eqm: Empirical Quantile Mapping method for bias correction

In SantanderMetGroup/downscaleR: A climate4R package for statistical downscaling <http://meteo.unican.es/climate4r>

Empirical Quantile Mapping method for bias correction

Description

Implementation of Empirical Quantile Mapping method for bias correction

Usage

eqm(o, p, s, precip, pr.threshold, n.quantiles, extrapolation)

Arguments

o	A vector (e.g. station data) containing the observed climate data for the training period
p	A vector containing the simulated climate by the model for the training period.
s	A vector containing the simulated climate for the variable used in p, but considering the test period.
precip	Logical for precipitation data. If TRUE Adjusts precipitation frequency in 'x' (prediction) to the observed frequency in 'y'. This is a preprocess to bias correct precipitation data following Themeßl et al. (2012). To adjust the frequency, parameter pr.threshold is used (see below).
pr.threshold	The minimum value that is considered as a non-zero precipitation. Ignored when precip = FALSE. See details in function biasCorrection.
n.quantiles	Integer indicating the number of quantiles to be considered when method = "eqm". Default is NULL, that considers all quantiles, i.e. n.quantiles = length(p).
extrapolation	Character indicating the extrapolation method to be applied to correct values in "s" that are out of the range of "p". Extrapolation is applied only to the "eqm" method, thus, this argument is ignored if other bias correction method is selected.

Author(s)

S. Herrera and M. Iturbide

SantanderMetGroup/downscaleR documentation built on July 4, 2023, 4:28 a.m.