Skip all navigation and jump to content Jump to site navigation
About MODIS News Data Tools /images2 Science Team Science Team Science Team

   + Home
MODIS Publications Link
MODIS Presentations Link
MODIS Biographies Link
MODIS Science Team Meetings Link



Yu, HB; Zhang, Y; Chin, M; Liu, ZY; Omar, A; Remer, LA; Yang, YK; Yuan, TL; Zhang, JL (2012). An integrated analysis of aerosol above clouds from A-Train multi-sensor measurements. REMOTE SENSING OF ENVIRONMENT, 121, 125-131.

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 (AOD(532)) from CALIPSO lidar, the UV aerosol index (AI) from OMI, and cloud fraction and cloud optical depth (COD) from MOD'S. 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 AOD(532)/AI ratio decreases with increasing COD. The dependence of AOD(532)/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 10 be further explored in the future. (c) 2012 Elsevier Inc. All rights reserved.



NASA Home Page Goddard Space Flight Center Home Page