp>0@ycje_8#&PtNl%QbsjLp!8z^UaOjPxr5JvW3fR^h(#sN( zlNBe;F5=wIkxwU9_mCXcw-}gD!}Z57fheyR;lBm@|0K!Gn&tp#a?d-P_qRbz4X7|4 zFve5PbCj$bmV$dEvfAPFeWl3p`VZEa8x_j?cbM)RJcd$JT}8Nb@ySh{&bT6Z_ko1` z)qk)uqZ$a%wIW#m`Wl@4*2f{?4jY};c>DorcsTPsZFk>ir;(HZ9AI*@AWcbB?$N4J z0BsKdH~izKu%$72u+b2^iUTfkLUs`5X6R}`-wepXQ! zs#s#9D2KswTz|Xm~*}~jb}BdP#dVL zU(VaWtt>rZ8)0k1QkB!AAnCzjYztR#2NiKUWRwU?_V^au@4nic&@!dO z?At(QpOk~fj$(xw7GFHb3dBR`ks>LnM-)H_B6g15{g`mu+kB?`c#y2%dU!jC5Biix$#etRJ3-TB>6?lbXY;l4*Ci**^^ zd76iX+iNMp3s<>z+9pvDy?>JIw&x4xZcQ)3?IR^7hhn;TD;TjG_j1gg2LFX(68*=p zNblEIO-ua_lL4b(X70@ zGMHow{9_!k`SLa7$mM^o#P03pmg%*#^lG}5EayV)`(F?{er*FcZ#r>?pz>DBnVEnvCfn=ZJGPS-vw&ql(SIO2LdZ6;@0-voB%=O^gSWgg%lyIx#?K?kb%nx zPb27gcb8@kj<@d(Y=2}O-o6)FPBNVh-}$mKP$}xuk_L)5RY-QeAOkU(KWqh?|Df!%HR}*EnzID$lZY17gum2+%e{V(_LVY8JDXNT4JCp6_h@!m zTF@Pd8V~k1L!Sv7PGqqV(RCj?gRiYQ^)(oqm1M-3cui7?wO8Gb+w+MsDU6Z(-R~BY zty2QuhktPAby!L{N$JT>R|Z+Jhi(RbKvbpj8}xz9%`tbb6?7PSg9D{KK3A>dywrNT zz<6Qn^h1jqXelVD0wmC-=-lC|=z^#9bTQ?01I&b~=zEYMd815BVd80uTt;aVd(B

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z?4H`H$jXj9^=OEaXujn?DGoX6bS05Yf4$dImHUd-Y1r$iXyw<^lk?`z&#oXDN&o6? zz185D@hQ?KtuhTVX{i6Yz(@DjeZ@1cNiuo?2epN4s^A z>Ekyo5>AJO6xeLJrlUmb!`I3`@QO?dyiO73^j5KvHGv8B>V;iQl_qaX_GZzaHD3O? zU_mAUs{(6TYBPmb{1abue_MV&Jyxv%v)Wd;9Tj~;BfM%fRaaH!_}6-SJb5l^0422y zy^Xn1|0@+ZI5I8%E|H%x@YP<$m}sEN=PgRV@9W4a$$Nexf$9%zRnzJA%7=!kvc>jx z?52~?*|KcD6f&&GOnto74IGd@u6MFEKK;Q^68aL~qPah?#?p;_vM?}fl7j~s5G8-E zIoVj|y|8E0F@5{eje{0p5#Ultb5F8>$UFM^^ut*pUJ-L9RrVrdcj@lEY3jpTH_3PW z*mZ#1d>VJo=SvKIgZt|1x`S-BJ0aXgYJ5N7;POU_q zvT^Sr)CbB}maws)tmI#;&B4gWiOZfcqJU+Om4VsBy6yOHB#XNv4G!a*Euo@NT2#>? zE}?8vSu_e+lCS-Eb^0OlMh8?{nvu971LFFkk4P;Sc4p&*%0u5RN`S6lach z-^8Pb?|4r8c-US*FR0swnSl?5 z^C}h`xJsg_E51X{kNo)iMlNO)avV7pPuSEW;c_jEMPM5&V__wxQ>0Evk{OiE;MYw6lxc5c+?6<6LvK z`|r8e#qH0&`riKff9qZK18heOp5G{`Oa4Bef41TGpZ^N$Hq}4>=;Jfr^7#DA<-aVC zFUa{|GOzb>&2~Fsh?j4u0_(l9mwDe}VLkwrFVG$ge&&Nag22Ffmlr7x9W2GK99nci zjNa`6oJ7*Qdv>2Uk(MEJ&#?x&_}pFH*G;gF7SZ-5Ob3nbF5P{zypvc@!tE_~2fBFY z?$p=%f0Hc^hdk^dcb|&86xw}cvf<&DTEM=X* z8Zma)?Aqx>dlD837UiI6r`^%lSlvl>u^uoBZ1*nT{9XuJf)Jmsp7$N7XE=AueBRXd R9n% + + **Authors**: David Mocko, Fadji Maina, Kim Locke, Sujay Kumar, Kristen Whitney, Rishi Anand, Siddharth Chaudhary, Chris Hain + + ## The North American Land Data Assimilation System (NLDAS) + NLDAS is a widely used land modeling environment that generates estimates of land surface fluxes and states such as soil moisture, snow, and streamflow. These estimates are critical for drought and flood monitoring, water availability and water resource management, climate assessments, and other uses. For instance, the University of Nebraska-Lincoln’s [National Drought Mitigation Center](https://drought.unl.edu/) (NDMC) relies on NLDAS data for their drought assessments published weekly in the [U.S. Drought Monitor](https://www.drought.gov/data-maps-tools/us-drought-monitor). Applications like [OpenET](https://etdata.org/) and [QuickDRI](https://quickdri.unl.edu/) also rely on the quality of NLDAS meteorological forcing and model outputs. The phase 2 of NLDAS (NLDAS-2) is currently operational at NOAA, with long-term archives of data back to Jan 1979 available from NASA. +

