FitAkdParameters: Fit the 5 parameters used for affine kernel dressing by...

In sieste/SpecsVerification: Forecast Verification Routines for Ensemble Forecasts of Weather and Climate

Description

Fit the 5 parameters used for affine kernel dressing by minimum CRPS estimation.

Usage

FitAkdParameters(ens, obs)

Arguments

ens	a N*R matrix. An archive of R-member ensemble forecasts for N time instances.
obs	a vector of length N. The verifying observations corresponding to the N ensemble forecasts.

Details

Affine Kernel Dressing transforms the discrete K-member forecast ensemble at time instance n, 'ens[n, ]', to a continuous distribution function for the target 'y' by the equation:

p(y|ens) = 1 / K * sum dnorm(y, z.i, s)
where s = (4/3/K)^0.4 * (s1 + s2 * a^2 * var(ens))
and z.i = r1 + r2 * mean(ens) + a * ens

The parameters r1, r2, a, s1, s2 are fitted by minimizing the continuously ranked probability score (CRPS). The optimization is carried out using the R function 'optim(...)'.

Since the evaluation of the CRPS is numerically expensive, the optimization can take a long time. Speed can be increased by optimizing the parameters only for a part of the forecast instances.

Value

The function returns a list of 5 parameters for affine kernel dressing.

References

Broecker J. and Smith L. (2008). From ensemble forecasts to predictive distribution functions. Tellus (2008), 60A, 663–678. doi: 10.1111/j.1600-0870.2008.00333.x.

See Also

DressEnsemble, DressCrps, DressIgn, PlotDressedEns, GetDensity

Examples

data(eurotempforecast)
FitAkdParameters(ens, obs)

sieste/SpecsVerification documentation built on May 29, 2019, 9:59 p.m.