Observationally-constrained estimates of aerosol optical depths (AODs) over East Asia via data assimilation techniques

Abstract:

Not only aerosol’s direct effect on climate by scattering and absorbing the incident solar radiation, but also they indirectly perturbs the radiation budget by influencing microphysics and dynamics of clouds. Aerosols also have a significant adverse impact on human health. With an importance of aerosols in climate, considerable research efforts have been made to quantify the amount of aerosols in the form of the aerosol optical depth (AOD). AOD is provided with ground-based aerosol networks such as the Aerosol Robotic NETwork (AERONET), and is derived from satellite measurements. However, these observational datasets have a limited areal and temporal coverage. To compensate for the data gaps, there have been several studies to provide AOD without data gaps by assimilating observational data and model outputs. In this study, AODs over East Asia simulated with the Community Multi-scale Air Quality (CMAQ) model and derived from the Geostationary Ocean Color Imager (GOCI) observation are interpolated via different data assimilation (DA) techniques such as Cressman’s method, Optimal Interpolation (OI), and Kriging for the period of the Distributed Regional Aerosol Gridded Observation Networks (DRAGON) Campaign (March – May 2012). Here, the interpolated results using the three DA techniques are validated intensively by comparing with AERONET AODs to examine the optimal DA method providing the most reliable AODs over East Asia.