The goal of rcoagmet is to provide functions for downloading data from CoAgMet weather stations, using their Data API.
See also this blog post describing the package and showing some examples.
You can install the development version of rcoagmet from GitHub with:
# install.packages("devtools")
devtools::install_github("andypicke/rcoagmet")library(rcoagmet)
meta <- get_coagmet_meta()
head(meta)
#> # A tibble: 6 × 13
#> station name location latitude_deg_n longitude_deg_e elevation_ft
#> <chr> <chr> <chr> <dbl> <dbl> <dbl>
#> 1 akr02 Akron USDA-ARS-GPRC 40.2 -103. 4537
#> 2 alt01 Ault 1 mi SE Ault 40.6 -105. 4910
#> 3 avn01 Avondale 1 mi SE Avond… 38.2 -104. 4630
#> 4 bla01 Blanca 8 mi SW Blanca 37.4 -106. 7755
#> 5 bnv01 Buena Vista CDW Area SW o… 38.8 -106. 7900
#> 6 brg01 Briggsdale 3 mi S Briggs… 40.6 -104. 4858
#> # ℹ 7 more variables: anemometer_height_m <dbl>, active <chr>,
#> # irrigation <chr>, first_observation <chr>, last_observation <chr>,
#> # timestep_s <dbl>, network <chr>meta <- get_coagmet_meta(network = "nw")
head(meta)
#> # A tibble: 6 × 13
#> station name location latitude_deg_n longitude_deg_e elevation_ft
#> <chr> <chr> <chr> <dbl> <dbl> <dbl>
#> 1 bld01 Boulder South We… Fairvie… 40.0 -105. 5515
#> 2 bld02 Boulder North We… Foothil… 40.0 -105. 5561
#> 3 bru01 Brush 1 mile … 40.3 -103. 4215
#> 4 btd01 Berthoud Norther… 40.3 -105. 5069
#> 5 crk01 Crook 3 miles… 40.8 -102. 3735
#> 6 eat01 Eaton 3 miles… 40.6 -104. 4900
#> # ℹ 7 more variables: anemometer_height_m <dbl>, active <chr>,
#> # irrigation <chr>, first_observation <chr>, last_observation <chr>,
#> # timestep_s <dbl>, network <chr>latest <- get_coagmet_data(station_id = "all", time_step = "latest")
head(latest)
#> # A tibble: 6 × 15
#> station date_and_time air_temp rh dewpoint solar_rad x5min_precip
#> <chr> <dttm> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 akr02 2024-05-14 09:00:00 66.4 0.461 45.1 629 NA
#> 2 alt01 2024-05-14 09:00:00 68.5 0.331 38.4 677. NA
#> 3 avn01 2024-05-14 09:00:00 68.6 0.459 47.0 630. 0
#> 4 bla01 2024-05-14 08:55:00 56.7 0.43 34.4 677 0
#> 5 bnv01 2024-05-14 09:00:00 56.7 0.417 33.7 743. 0
#> 6 brg01 2024-05-14 09:00:00 70.7 0.338 40.8 566. NA
#> # ℹ 8 more variables: hourly_precip <dbl>, wind <dbl>, wind_dir <dbl>,
#> # gust_speed <dbl>, gust_dir <dbl>, x5cm_soil_temp <dbl>,
#> # x15cm_soil_temp <dbl>, date <date># coordinates for Denver
xlat <- 39.74
xlon <- -104.99
nearest_station <- find_closest_coagmet_station(xlat, xlon)
nearest_station
#> # A tibble: 1 × 14
#> station name location latitude_deg_n longitude_deg_e elevation_ft
#> <chr> <chr> <chr> <dbl> <dbl> <dbl>
#> 1 den01 Denver CSU Spur campus, H… 39.8 -105 5280
#> # ℹ 8 more variables: anemometer_height_m <dbl>, active <chr>,
#> # irrigation <chr>, first_observation <chr>, last_observation <chr>,
#> # timestep_s <dbl>, network <chr>, distance_m <dbl>df <- get_coagmet_data(station_id = "den01")
head(df)
#> # A tibble: 6 × 14
#> station date_and_time air_temp rh dewpoint solar_rad precip wind
#> <chr> <dttm> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 den01 2024-05-09 00:00:00 48.2 0.262 15.1 0 0 1.93
#> 2 den01 2024-05-09 01:00:00 48 0.255 14.3 0 0 2.15
#> 3 den01 2024-05-09 02:00:00 47.8 0.255 14.1 0 0 1.28
#> 4 den01 2024-05-09 03:00:00 47.2 0.284 16.1 0 0 0.68
#> 5 den01 2024-05-09 04:00:00 46.3 0.329 18.7 0 0 1.65
#> 6 den01 2024-05-09 05:00:00 46.2 0.347 19.8 0.82 0 3.1
#> # ℹ 6 more variables: wind_dir <dbl>, gust_speed <dbl>, gust_dir <dbl>,
#> # x5cm_soil_temp <dbl>, x15cm_soil_temp <dbl>, date <date>df |>
ggplot2::ggplot(ggplot2::aes(date_and_time, air_temp)) +
ggplot2::geom_line()
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_line()`).
#plot_coagmet_plotly(df, "air_temp")