CERES Edition-2 Cloud Property Retrievals Using TRMM VIRS and Terra and Aqua MODIS Data—Part I: Algorithms

TLDR

The CERES Project was created to deepen knowledge of how clouds interact with solar and longwave radiation. This paper documents the CERES Edition‑2 cloud property retrieval system applied to TRMM VIRS and MODIS data from 1998 to 2007. The system combines broadband TOA radiation mapping with narrow‑band imager retrievals, using daytime VISIR SWIR split‑window for snow‑free surfaces, SWIR NIR for snow/ice, and SWIR split‑window at night, together with ancillary data and empirical cloud‑thickness parameterizations to derive cloud boundaries, phase, optical depth, effective particle size, and water path at pixel and footprint levels. The authors describe calibration‑difference impacts, correction methods, and known code errors, showing that consistent algorithms across platforms reduce instrument‑induced variability and enable reliable climate‑scale trend analyses.

Abstract

The National Aeronautics and Space Administration's Clouds and the Earth's Radiant Energy System (CERES) Project was designed to improve our understanding of the relationship between clouds and solar and longwave radiation. This is achieved using satellite broad-band instruments to map the top-of-atmosphere radiation fields with coincident data from satellite narrow-band 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 Visible and Infrared Scanner and by the MODerate-resolution Imaging Spectrometer instruments on board the Terra and Aqua satellites covering the period 1998 through 2007. Two daytime retrieval methods are explained: the Visible Infrared Shortwave-infrared Split-window Technique for snow-free surfaces and the Shortwave-infrared Infrared Near-infrared Technique for snow or ice-covered surfaces. The Shortwave-infrared Infrared Split-window Technique is used for all surfaces at night. These methods, along with the 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.