RF_Weights {CSTools}

Compute climatological weights for RainFARM stochastic precipitation downscaling

Description

Compute climatological ("orographic") weights from a fine-scale precipitation climatology file.

Usage

RF_Weights(
  zclim,
  latin,
  lonin,
  nf,
  lat,
  lon,
  fsmooth = TRUE,
  lonname = "lon",
  latname = "lat",
  ncores = NULL
)

Arguments

zclim

A multi-dimensional array with named dimension containing at least one precipiation field with spatial dimensions.

latin

A vector indicating the latitudinal coordinates corresponding to the zclim parameter.

lonin

A vector indicating the longitudinal coordinates corresponding to the zclim parameter.

nf

Refinement factor for downscaling (the output resolution is increased by this factor).

lat

Vector of latitudes. The number of longitudes and latitudes is expected to be even and the same. If not the function will perform a subsetting to ensure this condition.

lon

Vector of longitudes.

fsmooth

Logical to use smooth conservation (default) or large-scale box-average conservation.

lonname

A character string indicating the name of the longitudinal dimension set as 'lon' by default.

latname

A character string indicating the name of the latitudinal dimension set as 'lat' by default.

ncores

An integer that indicates the number of cores for parallel computations using multiApply function. The default value is one.

Value

An object of class 's2dv_cube' containing in matrix data the weights with dimensions (lon, lat).

Author(s)

Jost von Hardenberg - ISAC-CNR, [e-mail]

References

Terzago, S., Palazzi, E., & von Hardenberg, J. (2018). Stochastic downscaling of precipitation in complex orography: A simple method to reproduce a realistic fine-scale climatology. Natural Hazards and Earth System Sciences, 18(11), 2825-2840. doi: 10.5194/nhess-18-2825-2018.

Examples

a <- array(1:2500, c(lat = 50, lon = 50))
res <- RF_Weights(a, seq(0.1 ,5, 0.1), seq(0.1 ,5, 0.1), 
                 nf = 5, lat = 1:5, lon = 1:5)