diff --git a/.gitignore b/.gitignore
index 8cf7e82..8b1d724 100644
--- a/.gitignore
+++ b/.gitignore
@@ -5,3 +5,4 @@
/.quarto/
/_book/
.DS_Store
+tmp
diff --git a/data.qmd b/data.qmd
index c6ddec7..8ca6c68 100644
--- a/data.qmd
+++ b/data.qmd
@@ -39,6 +39,8 @@ options(readr.show_col_types = F)
## Temperature
+
+
### Observed
The [`rnoaa`](https://docs.ropensci.org/rnoaa/) R package uses NOAA NCDC API v2, which only goes to 2022-09-15.
@@ -51,7 +53,7 @@ The [`rnoaa`](https://docs.ropensci.org/rnoaa/) R package uses NOAA NCDC API v2,
* [Tampa International Airport](https://www.ncdc.noaa.gov/cdo-web/datasets/GHCND/stations/GHCND:USW00012842/detail)
- Start Date: 1939-02-01
- - End Date: 2024-01-07
+ - End Date: today - 3 days
Got token at [ncdc.noaa.gov/cdo-web/token](https://www.ncdc.noaa.gov/cdo-web/token). Added variable `NOAA_NCDC_CDO_token` to:
@@ -75,7 +77,7 @@ Got token at [ncdc.noaa.gov/cdo-web/token](https://www.ncdc.noaa.gov/cdo-web/tok
options(noaakey = Sys.getenv("NOAA_NCDC_CDO_token"))
# Specify datasetid and station
-stn <- "GHCND:USW00012842" # TAMPA INTERNATIONAL AIRPORT, FL US
+stn <- "GHCND:USW00012842" # TAMPA INTERNATIONAL AIRPORT, FL US
stn_csv <- here("data/tpa_ghcnd.csv")
stn_meta_csv <- here("data/tpa_meta.csv")
@@ -185,11 +187,337 @@ d |>
```
-#### Satellite
+TODO:
+- trend analysis. e.g. [NOAA's Climate at a Glance](https://www.ncdc.noaa.gov/cag/global/time-series/globe/land_ocean/ytd/12/1880-2020). Typically based on the last 30 years, but here we've got back to 1939-02-01 so almost 100 years. Keep it 5 years and see how rate changing over time.
+
+- severe weather events? "Sea-level rise exponentially increases coastal flood frequency Mohsen taherkhani"
+#### Satellite
## Precipitation
+Materials:
+
+* "RAIN AS A DRIVER" in [tbep-os-presentations/state\_of\_the\_bay\_2023.qmd](https://github.com/tbep-tech/tbep-os-presentations/blob/6ff9054aa0eb1f194a9a28e3dc8b1eff02b6a58f/state_of_the_bay_2023.qmd#L354)
+
+* [Precipitation - NEXRAD QPE CDR | National Centers for Environmental Information (NCEI)](https://www.ncei.noaa.gov/products/climate-data-records/precipitation-nexrad-qpe)
+
+```{r}
+#| eval: FALSE
+
+librarian::shelf(
+ dplyr, here, mapview, readxl, sf, tbep-tech/tbeptools)
+# register with renv
+library(dplyr)
+library(here)
+library(mapview)
+library(readxl)
+library(sf)
+library(tbeptools)
+
+# from SWFWMD grid cells, use only if interested in areas finer than TB watershed
+# this currently gets the same data as the compiled spreadsheet
+grd <- st_read(here('../tbep-os-presentations/data/swfwmd-GARR-gisfiles-utm/swfwmd_pixel_2_utm_m_83.shp'), quiet = T)
+mapView(grd)
+
+tbgrdcent <- grd %>%
+ st_transform(crs = st_crs(tbshed)) %>%
+ st_centroid() %>%
+ .[tbshed, ]
+
+# unzip folders
+loc <- here('../tbep-os-presentations/data/swfwmd_rain')
+# files <- list.files(loc, pattern = '.zip', full.names = T)
+# lapply(files, unzip, exdir = loc)
+
+# read text files
+raindat <- list.files(loc, pattern = '19.*\\.txt$|20.*\\.txt$', full.names = T) %>%
+ lapply(read.table, sep = ',', header = F) %>%
+ do.call('rbind', .) %>%
+ rename(
+ 'PIXEL' = V1,
+ 'yr' = V2,
+ 'inches' = V3) %>%
+ filter(PIXEL %in% tbgrdcent$PIXEL)
+
+# ave rain dat
+raindatave <- raindat %>%
+ summarise(
+ inches = mean(inches, na.rm = T),
+ .by = 'yr')
+
+##
