A Dynamical Systems Approach to Studying Mid-Latitude Weather Extremes

• Published in: Geophysical Research Letters
• Main Authors: Messori, Gabriele, Caballero, Rodrigo, Faranda, Davide
• Other Authors: Bolin Centre for Climate Research, Stockholm University, Department of Meteorology Stockholm (MISU), Laboratoire des Sciences du Climat et de l'Environnement Gif-sur-Yvette (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Extrèmes : Statistiques, Impacts et Régionalisation (ESTIMR), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Direction de Recherche Fondamentale (CEA) (DRF (CEA))
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2017
• Subjects: Classification: Physical Sciences; Earth; Atmospheric; and Planetary Sciences; Keywords: Predictability; Temperature Extremes; Dynamical Systems; [NLIN.NLIN-CD]Nonlinear Sciences [physics]/Chaotic Dynamics [nlin.CD]; [PHYS.PHYS.PHYS-DATA-AN]Physics [physics]/Physics [physics]/Data Analysis; Statistics and Probability [physics.data-an]; [SDU.OCEAN]Sciences of the Universe [physics]/Ocean; Atmosphere; North Atlantic
• Online Access: https://hal.science/hal-01460728; https://hal.science/hal-01460728/document; https://hal.science/hal-01460728/file/Messori_et_al_2017.pdf; https://doi.org/10.1002/2017GL072879

International audience Extreme weather occurrences carry enormous social and economic costs and routinely garner widespread scientific and media coverage. The ability to predict these events is therefore a topic of crucial importance. Here we propose a novel predictability pathway for extreme events, by building upon recent advances in dynamical systems theory. We show that simple dynamical systems metrics can be used to identify sets of large-scale atmospheric flow patterns with similar spatial structure and temporal evolution on timescales of several days to a week. In regions where these patterns favour extreme weather, they afford a particularly good predictability of the extremes. We specifically test this technique on the atmospheric circulation in the North Atlantic region, where it provides predictability of large-scale wintertime surface temperature extremes in Europe up to one week in advance. Significance Statement Extreme weather events carry major social and economic costs; improving their predictability is therefore of crucial importance. Forecasting the occurrence of a given extreme event can be more or less difficult depending on the state of the atmosphere from which the forecast is initialised. In this study we apply diagnostics from the field of dynamical systems analysis to identify the atmospheric states providing the best predictability and investigate their link to wintertime temperature extremes in Europe. We find that these states of " maximum predictability " correspond to significant changes in the frequency of very warm or cold spells, and are often followed by large-scale extreme temperature events. These findings can provide a useful complement to existing operational forecast tools.