skip to main content

SciTech ConnectSciTech Connect

Title: How do A-train Sensors Intercompare in the Retrieval of Above-Cloud Aerosol Optical Depth? A Case Study-based Assessment

We inter-compare the above-cloud aerosol optical depth (ACAOD) of biomass burning plumes retrieved from different A-train sensors, i.e., MODIS, CALIOP, POLDER, and OMI. These sensors have shown independent capabilities to detect and retrieve aerosol loading above marine boundary layer clouds--a kind of situation often found over the Southeast Atlantic Ocean during dry burning season. A systematic one-to-one comparison reveals that, in general, all passive sensors and CALIOP-based research methods derive comparable ACAOD with differences mostly within 0.2 over homogeneous cloud fields. The 532-nm ACAOD retrieved by CALIOP operational algorithm is largely underestimated; however, it’s 1064-nm AOD when converted to 500 nm shows closer agreement to the passive sensors. Given the different types of sensor measurements processed with different algorithms, the close agreement between them is encouraging. Due to lack of adequate direct measurements above cloud, the validation of satellite-based ACAOD retrievals remains an open challenge. The inter-satellite comparison, however, can be useful for the relative evaluation and consistency check.
 [1] ;  [2] ;  [3] ;  [4] ;  [5]
  1. Universities Space Research Association, Columbia, MD (United States); NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States)
  2. NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States)
  3. Univ of Lille (France)
  4. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  5. NASA Langley Research Center, Hampton, VA (United States)
Publication Date:
OSTI Identifier:
Report Number(s):
Journal ID: ISSN 0094-8276
DOE Contract Number:
Resource Type:
Journal Article
Resource Relation:
Journal Name: Geophysical Research Letters; Journal Volume: 41; Journal Issue: 1
American Geophysical Union
Research Org:
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Sponsoring Org:
Country of Publication:
United States
54 ENVIRONMENTAL SCIENCES a-train sensors; above-cloud; aerosol optical depth