+ + + NASA 2023 stakeholder workshop participant responses to the question, “How do you use NLDAS?” + +
+ + + + + + ## Community-Centered Model Development + Building on stakeholder feedback and advancements in Earth observations and data assimilation, teams across NASA are working on major enhancements to the NLDAS environment called “NLDAS Phase 3” (NLDAS-3). The vision for NLDAS-3 is to provide near field scale (~1 km), high quality, observation-informed estimates of land surface and hydrology conditions. Specifically, NLDAS-3 aims to: + - Improve the spatial resolution by providing meteorological forcing and land-surface model output at 1-km resolution; + - Expand the spatial coverage to encompass all of North and Central America, including Alaska, Hawaii, and Puerto Rico (see figures below); + - Utilize high quality surface meteorological data; + - Reduce the current NLDAS-2 latency of 3.5 days to near real-time; + - Upgrade the land surface model to include the latest scientific advancements, such as improved representation of groundwater processes (He et al., 2023); and + - Incorporate observational constraints by assimilating remote sensing datasets, which can help capture human management of water and vegetation, such as irrigation, groundwater withdrawal, droughts, floods, and hydrological impacts of wildland fire and other disturbances + +
+ + + Spatial domain of NLDAS-2 (CONUS) vs. NLDAS-3 (North and Central America). + +
+ + **Summary of NLDAS-3 improvements** +
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
AttributeNLDAS-2NLDAS-3
Spatial CoverageCONUS (25-53 North / 125-67 West)North America including Alaska, Hawaii, Puerto Rico and Central America (7-72 North / 169-52 West)
Spatial resolution12.5-km1.0-km
Latency~4 days~7 hours
PrecipitationCDC daily 12.5-km analysis over CONUSAssimilation using gauges, CaPA, IMERG, with MERRA-2/GEOS-IT as background
Surface meteorologyNARR with constant lapse rate adjustmentsMERRA-2/GEOS-IT with advanced downscaling
Land Surface Modeling4 (Noah, VIC, Mosaic, SAC)1 (Noah-MP)
Data assimilationNoneAssimilation of remotely sensed datasets of soil moisture (e.g., SMAP), leaf area index (e.g., MODIS), snow (e.g., AMSR), terrestrial water storage (GRACE-FO)
+
+
+ + To make these improvements, science and modeling teams across NASA centers are using the open source NASA Land Information System (LIS) framework (Kumar et al., 2006; Peters-Lidard et al., 2007), a state-of-the-art software suite for high performance terrestrial hydrology modeling and data assimilation. LIS software is open-source and available at [GitHub](https://github.com/NASA-LIS/LISF). +
+ + +
+
+
+ + + + ## Precipitation Data Updates + NASA is updating NLDAS precipitation by leveraging NASA’s reanalysis and remote sensing data products. Specifically, we are working on a new data assimilation approach used successfully in operational environments as well as advanced optimal interpolation techniques (Kemp et al. 2022) to blend well-known and widely used precipitation datasets. Daily precipitation amounts at 4 km of the NASA Integrated Multi-SatellitE Retrievals for GPM (IMERG; Huffman et al. 2020) and the ECCC Canadian Precipitation Analysis (CaPA; Lespinas et al. 2015) are assimilated into NASA Modern Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2; Gelaro et al. 2017) precipitation data. Then the precipitation analysis at 4 km is downscaled to a 1 km fine-scale resolution using a cloud cover frequency-based algorithm and disaggregated into hourly using IMERG and MERRA-2 datasets. Below are examples of NLDAS-2 and NLDAS-3 precipitation data over North America to illustrate improved spatial resolution of NLDAS-3 data. + + + +
+ + + + NLDAS-2 precipitation outputs for August 2017 and 2020. +
+
+ +
+ + + NLDAS-3 sample precipitation outputs for August 2017 and 2020. + +
+
+ + + + ## Data Browser + Users are encouraged to further examine the NLDAS-2 and sample NLDAS-3 precipitation using the following two data catalogs links. They contain monthly-averaged precipitation from both products for a ~20-year period. Click on “Explore Data” in the upper right of these two data catalogs. + - [NLDAS-2](https://deploy-preview-403--visex.netlify.app/data-catalog/nldas2) + - [NLDAS-3](https://deploy-preview-403--visex.netlify.app/data-catalog/nldas3) + + + + + + ## Explore the Data in the Cloud + Below are links to sample monthly precipitation forcing data in Jupyter Notebooks for you to further explore and examine NLDAS-2 and the sample NLDAS-3 data. + - [Notebook 1](https://nasa-impact.github.io/veda-docs/pr-preview/pr-154/notebooks/datasets/nldas_visualize_rawdata.html) shows how to visualize NLDAS-3 data. + - [Notebook 2](https://nasa-impact.github.io/veda-docs/pr-preview/pr-154/notebooks/datasets/nldas_time_series.html) shows you how to create time series for NLDAS-3 data. + - [Notebook 3](https://nasa-impact.github.io/veda-docs/pr-preview/pr-154/notebooks/datasets/nldas_compare2_3.html) shows you how to compare NLDAS-2 and NLDAS-3 data. + + + + + + + ## Surface Meteorology Data Updates + The other NLDAS-3 meteorological forcings are obtained by downscaling MERRA-2 datasets (except for Shortwave Down radiation, which will use CERES/POWER data) using the methods as follows: + +
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Meteorological VariableDownscaling Method
Surface PressureElevation-based following Cosgrove et al., 2003
Longwave Down RadiationElevation-based following Cosgrove et al., 2003
Air TemperatureDynamic lapse rate bias correction, following Rouf et al., 2020
Air HumidityAdjusted to be consistent after the Air Temperature adjustment
Wind SpeedMicroMet methodology following Liston & Elder, 2006
Shortwave Down RadiationSlope-aspect corrections of CERES/POWER data from Rutan et al., 2015
+
+
+
+
+ + + + ## Land surface model and Data Assimilation Updates + NLDAS-3 will employ the Noah-MP land surface model shown below (He et al., 2023) and implemented within LIS. +
+ + + +
+ Schematic diagrams of energy and water budgets and processes represented in Noah-MP version 5.0. + + **Integrating remote sensing data is crucial for accurately depicting the influence of human activities on the land surface, such as agricultural irrigation, groundwater extraction, reservoir management, and wildfires.** To better detect these impacts, we are working to assimilate the following NASA satellite data products in NLDAS-3: + +
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Land Surface VariableRemote Sensing Platform
Soil MoistureSMAP, AMSR-E, AMSR-2
SnowAMSR-E, AMSR-2, MODIS
Leaf Area IndexMODIS/VIIRS
Terrestrial Water StorageGRACE/GRACE-FO
Radar Altimetry Water LevelSWOT
+
+
+ + + The multivariate assimilation (also known as reanalysis) will produce land (e.g., vegetation states, evapotranspiration, snow dynamics) and hydrologic (soil moisture, groundwater and surface water storage) variables listed below at a spatial resolution of 1 km. + +
+
+ + + + + + + + + + + + + + + + + + + + + + + + + +
CategoryVariables
Energy fluxes and statesLatent heat flux, sensible heat flux, ground heat flux
Surface state variablesSnow water equivalent, snow depth, snow cover, skin temperature, albedo, evapotranspiration, leaf area index
Carbon variablesGross primary production, net primary production
Soil and subsurface state hydrologic variablesSoil moisture, terrestrial water storage, groundwater storage, water table depth, surface runoff, subsurface runoff, streamflow
+
+
+ + + Data will be provided in netCDF-4 format through NASA’s open source cloud environments. Based on the needs of the stakeholder community, a collection of selected variables will also be made available in cloud-optimized GEOTIFF and GIS-based formats, among others. + +
+
+ + + + ## Provide Your Feedback + What information on water availability and land surface meteorology do you need from NLDAS-3? Here are recent requests for downstream products and applications from the community: + - Soil moisture percentiles and outlooks + - Drought percentiles, indices and forecasts + - ET and PET products + - Soil hydrologic conductivity + - Modeled ET and runoff + - GIS-enabled data + - Weekly change maps + - Model uncertainty information + + NASA model developers are collecting feedback via our NLDAS GitHub discussion page [here](https://github.com/Earth-Information-System/NLDAS-3/discussions) and with periodic stakeholder workshops. Please join the NASA NLDAS community and help us create the next state-of-the-art land surface and hydrology model! + + + + + + ## Learn More + - [NASA NLDAS-3 Website](https://ldas.gsfc.nasa.gov/nldas/v3) + - [NASA NLDAS-3 GitHub Discussions Page](https://github.com/Earth-Information-System/NLDAS-3/discussions) + ## Acknowledgements + Thanks to the NLDAS-3 developers and science teams at the NASA Goddard Hydrological Sciences Laboratory and Marshall Space Flight Center SPoRT and all the NLDAS stakeholders who have participated in workshops, provided valuable feedback, and developed downstream applications for assessing water availability. + + + + + + ## References + - ​https://lis.gsfc.nasa.gov/ + - Cosgrove, B.A., Lohmann, D., Mitchell, K.E., Houser, P.R., Wood, E.F., Schaake, J.C., Robock, A., Marshall, C., Sheffield, J., Duan, Q., Luo, L., Higgins, R.W., Pinker, R.T., Tarpley, J.D., Meng, J., 2003. Real-time and retrospective forcing in the North American Land Data Assimilation System (NLDAS) project. Journal of Geophysical Research: Atmospheres 108. https://doi.org/10.1029/2002JD003118 + - Gelaro, R., McCarty, W., Suárez, M.J., Todling, R., Molod, A., Takacs, L., Randles, C.A., Darmenov, A., Bosilovich, M.G., Reichle, R., Wargan, K., Coy, L., Cullather, R., Draper, C., Akella, S., Buchard, V., Conaty, A., Silva, A.M. da, Gu, W., Kim, G.-K., Koster, R., Lucchesi, R., Merkova, D., Nielsen, J.E., Partyka, G., Pawson, S., Putman, W., Rienecker, M., Schubert, S.D., Sienkiewicz, M., Zhao, B., 2017. The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). Journal of Climate 30, 5419–5454. https://doi.org/10.1175/JCLI-D-16-0758.1 + - He, C., Valayamkunnath, P., Barlage, M., Chen, F., Gochis, D., Cabell, R., Schneider, T., Rasmussen, R., Niu, G.-Y., Yang, Z.-L., Niyogi, D., Ek, M., 2023. Modernizing the open-source community Noah with multi-parameterization options (Noah-MP) land surface model (version 5.0) with enhanced modularity, interoperability, and applicability. Geoscientific Model Development 16, 5131–5151. https://doi.org/10.5194/gmd-16-5131-2023 + - Kemp, E.M., Wegiel, J.W., Kumar, S.V., Geiger, J.V., Mocko, D.M., Jacob, J.P., Peters-Lidard, C.D., 2022. A NASA–Air Force Precipitation Analysis for Near-Real-Time Operations. Journal of Hydrometeorology 23, 965–989. https://doi.org/10.1175/JHM-D-21-0228.1 + - Kumar, S.V., Peters-Lidard, C.D., Tian, Y., Houser, P.R., Geiger, J., Olden, S., Lighty, L., Eastman, J.L., Doty, B., Dirmeyer, P., Adams, J., Mitchell, K., Wood, E.F., Sheffield, J., 2006. Land information system: An interoperable framework for high resolution land surface modeling. Environmental Modelling & Software 21, 1402–1415. https://doi.org/10.1016/j.envsoft.2005.07.004 + - Liston, G.E., Elder, K., 2006. A Meteorological Distribution System for High-Resolution Terrestrial Modeling (MicroMet). https://doi.org/10.1175/JHM486.1 + - Peters-Lidard, C.D., Houser, P.R., Tian, Y., Kumar, S.V., Geiger, J., Olden, S., Lighty, L., Doty, B., Dirmeyer, P., Adams, J., Mitchell, K., Wood, E.F., Sheffield, J., 2007. High-performance Earth system modeling with NASA/GSFC’s Land Information System. Innovations Syst Softw Eng 3, 157–165. https://doi.org/10.1007/s11334-007-0028-x + - Rouf, T., Mei, Y., Maggioni, V., Houser, P., Noonan, M., 2020. A Physically Based Atmospheric Variables Downscaling Technique. Journal of Hydrometeorology 21, 93–108. https://doi.org/10.1175/JHM-D-19-0109.1 + - Rutan, D.A., Kato, S., Doelling, D.R., Rose, F.G., Nguyen, L.T., Caldwell, T.E., Loeb, N.G., 2015. 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- -
- - - NLDAS-3 sample precipitation outputs for August 2017 and 2020. - -
-
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zlbvT^A1~HTTi7_3gy=XM69{}$2)mr#qUd0AiKySzAt~zO4R}Zed@dWdM}!+Z2ZOPj5 zBz_j|Tm{!FHIxH;D3)I(ST!FP*~zRAWKI!)!fumBx9>v`!U}8Plp!`2jpR~!RY^2Wd;-} z@RB5=#%P_UHU4S7CN$uY@;A4*|Cp!ntm!Z<1khi~dPjfteef6S1UaM3&5+WphEVVk PfFCWj>#8r6twR3~k#vdl literal 0 HcmV?d00001 diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index f51afda11..ef7be7bed 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -113,13 +113,23 @@ taxonomy: ## Monitoring air pollution with satellites Collecting measurements of sulfur dioxide plumes from space is a valuable way to monitor changes in emissions. +
+ + + Damage to a portion of Fort Myers Beach. Credit to Kevin Fogarty - REUTERS. + +
+
From 3a9936acbcded069ef9efbd24a39b54f936cbb30 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Mon, 16 Sep 2024 14:58:29 -0500 Subject: [PATCH 108/152] sr_v6 --- stories/black-belt-climate-ej.stories.mdx | 23 ++++++++++++++++------- 1 file changed, 16 insertions(+), 7 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index ef7be7bed..05f023e69 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -103,6 +103,7 @@ taxonomy:
+{/*

@@ -110,29 +111,37 @@ taxonomy:

+*/} - ## Monitoring air pollution with satellites - Collecting measurements of sulfur dioxide plumes from space is a valuable way to monitor changes in emissions. + ## Climate Extremes in the Black Belt Region + Alabama's Black Belt counties face escalating climate challenges. MERRA-2 data from 1980 to 2023 reveals significant shifts in temperature extremes. The region is experiencing an increase in warm days and nights (TX90P, TN90P) and a decrease in cool days and nights (TX10P, TN10P). These changes pose particular risks for the area's agricultural workforce and older residents, highlighting the growing impact of climate change on the region. + + + + ## Choctaw County
- - Damage to a portion of Fort Myers Beach. Credit to Kevin Fogarty - REUTERS.
-
-
+ From 19bfe5f96360ed1b2e81527a13f3d9ed83dd8bb4 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Mon, 16 Sep 2024 15:01:16 -0500 Subject: [PATCH 109/152] st_v7 --- stories/black-belt-climate-ej.stories.mdx | 2 -- 1 file changed, 2 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 05f023e69..30ca00f5c 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -136,8 +136,6 @@ taxonomy:
-
From d62d92a6aa9fc2b92e1d1570fc70509a309a0479 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Mon, 16 Sep 2024 15:07:10 -0500 Subject: [PATCH 110/152] st_v8 --- stories/black-belt-climate-ej.stories.mdx | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 30ca00f5c..48cd7f72d 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -136,6 +136,10 @@ taxonomy:
+ + Significant Trends in Climate Extremes from MERRA-2 (1980-2023): Slope Analysis (p < 0.1) +
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+ + + Significant Trends in Climate Extremes from MERRA-2 (1980-2023): Slope Analysis (p < 0.1) + +
+ + ## Choctaw County +
+ + + Significant Trends in Climate Extremes from MERRA-2 (1980-2023): Slope Analysis (p < 0.1) + +
+ + + ## Choctaw County +
+ + + Significant Trends in Climate Extremes from MERRA-2 (1980-2023): Slope Analysis (p < 0.1) + +
+ + + + + +{/* +*/} +{/* +*/} From 5b381cef42512e831ab7f5bd990c0bacbd1b89cf Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Mon, 16 Sep 2024 16:52:19 -0500 Subject: [PATCH 112/152] st_v9 --- stories/black-belt-climate-ej.stories.mdx | 31 ++++++++++++++++++----- 1 file changed, 25 insertions(+), 6 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index d73b304e8..4f7323eb4 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -143,7 +143,14 @@ taxonomy:
- ## Choctaw County + + ## Butler County
- - ## Choctaw County + + ## Pickens County
- ## Choctaw County + + ## Marengo County
+ - - {/* From 14f7f2c5b2a9abf2372e5ea40f3afeba59c894fb Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Mon, 16 Sep 2024 17:09:23 -0500 Subject: [PATCH 113/152] ST_V9 --- stories/black-belt-climate-ej.stories.mdx | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 4f7323eb4..dc9ce96e5 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -116,7 +116,7 @@ taxonomy:
+ Date: Tue, 17 Sep 2024 12:33:20 -0500 Subject: [PATCH 114/152] st_10 --- stories/black-belt-climate-ej.stories.mdx | 17 ++++++++++------- stories/census_bureua_Butler.csv | 10 ++++++++++ 2 files changed, 20 insertions(+), 7 deletions(-) create mode 100644 stories/census_bureua_Butler.csv diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index dc9ce96e5..7159aab33 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -116,7 +116,7 @@ taxonomy: -
- -
+
diff --git a/stories/census_bureua_Butler.csv b/stories/census_bureua_Butler.csv new file mode 100644 index 000000000..d318e9a6f --- /dev/null +++ b/stories/census_bureua_Butler.csv @@ -0,0 +1,10 @@ +index,GEO_ID,NAME,NAICS2012,SECTOR,INDLEVEL,INDGROUP,SUBSECTOR,NAICS2012_LABEL,LFO,LFO_LABEL,EMPSZES,EMPSZES_LABEL,YEAR,ESTAB,EMP,EMP_N,PAYQTR1,PAYQTR1_N,PAYANN,PAYANN_N,Unnamed: 20,NAICS2017,NAICS2017_LABEL,Unnamed: 16,EMP_numeric +2700,0500000US01013,"Butler County, Alabama",11,11.0,2.0,,,"Agriculture, forestry, fishing and hunting",1,All establishments,1,All establishments,2012-01-01,19,144,G,1262,G,5575,G,,,,,144.0 +2720,0500000US01013,"Butler County, Alabama",23,23.0,2.0,,,Construction,1,All establishments,1,All establishments,2012-01-01,29,195,G,1881,H,9213,H,,,,,195.0 +2760,0500000US01013,"Butler County, Alabama",48-49,48.0,2.0,,,Transportation and warehousing,1,All establishments,1,All establishments,2012-01-01,9,270,H,2171,H,10235,H,,,,,270.0 +2710,0500000US01013,"Butler County, Alabama",11,11.0,2.0,,,"Agriculture, forestry, fishing and hunting",1,All establishments,1,All establishments,2014-01-01,20,100 to 249 employees,S,1932,H,8364,H,,,,,174.5 +2730,0500000US01013,"Butler County, Alabama",23,23.0,2.0,,,Construction,1,All establishments,1,All establishments,2014-01-01,29,254,G,2556,H,14636,H,,,,,254.0 +2770,0500000US01013,"Butler County, Alabama",48-49,48.0,2.0,,,Transportation and warehousing,1,All establishments,1,All establishments,2014-01-01,9,339,H,2899,H,12262,H,,,,,339.0 +2670,0500000US01013,"Butler County, Alabama",11,11.0,2.0,,,"Agriculture, forestry, fishing and hunting",1,All establishments,1,All establishments,2016-01-01,20,230,H,1978,H,7972,G,,,,,230.0 +2690,0500000US01013,"Butler County, Alabama",23,23.0,2.0,,,Construction,1,All establishments,1,All establishments,2016-01-01,26,276,H,3402,H,15743,H,,,,,276.0 +2730,0500000US01013,"Butler County, Alabama",48-49,48.0,2.0,,,Transportation and warehousing,1,All establishments,1,All 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100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -259,15 +259,12 @@ taxonomy: Additionally, outdoor occupations such as transportation and construction have become crucial sources of income and have shown growth over the past few years. Data from the U.S. Census Bureau, which examines the number of establishments by employment category in counties like Choctaw and Butler, underscores the economic importance of these sectors.

