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Quantifying CMIP6 model uncertainties in extreme precipitation projections

Abstract : Projected changes in precipitation extremes and their uncertainties are evaluated using an ensemble of global climate models from phase 6 of the Coupled Model Intercomparison Project (CMIP). They are scaled by corresponding changes either in global mean surface temperature (∆GSAT) or in local surface temperature (∆T) and are expressed in terms of 20-yr return values (RV20) of annual maximum one-day precipitation. Our main objective is to quantify the model response uncertainty and to highlight the regions where changes may not be consistent with the widely used assumption of a Clausius-Clapeyron (CC) rate of ≈7%/K. When using a single realization for each model, as in the latest report from the Intergovernmental Panel on Climate Change (IPCC), the assessed inter-model spread includes both model uncertainty and internal variability, which can be however assessed separately using a large ensemble. Despite the overestimated inter-model spread, our results show a robust enhancement of extreme precipitation with more than 90% of models simulating an increase of RV20. Moreover this increase is consistent with the CC rate of ≈7%/K over about 94% of the global land domain when scaled by (∆GSAT). Our results also advocate for producing single model initial condition ensembles in the next CMIP projections, to better filter internal variability out in estimating the response of extreme events.
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Contributor : Amal John Connect in order to contact the contributor
Submitted on : Friday, December 3, 2021 - 3:24:14 PM
Last modification on : Tuesday, January 4, 2022 - 6:05:51 AM


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  • HAL Id : hal-03464913, version 1


Amal John, Hervé Douville, Aurélien Ribes, Pascal Yiou. Quantifying CMIP6 model uncertainties in extreme precipitation projections. 2021. ⟨hal-03464913⟩



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