+# use compiled SWFWMD data
+
+# # https://www.swfwmd.state.fl.us/resources/data-maps/rainfall-summary-data-region
+# # file is from the link "USGS watershed"
+# download.file(
+# 'https://www4.swfwmd.state.fl.us/RDDataImages/surf.xlsx?_ga=2.186665249.868698214.1705929229-785009494.1704644825',
+# here('data/swfwmdrainfall.xlsx'),
+# mode = 'wb'
+# )
+
+raindatave_url <- "https://www4.swfwmd.state.fl.us/RDDataImages/surf.xlsx"
+dir.create(here('data/swfwmd.state.fl.us'))
+raindatave_xl <- here('data/swfwmd.state.fl.us/surf.xlsx')
+
+download.file(raindatave_url, raindatave_xl)
+read_excel(raindatave_xl)
+
+download.file(raindatave_url, here('data/swfwmdrainfall.xlsx'), mode = 'wb')
+
+raindatave <- read_excel(
+ raindatave_xl, sheet = 'ann-usgsbsn', skip = 1) %>%
+ filter(Year %in% 1975:2023) %>%
+ select(
+ yr = Year,
+ inches = `Tampa Bay/Coastal Areas`
+ ) %>%
+ mutate_all(as.numeric)
+
+raindatave_now <-
+readxl::read_excel()
+
+raindatave <- read_excel(here('data/swfwmdrainfall.xlsx'), sheet = 'ann-usgsbsn', skip = 1) %>%
+ filter(Year %in% 1975:2023) %>%
+ select(
+ yr = Year,
+ inches = `Tampa Bay/Coastal Areas`
+ ) %>%
+ mutate_all(as.numeric)
+
+# ave chldat
+chlave <- anlz_avedat(epcdata) %>%
+ .$ann %>%
+ filter(var == 'mean_chla') %>%
+ summarise(
+ chla = mean(val, na.rm = T),
+ .by = 'yr'
+ ) %>%
+ filter(yr >= 1975)
+
+toplo <- inner_join(chlave, raindatave, by = 'yr')
+
+p1 <- ggplot(raindatave, aes(x = yr, y = inches)) +
+ geom_line() +
+ geom_point() +
+ geom_point(data = raindatave[chlave$yr == 2023, ], col = 'red', size = 2) +
+ theme_minimal() +
+ theme(
+ panel.grid.minor = element_blank(),
+ ) +
+ labs(
+ x = NULL,
+ y = 'Annual rainfall (inches)',
+ title = 'Annual rainfall',
+ subtitle = 'Tampa Bay watershed, 1975 - 2023'
+ )
+
+p2 <- ggplot(chlave, aes(x = yr, y = chla)) +
+ geom_line() +
+ geom_point() +
+ geom_point(data = chlave[chlave$yr == 2023, ], col = 'red', size = 2) +
+ theme_minimal() +
+ theme(
+ panel.grid.minor = element_blank(),
+ ) +
+ labs(
+ x = NULL,
+ y = 'Chlorophyll-a (ug/L)',
+ title = 'Annual mean chlorophyll-a',
+ subtitle = 'All segments, 1975 - 2023'
+ )
+
+p3 <- ggplot(toplo, aes(x = inches, y = chla)) +
+ geom_text_repel(aes(label = yr), point.size = NA, segment.size = NA) +
+ geom_label_repel(data = toplo[toplo$yr == 2023, ], aes(label = yr), color = 'red', point.size = NA) +
+ geom_smooth(formula = y ~ x, method = 'lm', se = F, color = 'red') +
+ # geom_segment(aes(x = 45, xend = 40, y = 4.86, yend = 4.86), color = 'red', arrow = arrow(length = unit(0.2, "inches")), linewidth = 1) +
+ theme_minimal() +
+ theme(
+ panel.grid.minor = element_blank(),
+ ) +
+ labs(
+ x = 'Annual rainfall (inches)',
+ y = 'Chlorophyll-a (ug/L)',
+ title = 'Annual mean chlorophyll-a vs. rainfall',
+ caption = 'Data from EPCHC, SWFWMD'
+ )
+
+p <- (p1 / p2) | p3
+p
+```
+
+### rNOMADS
+
+```{r}
+# librarian::shelf(rNOMADS)
+
+
+```
+
+### prism
+
+* [HMS: Hydrologic Micro Services | United States Environmental Protection Agency | US EPA](https://qed.epa.gov/hms/meteorology/humidity/algorithms/)
+
