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Drought is a meteorological phenomenon that threatens ecosystems, agricultural production, and living conditions. Central Asia is highly vulnerable to drought due to its special geographic location, water resource shortages, and extreme weather conditions, and poor management of water resources and reliance on irrigated agriculture exacerbate the effects of drought. In this study, the latest version of the Global Land Data Assimilation System was employed to calculate the Standardized Precipitation Evapotranspiration Index at different time scales during the period from 1981 to 2020. The varimax Rotated Empirical Orthogonal Function was applied for subregional delineation of drought patterns in Central Asia, and various methods were employed for a comparative analysis of the spatiotemporal characteristics of drought in these Central Asian subregions. The results show that drought patterns vary considerably in the Central Asian subregions. Over the past 40 years, alternating wet and dry conditions occurred in Central Asia. North Kazakhstan experienced more drought events with lower severity. East and west differences appear after 2001, the west becoming drier and the east becoming wetter. Some regions near lakes, such as Balkhash, Issyk-Kul, and the Aral Sea, suffer from droughts of long duration and high severity. In the Tianshan region, droughts in the northern slopes occur more frequently, with shorter durations and higher intensity and peaks. Northwestern China and western Mongolia have extensive agricultural land and grasslands with highly fragile ecosystems that have become progressively drier since 2001. [ABSTRACT FROM AUTHOR]

Future changes in drought characteristics in Central Asia are projected at the regional scale using 21 climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Based on the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI), drought characteristics were characterized by drought frequency at 1-, 3-, and 12-month timescales. The drought duration was analyzed based on SPI1 and SPEI1. Drought indices were calculated by the multimodel ensemble (MME) from 21 CMIP5 models. The varimax rotation method was used to identify drought conditions for the entire area and seven drought subregions. In general, the projection results of future drought in Central Asia are related to the choice of drought index, and SPI and SPEI show different results. The drought frequency based on SPEI1, SPEI3, and SPEI12 showed an increasing trend in the future periods, that is, the drought frequency based on monthly, seasonal, and annual timescales will show an increase trend in the future periods. However, for SPI1, SPI3, and SPI12, the drought frequency will decrease in the future. SPI projected that the duration of drought will decrease in the future, while SPEI mainly showed an increasing trend. The results of the study should be of sufficient concern to policymakers to avoid land degradation, crop loss, water resource deficit, and economic loss. [ABSTRACT FROM AUTHOR]

Using historical data compiled by the Climate Research Unit, spatial and temporal analysis, trend analysis, empirical orthogonal function (EOF) analysis, and Taylor diagram analysis were applied to test the ability of 24 Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models to accurately simulate the annual mean surface air temperature in central Asia from the perspective of the average climate state and climate variability. Results show that each model can reasonably capture the spatial distribution characteristics of the surface air temperature in central Asia but cannot accurately describe the regional details of climate change impacts. Some of the studied models, including CNRM-CM5, GFDL-CM3, and GISS-E2-H, could better simulate the high- and low-value centers and the contour distribution of the surface air temperature. Taylor diagram analysis showed that the root mean square errors of all models were less than 3, the standard deviations were between 8.36 and 13.45, and the spatial correlation coefficients were greater than 0.96. EOF analysis showed that the multi-model ensemble can accurately reproduce the surface air temperature characteristics in central Asia from 1901 to 2005, including the rising periods and the fluctuations of the north and south inversion phases. Overall, this study provides a valuable reference for future climate prediction studies in central Asia. [ABSTRACT FROM AUTHOR]