- +
+ +
From 6a6b2ae0fea59ccf8f5b7ee31551853e8f31e166 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 17 Sep 2024 13:13:19 -0500 Subject: [PATCH 116/152] v11 --- stories/black-belt-climate-ej.stories.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index c9ece6f87..edf1fabae 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -247,7 +247,7 @@ taxonomy:
From 0c8b9431e7a99077c99e966fc19e7bb66cb1313e Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 17 Sep 2024 14:45:07 -0500 Subject: [PATCH 117/152] fig_v1 --- stories/black-belt-climate-ej.stories.mdx | 8 +------- 1 file changed, 1 insertion(+), 7 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index edf1fabae..9e77e209e 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -247,7 +247,7 @@ taxonomy:
@@ -259,12 +259,6 @@ taxonomy: Additionally, outdoor occupations such as transportation and construction have become crucial sources of income and have shown growth over the past few years. Data from the U.S. Census Bureau, which examines the number of establishments by employment category in counties like Choctaw and Butler, underscores the economic importance of these sectors.

-
- -
From 2998d18580a44c9802c1f2b373741a660ca4fad2 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 17 Sep 2024 14:58:30 -0500 Subject: [PATCH 118/152] st_v4 --- stories/black-belt-climate-ej.stories.mdx | 21 +++++++++++++++++++++ stories/camp-fire-burn-scar.stories.mdx | 10 +++------- 2 files changed, 24 insertions(+), 7 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 9e77e209e..f3f41aea5 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -253,12 +253,33 @@ taxonomy:

+ +
+ + + Monthly-averaged MODIS-derived NDVI values over the Camp Fire domain from 2002 to 2022. The highlighted portion of the time series indicates when the Camp Fire was active. + +
+
+

Additionally, outdoor occupations such as transportation and construction have become crucial sources of income and have shown growth over the past few years. Data from the U.S. Census Bureau, which examines the number of establishments by employment category in counties like Choctaw and Butler, underscores the economic importance of these sectors.

+
+ +
diff --git a/stories/camp-fire-burn-scar.stories.mdx b/stories/camp-fire-burn-scar.stories.mdx index fdb1bee03..90045e2a9 100644 --- a/stories/camp-fire-burn-scar.stories.mdx +++ b/stories/camp-fire-burn-scar.stories.mdx @@ -130,13 +130,9 @@ taxonomy: Monthly-averaged MODIS-derived NDVI values over the Camp Fire domain from 2002 to 2022. The highlighted portion of the time series indicates when the Camp Fire was active. From bb4808f6e1e140d89827e96eac9aff8ca53bd353 Mon Sep 17 00:00:00 2001 From: mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Tue, 17 Sep 2024 15:04:17 -0500 Subject: [PATCH 119/152] st_v4 --- stories/black-belt-climate-ej.stories.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index f3f41aea5..b7b5d2ce5 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -257,7 +257,7 @@ taxonomy:
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- -
- - - Monthly-averaged MODIS-derived NDVI values over the Camp Fire domain from 2002 to 2022. The highlighted portion of the time series indicates when the Camp Fire was active. - -
-
@@ -276,7 +262,7 @@ taxonomy:
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mahineelam <152424185+mahineelam@users.noreply.github.com> Date: Wed, 18 Sep 2024 09:12:04 -0500 Subject: [PATCH 122/152] fig --- stories/black-belt-climate-ej.stories.mdx | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index f43ead7ab..977efb0b8 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -245,10 +245,10 @@ taxonomy: Agriculture remains the backbone of the Black Belt's economy, with many older adults working in the fields. This reliance on an aging workforce is concerning, particularly as the physical demands of farming intensify with rising temperatures. In Sumter County, the number of farm operators aged 55 and above is increasing, reflecting a broader national trend where the average age of U.S. farm producers has risen to 58.1 years by 2022.

-
+
@@ -260,10 +260,10 @@ taxonomy: Additionally, outdoor occupations such as transportation and construction have become crucial sources of income and have shown growth over the past few years. Data from the U.S. Census Bureau, which examines the number of establishments by employment category in counties like Choctaw and Butler, underscores the economic importance of these sectors.

-
+
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Available at seven soil layer depths." +media: + src: ::file ./soil-texture-background.jpeg + alt: Examples of two different soil types + author: + name: Soil Sensor + url: https://soilsensor.com/articles/soil-textures/ +taxonomy: + - name: Topics + values: + - Agriculture + - Land Cover + - name: Source + values: + - ISRIC +layers: + - id: soil-texture-0cm + stacCol: soil-texture-0cm + name: Soil Texture at the Surface (0 cm) + type: raster + description: 'ISRIC Soil Texture Classification at 0 cm' + zoomExtent: + - 0 + - 20 + sourceParams: + colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", + "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF}' + nodata: 0 + rescale: + - 1 + - 12 + legend: + type: categorical + min: "1" + max: "12" + stops: + - color: "#F89E61" + label: "Clay" + - color: "#BA8560" + label: "Silty Clay" + - color: "#D8D2B4" + label: "Sandy Clay" + - color: "#AE734C" + label: "Clay Loam" + - color: "#9E8478" + label: "Silty Clay Loam" + - color: "#C6A365" + label: "Sandy Clay Loam" + - color: "#B4A67D" + label: "Loam" + - color: "#E1D4C4" + label: "Silty Loam" + - color: "#BEB56D" + label: "Sandy Loam" + - color: "#777C7A" + label: "Silt" + - color: "#A89B6F" + label: "Loamy Sand" + - color: "#E9E2AF" + label: "Sand" + info: + source: ISRIC + spatialExtent: Global + temporalResolution: Annual + unit: N/A + +--- + + + +x + + From 6e6cc18742e781cb510a62659f4c73df1803254b Mon Sep 17 00:00:00 2001 From: Andrew Blackford <62357205+acblackford@users.noreply.github.com> Date: Wed, 18 Sep 2024 10:03:27 -0500 Subject: [PATCH 124/152] fixed bad indent --- datasets/soil-texture.data.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/datasets/soil-texture.data.mdx b/datasets/soil-texture.data.mdx index 291bb6aea..f41769280 100644 --- a/datasets/soil-texture.data.mdx +++ b/datasets/soil-texture.data.mdx @@ -25,7 +25,7 @@ layers: zoomExtent: - 0 - 20 - sourceParams: + sourceParams: colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF}' nodata: 0 From cdda660c82438fab9a4e293aa10bac73420d85b7 Mon Sep 17 00:00:00 2001 From: Andrew Blackford <62357205+acblackford@users.noreply.github.com> Date: Wed, 18 Sep 2024 10:08:05 -0500 Subject: [PATCH 125/152] changing env to staging for checking soil texture data --- .env | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.env b/.env index 0aeb58068..095a452ab 100644 --- a/.env +++ b/.env @@ -8,10 +8,10 @@ APP_DESCRIPTION=Visualization, Exploration, and Data Analysis (VEDA) APP_CONTACT_EMAIL=email@example.org # Endpoint for the Tiler server. No trailing slash. -API_RASTER_ENDPOINT='https://openveda.cloud/api/raster' +API_RASTER_ENDPOINT='https://staging.openveda.cloud/api/raster' # Endpoint for the STAC server. No trailing slash. -API_STAC_ENDPOINT='https://openveda.cloud/api/stac' +API_STAC_ENDPOINT='https://staging.openveda.cloud/api/stac' API_XARRAY_ENDPOINT='https://prod-titiler-xarray.delta-backend.com/tilejson.json' MAPBOX_STYLE_URL='mapbox://styles/covid-nasa/ckb01h6f10bn81iqg98ne0i2y' From 639a0b20d5b44e1a15dea7edc58aee288d667a37 Mon Sep 17 00:00:00 2001 From: Andrew Blackford <62357205+acblackford@users.noreply.github.com> Date: Wed, 18 Sep 2024 10:22:45 -0500 Subject: [PATCH 126/152] added dataset info and 5cm layer --- datasets/soil-texture.data.mdx | 85 ++++++++++++++++++++++++++++++++-- 1 file changed, 81 insertions(+), 4 deletions(-) diff --git a/datasets/soil-texture.data.mdx b/datasets/soil-texture.data.mdx index f41769280..97e331df3 100644 --- a/datasets/soil-texture.data.mdx +++ b/datasets/soil-texture.data.mdx @@ -67,10 +67,87 @@ layers: temporalResolution: Annual unit: N/A + - id: soil-texture-5cm + stacCol: soil-texture-5cm + name: Soil Texture at 5 cm Depth + type: raster + description: 'ISRIC Soil Texture Classification at 5 cm' + zoomExtent: + - 0 + - 20 + sourceParams: + colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", + "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF}' + nodata: 0 + rescale: + - 1 + - 12 + legend: + type: categorical + min: "1" + max: "12" + stops: + - color: "#F89E61" + label: "Clay" + - color: "#BA8560" + label: "Silty Clay" + - color: "#D8D2B4" + label: "Sandy Clay" + - color: "#AE734C" + label: "Clay Loam" + - color: "#9E8478" + label: "Silty Clay Loam" + - color: "#C6A365" + label: "Sandy Clay Loam" + - color: "#B4A67D" + label: "Loam" + - color: "#E1D4C4" + label: "Silty Loam" + - color: "#BEB56D" + label: "Sandy Loam" + - color: "#777C7A" + label: "Silt" + - color: "#A89B6F" + label: "Loamy Sand" + - color: "#E9E2AF" + label: "Sand" + info: + source: ISRIC + spatialExtent: Global + temporalResolution: Annual + unit: N/A + --- + + + ## Dataset Details + - **Temporal Extent:** 2017 + - **Temporal Resolution:** N/A + - **Spatial Extent:** Global + - **Spatial Resolution:** 250 m + - **Data Units:** N/A + - **Data Type:** Research + - **Data Latency:** N/A + +

