When and where do ECMWF seasonal forecast systems exhibit anomalously low signal‐to‐noise ratio?

[thumbnail of charlton_perez_seas5.pdf]
Preview
Text - Accepted Version
· Please see our End User Agreement before downloading.
| Preview

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

Charlton-Perez, A. J. orcid id iconORCID: https://orcid.org/0000-0001-8179-6220, Bröcker, J., Stockdale, T. N. and Johnson, S. (2019) When and where do ECMWF seasonal forecast systems exhibit anomalously low signal‐to‐noise ratio? Quarterly Journal of the Royal Meteorological Society, 145 (725). pp. 3466-3478. ISSN 1477-870X doi: 10.1002/qj.3631

Abstract/Summary

Seasonal predictions of wintertime climate in the Northern Hemisphere midlatitudes, while showing clear correlation skill, suffer from anomalously low signal‐to‐noise ratio. The low signal‐to‐noise ratio means that forecasts need to be made with large ensemble sizes and require significant post‐processing to correct the forecast distribution. In this study, a recently introduced statistical model of seasonal climate predictability is adapted so that it can be used to examine the signal‐to‐noise ratio in two versions of the ECMWF seasonal forecast system. Three novel features of the low signal‐to‐noise ratio are revealed. The low signal‐to‐noise ratio is present only for forecasts initialized on 1 November and not for forecasts initialized on 1 December. The low signal‐to‐noise ratio is predominantly a feature of the lower and middle troposphere and is not present in the stratosphere. The low signal‐to‐noise ratio is linked to low signal amplitude of the forecast systems in early winter. Future studies attempting to examine the signal‐to‐noise ratio should focus on the extent to which this early winter variability is predictable.

Altmetric Badge

Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/87447
Identification Number/DOI 10.1002/qj.3631
Refereed Yes
Divisions Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher Royal Meteorological Society
Download/View statistics View download statistics for this item

Downloads

Downloads per month over past year

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

Search Google Scholar