Work in progress, contributions/input welcome
R wrapper for querying the Meteorological Service of Canada’s (MSC) GeoMet webservices.
Includes functionality for querying both the GeoMet Web Coverage Service (WCS) as well as the OGC OpenAPI endpoint.
For more information on both services, please see the official documentation.
mscgeometR is not available on CRAN, you can install it from GitHub
using remotes
remotes::install_github("rywhale/mscgeometR")Queries to the WCS endpoint require you to know the coverage ID of the
layer you’re after. You can get a full list of these IDs with
geomet_wcs_capabilities()
Setting the query parameters requires some familiarity with the product specification (e.g. resolution). Generally, specifying no “TIME” in the query will lead to the most recent product being returned.
Once you have the coverage ID, you can query data like so
library(raster)
#> Warning: package 'raster' was built under R version 4.1.3
#> Loading required package: sp
#> Warning: package 'sp' was built under R version 4.1.3
# Downloads to temporary .tif file
rdpa_file <- geomet_wcs_data(
# Regional Deterministic Precipitation Analysis
coverage_id = "RDPA.24F_PR",
# Set query parameters
query = list(
"SUBSETTINGCRS" = "EPSG:4326",
"OUTPUTCRS" = "EPSG:4326",
# Res
"RESOLUTION" = "x(0.09)",
"RESOLUTION" = "y(0.09)",
# Bounding box
"SUBSET" = "x(-96.3553, -89.8336)",
"SUBSET" = "y(47.3633, 52.0529)",
"TIME" = paste0(Sys.Date() - 1, "T12:00:00Z")
)
)
rdpa_rast <- raster(rdpa_file)
raster::crs(rdpa_rast) <- raster::crs("EPSG:4326")
plot(rdpa_rast)
geomet_wcs_data() downloads the query result to a GeoTIFF file in a
temporary directory. Restarting your R session will clear these
temporary files.
You can get a full list of the collections available with
geomet_api_collections()
#> # A tibble: 72 x 2
#> collection collection_id
#> <chr> <chr>
#> 1 Hydrometric Monitoring Stations hydrometric-sta~
#> 2 Daily Mean of Water Level or Flow hydrometric-dai~
#> 3 Monthly Mean of Water Level or Flow hydrometric-mon~
#> 4 Annual Maximum and Minimum Daily Water Level or Flow hydrometric-ann~
#> 5 Annual Maximum and Minimum Instantaneous Water Level or Flow hydrometric-ann~
#> 6 Real-time hydrometric data hydrometric-rea~
#> 7 1981-2010 Climate Normals climate-normals
#> 8 Climate Stations climate-stations
#> 9 Monthly Climate Observation Summaries climate-monthly
#> 10 Daily Climate Observations climate-daily