+> The [Parameter-elevation Relationship on Independent Slopes Model (PRISM)](https://prism.oregonstate.edu/) is a combined dataset consisting of ground gauge station and RADAR products. The data is on a 4km grid resolution covering the contiguous United States. Data is available from 1981 to present.PRISM data are reported in GMT (UTC). PRISM provides daily average temperature and dew-point temperature data. Relative humidity is calculated using a version of the [August-Roche-Magnus equation](https://bmcnoldy.rsmas.miami.edu/Humidity.html) as follows ): `RH = 100*(EXP((17.625*TD)/(243.04+TD))/EXP((17.625*T)/(243.04+T)))` where, `RH` is % relative humidity, `TD` is dew-point temperature (celsius), and `T` is air temperature (celsius).
+
+* [AHPS Precipitation Analysis](https://water.weather.gov/precip/about.php)
+
+ > "Normal" precipitation is derived from PRISM climate data, created at Oregon State University. The PRISM gridded climate maps are considered the most detailed, highest-quality spatial climate datasets currently available.
+
+* [prism](https://docs.ropensci.org/prism/articles/prism.html#prism-data-and-parameters) R package
+
+Parameter | Description
+----------|-------------
+`tmin` | Minimum temperature
+`tmax` | Maximum temperature
+`tmean` | Mean temperature (`tmean == mean(tmin, tmax)`)
+`tdmean` | Mean dew point temperature
+`ppt` | Total precipitation (rain and snow)
+`vpdmin` | Daily minimum vapor pressure deficit
+`vpdmax` | Daily maximum vapor pressure deficit
+
+> Data are at 4km resolution, except for the normals which can also be downloaded at 800m resolution.
+
+Temporal data availability:
+
+- **Recent**\
+ 1981 to present\
+ daily, monthly, annual data
+
+- **Historical**\
+ 1895 through 1980\
+ complete monthly and annual data by year
+
+- **Normals**\
+ 30-year normals
+ daily, monthly, and annual normals, each as a single grid
+ The 30 year PRISM normal from 1981-2010 is used for precipitation analysis since 2004. Prior to 2004 the 30 year PRISM normal from 1961-1990 is used.
+
+```{r}
+#| label: get prism
+#| messages: false
+#| warning: false
+
+librarian::shelf(glue, here, lubridate, mapview, prism, stars, stringr, tbep-tech/tbeptools, terra)
+# renv register libraries
+library(glue)
+library(here)
+library(lubridate)
+library(mapview)
+library(prism)
+library(stars)
+library(stringr)
+library(tbeptools)
+library(terra)
+
+dir_prism <- here("tmp/prism")
+dir.create(dir_prism, showWarnings = F)
+prism_set_dl_dir(dir_prism)
+
+# get_prism_dailys(
+# type = "tmean",
+# minDate = today() - days(8),
+# maxDate = today() - days(1), # up to yesterday
+# keepZip = F)
+# prism_archive_clean("tmean")
+# https://prism.nacse.org/downloads/
+# https://prism.nacse.org/documents/PRISM_downloads_web_service.pdf
+# http://services.nacse.org/prism/data/public/4km/tmin/20090405
+
+# get_prism_dailys(
+# type = "tmin",
+# minDate = "2024-01-01",
+# maxDate = "2024-03-07",
+# keepZip = F)
+#
+# get_prism_dailys(
+# type = "tmax",
+# minDate = "2024-01-01",
+# maxDate = "2024-03-07",
+# keepZip = F)
+
+# Get monthly (every month) and annual 30-year normals for precipitation
+# get_prism_normals(
+# type = "ppt",
+# resolution = "800m",
+# mon = 1:12,
+# annual = TRUE,
+# keepZip = FALSE)
+
+# Plot the January 30-year average temperatures
+# grab only the first value, just in case multiple values are returned
+# pd_tmean_day <- prism_archive_subset(
+# "tmean", "daily", dates = "2024-03-07")
+# Error in pd_image(pd_tmean_day, col = "redblue") :
+# You can only quick image one file at a time.
