The signature of the main modes of climatic variability as revealed by the Jenkinson-Collison classification over Europe

• Published in: International Journal of Climatology
• Main Authors: Fernández de la Granja, Juan Antonio, Bedía Jiménez, Joaquín, Casanueva Vicente, Ana, Brands, Swen Franz, Fernández Fernández, Jesús (matemático)
• Other Authors: Universidad de Cantabria
• Format: Article in Journal/Newspaper
• Language: English
• Published: John Wiley and Sons Ltd 2024
• Subjects: Atmospheric blocking; Sea-level pressure; Variability modes; Weather typing; North Atlantic; North Atlantic oscillation
• Online Access: https://hdl.handle.net/10902/33792; https://doi.org/10.1002/joc.8569

The Jenkinson-Collison Weather Typing (JC-WT) method uses sea-level pressure gradients to create 27 types based on the geostrophic flow and vorticity around any extratropical target location. Typically, JC-WTs are applied over specific locations or limited domains, thus hampering the understanding of the impact of large-scale mechanisms on regional climate. This study explores the links between regional climate variability, as represented by the JC-WTs, and large-scale phenomena, to describe the synoptic-scale variability in the North Atlantic-European region and evaluate the JC-WT methodology. Largescale circulation is here characterized by major atmospheric low-frequency modes, namely the North Atlantic Oscillation, the East Atlantic and the Scandinavian teleconnection indices, and by atmospheric blockings. Results show that JC-WTs coherently capture the spatial and temporal variability of the large-scale modes and yields a characteristic response to blocking events. Overall, our results underpin the exploratory potential of this method for the analysis of the near-surface circulation. These findings endorse the use of JC-WTs and support the reliability and utility of the JC-WT classification for processbased model assessments and model selection, a crucial task for climate impact studies. CORDyS project (PID2020-116595RB-I00) and ATLAS(PID2019-111481RB-I00) funded by Ministerio de Cienciae Innovaci on / Agencia Estatal de Investigaci on (MCIN/AEI/10.13039/501100011033). Project COMPOUND(TED2021-131334A-I00) funded by MCIN/AEI/10.13039/501100011033 and by the European Union NextGenera-tionEU/PRTR. Ph.D. grant PRE2020-094728 (MCIN/AEI/10.13039/501100011033); PTI-Clima, MITECO andNextGenerationEU (Regulation EU 2020/2094) IMPET-US4CHANGE, grant agreement no. 101081555, from theEuropean Union's Horizon Europe research and innova-tion programme