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Projected changes in meteorological drought over East Africa inferred from bias-adjusted CMIP6 models.

ABSTRACT: The ongoing global warming has caused unprecedented changes in the climate system, leading to an increase in the intensity and frequency of weather and climate extremes. This study uses the sixth phase of Coupled Model Intercomparison Project (CMIP6) data to investigate projected changes in drought events over East Africa (EA) under four Shared Socioeconomic Pathway (SSP) emission scenarios (SSP1-2.6, SSP2-4.5, SSP3-4.0, and SSP5-8.5). The CMIP6 data are bias-corrected using a quantile mapping method, with the Climatic Research Unit's precipitation dataset as reference. Drought is quantified using the standardized precipitation index and different measures of drought are estimated: drought duration, drought frequency, drought severity, and drought intensity. Evaluating the accuracy and reliability of historical data before and after bias correction demonstrates the importance of the approach. The overall distribution after bias correction depicts a close agreement with observation. Moreover, the multi-model ensemble mean demonstrate superiority over individual Global Circulation Models. Projected future changes show enhancement in precipitation over most parts of EA in the far future under different SSP scenarios. However, the arid and semi-arid regions are expected to receive less amount of precipitation, whereas the highlands and lake regions are expected to receive a larger amount of precipitation increase. Furthermore, the dry areas of EA are likely to experience more frequent drought events with longer duration, stronger intensity, and severity in the far future. Overall, this study identifies possible drought hotspots over EA, enabling early preparation for such events.

Supplementary information

The online version contains supplementary material available at 10.1007/s11069-022-05341-8.

SUBMITTER: Ayugi B

PROVIDER: S-EPMC8993679 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description: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 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. Key Points Simulations reproduce observed drought duration and severity in terms of the Standardized Precipitation Index (SPI) but simulated low precipitation is considerably biased Variance in drought statistics among the simulations is higher in the tropics compared to other latitudinal zones Good model performance in terms of SPI does not imply that low precipitation values are well simulated by the climate models

Dataset Information

Projected changes in meteorological drought over East Africa inferred from bias-adjusted CMIP6 models.

Supplementary information

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