+# > pd_tmean_day
+# [1] "PRISM_tmean_early_4kmD2_20240307_bil" "PRISM_tmean_provisional_4kmD2_20240307_bil"
+# prism_archive_clean("tmean", "daily") # 'cleans' the prism download data by removing early and/or provisional data if newer (provisional or stable) data also exist for the same variable and temporal period
+pd_tmean_day <- prism_archive_subset(
+ "tmean", "daily", dates = "2024-03-07")
+pd_image(pd_tmean_day, col="redblue")
+
+pd_ppt_nrml <- prism_archive_subset(
+ "ppt", "monthly normals",
+ mon = 1, resolution = "800m")
+(path_ppt_nrml <- pd_to_file(pd_ppt_nrml))
+
+# raster stack ----
+var <- "tmean"
+period <- "daily"
+
+get_prism_dailys(
+ type = var,
+ minDate = today() - days(3), # last 3 days
+ maxDate = today() - days(1), # up to yesterday
+ keepZip = F)
+prism_archive_clean(var, period)
+
+pd <- prism_archive_subset(var, period)
+pd_dates <- pd_get_date(pd)
+
+r <- pd_stack(pd) |>
+ rast()
+# tbshed_pd <- tbshed |>
+tbshed_pd <- tbsegshed |>
+ st_transform(crs(r, proj=T))
+r_tb <- r |>
+ crop(tbshed_pd, mask = T, touches = T) |>
+ trim()
+
+# TODO: summarize by tbeptools::tbsegshed, zip code
+
+# r_tif <- here("tmp/prism", glue("tmean_20240307_bil")
+# terra::writeRaster(r_tb, , overwrite = T)
+
+date <- max(pd_dates)
+i <- which(pd_dates == date)
+lyr <- glue("{var}
{period}
{date}")
+
+# terra::writeRaster(r_tb[[i]], here("tmp", glue("{var}_{date}.tif")), overwrite = T)
+
+mapView(r_tb[[i]], layer.name = lyr) +
+ mapView(tbshed_pd)
+```
+
+
+TODO:
+
+- [ ] compare these precip data w/ Water District data to make case for using PRISM data
+
+Questions:
+
+1. Given variability within each polygon, which of these products shall we use to plot: min(min_temp), mean(mean_temp), max(max_temp); min(mean_temp), mean(mean_temp), max(max_temp)?
+
+### Communicating results
+
+* Choi et al. (2024) [North-South disparity in impact of climate change on “outdoor days”](https://journals.ametsoc.org/view/journals/clim/aop/JCLI-D-23-0346.1/JCLI-D-23-0346.1.xml). _Journal of Climate_
+ * news summary: [A new way to quantify climate change impacts: “Outdoor days” | MIT News | Massachusetts Institute of Technology](https://news.mit.edu/2024/new-way-quantify-climate-change-impacts-outdoor-days-0322)
+ * Shiny app: [California Outdoor Days | Eltahir Research Group](https://eltahir.mit.edu/california-outdoor-days/)
+
+
## Sea Level Rise
Sea level rise occurs from principally two sources: 1) thermal expansion; and 2) freshwater inputs from glacial melting. Data for these trends can be obtained from NOAA's [Sea Level Trends](https://tidesandcurrents.noaa.gov/sltrends/sltrends.html) (@fig-slr-noaa)
@@ -208,6 +536,17 @@ Types of data:
* [PORTS: Tampa Bay PORTS - NOAA Tides & Currents](https://tidesandcurrents.noaa.gov/ports/index.html?port=tb)
+```{r}
+librarian::shelf(
+ ropensci/rnoaa)
+# register with renv
+library(rnoaa)
+
+
+
+```
+
+
### Satellite
* [NOAA / NESDIS / STAR - Laboratory for Satellite Altimetry / Sea Level Rise](https://www.star.nesdis.noaa.gov/socd/lsa/SeaLevelRise/LSA_SLR_maps.php)
diff --git a/data/swfwmd.state.fl.us/surf.xlsx b/data/swfwmd.state.fl.us/surf.xlsx
new file mode 100644
index 0000000..548a72f
Binary files /dev/null and b/data/swfwmd.state.fl.us/surf.xlsx differ
diff --git a/renv.lock b/renv.lock
index 1fccc7d..998154b 100644
--- a/renv.lock
+++ b/renv.lock
@@ -51,14 +51,14 @@
},
"DBI": {
"Package": "DBI",
- "Version": "1.2.0",
+ "Version": "1.2.2",
"Source": "Repository",
"Repository": "RSPM",
"Requirements": [
"R",
"methods"
],
- "Hash": "3e0051431dff9acfe66c23765e55c556"
+ "Hash": "164809cd72e1d5160b4cb3aa57f510fe"
},
"KernSmooth": {
"Package": "KernSmooth",
@@ -73,9 +73,9 @@
},
"MASS": {
"Package": "MASS",
- "Version": "7.3-60",
+ "Version": "7.3-60.0.1",
"Source": "Repository",
- "Repository": "CRAN",
+ "Repository": "RSPM",
"Requirements": [
"R",
"grDevices",
@@ -84,13 +84,13 @@
"stats",
"utils"
],
- "Hash": "a56a6365b3fa73293ea8d084be0d9bb0"
+ "Hash": "b765b28387acc8ec9e9c1530713cb19c"
},
"Matrix": {
"Package": "Matrix",
