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Dynamics and predictability of cold spells over the Eastern Mediterranean

Hochman, Assaf; Scher, Sebastian; Quinting, Julian; Pinto, Joaquim G.; Messori, Gabriele

Abstract:
The accurate prediction of extreme weather events is an important and challenging task, and has typically relied on numerical simulations of the atmosphere. Here, we combine insights from numerical forecasts with recent developments in dynamical systems theory, which describe atmospheric states in terms of their persistence (θ$^{-1}$) and local dimension (d), and inform on how the atmosphere evolves to and from a given state of interest. These metrics are intuitively linked to the intrinsic predictability of the atmosphere: a highly persistent, low-dimensional state will be more predictable than a low-persistence, high-dimensional one. We argue that θ$^{-1}$ and d, derived from reanalysis sea level pressure (SLP) and geopotential height (Z500) fields, can provide complementary predictive information for mid-latitude extreme weather events. Specifically, signatures of regional extreme weather events might be reflected in the dynamical systems metrics, even when the actual extreme is not well-simulated in numerical forecasting systems. We focus on cold spells in the Eastern Mediterranean, and particularly those associated with snow cover in Jerusalem. ... mehr

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Verlagsausgabe §
DOI: 10.5445/IR/1000124471
Veröffentlicht am 26.11.2020
Originalveröffentlichung
DOI: 10.1007/s00382-020-05465-2
Scopus
Zitationen: 3
Dimensions
Zitationen: 4
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung - Forschungsbereich Troposphäre (IMK-TRO)
KIT-Zentrum Klima und Umwelt (ZKU)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2020
Sprache Englisch
Identifikator ISSN: 0930-7575, 1432-0894
KITopen-ID: 1000124471
HGF-Programm 12.01.02 (POF III, LK 01) Proc.res.f.multisc.predictab.of weather
Erschienen in Climate dynamics
Verlag Springer
Vorab online veröffentlicht am 10.10.2020
Schlagwörter Dynamical systems, Chaos, Extreme weather, Extreme temperatures, Prediction, Atmospheric dynamics, Weather forecasting, Numerical weather prediction
Nachgewiesen in Scopus
Web of Science
Dimensions
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