Atmospheric aerosols are known to exert a cooling effect (negative radiative forcing) on the climate. This assessment relies on aerosol observations in the cloud-free part of the atmosphere. Satellite observations have shown the presence of aerosols, particularly absorbing type such as carbonaceous aerosols and mineral dust, over low-lying cloud decks over several regions of the world. This kind of aerosol/cloud overlap situation is likely to result in atmospheric heating whose magnitude depends on the aerosol optical thickness (AOT), single-scattering albedo, cloud optical thickness (COT), and cloud fraction. Unless the aerosol loading above cloud is quantified and taken in to account, the assessment of all-sky radiative effects of aerosols and cloud will remain incomplete.
The interest in this aspect of aerosol research has grown significantly in the recent years. Particularly, development of the satellite-based retrieval techniques and its application to the case studies look promising. We have developed a ‘color ratio’ based technique to retrieve the AOT above cloud and underlying COT, simultaneously, from the OMI and MODIS observations. The application of the present algorithm to the land and ocean case studies will be demonstrated in this talk. The absorption effect above cloud also produces bias in the cloud retrieval, if aerosols are not accounted in the inversion such as the case with the MODIS standard cloud algorithm (MOD06). We have developed an empirical approach which is driven by the radiative transfer calculations to correct the COT retrieval using combined OMI (UVAI) and MODOS (COT) observations. This approach does not require explicit above-cloud aerosol retrieval; instead it takes advantage of the existing products to estimate the uncertainty in cloud retrieval.
A direct validation of satellite AOT above cloud is a difficult task primarily due to lack of ample sub-orbital measurements of aerosols above cloud. However, a comparative analysis on the inter-satellite AOT above cloud can be performed for the sack of consistency check. I will present the results of inter-satellite comparison of above-cloud AOT of biomass burning plumes observed from different A-train sensors, i.e., MODIS, CALIOP, POLDER, and OMI.