README.md
In rywhale/rforecastca: Retrieve Weather Forecasts for Canadian Cities from Environment Canada
rforecastca
Overview
Allows users to retrieve weather forecasts from Environment Canada’s
Datamart service in tabular format.
Currently supports retrieving the following forecasts:
FYI: This package is still in development and breaking changes may
occur in the near future.
CityPage Weather Forecasts
Get List of Available Locations
You can get a list of all the locations with forecasts available by
using the rfca_cityweather_locations() function
all_locations <- rfca_cityweather_locations()
head(all_locations)
## site_name site_id province
## 1 Athabasca s0000001 AB
## 2 Clearwater s0000002 BC
## 3 Valemount s0000003 BC
## 4 Grand Forks s0000004 BC
## 5 McBride s0000005 BC
## 6 Merritt s0000006 BC
ontario_locations <- rfca_cityweather_locations(prov = "ON")
head(ontario_locations)
## site_name site_id province
## 1 Marathon s0000022 ON
## 2 Terrace Bay s0000023 ON
## 3 Attawapiskat s0000024 ON
## 4 Gogama s0000025 ON
## 5 Hawkesbury s0000069 ON
## 6 Alexandria s0000070 ON
A data frame containing short codes for all provinces can be accessed
using data(prov_state_codes)
data(prov_state_codes)
# Filter for only Canadian short codes
prov_short_codes <- prov_state_codes %>%
filter(country == "CA")
head(prov_short_codes)
## # A tibble: 6 x 3
## country prov_state_shortcode prov_state_name
## <chr> <chr> <chr>
## 1 CA AB Alberta
## 2 CA BC British Columbia
## 3 CA MB Manitoba
## 4 CA NB New Brunswick
## 5 CA NL Newfoundland
## 6 CA NS Nova Scotia
Get Forecast for Location
You can then pass the site_id for the site you’re interested in to
rfca_cityweather_forecast() to retrieve the forecast
my_forecast <- rfca_cityweather_forecast(site_id = "s0000318")
my_forecast
## site_name site_id Timestamp Temperature Temperature_Units
## 1 Halifax s0000318 2018-11-19 16:00:00 2 C
## 2 Halifax s0000318 2018-11-19 17:00:00 3 C
## 3 Halifax s0000318 2018-11-19 18:00:00 3 C
## 4 Halifax s0000318 2018-11-19 19:00:00 3 C
## 5 Halifax s0000318 2018-11-19 20:00:00 3 C
## 6 Halifax s0000318 2018-11-19 21:00:00 3 C
## 7 Halifax s0000318 2018-11-19 22:00:00 4 C
## 8 Halifax s0000318 2018-11-19 23:00:00 5 C
## 9 Halifax s0000318 2018-11-20 00:00:00 6 C
## 10 Halifax s0000318 2018-11-20 01:00:00 6 C
## 11 Halifax s0000318 2018-11-20 02:00:00 7 C
## 12 Halifax s0000318 2018-11-20 03:00:00 7 C
## 13 Halifax s0000318 2018-11-20 04:00:00 7 C
## 14 Halifax s0000318 2018-11-20 05:00:00 7 C
## 15 Halifax s0000318 2018-11-20 06:00:00 7 C
## 16 Halifax s0000318 2018-11-20 07:00:00 6 C
## 17 Halifax s0000318 2018-11-20 08:00:00 6 C
## 18 Halifax s0000318 2018-11-20 09:00:00 5 C
## 19 Halifax s0000318 2018-11-20 10:00:00 3 C
## 20 Halifax s0000318 2018-11-20 11:00:00 4 C
## 21 Halifax s0000318 2018-11-20 12:00:00 5 C
## 22 Halifax s0000318 2018-11-20 13:00:00 5 C
## 23 Halifax s0000318 2018-11-20 14:00:00 5 C
## 24 Halifax s0000318 2018-11-20 15:00:00 5 C
## Wind_Direction Wind_Speed Wind_Speed_Units Condition
## 1 VR 5 km/h Periods of light snow
## 2 VR 5 km/h Periods of light snow
## 3 VR 5 km/h Showers
## 4 S 20 km/h Showers
## 5 S 20 km/h Showers
## 6 S 20 km/h Showers
## 7 S 20 km/h Periods of rain
## 8 S 20 km/h Periods of rain
## 9 S 20 km/h Periods of rain
## 10 S 20 km/h Periods of rain
## 11 S 20 km/h Periods of rain
## 12 S 20 km/h Periods of rain
## 13 S 20 km/h Periods of rain
## 14 S 20 km/h Periods of rain
## 15 N 10 km/h Periods of rain
## 16 N 10 km/h Overcast
## 17 N 10 km/h Overcast
## 18 N 10 km/h Overcast
## 19 VR 5 km/h Chance of showers
## 20 VR 5 km/h Chance of showers
## 21 VR 5 km/h Chance of showers
## 22 VR 5 km/h Chance of showers
## 23 VR 5 km/h Chance of showers
## 24 VR 5 km/h Chance of showers
North American Ensemble Forecast System (NAEFS) Forecasts
