An integrated analysis of aerosol above clouds from A-Train multi-sensor measurements

Quantifying above-cloud aerosol can help improve the assessment of aerosol intercontinental transport and climate impacts. In this study we conduct an integrated analysis of aerosols above clouds by using multi-sensor A-Train measurements, including above-cloud aerosol optical depth at 532 nm (AOD532) from CALIPSO lidar, the UV aerosol index (AI) from OMI, and cloud fraction and cloud optical depth (COD) from MODIS. The analysis of Saharan dust outflow and Southwest African smoke outflow regions shows that the above-cloud AOD correlates positively with AI in an approximately linear manner, and that the AOD532/AI ratio decreases with increasing COD. The dependence of AOD532/AI ratio on COD doesn't depend on aerosol type when potential biases in the CALIOP AOD measurements are empirically accounted for. Our results may suggest the potential of combining OMI AI and MODIS cloud measurements to empirically derive above-cloud AOD with a spatial coverage much more extensive than CALIPSO measurements, which needs to be further explored in the future.

► CALIPSO above-cloud AOD532 correlates linearly with OMI aerosol index (AI). ► AOD532/AI ratio decreases with increasing cloud optical depth (COD). ► The COD-dependence of AOD532/AI ratio doesn't depend much on aerosol type. ► Above-cloud AOD with extensive coverage may be derived from A-Train measurements.