GaussCrps: Calculate the Continuous Ranked Probability Score (CRPS) for...

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

Description

Calculate the Continuous Ranked Probability Score (CRPS) for forecasts issued as Normal distributions

Usage

GaussCrps(mean, sd, obs)

Arguments

mean	A vector of length N. The forecast means.
sd	A vector of length N. The forecast standard deviations.
obs	A numeric vector of length N of real-valued verifying observations

Value

numeric vector of length N with the CRPS values

References

Gneiting et al (2005). Calibrated Probabilistic Forecasting Using Ensemble Model Output Statistics and Minimum CRPS Estimation. Mon. Wea. Rev. doi: 10.1175/MWR2904.1

See Also

EnsCrps, DressCrps, ScoreDiff, SkillScore

Examples

data(eurotempforecast)
mean <- rowMeans(ens)
sd <- apply(ens, 1, sd)
mean(GaussCrps(mean, sd, obs))

Example output

[1] 0.1377574

SpecsVerification documentation built on March 26, 2020, 7:55 p.m.