This package makes it easier to search for and download multiple months/years of historical weather data from Environment and Climate Change Canada (ECCC) website.
Bear in mind that these downloads can be fairly large and performing multiple downloads may use up ECCC’s bandwidth unnecessarily. Try to stick to what you need.
For more details and tutorials checkout the weathercan website (or see the development docs)
Check out the Demo weathercan shiny dashboard (html; source)
You can install weathercan from the rOpenSci
r-Universe:
install.packages("weathercan",
repos = c("https://ropensci.r-universe.dev",
"https://cloud.r-project.org"))View the available vignettes with vignette(package = "weathercan")
View a particular vignette with, for example,
vignette("weathercan", package = "weathercan")
To download data, you first need to know the station_id associated
with the station you’re interested in.
weathercan includes the function stations() which returns a list of
stations and their details (including station_id).
head(stations())## # A tibble: 6 × 16
## prov station_name station_id climate_id WMO_id TC_id lat lon elev tz interval start end normals normals_1981_2010 normals_1971_2000
## <chr> <chr> <dbl> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <chr> <chr> <dbl> <dbl> <lgl> <lgl> <lgl>
## 1 AB DAYSLAND 1795 301AR54 NA <NA> 52.9 -112. 689. Etc/GMT+7 day 1908 1922 FALSE FALSE FALSE
## 2 AB DAYSLAND 1795 301AR54 NA <NA> 52.9 -112. 689. Etc/GMT+7 hour NA NA FALSE FALSE FALSE
## 3 AB DAYSLAND 1795 301AR54 NA <NA> 52.9 -112. 689. Etc/GMT+7 month 1908 1922 FALSE FALSE FALSE
## 4 AB EDMONTON CORONATION 1796 301BK03 NA <NA> 53.6 -114. 671. Etc/GMT+7 day 1978 1979 FALSE FALSE FALSE
## 5 AB EDMONTON CORONATION 1796 301BK03 NA <NA> 53.6 -114. 671. Etc/GMT+7 hour NA NA FALSE FALSE FALSE
## 6 AB EDMONTON CORONATION 1796 301BK03 NA <NA> 53.6 -114. 671. Etc/GMT+7 month 1978 1979 FALSE FALSE FALSE
glimpse(stations())## Rows: 26,382
## Columns: 16
## $ prov <chr> "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", "AB", …
## $ station_name <chr> "DAYSLAND", "DAYSLAND", "DAYSLAND", "EDMONTON CORONATION", "EDMONTON CORONATION", "EDMONTON CORONATION", "FLEET", "FLEET", "FLEET", …
## $ station_id <dbl> 1795, 1795, 1795, 1796, 1796, 1796, 1797, 1797, 1797, 1798, 1798, 1798, 1799, 1799, 1799, 1800, 1800, 1800, 1801, 1801, 1801, 1802, …
## $ climate_id <chr> "301AR54", "301AR54", "301AR54", "301BK03", "301BK03", "301BK03", "301B6L0", "301B6L0", "301B6L0", "301B8LR", "301B8LR", "301B8LR", …
## $ WMO_id <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ TC_id <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ lat <dbl> 52.87, 52.87, 52.87, 53.57, 53.57, 53.57, 52.15, 52.15, 52.15, 53.20, 53.20, 53.20, 52.40, 52.40, 52.40, 54.08, 54.08, 54.08, 53.52,…
## $ lon <dbl> -112.28, -112.28, -112.28, -113.57, -113.57, -113.57, -111.73, -111.73, -111.73, -110.15, -110.15, -110.15, -115.20, -115.20, -115.2…
## $ elev <dbl> 688.8, 688.8, 688.8, 670.6, 670.6, 670.6, 838.2, 838.2, 838.2, 640.0, 640.0, 640.0, 1036.0, 1036.0, 1036.0, 585.2, 585.2, 585.2, 668…
## $ tz <chr> "Etc/GMT+7", "Etc/GMT+7", "Etc/GMT+7", "Etc/GMT+7", "Etc/GMT+7", "Etc/GMT+7", "Etc/GMT+7", "Etc/GMT+7", "Etc/GMT+7", "Etc/GMT+7", "E…
## $ interval <chr> "day", "hour", "month", "day", "hour", "month", "day", "hour", "month", "day", "hour", "month", "day", "hour", "month", "day", "hour…
## $ start <dbl> 1908, NA, 1908, 1978, NA, 1978, 1987, NA, 1987, 1987, NA, 1987, 1980, NA, 1980, 1980, NA, 1980, 1986, NA, 1986, 1987, NA, 1987, 1986…
## $ end <dbl> 1922, NA, 1922, 1979, NA, 1979, 1990, NA, 1990, 1998, NA, 1998, 2009, NA, 2007, 1981, NA, 1981, 2019, NA, 2007, 1991, NA, 1991, 1995…
## $ normals <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, TRUE, TRU…
## $ normals_1981_2010 <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, TRUE, TRU…
## $ normals_1971_2000 <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,…
You can look through this data frame directly, or you can use the
stations_search function:
stations_search("Kamloops", interval = "hour")## # A tibble: 3 × 16
## prov station_name station_id climate_id WMO_id TC_id lat lon elev tz interval start end normals normals_1981_2010 normals_1971_2000
## <chr> <chr> <dbl> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <chr> <chr> <dbl> <dbl> <lgl> <lgl> <lgl>
## 1 BC KAMLOOPS A 1275 1163780 71887 YKA 50.7 -120. 345. Etc/GMT+8 hour 1953 2013 TRUE TRUE TRUE
## 2 BC KAMLOOPS A 51423 1163781 71887 YKA 50.7 -120. 345. Etc/GMT+8 hour 2013 2023 FALSE FALSE FALSE
## 3 BC KAMLOOPS AUT 42203 1163842 71741 ZKA 50.7 -120. 345 Etc/GMT+8 hour 2006 2023 FALSE FALSE FALSE
Time frame must be one of “hour”, “day”, or “month”.
You can also search by proximity:
stations_search(coords = c(50.667492, -120.329049), dist = 20, interval = "hour")## # A tibble: 3 × 17
## prov station_name station_id climate_id WMO_id TC_id lat lon elev tz interval start end normals normals_1981_2010 normals_1971_2000 distance
## <chr> <chr> <dbl> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <chr> <chr> <dbl> <dbl> <lgl> <lgl> <lgl> <dbl>
## 1 BC KAMLOOPS A 1275 1163780 71887 YKA 50.7 -120. 345. Etc/GMT+8 hour 1953 2013 TRUE TRUE TRUE 8.61
## 2 BC KAMLOOPS AUT 42203 1163842 71741 ZKA 50.7 -120. 345 Etc/GMT+8 hour 2006 2023 FALSE FALSE FALSE 8.61
## 3 BC KAMLOOPS A 51423 1163781 71887 YKA 50.7 -120. 345. Etc/GMT+8 hour 2013 2023 FALSE FALSE FALSE 9.26
You can update this list of stations with
stations_dl()## According to Environment Canada, Modified Date: 2023-01-24 23:30 UTC
## Environment Canada Disclaimers:
## "Station Inventory Disclaimer: Please note that this inventory list is a snapshot of stations on our website as of the modified date, and may be subject to change without notice."
## "Station ID Disclaimer: Station IDs are an internal index numbering system and may be subject to change without notice."
## Stations data saved...
## Use `stations()` to access most recent version and `stations_meta()` to see when this was last updated
And check when it was last updated with
stations_meta()## $ECCC_modified
## [1] "2023-01-24 23:30:00 UTC"
##
## $weathercan_modified
## [1] "2023-09-20"
Note: For reproducibility, if you are using the stations list to gather your data, it can be a good idea to take note of the ECCC date of modification and include it in your reports/manuscripts.
Once you have your station_id(s) you can download weather data:
kam <- weather_dl(station_ids = 51423, start = "2018-02-01", end = "2018-04-15")## As of weathercan v0.3.0 time display is either local time or UTC
