Articles | Volume 30, issue 1
https://doi.org/10.5194/npg-30-1-2023
https://doi.org/10.5194/npg-30-1-2023
Research article
 | 
09 Jan 2023
Research article |  | 09 Jan 2023

Weather pattern dynamics over western Europe under climate change: predictability, information entropy and production

Stéphane Vannitsem

Related authors

Nonlinear causal dependencies as a signature of the complexity of the climate dynamics
Stéphane Vannitsem, X. San Liang, and Carlos A. Pires
EGUsphere, https://doi.org/10.5194/egusphere-2024-3308,https://doi.org/10.5194/egusphere-2024-3308, 2024
Short summary
Variability and predictability of a reduced-order land–atmosphere coupled model
Anupama K. Xavier, Jonathan Demaeyer, and Stéphane Vannitsem
Earth Syst. Dynam., 15, 893–912, https://doi.org/10.5194/esd-15-893-2024,https://doi.org/10.5194/esd-15-893-2024, 2024
Short summary
A comparison of two causal methods in the context of climate analyses
David Docquier, Giorgia Di Capua, Reik V. Donner, Carlos A. L. Pires, Amélie Simon, and Stéphane Vannitsem
Nonlin. Processes Geophys., 31, 115–136, https://doi.org/10.5194/npg-31-115-2024,https://doi.org/10.5194/npg-31-115-2024, 2024
Short summary
Quantitative rainfall analysis of the 2021 mid-July flood event in Belgium
Michel Journée, Edouard Goudenhoofdt, Stéphane Vannitsem, and Laurent Delobbe
Hydrol. Earth Syst. Sci., 27, 3169–3189, https://doi.org/10.5194/hess-27-3169-2023,https://doi.org/10.5194/hess-27-3169-2023, 2023
Short summary
The EUPPBench postprocessing benchmark dataset v1.0
Jonathan Demaeyer, Jonas Bhend, Sebastian Lerch, Cristina Primo, Bert Van Schaeybroeck, Aitor Atencia, Zied Ben Bouallègue, Jieyu Chen, Markus Dabernig, Gavin Evans, Jana Faganeli Pucer, Ben Hooper, Nina Horat, David Jobst, Janko Merše, Peter Mlakar, Annette Möller, Olivier Mestre, Maxime Taillardat, and Stéphane Vannitsem
Earth Syst. Sci. Data, 15, 2635–2653, https://doi.org/10.5194/essd-15-2635-2023,https://doi.org/10.5194/essd-15-2635-2023, 2023
Short summary

Related subject area

Subject: Predictability, probabilistic forecasts, data assimilation, inverse problems | Topic: Climate, atmosphere, ocean, hydrology, cryosphere, biosphere | Techniques: Big data and artificial intelligence
Selecting and weighting dynamical models using data-driven approaches
Pierre Le Bras, Florian Sévellec, Pierre Tandeo, Juan Ruiz, and Pierre Ailliot
Nonlin. Processes Geophys., 31, 303–317, https://doi.org/10.5194/npg-31-303-2024,https://doi.org/10.5194/npg-31-303-2024, 2024
Short summary
A quest for precipitation attractors in weather radar archives
Loris Foresti, Bernat Puigdomènech Treserras, Daniele Nerini, Aitor Atencia, Marco Gabella, Ioannis V. Sideris, Urs Germann, and Isztar Zawadzki
Nonlin. Processes Geophys., 31, 259–286, https://doi.org/10.5194/npg-31-259-2024,https://doi.org/10.5194/npg-31-259-2024, 2024
Short summary
Robust weather-adaptive post-processing using model output statistics random forests
Thomas Muschinski, Georg J. Mayr, Achim Zeileis, and Thorsten Simon
Nonlin. Processes Geophys., 30, 503–514, https://doi.org/10.5194/npg-30-503-2023,https://doi.org/10.5194/npg-30-503-2023, 2023
Short summary
Guidance on how to improve vertical covariance localization based on a 1000-member ensemble
Tobias Necker, David Hinger, Philipp Johannes Griewank, Takemasa Miyoshi, and Martin Weissmann
Nonlin. Processes Geophys., 30, 13–29, https://doi.org/10.5194/npg-30-13-2023,https://doi.org/10.5194/npg-30-13-2023, 2023
Short summary
Calibrated ensemble forecasts of the height of new snow using quantile regression forests and ensemble model output statistics
Guillaume Evin, Matthieu Lafaysse, Maxime Taillardat, and Michaël Zamo
Nonlin. Processes Geophys., 28, 467–480, https://doi.org/10.5194/npg-28-467-2021,https://doi.org/10.5194/npg-28-467-2021, 2021
Short summary

Cited articles

Allen, S.: Advanced statistical post-processing of ensemble weather forecasts, PhD thesis, University of Exeter, http://hdl.handle.net/10871/126003 (last access: 2 January 2023), 2021. a, b
Andrieux, D., Gaspard, P., Ciliberto, S., Garnier, N., Joubaud, S., and Petrosyan, A.: Entropy production and time asymmetry in nonequilibrium fluctuations, Phys. Rev. Lett., 98, 150601, https://doi.org/10.1103/PhysRevLett.98.150601, 2007. a, b, c
Barry, R. G. and Perry, A. H.: Synoptic climatology: methods and applications. Methuen and Co. Ltd, 555 pp., 1973. a
Basios, V., Oikonomou, Th., and De Gernier, R.: Symbolic dynamics of music from Europe and Japan, Chaos, 31, 053122, https://doi.org/10.1063/5.0048396, 2021. a
Bilingsley, P.: Statistical methods in Markov chains, Ann. Math. Stat., 32, 12–40, https://doi.org/10.1214/aoms/1177705136, 1961. a
Download
Short summary
The impact of climate change on weather pattern dynamics over the North Atlantic is explored through the lens of information theory. These tools allow the predictability of the succession of weather patterns and the irreversible nature of the dynamics to be clarified. It is shown that the predictability is increasing in the observations, while the opposite trend is found in model projections. The irreversibility displays an overall increase in time in both the observations and the model runs.