Preprints
https://doi.org/10.5194/nhess-2022-127
https://doi.org/10.5194/nhess-2022-127
 
09 May 2022
09 May 2022
Status: this preprint is currently under review for the journal NHESS.

Time of Emergence of compound events: contribution of univariate and dependence properties

Bastien François and Mathieu Vrac Bastien François and Mathieu Vrac
  • Laboratoire des Sciences du Climat et l’Environnement (LSCE-IPSL) CNRS/CEA/UVSQ, UMR8212, Université Paris-Saclay, Gif-sur-Yvette, France

Abstract. Many climate-related disasters often result from a combination of several climate phenomena, also referred to as "compound events" (CEs). By interacting with each other, these phenomena can lead to huge environmental and societal impacts, at a scale potentially far greater than any of these climate events could have caused separately. Marginal and dependence properties of the climate phenomena forming the CEs are key statistical properties characterising their probabilities of occurrence. In this study, we propose a new methodology to assess the time of emergence of compound events probabilities, which is critical for mitigation strategies and adaptation planning. Using copula theory, we separate and quantify the contribution of marginal and dependence properties to the overall probability changes of multivariate hazards leading to compound events. It provides a better understanding of how the statistical properties of variables leading to CEs evolve and contribute to the change of their occurrences. For illustration purposes, the methodology is applied over a 13-member multi-model ensemble (CMIP6) to two case studies: compound wind and precipitation extremes over the region of Brittany (France), and frost events occurring during the growing season preconditioned by warm temperatures (growing-period frost) over Central France. For compound wind and precipitation extremes, results show that probabilities emerge before the end of the 21st century for 6 models of the considered CMIP6 ensemble. For growing-period frosts, significant changes of probability are detected for 11 models. Yet, the contribution of marginal and dependence properties to these changes of probabilities can be very different from a climate hazard to another, and from one model to another. Depending on the CE, some models give a strong importance to both marginal properties and dependence properties for probability changes. These results highlight the importance of considering both marginal and dependence properties changes, as well as their inter-model variability, for future risk assessments due to compound events.

Bastien François and Mathieu Vrac

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2022-127', Jakob Zscheischler, 24 Jun 2022
  • RC2: 'Review report for nhess-2022-127', Anonymous Referee #2, 03 Aug 2022

Bastien François and Mathieu Vrac

Bastien François and Mathieu Vrac

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Short summary
Compound events (CEs) result from a combination of several climate phenomena. In this study, we propose a new methodology to assess the time of emergence of CEs probabilities and to quantify the contribution of marginal and dependence properties of climate phenomena to the overall CE probability changes. By applying our methodology to two case studies, we show the importance of considering both marginal and dependence properties changes for future risk assessments due to compound events.
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