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Challenges to Understanding Extreme Weather Changes in Lower Income Countries

Summary/Abstract

The science of event attribution has emerged to routinely answer the question whether and to what extent human-induced climate change altered the likelihood and intensity of recently observed extreme weather events. In Europe a pilot program to operationalize the method started in November 2019, highlighting the demand for timely information on the role of climate change when it is needed most: in the direct aftermath of an extreme event. Independent of whether studies are provided operationally or as academic studies, the necessity of good observational data and well-verified climate models imply most attributions are currently made for highly developed countries only. Current attribution assessments therefore provide very little information about those events and regions where the largest damages and socio-economic losses are incurred. Arguably, these larger damages signify a much greater need for information on how the likelihood and intensity of such high-impact events have been changing and are likely to change in a warmer world. In short, why do we not focus event attribution research efforts on the whole world, and particularly events in the developing world? The reasons are not just societal and political but also scientific. We simply cannot attribute these events in the same probabilistic framework employed in most studies today. We outline six focus areas to lessen these barriers, but we will not overcome them in the near future.

Otto, F. E. L. et al. (2020). Challenges to Understanding Extreme Weather Changes in Lower Income Countries, Bulletin of the American Meteorological Society, 101(10), E1851-E1860. Retrieved Feb 11, 2022.

View Resource
October 2020
Friederike E. L. Otto, Luke Harrington, Katharina Schmitt, Sjoukje Philip, Sarah Kew, Geert Jan van Oldenborgh, Roop Singh, Joyce Kimutai, and Piotr Wolski
Bulletin of the American Meteorological Society
Review Article
Global
Extreme Event Attribution → Cross-cutting Research
Extreme Event Attribution → Regional Assessments

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