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