Assessing Global and Regional Trends in Spatially Co-Occurring Hot or Wet Annual Maxima Under Climate Change

Abstract

Recent years were characterized by spatially co-occurring hot and wet extremes around the globe, raising questions about the contribution of human-induced global warming to the changing likelihoods of such extreme years. To characterize spatially co-occurring extremes we investigate recent trends in global and regional land area that is concurrently affected by hot or wet annual maxima taking observational uncertainty into account. Observed trends in the land area affected by extreme events are assessed in the context of Earth System Model (ESM) simulations for present-day and early-industrial climate conditions in a detection and attribution setting. We compare different reanalysis and station-based observational products to account for observational data uncertainty. At the global scale, trends of spatially co-occurring hot or wet annual maxima in all observational products can be explained by ESM simulations driven by historical radiative forcing that accounts for human-induced changes in the composition of the atmosphere but cannot be explained by ESM simulations that account for an early-industrial radiative forcing. At the regional scale, trends in spatially co-occurring hot annual maxima are in general coherent among observational products and can in most cases be attributed to human influence on the climate system. Trends in spatially co-occurring wet annual maxima show differences in some regions, highlighting the importance of a multi-dataset approach to overcome observational product dependencies. Despite observational uncertainty, we find robust detection and attribution results for many regions. These results can complement previous assessments on regional exposure to hot and wet events from the new IPCC AR6 report.