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CERES Edition-2 cloud property retrievals using TRMM VIRS and Terra and Aqua...

Minnis, P., S. Sun-Mack, D. Young, P. W. Heck, D. P. Garber, Y. Chen, D. Spangenberg, R. F. Arduini, Q. Z. Trepte, W. Smith, K. Ayers, S. C. Gibson, W. F. Miller, V. Chakrapani, Y. Takano, K. Liou, Y. Xie, and P. Yang (2011), CERES Edition-2 cloud property retrievals using TRMM VIRS and Terra and Aqua MODIS data, Part I: Algorithms, IEEE Trans. Geosci. Remote Sens., 49, 11-2892).

The NASA Clouds and Earth’s Radiant Energy System (CERES) Project is designed to improve our understanding of the relationship between clouds and solar and longwave radiation. This is achieved using satellite broadband instruments to map the top-of-atmosphere radiation fields with coincident data from satellite narrowband imagers employed to retrieve the properties of clouds associated with those fields. This paper documents the CERES Edition-2 cloud property retrieval system used to analyze data from the Tropical Rainfall Measuring Mission (TRMM) Visible Infrared Scanner (VIRS) and by the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments onboard the Terra and Aqua satellites covering the period 1998 through 2007. Two daytime retrieval methods are explained: the Visible Infrared Solar-infrared Split-Window Technique (VISST) for snow-free surfaces, and the Shortwave-infrared Infrared Near-infrared Technique (SINT) for snow or ice-covered surfaces. The Shortwave-infrared Infrared Split-window Technique (SIST) is used for all surfaces at night. These methods, along with ancillary data and empirical parameterizations of cloud thickness, are used to derive cloud boundaries, phase, optical depth, effective particle size, and condensed/frozen water path at both pixel and CERES footprint levels. Additional information is presented detailing the potential effects of satellite calibration differences, highlighting methods to compensate for spectral differences and correct for atmospheric absorption and emissivity, and discussing known errors in the code. Because a consistent set of algorithms, auxiliary input, and calibrations across platforms are used, instrument and algorithm-induced changes in the data record are minimized. This facilitates the use of the CERES data products for studying climate-scale trends.

Research Program: 
Modeling Analysis and Prediction Program (MAP)
Radiation Science Program (RSP)