Modular function that 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