Rankhist: Rank histogram for ensemble forecasts

In SpecsVerification: Forecast Verification Routines for Ensemble Forecasts of Weather and Climate

Description

Calculate the rank histogram for an archive of ensemble forecasts and their corresponding verifying observations.

Usage

Rankhist(ens, obs, reduce.bins = 1, handle.na = "na.fail")

Arguments

ens	matrix of dimension (N,K). An archive of K-member ensemble forecasts for N time instances.
obs	vector of length N. The corresponding verifying observations.
reduce.bins	number of adjacent bins that will be merged into one bin; has to be a divisor of K+1
handle.na	how should missing values in ensemble and observation data be handled; possible values are 'na.fail' (fails if any data is missing) and 'use.complete' (only uses times where all ensemble members and obs are available); default: 'na.fail'

Value

a vector of length (K+1)/reduce.bins containing the rank counts

References

Anderson J.L. (1996). A Method for Producing and Evaluating Probabilistic Forecasts from Ensemble Model Integrations. J. Climate, 9, 1518–1530. Hammill T.M. (2001). Interpretation of Rank Histograms for Verifying Ensemble Forecasts. Mon. Wea. Rev., 129, 550–560.

See Also

PlotRankhist, TestRankhist

Examples

data(eurotempforecast)
rh <- Rankhist(ens, obs)

Example output

SpecsVerification documentation built on March 26, 2020, 7:55 p.m.