Preprints
https://doi.org/10.5194/egusphere-2022-778
https://doi.org/10.5194/egusphere-2022-778
 
16 Aug 2022
16 Aug 2022

Weather pattern dynamics over Western Europe under climate change: Predictability, Information Entropy and Production

Stéphane Vannitsem Stéphane Vannitsem
  • Royal Meteorological Institute of Belgium

Abstract. The impact of climate change on weather pattern dynamics over the North Atlantic is explored through the lens of the information theory of forced dissipative dynamical systems.

The predictability problem is first tackled by investigating the evolution of block-entropies on observational time series of weather patterns produced by the Met Office, which reveals that predictability is increasing as a function of time in the observations during the 19th and beginning of the 20th Century, while the trend is reversed at the end of the 20th century and beginning of the 21st Century. This feature is also investigated in the 15-member ensemble of the UK Met Office CMIP5 model for the 20th and 21st centuries under two climate change scenarios, revealing a wide range of possible evolutions depending on the realization considered, with an overall decrease of predictability in the 21st century for both scenarios.

Lower bounds of the information entropy production is also extracted providing information on the degree of time-asymmetry and irreversibility of the dynamics. The analysis of the UK Met Office model runs suggests that the information entropy production will increase by the end of the 21st century, by a factor of 10 % in the RCP2.6 scenario and a factor of 30–40 % in the RCP8.5 one, as compared to the beginning of the 20th century. This allows for making the conjecture that the degree of irreversibility is increasing, and hence heat production and dissipation will also increase under climate change, corroborating earlier findings based on the analysis of the thermodynamic entropy production.

Journal article(s) based on this preprint

09 Jan 2023
Weather pattern dynamics over western Europe under climate change: predictability, information entropy and production
Stéphane Vannitsem
Nonlin. Processes Geophys., 30, 1–12, https://doi.org/10.5194/npg-30-1-2023,https://doi.org/10.5194/npg-30-1-2023, 2023
Short summary

Stéphane Vannitsem

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-778', Anonymous Referee #1, 09 Sep 2022
  • RC2: 'Comment on egusphere-2022-778', Anonymous Referee #2, 28 Oct 2022

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-778', Anonymous Referee #1, 09 Sep 2022
  • RC2: 'Comment on egusphere-2022-778', Anonymous Referee #2, 28 Oct 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Stéphane Vannitsem on behalf of the Authors (18 Nov 2022)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (21 Nov 2022) by Stefano Pierini
RR by Anonymous Referee #2 (11 Dec 2022)
ED: Publish as is (14 Dec 2022) by Stefano Pierini

Journal article(s) based on this preprint

09 Jan 2023
Weather pattern dynamics over western Europe under climate change: predictability, information entropy and production
Stéphane Vannitsem
Nonlin. Processes Geophys., 30, 1–12, https://doi.org/10.5194/npg-30-1-2023,https://doi.org/10.5194/npg-30-1-2023, 2023
Short summary

Stéphane Vannitsem

Stéphane Vannitsem

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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 for clarifying the predictability of the succession of weather patterns, and the irreversible nature of the dynamics. 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.