Journal article
Guidelines for Studying Diverse Types of Compound Weather and Climate Events
E Bevacqua, C De Michele, C Manning, A Couasnon, AFS Ribeiro, AM Ramos, E Vignotto, A Bastos, S Blesić, F Durante, J Hillier, SC Oliveira, JG Pinto, E Ragno, P Rivoire, K Saunders, K van der Wiel, W Wu, T Zhang, J Zscheischler
Earth S Future | AMER GEOPHYSICAL UNION | Published : 2021
DOI: 10.1029/2021EF002340
Open access
Abstract
Compound weather and climate events are combinations of climate drivers and/or hazards that contribute to societal or environmental risk. Studying compound events often requires a multidisciplinary approach combining domain knowledge of the underlying processes with, for example, statistical methods and climate model outputs. Recently, to aid the development of research on compound events, four compound event types were introduced, namely (a) preconditioned, (b) multivariate, (c) temporally compounding, and (d) spatially compounding events. However, guidelines on how to study these types of events are still lacking. Here, we consider four case studies, each associated with a specific event t..
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Awarded by AXA Research Fund
Funding Acknowledgements
The authors acknowledge the European COST Action DAMOCLES (CA17109). This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 101003469. E. Bevacqua acknowledges financial support from the DOCILE project (NERC grant: NE/P002099/1). J. Zscheischler acknowledges the Swiss National Science Foundation (Ambizione grant 179876) and the Helmholtz Initiative and Networking Fund (Young Investigator Group COMPOUNDX; grant agreement no. VH-NG-1537). A. Couasnon acknowledges the Netherlands Organisation for Scientific Research (NWO) (VIDI grant no. 016.161.324). A.M. Ramos acknowledges the Fundacao para a Ciencia e a Tecnologia, Portugal (FCT) through the project WEx-Atlantic (PTDC/CTA-MET/29233/2017) and Scientific Employment Stimulus 2017 (CEECIND/00027/2017). C. De Michele acknowledges the Italian Ministry of University and Research (Ministero dell'Universita e della Ricerca) for the support through the PRIN2017 RELAID project. E. Ragno acknowledges the European Union's Horizon 2020 research and innovation programme (Marie Sklodowska-Curie grant agreement No 707404). J.G. Pinto thanks the AXA Research Fund for support (https://axa-research.org/en/project/joaquim-pinto).S.C.Oliveira was financed by the Portuguese Foundation for Science and Technology, I.P., under the framework of the project BeSafeSlide-Landslide EarlyWarning soft technology prototype to improve community resilience and adaptation to environmental change (PTDC/GES-AMB/30052/2017). Open access funding enabled and organized by Projekt DEAL.