CERES MODIS Cloud Product Retrievals for Edition 4--Part I: Algorithm Changes
- Science Systems and Applications, Inc., Hampton, VA (United States)
- NASA Langley Research Center, Hampton, VA (United States)
- National Oceanic and Atmospheric Administration (NOAA), Madison, CO (United States)
- Lanzhou Univ. (China.)
- NASA Goddard Inst. for Space Studies (GISS), New York, NY (United States)
- Texas A & M Univ., College Station, TX (United States)
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
The Edition 2 (Ed2) cloud property retrieval algorithm system was upgraded and applied to the MODerate-resolution Imaging Spectroradiometer (MODIS) data for the Clouds and the Earth's Radiant Energy System (CERES) Edition 4 (Ed4) products. New calibrations for solar channels and the use of the 1.24-μm channel for cloud optical depth (COD) over snow improve the daytime consistency between Terra and Aqua MODIS retrievals. Use of additional spectral channels and revised logic enhanced the cloud-top phase retrieval accuracy. A new ice crystal reflectance model and a CO₂-channel algorithm retrieved higher ice clouds, while a new regional lapse rate technique produced more accurate water cloud heights than in Ed2. Ice cloud base heights are more accurate due to a new cloud thickness parameterization. Overall, CODs increased, especially over the polar (PO) regions. The mean particle sizes increased slightly for water clouds, but more so for ice clouds in the PO areas. New experimental parameters introduced in Ed4 are limited in utility, but will be revised for the next CERES edition. As part of the Ed4 retrieval evaluation, the average properties are compared with those from other algorithms and the differences between individual reference data and matched Ed4 retrievals are explored. Part II of this article provides a comprehensive, objective evaluation of selected parameters. More accurate interpretation of the CERES radiation measurements has resulted from the use of the Ed4 cloud properties.
- Research Organization:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Brookhaven National Lab. (BNL), Upton, NY (United States); Argonne National Lab. (ANL), Argonne, IL (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- Contributing Organization:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States); Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Brookhaven National Laboratory (BNL), Upton, NY (United States); Argonne National Laboratory (ANL), Argonne, IL (United States)
- Grant/Contract Number:
- AC05-76RL01830
- OSTI ID:
- 1706723
- Journal Information:
- IEEE Transactions on Geoscience and Remote Sensing, Vol. IEEE Transactions on Geoscience and Remote Sensing, Issue IEEE Transactions on Geoscience and Remote Sensing; ISSN 0196-2892
- Publisher:
- IEEECopyright Statement
- Country of Publication:
- United States
- Language:
- English
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