petExtremes {envirem}

PET Extremes

Description

Calculates summed PET of the coldest, warmest, wettest and driest quarters.

Usage

petExtremes(PETstack, precipStack, meantempStack)

Arguments

PETstack

SpatRaster of monthly PET, layer names assumed to end in month numbers

precipStack

SpatRaster of monthly precipitation

meantempStack

SpatRaster of monthly mean temperature

Details

Generates summed monthly PET for the warmest, coldest, wettest and driest 3 consecutive months. Previous versions of the envirem package incorrectly calculated mean quarterly PET.

Value

SpatRaster of PETColdestQuarter, PETWarmestQuarter, PETWettestQuarter, PETDriestQuarter in mm / month.

Author(s)

Pascal Title

References

Metzger, M.J., Bunce, R.G.H., Jongman, R.H.G., Sayre, R., Trabucco, A. & Zomer, R. (2013). A high-resolution bioclimate map of the world: a unifying framework for global biodiversity research and monitoring. Global Ecology and Biogeography, 22, 630-638.

See Also

monthlyPET

Examples

# Find example rasters
rasterFiles <- list.files(system.file('extdata', package='envirem'), full.names=TRUE)
env <- rast(rasterFiles)

# identify the appropriate layers
meantemp <- grep('mean', names(env), value=TRUE)
solar <- grep('solrad', names(env), value=TRUE)
maxtemp <- grep('tmax', names(env), value=TRUE)
mintemp <- grep('tmin', names(env), value=TRUE)
precip <- grep('prec', names(env), value=TRUE)

# read them in as SpatRasters
meantemp <- env[[meantemp]]
solar <- env[[solar]]
maxtemp <- env[[maxtemp]]
mintemp <- env[[mintemp]]
tempRange <- abs(maxtemp - mintemp)
precip <- env[[precip]]

# set up naming scheme - only precip is different from default
assignNames(precip = 'prec_##')

# get monthly PET
pet <- monthlyPET(meantemp, solar, tempRange)

petExtremes(pet, precip, meantemp)

# set back to defaults
assignNames(reset = TRUE)