Awesome
canadaHCD
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Access Canadian Historical Climate Data from R. The Government of Canada’s Historical Climate Data website provides access to hourly, daily, and monthly weather records for stations throughout Canada.
These are raw data that have undergone some quality control, but issues
such as changes in station location are unmanged; the data for the
original stationID stops at a certain point and a new stationID
continues recording. For a more curated data set for climate change
research at broad spatial and temporal scales see the Adjusted and
Homogenized Canadian Climate Data
(AHCCD).
Installation
canadaHCD is still under active development towards a 0.1 release. In the meantime, if you wish to use the package, please install it from this github repo, which is most easily achieved using Hadley Wickham’s remotes package:
## install.packages("devtools")
remotes::install_github("gavinsimpson/canadaHCD")
Usage
Say I’m interested in climate data for stations in Yellowknife, I can
search for all known stationIDs with "Yellowknife" in their name
using find_station()
library("canadaHCD")
find_station("Yellowknife")
#> # A tibble: 6 × 6
#> Name Province ClimateID StationID LatitudeDD
#> <chr> <chr> <chr> <chr> <dbl>
#> 1 YELLOWKNIFE A Northwest Territories 2204100 1706 62.5
#> 2 YELLOWKNIFE A Northwest Territories 2204101 51058 62.5
#> 3 YELLOWKNIFE AIRPORT Northwest Territories 2204108 55358 62.5
#> 4 YELLOWKNIFE-HENDERSON Northwest Territories 2204110 45467 62.4
#> 5 YELLOWKNIFE CS Northwest Territories 2204155 27338 62.5
#> 6 YELLOWKNIFE HYDRO Northwest Territories 2204200 1707 62.7
#> LongitudeDD
#> <dbl>
#> 1 -114.
#> 2 -114.
#> 3 -114.
#> 4 -114.
#> 5 -114.
#> 6 -114.
To download the monthly HCD from YELLOWKNIFE HYDRO I can use
hcd_monthly(), providing it with the StationID for that particular
weather station
yh <- hcd_monthly(1707)
The data are returned as a
tibble
(a tbl_df), which shows a compact version of the data frame.
yh
#> # A tibble: 690 × 16
#> Station ClimateID Longitude Latitude Date MaxTemp MinTemp
#> <chr> <chr> <dbl> <dbl> <yearmon> <dbl> <dbl>
#> 1 YELLOWKNIFE HYDRO 2204200 -114. 62.7 Jan 1943 NA NA
#> 2 YELLOWKNIFE HYDRO 2204200 -114. 62.7 Feb 1943 -16.2 -26.4
#> 3 YELLOWKNIFE HYDRO 2204200 -114. 62.7 Mar 1943 -14.4 -29.4
#> 4 YELLOWKNIFE HYDRO 2204200 -114. 62.7 Apr 1943 1.2 -12.3
#> 5 YELLOWKNIFE HYDRO 2204200 -114. 62.7 May 1943 9.3 -3.6
#> 6 YELLOWKNIFE HYDRO 2204200 -114. 62.7 Jun 1943 17.6 2.4
#> 7 YELLOWKNIFE HYDRO 2204200 -114. 62.7 Jul 1943 20.6 9.6
#> 8 YELLOWKNIFE HYDRO 2204200 -114. 62.7 Aug 1943 18.9 7.2
#> 9 YELLOWKNIFE HYDRO 2204200 -114. 62.7 Sep 1943 10.9 2
#> 10 YELLOWKNIFE HYDRO 2204200 -114. 62.7 Oct 1943 6.1 -1.9
#> MeanTemp ExtremeHigh ExtremeLow TotalRain TotalSnow TotalPrecip LastSnowGrnd
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int>
#> 1 NA NA NA NA NA NA NA
#> 2 -21.3 1.1 -44.4 0 9.4 9.4 NA
#> 3 -21.9 -3.3 -40.6 0 2.8 2.8 NA
#> 4 -5.6 12.2 -31.7 0 18 18 NA
#> 5 2.9 20 -11.7 9.9 2.8 12.7 NA
#> 6 10 27.2 -1.7 4.8 0 4.8 NA
#> 7 15.1 27.2 4.4 36.6 0 36.6 NA
#> 8 13.1 27.2 1.7 17.8 0 17.8 NA
#> 9 6.5 18.3 -6.1 5.8 2.8 8.6 NA
#> 10 2.1 17.2 -15.6 19.1 5.1 24.1 NA
#> # ℹ 680 more rows
#> # ℹ 2 more variables: MaxGustDir <int>, MaxGustSpeed <chr>
You should be able to work with these objects mostly as if they were data frames.
