EnsSprErr: Spread to Error Ratio

In easyVerification: Ensemble Forecast Verification for Large Data Sets

Spread to Error Ratio

Description

Computes the spread to error ratio (SPR) for probabilistic forecasts - not unlike the functions in SpecsVerification. SPR > 1 indicates overdispersion (underconfidence), whereas SPR < indicates overconfidence in the forecasts.

Usage

EnsSprErr(ens, obs)

Arguments

ens	n x k matrix of n forecasts for k ensemble members
obs	vector with n verifying observations

Details

Here we define the spread-error rate as the square root of the ratio of mean ensemble variance to the mean squared error of the ensemble mean with the verifying observations

See Also

veriApply, FairSprErr

Examples

tm <- toymodel()
EnsSprErr(tm$fcst, tm$obs)

## compute spread to error ratio using veriApply
veriApply("EnsSprErr", fcst = tm$fcst, obs = tm$obs)

easyVerification documentation built on Aug. 15, 2023, 9:06 a.m.