Calculate precipitation sums based on CHIRPS — precipitation

This functions allows to calculate precipitation sums based on the CHIRPS rainfall estimates. Corresponding to the time-frame of the analysis of the portfolio, monthly precipitation sums are calculated.

Usage

calc_precipitation_chirps(years = 1981:2020, engine = "extract")

Arguments

years: A numeric vector indicating the years for which to calculate precipitation statistics.
engine: The preferred processing functions from either one of "zonal", "extract" or "exactextract" as character.

Value

A function that returns an indicator tibble with variable precipitation and sum of precipitation (in mm) as value.

Details

The required resources for this indicator are:

chirps

Examples

# \dontshow{
mapme.biodiversity:::.copy_resource_dir(file.path(tempdir(), "mapme-data"))
# }
# \dontrun{
library(sf)
library(mapme.biodiversity)

outdir <- file.path(tempdir(), "mapme-data")
dir.create(outdir, showWarnings = FALSE)

mapme_options(
  outdir = outdir,
  verbose = FALSE
)

aoi <- system.file("extdata", "sierra_de_neiba_478140_2.gpkg",
  package = "mapme.biodiversity"
) %>%
  read_sf() %>%
  get_resources(get_chirps(years = 2010)) %>%
  calc_indicators(
    calc_precipitation_chirps(
      years = 2010,
      engine = "extract"
    )
  ) %>%
  portfolio_long()

aoi
#> Simple feature collection with 12 features and 8 fields
#> Geometry type: POLYGON
#> Dimension:     XY
#> Bounding box:  xmin: -71.80933 ymin: 18.57668 xmax: -71.33201 ymax: 18.69931
#> Geodetic CRS:  WGS 84
#> # A tibble: 12 × 9
#>    WDPAID ISO3  assetid indicator       datetime            variable unit  value
#>     <dbl> <chr>   <int> <chr>           <dttm>              <chr>    <chr> <dbl>
#>  1 478140 DOM         1 precipitation_… 2010-01-01 00:00:00 precipi… mm      102
#>  2 478140 DOM         1 precipitation_… 2010-02-01 00:00:00 precipi… mm      129
#>  3 478140 DOM         1 precipitation_… 2010-03-01 00:00:00 precipi… mm      199
#>  4 478140 DOM         1 precipitation_… 2010-04-01 00:00:00 precipi… mm      827
#>  5 478140 DOM         1 precipitation_… 2010-05-01 00:00:00 precipi… mm     1067
#>  6 478140 DOM         1 precipitation_… 2010-06-01 00:00:00 precipi… mm     1220
#>  7 478140 DOM         1 precipitation_… 2010-07-01 00:00:00 precipi… mm      878
#>  8 478140 DOM         1 precipitation_… 2010-08-01 00:00:00 precipi… mm      588
#>  9 478140 DOM         1 precipitation_… 2010-09-01 00:00:00 precipi… mm      582
#> 10 478140 DOM         1 precipitation_… 2010-10-01 00:00:00 precipi… mm      560
#> 11 478140 DOM         1 precipitation_… 2010-11-01 00:00:00 precipi… mm      683
#> 12 478140 DOM         1 precipitation_… 2010-12-01 00:00:00 precipi… mm       59
#> # ℹ 1 more variable: geom <POLYGON [°]>
# }