+ + + ISRIC surface soil texture classifications (0 cm depth) in the Ohio River Valley. + +
+ - - -x - + + + x + From ea7d2cbb822be112551d79e3ff4a1e69ef10b797 Mon Sep 17 00:00:00 2001 From: Andrew Blackford <62357205+acblackford@users.noreply.github.com> Date: Wed, 18 Sep 2024 10:25:10 -0500 Subject: [PATCH 127/152] fixed another bad indent --- datasets/soil-texture.data.mdx | 96 +++++++++++++++++----------------- 1 file changed, 48 insertions(+), 48 deletions(-) diff --git a/datasets/soil-texture.data.mdx b/datasets/soil-texture.data.mdx index 97e331df3..c12f6429a 100644 --- a/datasets/soil-texture.data.mdx +++ b/datasets/soil-texture.data.mdx @@ -68,54 +68,54 @@ layers: unit: N/A - id: soil-texture-5cm - stacCol: soil-texture-5cm - name: Soil Texture at 5 cm Depth - type: raster - description: 'ISRIC Soil Texture Classification at 5 cm' - zoomExtent: - - 0 - - 20 - sourceParams: - colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", - "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF}' - nodata: 0 - rescale: - - 1 - - 12 - legend: - type: categorical - min: "1" - max: "12" - stops: - - color: "#F89E61" - label: "Clay" - - color: "#BA8560" - label: "Silty Clay" - - color: "#D8D2B4" - label: "Sandy Clay" - - color: "#AE734C" - label: "Clay Loam" - - color: "#9E8478" - label: "Silty Clay Loam" - - color: "#C6A365" - label: "Sandy Clay Loam" - - color: "#B4A67D" - label: "Loam" - - color: "#E1D4C4" - label: "Silty Loam" - - color: "#BEB56D" - label: "Sandy Loam" - - color: "#777C7A" - label: "Silt" - - color: "#A89B6F" - label: "Loamy Sand" - - color: "#E9E2AF" - label: "Sand" - info: - source: ISRIC - spatialExtent: Global - temporalResolution: Annual - unit: N/A + stacCol: soil-texture-5cm + name: Soil Texture at 5 cm Depth + type: raster + description: 'ISRIC Soil Texture Classification at 5 cm' + zoomExtent: + - 0 + - 20 + sourceParams: + colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", + "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF}' + nodata: 0 + rescale: + - 1 + - 12 + legend: + type: categorical + min: "1" + max: "12" + stops: + - color: "#F89E61" + label: "Clay" + - color: "#BA8560" + label: "Silty Clay" + - color: "#D8D2B4" + label: "Sandy Clay" + - color: "#AE734C" + label: "Clay Loam" + - color: "#9E8478" + label: "Silty Clay Loam" + - color: "#C6A365" + label: "Sandy Clay Loam" + - color: "#B4A67D" + label: "Loam" + - color: "#E1D4C4" + label: "Silty Loam" + - color: "#BEB56D" + label: "Sandy Loam" + - color: "#777C7A" + label: "Silt" + - color: "#A89B6F" + label: "Loamy Sand" + - color: "#E9E2AF" + label: "Sand" + info: + source: ISRIC + spatialExtent: Global + temporalResolution: Annual + unit: N/A --- From ae6150724f8f6675fb4f6241cdd843c62d79e3e7 Mon Sep 17 00:00:00 2001 From: Andrew Blackford <62357205+acblackford@users.noreply.github.com> Date: Wed, 18 Sep 2024 10:43:09 -0500 Subject: [PATCH 128/152] added 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zs@Hyn42by@`eW#Sw-RC#YcAK_?1o=-b#udAuLQ5STIlZkO>%6?SA1n$A_w~0yCmT6 zqp@FAHx`%1cInwZ8a!Im=P^=c`3jloNzlbhZ5R0q8ztK=TJIm99MtHN6>@Q-E=p(I z9~p>Rmf)l!c2OEsX&m_?A2()Ie{0j2 zLhaLwM>)E7eD%>(6!Af?G0sUuu*_1hoQn>V7ca^NoJwi%&??^3NYI2JR=b6i&*mNhhJ+!fXQs@x=z(^oAls3Qhgj zEG8-d&I9Hql46Re5fyrU#z$oQjGlO5E~Y>IFcsP+?0a}7IcgT~rNK0d0hE$f%0YxF z6k5r3d9^_mZ(k1l#u01*gKVqY-fk#itB$gjvKRoAqlhSH`;JbdpSacG%x#@C>%IP)k;MRW+sHHc?9p6d4Payr}j*0AStkzJ&N?JwihZU#s=N-+_t$j#KPX6S~R>4>ws@YqIP5`m&(9dX_&YyMjMLJnI(>~n0p7e6e V+ckkgu^PpI0000000000008{Lqp$z~ literal 0 HcmV?d00001 diff --git a/datasets/soil-texture.data.mdx b/datasets/soil-texture.data.mdx index c12f6429a..9ebca7e5f 100644 --- a/datasets/soil-texture.data.mdx +++ b/datasets/soil-texture.data.mdx @@ -117,6 +117,264 @@ layers: temporalResolution: Annual unit: N/A + + - id: soil-texture-15cm + stacCol: soil-texture-15cm + name: Soil Texture at 15 cm Depth + type: raster + description: 'ISRIC Soil Texture Classification at 15 cm' + zoomExtent: + - 0 + - 20 + sourceParams: + colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", + "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF}' + nodata: 0 + rescale: + - 1 + - 12 + legend: + type: categorical + min: "1" + max: "12" + stops: + - color: "#F89E61" + label: "Clay" + - color: "#BA8560" + label: "Silty Clay" + - color: "#D8D2B4" + label: "Sandy Clay" + - color: "#AE734C" + label: "Clay Loam" + - color: "#9E8478" + label: "Silty Clay Loam" + - color: "#C6A365" + label: "Sandy Clay Loam" + - color: "#B4A67D" + label: "Loam" + - color: "#E1D4C4" + label: "Silty Loam" + - color: "#BEB56D" + label: "Sandy Loam" + - color: "#777C7A" + label: "Silt" + - color: "#A89B6F" + label: "Loamy Sand" + - color: "#E9E2AF" + label: "Sand" + info: + source: ISRIC + spatialExtent: Global + temporalResolution: Annual + unit: N/A + + - id: soil-texture-30cm + stacCol: soil-texture-30cm + name: Soil Texture at 30 cm Depth + type: raster + description: 'ISRIC Soil Texture Classification at 30 cm' + zoomExtent: + - 0 + - 20 + sourceParams: + colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", + "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF}' + nodata: 0 + rescale: + - 1 + - 12 + legend: + type: categorical + min: "1" + max: "12" + stops: + - color: "#F89E61" + label: "Clay" + - color: "#BA8560" + label: "Silty Clay" + - color: "#D8D2B4" + label: "Sandy Clay" + - color: "#AE734C" + label: "Clay Loam" + - color: "#9E8478" + label: "Silty Clay Loam" + - color: "#C6A365" + label: "Sandy Clay Loam" + - color: "#B4A67D" + label: "Loam" + - color: "#E1D4C4" + label: "Silty Loam" + - color: "#BEB56D" + label: "Sandy Loam" + - color: "#777C7A" + label: "Silt" + - color: "#A89B6F" + label: "Loamy Sand" + - color: "#E9E2AF" + label: "Sand" + info: + source: ISRIC + spatialExtent: Global + temporalResolution: Annual + unit: N/A + + + + - id: soil-texture-60cm + stacCol: soil-texture-60cm + name: Soil Texture at 60 cm Depth + type: raster + description: 'ISRIC Soil Texture Classification at 60 cm' + zoomExtent: + - 0 + - 20 + sourceParams: + colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", + "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF}' + nodata: 0 + rescale: + - 1 + - 12 + legend: + type: categorical + min: "1" + max: "12" + stops: + - color: "#F89E61" + label: "Clay" + - color: "#BA8560" + label: "Silty Clay" + - color: "#D8D2B4" + label: "Sandy Clay" + - color: "#AE734C" + label: "Clay Loam" + - color: "#9E8478" + label: "Silty Clay Loam" + - color: "#C6A365" + label: "Sandy Clay Loam" + - color: "#B4A67D" + label: "Loam" + - color: "#E1D4C4" + label: "Silty Loam" + - color: "#BEB56D" + label: "Sandy Loam" + - color: "#777C7A" + label: "Silt" + - color: "#A89B6F" + label: "Loamy Sand" + - color: "#E9E2AF" + label: "Sand" + info: + source: ISRIC + spatialExtent: Global + temporalResolution: Annual + unit: N/A + + + + - id: soil-texture-100cm + stacCol: soil-texture-100cm + name: Soil Texture at 100 cm Depth + type: raster + description: 'ISRIC Soil Texture Classification at 100 cm' + zoomExtent: + - 0 + - 20 + sourceParams: + colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", + "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF}' + nodata: 0 + rescale: + - 1 + - 12 + legend: + type: categorical + min: "1" + max: "12" + stops: + - color: "#F89E61" + label: "Clay" + - color: "#BA8560" + label: "Silty Clay" + - color: "#D8D2B4" + label: "Sandy Clay" + - color: "#AE734C" + label: "Clay Loam" + - color: "#9E8478" + label: "Silty Clay Loam" + - color: "#C6A365" + label: "Sandy Clay Loam" + - color: "#B4A67D" + label: "Loam" + - color: "#E1D4C4" + label: "Silty Loam" + - color: "#BEB56D" + label: "Sandy Loam" + - color: "#777C7A" + label: "Silt" + - color: "#A89B6F" + label: "Loamy Sand" + - color: "#E9E2AF" + label: "Sand" + info: + source: ISRIC + spatialExtent: Global + temporalResolution: Annual + unit: N/A + + + + - id: soil-texture-200cm + stacCol: soil-texture-200cm + name: Soil Texture at 200 cm Depth + type: raster + description: 'ISRIC Soil Texture Classification at 200 cm' + zoomExtent: + - 0 + - 20 + sourceParams: + colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", + "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF}' + nodata: 0 + rescale: + - 1 + - 12 + legend: + type: categorical + min: "1" + max: "12" + stops: + - color: "#F89E61" + label: "Clay" + - color: "#BA8560" + label: "Silty Clay" + - color: "#D8D2B4" + label: "Sandy Clay" + - color: "#AE734C" + label: "Clay Loam" + - color: "#9E8478" + label: "Silty Clay Loam" + - color: "#C6A365" + label: "Sandy Clay Loam" + - color: "#B4A67D" + label: "Loam" + - color: "#E1D4C4" + label: "Silty Loam" + - color: "#BEB56D" + label: "Sandy Loam" + - color: "#777C7A" + label: "Silt" + - color: "#A89B6F" + label: "Loamy Sand" + - color: "#E9E2AF" + label: "Sand" + info: + source: ISRIC + spatialExtent: Global + temporalResolution: Annual + unit: N/A + + --- @@ -148,6 +406,90 @@ layers: - x + ### About + The ISRIC Soil Texture dataset (SoilGrids 250) provides detailed soil texture classifications, which are critical for understanding soil properties, water retention, and agricultural potential. Maintained by the International Soil Reference and Information Centre (ISRIC), this dataset has been instrumental in various environmental and agricultural studies across the globe. This classification system breaks soils down into different categories based on their percentage of sand, silt, and clay, providing an essential resource for researchers, land managers, and farmers. + + +
+ Soil Texture Classification Triangle. + + ISRIC Soil Texture Classification Triangle showing the percentage of clay, silt, and sand in each type. + +
+
+ + + + ### What the ISRIC Soil Texture Dataset Offers + - Soil Texture Classes: This dataset classifies soils into twelve texture categories, ranging from sand, silt, and clay, to more complex combinations such as loam, clay loam, and silty clay. Each category offers a distinct combination of sand, silt, and clay content, helping users determine soil characteristics. + + - Soil Texture Triangle: A visualization tool used to depict the relationships between the percentage of sand, silt, and clay in soil. It allows users to easily locate and interpret soil types based on their texture composition. + + - Applications in Agriculture and Environmental Studies: The soil texture classification is pivotal in determining soil fertility, drainage capabilities, and erosion potential, making it crucial for land use planning, crop management, and climate studies. + + + + + + + + ### Access the Data + + Visit the [ISRIC](https://www.isric.org) webpage to explore all of the data options that ISRIC offers. + + + + + + + + ### Citing this Dataset + + International Soil Reference and Information Centre (ISRIC). (2017). ISRIC Soil Texture Classification: Global Soil Properties. https://www.isric.org + + + + + + + + ## Disclaimer + + All data provided in VEDA has been transformed from the original format (TIFF) into Cloud Optimized GeoTIFFs ([COG](https://www.cogeo.org)). Careful quality checks are used to ensure data transformation has been performed correctly. + + + + + + ### Key Publications + + Hengl, T., de Jesus, J.M., Heuvelink, G.B.M., Gonzalez, M.R., Kilibarda, M., Blagotić, A., ... & Kempen, B. (2017). SoilGrids250m: Global gridded soil information based on machine learning. PLoS One, 12(2), e0169748. https://doi.org/10.1371/journal.pone.0169748 + + Rossiter, D. G. (2001). Methodology for soil resource inventories. Computers and Electronics in Agriculture, 35(2), 189–214. + + + + + + + ## Data Stories Using This Dataset + + **[Climate Extremes Aggrevate Social Vulnerabilities in Alabama's Black Belt](https://www.earthdata.nasa.gov/dashboard/stories/black-belt-climate)** + + + + + + + + ## License + + [Creative Commons Attribution 1.0 International](https://creativecommons.org/publicdomain/zero/1.0/legalcode) (CC BY 1.0) + + + \ No newline at end of file From bb141ebc246c19898f720fd3aeeac5b4328d74d9 Mon Sep 17 00:00:00 2001 From: Andrew Blackford <62357205+acblackford@users.noreply.github.com> Date: Wed, 18 Sep 2024 10:51:19 -0500 Subject: [PATCH 129/152] fixed nodata values --- datasets/soil-texture.data.mdx | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/datasets/soil-texture.data.mdx b/datasets/soil-texture.data.mdx index 9ebca7e5f..8dde7a10a 100644 --- a/datasets/soil-texture.data.mdx +++ b/datasets/soil-texture.data.mdx @@ -28,7 +28,7 @@ layers: sourceParams: colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF}' - nodata: 0 + nodata: 255 rescale: - 1 - 12 @@ -78,7 +78,7 @@ layers: sourceParams: colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF}' - nodata: 0 + nodata: 255 rescale: - 1 - 12 @@ -129,7 +129,7 @@ layers: sourceParams: colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF}' - nodata: 0 + nodata: 255 rescale: - 1 - 12 @@ -179,7 +179,7 @@ layers: sourceParams: colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF}' - nodata: 0 + nodata: 255 rescale: - 1 - 12 @@ -231,7 +231,7 @@ layers: sourceParams: colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF}' - nodata: 0 + nodata: 255 rescale: - 1 - 12 @@ -283,7 +283,7 @@ layers: sourceParams: colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF}' - nodata: 0 + nodata: 255 rescale: - 1 - 12 @@ -335,7 +335,7 @@ layers: sourceParams: colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF}' - nodata: 0 + nodata: 255 rescale: - 1 - 12 From d5cbbf9895bcf695caf91f2075e96b0cd0410125 Mon Sep 17 00:00:00 2001 From: Andrew Blackford <62357205+acblackford@users.noreply.github.com> Date: Wed, 18 Sep 2024 10:54:05 -0500 Subject: [PATCH 130/152] swapped figure-prose sides --- datasets/soil-texture.data.mdx | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/datasets/soil-texture.data.mdx b/datasets/soil-texture.data.mdx index 8dde7a10a..68c7a2bf6 100644 --- a/datasets/soil-texture.data.mdx +++ b/datasets/soil-texture.data.mdx @@ -405,12 +405,7 @@ layers:
