Paper
1 September 1990 Angular dependence models for radiance to flux conversion
Richard N. Green, John T. Suttles, Bruce A. Wielicki
Author Affiliations +
Abstract
Scanning radiometers aboard satellites have been employed for over a decade to measure the Earth radiation budget. The measured radiance is converted to flux at the top of the atmosphere by applying angular dependence models (ADM''s) that are a function of the viewing geometry and the scene type. This paper examines the significance of the number of ADM''s used a measure of the effectiveness of the ADM''s and the implications of requiring the ADM''s to satisfy reciprocity. The overall significance of the ADM''s is determined by analyzing the same satellite data with a single Lambertian model a single mean model and the 12 Earth Radiation Budget Experiment (ERBE)1 ADM''s. The ERBE ADM''s will undergo reexamination and possible improvement before they are applied to the future Clouds and the Earth''s Radiant Energy System (CERES) radiation measurements. To measure the improvement of the models we develop a test of " goodness" for the models which includes normality reciprocity and uniformity of flux estimates determined from different viewing geometries. Alongtrack scan data are used for this test of the ADM''s. We discuss the task of constraining the standard ERBE ADM''s to satisfy the reciprocity condition. Earth Radiation Budget Satellite (ERBS) data are used to demonstrate the effect of these modified models. 1. FORMULATION OF ADM''S The radiance L at a point in Wm2sr1 is given by L (1) where M is the flux in
© (1990) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Richard N. Green, John T. Suttles, and Bruce A. Wielicki "Angular dependence models for radiance to flux conversion", Proc. SPIE 1299, Long-Term Monitoring of the Earth's Radiation Budget, (1 September 1990); https://doi.org/10.1117/12.21369
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Scanners

Clouds

Data modeling

Satellites

Shortwaves

Atmospheric modeling

Anisotropy

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