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Author Chang, M.; Liu, B.; Wang, B.; Martinez-Villalobos, C.; Ren, G.; Zhou, T.
Title Understanding future increases in precipitation extremes in global land monsoon regions Type
Year 2022 Publication Journal of Climate Abbreviated Journal J. Clim.
Volume 35 Issue Pages 1839-1851
Keywords Precipitation; Extreme events; Monsoons; Climate prediction; Thermodynamics; Dynamics
Abstract This study investigates future changes in daily precipitation extremes and the involved physics over the global land monsoon (GM) region using climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6). The daily precipitation extreme is identified by the cutoff scale, measuring the extreme tail of the precipitation distribution. Compared to the historical period, multi-model results reveal a continuous increase in precipitation extremes under four scenarios, with a progressively higher fraction of precipitation exceeding the historical cutoff scale when moving into the future. The rise of the cutoff-scale by the end of the century is reduced by 57.8% in the moderate emission scenario relative to the highest scenario, underscoring the social benefit in reducing emissions. The cutoff scale sensitivity, defined by the increasing rates of the cutoff scale over the GM region to the global mean surface temperature increase, is nearly independent of the projected periods and emission scenarios, roughly 8.0% K−1 by averaging all periods and scenarios. To understand the cause of the changes, we applied a physical scaling diagnostic to decompose them into thermodynamic and dynamic contributions. We find that thermodynamics and dynamics have comparable contributions to the intensified precipitation extremes in the GM region. Changes in thermodynamic scaling contribute to a spatially uniform increase pattern, while changes in dynamic scaling dominate the regional differences in the increased precipitation extremes. Furthermore, the large inter-model spread of the projection is primarily attributed to variations of dynamic scaling among models.
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ISSN 0894-8755 ISBN Medium
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Notes Approved
Call Number UAI @ alexi.delcanto @ Serial 1500
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