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Using hydrotoolbox with Canadian data - Part 2

Ezequiel Toum and Kevin Shook

2023-04-12

library(weathercan)
library(hydrotoolbox)

The package weathercan provides a very easy way to access Canadian historical weather data from Environment and Climate Change Canada (ECCC) website. In this vignette we show how to combine the weathercan and hydrotoolbox functionality.

Installing weathercan

You can install weathercan directly from CRAN: install.packages("weathercan"). Since this package makes it easier to search for and download multiple months/years of historical weather data, these downloads can be fairly large and performing multiple downloads may use up ECCC’s bandwidth unnecessarily. Try to stick to what you need.

Combining weathercan with hydrotoolbox

Once you know your station ID, you can download it (see this link). In the next code lines we show an example.

# get station ID's
head(stations)

# search by name
stations_search("Kamloops", interval = "day")

# Kamloops A - BC province
station_id <- 1274    

kam <- 
  weather_dl(station_ids = station_id,
             start = "1900-01-01",
             end = "1950-12-31", 
             interval = "day") %>%
  as.data.frame()

# now we create the station object and we set the data 
kamloops_hm <- 
  hm_create() %>%
  hm_set(id = station_id, 
         station = kam$station_name[1], 
         province = kam$prov[1], 
         country = "Canada", 
         lat = kam$lat[1], 
         long = kam$lon[1], 
         alt = kam$elev[1], 
         tmean = kam[ , c("date", "mean_temp")], 
         tmax = kam[ , c("date", "max_temp")],
         tmin = kam[ , c("date", "min_temp")], 
         precip = kam[ , c("date", "total_precip")], 
         rainfall = kam[ , c("date", "total_rain")]
         )

kamloops_hm %>% hm_show()

# we plot air temperatures 
kamloops_hm %>%
  hm_plot(slot_name = c('tmean', 'tmax', 'tmin'), 
          col_name = list('mean_temp', 'max_temp', 'min_temp'), 
          interactive = TRUE, 
          line_color = c('forestgreen', 'red', 'dodgerblue'), 
          x_lab = 'Date', y_lab = 'T(ºC)', 
          legend_lab = c('mean', 'max', 'min') )

Using an own made function to build the object

Note that you can save a lot of time by recycling the following function:

# before running this function, the packages
# weathercan and hydrotoolbox should be attached

# station_number: character with station ID
build_weathercan <- function(station_id, 
                             from, to,
                             time_step){
  
  # download station data
  station <-
    weather_dl(station_ids = station_id,
             start = from,
             end = to, 
             interval = time_step) %>%
    as.data.frame()

  # now we create the station object and we set the (meta)data 
  station_hm <- 
    hm_create() %>%
    hm_set(id = station_id, 
         station = station$station_name[1], 
         province = station$prov[1], 
         country = "Canada", 
         lat = station$lat[1], 
         long = station$lon[1], 
         alt = station$elev[1], 
         tmean = station[ , c("date", "mean_temp")], 
         tmax = station[ , c("date", "max_temp")],
         tmin = station[ , c("date", "min_temp")], 
         precip = station[ , c("date", "total_precip")], 
         rainfall = station[ , c("date", "total_rain")]
         )
  
  return(station_hm)
}

once the function is loaded in the Global Environment, we set up the station

# we construct the Kamloops station
# but in a single code line

kamloops_station <- 
  build_weathercan(station_id = 1274, 
                   from = "1900-01-01", 
                   to = "1950-12-31",
                   time_step = "day")

kamloops_station %>%
  hm_show()

Since the builder function is the only one that differs from what was developed for SNIH data, we recommend (re)visiting this vignette (vignette ('snih_arg', package = 'hydrotoolbox')) to explore some of the available methods.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.