Accessibility navigation


Assessing the reliability of ensemble forecasting systems under serial dependence

Broecker, 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

[img]
Preview
Text - Accepted Version
· Please see our End User Agreement before downloading.

863kB

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

To link to this item 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
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics
Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:78201
Publisher:Royal Meteorological Society

Downloads

Downloads per month over past year

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

Page navigation