smoothobs_mul: Multiplicative De-biasing With Smoothed Observation...

In jonasbhend/biascorrection: Bias Correct Ensemble Forecasts

Multiplicative De-biasing With Smoothed Observation Climatology

Description

Computes multiplicative de-biasing with loess smoothing (obs. only)

Usage

smoothobs_mul(fcst, obs, fcst.out = fcst, span = min(1, 31/nrow(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)
span	the parameter which controls the degree of smoothing (see loess)
...	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 climatology is smoothed using a loess smoothing.

See Also

smooth_mul smoothobs

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:::smoothobs_mul(fcst[,1:20,], obs[,1:20], fcst.out=fcst, span=0.5)

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