@article{e039d707869a458397998ca1b829b382,
title = "Regionally high risk increase for precipitation extreme events under global warming",
abstract = "Daily precipitation extremes are projected to intensify with increasing moisture under global warming following the Clausius-Clapeyron (CC) relationship at about 7 % / ∘C. However, this increase is not spatially homogeneous. Projections in individual models exhibit regions with substantially larger increases than expected from the CC scaling. Here, we leverage theory and observations of the form of the precipitation probability distribution to substantially improve intermodel agreement in the medium to high precipitation intensity regime, and to interpret projected changes in frequency in the Coupled Model Intercomparison Project Phase 6. Besides particular regions where models consistently display super-CC behavior, we find substantial occurrence of super-CC behavior within a given latitude band when the multi-model average does not require that the models agree point-wise on location within that band. About 13% of the globe and almost 25% of the tropics (30% for tropical land) display increases exceeding 2CC. Over 40% of tropical land points exceed 1.5CC. Risk-ratio analysis shows that even small increases above CC scaling can have disproportionately large effects in the frequency of the most extreme events. Risk due to regional enhancement of precipitation scale increase by dynamical effects must thus be included in vulnerability assessment even if locations are imprecise.",
author = "Cristian Martinez-Villalobos and Neelin, {J. David}",
note = "Funding Information: This work was supported in part by National Science Foundation Grant AGS-1936810, National Oceanic and Atmospheric Administration Grants NA21OAR4310354 and NA18OAR4310280 (JDN and CM-V), and by Proyecto ANID Fondecyt Postdoctorado c{\'o}digo 3200621, Proyecto Corfo Ingenier{\'i}a 2030 c{\'o}digo 14ENI2-26865, and by the Data Observatory Foundation (CM-V). We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP6. We thank the climate modeling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies that support CMIP6 and ESGF. We also acknowledge high-performance computing support from Cheyenne provided by NCAR{\textquoteright}s Computational and Information Systems Laboratory, sponsored by the National Science Foundation. Funding Information: This work was supported in part by National Science Foundation Grant AGS-1936810, National Oceanic and Atmospheric Administration Grants NA21OAR4310354 and NA18OAR4310280 (JDN and CM-V), and by Proyecto ANID Fondecyt Postdoctorado c{\'o}digo 3200621, Proyecto Corfo Ingenier{\'i}a 2030 c{\'o}digo 14ENI2-26865, and by the Data Observatory Foundation (CM-V). We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP675. We thank the climate modeling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies that support CMIP6 and ESGF. We also acknowledge high-performance computing support from Cheyenne76provided by NCAR{\textquoteright}s Computational and Information Systems Laboratory, sponsored by the National Science Foundation. Publisher Copyright: {\textcopyright} 2023, The Author(s).",
year = "2023",
month = dec,
doi = "10.1038/s41598-023-32372-3",
language = "English",
volume = "13",
journal = "Scientific Reports",
issn = "2045-2322",
publisher = "Nature Publishing Group",
number = "1",
}