## See Details under ?weather_dl for more information.
## This message is shown once per session
kam## # A tibble: 1,776 × 37
## station_name station_id station_operator prov lat lon elev climate_id WMO_id TC_id date time year month day hour weather hmdx
## <chr> <dbl> <lgl> <chr> <dbl> <dbl> <dbl> <chr> <chr> <chr> <date> <dttm> <chr> <chr> <chr> <chr> <chr> <dbl>
## 1 KAMLOOPS A 51423 NA BC 50.7 -120. 345. 1163781 71887 YKA 2018-02-01 2018-02-01 00:00:00 2018 02 01 00:00 <NA> NA
## 2 KAMLOOPS A 51423 NA BC 50.7 -120. 345. 1163781 71887 YKA 2018-02-01 2018-02-01 01:00:00 2018 02 01 01:00 Snow NA
## 3 KAMLOOPS A 51423 NA BC 50.7 -120. 345. 1163781 71887 YKA 2018-02-01 2018-02-01 02:00:00 2018 02 01 02:00 <NA> NA
## 4 KAMLOOPS A 51423 NA BC 50.7 -120. 345. 1163781 71887 YKA 2018-02-01 2018-02-01 03:00:00 2018 02 01 03:00 <NA> NA
## 5 KAMLOOPS A 51423 NA BC 50.7 -120. 345. 1163781 71887 YKA 2018-02-01 2018-02-01 04:00:00 2018 02 01 04:00 Cloudy NA
## 6 KAMLOOPS A 51423 NA BC 50.7 -120. 345. 1163781 71887 YKA 2018-02-01 2018-02-01 05:00:00 2018 02 01 05:00 <NA> NA
## 7 KAMLOOPS A 51423 NA BC 50.7 -120. 345. 1163781 71887 YKA 2018-02-01 2018-02-01 06:00:00 2018 02 01 06:00 <NA> NA
## 8 KAMLOOPS A 51423 NA BC 50.7 -120. 345. 1163781 71887 YKA 2018-02-01 2018-02-01 07:00:00 2018 02 01 07:00 Cloudy NA
## 9 KAMLOOPS A 51423 NA BC 50.7 -120. 345. 1163781 71887 YKA 2018-02-01 2018-02-01 08:00:00 2018 02 01 08:00 <NA> NA
## 10 KAMLOOPS A 51423 NA BC 50.7 -120. 345. 1163781 71887 YKA 2018-02-01 2018-02-01 09:00:00 2018 02 01 09:00 <NA> NA
## # ℹ 1,766 more rows
You can also download data from multiple stations at once:
kam_pg <- weather_dl(station_ids = c(48248, 51423), start = "2018-02-01", end = "2018-04-15")To access climate normals, you first need to know the climate_id
associated with the station you’re interested in.
stations_search("Winnipeg", normals_years = "current")## # A tibble: 1 × 13
## prov station_name station_id climate_id WMO_id TC_id lat lon elev tz normals normals_1981_2010 normals_1971_2000
## <chr> <chr> <dbl> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <chr> <lgl> <lgl> <lgl>
## 1 MB WINNIPEG RICHARDSON INT'L A 3698 5023222 71852 YWG 49.9 -97.2 239. Etc/GMT+6 TRUE TRUE TRUE
Then you can download the climate normals with the normals_dl()
function.
n <- normals_dl("5023222")See the Getting Started vignette for more details.
citation("weathercan")## To cite 'weathercan' in publications, please use:
##
## LaZerte, Stefanie E and Sam Albers (2018). weathercan: Download and format weather data from Environment and Climate Change Canada. The
## Journal of Open Source Software 3(22):571. doi:10.21105/joss.00571.
##
## A BibTeX entry for LaTeX users is
##
## @Article{,
## title = {{weathercan}: {D}ownload and format weather data from Environment and Climate Change Canada},
## author = {Stefanie E LaZerte and Sam Albers},
## journal = {The Journal of Open Source Software},
## volume = {3},
## number = {22},
## pages = {571},
## year = {2018},
## url = {https://joss.theoj.org/papers/10.21105/joss.00571},
## }
The data and the code in this repository are licensed under multiple licences. All code is licensed GPL-3. All weather data is licensed under the (Open Government License - Canada).
- Browse
weathercanuse cases on rOpenSci.org - Checkout the
weathercanShiny App by Nick Rong (@nickyrong) and Nathan Smith (@WraySmith) - R package
RavenRhas functions for converting ECCC data downloaded byweathercanto the .rvt format for Raven. - R package
meteolandhas functions for converting ECCC data downloaded byweathercanto the format required for use inmeteoland.
weathercan and rclimateca were developed at roughly the same time
and as a result, both present up-to-date methods for accessing and
downloading data from ECCC. The largest differences between the two
packages are: a) weathercan includes functions for interpolating
weather data and directly integrating it into other data sources. b)
weathercan actively seeks to apply tidy data principles in R and
integrates well with the tidyverse including using tibbles and nested
listcols. c) rclimateca contains arguments for specifying short
vs. long data formats. d) rclimateca has the option of formatting data
in the MUData format using the
mudata2 package by the
same author.
CHCN is an older package last updated in 2012. Unfortunately, ECCC
updated their services within the last couple of years which caused a
great many of the previous web scrapers to fail. CHCN relies on a
decommissioned older web-scraper and so is
currently broken.
We welcome any and all contributions! To make the process as painless as possible for all involved, please see our guide to contributing
Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.