- - ### About - The ISRIC Soil Texture dataset (SoilGrids 250) provides detailed soil texture classifications, which are critical for understanding soil properties, water retention, and agricultural potential. Maintained by the International Soil Reference and Information Centre (ISRIC), this dataset has been instrumental in various environmental and agricultural studies across the globe. This classification system breaks soils down into different categories based on their percentage of sand, silt, and clay, providing an essential resource for researchers, land managers, and farmers. - - -
+
Soil Texture Classification Triangle.
+ + + ### About + The ISRIC Soil Texture dataset (SoilGrids 250) provides detailed soil texture classifications, which are critical for understanding soil properties, water retention, and agricultural potential. Maintained by the International Soil Reference and Information Centre (ISRIC), this dataset has been instrumental in various environmental and agricultural studies across the globe. This classification system breaks soils down into different categories based on their percentage of sand, silt, and clay, providing an essential resource for researchers, land managers, and farmers. + From 7027aee5e0b5358e66d69cc064c758839520ffda Mon Sep 17 00:00:00 2001 From: Andrew Blackford <62357205+acblackford@users.noreply.github.com> Date: Wed, 18 Sep 2024 10:57:09 -0500 Subject: [PATCH 131/152] fixed data citation --- datasets/soil-texture.data.mdx | 16 +++++++++++++--- 1 file changed, 13 insertions(+), 3 deletions(-) diff --git a/datasets/soil-texture.data.mdx b/datasets/soil-texture.data.mdx index 68c7a2bf6..7468d516f 100644 --- a/datasets/soil-texture.data.mdx +++ b/datasets/soil-texture.data.mdx @@ -438,7 +438,7 @@ layers: ### Access the Data - Visit the [ISRIC](https://www.isric.org) webpage to explore all of the data options that ISRIC offers. + Visit the [SoilGrids](https://www.soilgrids.org) webpage to explore all of the data options that SoilGrids 250 offers. @@ -448,7 +448,7 @@ layers: ### Citing this Dataset - International Soil Reference and Information Centre (ISRIC). (2017). ISRIC Soil Texture Classification: Global Soil Properties. https://www.isric.org + Hengl, T., de Jesus, J.M., Heuvelink, G.B.M., Gonzalez, M.R., Kilibarda, M., Blagotić, A., ... & Kempen, B. (2017). SoilGrids250m: Global gridded soil information based on machine learning. PLoS One, 12(2), e0169748. https://doi.org/10.1371/journal.pone.0169748 @@ -466,14 +466,24 @@ layers: - ### Key Publications + ### Key Publication Hengl, T., de Jesus, J.M., Heuvelink, G.B.M., Gonzalez, M.R., Kilibarda, M., Blagotić, A., ... & Kempen, B. (2017). SoilGrids250m: Global gridded soil information based on machine learning. PLoS One, 12(2), e0169748. https://doi.org/10.1371/journal.pone.0169748 + + + + + + + ### Other Publications + Rossiter, D. G. (2001). Methodology for soil resource inventories. Computers and Electronics in Agriculture, 35(2), 189–214. + + From 8d134b4edfdcde331b3bf9c7803b2ed1564ff410 Mon Sep 17 00:00:00 2001 From: Andrew Blackford <62357205+acblackford@users.noreply.github.com> Date: Wed, 18 Sep 2024 11:02:10 -0500 Subject: [PATCH 132/152] missing " added --- datasets/soil-texture.data.mdx | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/datasets/soil-texture.data.mdx b/datasets/soil-texture.data.mdx index 7468d516f..6ef736506 100644 --- a/datasets/soil-texture.data.mdx +++ b/datasets/soil-texture.data.mdx @@ -27,7 +27,7 @@ layers: - 20 sourceParams: colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", - "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF}' + "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF"}' nodata: 255 rescale: - 1 @@ -77,7 +77,7 @@ layers: - 20 sourceParams: colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", - "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF}' + "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF"}' nodata: 255 rescale: - 1 @@ -128,7 +128,7 @@ layers: - 20 sourceParams: colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", - "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF}' + "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF"}' nodata: 255 rescale: - 1 @@ -178,7 +178,7 @@ layers: - 20 sourceParams: colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", - "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF}' + "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF"}' nodata: 255 rescale: - 1 @@ -230,7 +230,7 @@ layers: - 20 sourceParams: colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", - "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF}' + "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF"}' nodata: 255 rescale: - 1 @@ -282,7 +282,7 @@ layers: - 20 sourceParams: colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", - "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF}' + "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF"}' nodata: 255 rescale: - 1 @@ -334,7 +334,7 @@ layers: - 20 sourceParams: colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", - "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF}' + "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF"}' nodata: 255 rescale: - 1 From e5d08891ff3c3a445e913e991171e8f7a0e848fb Mon Sep 17 00:00:00 2001 From: Andrew Blackford <62357205+acblackford@users.noreply.github.com> Date: Wed, 18 Sep 2024 11:10:26 -0500 Subject: [PATCH 133/152] more cmap testing --- datasets/soil-texture.data.mdx | 22 ++++++++-------------- 1 file changed, 8 insertions(+), 14 deletions(-) diff --git a/datasets/soil-texture.data.mdx b/datasets/soil-texture.data.mdx index 6ef736506..c53018ae8 100644 --- a/datasets/soil-texture.data.mdx +++ b/datasets/soil-texture.data.mdx @@ -19,7 +19,7 @@ taxonomy: layers: - id: soil-texture-0cm stacCol: soil-texture-0cm - name: Soil Texture at the Surface (0 cm) + name: Soil Texture at the Surface (0 cm Depth) type: raster description: 'ISRIC Soil Texture Classification at 0 cm' zoomExtent: @@ -117,7 +117,6 @@ layers: temporalResolution: Annual unit: N/A - - id: soil-texture-15cm stacCol: soil-texture-15cm name: Soil Texture at 15 cm Depth @@ -218,8 +217,6 @@ layers: temporalResolution: Annual unit: N/A - - - id: soil-texture-60cm stacCol: soil-texture-60cm name: Soil Texture at 60 cm Depth @@ -270,8 +267,6 @@ layers: temporalResolution: Annual unit: N/A - - - id: soil-texture-100cm stacCol: soil-texture-100cm name: Soil Texture at 100 cm Depth @@ -281,12 +276,14 @@ layers: - 0 - 20 sourceParams: - colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", + resampling: bilinear + bidx: 1 + colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF"}' - nodata: 255 - rescale: - - 1 - - 12 + nodata: 255 + rescale: + - 1 + - 12 legend: type: categorical min: "1" @@ -322,8 +319,6 @@ layers: temporalResolution: Annual unit: N/A - - - id: soil-texture-200cm stacCol: soil-texture-200cm name: Soil Texture at 200 cm Depth @@ -374,7 +369,6 @@ layers: temporalResolution: Annual unit: N/A - --- From 48adcb3ad4dd462228e69651553be44a7c05fd42 Mon Sep 17 00:00:00 2001 From: Andrew Blackford <62357205+acblackford@users.noreply.github.com> Date: Wed, 18 Sep 2024 11:16:18 -0500 Subject: [PATCH 134/152] trying changing cmap def indents --- datasets/soil-texture.data.mdx | 2 -- 1 file changed, 2 deletions(-) diff --git a/datasets/soil-texture.data.mdx b/datasets/soil-texture.data.mdx index c53018ae8..291fb6ec3 100644 --- a/datasets/soil-texture.data.mdx +++ b/datasets/soil-texture.data.mdx @@ -276,8 +276,6 @@ layers: - 0 - 20 sourceParams: - resampling: bilinear - bidx: 1 colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF"}' nodata: 255 From fd86475be8dc67c80296bfbf99c48a42f6f0df54 Mon Sep 17 00:00:00 2001 From: Andrew Blackford <62357205+acblackford@users.noreply.github.com> Date: Wed, 18 Sep 2024 11:17:07 -0500 Subject: [PATCH 135/152] matching indents from dataset that worked --- datasets/soil-texture.data.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/datasets/soil-texture.data.mdx b/datasets/soil-texture.data.mdx index 291fb6ec3..c7b8c3048 100644 --- a/datasets/soil-texture.data.mdx +++ b/datasets/soil-texture.data.mdx @@ -277,7 +277,7 @@ layers: - 20 sourceParams: colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", - "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF"}' + "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF"}' nodata: 255 rescale: - 1 From 9b87e7716aee12a35d5dffc45034a5c136e90d77 Mon Sep 17 00:00:00 2001 From: Andrew Blackford <62357205+acblackford@users.noreply.github.com> Date: Wed, 18 Sep 2024 11:39:21 -0500 Subject: [PATCH 136/152] trying pre-defined cmap --- datasets/soil-texture.data.mdx | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/datasets/soil-texture.data.mdx b/datasets/soil-texture.data.mdx index c7b8c3048..b2508afe3 100644 --- a/datasets/soil-texture.data.mdx +++ b/datasets/soil-texture.data.mdx @@ -276,8 +276,7 @@ layers: - 0 - 20 sourceParams: - colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", - "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF"}' + colormap_name: reds nodata: 255 rescale: - 1 From 7634a6814e8047e2fc1def9574389eedfbc0d677 Mon Sep 17 00:00:00 2001 From: Andrew Blackford <62357205+acblackford@users.noreply.github.com> Date: Wed, 18 Sep 2024 11:45:25 -0500 Subject: [PATCH 137/152] more cmap testing --- datasets/soil-texture.data.mdx | 6 +----- 1 file changed, 1 insertion(+), 5 deletions(-) diff --git a/datasets/soil-texture.data.mdx b/datasets/soil-texture.data.mdx index b2508afe3..ee587cf25 100644 --- a/datasets/soil-texture.data.mdx +++ b/datasets/soil-texture.data.mdx @@ -29,13 +29,9 @@ layers: colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF"}' nodata: 255 - rescale: - - 1 - - 12 + legend: type: categorical - min: "1" - max: "12" stops: - color: "#F89E61" label: "Clay" From 1faa05c08761cd75c8d4548d888b16c44e3edd74 Mon Sep 17 00:00:00 2001 From: Andrew Blackford <62357205+acblackford@users.noreply.github.com> Date: Wed, 18 Sep 2024 11:50:10 -0500 Subject: [PATCH 138/152] custom cmap fixed! --- datasets/soil-texture.data.mdx | 41 ++++++++-------------------------- 1 file changed, 9 insertions(+), 32 deletions(-) diff --git a/datasets/soil-texture.data.mdx b/datasets/soil-texture.data.mdx index ee587cf25..14bd37212 100644 --- a/datasets/soil-texture.data.mdx +++ b/datasets/soil-texture.data.mdx @@ -75,13 +75,9 @@ layers: colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF"}' nodata: 255 - rescale: - - 1 - - 12 + legend: type: categorical - min: "1" - max: "12" stops: - color: "#F89E61" label: "Clay" @@ -125,13 +121,9 @@ layers: colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF"}' nodata: 255 - rescale: - - 1 - - 12 + legend: type: categorical - min: "1" - max: "12" stops: - color: "#F89E61" label: "Clay" @@ -175,13 +167,9 @@ layers: colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF"}' nodata: 255 - rescale: - - 1 - - 12 + legend: type: categorical - min: "1" - max: "12" stops: - color: "#F89E61" label: "Clay" @@ -225,13 +213,9 @@ layers: colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF"}' nodata: 255 - rescale: - - 1 - - 12 + legend: type: categorical - min: "1" - max: "12" stops: - color: "#F89E61" label: "Clay" @@ -272,15 +256,12 @@ layers: - 0 - 20 sourceParams: - colormap_name: reds - nodata: 255 - rescale: - - 1 - - 12 + colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", + "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF"}' + nodata: 255 + legend: type: categorical - min: "1" - max: "12" stops: - color: "#F89E61" label: "Clay" @@ -324,13 +305,9 @@ layers: colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF"}' nodata: 255 - rescale: - - 1 - - 12 + legend: type: categorical - min: "1" - max: "12" stops: - color: "#F89E61" label: "Clay" From eaa64c2b5f0ca2ad72de27e96b70528bd10b8c22 Mon Sep 17 00:00:00 2001 From: Andrew Blackford <62357205+acblackford@users.noreply.github.com> Date: Wed, 18 Sep 2024 15:14:11 -0500 Subject: [PATCH 139/152] added interactive soil textures to story --- stories/black-belt-climate-ej.stories.mdx | 28 +++++++++++++++++------ 1 file changed, 21 insertions(+), 7 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 977efb0b8..7a1e9e88f 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -45,17 +45,31 @@ taxonomy: The Alabama Black Belt, a region integral to the Southern United States, derives its name from its dark, fertile soil. This rich land, ideal for agriculture, especially cotton, owes its fertility to a unique geological history. Millions of years ago, when the Gulf of Mexico extended further inland, plankton deposits formed soft limestone called Selma Chalk. Over time, this limestone weathered, creating the calcium-rich, chalky subsoil that characterizes the Black Belt, transforming it into an agricultural powerhouse.

