snotelr

Introduction

The SNOTEL network is composed of over 800 automated data collection sites located in remote, high-elevation mountain watersheds in the western U.S. They are used to monitor snowpack, precipitation, temperature, and other climatic conditions. The data collected at SNOTEL sites are transmitted to a central database. This package queries this centralized database to provide easy access to these data and additional seasonal metrics of snow accumulation (snow phenology).

Downloading site meta-data

The SNOTEL network consists of a vast number of observation sites, all of them listed together with their meta-data on the SNOTEL website. The snotel_info() function allows you to query this table and import it as a neat table into R. Some of the meta-data, in particular the site id (site_id), you will need of you want to download the data for a site. You can save this table to disk using the path variable to specify a location on your computer where to store the data as a csv. If this parameter is missing the data is returned as an R variable.

# download and list site information
site_meta_data <- snotel_info()
head(site_meta_data)
#>   network state         site_name
#> 1    SNTL    AK frostbite bottom 
#> 2    SNTL    AK          mcgrath 
#> 3    SNTL    UT    parleys upper 
#> 4    SNTL    AK      east palmer 
#> 5    SNTL    AK        galena ak 
#> 6    SNTL    MT        jl meadow 
#>                                          description      start        end
#> 1 Fishhook Creek-Little Susitna River (190205051202) 2019-02-01 2020-05-08
#> 2     Town of McGrath-Kuskokwim River (190304050502) 2019-08-01 2020-05-08
#> 3                       Parleys Creek (160202040302) 2019-08-01 2020-05-08
#> 4              Outlet Matanuska River (190204020709) 2018-07-01 2020-05-08
#> 5           Louden Slough-Yukon River (190902051104) 2018-08-01 2020-05-08
#> 6      Dad Creek-Medicine Lodge Creek (100200011202) 2017-10-01 2020-05-08
#>   latitude longitude elev            county site_id
#> 1    61.75   -149.27  823 Matanuska-susitna     641
#> 2    62.95   -155.61  104     Yukon-koyukuk     785
#> 3    40.70   -111.61 2546         Salt Lake     856
#> 4    61.60   -149.10   70 Matanuska-susitna     953
#> 5    64.70   -156.71  125     Yukon-koyukuk     429
#> 6    44.78   -113.12 2682        Beaverhead    1287

Downloading site data

If you downloaded the meta-data for all sites you can make a selection using either geographic coordinates, or state columns. For the sake of brevity I’ll only query data for one site using its site_id below. By default the data, reported in imperial values, are converted to metric measurements.

# downloading data for a random site
snow_data <- snotel_download(site_id = 670, internal = TRUE)
#> Downloading site: northeast entrance , with id: 670

# show the data
head(snow_data)
#>   network state           site_name               description      start
#> 1    SNTL    MT northeast entrance  Cold Creek (100700010602) 1937-10-01
#> 2    SNTL    MT northeast entrance  Cold Creek (100700010602) 1937-10-01
#> 3    SNTL    MT northeast entrance  Cold Creek (100700010602) 1937-10-01
#> 4    SNTL    MT northeast entrance  Cold Creek (100700010602) 1937-10-01
#> 5    SNTL    MT northeast entrance  Cold Creek (100700010602) 1937-10-01
#> 6    SNTL    MT northeast entrance  Cold Creek (100700010602) 1937-10-01
#>          end latitude longitude elev                    county site_id
#> 1 2020-05-08    45.01   -110.01 2240 Yellowstone National Park     670
#> 2 2020-05-08    45.01   -110.01 2240 Yellowstone National Park     670
#> 3 2020-05-08    45.01   -110.01 2240 Yellowstone National Park     670
#> 4 2020-05-08    45.01   -110.01 2240 Yellowstone National Park     670
#> 5 2020-05-08    45.01   -110.01 2240 Yellowstone National Park     670
#> 6 2020-05-08    45.01   -110.01 2240 Yellowstone National Park     670
#>         date snow_water_equivalent precipitation_cumulative temperature_max
#> 1 1966-10-01                     0                       NA              NA
#> 2 1966-10-02                     8                       NA              NA
#> 3 1966-10-03                     0                       NA              NA
#> 4 1966-10-04                     0                       NA              NA
#> 5 1966-10-05                     0                       NA              NA
#> 6 1966-10-06                     0                       NA              NA
#>   temperature_min temperature_mean precipitation
#> 1              NA               NA            NA
#> 2              NA               NA            NA
#> 3              NA               NA            NA
#> 4              NA               NA            NA
#> 5              NA               NA            NA
#> 6              NA               NA            NA

# A plot of snow accummulation through the years
plot(as.Date(snow_data$date),
     snow_data$snow_water_equivalent,
     type = "l",
     xlab = "Date",
     ylab = "SWE (mm)")

Calculating snow phenology from downloaded data or data frames

Although the main function of the package is to provide easy access to the SNOTEL data a function snotel_phenology() is provided to calculate seasonal metrics of snow deposition.

# calculate snow phenology
phenology <- snotel_phenology(snow_data)

# subset data to the first decade of the century
snow_data_subset <- subset(snow_data, as.Date(date) > as.Date("2000-01-01") &
                             as.Date(date) < as.Date("2010-01-01"))

# plot the snow water equivalent time series
plot(as.Date(snow_data_subset$date),
     snow_data_subset$snow_water_equivalent,
     type = "l",
     xlab = "Date",
     ylab = "SWE (mm)")

# plot the dates of first snow accumulation as a red dot
points(as.Date(paste(phenology$year, phenology$first_snow_acc),"%Y %j"),
       rep(1,nrow(phenology)),
       col = "red",
       pch = 19,
       cex = 0.5)

A list of all provided snow phenology statistics is provided below.

Reference

Please use the proper Zenodo DOI when using this software for research purposes.