Assessing the reliability of ensemble forecasting systems under serial dependence

Bröcker, J. (2018) Assessing the reliability of ensemble forecasting systems under serial dependence. Quarterly Journal of the Royal Meteorological Society, 144 (717). pp. 2666-2675. ISSN 1477-870X doi: 10.1002/qj.3379

Abstract/Summary

The problem of testing the reliability of ensemble forecasting systems is revisited. A popular tool to assess the reliability of ensemble forecasting systems (for scalar verifications) is the rank histogram; this histogram is expected to be more or less flat, since for a reliable ensemble, the ranks are uniformly distributed among their possible outcomes. Quantitative tests for flatness (e.g. Pearson's goodness–of–fit test) have been suggested; without exception though, these tests assume the ranks to be a sequence of independent random variables, which is not the case in general as can be demonstrated with simple toy examples. In this paper, tests are developed that take the temporal correlations between the ranks into account. A refined analysis exploiting the reliability property shows that the ranks still exhibit strong decay of correlations. This property is key to the analysis, and the proposed tests are valid for general ensemble forecasting systems with minimal extraneous assumptions.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/78201
Item Type	Article
Refereed	Yes
Divisions	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	Royal Meteorological Society
Download/View statistics	View download statistics for this item