#> # ... with 62 more rowsThe collection_id values in the above table can then be used to list
potential query parameters for each collection, e.g. for hydrometric
stations
geomet_api_queryables("hydrometric-stations")
#> # A tibble: 9 x 2
#> queryable type
#> <chr> <chr>
#> 1 CONTRIBUTOR_EN string
#> 2 CONTRIBUTOR_FR string
#> 3 IDENTIFIER string
#> 4 PROV_TERR_STATE_LOC string
#> 5 STATION_NAME string
#> 6 STATION_NUMBER string
#> 7 STATUS_EN string
#> 8 STATUS_FR string
#> 9 VERTICAL_DATUM stringNote that boolean variables should be quoted, e.g. FALSE -> "false"
# View available stations
head(geomet_ahccd_stns())
#> identifier__identifiant station_id__id_station station_name__nom_station
#> 1 2403053 2403053 PANGNIRTUNG A
#> 2 2403201 2403201 POND INLET A
#> 3 2403450 2403450 REA POINT
#> 4 2403490 2403490 REPULSE BAY A
#> 5 2403625 2403625 ROWLEY ISLAND
#> 6 2403854 2403854 TALOYOAK A
#> measurement_type__type_mesure period__periode trend_value__valeur_tendance
#> 1 pressure_sea_level Ann NA
#> 2 pressure_sea_level Ann NA
#> 3 pressure_sea_level Ann NA
#> 4 pressure_sea_level Ann NA
#> 5 pressure_sea_level Ann NA
#> 6 pressure_sea_level Ann NA
#> elevation__elevation province__province joined__rejoint year_range__annees
#> 1 22.6 NU 1 <NA>
#> 2 55.2 NU 1 <NA>
#> 3 15.0 NU 0 <NA>
#> 4 24.4 NU 1 <NA>
#> 5 41.0 NU 0 <NA>
#> 6 28.0 NU 0 <NA>
#> start_date__date_debut end_date__date_fin coordinates
#> 1 2014-12-01 2014-12-01 -65.70, 66.13
#> 2 2014-09-01 2014-09-01 -77.98, 72.68
#> 3 2014-12-01 2014-12-01 -105.72, 75.38
#> 4 2014-12-01 2014-12-01 -86.22, 66.52
#> 5 2009-06-01 2009-06-01 -79.03, 69.08
#> 6 2014-12-01 2014-12-01 -93.58, 69.55
# Example query
ahccd_dat <- geomet_ahccd_data(
station_number = "3011120",
period = "year"
)
head(ahccd_dat)
#> lat__lat lon__long identifier__identifiant station_id__id_station
#> 1 53.2 -113.8 3011120.1936 3011120
#> 2 53.2 -113.8 3011120.1975 3011120
#> 3 53.2 -113.8 3011120.1982 3011120
#> 4 53.2 -113.8 3011120.1928 3011120
#> 5 53.2 -113.8 3011120.1918 3011120
#> 6 53.2 -113.8 3011120.1985 3011120
#> period_group__groupe_periode period_value__valeur_periode province__province
#> 1 Annual Ann AB
#> 2 Annual Ann AB
#> 3 Annual Ann AB
#> 4 Annual Ann AB
#> 5 Annual Ann AB
#> 6 Annual Ann AB
#> year__annee temp_mean__temp_moyenne temp_mean_units__temp_moyenne_unites
#> 1 1936 0.7 C
#> 2 1975 1.8 C
#> 3 1982 0.9 C
#> 4 1928 3.5 C
#> 5 1918 -9999.9 C
#> 6 1985 2.6 C
#> temp_min__temp_min temp_min_units__temp_min_unites temp_max__temp_max
