
Calculate precipitation statistics based on CHIRPS
Source:R/calc_precipitation_chirps.R
precipitation_chirps.Rd
This functions allows to calculate precipitation statistics based on the
CHIRPS rainfall estimates. Corresponding to the time-frame of the analysis
of the portfolio, monthly precipitation statistics are calculated. These include
the total rainfall amount, rainfall anomaly against the 1981-2010 climate normal,
and the Standardized Precipitation Index (SPI) which is available for scales
between 1 and 48 months. Th function needs the SPEI
package to be
installed.
The required resources for this indicator are:
Format
A tibble with a column for years, months, absolute rainfall (in mm), rainfall anomaly (in mm) and one or more columns per selected time-scale for SPI (dimensionless).
Details
The following arguments can be set:
- scales_spi
An integer vector indicating the scales for which to calculate the SPI.
- spi_previous_year
An integer specifying how many previous years to include in order to fit the SPI. Defaults to 8 years.
- engine
The preferred processing functions from either one of "zonal", "extract" or "exactextract" as character.
Examples
if (Sys.getenv("NOT_CRAN") == "true") {
library(sf)
library(mapme.biodiversity)
temp_loc <- file.path(tempdir(), "mapme.biodiversity")
if (!file.exists(temp_loc)) {
dir.create(temp_loc)
resource_dir <- system.file("res", package = "mapme.biodiversity")
file.copy(resource_dir, temp_loc, recursive = TRUE)
}
(try(aoi <- system.file("extdata", "sierra_de_neiba_478140_2.gpkg",
package = "mapme.biodiversity"
) %>%
read_sf() %>%
init_portfolio(
years = 2010,
outdir = file.path(temp_loc, "res"),
tmpdir = tempdir(),
verbose = FALSE
) %>%
get_resources("chirps") %>%
calc_indicators("precipitation_chirps",
engine = "exactextract",
scales_spi = 3,
spi_prev_years = 8
) %>%
tidyr::unnest(precipitation_chirps)))
}
#> Simple feature collection with 12 features and 9 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 × 10
#> WDPAID NAME DESIG_ENG ISO3 assetid dates absolute anomaly spi_3
#> <dbl> <chr> <chr> <chr> <int> <date> <dbl> <dbl> <dbl>
#> 1 478140 Sierra de … National… DOM 1 2010-01-01 17.9 7.49 -0.201
#> 2 478140 Sierra de … National… DOM 1 2010-02-01 21.7 1.69 1.15
#> 3 478140 Sierra de … National… DOM 1 2010-03-01 33.3 -8.03 0.682
#> 4 478140 Sierra de … National… DOM 1 2010-04-01 139. 37.3 0.507
#> 5 478140 Sierra de … National… DOM 1 2010-05-01 178. -16.1 0.172
#> 6 478140 Sierra de … National… DOM 1 2010-06-01 206. 93.9 0.818
#> 7 478140 Sierra de … National… DOM 1 2010-07-01 143. 67.9 0.989
#> 8 478140 Sierra de … National… DOM 1 2010-08-01 96.7 -8.52 1.57
#> 9 478140 Sierra de … National… DOM 1 2010-09-01 96.5 -52.7 0.126
#> 10 478140 Sierra de … National… DOM 1 2010-10-01 91.4 -52.4 -0.967
#> 11 478140 Sierra de … National… DOM 1 2010-11-01 117. 31.3 -0.269
#> 12 478140 Sierra de … National… DOM 1 2010-12-01 10.8 -2.07 0.229
#> # ℹ 1 more variable: geom <POLYGON [°]>