Dynamical Properties of Weather Regime Transitions

• Main Authors: Platzer, Paul, Chapron, Bertrand, Tandeo, Pierre
• Other Authors: Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER), Laboratoire d'Océanographie Physique et Spatiale (LOPS), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS), Département Mathematical and Electrical Engineering (IMT Atlantique - MEE), IMT Atlantique (IMT Atlantique), Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT), Equipe Observations Signal & Environnement (Lab-STICC_OSE), Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom Paris (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom Paris (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom Paris (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom Paris (IMT), Océan Dynamique Observations Analyse (ODYSSEY), Université de Bretagne Occidentale - UFR Sciences et Techniques (UBO UFR ST), Université de Brest (UBO)-Université de Brest (UBO)-Université de Rennes (UR)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-IMT Atlantique (IMT Atlantique), This work was financially supported by the ERC project 856408-STUOD. Support for theTwentieth Century Reanalysis Project version 3 dataset is provided by the U.S. Department ofEnergy, Office of Science Biological and Environmental Research (BER), by the National Oceanicand Atmospheric Administration Climate Program Office, and by the NOAA Physical SciencesLaboratory. We thank the anonymous reviewer for helpful comments and suggestions., European Project: 856408,STUOD(2020)
• Format: Conference Object
• Language: English
• Published: HAL CCSD 2021
• Subjects: Weather Regime Transition Shift Dynamical systems Dimension Persistence; Weather; Regime; Transition; Shift; Dynamical systems; Dimension; Persistence; [SDU.OCEAN]Sciences of the Universe [physics]/Ocean; Atmosphere; North Atlantic
• Online Access: https://imt-atlantique.hal.science/hal-03906946; https://imt-atlantique.hal.science/hal-03906946/document; https://imt-atlantique.hal.science/hal-03906946/file/platzer_2023.pdf; https://doi.org/10.1007/978-3-031-18988-3_14

International audience Large-scale weather can often be successfully described using a small amount of patterns. A statistical description of reanalysed pressure fields identifies these recurring patterns with clusters in state-space, also called “regimes”. Recently, these weather regimes have been described through instantaneous, local indicators of dimension and persistence, borrowed from dynamical systems theory and extreme value theory. Using similar indicators and going further, we focus here on weather regime transitions. We use 60 years of winter-time sea-level pressure reanalysis data centered on the North-Atlantic ocean and western Europe. These experiments reveal regime-dependent behaviours of dimension and persistence near transitions, although in average one observes an increase of dimension and a decrease of persistence near transitions. The effect of transition on persistence is stronger and lasts longer than on dimension. These findings confirm the relevance of such dynamical indicators for the study of large-scale weather regimes, and reveal their potential to be used for both the understanding and detection of weather regime transitions.