#> 1 -6.1 C 7.6
#> 2 -4.6 C 8.2
#> 3 -5.6 C 7.3
#> 4 -3.9 C 10.8
#> 5 -9999.9 C -9999.9
#> 6 -3.7 C 9.0
#> temp_max_units__temp_max_unites total_precip__precip_totale
#> 1 C 488.1
#> 2 C 503.6
#> 3 C 624.9
#> 4 C -9999.9
#> 5 C -9999.9
#> 6 C 449.3
#> total_precip_units__precip_totale_unites rain__pluie rain_units__pluie_unites
#> 1 mm 291.8 mm
#> 2 mm 374.4 mm
#> 3 mm 402.8 mm
#> 4 mm -9999.9 mm
#> 5 mm -9999.9 mm
#> 6 mm 348.9 mm
#> snow__neige snow_units__neige_unites pressure_sea_level__pression_niveau_mer
#> 1 196.3 mm NA
#> 2 129.2 mm NA
#> 3 222.2 mm NA
#> 4 -9999.9 mm NA
#> 5 -9999.9 mm NA
#> 6 100.3 mm NA
#> pressure_sea_level_units__pression_niveau_mer_unite
#> 1 hPa
#> 2 hPa
#> 3 hPa
#> 4 hPa
#> 5 hPa
#> 6 hPa
#> pressure_station__pression_station
#> 1 NA
#> 2 NA
#> 3 NA
#> 4 NA
#> 5 NA
#> 6 NA
#> pressure_station_units__pression_station_unites wind_speed__vitesse_vent
#> 1 hPa NA
#> 2 hPa NA
#> 3 hPa NA
#> 4 hPa NA
#> 5 hPa NA
#> 6 hPa NA
#> wind_speed_units__vitesse_vent_unites coordinates
#> 1 kph -113.8, 53.2
#> 2 kph -113.8, 53.2
#> 3 kph -113.8, 53.2
#> 4 kph -113.8, 53.2
#> 5 kph -113.8, 53.2
#> 6 kph -113.8, 53.2# View available stations
clim_stns <- geomet_clim_stns()
# Lots of columns, here are the first few
head(clim_stns[, 1:5])
#> STN_ID STATION_NAME PROV_STATE_TERR_CODE ENG_PROV_NAME FRE_PROV_NAME
#> 1 2233 COWLEY A AB ALBERTA ALBERTA
#> 2 2241 FOREMOST EAST AB ALBERTA ALBERTA
#> 3 2252 HAYS AB ALBERTA ALBERTA
#> 4 2254 HERRONTON EAST AB ALBERTA ALBERTA
#> 5 2264 LETHBRIDGE BEGAMY AB ALBERTA ALBERTA
#> 6 2268 LOMOND AB ALBERTA ALBERTA
# Example query
clim_data <- geomet_clim_means(
station_number = "1126070",
start_date = "2016-01-01",
end_date = "2016-01-02"
)
head(clim_data)
#> STATION_NAME CLIMATE_IDENTIFIER ID LOCAL_DATE
#> 1 PEACHLAND 1126070 1126070.2016.1.1 2016-01-01 00:00:00
#> 2 PEACHLAND 1126070 1126070.2016.1.2 2016-01-02 00:00:00
#> PROVINCE_CODE LOCAL_YEAR LOCAL_MONTH LOCAL_DAY MEAN_TEMPERATURE
#> 1 BC 2016 1 1 -6.3
#> 2 BC 2016 1 2 -7.8
#> MEAN_TEMPERATURE_FLAG MIN_TEMPERATURE MIN_TEMPERATURE_FLAG MAX_TEMPERATURE
#> 1 NA -7.0 NA -5.5
#> 2 NA -9.5 NA -6.0
#> MAX_TEMPERATURE_FLAG TOTAL_PRECIPITATION TOTAL_PRECIPITATION_FLAG TOTAL_RAIN
#> 1 NA 0 NA 0
#> 2 NA 0 NA 0
#> TOTAL_RAIN_FLAG TOTAL_SNOW TOTAL_SNOW_FLAG SNOW_ON_GROUND SNOW_ON_GROUND_FLAG
#> 1 NA 0 NA 28 NA
#> 2 NA 0 NA 27 NA
#> DIRECTION_MAX_GUST DIRECTION_MAX_GUST_FLAG SPEED_MAX_GUST SPEED_MAX_GUST_FLAG
