RFSlope {CSTools}

RainFARM spectral slopes from an array (reduced version)

Description

This function computes spatial spectral slopes from an array, to be used for RainFARM stochastic precipitation downscaling method.

Usage

RFSlope(
  data,
  kmin = 1,
  time_dim = NULL,
  lon_dim = "lon",
  lat_dim = "lat",
  ncores = NULL
)

Arguments

data

Array containing the spatial precipitation fields to downscale. The input array is expected to have at least two dimensions named "lon" and "lat" by default (these default names can be changed with the lon_dim and lat_dim parameters) and one or more dimensions over which to average the slopes, which can be specified by parameter time_dim.

kmin

First wavenumber for spectral slope (default kmin=1).

time_dim

String or character array with name(s) of dimension(s) (e.g. "ftime", "sdate", "member" ...) over which to compute spectral slopes. If a character array of dimension names is provided, the spectral slopes will be computed as an average over all elements belonging to those dimensions. If omitted one of c("ftime", "sdate", "time") is searched and the first one with more than one element is chosen.

lon_dim

Name of lon dimension ("lon" by default).

lat_dim

Name of lat dimension ("lat" by default).

ncores

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

Value

RFSlope() returns spectral slopes using the RainFARM convention (the logarithmic slope of k*|A(k)|^2 where A(k) are the spectral amplitudes). The returned array has the same dimensions as the input array, minus the dimensions specified by lon_dim, lat_dim and time_dim.

Author(s)

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

Examples

# Example for the 'reduced' RFSlope function 
# Create a test array with dimension 8x8 and 20 timesteps, 
# 3 starting dates and 20 ensemble members.
pr <- 1:(4*3*8*8*20)
dim(pr) <- c(ensemble = 4, sdate = 3, lon = 8, lat = 8, ftime = 20)
# Compute the spectral slopes ignoring the wavenumber
# corresponding to the largest scale (the box)
slopes <- RFSlope(pr, kmin = 2, time_dim = 'ftime')