rank.ensembles: Rank Ensembles

In afc: Generalized Discrimination Score

Description

Routine to rank a set of given ensemble forecasts according to their "value"

Usage

rank.ensembles(fcst)

Arguments

fcst	two-dimensional array with ensemble forecasts; dim(fcst)[1] = number of ensemble forecasts; dim(fcst)[2] = number of ensemble members

Details

This routine ranks a set of ensemble forecasts according to their "value". The higher the "value" of an ensemble forecasts, the higher the rank. The following principle is applied: Assume two ensembles A and B are to be ranked. Without loss of generality, we define A>B if the probability of a random ensemble member of A being larger than a random ensemble member of B exceeds 0.5. This probability is calculated by a 2AFC-like approach based on Eq. 8 of Mason and Weigel (2009). By pairwise comparison of all ensembles, the final ranking is obtained.

Value

ranks

vector with the ranks of the ensemble forecasts

Author(s)

Andreas Weigel, Federal Office of Meteorology and Climatology, MeteoSwiss, Zurich, Switzerland

References

S.J. Mason and A.P. Weigel, 2009. A generic verification framework for administrative purposes. Mon. Wea. Rev., 137, 331-349

See Also

afc.de afc.me afc.ce afc

Examples

  #Load a set of ensemble forecasts
  data(cnrm.nino34.ce)
  fcst = cnrm.nino34.ce$fcst

  #Rank ensemble forecasts
  rank.ensembles(fcst)

afc documentation built on May 1, 2019, 9:46 p.m.