#> 1 NA NA NA NA
#> 2 NA NA NA NA
#> COOLING_DEGREE_DAYS COOLING_DEGREE_DAYS_FLAG HEATING_DEGREE_DAYS
#> 1 0 NA 24.3
#> 2 0 NA 25.8
#> HEATING_DEGREE_DAYS_FLAG MIN_REL_HUMIDITY MIN_REL_HUMIDITY_FLAG
#> 1 NA NA NA
#> 2 NA NA NA
#> MAX_REL_HUMIDITY MAX_REL_HUMIDITY_FLAG coordinates
#> 1 NA NA -119.71667, 49.78333
#> 2 NA NA -119.71667, 49.78333
# Normals
clim_normals <- geomet_clim_normals(station_number = "1126070")
head(clim_normals)
#> STATION_NAME CLIMATE_IDENTIFIER ID PERIOD CURRENT_FLAG NORMAL_CODE
#> 1 PEACHLAND 1126070 1046.24.8 NORM Y C
#> 2 PEACHLAND 1126070 1046.24.9 NORM Y C
#> 3 PEACHLAND 1126070 1046.24.10 NORM Y D
#> 4 PEACHLAND 1126070 1046.24.11 NORM Y C
#> 5 PEACHLAND 1126070 1046.24.12 NORM Y C
#> 6 PEACHLAND 1126070 1046.24.13 NORM Y D
#> NORMAL_ID PUBLICATION_CODE DATE_CALCULATED FIRST_OCCURRENCE_DATE
#> 1 24 1 2012-10-10 14:40:42 <NA>
#> 2 24 1 2012-10-10 14:40:42 <NA>
#> 3 24 1 2012-10-10 14:40:42 <NA>
#> 4 24 1 2012-10-10 14:40:42 <NA>
#> 5 24 1 2012-10-10 14:40:42 <NA>
#> 6 24 1 2012-10-10 14:40:42 <NA>
#> PROVINCE_CODE PERIOD_BEGIN PERIOD_END FIRST_YEAR FIRST_YEAR_NORMAL_PERIOD
#> 1 BC 1981 2010 NA 1983
#> 2 BC 1981 2010 NA 1983
#> 3 BC 1981 2010 NA 1983
#> 4 BC 1981 2010 NA 1983
#> 5 BC 1981 2010 NA 1982
#> 6 BC 1981 2010 NA 1982
#> LAST_YEAR LAST_YEAR_NORMAL_PERIOD YEAR_COUNT_NORMAL_PERIOD TOTAL_OBS_COUNT
#> 1 NA 2006 21 651
#> 2 NA 2006 20 600
#> 3 NA 2006 18 558
#> 4 NA 2006 20 600
#> 5 NA 2006 20 620
#> 6 NA 2007 22 7334
#> OCCURRENCE_COUNT MAX_DURATION_MISSING_YEARS PERCENT_OF_POSSIBLE_OBS
#> 1 NA 2 95.45
#> 2 NA 1 90.91
#> 3 NA 2 81.82
#> 4 NA 1 86.96
#> 5 NA 2 86.96
#> 6 NA 2 89.96
#> E_NORMAL_ELEMENT_NAME
#> 1 Total degree-days Above 15 deg C
#> 2 Total degree-days Above 15 deg C
#> 3 Total degree-days Above 15 deg C
#> 4 Total degree-days Above 15 deg C
#> 5 Total degree-days Above 15 deg C
#> 6 Total degree-days Above 15 deg C
#> F_NORMAL_ELEMENT_NAME MONTH VALUE
#> 1 Total des degrés-jours supérieurs à 15 degree C 8 183.19
#> 2 Total des degrés-jours supérieurs à 15 degree C 9 52.62
#> 3 Total des degrés-jours supérieurs à 15 degree C 10 1.99
#> 4 Total des degrés-jours supérieurs à 15 degree C 11 0.00
#> 5 Total des degrés-jours supérieurs à 15 degree C 12 0.00
#> 6 Total des degrés-jours supérieurs à 15 degree C 13 578.55
#> coordinates
#> 1 -119.71667, 49.78333
#> 2 -119.71667, 49.78333
#> 3 -119.71667, 49.78333
#> 4 -119.71667, 49.78333
#> 5 -119.71667, 49.78333