Get Available Locations
You can get a list of available forecast locations using
rfca_naefs_locations(). By default this returns all available
locations
naefs_locations <- rfca_naefs_locations()
head(naefs_locations)
## City WMO_code Latitude Longitude Altitude Country Province_state
## 1 Argentia 47.30 -54.00 16 CA NL
## 2 Badger 48.97 -56.07 105 CA NL
## 3 Bonavista 48.67 -53.12 27 CA NL
## 4 Burgeo 47.62 -57.62 12 CA NL
## 5 Cape Race 46.65 -53.07 28 CA NL
## 6 Cartwright YRF 53.70 -57.03 14 CA NL
## File_path
## 1 ARGENTIA_NL_CA
## 2 BADGER_NL_CA
## 3 BONAVISTA_NL_CA
## 4 BURGEO_NL_CA
## 5 CAPE_RACE_NL_CA
## 6 CARTWRIGHT_NL_CA
You can also subset locations by country using a two letter short code
# Canadian locatiosn
can_naefs_locations <- rfca_naefs_locations(country = "CA")
head(can_naefs_locations)
## City WMO_code Latitude Longitude Altitude Country Province_state
## 1 Argentia 47.30 -54.00 16 CA NL
## 2 Badger 48.97 -56.07 105 CA NL
## 3 Bonavista 48.67 -53.12 27 CA NL
## 4 Burgeo 47.62 -57.62 12 CA NL
## 5 Cape Race 46.65 -53.07 28 CA NL
## 6 Cartwright YRF 53.70 -57.03 14 CA NL
## File_path
## 1 ARGENTIA_NL_CA
## 2 BADGER_NL_CA
## 3 BONAVISTA_NL_CA
## 4 BURGEO_NL_CA
## 5 CAPE_RACE_NL_CA
## 6 CARTWRIGHT_NL_CA
Or by province/state
ontario_naefs_locations <- rfca_naefs_locations(province_state = "ON")
head(ontario_naefs_locations)
## City WMO_code Latitude Longitude Altitude Country
## 1 Armstrong YYW 50.30 -89.03 351 CA
## 2 Atikokan YIB 48.75 -91.62 393 CA
## 3 Barrie 44.38 -79.78 295 CA
## 4 Big Trout Lake YTL 53.83 -89.87 224 CA
## 5 Britt 45.80 -80.53 190 CA
## 6 Caribou Island YCI 47.33 -85.83 187 CA
## Province_state File_path
## 1 ON ARMSTRONG_ON_CA
## 2 ON ATIKOKAN_ON_CA
## 3 ON BARRIE_ON_CA
## 4 ON BIG_TROUT_LAKE_ON_CA
## 5 ON BRITT_ON_CA
## 6 ON CARIBOU_ISLAND_ON_CA
The full list of country short codes is available using
data(country_codes)
data(country_codes)
head(country_codes)
## # A tibble: 6 x 2
## country country_shortcode
## <chr> <chr>
## 1 Canada CA
## 2 United States US
## 3 Mexico MX
## 4 Antigua and Barbuda AG
## 5 Bahamas BS
## 6 Barbados BB
and the full list of province/state short codes using
data(prov_state_codes)
data(prov_state_codes)
head(prov_state_codes)
## # A tibble: 6 x 3
## country prov_state_shortcode prov_state_name
## <chr> <chr> <chr>
## 1 CA AB Alberta
## 2 MX AG Aguascalientes
## 3 US AK Alaska
## 4 US AL Alabama
## 5 US AR Arkansas
## 6 US AZ Arizona
Get Available Parameters
The NAEFS forecast includes a variety of parameters. You can get a data
frame containing the short code for each parameter, as well as text
description and the units using rfca_naefs_parameters()
all_params <- rfca_naefs_parameters()
head(all_params)
## parameter
## 1 APCP-SFC
## 2 MSLP
## 3 TCDC
## 4 HGT-500HPA
## 5 LAYER-1000-500HPA
## 6 WIND-SFC
## parameter_desc
## 1 Surface Accumulated Precipitation
## 2 Mean Sea level Pressure
## 3 Total Cloud Cover
## 4 Geopotential at 500 hPa
## 5 Thicknesses (Geopotentiel Difference) between 1000 and 500 hPa
## 6 Surface Wind Speed
## parameter_desc_fr units
## 1 Précipitations accumulées à la surface mm
## 2 Pression moyenne au niveau de la mer hPa
## 3 Couvert nuageux total tenths
## 4 Géopotentiel à 500 hPa dam
## 5 Épaisseurs (différence de géopotentiel entre 1000 et 500 hPa dam
## 6 Vitesse du vent à la surface km/h
Get NAEFS Forecast for Location
You can retrieve NAEFS forecasts for a specific location using
rfca_naefs_forecast() which takes four arguments:
- forecast_date - The date of the forecast in YYYY-mm-dd format. By
default this is set to the current day (using
Sys.Date()) but
Environment Canada archives forecasts for 30 days so you can query
older forecasts if you’d like.
