R: Multivariate bias correction (Pearson correlation)

MBCp {MBC}

R Documentation

Multivariate bias correction (Pearson correlation)

Description

Multivariate bias correction that matches marginal distributions using QDM and the Pearson correlation dependence structure following Cannon (2016).

Usage

MBCp(o.c, m.c, m.p, iter=20, cor.thresh=1e-4,
     ratio.seq=rep(FALSE, ncol(o.c)), trace=0.05,
     trace.calc=0.5*trace, jitter.factor=0, n.tau=NULL,
     ratio.max=2, ratio.max.trace=10*trace, ties='first',
     qmap.precalc=FALSE, silent=FALSE, subsample=NULL,
     pp.type=7)

Arguments

`o.c`	matrix of observed samples during the calibration period.
`m.c`	matrix of model outputs during the calibration period.
`m.p`	matrix of model outputs during the projected period.
`iter`	maximum number of algorithm iterations.
`cor.thresh`	if greater than zero, a threshold indicating the change in magnitude of Pearson correlations required for convergence.
`ratio.seq`	vector of logical values indicating if samples are of a ratio quantity (e.g., precipitation).
`trace`	numeric values indicating thresholds below which values of a ratio quantity (e.g., `ratio=TRUE`) should be considered exact zeros.
`trace.calc`	numeric values of thresholds used internally when handling of exact zeros; defaults to one half of `trace`.
`jitter.factor`	optional strength of jittering to be applied when quantities are quantized.
`n.tau`	number of quantiles used in the quantile mapping; `NULL` equals the length of the `m.p` series.
`ratio.max`	numeric values indicating the maximum proportional changes allowed for ratio quantities below the `ratio.max.trace` threshold.
`ratio.max.trace`	numeric values of trace thresholds used to constrain the proportional change in ratio quantities to `ratio.max`; defaults to ten times `trace`.
`ties`	method used to handle ties when calculating ordinal ranks.
`qmap.precalc`	logical value indicating if `m.c` and `m.p` are outputs from `QDM`.
`silent`	logical value indicating if algorithm progress should be reported.
`subsample`	use `subsample` draws of size `n.tau` to calculate initial empirical quantiles; if `NULL`, calculate normally.
`pp.type`	type of plotting position used in `quantile`.

Value

a list of with elements consisting of:

`mhat.c`	matrix of bias corrected `m.c` values for the calibration period.
`mhat.p`	matrix of bias corrected `m.p` values for the projection period.

References

Cannon, A.J., 2016. Multivariate bias correction of climate model output: Matching marginal distributions and inter-variable dependence structure. Journal of Climate, 29:7045-7064. doi:10.1175/JCLI-D-15-0679.1