# amadeus workflow

#### Mitchell Manware

#### 2024-07-29

The following vignette will demonstrate how to download, process, and calculate covariates using `amadeus` functions. The examples will utilize air temperature at 2m height (“air.2m”) data from the NOAA North American Regional Reanalysis (NARR) dataset.

## Download

Download data for years 2021 and 2022 with `download_data`.

    dir <- tempdir()
    download_data(
      dataset_name = "narr",
      variable = "air.2m",
      year = c(2021, 2022),
      directory_to_save = dir,
      acknowledgement = TRUE,
      download = TRUE,
      remove_command = TRUE
    )

Check for the downloaded files.

    list.files(paste0(dir, "/air.2m"))

    [1] "air.2m.2021.nc" "air.2m.2022.nc"

## Process

Process data for all dates from December 28, 2021 to January 3, 2022 with `process_covariates`.

    temp_process <- process_covariates(
      covariate = "narr",
      variable = "air.2m",
      date = c("2021-12-28", "2022-01-03"),
      path = paste0(dir, "/air.2m")
    )

Check the processed `SpatRaster` object.

    temp_process

    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

## Calculate covariates

Calculate covariates for North Carolina county boundaries with `calc_covariates`. County boundaries are accessed with the `tigris::counties` function. `geom = TRUE` will return the covariates as a `SpatVector` object.

    library(tigris)
    temp_covar <- calc_covariates(
      covariate = "narr",
      from = temp_process,
      locs = tigris::counties("NC", year = 2021),
      locs_id = "NAME",
      radius = 0,
      geom = TRUE
    )

Check the calculated covariates `SpatVector` object.

    temp_covar

    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