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Monthly climate normals for an arbitrary period from climr

Source: R/wet_climr_normals.R
wet_climr_normals.Rd

Downscales climr's reference climatology onto an elevation grid, shifted to the mean of an observed time series over years. climr expresses each observed year as an anomaly on its 1961-1990 reference period: a ratio for precipitation and an offset for temperature. Both are linear, so averaging the anomalies before downscaling gives the same normal as downscaling each year and averaging, at a thirtieth of the cost.

Usage

wet_climr_normals(
  dem,
  years = 1981:2010,
  dataset = "mswx.blend",
  vars = c(sprintf("PPT_%02d", 1:12), sprintf("Tave_%02d", 1:12)),
  dir = "data/climr",
  overwrite = FALSE
)

Arguments

dem

Path to a one-layer elevation raster (m, EPSG:4326), or a SpatRaster. Its grid is the output grid.

years

Integer vector of years to average.

dataset

climr observed time series: "mswx.blend" (default), "climatena" or "cru.gpcc". The ClimateNA series is NA over coastal islands (Haida Gwaii, northern Vancouver Island) on its 1-degree grid, so averaging its anomalies leaves those islands without normals; the 0.5-degree MSWX blend covers them.

vars

climr variable codes to return: monthly PPT_MM, Tave_MM, Tmax_MM, Tmin_MM, and MAP, MAT. Derived variables that are not linear in the anomalies (degree days, PAS, CMD) are refused, since averaging anomalies first would bias them.

dir

Cache directory.

overwrite

Logical. Rebuild even when cached.

Value

Path to a GeoTIFF with one layer per variable in vars.