Probabilistic Evaluation of Drought in CMIP6 Simulations.

ABSTRACT: 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

SUBMITTER: Papalexiou SM 

PROVIDER: S-EPMC8596413 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature