Ying Xu

Based on the CN05.1 observation grid data and CMIP6 (Coupled Model Intercomparison Project Phase 6) model simulation data, this study comprehensively evaluated the simulation capability of CMIP6 models for scPDSI (selfcalibrating Palmer Drought Severity Index) of China and selected seven model ensembles with relatively good performance to project the change characteristics of scPDSI, runoff, and soil moisture in China in the 21st century. On this basis, this study analyzed the uncertainty in the CMIP6 future projection. The results show that the simulation capability of CMIP6 models for scPDSI over China still needs improvement and the simulation performance of the multimodel ensemble is better than most individual models, but deficiencies remain in temporal and amplitude trends. The temporal trend of scPDSI shows a slightly increasing trend for the SSP1-2.6 and SSP2-4.5 scenarios, with trend values of 0.03 (10 a)−1 and 0.01 (10 a)−1, respectively, and decreasing for the SSP5-8.5 scenario [−0.05 (10 a)−1]. Soil moisture shows decreasing trends over time: the trend values of the surface soil moisture and total soil moisture are −0.30% (10 a)−1 and −0.26% (10 a)−1 for the SSP5-8.5 scenario, respectively. Runoff shows increasing trends with time: the trend values of the surface runoff and total runoff are 1.76% (10 a)−1 and 3.13% (10 a)−1 for the SSP5-8.5 scenario, respectively. At the end of the 21st century, the annual scPDSI over China generally decreases under SSP5-8.5scenario, changes in soil moisture are generally “high in the North and low in the South”, the downtrend is most significant in the Qinghai–Xizang Plateau region, and the change range of surface soil moisture is bigger than total soil moisture. Runoff tends to rise in most areas, except in Northwest China and Qinghai–Xizang Plateau region, and its change range is bigger with the emission scenarios. The probability density curves of most variables in the 21st century flatten as the emission scenarios increase, so future changes will become more dramatic.

Cold winters in Eurasia considerably affect transportation, agriculture, energy, and public health. This study utilizes 31 global climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and 33 CMIP5 models to evaluate the historical surface air temperature, sea level pressure, 500‐hPa geopotential height, 150‐hPa meridional and zonal wind, and polar vortex indices during cold winters. Our research quantifies the advancements of CMIP6 over CMIP5. Additionally, future changes in these variables under three different Shared Socioeconomic Pathways (SSPs), that is, SSP 1–2.6, SSP 2–4.5, and SSP 5–8.5, are projected based on 20 out of the 31 CMIP6 models. The results indicate that the multimodel ensemble means from both CMIP5 and CMIP6 effectively capture the main features of the observed Eurasian cold winters and their associated factors with good simulation agreement. The CMIP6 ensemble mean outperforms its CMIP5 counterpart, and both ensemble means (CMIP5 and CMIP6) perform better than individual CMIP6 models. Among CMIP6 models, 500‐hPa geopotential height achieves the highest simulation skill, whereas sea level pressure shows the lowest. Compared with same‐institute models from CMIP5, CMIP6 models show overall improvements with sea level pressure simulation being notably advanced. Under the three SSPs, the occurrence probability of cold winters is projected to decrease as the area and intensity indices of the polar vortex decline. Moreover, surface temperature anomalies are projected to exhibit a “warm Arctic and cold Eurasia” pattern, and the anticyclonic anomalies at 500 hPa and 150 hPa are projected to be centered at high latitudes.

Using the simulation results from the CMIP6 global climate models, we calculate the projected changes of different kinds of Arctic cyclones (ACs)in the 21st century and examine the characteristics related to the Arctic cyclones under two shared socio-economic pathways (SSP1-2.6, SSP5-8.5). There is a significant decline of ACs during winter over southern Greenland, the Barents Sea, and the Gulf of Alaska. The number of Arctic cyclones has a significant circular decrease along the Arctic over most of the continent region in summer. By the end of the 21st century, the proportion of weaker, large-radius, and long-lifespan ACs will increase. The number of extreme Arctic cyclones will decrease in the future. However, the trend in the intensity of Arctic cyclones depends on the measure of cyclone intensity we use. Weaker baroclinic instability in the future is the primary reason for the decline of cyclone density in winter, but the situation in summer is more complicated. The number of Arctic cyclones in summer is affected by various factors like tropopause polar vortex and mid-latitude cyclones entering the Arctic. The positive anomaly of Eady growth rate can also cause the explosive growth of cyclones over the ocean.