- forecast_time - Forecasts validity start. Either “00” (0 zulu) or
“12” (12 zulu)
- forecast_location - The name of the location to retrieve a forecast
for, see
rfca_naefs_locations() for valid options
- forecast_parameter - Defaults to all available parameters. Can also
specify parameters using a short code, see
rfca_naefs_parameters()
for valid options.
# Retrieve NAEFS forecast for Argentia, NL for current date
# (all parameters)
arg_forecast <- rfca_naefs_forecast(
forecast_time = "00",
forecast_location = "Argentia"
)
head(arg_forecast)
## Timestamp Values forecast_parameter Units Model_Id
## 1 2018-11-19 06:00:00 0 APCP-SFC mm 1
## 2 2018-11-19 06:00:00 0 APCP-SFC mm 2
## 3 2018-11-19 06:00:00 0 APCP-SFC mm 3
## 4 2018-11-19 06:00:00 0 APCP-SFC mm 4
## 5 2018-11-19 06:00:00 0 APCP-SFC mm 5
## 6 2018-11-19 06:00:00 0 APCP-SFC mm 6
rywhale/rforecastca documentation built on May 4, 2019, 7:38 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
rforecastca
Overview
Allows users to retrieve weather forecasts from Environment Canada’s Datamart service in tabular format.
Currently supports retrieving the following forecasts:
FYI: This package is still in development and breaking changes may occur in the near future.
CityPage Weather Forecasts
Get List of Available Locations
You can get a list of all the locations with forecasts available by
using the rfca_cityweather_locations() function
all_locations <- rfca_cityweather_locations()
head(all_locations)
## site_name site_id province
## 1 Athabasca s0000001 AB
## 2 Clearwater s0000002 BC
## 3 Valemount s0000003 BC
## 4 Grand Forks s0000004 BC
## 5 McBride s0000005 BC
## 6 Merritt s0000006 BC
ontario_locations <- rfca_cityweather_locations(prov = "ON")
head(ontario_locations)
## site_name site_id province
## 1 Marathon s0000022 ON
## 2 Terrace Bay s0000023 ON
## 3 Attawapiskat s0000024 ON
## 4 Gogama s0000025 ON
## 5 Hawkesbury s0000069 ON
## 6 Alexandria s0000070 ON
A data frame containing short codes for all provinces can be accessed
using data(prov_state_codes)
data(prov_state_codes)
# Filter for only Canadian short codes
prov_short_codes <- prov_state_codes %>%
filter(country == "CA")
head(prov_short_codes)
## # A tibble: 6 x 3
## country prov_state_shortcode prov_state_name
## <chr> <chr> <chr>
## 1 CA AB Alberta
## 2 CA BC British Columbia
## 3 CA MB Manitoba
## 4 CA NB New Brunswick
## 5 CA NL Newfoundland
## 6 CA NS Nova Scotia
Get Forecast for Location
You can then pass the site_id for the site you’re interested in to
rfca_cityweather_forecast() to retrieve the forecast
my_forecast <- rfca_cityweather_forecast(site_id = "s0000318")
my_forecast
