Understanding historical and future drought patterns is crucial to acclimation and the mitigation of drought. The negative impact of China’s droughts on the social economy has attracted attention; however, there is still no comprehensive or long-term monitoring pattern for future droughts. Here we evaluated the precipitation and temperature simulation capability of Coupled Model Intercomparison Project Phase 6 (CMIP6) and evaluated the temporal and spatial pattern of droughts during 1961–2099 across China. The results show that the multi-model ensemble mean (MME) is more representative of the observed precipitation and temperatures across China than the single climate model. China experienced an overall drying trend in the historical period. After 1991, the drought frequency (DF), drought duration (DD), and drought intensity (DI) in the northwest of the Inland River Basin and in the Yangtze River Basin increased significantly. Compared with the historical period, China will suffer more frequent drought events, although the DD and DI will be weakened under SSP1-2.6 and SSP2-4.5, while China will experience longer DD and more serious drought events under SSP3-7.0 and SSP5-8.5. The Hai River Basin and Huai River Basin are expected to have more serious drought trends in summer. Compared with historical periods, the drought trend will increase by 2.9‒5.7 times and 1.1‒4.2 times, respectively. The results can be used for decision making regarding future drought control.
In the context of global warming, relevant studies have shown that China will experience the largest temperature rise in the Qinghai–Tibet Plateau and northwestern regions in the future. Based on MOD10A2 and MYD10A2 snow products and snow depth data, this study analyzes the temporal and spatial evolution characteristics of the snow cover fraction, snow depth, and snow cover days in the three stable snow cover areas in China, and combines 15 modes in CMIP6 snow cover data in four different scenarios with three kinds of variables, predicting the spatiotemporal evolution pattern of snow cover in China’s three stable snow cover areas in the future. The results show that (1) the mean snow cover fraction, snow depth, and snow cover days in the snow cover area of Northern Xinjiang are all the highest. Seasonal changes in the snow cover areas of the Qinghai–Tibet Plateau are the most stable. The snow cover fraction, snow depth, and snow cover days of the three stable snow cover areas are consistent in spatial distribution. The high values are mainly distributed in the southeast and west of the Qinghai–Tibet Plateau, the south and northeast of Northern Xinjiang, and the north of the snow cover area of Northeast China. (2) The future snow changes in the three stable snow cover areas will continue to decline with the increase in development imbalance. Snow cover fraction and snow depth decrease most significantly in the Qinghai–Tibet Plateau and the snow cover days in Northern Xinjiang decrease most significantly under the SSPs585 scenario. In the future, the southeast of the Qinghai–Tibet Plateau, the northwest of Northern Xinjiang, and the north of Northeast China will be the center of snow cover reduction. (3) Under the four different scenarios, the snow cover changes in the Qinghai–Tibet Plateau and Northern Xinjiang are the most significant. Under the SSPs126 and SSPs245 scenarios, the Qinghai–Tibet Plateau snow cover has the most significant change in response. Under the SSPs370 and SSPs585 scenarios, the snow cover in Northern Xinjiang has the most significant change.
Inner Mongolia is one of the main green production bases of agricultural and animal husbandry products. Due to factors such as natural geographical location, drought occurs frequently in Inner Mongolia. Based on the MOD16 product and the method of crop water stress index (CWSI) combined with multi-year precipitation and temperature data, the spatial and temporal distribution characteristics and major influencing factors of drought in Inner Mongolia from 2001 to 2017 were analyzed. In order to provide effective scientific basis for drought control and drought resistance in Inner Mongolia for decision. The results showed that: (1) during 2001–2017, the average annual CWSI in Inner Mongolia had a strong spatial heterogeneity, which showed a trend of gradual increase from northeast to southwest. The annual average CWSI was 0.7787 and showed a fluctuating downward trend for Inner Mongolia. (2) The CWSI of every 8d during one year in Inner Mongolia showed the double-peak trend, reaching its maximum of 0.9043 in the 121st day. In addition, the average CWSI of every 8d was 0.6749. (3) In Inner Mongolia, the average CWSI of different land-use types showed little difference and ranged from small to large: woodland (0.5954) < cropland (0.7733) < built-up land (0.8126) < grassland (0.8147) < unused land (0.8392). (4) The average correlation coefficients between CWSI and precipitation, temperature respectively were −0.53 and 0.18, which indicated that CWSI was highly correlated with precipitation in Inner Mongolia.
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