Assessing the assimilation of Himawari-8 observations on aerosol forecasts and radiative effects during pollution transport from South Asia to the Tibetan Plateau

Abstract

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 the 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 model coupled with Chemistry (WRF-Chem) to depict one SA air pollution outbreak event in spring 2018. Sensitivity tests for the assimilation system were conducted first 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 a 12 h window, which are both better than assimilating the hourly observations in the current assimilation time slot. 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 AOT assimilation with 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.