mul: Multiplicative De-biasing

In jonasbhend/biascorrection: Bias Correct Ensemble Forecasts

Multiplicative De-biasing

Description

Computes multiplicative de-biasing without smoothing

Usage

mul(fcst, obs, fcst.out = fcst, ...)

Arguments

fcst	n x m x k array of n lead times, m forecasts, of k ensemble members
obs	n x m matrix of veryfing observations
fcst.out	array of forecast values to which bias correction should be applied (defaults to fcst)
...	additional arguments for compatibility with other bias correction methods

Details

The bias corrected forecast is scaled by the lead-time dependent ratio of observed to forecast climatology, where the observed and the forecast climatologies are smoothed using a loess smoothing.

See Also

smoothobs_mul smooth_mul unbias

Examples

## initialise forcast observation pairs
signal <- outer(1.5 + sin(seq(0,4,length=215)), rnorm(30)**2, '*')
fcst <- array(rnorm(length(signal)*15)**2, c(dim(signal), 15)) * c(signal)
obs <- rnorm(length(signal), mean=1.4)**2 * signal 
fcst.debias <- biascorrection:::mul(fcst[,1:20,], obs[,1:20], fcst.out=fcst)

jonasbhend/biascorrection documentation built on Nov. 11, 2023, 1:16 a.m.