- "Version": "1.6-4",
+ "Version": "1.6-5",
"Source": "Repository",
- "Repository": "CRAN",
+ "Repository": "RSPM",
"Requirements": [
"R",
"grDevices",
@@ -101,7 +101,7 @@
"stats",
"utils"
],
- "Hash": "d9c655b30a2edc6bb2244c1d1e8d549d"
+ "Hash": "8c7115cd3a0e048bda2a7cd110549f7a"
},
"R6": {
"Package": "R6",
@@ -125,18 +125,18 @@
},
"Rcpp": {
"Package": "Rcpp",
- "Version": "1.0.11",
+ "Version": "1.0.12",
"Source": "Repository",
"Repository": "RSPM",
"Requirements": [
"methods",
"utils"
],
- "Hash": "ae6cbbe1492f4de79c45fce06f967ce8"
+ "Hash": "5ea2700d21e038ace58269ecdbeb9ec0"
},
"XML": {
"Package": "XML",
- "Version": "3.99-0.16",
+ "Version": "3.99-0.16.1",
"Source": "Repository",
"Repository": "RSPM",
"Requirements": [
@@ -144,7 +144,19 @@
"methods",
"utils"
],
- "Hash": "131e2febe15d5bbca3a37bd69e71b873"
+ "Hash": "da3098169c887914551b607c66fe2a28"
+ },
+ "abind": {
+ "Package": "abind",
+ "Version": "1.4-5",
+ "Source": "Repository",
+ "Repository": "RSPM",
+ "Requirements": [
+ "R",
+ "methods",
+ "utils"
+ ],
+ "Hash": "4f57884290cc75ab22f4af9e9d4ca862"
},
"askpass": {
"Package": "askpass",
@@ -190,6 +202,13 @@
],
"Hash": "9fe98599ca456d6552421db0d6772d8f"
},
+ "brew": {
+ "Package": "brew",
+ "Version": "1.0-10",
+ "Source": "Repository",
+ "Repository": "RSPM",
+ "Hash": "8f4a384e19dccd8c65356dc096847b76"
+ },
"bslib": {
"Package": "bslib",
"Version": "0.6.1",
@@ -224,7 +243,7 @@
},
"callr": {
"Package": "callr",
- "Version": "3.7.3",
+ "Version": "3.7.5",
"Source": "Repository",
"Repository": "RSPM",
"Requirements": [
@@ -233,7 +252,7 @@
"processx",
"utils"
],
- "Hash": "9b2191ede20fa29828139b9900922e51"
+ "Hash": "9f0e4fae4963ba775a5e5c520838c87b"
},
"cellranger": {
"Package": "cellranger",
@@ -249,7 +268,7 @@
},
"chromote": {
"Package": "chromote",
- "Version": "0.1.2",
+ "Version": "0.2.0",
"Source": "Repository",
"Repository": "RSPM",
"Requirements": [
@@ -262,9 +281,10 @@
"processx",
"promises",
"rlang",
+ "utils",
"websocket"
],
- "Hash": "14c8f71bf7b112634b154f8a6a0867e1"
+ "Hash": "3cfaf9cbd331e07055acada321664e12"
},
"class": {
"Package": "class",
@@ -332,10 +352,10 @@
},
"commonmark": {
"Package": "commonmark",
- "Version": "1.9.0",
+ "Version": "1.9.1",
"Source": "Repository",
"Repository": "RSPM",
- "Hash": "d691c61bff84bd63c383874d2d0c3307"
+ "Hash": "5d8225445acb167abf7797de48b2ee3c"
},
"cpp11": {
"Package": "cpp11",
@@ -389,28 +409,28 @@
},
"curl": {
"Package": "curl",
- "Version": "5.2.0",
+ "Version": "5.2.1",
"Source": "Repository",
"Repository": "RSPM",
"Requirements": [
"R"
],
- "Hash": "ce88d13c0b10fe88a37d9c59dba2d7f9"
+ "Hash": "411ca2c03b1ce5f548345d2fc2685f7a"
},
"data.table": {
"Package": "data.table",
- "Version": "1.14.10",
+ "Version": "1.15.2",
"Source": "Repository",
"Repository": "RSPM",
"Requirements": [
"R",
"methods"
],
- "Hash": "6ea17a32294d8ca00455825ab0cf71b9"
+ "Hash": "536dfe4ac4093b5d115caed7a1a7223b"
},
"dataRetrieval": {
"Package": "dataRetrieval",
- "Version": "2.7.14",
+ "Version": "2.7.15",
"Source": "Repository",
"Repository": "RSPM",
"Requirements": [
@@ -424,18 +444,18 @@
"utils",
"xml2"
],
- "Hash": "6f41d853cf2b5d150c3d8de9fe9eca42"
+ "Hash": "fafb396875c3d89fd8e8e91789d2192f"
},
"digest": {
"Package": "digest",
- "Version": "0.6.33",
+ "Version": "0.6.34",
"Source": "Repository",
- "Repository": "CRAN",
+ "Repository": "RSPM",
"Requirements": [
"R",
"utils"
],
- "Hash": "b18a9cf3c003977b0cc49d5e76ebe48d"
+ "Hash": "7ede2ee9ea8d3edbf1ca84c1e333ad1a"
},
"dplyr": {
"Package": "dplyr",
@@ -541,7 +561,7 @@
},
"flextable": {
"Package": "flextable",
- "Version": "0.9.4",
+ "Version": "0.9.5",
"Source": "Repository",
"Repository": "RSPM",
"Requirements": [
@@ -561,7 +581,7 @@
"uuid",
"xml2"
],
- "Hash": "db48820af2b3e5afa64726cf5615da27"
+ "Hash": "703b952d6be3f841274df7831ec95e5d"
},
"fontBitstreamVera": {
"Package": "fontBitstreamVera",
@@ -620,7 +640,7 @@
},
"gdtools": {
"Package": "gdtools",
- "Version": "0.3.5",
+ "Version": "0.3.7",
"Source": "Repository",
"Repository": "RSPM",