-
- + + ### Your markdown header + + Your markdown contents comes here. + + + +
+ - - General Soil Map of Alabama. - + + Surface soil textures classified from the International Soil Reference and Information Centre (ISRIC) show the fertile 'black belt' region of Alabama quite well. +
+ + +

From 14e7f8456237284cf782081a5a511dfa6266bcb1 Mon Sep 17 00:00:00 2001 From: Andrew Blackford <62357205+acblackford@users.noreply.github.com> Date: Wed, 18 Sep 2024 15:17:20 -0500 Subject: [PATCH 140/152] fixing prose mdx error --- stories/black-belt-climate-ej.stories.mdx | 8 -------- 1 file changed, 8 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 7a1e9e88f..118914147 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -45,14 +45,6 @@ taxonomy: The Alabama Black Belt, a region integral to the Southern United States, derives its name from its dark, fertile soil. This rich land, ideal for agriculture, especially cotton, owes its fertility to a unique geological history. Millions of years ago, when the Gulf of Mexico extended further inland, plankton deposits formed soft limestone called Selma Chalk. Over time, this limestone weathered, creating the calcium-rich, chalky subsoil that characterizes the Black Belt, transforming it into an agricultural powerhouse.

- - - ### Your markdown header - - Your markdown contents comes here. - - -
Date: Wed, 18 Sep 2024 15:19:48 -0500 Subject: [PATCH 141/152] more error fixing --- stories/black-belt-climate-ej.stories.mdx | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 118914147..7e14fd21c 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -45,6 +45,7 @@ taxonomy: The Alabama Black Belt, a region integral to the Southern United States, derives its name from its dark, fertile soil. This rich land, ideal for agriculture, especially cotton, owes its fertility to a unique geological history. Millions of years ago, when the Gulf of Mexico extended further inland, plankton deposits formed soft limestone called Selma Chalk. Over time, this limestone weathered, creating the calcium-rich, chalky subsoil that characterizes the Black Belt, transforming it into an agricultural powerhouse.

