EnsCrps: Calculate the ensemble-adjusted Continuous Ranked Probability...

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

Description

Calculate the ensemble-adjusted Continuous Ranked Probability Score (CRPS)

Usage

EnsCrps(ens, obs, R.new = NA)

FairCrps(ens, obs)

Arguments

ens	a N*R matrix representing N time instances of real-valued R-member ensemble forecasts
obs	a numeric vector of length N with real-valued observations
R.new	positive number, can be 'Inf', ensemble size for which the scores should be adjusted, default is NA for no adjustment

Details

'FairCrps(ens, obs)' returns 'EnsCrps(ens, obs, R.new=Inf)'

Value

numeric vector of length N with the ensemble-adjusted CRPS values

References

Ferro CAT, Richardson SR, Weigel AP (2008) On the effect of ensemble size on the discrete and continuous ranked probability scores. Meteorological Applications. doi: 10.1002/met.45

See Also

EnsBrier, EnsRps, DressCrps, GaussCrps, ScoreDiff, SkillScore

Examples

data(eurotempforecast)
mean(EnsCrps(ens, obs, R.new=Inf))

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