Abstract. As the resolution of global Earth system models increases, regional-scale evaluations are becoming ever more important. This study presents a framework for quantifying precipitation distributions at regional scales and applies it to evaluate Coupled Model Intercomparison Project (CMIP) 5 and 6 models. We employ the Intergovernmental Panel on Climate Change (IPCC) sixth assessment report (AR6) climate reference regions over land and propose refinements to the oceanic regions based on the homogeneity of precipitation distribution characteristics. The homogeneous regions are identified as heavy-, moderate-, and light-precipitating areas by K-means clustering of Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) version 6 final run product (IMERG) precipitation frequency and amount distributions. With the global domain partitioned into 62 regions, including 46 land and 16 ocean regions, we apply 10 established precipitation distribution metrics. The collection includes metrics focused on the maximum peak, lower 10th percentile, and upper 90th percentile in precipitation amount and frequency distributions; the similarity between observed and modeled frequency distributions; an unevenness measure based on cumulative amount; average total intensity on all days with precipitation; and number of precipitating days each year. We apply our framework to 25 CMIP5 and 41 CMIP6 models, as well as six observation-based products of daily precipitation. Our results indicate that many CMIP5 and 6 models substantially overestimate the observed light-precipitation amount and frequency, as well as the number of precipitating days, especially over midlatitude regions outside of some land regions in the Americas and Eurasia. Improvement from CMIP5 to 6 is shown in some regions, especially in midlatitude regions, but it is not evident globally, and over the tropics most metrics point toward degradation.

Abstract. A framework for quantifying precipitation distributions at regional scales is presented and applied to CMIP 5 and 6 models. We employ the IPCC AR6 climate reference regions over land and propose refinements to the oceanic regions based on the homogeneity of precipitation distribution characteristics. The homogeneous regions are identified as heavy, moderate, and light precipitating areas by K-means clustering of IMERG precipitation frequency and amount distributions. With the global domain partitioned into 62 regions, including 46 land and 16 ocean regions, we apply 10 established precipitation distribution metrics. The collection includes metrics focused on the maximum peak, lower 10th percentile, and upper 90th percentile in precipitation amount and frequency distributions, the similarity between observed and modeled frequency distributions, an unevenness measure based on cumulative amount, average total intensity on all days with precipitation, and number of precipitating days each year. We apply our framework to 25 CMIP5 and 41 CMIP6 models, and 6 observation-based products of daily precipitation. Our results indicate that many CMIP 5 and 6 models substantially overestimate the observed light precipitation amount and frequency as well as the number of precipitating days, especially over mid-latitude regions outside of some land regions in the Americas and Eurasia. Improvement from CMIP 5 to 6 is shown in some regions, especially in mid-latitude regions, but it is not evident globally, and over the tropics most metrics point toward over degradation.

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We are interested in the modelling of saturated thermo-hydro-mechanical (THM) problems that describe the behaviour of a soil in which a weakly compressible fluid evolves. It is used for the evaluation of the THM impact of high-level activity radioactive waste exothermicity within a deep geological disposal facility. We shall present the definition of a block preconditioner with nested Krylov solvers for the fully coupled THM equations. Numerical results reflect the good performance of the proposed preconditioners that show to be weakly scalable until more than 2000 cores and more than 1 billion degrees of freedom. Thanks to their performance and robustness, a real waste storage problem on a scale, to our knowledge, unprecedented in the field, can be addressed.

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