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Understanding and Anticipating Anomalous Surface Impacts During Large‐Scale Regimes

Gerighausen, Judith 1,2; Oldham-Dorrington, Joshua 1,2; Mockert, Fabian 1,2; Osman, Marisol 1,2; Grams, Christian M. 1,2
1 Institut für Meteorologie und Klimaforschung Troposphärenforschung (IMKTRO), Karlsruher Institut für Technologie (KIT)
2 Institut für Meteorologie und Klimaforschung (IMK), Karlsruher Institut für Technologie (KIT)

Abstract:

Weather regimes describe the large-scale atmospheric circulation in the mid-latitudes in terms of a few circulation states that modulate regional surface weather conditions on time scales of multiple days to a few weeks. This low-dimensional representation of weather has proven useful for the study of large-scale dynamics, climate trends, flow-dependent predictability, and as proxies for applied medium- to extended-range forecasting in the energy sector, for example. Previous studies have often focused on the mean surface weather associated with a regime, with only a few commenting quantitatively on intra-regime variability. In this paper, we comprehensively quantify variability of daily surface weather within regimes and show that it cannot be ignored as mean-composite approaches can be misleading. Signal-to-noise metrics highlight regime configurations that provide windows of predictive opportunity, where surface dynamics are well controlled by the large-scale regime. We discuss in detail wintertime temperature and wind speed regime anomalies for four selected countries (Spain, Norway, Germany, and the United Kingdom) and show that in each case there is impactful intra-regime variability that can be explained by different subtypes and life cycle stages of a regime. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000187002
Veröffentlicht am 25.11.2025
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung (IMK)
Institut für Meteorologie und Klimaforschung Troposphärenforschung (IMKTRO)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2025
Sprache Englisch
Identifikator ISSN: 1350-4827, 1469-8080
KITopen-ID: 1000187002
HGF-Programm 12.11.34 (POF IV, LK 01) Improved predictions from weather to climate scales
Erschienen in Meteorological Applications
Verlag John Wiley and Sons
Band 32
Heft 6
Seiten Article no: e70099
Vorab online veröffentlicht am 13.11.2025
Nachgewiesen in OpenAlex
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