"Requirements": [
@@ -633,7 +653,7 @@
"systemfonts",
"tools"
],
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"generics": {
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@@ -646,6 +666,31 @@
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+ "Source": "Repository",
+ "Repository": "RSPM",
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+ "rapidjsonr",
+ "sfheaders"
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+ "Hash": "8d077646c6713838233e8710910ef92e"
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@@ -676,7 +721,7 @@
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+ "Version": "3.5.0",
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@@ -697,18 +742,18 @@
"vctrs",
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],
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+ "Hash": "52ef83f93f74833007f193b2d4c159a2"
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+ "Version": "1.7.0",
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+ "Repository": "RSPM",
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"methods"
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+ "Hash": "e0b3a53876554bd45879e596cdb10a52"
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"gridExtra": {
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@@ -776,7 +821,7 @@
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+ "Version": "0.5.4",
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@@ -784,7 +829,7 @@
"digest",
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+ "Hash": "2f50e36abbb197b70c7dd55e7592b4f5"
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"htmltools": {
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@@ -827,7 +872,7 @@
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@@ -838,7 +883,7 @@
"promises",
"utils"
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+ "Hash": "16abeb167dbf511f8cc0552efaf05bab"
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"httr": {
"Package": "httr",
@@ -888,6 +933,18 @@
],
"Hash": "5aab57a3bd297eee1c1d862735972182"
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+ "Package": "jsonify",
+ "Version": "1.2.2",
+ "Source": "Repository",
+ "Repository": "RSPM",
+ "Requirements": [
+ "R",
+ "Rcpp",
+ "rapidjsonr"
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+ "Hash": "49a9775e4f8c96c654b6018739067055"
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@@ -961,6 +1018,25 @@
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"Hash": "d908914ae53b04d4c0c0fd72ecc35370"
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+ "Package": "leafem",
+ "Version": "0.2.3",
+ "Source": "Repository",
+ "Repository": "RSPM",
+ "Requirements": [
+ "R",
+ "base64enc",
+ "geojsonsf",
+ "htmltools",
+ "htmlwidgets",
+ "leaflet",
+ "methods",
+ "png",
+ "raster",
+ "sf"
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+ "Hash": "6b43f986a9a0c1c1810b2deec71bfdf2"
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@@ -997,6 +1073,22 @@
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"Hash": "c0b81ad9d5d932772f7a457ac398cf36"
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+ "Version": "0.1.0",
+ "Source": "Repository",
+ "Repository": "RSPM",
+ "Requirements": [
+ "base64enc",
+ "brew",
+ "htmltools",
+ "htmlwidgets",
+ "sf",
+ "svglite",
+ "uuid"
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+ "Hash": "0c1e9e9a79598ec5acb1820d1948dae8"
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@@ -1047,6 +1139,31 @@
],
"Hash": "7ce2733a9826b3aeb1775d56fd305472"
},
+ "mapview": {
+ "Package": "mapview",
+ "Version": "2.11.2",
+ "Source": "Repository",
+ "Repository": "RSPM",
+ "Requirements": [
+ "R",
+ "base64enc",
+ "htmltools",
+ "htmlwidgets",
+ "lattice",
+ "leafem",
+ "leaflet",
+ "leafpop",
+ "methods",
+ "png",
+ "raster",
+ "satellite",
+ "scales",
+ "servr",
+ "sf",
+ "sp"
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+ "Hash": "58f4c5693a12fd108a0c7996c18ebfba"
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@@ -1060,9 +1177,9 @@
