edu.ucar.opensky::articles:24833 UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact 2025-12-24T23:02:48.001700 ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data ISO 19115-2:2009(E) https://n2t.org/ark:/85065/d7gx4g1j https://doi.org/10.22033/ESGF/CMIP6.10843 https Related Dataset #1 NCC NorCPM1 model output prepared for CMIP6 CMIP https://doi.org/10.22033/ESGF/CMIP6.1421 https Related Dataset #2 NASA-GISS GISS-E2.1H model output prepared for CMIP6 CMIP https://doi.org/10.22033/ESGF/CMIP6.2066 https Related Dataset #3 NASA-GISS GISS-E2.1G model output prepared for CMIP6 ISMIP6 https://doi.org/10.22033/ESGF/CMIP6.2294 https Related Dataset #4 E3SM-Project E3SM1.0 model output prepared for CMIP6 CMIP https://doi.org/10.22033/ESGF/CMIP6.3610 https Related Dataset #5 CCCma CanESM5 model output prepared for CMIP6 CMIP historical https://doi.org/10.22033/ESGF/CMIP6.5070 https Related Dataset #6 INM INM-CM5-0 model output prepared for CMIP6 CMIP historical https://doi.org/10.22033/ESGF/CMIP6.5195 https Related Dataset #7 IPSL IPSL-CM6A-LR model output prepared for CMIP6 CMIP historical https://doi.org/10.22033/ESGF/CMIP6.621 https Related Dataset #8 MRI MRI-ESM2.0 model output prepared for CMIP6 CMIP https://doi.org/10.22033/ESGF/CMIP6.6594 https Related Dataset #9 MPI-M MPI-ESM1.2-HR model output prepared for CMIP6 CMIP historical https://doi.org/10.22033/ESGF/CMIP6.6595 https Related Dataset #10 MPI-M MPI-ESM1.2-LR model output prepared for CMIP6 CMIP historical Probabilistic evaluation of drought in CMIP6 simulations 2021-10-01T00:00:00Z publication https://n2t.org/ark:/85065/d7gx4g1j https://doi.org/10.1029/2021EF002150 Papalexiou, S. M. author Rajulapati, C. R. author Andreadis, K. M. author Foufoula-Georgiou, E. author Clark, M. P. author Trenberth, Kevin E. author UCAR/NCAR - Library publisher As droughts have widespread social and ecological impacts, it is critical to develop long-term adaptation and mitigation strategies to reduce drought vulnerability. Climate models are important in quantifying drought changes. Here, we assess the ability of 285 CMIP6 historical simulations, from 17 models, to reproduce drought duration and severity in three observational data sets using the Standardized Precipitation Index (SPI). We used summary statistics beyond the mean and standard deviation, and devised a novel probabilistic framework, based on the Hellinger distance, to quantify the difference between observed and simulated drought characteristics. Results show that many simulations have less than +/- 10% error in reproducing the observed drought summary statistics. The hypothesis that simulations and observations are described by the same distribution cannot be rejected for more than 80% of the grids based on our H distance framework. No single model stood out as demonstrating consistently better performance over large regions of the globe. The variance in drought statistics among the simulations is higher in the tropics compared to other latitudinal zones. Though the models capture the characteristics of dry spells well, there is considerable bias in low precipitation values. Good model performance in terms of SPI does not imply good performance in simulating low precipitation. Our study emphasizes the need to probabilistically evaluate climate model simulations in order to both pinpoint model weaknesses and identify a subset of best-performing models that are useful for impact assessments. UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact PDF Text theme Resource Type 2016-01-01T00:00:00Z publication Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. None eng geoscientificInformation