On reliability analysis of multi-categorical forecasts

Full text not archived in this repository.

Please see our End User Agreement.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

Bröcker, J. (2008) On reliability analysis of multi-categorical forecasts. Nonlinear Processes in Geophysics, 15 (4). pp. 661-673. ISSN 1023-5809 doi: 10.5194/npg-15-661-2008

Abstract/Summary

Reliability analysis of probabilistic forecasts, in particular through the rank histogram or Talagrand diagram, is revisited. Two shortcomings are pointed out: Firstly, a uniform rank histogram is but a necessary condition for reliability. Secondly, if the forecast is assumed to be reliable, an indication is needed how far a histogram is expected to deviate from uniformity merely due to randomness. Concerning the first shortcoming, it is suggested that forecasts be grouped or stratified along suitable criteria, and that reliability is analyzed individually for each forecast stratum. A reliable forecast should have uniform histograms for all individual forecast strata, not only for all forecasts as a whole. As to the second shortcoming, instead of the observed frequencies, the probability of the observed frequency is plotted, providing and indication of the likelihood of the result under the hypothesis that the forecast is reliable. Furthermore, a Goodness-Of-Fit statistic is discussed which is essentially the reliability term of the Ignorance score. The discussed tools are applied to medium range forecasts for 2 m-temperature anomalies at several locations and lead times. The forecasts are stratified along the expected ranked probability score. Those forecasts which feature a high expected score turn out to be particularly unreliable.

Altmetric Badge

Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/29152
Identification Number/DOI 10.5194/npg-15-661-2008
Refereed Yes
Divisions No Reading authors. Back catalogue items
Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher European Geosciences Union
Download/View statistics View download statistics for this item

University Staff: Request a correction | Centaur Editors: Update this record

Search Google Scholar