## site_name site_id Timestamp Temperature Temperature_Units
## 1 Halifax s0000318 2018-11-19 16:00:00 2 C
## 2 Halifax s0000318 2018-11-19 17:00:00 3 C
## 3 Halifax s0000318 2018-11-19 18:00:00 3 C
## 4 Halifax s0000318 2018-11-19 19:00:00 3 C
## 5 Halifax s0000318 2018-11-19 20:00:00 3 C
## 6 Halifax s0000318 2018-11-19 21:00:00 3 C
## 7 Halifax s0000318 2018-11-19 22:00:00 4 C
## 8 Halifax s0000318 2018-11-19 23:00:00 5 C
## 9 Halifax s0000318 2018-11-20 00:00:00 6 C
## 10 Halifax s0000318 2018-11-20 01:00:00 6 C
## 11 Halifax s0000318 2018-11-20 02:00:00 7 C
## 12 Halifax s0000318 2018-11-20 03:00:00 7 C
## 13 Halifax s0000318 2018-11-20 04:00:00 7 C
## 14 Halifax s0000318 2018-11-20 05:00:00 7 C
## 15 Halifax s0000318 2018-11-20 06:00:00 7 C
## 16 Halifax s0000318 2018-11-20 07:00:00 6 C
## 17 Halifax s0000318 2018-11-20 08:00:00 6 C
## 18 Halifax s0000318 2018-11-20 09:00:00 5 C
## 19 Halifax s0000318 2018-11-20 10:00:00 3 C
## 20 Halifax s0000318 2018-11-20 11:00:00 4 C
## 21 Halifax s0000318 2018-11-20 12:00:00 5 C
## 22 Halifax s0000318 2018-11-20 13:00:00 5 C
## 23 Halifax s0000318 2018-11-20 14:00:00 5 C
## 24 Halifax s0000318 2018-11-20 15:00:00 5 C
## Wind_Direction Wind_Speed Wind_Speed_Units Condition
## 1 VR 5 km/h Periods of light snow
## 2 VR 5 km/h Periods of light snow
## 3 VR 5 km/h Showers
## 4 S 20 km/h Showers
## 5 S 20 km/h Showers
## 6 S 20 km/h Showers
## 7 S 20 km/h Periods of rain
## 8 S 20 km/h Periods of rain
## 9 S 20 km/h Periods of rain
## 10 S 20 km/h Periods of rain
## 11 S 20 km/h Periods of rain
## 12 S 20 km/h Periods of rain
## 13 S 20 km/h Periods of rain
## 14 S 20 km/h Periods of rain
## 15 N 10 km/h Periods of rain
## 16 N 10 km/h Overcast
## 17 N 10 km/h Overcast
## 18 N 10 km/h Overcast
## 19 VR 5 km/h Chance of showers
## 20 VR 5 km/h Chance of showers
## 21 VR 5 km/h Chance of showers
## 22 VR 5 km/h Chance of showers
## 23 VR 5 km/h Chance of showers
## 24 VR 5 km/h Chance of showers
North American Ensemble Forecast System (NAEFS) Forecasts
Get Available Locations
You can get a list of available forecast locations using
rfca_naefs_locations(). By default this returns all available
locations
naefs_locations <- rfca_naefs_locations()
head(naefs_locations)
## City WMO_code Latitude Longitude Altitude Country Province_state
## 1 Argentia 47.30 -54.00 16 CA NL
## 2 Badger 48.97 -56.07 105 CA NL
## 3 Bonavista 48.67 -53.12 27 CA NL
## 4 Burgeo 47.62 -57.62 12 CA NL
## 5 Cape Race 46.65 -53.07 28 CA NL
## 6 Cartwright YRF 53.70 -57.03 14 CA NL
## File_path
## 1 ARGENTIA_NL_CA
## 2 BADGER_NL_CA
## 3 BONAVISTA_NL_CA
## 4 BURGEO_NL_CA
## 5 CAPE_RACE_NL_CA
## 6 CARTWRIGHT_NL_CA
You can also subset locations by country using a two letter short code
# Canadian locatiosn
can_naefs_locations <- rfca_naefs_locations(country = "CA")
head(can_naefs_locations)
## City WMO_code Latitude Longitude Altitude Country Province_state
## 1 Argentia 47.30 -54.00 16 CA NL
## 2 Badger 48.97 -56.07 105 CA NL
## 3 Bonavista 48.67 -53.12 27 CA NL
## 4 Burgeo 47.62 -57.62 12 CA NL
## 5 Cape Race 46.65 -53.07 28 CA NL
## 6 Cartwright YRF 53.70 -57.03 14 CA NL
## File_path
## 1 ARGENTIA_NL_CA
## 2 BADGER_NL_CA
## 3 BONAVISTA_NL_CA
## 4 BURGEO_NL_CA
## 5 CAPE_RACE_NL_CA
## 6 CARTWRIGHT_NL_CA
Or by province/state
ontario_naefs_locations <- rfca_naefs_locations(province_state = "ON")
head(ontario_naefs_locations)
