Unravelling compound risks of hydrological extremes in a changing climate: Typology, methods and futures
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arXiv
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| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866914959619784704 |
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| author | Chun, Kwok P Octavianti, Thanti Papacharalampous, Georgia Tyralis, Hristos Sutanto, Samuel J. Terskii, Pavel Mazzoglio, Paola Treppiedi, Dario Rivera, Juan Dogulu, Nilay Olusola, Adeyemi Dieppois, Bastien Dembélé, Moctar Moulds, Simon Li, Cheng Morales-Marin, Luis Alejandro Macdonald, Neil Amoussou, Toundji Olivier Yonaba, Roland Obahoundje, Salomon Massei, Nicolas Hannah, David M. Chidepudi, Sivarama Krishna Reddy Hamududu, Byman |
| author_facet | Chun, Kwok P Octavianti, Thanti Papacharalampous, Georgia Tyralis, Hristos Sutanto, Samuel J. Terskii, Pavel Mazzoglio, Paola Treppiedi, Dario Rivera, Juan Dogulu, Nilay Olusola, Adeyemi Dieppois, Bastien Dembélé, Moctar Moulds, Simon Li, Cheng Morales-Marin, Luis Alejandro Macdonald, Neil Amoussou, Toundji Olivier Yonaba, Roland Obahoundje, Salomon Massei, Nicolas Hannah, David M. Chidepudi, Sivarama Krishna Reddy Hamududu, Byman |
| contents | We have witnessed and experienced increasing compound extreme events resulting from simultaneous or sequential occurrence of multiple events in a changing climate. In addition to a growing demand for a clearer explanation of compound risks from a hydrological perspective, there has been a lack of attention paid to socioeconomic factors driving and impacted by these risks. Through a critical review and co-production approaches, we identified four types of compound hydrological events based on autocorrelated, multivariate, and spatiotemporal patterns. A framework to quantify compound risks based on conditional probability is offered, including an argument on the potential use of generative Artificial Intelligence (AI) algorithms for identifying emerging trends and patterns for climate change. Insights for practices are discussed, highlighting the implications for disaster risk reduction and knowledge co-production. Our argument centres on the importance of meaningfully considering the socioeconomic contexts in which compound risks may have impacts, and the need for interdisciplinary collaboration to effectively translate climate science to climate actions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_19003 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Unravelling compound risks of hydrological extremes in a changing climate: Typology, methods and futures Chun, Kwok P Octavianti, Thanti Papacharalampous, Georgia Tyralis, Hristos Sutanto, Samuel J. Terskii, Pavel Mazzoglio, Paola Treppiedi, Dario Rivera, Juan Dogulu, Nilay Olusola, Adeyemi Dieppois, Bastien Dembélé, Moctar Moulds, Simon Li, Cheng Morales-Marin, Luis Alejandro Macdonald, Neil Amoussou, Toundji Olivier Yonaba, Roland Obahoundje, Salomon Massei, Nicolas Hannah, David M. Chidepudi, Sivarama Krishna Reddy Hamududu, Byman Physics and Society Atmospheric and Oceanic Physics We have witnessed and experienced increasing compound extreme events resulting from simultaneous or sequential occurrence of multiple events in a changing climate. In addition to a growing demand for a clearer explanation of compound risks from a hydrological perspective, there has been a lack of attention paid to socioeconomic factors driving and impacted by these risks. Through a critical review and co-production approaches, we identified four types of compound hydrological events based on autocorrelated, multivariate, and spatiotemporal patterns. A framework to quantify compound risks based on conditional probability is offered, including an argument on the potential use of generative Artificial Intelligence (AI) algorithms for identifying emerging trends and patterns for climate change. Insights for practices are discussed, highlighting the implications for disaster risk reduction and knowledge co-production. Our argument centres on the importance of meaningfully considering the socioeconomic contexts in which compound risks may have impacts, and the need for interdisciplinary collaboration to effectively translate climate science to climate actions. |
| title | Unravelling compound risks of hydrological extremes in a changing climate: Typology, methods and futures |
| topic | Physics and Society Atmospheric and Oceanic Physics |
| url | https://arxiv.org/abs/2409.19003 |