Surface wind speed has great impacts on the economy, environment, and society around the world. Based on 24 global climate models (GCMs) from Coupled Model Intercomparison Project Phase 6 (CMIP6), this paper assesses the historical surface wind speed over China, and quantifies the advancements of CMIP6 over CMIP5. In addition, future changes of surface wind speed under the Shared Socioeconomic Pathway scenarios of 1‐2.6, 2‐4.5, and 5‐8.5 (SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5) are also provided, by using 18 out of the 24 models with all three scenarios. Results show that multimodel ensemble mean of CMIP6 can well capture the spatial distributions of the annual, summer, and winter surface wind speed and generally performs better than both the median of the individual CMIP6 GCMs and multimodel ensemble mean of CMIP5 in monthly, seasonal, and annual wind climatology. However, CMIP6 GCMs fail to reproduce the observed decreasing trends, in terms of magnitude and/or sign. Meanwhile, the annual cycle of the surface wind speed simulated by CMIP6 GCMs falsely demonstrates the maximum in winter instead of spring. In the context of global warming, surface wind speed is projected to decrease in most parts of China in the middle and late 21st century under the three scenarios. Moreover, the trends of wind speed averaged over China will decrease significantly in both annual and winter under all three scenarios, but it will increase significantly in summer under SSP5‐8.5.

This article revealed that strengthening of winter Hadley circulation in the context of climate change may partially contribute to interdecadal increasing of snowfall intensity over northeastern China in recent decades. This hypothesis is well supported by the process‐based linkage between Hadley circulation and atmospheric circulations over the Asian‐Pacific region on the interdecadal time scale. The strengthening of winter Hadley circulation corresponds to a weakening of the Siberian high, an eastward shifting of the Aleutian low, a reduction of the East Asian trough, and anomalous southwesterly prevailing over northeastern China. These atmospheric situations weaken the East Asian winter monsoon and lead to an increase of air temperature over northeastern China. Increased local evaporation due to the increase of air temperature, concurrent with more water vapor transported from the Pacific Ocean, can significantly enhance atmospheric water vapor content in the target region. Meanwhile, the ascending of airflows is also strengthened over northeastern China. All of these provide favorable interdecadal backgrounds for the occurrence of intense snowfalls, and thus, snowfall intensity is intensified over northeastern China after the 1980s. Further analysis suggests that the circum‐Pacific‐like teleconnection pattern may play an important role in connecting Hadley circulation strengthening signal and atmospheric circulation anomalies favoring interdecadal intensification of snowfalls over northeastern China.

Based on climate simulations over East Asia from a high-resolution regional climate model under RCP4.5 and 8.5 scenarios, we examine the impact of future climate change and heating policy changes on energy demand in current central heating areas over China using the heating degree days (HDD) and the number of the heating days (NHD) with different base temperature as the indices. Based on current heating policy in China, significant decreases of NHDs are projected, with larger decreases under RCP8.5 than RCP4.5. This decrease of NHDs would cause a northward shift of the decadal heating boundary line, with significant implications for infrastructure planning and development. Changing the heating policy currently in practice to one used in Europe and USA would cause an immediate jump in NHDs and in HDDs; as warming progresses in the future, these effects attenuate with time in an approximately linear trend under the two scenarios. Under RCP8.5, by 2050, the effects of warming climate would dominate over the heating policy change, and heating demand would be lower than the present day HDD and continue to decrease until the end of the century. Energy demand and the number of the heating days during peak winter shows no dependence on heating policy, as the policy-induced increase of energy demand would occur primarily during warmer months of the year. In addition, the indices are further weighted by population, and results show that increases in both HDDs and NHDs can be found in parts of northern China due to the increased population there by the end of the 21st century.

Using the Regional Climate Model (RegCM) coupled with the Community Land Model (CLM) including modules of carbon–nitrogen cycling (CN) and vegetation dynamics (DV), this study evaluates the performance of the model with different capacity of representing vegetation processes in simulating the present-day climate over China based on three 21-yr simulations driven with boundary conditions from the ERA-Interim reanalysis data during 1989–2009. For each plant functional type (PFT), the plant pheonology, density, and fractional coverage in RegCM-CLM are all prescribed as static from year to year; RegCM-CLM-CN prescribes static fractional coverage but predicts plant phenology and density, and RegCM-CLM-CN-DV predicts plant phenology, density, and fractional coverage. Compared against the observational data, all three simulations reproduce the present-day climate well, including the wind fields, temperature and precipitation seasonal cycles, extremes, and interannual variabilities. Relative to RegCM-CLM, both RegCM-CLM-CN and RegCM-CLM-CN-DV perform better in simulating the interannual variability of temperature and spatial distribution of mean precipitation, but produce larger biases in the mean temperature field. RegCM-CLM-CN overestimates leaf area index (LAI), which enhances the cold biases and alleviates the dry biases found in RegCM-CLM. RegCM-CLM-CN-DV underestimates vegetation cover and/or stature, and hence overestimates surface albedo, which enhances the wintertime cold and dry biases found in RegM-CLM. During summer, RegCM-CLM-CN-DV overestimates LAI in south and east China, which enhances the cold biases through increased evaporative cooling; in the west where evaporation is low, the albedo effect of the underestimated vegetation cover is still dominant, leading to enhanced cold biases relative to RegCM-CLM.