## City WMO_code Latitude Longitude Altitude Country
## 1 Armstrong YYW 50.30 -89.03 351 CA
## 2 Atikokan YIB 48.75 -91.62 393 CA
## 3 Barrie 44.38 -79.78 295 CA
## 4 Big Trout Lake YTL 53.83 -89.87 224 CA
## 5 Britt 45.80 -80.53 190 CA
## 6 Caribou Island YCI 47.33 -85.83 187 CA
## Province_state File_path
## 1 ON ARMSTRONG_ON_CA
## 2 ON ATIKOKAN_ON_CA
## 3 ON BARRIE_ON_CA
## 4 ON BIG_TROUT_LAKE_ON_CA
## 5 ON BRITT_ON_CA
## 6 ON CARIBOU_ISLAND_ON_CA
The full list of country short codes is available using
data(country_codes)
data(country_codes)
head(country_codes)
## # A tibble: 6 x 2
## country country_shortcode
## <chr> <chr>
## 1 Canada CA
## 2 United States US
## 3 Mexico MX
## 4 Antigua and Barbuda AG
## 5 Bahamas BS
## 6 Barbados BB
and the full list of province/state short codes using
data(prov_state_codes)
data(prov_state_codes)
head(prov_state_codes)
## # A tibble: 6 x 3
## country prov_state_shortcode prov_state_name
## <chr> <chr> <chr>
## 1 CA AB Alberta
## 2 MX AG Aguascalientes
## 3 US AK Alaska
## 4 US AL Alabama
## 5 US AR Arkansas
## 6 US AZ Arizona
Get Available Parameters
The NAEFS forecast includes a variety of parameters. You can get a data
frame containing the short code for each parameter, as well as text
description and the units using rfca_naefs_parameters()
all_params <- rfca_naefs_parameters()
head(all_params)
## parameter
## 1 APCP-SFC
## 2 MSLP
## 3 TCDC
## 4 HGT-500HPA
## 5 LAYER-1000-500HPA
## 6 WIND-SFC
## parameter_desc
## 1 Surface Accumulated Precipitation
## 2 Mean Sea level Pressure
## 3 Total Cloud Cover
## 4 Geopotential at 500 hPa
## 5 Thicknesses (Geopotentiel Difference) between 1000 and 500 hPa
## 6 Surface Wind Speed
## parameter_desc_fr units
## 1 Précipitations accumulées à la surface mm
## 2 Pression moyenne au niveau de la mer hPa
## 3 Couvert nuageux total tenths
## 4 Géopotentiel à 500 hPa dam
## 5 Épaisseurs (différence de géopotentiel entre 1000 et 500 hPa dam
## 6 Vitesse du vent à la surface km/h
Get NAEFS Forecast for Location
You can retrieve NAEFS forecasts for a specific location using
rfca_naefs_forecast() which takes four arguments:
- forecast_date - The date of the forecast in YYYY-mm-dd format. By
default this is set to the current day (using
Sys.Date()) but Environment Canada archives forecasts for 30 days so you can query older forecasts if you’d like. - forecast_time - Forecasts validity start. Either “00” (0 zulu) or “12” (12 zulu)
- forecast_location - The name of the location to retrieve a forecast
for, see
rfca_naefs_locations()for valid options - forecast_parameter - Defaults to all available parameters. Can also
specify parameters using a short code, see
rfca_naefs_parameters()for valid options.
# Retrieve NAEFS forecast for Argentia, NL for current date
# (all parameters)
arg_forecast <- rfca_naefs_forecast(
forecast_time = "00",
forecast_location = "Argentia"
)
head(arg_forecast)
## Timestamp Values forecast_parameter Units Model_Id
## 1 2018-11-19 06:00:00 0 APCP-SFC mm 1
## 2 2018-11-19 06:00:00 0 APCP-SFC mm 2
## 3 2018-11-19 06:00:00 0 APCP-SFC mm 3
## 4 2018-11-19 06:00:00 0 APCP-SFC mm 4
## 5 2018-11-19 06:00:00 0 APCP-SFC mm 5
## 6 2018-11-19 06:00:00 0 APCP-SFC mm 6
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