#> 6 -119.71667, 49.78333# View available Ontario stations
hydro_stns <- geomet_hydro_stns(
query = list(
"PROV_TERR_STATE_LOC" = "ON"
)
)
head(hydro_stns)
#> STATION_NAME IDENTIFIER STATION_NUMBER
#> 1 PINE RIVER NEAR CROOKS 02AA002 02AA002
#> 2 KAMINISTIQUIA RIVER NEAR DONA 02AB001 02AB001
#> 3 SHEBANDOWAN RIVER NEAR KAMINISTIQUIA 02AB002 02AB002
#> 4 KAMINISTIQUIA RIVER AT MOKOMON 02AB003 02AB003
#> 5 KAMINISTIQUIA RIVER AT OUTLET OF DOG LAKE 02AB004 02AB004
#> 6 SHEBANDOWAN RIVER AT GLENWATER 02AB005 02AB005
#> PROV_TERR_STATE_LOC STATUS_EN STATUS_FR CONTRIBUTOR_EN
#> 1 ON Discontinued Fermée
#> 2 ON Discontinued Fermée
#> 3 ON Discontinued Fermée
#> 4 ON Discontinued Fermée
#> 5 ON Discontinued Fermée ONTARIO POWER GENERATION
#> 6 ON Discontinued Fermée
#> CONTRIBUTOR_FR VERTICAL_DATUM
#> 1 ASSUMED DATUM
#> 2
#> 3
#> 4 GEODETIC SURVEY OF CANADA DATUM
#> 5 SOCIÉTÉ ONTARIO POWER GENERATION
#> 6
#> coordinates
#> 1 -89.53333, 48.07222
#> 2 -89.58861, 48.55556
#> 3 -89.62361, 48.54583
#> 4 -89.60000, 48.49167
#> 5 -89.63333, 48.70833
#> 6 -89.78333, 48.54333
# Example means query
hydro_dat <- geomet_hydro_means(
station_number = "04HA001",
start_date = "2016-01-01",
end_date = "2016-01-02"
)
head(hydro_dat)
#> IDENTIFIER STATION_NAME STATION_NUMBER
#> 1 04HA001.2016-01-01 ALBANY RIVER NEAR HAT ISLAND 04HA001
#> 2 04HA001.2016-01-02 ALBANY RIVER NEAR HAT ISLAND 04HA001
#> PROV_TERR_STATE_LOC DATE LEVEL DISCHARGE DISCHARGE_SYMBOL_EN
#> 1 ON 2016-01-01 3.543 412 Ice Conditions
#> 2 ON 2016-01-02 NA 406 Ice Conditions
#> DISCHARGE_SYMBOL_FR LEVEL_SYMBOL_EN LEVEL_SYMBOL_FR coordinates
#> 1 Conditions à glace Partial Day Journée incomplète -83.83333, 51.33056
#> 2 Conditions à glace <NA> <NA> -83.83333, 51.33056
# Real time query
hydro_rt <- geomet_hydro_realtime(station_number = "04HA001")
head(hydro_rt)
#> IDENTIFIER STATION_NUMBER STATION_NAME
#> 1 04HA001.2022-12-20.05:00:00 04HA001 ALBANY RIVER NEAR HAT ISLAND
#> 2 04HA001.2022-12-20.05:05:00 04HA001 ALBANY RIVER NEAR HAT ISLAND
#> 3 04HA001.2022-12-20.05:10:00 04HA001 ALBANY RIVER NEAR HAT ISLAND
#> 4 04HA001.2022-12-20.05:15:00 04HA001 ALBANY RIVER NEAR HAT ISLAND
#> 5 04HA001.2022-12-20.05:20:00 04HA001 ALBANY RIVER NEAR HAT ISLAND
#> 6 04HA001.2022-12-20.05:25:00 04HA001 ALBANY RIVER NEAR HAT ISLAND
#> PROV_TERR_STATE_LOC DATETIME DATETIME_LST LEVEL
#> 1 ON 2022-12-20T05:00:00 2022-12-20T00:00:00-05:00 2.986
#> 2 ON 2022-12-20T05:05:00 2022-12-20T00:05:00-05:00 2.986
