Understanding the source of atmospheric aerosol is an essential step in determining the aerosol radiative effect over the Tibetan Plateau (TP). This study aims to clarify the contributions of anthropogenic and natural emission to the aerosols (carbonaceous and sulphate) characteristics inside the TP. An aerosol model named Spectral Radiation Transport Model for Aerosol Species (SPRINTARS) recently coupled to the climate model named Chinese Academy of Sciences Flexible Global Ocean Atmosphere Land System (CAS‐FGOALS‐f3‐L) is used to simulate meteorological conditions and aerosols from 1985 to 2013, given emissions from the sixth phase of the Coupled Models Intercomparison Project (CMIP6). Comparisons between the simulations and ERA5 reanalysis data present that the model can capture the key spatial and temporal features of meteorological elements (2‐m temperature, relative humidity, and wind field at 500 hPa) over the Asia. Subsequently, we conduct six sensitivity studies to quantify the contributions of sources to aerosol surface concentration, burden and aerosol optical depth (AOD) over the TP. Our results illustrate that the outside and local anthropogenic sources contribute about 75.2% (78.9% in summer and 66.6% in winter) and 13.5% (7.4% in summer and 24.0% in winter) to the annual mean aerosols surface concentrations over the TP. The outside anthropogenic sources contribute to AODs in TP up to 87.3% (93.9% in autumn and 80.6% in winter). The ascending air over the TP is conducive to the transportation of the outsource pollutions to the TP. The outside natural sources (refer to biomass burning sources) contribute about 10% to aerosols over TP, and the inside natural sources play minor roles. The black carbon, organic carbon and sulphate (BOCS) induce average radiative forcing of −0.7 W m−2 at the near surface over the TP.

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Abstract. The emissions from South Asia (SA) represent a critical source of aerosols on the Tibetan Plateau (TP), and aerosols can significantly reduce the surface solar energy. To enhance the precision of aerosol forecasting and its radiative effects in SA and TP, we employed a four-dimensional local ensemble transform Kalman filter (4D-LETKF) aerosol data assimilation (DA) system. This system was utilized to assimilate Himawari-8 aerosol optical thickness (AOT) into the Weather Research and Forecasting-Chemistry (WRF-Chem) model to depict one SA air pollution outbreak event in spring 2018. Sensitivity tests for the assimilation system have been conducted firstly to tune temporal localization lengths. Comparisons with independent Moderate Resolution Imaging Spectroradiometer (MODIS) and AErosol RObotic NETwork (AERONET) observations demonstrate that the AOT analysis and forecast fields have more reasonable diurnal variations by assimilating all the observations within 12 h window, which are both better than assimilating the hourly observations in the current assimilation timeslot. Assimilation of the entire window of observations with aerosol radiative effect activation significantly improves the prediction of downward solar radiation compared to the free-run experiment. The assimilation of aerosol radiative effect activation led to a reduction in aerosol concentrations over SA, resulting in increased surface radiation, temperature, boundary layer height, and atmospheric instability. These changes facilitated air uplift, promoting aerosol transport from SA to the southeastern TP and leading to an increase in AOT in this region.