An analysis is presented of the precipitation bias and change signal in an ensemble of regional climate model (RCM) (RegCM4) projections driven by multiple general circulation models (GCMs) over China. RegCM4 is driven by five different GCMs for the 120‐year period 1979–2099 at 25 km grid spacing, under the representative concentration pathway RCP8.5. We find that the GCMs and RegCM4 reproduce the general spatial pattern of precipitation over China in all four seasons, with RegCM4 providing greater spatial detail, especially over areas with complex terrain. The spatial patterns of precipitation bias show common features between the GCMs and RegCM4, characterized by an underestimation in the wetter regions, and an overestimation in the drier ones. Systematic increases of precipitation are projected in northern China, most pronounced in the Northwest basins, by both the GCMs and RegCM4 in all seasons except summer, when more mixed results are found. In addition, weak correlations of the projected change patterns are found in summer between the GCMs and nested RegCM4, indicating the greater role played by the representation of local convection processes during this monsoon season. The projections across the RegCM4 experiments show higher consistency and lower spread compared to the GCM ensemble, again indicating that the nested model physics significantly modulates the change signal deriving from the GCM boundary forcing.

Based on ERA5 and 23 CMIP6 models under three Shared Socioeconomic Pathways (SSPs), we assess the performance of CMIP6 models in reproducing the summer precipitation, evaporation and precipitation recycling ratio (PRR) over the Tibetan Plateau (TP) during 1981-2014. We also project future changes of the summer precipitation, evaporation, PRR and moisture transport over the TP during 2021-2100. CMIP6 models and their ensemble mean reproduce the temporal and spatial characteristics of precipitation, evaporation, PRR and moisture transport over the TP. And the performance in simulating precipitation is better than that in simulating evaporation and PRR. The precipitation and evaporation under the three Shared Socioeconomic Pathways (SSPs) will increase, with the significant upward trends of 0.84%/decade~2.79%/decade and 0.80%/decade~2.14%/decade, respectively. However, the PRR will increase slightly (0.13%/decade) then marginally reduce (-0.22%/decade). In the late 21st century, regional mean summer precipitation, evaporation and PRR over the TP in SSP5-8.5 will change by about 20.13%, 17.14% and -0.77%, respectively. From spatial distribution, precipitation will increase in most parts of the TP in the 21st century, especially in the western part of the plateau, reaching more than 50% in of the late 21st century, the area of PRR decreased gradually expanded, with the maximum reduction (15~20%) of PRR in the western region. It indicates that more precipitation in the western of the plateau depends on the external moisture transport. The PRR in the southern part of the plateau will increase, with a maximum of more than 20%, which indicates the contribution of the external water vapor transport to the southern precipitation will decrease, and that of the internal cycle (local evaporation) to the local precipitation will increase. In conclusion, the increase of the regional mean precipitation over the TP in the near and mid-21st century is mainly due to the local evaporation, while the increase of the summer precipitation in the late 21st century is due to both the local evaporation and the external water vapor advection, it shows that the precipitation generated by the inner circulation is becoming weaker and more dependent on the external water vapor transport.

