Rank Ensembles

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

Value

ranks: vector with the ranks of the ensemble forecasts

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.

References

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

Author

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

Examples

  data(cnrm.nino34.ce)
  fcst = cnrm.nino34.ce$fcst
  rank.ensembles(fcst)
#>  [1] 19.0 12.0 21.0 34.0  6.0 37.0 17.0 11.0 31.5 24.0  3.0  8.0 39.0  2.0  9.0
#> [16]  4.0 32.5 28.0 18.0 25.0 23.0 13.0 38.0 16.0 15.0 22.0 35.0 32.0  1.0 10.0
#> [31] 27.0 36.0 27.0 28.0 30.0 14.0 20.0 40.0  7.0  5.0