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Quantifying stratospheric biases and identifying their potential sources in subseasonal forecast systems

Lawrence, Zachary D. ; Abalos, Marta; Ayarzagüena, Blanca; Barriopedro, David; Butler, Amy H.; Calvo, Natalia; de la Cámara, Alvaro; Charlton-Perez, Andrew; Domeisen, Daniela I. V.; Dunn-Sigouin, Etienne; García-Serrano, Javier; Garfinkel, Chaim I.; Hindley, Neil P.; Jia, Liwei; Jucker, Martin; Karpechko, Alexey Y.; Kim, Hera; Lang, Andrea L.; Lee, Simon H.; ... mehr

Abstract:

The stratosphere can be a source of predictability for surface weather on timescales of several weeks to months. However, the potential predictive skill gained from stratospheric variability can be limited by biases in the representation of stratospheric processes and the coupling of the stratosphere with surface climate in forecast systems. This study provides a first systematic identification of model biases in the stratosphere across a wide range of subseasonal forecast systems.

It is found that many of the forecast systems considered exhibit warm global-mean temperature biases from the lower to middle stratosphere, too strong/cold wintertime polar vortices, and too cold extratropical upper-troposphere/lower-stratosphere regions. Furthermore, tropical stratospheric anomalies associated with the Quasi-Biennial Oscillation tend to decay toward each system's climatology with lead time. In the Northern Hemisphere (NH), most systems do not capture the seasonal cycle of extreme-vortex-event probabilities, with an underestimation of sudden stratospheric warming events and an overestimation of strong vortex events in January. In the Southern Hemisphere (SH), springtime interannual variability in the polar vortex is generally underestimated, but the timing of the final breakdown of the polar vortex often happens too early in many of the prediction systems.
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Verlagsausgabe §
DOI: 10.5445/IR/1000151266
Veröffentlicht am 20.10.2022
Originalveröffentlichung
DOI: 10.5194/wcd-3-977-2022
Scopus
Zitationen: 13
Dimensions
Zitationen: 13
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung Troposphärenforschung (IMKTRO)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2022
Sprache Englisch
Identifikator ISSN: 2698-4016
KITopen-ID: 1000151266
Erschienen in Weather and Climate Dynamics
Verlag Copernicus
Band 3
Heft 3
Seiten 977–1001
Vorab online veröffentlicht am 19.08.2022
Nachgewiesen in Dimensions
Scopus
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