R: Multivariate bias correction (Spearman rank correlation)

MBCr {MBC}

R Documentation

Multivariate bias correction (Spearman rank correlation)

Description

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

Usage

MBCr(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 Spearman rank 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 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