Multi-sensor data assimilation of aerosol optical depth

As a result of increasing attention paid to aerosols in climate studies, numerous global satellite aerosol products have been generated. There exists, however, an outstanding problem that these satellite products have substantial discrepancies, that must be lowered substantially for narrowing the range of the estimates of aerosol´s climate effects. In this paper, three different data assimilation methods were used to produce consistent aerosol optical depth (AOD) with four different derived AOD products. The results illustrate that the data assimilation method can produce comprehensive AOD fields with reasonably good data values and acceptable errors. Through comparing, the Kalman filter method is more preferable to the optimal interpolation and three-dimensional variation method.