# packages knitr::opts_chunk$set( collapse = TRUE, comment = "" ) library(amadeus)
This vignette demonstrates how to download, process, and calculate covariates from the NOAA North American Regional Reanalysis (NARR) dataset using amadeus
functions.
Details are provided for each function's parameters and outputs.
The examples utilize daily air temperature at 2m height ("air.2m") data.
The messages returned by amadeus
functions have been omitted for brevity.
Start by downloading the netCDF data files with download_data
.
dataset_name = "narr"
: NARR dataset acronym.variable = "air.2m"
: air temperature at 2m height variable code.year = c(2021, 2022)
: years of interest.directory_to_save = dir
: directory to save the downloaded files.acknowledgement = TRUE
: acknowledge that the raw data files are large and may consume lots of local storage.download = TRUE
: download the data files.remove_command = TRUE
: remove the temporary command file used to download the data.hash = TRUE
: generate unique SHA-1 hash for the downloaded files.dir <- tempdir() amadeus::download_data( dataset_name = "narr", variable = "air.2m", year = c(2021, 2022), directory_to_save = dir, acknowledgement = TRUE, download = TRUE, remove_command = TRUE, hash = TRUE )
cat('[1] "e839448db9634a6534f89f5e8a1d18525dc3b206"')
Check the downloaded netCDF files.
list.files(dir, recursive = TRUE, pattern = "air.2m")
cat('[1] "air.2m/air.2m.2021.nc" "air.2m/air.2m.2022.nc"')
Import and process the downloaded netCDF files with process_covariates
.
covariate = "narr"
: NARR dataset acronym.variable = "air.2m"
: air temperature at 2m height variable code.date = c("2021-12-28", "2022-01-03")
: date range of interest.path = paste0(dir, "/air.2m")
: directory containing the downloaded files.air2m_process <- amadeus::process_covariates( covariate = "narr", variable = "air.2m", date = c("2021-12-28", "2022-01-03"), path = file.path(dir, "/air.2m") )
Check the processed SpatRaster
object.
air2m_process
cat('class : SpatRaster dimensions : 277, 349, 7 (nrow, ncol, nlyr) resolution : 32462.99, 32463 (x, y) extent : -16231.49, 11313351, -16231.5, 8976020 (xmin, xmax, ymin, ymax) coord. ref. : +proj=lcc +lat_0=50 +lon_0=-107 +lat_1=50 +lat_2=50 +x_0=5632642.22547 +y_0=4612545.65137 +datum=WGS84 +units=m +no_defs sources : air.2m.2021.nc:air (4 layers) air.2m.2022.nc:air (3 layers) varnames : air (Daily Air Temperature at 2 m) air (Daily Air Temperature at 2 m) names : air.2~11228, air.2~11229, air.2~11230, air.2~11231, air.2~20101, air.2~20102, ... unit : K, K, K, K, K, K, ... time : 2021-12-28 to 2022-01-03 UTC ')
terra::plot(air2m_process[[1]])
{style="display: block; margin-left: auto; margin-right: auto;"}
Calculate covariates for North Carolina county boundaries with calculate_covariates
.
County boundaries are accessed with the tigris::counties
function.\insertRef{package_tigris}
covariate = "narr"
: NARR dataset acronym.from = air2m_process
: processed SpatRaster
object.locs = tigris::counties("NC", year = 2021)
: North Carolina county boundaries.locs_id = "NAME"
: county name identifier.radius = 0
: size of buffer radius around each county.geom = "terra"
: return covariates as a SpatVector
object.library(tigris) air2m_covar <- amadeus::calculate_covariates( covariate = "narr", from = air2m_process, locs = tigris::counties("NC", year = 2021), locs_id = "NAME", radius = 0, geom = "terra" )
Check the calculated covariates SpatVector
object.
air2m_covar
cat('class : SpatVector geometry : polygons dimensions : 700, 3 (geometries, attributes) extent : 7731783, 8506154, 3248490, 3694532 (xmin, xmax, ymin, ymax) coord. ref. : +proj=lcc +lat_0=50 +lon_0=-107 +lat_1=50 +lat_2=50 +x_0=5632642.22547 +y_0=4612545.65137 +datum=WGS84 +units=m +no_defs names : NAME time air.2m_0 type : <chr> <POSIXt> <num> values : Chatham 2021-12-28 289.3 Alamance 2021-12-28 288.8 Davidson 2021-12-28 289.1 ')
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