Allthough not yet exposed through any functions in the package, you can
access a snapshot of the station metadata via the
canadaHCD:::station_data data frame.
canadaHCD:::station_data
#> # A tibble: 8,797 × 20
#> Name Province ClimateID StationID WMOID TCID LatitudeDD LongitudeDD
#> <chr> <chr> <chr> <chr> <chr> <chr> <dbl> <dbl>
#> 1 ACTIVE PASS British… 1010066 14 <NA> <NA> 48.9 -123.
#> 2 ALBERT HEAD British… 1010235 15 <NA> <NA> 48.4 -123.
#> 3 BAMBERTON OC… British… 1010595 16 <NA> <NA> 48.6 -124.
#> 4 BEAR CREEK British… 1010720 17 <NA> <NA> 48.5 -124
#> 5 BEAVER LAKE British… 1010774 18 <NA> <NA> 48.5 -123.
#> 6 BECHER BAY British… 1010780 19 <NA> <NA> 48.3 -124.
#> 7 BRENTWOOD BA… British… 1010960 20 <NA> <NA> 48.6 -123.
#> 8 BRENTWOOD CL… British… 1010961 21 <NA> <NA> 48.6 -123.
#> 9 BRENTWOOD W … British… 1010965 22 <NA> <NA> 48.6 -123.
#> 10 CENTRAL SAAN… British… 1011467 25 <NA> <NA> 48.6 -123.
#> Latitude Longitude Elevation FirstYear LastYear HourlyFirstYr HourlyLastYr
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 485200000 -1231700000 4 1984 1996 NA NA
#> 2 482400000 -1232900000 17 1971 1995 NA NA
#> 3 483500000 -1233100000 85.3 1961 1980 NA NA
#> 4 483000000 -1240000000 350. 1910 1971 NA NA
#> 5 483000000 -1232100000 61 1894 1952 NA NA
#> 6 482000000 -1233800000 12.2 1956 1966 NA NA
#> 7 483600000 -1232800000 38 1987 1997 NA NA
#> 8 483400000 -1232700000 30.5 1972 1980 NA NA
#> 9 483400000 -1232600000 91.4 1960 1970 NA NA
#> 10 483500000 -1232500000 53.3 1963 1994 NA NA
#> # ℹ 8,787 more rows
#> # ℹ 5 more variables: DailyFirstYr <dbl>, DailyLastYr <dbl>, MonthlyFirstYr <dbl>, MonthlyLastYr <dbl>, TimeZone <chr>
If we wanted to know which resolutions of data were available for the
YELLOWKNIFE HYDRO station, we can extract certain columns from the
station data object
id <- grep("YELLOWKNIFE HYDRO", canadaHCD:::station_data$Name)
vars <- c("HourlyFirstYr", "HourlyLastYr", "DailyFirstYr", "DailyLastYr",
"MonthlyFirstYr", "MonthlyLastYr")
canadaHCD:::station_data[id, vars]
#> # A tibble: 1 × 6
#> HourlyFirstYr HourlyLastYr DailyFirstYr DailyLastYr MonthlyFirstYr
#> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 NA NA 1943 2000 1943
#> MonthlyLastYr
#> <dbl>
#> 1 2000
The output shows that this station has no hourly data, but daily and monthly data sets exist.