#> 3 ON 2022-12-20T05:10:00 2022-12-20T00:10:00-05:00 2.985
#> 4 ON 2022-12-20T05:15:00 2022-12-20T00:15:00-05:00 2.986
#> 5 ON 2022-12-20T05:20:00 2022-12-20T00:20:00-05:00 2.986
#> 6 ON 2022-12-20T05:25:00 2022-12-20T00:25:00-05:00 2.986
#> DISCHARGE LEVEL_SYMBOL_EN LEVEL_SYMBOL_FR DISCHARGE_SYMBOL_EN
#> 1 1120 NA NA NA
#> 2 1120 NA NA NA
#> 3 1120 NA NA NA
#> 4 1120 NA NA NA
#> 5 1120 NA NA NA
#> 6 1120 NA NA NA
#> DISCHARGE_SYMBOL_FR coordinates
#> 1 NA -83.83333, 51.33056
#> 2 NA -83.83333, 51.33056
#> 3 NA -83.83333, 51.33056
#> 4 NA -83.83333, 51.33056
#> 5 NA -83.83333, 51.33056
#> 6 NA -83.83333, 51.33056# View available stations in Ontario
ltce_stns <- geomet_ltce_stns(
query = list(
"PROVINCE_CODE" = "ON"
)
)
head(ltce_stns)
#> VIRTUAL_CLIMATE_ID VIRTUAL_STATION_NAME_E VIRTUAL_STATION_NAME_F
#> 1 VSON74V KEMPTVILLE AREA KEMPTVILLE
#> 2 VSON98V ST. THOMAS AREA ST. THOMAS
#> 3 VSON98V ST. THOMAS AREA ST. THOMAS
#> 4 VSON16V WALKERTON AREA WALKERTON
#> 5 VSON16V WALKERTON AREA WALKERTON
#> 6 VSON16V WALKERTON AREA WALKERTON
#> WXO_CITY_CODE ELEMENT_NAME_E CLIMATE_IDENTIFIER
#> 1 ON-74 DAILY MAXIMUM TEMPERATURE 6104027
#> 2 ON-98 DAILY TOTAL PRECIPITATION 6144478
#> 3 ON-98 DAILY TOTAL PRECIPITATION 6137362
#> 4 ON-16 DAILY TOTAL PRECIPITATION 6145504
#> 5 ON-16 DAILY TOTAL PRECIPITATION 6113329
#> 6 ON-16 DAILY TOTAL PRECIPITATION 6113329
#> START_DATE END_DATE DATA_SOURCE ENG_STN_NAME
#> 1 2007-01-01T00:00:00Z <NA> DLY02 KEMPTVILLE CS
#> 2 2007-01-01T00:00:00Z <NA> DLY02 LONDON CS
#> 3 1980-05-01T00:00:00Z 2006-12-31T00:00:00Z DLY04 ST THOMAS WPCP
#> 4 2008-10-01T00:00:00Z <NA> DLY02 MOUNT FOREST (AUT)
#> 5 2007-01-01T00:00:00Z 2008-09-30T00:00:00Z DLY44 HANOVER
#> 6 1972-01-01T00:00:00Z 2006-12-31T00:00:00Z DLY04 HANOVER
#> FRE_STN_NAME PROVINCE_CODE
#> 1 <NA> ON
#> 2 <NA> ON
#> 3 <NA> ON
#> 4 <NA> ON
#> 5 <NA> ON
#> 6 <NA> ON
#> IDENTIFIER
#> 1 vson74v-daily-maximum-temperature-6104027-2007-01-01t00-00-00z-none
#> 2 vson98v-daily-total-precipitation-6144478-2007-01-01t00-00-00z-none
#> 3 vson98v-daily-total-precipitation-6137362-1980-05-01t00-00-00z-2006-12-31t00-00-00z
#> 4 vson16v-daily-total-precipitation-6145504-2008-10-01t00-00-00z-none
#> 5 vson16v-daily-total-precipitation-6113329-2007-01-01t00-00-00z-2008-09-30t00-00-00z
#> 6 vson16v-daily-total-precipitation-6113329-1972-01-01t00-00-00z-2006-12-31t00-00-00z
#> coordinates
#> 1 -75.64, 45.02
#> 2 -81.19, 42.78
#> 3 -81.19, 42.78
#> 4 -81.15, 44.13