+
- - From a1639600402d78f23a293d1ea3c842326ca5b0e7 Mon Sep 17 00:00:00 2001 From: siddharth0248 Date: Mon, 23 Sep 2024 13:56:26 -0500 Subject: [PATCH 142/152] slider date --- stories/nldas3.stories.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/stories/nldas3.stories.mdx b/stories/nldas3.stories.mdx index fb6bb976e..f941cc4f0 100644 --- a/stories/nldas3.stories.mdx +++ b/stories/nldas3.stories.mdx @@ -133,7 +133,7 @@ taxonomy: layerId='nldas2' zoom={6} center={[-90,39]} - dateTime='2020-08' + dateTime='2017-08' compareDateTime='2017-08' /> Date: Mon, 23 Sep 2024 14:34:16 -0500 Subject: [PATCH 143/152] remove one onotebook --- stories/nldas3.stories.mdx | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/stories/nldas3.stories.mdx b/stories/nldas3.stories.mdx index f941cc4f0..ccc765ed0 100644 --- a/stories/nldas3.stories.mdx +++ b/stories/nldas3.stories.mdx @@ -157,9 +157,8 @@ taxonomy: ## Explore the Data in the Cloud Below are links to sample monthly precipitation forcing data in Jupyter Notebooks for you to further explore and examine NLDAS-2 and the sample NLDAS-3 data. - - [Notebook 1](https://nasa-impact.github.io/veda-docs/notebooks/datasets/nldas_visualize_rawdata.html) shows how to visualize NLDAS-3 data. - - [Notebook 2](https://nasa-impact.github.io/veda-docs/notebooks/datasets/nldas_time_series.html) shows you how to create time series for NLDAS-3 data. - - [Notebook 3](https://nasa-impact.github.io/veda-docs/notebooks/datasets/nldas_compare2_3.html) shows you how to compare NLDAS-2 and NLDAS-3 data. + - [Notebook 1](https://nasa-impact.github.io/veda-docs/notebooks/datasets/nldas_time_series.html) shows you how to create time series for NLDAS-3 data. + - [Notebook 2](https://nasa-impact.github.io/veda-docs/notebooks/datasets/nldas_compare2_3.html) shows you how to compare NLDAS-2 and NLDAS-3 data. From 6566bae47c8ddfb3ee90dcea0a4ec3bada380b2a Mon Sep 17 00:00:00 2001 From: siddharth0248 Date: Tue, 24 Sep 2024 10:03:05 -0500 Subject: [PATCH 144/152] env and file size changed --- .env | 4 ++-- stories/nldas-fig4.png | Bin 257001 -> 0 bytes stories/nldas-fig5.png | Bin 376409 -> 0 bytes stories/nldas-fig7.png | Bin 823682 -> 225884 bytes stories/nldas3-fig1b.png | Bin 2574734 -> 512088 bytes 5 files changed, 2 insertions(+), 2 deletions(-) delete mode 100644 stories/nldas-fig4.png delete mode 100644 stories/nldas-fig5.png diff --git a/.env b/.env index 095a452ab..0aeb58068 100644 --- a/.env +++ b/.env @@ -8,10 +8,10 @@ APP_DESCRIPTION=Visualization, Exploration, and Data Analysis (VEDA) APP_CONTACT_EMAIL=email@example.org # Endpoint for the Tiler server. No trailing slash. -API_RASTER_ENDPOINT='https://staging.openveda.cloud/api/raster' +API_RASTER_ENDPOINT='https://openveda.cloud/api/raster' # Endpoint for the STAC server. 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z8Zma)?Aqx>dlD837UiI6r`^%lSlvl>u^uoBZ1*nT{9XuJf)Jmsp7$N7XE=AueBRXd R9n% Date: Tue, 24 Sep 2024 11:09:06 -0500 Subject: [PATCH 145/152] nldas2 data mdx description added --- datasets/nldas2.data.mdx | 1 + 1 file changed, 1 insertion(+) diff --git a/datasets/nldas2.data.mdx b/datasets/nldas2.data.mdx index 429834658..e8d253422 100644 --- a/datasets/nldas2.data.mdx +++ b/datasets/nldas2.data.mdx @@ -1,6 +1,7 @@ --- id: nldas2 name: "NLDAS-2 Precipitation Forcing Dataset" +description: "NLDAS-2 is a surface meteorological analysis and land-surface model dataset running in operations to produce outputs of soil moisture, snow, surface fluxes, streamflow, etc. for drought monitoring and other applications." media: src: ::file ./nldas-cover.png alt: Landsat 8 — OLI image of the Mississippi River below Memphis, Tennessee on September 16, 2023 at near record low water levels, limiting barge shipments, threatening drinking water supplies, agriculture, and ecosystems.y. From 414127c57d8345106e7bff16fee4f58bc646c3d7 Mon Sep 17 00:00:00 2001 From: Gjore Milevski Date: Wed, 16 Oct 2024 11:34:45 +0200 Subject: [PATCH 146/152] Update UI submodule --- .veda/ui | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.veda/ui b/.veda/ui index 4591e7936..7839e8d42 160000 --- a/.veda/ui +++ b/.veda/ui @@ -1 +1 @@ -Subproject commit 4591e79366e06c48a36f47b7677d45a1b970c984 +Subproject commit 7839e8d425dae7dde41676571e92a4b7d3937a88 From 6f2025c9fb5ce81aeaa3c888392fdfb5dc0351a4 Mon Sep 17 00:00:00 2001 From: Gjore Milevski Date: Wed, 16 Oct 2024 11:47:16 +0200 Subject: [PATCH 147/152] Enable configurable colormap --- .env | 2 ++ 1 file changed, 2 insertions(+) diff --git a/.env b/.env index 095a452ab..096053275 100644 --- a/.env +++ b/.env @@ -27,3 +27,5 @@ GOOGLE_FORM = 'https://docs.google.com/forms/d/e/1FAIpQLSfGcd3FDsM3kQIOVKjzdPn4f GOOGLE_ANALYTICS_ID='G-CQ3WLED121' FEATURE_NEW_EXPLORATION = 'TRUE' + +SHOW_CONFIGURABLE_COLOR_MAP = 'TRUE' \ No newline at end of file From 554b2edfc546a44734ba50320355a2f8584ead9d Mon Sep 17 00:00:00 2001 From: Gjore Milevski Date: Wed, 16 Oct 2024 12:50:41 +0200 Subject: [PATCH 148/152] Bump package json version --- package.json | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/package.json b/package.json index af6bd1759..7bbd65bfc 100644 --- a/package.json +++ b/package.json @@ -1,7 +1,7 @@ { "name": "veda-config", "description": "Configuration for Veda", - "version": "0.16.0", + "version": "0.17.0", "source": "./.veda/ui/app/index.html", "license": "Apache-2.0", "scripts": { From c815350e2421ea456f9a7270f594b86a7e7e8a8f Mon Sep 17 00:00:00 2001 From: Sandra Hoang Date: Fri, 18 Oct 2024 12:04:13 +0200 Subject: [PATCH 149/152] add codeowners for now --- .github/CODEOWNERS | 5 +++++ 1 file changed, 5 insertions(+) create mode 100644 .github/CODEOWNERS diff --git a/.github/CODEOWNERS b/.github/CODEOWNERS new file mode 100644 index 000000000..3907ac7dc --- /dev/null +++ b/.github/CODEOWNERS @@ -0,0 +1,5 @@ +# These owners will be the default owners for everything in +# the repo. Unless a later match takes precedence, +# these will be requested for +# review when someone opens a pull request. +* @hanbyul-here @sandrahoang686 @dzole0311 @aboydnw @AliceR @snmln \ No newline at end of file From 2fd92712502b23de3843fd63b201fa651dd0dc43 Mon Sep 17 00:00:00 2001 From: Sandra Hoang Date: Mon, 21 Oct 2024 11:07:43 -0400 Subject: [PATCH 150/152] Just remove dataset for now - soil texture --- datasets/soil-texture.data.mdx | 469 --------------------------------- 1 file changed, 469 deletions(-) delete mode 100644 datasets/soil-texture.data.mdx diff --git a/datasets/soil-texture.data.mdx b/datasets/soil-texture.data.mdx deleted file mode 100644 index 14bd37212..000000000 --- a/datasets/soil-texture.data.mdx +++ /dev/null @@ -1,469 +0,0 @@ ---- -id: soil-texture -name: 'ISRIC World Soil Texture Classifications' -description: "250 meter resolution global soil texture dataset from ISRIC, produced in 2017. Available at seven soil layer depths." -media: - src: ::file ./soil-texture-background.jpeg - alt: Examples of two different soil types - author: - name: Soil Sensor - url: https://soilsensor.com/articles/soil-textures/ -taxonomy: - - name: Topics - values: - - Agriculture - - Land Cover - - name: Source - values: - - ISRIC -layers: - - id: soil-texture-0cm - stacCol: soil-texture-0cm - name: Soil Texture at the Surface (0 cm Depth) - type: raster - description: 'ISRIC Soil Texture Classification at 0 cm' - zoomExtent: - - 0 - - 20 - sourceParams: - colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", - "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF"}' - nodata: 255 - - legend: - type: categorical - stops: - - color: "#F89E61" - label: "Clay" - - color: "#BA8560" - label: "Silty Clay" - - color: "#D8D2B4" - label: "Sandy Clay" - - color: "#AE734C" - label: "Clay Loam" - - color: "#9E8478" - label: "Silty Clay Loam" - - color: "#C6A365" - label: "Sandy Clay Loam" - - color: "#B4A67D" - label: "Loam" - - color: "#E1D4C4" - label: "Silty Loam" - - color: "#BEB56D" - label: "Sandy Loam" - - color: "#777C7A" - label: "Silt" - - color: "#A89B6F" - label: "Loamy Sand" - - color: "#E9E2AF" - label: "Sand" - info: - source: ISRIC - spatialExtent: Global - temporalResolution: Annual - unit: N/A - - - id: soil-texture-5cm - stacCol: soil-texture-5cm - name: Soil Texture at 5 cm Depth - type: raster - description: 'ISRIC Soil Texture Classification at 5 cm' - zoomExtent: - - 0 - - 20 - sourceParams: - colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", - "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF"}' - nodata: 255 - - legend: - type: categorical - stops: - - color: "#F89E61" - label: "Clay" - - color: "#BA8560" - label: "Silty Clay" - - color: "#D8D2B4" - label: "Sandy Clay" - - color: "#AE734C" - label: "Clay Loam" - - color: "#9E8478" - label: "Silty Clay Loam" - - color: "#C6A365" - label: "Sandy Clay Loam" - - color: "#B4A67D" - label: "Loam" - - color: "#E1D4C4" - label: "Silty Loam" - - color: "#BEB56D" - label: "Sandy Loam" - - color: "#777C7A" - label: "Silt" - - color: "#A89B6F" - label: "Loamy Sand" - - color: "#E9E2AF" - label: "Sand" - info: - source: ISRIC - spatialExtent: Global - temporalResolution: Annual - unit: N/A - - - id: soil-texture-15cm - stacCol: soil-texture-15cm - name: Soil Texture at 15 cm Depth - type: raster - description: 'ISRIC Soil Texture Classification at 15 cm' - zoomExtent: - - 0 - - 20 - sourceParams: - colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", - "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF"}' - nodata: 255 - - legend: - type: categorical - stops: - - color: "#F89E61" - label: "Clay" - - color: "#BA8560" - label: "Silty Clay" - - color: "#D8D2B4" - label: "Sandy Clay" - - color: "#AE734C" - label: "Clay Loam" - - color: "#9E8478" - label: "Silty Clay Loam" - - color: "#C6A365" - label: "Sandy Clay Loam" - - color: "#B4A67D" - label: "Loam" - - color: "#E1D4C4" - label: "Silty Loam" - - color: "#BEB56D" - label: "Sandy Loam" - - color: "#777C7A" - label: "Silt" - - color: "#A89B6F" - label: "Loamy Sand" - - color: "#E9E2AF" - label: "Sand" - info: - source: ISRIC - spatialExtent: Global - temporalResolution: Annual - unit: N/A - - - id: soil-texture-30cm - stacCol: soil-texture-30cm - name: Soil Texture at 30 cm Depth - type: raster - description: 'ISRIC Soil Texture Classification at 30 cm' - zoomExtent: - - 0 - - 20 - sourceParams: - colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", - "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF"}' - nodata: 255 - - legend: - type: categorical - stops: - - color: "#F89E61" - label: "Clay" - - color: "#BA8560" - label: "Silty Clay" - - color: "#D8D2B4" - label: "Sandy Clay" - - color: "#AE734C" - label: "Clay Loam" - - color: "#9E8478" - label: "Silty Clay Loam" - - color: "#C6A365" - label: "Sandy Clay Loam" - - color: "#B4A67D" - label: "Loam" - - color: "#E1D4C4" - label: "Silty Loam" - - color: "#BEB56D" - label: "Sandy Loam" - - color: "#777C7A" - label: "Silt" - - color: "#A89B6F" - label: "Loamy Sand" - - color: "#E9E2AF" - label: "Sand" - info: - source: ISRIC - spatialExtent: Global - temporalResolution: Annual - unit: N/A - - - id: soil-texture-60cm - stacCol: soil-texture-60cm - name: Soil Texture at 60 cm Depth - type: raster - description: 'ISRIC Soil Texture Classification at 60 cm' - zoomExtent: - - 0 - - 20 - sourceParams: - colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", - "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF"}' - nodata: 255 - - legend: - type: categorical - stops: - - color: "#F89E61" - label: "Clay" - - color: "#BA8560" - label: "Silty Clay" - - color: "#D8D2B4" - label: "Sandy Clay" - - color: "#AE734C" - label: "Clay Loam" - - color: "#9E8478" - label: "Silty Clay Loam" - - color: "#C6A365" - label: "Sandy Clay Loam" - - color: "#B4A67D" - label: "Loam" - - color: "#E1D4C4" - label: "Silty Loam" - - color: "#BEB56D" - label: "Sandy Loam" - - color: "#777C7A" - label: "Silt" - - color: "#A89B6F" - label: "Loamy Sand" - - color: "#E9E2AF" - label: "Sand" - info: - source: ISRIC - spatialExtent: Global - temporalResolution: Annual - unit: N/A - - - id: soil-texture-100cm - stacCol: soil-texture-100cm - name: Soil Texture at 100 cm Depth - type: raster - description: 'ISRIC Soil Texture Classification at 100 cm' - zoomExtent: - - 0 - - 20 - sourceParams: - colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", - "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF"}' - nodata: 255 - - legend: - type: categorical - stops: - - color: "#F89E61" - label: "Clay" - - color: "#BA8560" - label: "Silty Clay" - - color: "#D8D2B4" - label: "Sandy Clay" - - color: "#AE734C" - label: "Clay Loam" - - color: "#9E8478" - label: "Silty Clay Loam" - - color: "#C6A365" - label: "Sandy Clay Loam" - - color: "#B4A67D" - label: "Loam" - - color: "#E1D4C4" - label: "Silty Loam" - - color: "#BEB56D" - label: "Sandy Loam" - - color: "#777C7A" - label: "Silt" - - color: "#A89B6F" - label: "Loamy Sand" - - color: "#E9E2AF" - label: "Sand" - info: - source: ISRIC - spatialExtent: Global - temporalResolution: Annual - unit: N/A - - - id: soil-texture-200cm - stacCol: soil-texture-200cm - name: Soil Texture at 200 cm Depth - type: raster - description: 'ISRIC Soil Texture Classification at 200 cm' - zoomExtent: - - 0 - - 20 - sourceParams: - colormap: '{"1":"#F89E61", "2":"#BA8560", "3": "#D8D2B4", "4": "#AE734C", "5": "#9E8478", "6": "#C6A365", - "7":"#B4A67D", "8":"#E1D4C4", "9": "#BEB56D", "10": "#777C7A", "11": "#A89B6F", "12": "#E9E2AF"}' - nodata: 255 - - legend: - type: categorical - stops: - - color: "#F89E61" - label: "Clay" - - color: "#BA8560" - label: "Silty Clay" - - color: "#D8D2B4" - label: "Sandy Clay" - - color: "#AE734C" - label: "Clay Loam" - - color: "#9E8478" - label: "Silty Clay Loam" - - color: "#C6A365" - label: "Sandy Clay Loam" - - color: "#B4A67D" - label: "Loam" - - color: "#E1D4C4" - label: "Silty Loam" - - color: "#BEB56D" - label: "Sandy Loam" - - color: "#777C7A" - label: "Silt" - - color: "#A89B6F" - label: "Loamy Sand" - - color: "#E9E2AF" - label: "Sand" - info: - source: ISRIC - spatialExtent: Global - temporalResolution: Annual - unit: N/A - ---- - - - ## Dataset Details - - **Temporal Extent:** 2017 - - **Temporal Resolution:** N/A - - **Spatial Extent:** Global - - **Spatial Resolution:** 250 m - - **Data Units:** N/A - - **Data Type:** Research - - **Data Latency:** N/A - -

- - - ISRIC surface soil texture classifications (0 cm depth) in the Ohio River Valley. - -
- - - -
- Soil Texture Classification Triangle. - - ISRIC Soil Texture Classification Triangle showing the percentage of clay, silt, and sand in each type. - -
- - - ### About - The ISRIC Soil Texture dataset (SoilGrids 250) provides detailed soil texture classifications, which are critical for understanding soil properties, water retention, and agricultural potential. Maintained by the International Soil Reference and Information Centre (ISRIC), this dataset has been instrumental in various environmental and agricultural studies across the globe. This classification system breaks soils down into different categories based on their percentage of sand, silt, and clay, providing an essential resource for researchers, land managers, and farmers. - -
- - - - ### What the ISRIC Soil Texture Dataset Offers - - Soil Texture Classes: This dataset classifies soils into twelve texture categories, ranging from sand, silt, and clay, to more complex combinations such as loam, clay loam, and silty clay. Each category offers a distinct combination of sand, silt, and clay content, helping users determine soil characteristics. - - - Soil Texture Triangle: A visualization tool used to depict the relationships between the percentage of sand, silt, and clay in soil. It allows users to easily locate and interpret soil types based on their texture composition. - - - Applications in Agriculture and Environmental Studies: The soil texture classification is pivotal in determining soil fertility, drainage capabilities, and erosion potential, making it crucial for land use planning, crop management, and climate studies. - - - - - - - - ### Access the Data - - Visit the [SoilGrids](https://www.soilgrids.org) webpage to explore all of the data options that SoilGrids 250 offers. - - - - - - - - ### Citing this Dataset - - Hengl, T., de Jesus, J.M., Heuvelink, G.B.M., Gonzalez, M.R., Kilibarda, M., Blagotić, A., ... & Kempen, B. (2017). SoilGrids250m: Global gridded soil information based on machine learning. PLoS One, 12(2), e0169748. https://doi.org/10.1371/journal.pone.0169748 - - - - - - - - ## Disclaimer - - All data provided in VEDA has been transformed from the original format (TIFF) into Cloud Optimized GeoTIFFs ([COG](https://www.cogeo.org)). Careful quality checks are used to ensure data transformation has been performed correctly. - - - - - - - - ### Key Publication - - Hengl, T., de Jesus, J.M., Heuvelink, G.B.M., Gonzalez, M.R., Kilibarda, M., Blagotić, A., ... & Kempen, B. (2017). SoilGrids250m: Global gridded soil information based on machine learning. PLoS One, 12(2), e0169748. https://doi.org/10.1371/journal.pone.0169748 - - - - - - - - ### Other Publications - - Rossiter, D. G. (2001). Methodology for soil resource inventories. Computers and Electronics in Agriculture, 35(2), 189–214. - - - - - - - - - ## Data Stories Using This Dataset - - **[Climate Extremes Aggrevate Social Vulnerabilities in Alabama's Black Belt](https://www.earthdata.nasa.gov/dashboard/stories/black-belt-climate)** - - - - - - - - ## License - - [Creative Commons Attribution 1.0 International](https://creativecommons.org/publicdomain/zero/1.0/legalcode) (CC BY 1.0) - - - \ No newline at end of file From 4196a396b4891cdd581499de381a3df68cc0da7e Mon Sep 17 00:00:00 2001 From: Sandra Hoang Date: Mon, 21 Oct 2024 11:09:27 -0400 Subject: [PATCH 151/152] revert env file --- .env | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.env b/.env index 096053275..5f2c25abf 100644 --- a/.env +++ b/.env @@ -8,10 +8,10 @@ APP_DESCRIPTION=Visualization, Exploration, and Data Analysis (VEDA) APP_CONTACT_EMAIL=email@example.org # Endpoint for the Tiler server. No trailing slash. -API_RASTER_ENDPOINT='https://staging.openveda.cloud/api/raster' +API_RASTER_ENDPOINT='https://openveda.cloud/api/raster' # Endpoint for the STAC server. No trailing slash. -API_STAC_ENDPOINT='https://staging.openveda.cloud/api/stac' +API_STAC_ENDPOINT='https://openveda.cloud/api/stac' API_XARRAY_ENDPOINT='https://prod-titiler-xarray.delta-backend.com/tilejson.json' MAPBOX_STYLE_URL='mapbox://styles/covid-nasa/ckb01h6f10bn81iqg98ne0i2y' From 335785ddd59ea58dd49465075535c18f893e82ef Mon Sep 17 00:00:00 2001 From: Sandra Hoang Date: Mon, 21 Oct 2024 11:27:58 -0400 Subject: [PATCH 152/152] remove black belt climate stories in relation to soil-texture --- stories/black-belt-climate-ej.stories.mdx | 317 ---------------------- 1 file changed, 317 deletions(-) delete mode 100644 stories/black-belt-climate-ej.stories.mdx diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx deleted file mode 100644 index 7e14fd21c..000000000 --- a/stories/black-belt-climate-ej.stories.mdx +++ /dev/null @@ -1,317 +0,0 @@ ---- -id: black-belt-climate -name: Climate Extremes Aggravate Social Vulnerabilities in Alabama's Black Belt -description: "Rising temperatures worsen social vulnerabilities for the elderly population by increasing their heat-related health risks." -media: - src: ::file ./black_belt_cover.jpg - alt: Farmer in the fields. - author: - name: NASA - url: https://widerimage.reuters.com/photographer/lucy-nicholson.html -pubDate: 2024-09-01 -taxonomy: - - name: Topics - values: - - Environmental Justice - - Disasters ---- - - - -

