Paper
8 December 1999 Self-validation of radiance measurements from the CERES (TRMM) instrument
Author Affiliations +
Abstract
Eight continuous months of earth-nadir-viewing radiance measurements from the 3-channel Tropical Rainfall Measuring Mission (TRMM), Clouds and the Earth's Radiant Energy System (CERES) scanning radiometric measurement instrument, have been analyzed. While previous remote sensing satellites, such as the Earth Radiation Budget Experiment (ERBE) covered all subsets of the broadband radiance spectrum (total, longwave and shortwave). CERES has two subset channels (window and shortwave) which do not give continuous frequency coverage over the total band. Previous experience with ERBE indicated the need for us to model the 'equivalent' daytime longwave radiance using a window channel regression, which will allow us to validate the performance of the instrument using a three-channel inter-comparison. Limiting our consideration to the fixed azimuth plane, cross-track, scanning mode (FAPS), each nadir-viewing measurement was averaged into three subjective categories called daytime, nighttime, and twilight. Daytime was defined as any measurement taken when the solar zenith angle (SZA) was less than 90 degrees; nighttime was taken to be any measurement where the SZA was greater than 117 degrees; and twilight was everything else. Our analysis indicates that there are only two distinct categories of nadir-view data; daytime, and non-daytime (i.e., the union of the nighttime and twilight sets); and that the CERES longwave radiance is predictable to an accuracy of 1%, based on the SZA, and window channel measurements.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jack Paden, Dhirendra K. Pandey, Robert Benjamin Lee III, and Kory J. Priestley "Self-validation of radiance measurements from the CERES (TRMM) instrument", Proc. SPIE 3867, Satellite Remote Sensing of Clouds and the Atmosphere IV, (8 December 1999); https://doi.org/10.1117/12.373053
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KEYWORDS
Shortwaves

Satellites

Remote sensing

Sensors

Statistical analysis

Clouds

Data acquisition

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