#> 5 -81.15, 44.13
#> 6 -81.15, 44.13
# Example query
ltce_dat <- geomet_ltce_data(
station_number = "VSON99V",
param = "temp"
)
# Lots of columns, here are the first few
head(ltce_dat[, 1:5])
#> WXO_CITY_CODE VIRTUAL_STATION_NAME_E VIRTUAL_STATION_NAME_F
#> 1 ON-99 PEAWANUCK AREA PEAWANUCK
#> 2 ON-99 PEAWANUCK AREA PEAWANUCK
#> 3 ON-99 PEAWANUCK AREA PEAWANUCK
#> 4 ON-99 PEAWANUCK AREA PEAWANUCK
#> 5 ON-99 PEAWANUCK AREA PEAWANUCK
#> 6 ON-99 PEAWANUCK AREA PEAWANUCK
#> VIRTUAL_CLIMATE_ID LOCAL_MONTH
#> 1 VSON99V 1
#> 2 VSON99V 1
#> 3 VSON99V 1
#> 4 VSON99V 1
#> 5 VSON99V 1
#> 6 VSON99V 1swob_dat <- geomet_swob_realtime(
station_number = "1192948",
start_date = Sys.Date(),
end_date = Sys.Date(),
query = list(
"_is-minutely_obs-value" = "false"
)
)
# Lots of columns, here are the first few
head(swob_dat[, 1:5])
#> dataset
#> 1 msc-observation-atmospheric-surface_weather-ca-1.1-ascii
#> 2 msc-observation-atmospheric-surface_weather-ca-1.1-ascii
#> 3 msc-observation-atmospheric-surface_weather-ca-1.1-ascii
#> 4 msc-observation-atmospheric-surface_weather-ca-1.1-ascii
#> 5 msc-observation-atmospheric-surface_weather-ca-1.1-ascii
#> 6 msc-observation-atmospheric-surface_weather-ca-1.1-ascii
#> id
#> 1 2023-01-19-0000-CVFN-AUTO-swob.xml
#> 2 2023-01-19-0200-CVFN-AUTO-swob.xml
#> 3 2023-01-19-0500-CVFN-AUTO-swob.xml
#> 4 2023-01-19-0300-CVFN-AUTO-swob.xml
#> 5 2023-01-19-0100-CVFN-AUTO-swob.xml
#> 6 2023-01-19-0400-CVFN-AUTO-swob.xml
#> url
#> 1 https://dd.weather.gc.ca//observations/swob-ml/20230119/CVFN/2023-01-19-0000-CVFN-AUTO-swob.xml
#> 2 https://dd.weather.gc.ca//observations/swob-ml/20230119/CVFN/2023-01-19-0200-CVFN-AUTO-swob.xml
#> 3 https://dd.weather.gc.ca//observations/swob-ml/20230119/CVFN/2023-01-19-0500-CVFN-AUTO-swob.xml
#> 4 https://dd.weather.gc.ca//observations/swob-ml/20230119/CVFN/2023-01-19-0300-CVFN-AUTO-swob.xml
#> 5 https://dd.weather.gc.ca//observations/swob-ml/20230119/CVFN/2023-01-19-0100-CVFN-AUTO-swob.xml
#> 6 https://dd.weather.gc.ca//observations/swob-ml/20230119/CVFN/2023-01-19-0400-CVFN-AUTO-swob.xml
#> date_tm-uom date_tm-value
#> 1 datetime 2023-01-19T00:00:00.000Z
#> 2 datetime 2023-01-19T02:00:00.000Z
#> 3 datetime 2023-01-19T05:00:00.000Z
#> 4 datetime 2023-01-19T03:00:00.000Z
#> 5 datetime 2023-01-19T01:00:00.000Z
#> 6 datetime 2023-01-19T04:00:00.000ZIf you see data sets missing or come across any problems, please submit an issue.
See here for general contribution guidelines.