The climatic effects of various types of aerosol in China have been investigated by using the atmospheric general circulation model (AGCM) developed at the University of California, Los Angeles (UCLA). The model includes an efficient and physically based radiation parameterization scheme specifically developed for application to clouds and aerosols. Simulation results show that inclusion of a background aerosol optical depth of 0.2 reduces the global mean net surface solar flux by about 5 W m⁻²and produces a decrease in precipitation in the tropics as a result of decreased temperature contrast between this area and the middle to high latitudes, which suppresses tropical convection. These decreases have partially corrected the overestimates in the surface solar flux and precipitation in the UCLA AGCM simulations without the aerosol effect. The experiment with increased aerosol optical depths in China shows a noticeable increase in precipitation in the southern part of China in July due to the cooling in the midlatitudes that leads to the strengthening of the Hadley circulation. Aerosol types play an important role in the determination of the global mean radiation budget and regional climate. While sulfates mainly reflect solar radiation and induce negative forcing at the surface, black carbon and large dust particles absorb substantial solar radiation and have a positive solar forcing at the top of the atmosphere, but reduce the solar radiation reaching the surface. Large dust particles also have a significant effect on thermal IR radiation under clear conditions, but this effect is largely masked by clouds generated from the model in AGCM simulations. Black carbon and large dust particles in China would heat the air column in the middle to high latitudes and tend to move the simulated precipitation inland, i.e., toward the Himalayas. The inclusion of black carbon in our simulations has not produced the “north drought/south flooding” precipitation pattern that has frequently occurred in China during the past 50 years.

The Beijing–Tianjin–Hebei (BTH) region has been suffering from the most severe fine-particle (PM_2. 5) pollution in China, which causes serious health damage and economic loss. Quantifying the source contributions to PM_2. 5 concentrations has been a challenging task because of the complicated nonlinear relationships between PM_2. 5 concentrations and emissions of multiple pollutants from multiple spatial regions and economic sectors. In this study, we use the extended response surface modeling (ERSM) technique to investigate the nonlinear response of PM_2. 5 concentrations to emissions of multiple pollutants from different regions and sectors over the BTH region, based on over 1000 simulations by a chemical transport model (CTM). The ERSM-predicted PM_2. 5 concentrations agree well with independent CTM simulations, with correlation coefficients larger than 0.99 and mean normalized errors less than 1 %. Using the ERSM technique, we find that, among all air pollutants, primary inorganic PM_2. 5 makes the largest contribution (24–36 %) to PM_2. 5 concentrations. The contribution of primary inorganic PM_2. 5 emissions is especially high in heavily polluted winter and is dominated by the industry as well as residential and commercial sectors, which should be prioritized in PM_2. 5 control strategies. The total contributions of all precursors (nitrogen oxides, NO_x; sulfur dioxides, SO₂; ammonia, NH₃; non-methane volatile organic compounds, NMVOCs; intermediate-volatility organic compounds, IVOCs; primary organic aerosol, POA) to PM_2. 5 concentrations range between 31 and 48 %. Among these precursors, PM_2. 5 concentrations are primarily sensitive to the emissions of NH₃, NMVOC + IVOC, and POA. The sensitivities increase substantially for NH₃ and NO_x and decrease slightly for POA and NMVOC + IVOC with the increase in the emission reduction ratio, which illustrates the nonlinear relationships between precursor emissions and PM_2. 5 concentrations. The contributions of primary inorganic PM_2. 5 emissions to PM_2. 5 concentrations are dominated by local emission sources, which account for over 75 % of the total primary inorganic PM_2. 5 contributions. For precursors, however, emissions from other regions could play similar roles to local emission sources in the summer and over the northern part of BTH. The source contribution features for various types of heavy-pollution episodes are distinctly different from each other and from the monthly mean results, illustrating that control strategies should be differentiated based on the major contributing sources during different types of episodes.

Topography exerts significant influences on the incoming solar radiation at the land surface. A few stand-alone regional and global atmospheric models have included parameterizations for sub-grid topographic effects on solar radiation. However, nearly all Earth system models (ESMs) that participated in the Coupled Model Intercomparison Project (CMIP6) use a plane-parallel (PP) radiative transfer scheme that assumes that the terrain is flat. In this study, we incorporated a well-validated sub-grid topographic (TOP) parameterization in the Energy Exascale Earth System Model (E3SM) Land Model (ELM) version 1.0 to quantify the effects of sub-grid topography on solar radiation flux, including the shadow effects and multi-scattering between adjacent terrain. We studied the role of sub-grid topography by performing ELM simulations with the PP and TOP schemes over the Tibetan Plateau (TP). Additional ELM simulations were performed at multiple spatial resolutions to investigate the role of spatial scale on sub-grid topographic effects on solar radiation. The Moderate Resolution Imaging Spectroradiometer (MODIS) data was used to compare with the ELM simulations. The results show that topography has non-negligible effects on surface energy budget, snow cover, snow depth, and surface temperature over the TP. The absolute differences in surface energy fluxes for net solar radiation, latent heat flux, and sensible heat flux between TOP and PP exceed 20, 10, and 5 W m⁻², respectively. The differences in land surface albedo, snow cover fraction, snow depth, and surface temperature between TOP and PP exceed 0.1, 0.1, 10 cm, and 1 K, respectively. The magnitude of the sub-grid topographic effects is dependent on seasons and elevations and is also sensitive to the spatial scales. Although the sub-grid topographic effects on solar radiation are larger with more spatial details at finer spatial scales, they cannot be simply neglected at coarse spatial scales. When compared to MODIS data, incorporating the sub-grid topographic effects overall reduces the biases of ELM in simulating surface energy balance, snow cover, and surface temperature, especially in the high-elevation and snow-covered regions over the TP. The inclusion of sub-grid topographic effects on solar radiation parameterization in ELM will contribute to advancing our understanding of the role of the surface topography on terrestrial processes over complex terrain.