smoothobs_scale: Mean De-biasing With Variance Scaling

In jonasbhend/biascorrection: Bias Correct Ensemble Forecasts

Mean De-biasing With Variance Scaling

Description

Computes mean de-biasing with loess smoothing (obs. only) and adjusts variance

Usage

smoothobs_scale(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 standard deviation of the observations is computed against the smoothed climatology (1/n definition) in order to get consistent results. The disadvantage of this approach is the dependence of the scaling on the climatological fit.

Examples

## initialise forcast observation pairs
fcst <- array(rnorm(215*30*51, mean=3, sd=0.2), c(215, 30, 51)) + 
0.5*sin(seq(0,4,length=215))
obs <- array(rnorm(215*30, mean=2), c(215, 30)) + 
sin(seq(0,4, length=215))
fcst.debias <- biascorrection:::smoothobs_scale(fcst[,1:20,], obs[,1:20], fcst.out=fcst, span=0.5)

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