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+ "Version": "1.9-1",
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- "Repository": "CRAN",
+ "Repository": "RSPM",
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"R",
@@ -1073,7 +1190,7 @@
"stats",
"utils"
],
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+ "Hash": "110ee9d83b496279960e162ac97764ce"
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"mime": {
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@@ -1112,7 +1229,7 @@
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@@ -1127,7 +1244,7 @@
"xml2",
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],
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+ "Hash": "3a71a529237487233ead151cba12be3f"
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"openssl": {
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@@ -1186,7 +1303,7 @@
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@@ -1214,7 +1331,18 @@
"vctrs",
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+ "Hash": "a1ac5c03ad5ad12b9d1597e00e23c3dd"
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+ "Repository": "RSPM",
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"png": {
"Package": "png",
@@ -1236,6 +1364,23 @@
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+ "Source": "Repository",
+ "Repository": "RSPM",
+ "Requirements": [
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+ "ggplot2",
+ "httr",
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+ "raster",
+ "readr",
+ "stringr",
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@@ -1293,14 +1438,14 @@
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+ "Hash": "dd2b9319ee0656c8acf45c7f40c59de7"
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"purrr": {
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@@ -1328,6 +1473,13 @@
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+ "Repository": "RSPM",
+ "Hash": "88b9f48c93d17cdb811b54079a6a414f"
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@@ -1379,7 +1531,7 @@
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@@ -1398,7 +1550,7 @@
"utils",
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"readxl": {
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@@ -1458,20 +1610,20 @@
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+ "Repository": "RSPM",
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@@ -1482,20 +1634,24 @@
"jsonlite",
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"methods",
- "stringr",
"tinytex",
"tools",
"utils",
"xfun",
"yaml"
],
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"rnoaa": {
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"Version": "1.4.0",
- "Source": "Repository",
- "Repository": "RSPM",
+ "Source": "GitHub",
+ "RemoteType": "github",
+ "RemoteHost": "api.github.com",
+ "RemoteUsername": "ropensci",
+ "RemoteRepo": "rnoaa",
+ "RemoteRef": "master",
+ "RemoteSha": "95868c968c62768fe7e8143a8f631b97de120910",
"Requirements": [
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"crul",
@@ -1515,7 +1671,7 @@
"utils",
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@@ -1553,6 +1709,27 @@
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+ "Repository": "RSPM",
+ "Requirements": [
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+ "Rcpp",
+ "grDevices",
+ "graphics",
+ "methods",
+ "plyr",
+ "raster",
+ "stats",
+ "stats4",
+ "terra",
+ "tools",
+ "utils"
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@@ -1573,6 +1750,20 @@
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"Hash": "c19df082ba346b0ffa6f833e92de34d1"
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+ "Version": "0.30",
+ "Source": "Repository",
+ "Repository": "RSPM",
+ "Requirements": [
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+ "jsonlite",
+ "mime",
+ "xfun"
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+ "Hash": "562294886e51319dfad3f3e6e61fb0b8"
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@@ -1596,6 +1787,18 @@