This paper evaluates the historical simulated surface concentrations of particulate matter small than 2.5 µm in diameter (PM_2.5) and its components (black carbon (BC), dust, SO₄, and organic aerosol (OA)) in Asia, which come from Coupled Model Intercomparison Project Phase 6 (CMIP6). In addition, future projected changes of surface PM_2.5 and its components, as well as their exposure to population, under the different Shared Socioeconomic Pathway (SSP) scenarios are also provided. Results show that the simulated spatial distribution of surface PM_2.5 concentrations is consistent with the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) and Socioeconomic Data and Applications Center (SEDAC). The model spreads are small/large over the regions with low/high climatic mean surface PM_2.5 concentrations, i.e., Northern Asia/Saudi Arabia, Iran, and Xinjiang Province of China. The multi-model ensemble of CMIP6 reproduces the main features of annual cycles and seasonal variations in Asia and its sub-regions. Under the scenarios of SSP1-2.6, SSP2-4.5, and SSP5-8.5, compared to the present-day period of 1995–2014, annual mean surface PM_2.5 concentrations are projected to decrease in Asia, with obvious differences among the scenarios. Meanwhile, the magnitudes and timings of changes at the regional scale are quite different, with the largest decreases in South Asia (SAS). Under SSP3-7.0, the increase of surface PM_2.5 concentrations in SAS is the largest, with the increase value of 8 μg/m³ in 2050; while under SSP370-lowNTCF, which assumes stronger levels of air quality control measures relative to the SSP3-7.0, the decreases of surface PM_2.5 concentrations in SAS, East Asia (EAS) and Southeast Asia (SEAS) are the largest. The characteristics of seasonal trends are consistent with that of the annual trend. The trends in the concentrations of surface PM_2.5 and its components are similar. The population-weighted average values of surface PM_2.5 concentrations are projected to decrease in Central Asia (CAS), EAS, North Asia (NAS), and SEAS, and it indicates that the surface PM_2.5 concentrations over the most populated area of Asia will decrease. In SAS, because of its large population, the impact of air pollutants on human health is still disastrous in the future. In summary, the surface PM_2.5 concentrations over the most area of Asia will decrease, which is beneficial to air quality and human health; under SSP370-lowNTCF, the reduction of short-lived climate forcers (SLCFs) will further improve air quality.

Using the dynamical downscaling by the regional climate model RegCM4 from four global climate models, future changes in heat waves (HWs) over China under the RCP4.5 scenario are projected in terms of frequency and magnitude. The magnitude combines the duration and intensity together to characterize HW severity. The ensemble of RegCM4 downscaling simulations indicates a substantial increase in the frequency and magnitude of HWs over China toward the end of the 21st century relative to the current climate (1986–2005). The considerable changes occur in Southwest, South, North, and Northeast China for the frequency and in South, Southwest, East, and Central China for the magnitude. The prolonged HW duration plays a leading role in the enhancement of HW severity. In particular, an accelerated aggravation of the risk of extreme HWs is anticipated. Unusual HWs that never occurred in the current climate are expected to be usual phenomenon. For instance, by the end of the 21st century, the risks of the occurrence of extreme HWs (above the 99th percentile) in Southwest and South China are 64 and 53 times of the current, respectively, while the projected risks of the occurrence of mild HWs (below the 60th percentile) are much smaller and comparable in China. The HW frequency above the maximum of the current would appear once almost every year, and South, Central, and East China (North and Northeast China) would experience more severe HWs than the most extreme of the present every 1–2 (2–4) years.

Based on the dynamic downscaling by the regional climate model RegCM4 from three CMIP5 global models under the historical and the RCP4.5 simulations, this article evaluated the performance of the RegCM4 downscaling simulations on the air environment carrying capacity (AEC) and weak ventilation days (WVDs) in China, which are applied to measure haze pollution potential. Their changes during the middle and the end of the 21st century were also projected. The evaluations show that the RegCM4 downscaling simulations can generally capture the observed features of the AEC and WVD distributions over the period 1986–2005. The projections indicate that the annual AEC tends to decrease and the annual WVDs tend to increase over almost the whole country except central China, concurrent with greater change by the late 21st century than by the middle of the 21st century. It suggests that annual haze pollution potential would be enlarged under the RCP4.5 scenario compared to the present. For seasonal change in the four main economic zones of China, it is projected consistently that there would be a higher probability of haze pollution risk over the Beijing–Tianjin–Hebei (BTH) region and the Yangtze River Delta (YRD) region in winter and over the Pearl River Delta (PRD) region in spring and summer in the context of the warming scenario. Over Northeast China (NEC), future climate change might reduce the AEC or increase the WVDs throughout the whole year, which favours the occurrence of haze pollution and thus the haze pollution risk would be aggravated. The relative contribution of different components related to the AEC change further indicates that changes in the boundary layer depth and the wind speed play leading roles in the AEC change over the BTH and NEC regions. In addition to those two factors, the precipitation change also exerts important impacts on the AEC change over the YRD and PRD zones.