Estimation of atmospheric aerosol volume concentration over the East European region by optimal interpolation of AERONET observations

Abstract

Aerosols are an important component in the Earth's atmosphere. They cause atmospheric pollution which influence negatively on human health and affect the radiation balance of the atmosphere, resulting in climate change. Aerosol distribution in the Earth's atmosphere is studied using measurements from many satellite and ground-based instruments. One of the valuable sources of atmospheric aerosol data is measurements by a ground-based network of sun and sky radiometers AERONET. The AERONET retrieval algorithm provides aerosol volume concentration. However, AERONET observations are sparse in space and time. To obtain information on aerosol volume concentrations with complete spatial and temporal coverage, model simulations can be applied. However, the agreement between model results and measurements is not good enough. To obtain the most likely true estimate on aerosol volume concentration, the optimal interpolation method is used in the present work. This approach is much less computationally expensive than other data assimilation methods. The method of optimal interpolation is based on the minimization of the mean-square error in the estimate. In the present work, the technique is used that combines observational data, statistical mean values, and results of the global chemical transport model GEOS-Chem simulation. Implementation of the optimal interpolation method makes it possible to estimate the values of the aerosol volume concentration when measurements are absent. The estimates of aerosol daily mean volume concentrations at all spatial grid points (2 x 2.5 degrees) over the East European region are determined in the present work.