- Authors: Maheshwari Neelam [1], Udaysankar Nair [2], Andrew Blackford [2], and Natalie P.Thomas [3] -

-

- [1] USRA and National Aeronautics and Space Administration (NASA) -

-

- [2] The University of Alabama in Huntsville -

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- [3] University of Maryland and Global Modeling and Assimilation Office, NASA -

-

- Mission: NASA Earth Action: A thriving world, driven by trusted, actionable Earth science -

-

- Disclaimer: This study demonstrates innovative and practical applications of NASA Earth science data to highlight existing environmental inequities. Please note that the results have not undergone peer review. -

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- The Alabama Black Belt, a region integral to the Southern United States, derives its name from its dark, fertile soil. This rich land, ideal for agriculture, especially cotton, owes its fertility to a unique geological history. Millions of years ago, when the Gulf of Mexico extended further inland, plankton deposits formed soft limestone called Selma Chalk. Over time, this limestone weathered, creating the calcium-rich, chalky subsoil that characterizes the Black Belt, transforming it into an agricultural powerhouse. -

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- - - Surface soil textures classified from the International Soil Reference and Information Centre (ISRIC) show the fertile 'black belt' region of Alabama quite well. - -
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- The Black Belt's crescent shape is captured in a natural-color image by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite. This image is a composition of segments from several images taken between 2015 and 2018, allowing for the removal of clouds and haze. -

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- - - Black Belt Prairie from MODIS. - -
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- The region's rich soil played a pivotal role in shaping the region's history and demographics. This fertile land transformed the area into an agricultural powerhouse, making it a cornerstone of the cotton economy, heavily reliant on enslaved African American labor. After the Civil War, many African Americans remained in the area, working as sharecroppers and tenant farmers. The region became a significant cultural and political area, particularly noted for its role in the civil rights movement. Despite its agricultural legacy, the Black Belt has faced economic and social challenges, including poverty and limited access to education and healthcare, which continue to impact its predominantly African American population. -

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- Analyzing Social Vulnerability Index (SVI) data from the CDC between 2000 and 2022 shows a concerning demographic shift: the younger generation, including those as young as 17, is increasingly moving out of the region, leaving behind an aging population, particularly those aged 65 and above. A linear trend is observed, with color coding representing the slope of this shift. This trend exacerbates the region's vulnerabilities, as the older population becomes more isolated and dependent. -

- -
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- -{/* - - -

- The region is now facing a significant new challenge: climate change. As global temperatures rise, extreme weather events like heatwaves are becoming increasingly frequent and severe. This is particularly concerning for areas where many residents, especially older adults, rely on outdoor agricultural work. Data from the MERRA-2 climate extreme indices dataset reveal troubling trends, showing changes in temperature extremes. Indices such as Cool Nights (TN10P) and Warm Nights (TN90P) track the frequency of days with nighttime temperatures falling below the 10th percentile or exceeding the 90th percentile. Similarly, Cool Days (TX10P) and Warm Days (TX90P) monitor daytime temperature extremes. Analyzing these indices from 1980 to 2023 uncovers a clear pattern of rising temperatures, with an increasing number of warm days and nights, highlighting the escalating climate challenges facing the region. -

-
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-*/} - - - - ## Climate Extremes in the Black Belt Region - Alabama's Black Belt counties face escalating climate challenges. MERRA-2 data from 1980 to 2023 reveals significant shifts in temperature extremes. The region is experiencing an increase in warm days and nights (TX90P, TN90P) and a decrease in cool days and nights (TX10P, TN10P). These changes pose particular risks for the area's agricultural workforce and older residents, highlighting the growing impact of climate change on the region. - - - - ## Choctaw County -
- - - Significant Trends in Climate Extremes from MERRA-2 (1980-2023): Slope Analysis (p < 0.1) - -
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- - - ## Butler County -
- - - Significant Trends in Climate Extremes from MERRA-2 (1980-2023): Slope Analysis (p < 0.1) - -
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- - - ## Pickens County -
- - - Significant Trends in Climate Extremes from MERRA-2 (1980-2023): Slope Analysis (p < 0.1) - -
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- - - ## Marengo County -
- - - Significant Trends in Climate Extremes from MERRA-2 (1980-2023): Slope Analysis (p < 0.1) - -
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- - -{/* - - - Increasing Warm Nights -

- The increasing occurrences of warm days and warm nights are significantly impacting the counties within Alabama's Black Belt. The colorbar illustrates the slope of the linear trend. -

- Increasing Warm Days -
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-*/} - -{/* - - - Increasing Warm Nights -

- Concurrently, the decreasing occurrences of cool days and cool nights are also affecting the region. -

- Increasing Warm Days -
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-*/} - - - -

- Agriculture remains the backbone of the Black Belt's economy, with many older adults working in the fields. This reliance on an aging workforce is concerning, particularly as the physical demands of farming intensify with rising temperatures. In Sumter County, the number of farm operators aged 55 and above is increasing, reflecting a broader national trend where the average age of U.S. farm producers has risen to 58.1 years by 2022. -

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- Additionally, outdoor occupations such as transportation and construction have become crucial sources of income and have shown growth over the past few years. Data from the U.S. Census Bureau, which examines the number of establishments by employment category in counties like Choctaw and Butler, underscores the economic importance of these sectors. -

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- The combination of rising temperatures and an older workforce underscores the urgent need for adaptive strategies to protect both the health of the population and the viability of these economic sectors.Addressing these intertwined challenges requires targeted policies and investments in climate resilience measures. By enhancing education, healthcare, and job opportunities, along with adopting sustainable agricultural practices, the Black Belt can work towards a more resilient and prosperous future in the face of climate change. - ### To mitigate heat-related risks, several safeguards can be implemented: - - Improved Access to Cooling Centers: Establishing more cooling centers in rural areas can provide relief during extreme heat events. - - Health Monitoring Programs: Implementing regular health check-ups for older adults working in agriculture can help prevent heat-related illnesses. - - Education and Training: Providing training on heat safety and recognizing symptoms of heat stress can empower workers to take preventive actions. - - Flexible Work Schedules: Adjusting work hours to cooler parts of the day can reduce exposure to extreme heat. -

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- ### Data Access - * [NASA Description for MERRA-2 Climate Indices ](https://search.earthdata.nasa.gov/search/granules?p=C1949649168-GES_DISC&pg[0][v]=f&pg[0][gsk]=-start_date&q=MERRA-2%20extremes&tl=1724265744.288!3!!/) - * [CDC/ATSDR SVI Data and Documentation Download | Place and Health | ATSDR](https://www.atsdr.cdc.gov/placeandhealth/svi/data_documentation_download.html) - * [United States Department of Agriculture (USDA) | National Agricultural Statistics Service (NASS) | Census](https://www.nass.usda.gov/) - * [Census Bureau Data | Occupation](https://www.census.gov/topics/employment/industry-occupation.html)] -

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- **Editor**: Maheshwari Neelam and Derek Koehl; - **Developers**: Andrew Blackford, Trent Cowan, Jerika Christman, Brian Freitag, and Aaron Kaulfus ; - **Science and Content Contributors**: Maheshwari Neelam and Udaysankar Nair; - **Acknowledgements**: All individuals dedicated to Environmental Justice ; - **Questions / Feedback (email address)**: maheshwari.neelam@nasa.gov -

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- #### Additional Resources - * https://blogs.edf.org/growingreturns/2023/08/02/heat-threat-for-farmworkers/ - * https://www.thenation.com/article/society/black-farmers-pigford-debt/ - * https://foodprint.org/issues/black-land-loss-in-the-united-states/ - * https://inthesetimes.com/article/black-farmers-stress-debt-land-loss-racism-mental-health-crisis -

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a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -1,6 +1,6 @@ --- id: black-belt-climate -name: Climate Extremes Aggrevate Social Vulnerabilities in Alabama's Black Belt +name: Climate Extremes Aggravate Social Vulnerabilities in Alabama's Black Belt description: "Rising temperatures worsen social vulnerabilities for elder population by increasing their heat-related health risks." media: src: ::file ./black_belt_cover.jpg @@ -32,7 +32,7 @@ taxonomy: - +

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--- stories/black-belt-climate-ej.stories.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/stories/black-belt-climate-ej.stories.mdx b/stories/black-belt-climate-ej.stories.mdx index 5fdd690c0..8a689fa83 100644 --- a/stories/black-belt-climate-ej.stories.mdx +++ b/stories/black-belt-climate-ej.stories.mdx @@ -33,7 +33,7 @@ taxonomy: - The Black Belt is a region in the Southern United States. The term "Black Belt" originally referred to the region's fertile black soil, ideal for agriculture, particularly cotton plantations. The fertile soil of the Black Belt is intricately connected to the weathering of limestone bases in the Selma Chalk region, which dates back to the Cretaceous Period when the Gulf of Mexico's shoreline was much further inland. Over millions of years, plankton deposited exoskeletons rich in calcium carbonate, leading to the formation of soft limestone known as Selma Chalk. This geological process resulted in a chalky subsoil that, due to its high calcium content, provides exceptional fertility, making the Black Belt particularly suitable for agriculture. + The Black Belt is a region in the Southern United States OF America. The term "Black Belt" originally referred to the region's fertile black soil, ideal for agriculture, particularly cotton plantations. The fertile soil of the Black Belt is intricately connected to the weathering of limestone bases in the Selma Chalk region, which dates back to the Cretaceous Period when the Gulf of Mexico's shoreline was much further inland. Over millions of years, plankton deposited exoskeletons rich in calcium carbonate, leading to the formation of soft limestone known as Selma Chalk. This geological process resulted in a chalky subsoil that, due to its high calcium content, provides exceptional fertility, making the Black Belt particularly suitable for agriculture.