Skip all navigation and jump to content Jump to site navigation
NASA Logo - Goddard Space Flight Center

+ NASA Homepage

    
Goddard Space Flight Center
About MODIS News Data /images2 Science Team Science Team Science Team

   + Home
ABOUT MODIS
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.

Abstract
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.

DOI:
0034-4257

ISSN:
10.1016/j.rse.2012.01.011

FirstGov logo Privacy Policy and Important Notices NASA logo

Curator: Brandon Maccherone
NASA Official: Shannell Frazier

NASA Home Page Goddard Space Flight Center Home Page