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Read WorldClim bioclimatic variables from Google Earth Engine

Source: R/read_worldclim.R
read_worldclim.Rd

[Experimental]

Reads WorldClim V1 bioclimatic variables (WORLDCLIM/V1/BIO) from Google Earth Engine. This is a static dataset representing 1960-1990 climate normals at ~1 km resolution. Note that Google Earth Engine hosts WorldClim version 1, not version 2; the two differ in both their normal period and their source publication.

Usage

read_worldclim(
  region,
  variable = "bio01",
  backend = c("rest", "rgee"),
  cache = TRUE,
  max_tries = 3L,
  initial_delay = 1L
)

Arguments

region

An sf::sf, sf::st_sfc(), or terra::ext() object defining the spatial extent. Required.

variable

Character. Bioclimatic variable band name. One of "bio01" through "bio19". Default "bio01" (annual mean temperature, degrees C x 10).

backend

Character. "rest" (default) or "rgee".

cache

Logical. Use disk cache? Default TRUE.

max_tries

Integer. Retry attempts. Default 3L.

initial_delay

Numeric. Initial retry delay in seconds. Default 1.

Value

A terra::rast() SpatRaster. CRS: EPSG:4326. Values depend on the variable (see WorldClim documentation).

Data availability

Static (1960-1990 normals). Global land. ~1 km spatial resolution.

Variables

  • bio01: Annual Mean Temperature (deg C x 10)

  • bio02: Mean Diurnal Range

  • bio03: Isothermality

  • bio04: Temperature Seasonality

  • bio05-bio11: Various temperature metrics

  • bio12: Annual Precipitation (mm)

  • bio13-bio19: Various precipitation metrics

References

Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G. & Jarvis, A. (2005). Very High Resolution Interpolated Climate Surfaces for Global Land Areas. International Journal of Climatology, 25(15), 1965-1978. doi:10.1002/joc.1276

See also

read_gee(), collect_gee_data()

Other GEE readers: read_chirps(), read_era5(), read_gee(), read_landsat(), read_modis_lst(), read_modis_ndvi(), read_sentinel2(), read_slga(), read_srtm()

Examples

if (FALSE) { # interactive()
# Annual mean temperature
temp <- read_worldclim(region = terra::ext(138, 140, -36, -34))

# Annual precipitation
precip <- read_worldclim(region = terra::ext(138, 140, -36, -34),
                         variable = "bio12")
}