Projections of future drought conditions under climate change are an important step in formulating the long‐term climate adaptation strategies. It is therefore valuable to predict the drought conditions in China following the release of the CMIP6 (the phase six of the Coupled Model Inter‐comparison Project). Thus, based on 20 global climate model simulations from CMIP6, we project China's drought conditions and its socioeconomic impacts using the self‐calibrated Palmer Drought Severity Index (scPDSI). Four scenarios are considered in this analysis: SSP1‐2.6 (the low‐level development scenario), SSP2‐4.5 (the middle‐level development scenario), SSP3‐7.0 (the medium to high‐level development scenario) and SSP5‐8.5 (the high‐level development scenario). Under SSP1‐2.6, we observed wetting trends over large areas of China except the arid region during 2020–2099; however, under SSP2‐4.5, SSP3‐7.0 and SSP5‐8.5, significant drying trends are detected in the humid and temperate semi‐humid region, while in other areas there are significant wetting trends. The projected drought conditions are likely to be severe with more frequent monthly occurrences and higher probability of extreme drying conditions, especially in these humid and temperate semi‐humid regions under SSP3‐7.0 and SSP5‐8.5. Consequently, the population exposure to drought in most climatic regions will increase initially up to 2040s and gradually decrease under all the scenarios except SSP3‐7.0; and the humid region will be a future hotspot where the impact of climate on population exposure to drought will be more significant. The economic exposure to drought will increase over the whole China under all four scenarios, especially in the humid and semi‐humid region. Our results have important implications for future drought projections and provide a scientific evidence for developing climate change adaptation strategies and disaster prevention.

Climate warming has significantly changed the global water cycle, particularly the components of land evapotranspiration (ET), precipitation and runoff, in observations and numerical simulations (Durack et al.

Soil moisture is an important parameter in land surface processes, which can control the surface energy and water budgets and thus affect the air temperature. Studying the coupling between soil moisture and air temperature is of vital importance for forecasting climate change. This study evaluates this coupling over China from 1980–2013 by using an energy-based diagnostic method, which represents the momentum, heat, and water conservation equations in the atmosphere, while the contributions of soil moisture are treated as external forcing. The results showed that the soil moisture–temperature coupling is strongest in the transitional climate zones between wet and dry climates, which here includes Northeast China and part of the Tibetan Plateau from a viewpoint of annual average. Furthermore, the soil moisture–temperature coupling was found to be stronger in spring than in the other seasons over China, and over different typical climatic zones, it also varied greatly in different seasons. We conducted two case studies (the heatwaves of 2013 in Southeast China and 2009 in North China) to understand the impact of soil moisture–temperature coupling during heatwaves. The results indicated that over areas with soil moisture deficit and temperature anomalies, the coupling strength intensified. This suggests that soil moisture deficits could lead to enhanced heat anomalies, and thus, result in enhanced soil moisture coupling with temperature. This demonstrates the importance of soil moisture and the need to thoroughly study it and its role within the land–atmosphere interaction and the climate on the whole.

Evapotranspiration (ET) bridges the hydrological and energy cycle through vegetation transpiration (T), soil evaporation (ES), and canopy interception evaporation (EI). Transpiration to evapotranspiration ratio (T/ET) quantifies the water use efficiency of terrestrial ecosystems explaining the mechanism of vegetation water transport and water–carbon interactions. This study employed GIMMS LAI3g data to improve the CLM4.5 land surface scheme of RegCM4.6. We designed two simulation experiments, each with control (CTL) and sensitivity (SEN), simulating the interannual variability of vegetation on ET and T/ET in China from 1982 to 2015. Studies show China has experienced a greening trend, especially in mid-south China and South China. Leaf area index (LAI) increased significantly (0.002 m2m−2yr−1). ∆LAI (SEN input LAI data minus CTL input LAI data) and ∆T/ET (T/ET data output by SEN minus T/ET data output by CTL) have shown significant positive correlations. The impacts of LAI on T/ET are more prominent during spring and winter than in autumn and summer. Compared with T/ET and LAI (R = 0.70), the correlation between ET and LAI is moderate (R < 0.5), indicating that vegetation has a higher impact on T/ET than ET. The impact of vegetation anomalies (positive and negative LAI anomalies) on T/ET and ET is spatially different, mainly due to dominant factors affecting ET and T/ET changes. In spring, summer, and autumn, &T (transpiration changes corresponding to vegetation anomalies) is the leading factor affecting both ET and T/ET regionally, and &T has a stronger influence on T/ET than ET, especially in summer. Vegetation anomalies have a stronger influence on T/ET than ET; and the influence of positive vegetation anomalies on ET and T/ET is greater than that of negative vegetation anomalies, especially in spring and autumn. This study reveals the mechanisms behind vegetation processes and their influences on the water and heat fluxes at the land–atmosphere interface and provides a strong scientific basis for studying the water cycle under climate warming.