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"Hash": "f432b3379fb1a47046e253468b6b6b6d"
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+ "Version": "0.4.4",
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+ "Repository": "RSPM",
+ "Requirements": [
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+ "Rcpp",
+ "geometries"
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+ "Hash": "d63e904c63deda45f3f9149c7dcf8703"
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@@ -1642,7 +1845,7 @@
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@@ -1655,7 +1858,24 @@
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+ "rlang",
+ "sf",
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"stringi": {
"Package": "stringi",
@@ -1687,6 +1907,18 @@
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+ "Version": "2.1.3",
+ "Source": "Repository",
+ "Repository": "RSPM",
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+ "systemfonts"
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"sys": {
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@@ -1707,14 +1939,15 @@
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+ "Version": "2.0.1.9020",
"Source": "GitHub",
"RemoteType": "github",
- "RemoteHost": "api.github.com",
- "RemoteRepo": "tbeptools",
"RemoteUsername": "tbep-tech",
+ "RemoteRepo": "tbeptools",
"RemoteRef": "HEAD",
- "RemoteSha": "44c08a5262a1f1371e72161ffa8b66863df11daa",
+ "RemoteSha": "6fa2a75094008f8eeb60a84ab92c0a6b51d1da11",
+ "RemoteHost": "api.github.com",
+ "Remotes": "ropensci/rnoaa",
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@@ -1737,11 +1970,11 @@
"tidyr",
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@@ -1749,7 +1982,7 @@
"Rcpp",
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+ "Hash": "e8611881ab70a4fb7a1f629b31e6fcff"
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@@ -1784,7 +2017,7 @@
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@@ -1803,7 +2036,7 @@
"utils",
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+ "Hash": "915fb7ce036c22a6a33b5a8adb712eb1"
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@@ -1823,14 +2056,14 @@
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+ "Hash": "c5f3c201b931cd6474d17d8700ccb1c8"
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"tinytex": {
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@@ -1899,13 +2132,13 @@
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+ "Hash": "303c19bfd970bece872f93a824e323d9"
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@@ -1923,7 +2156,7 @@
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@@ -1932,7 +2165,7 @@
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@@ -2000,16 +2233,15 @@
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+ "Version": "3.0.0",
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"Requirements": [
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+ "Hash": "d31b6c62c10dcf11ec530ca6b0dd5d35"
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"wk": {
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@@ -2023,14 +2255,15 @@
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+ "Version": "0.42",
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"Repository": "RSPM",
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"stats",
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+ "Hash": "fd1349170df31f7a10bd98b0189e85af"
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"xml2": {
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@@ -2059,7 +2292,7 @@
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@@ -2067,7 +2300,7 @@
"methods",
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"yaml": {
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@@ -2078,10 +2311,10 @@
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+ "Hash": "fcc4bd8e6da2d2011eb64a5e5cc685ab"
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"zoo": {
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