Scholarly Communications Project

A Study of Earth Radiation Budget Radiometric Channel Performance and Data Interpretation Protocols


Martial P. A. Haeffelin

Dissertation submitted to the Faculty of the Virginia Polytechnic Institute and State University in partial fulfillment of the requirements for the degree of

Doctor of Philosophy


J. R. Mahan, Chair
G. Brogniez
R. S. Kandel
M. Legrand
E. P. Scott
H. F. VanLandingham

August 27, 1996
Blacksburg, Virginia


Two aspects of the study of the Earth radiation budget and the effects of clouds on our climate system are considered in this dissertation: instrumentation and data interpretation. Numerical models have been developed to characterize the optical/thermal-radiative behavior, the dynamic electrothermal response and the structural thermal transients of radiometric channels. These models, applied to a satellite-borne scanning radiometer, are used to determine the instrument point spread function and the potential for optical and thermal-radiative contamination of the signal due to out-of-field radiation and emission from the radiometer structure. The capabilities of the model are demonstrated by scanning realistic Earth scenes. In addition, the optical/thermal-radiative model is used for the development of an infrared field radiometer to interpret results from the experimental characterization of the instrument. The model allowed the sensitivity of the instrument response to assembly uncertainties to be determined. Data processing consists of converting radiometric data into estimates of the flux at the top of the atmosphere. Primary error sources are associated with the procedures used to compensate for unsampled data. The time interpolation algorithm applied to a limited number of observations can produce significantly biased estimates of monthly mean fluxes. A diurnal interpolation protocol using correlative ISCCP cloudiness data is developed to compensate for sparse temporal sampling of Earth radiation budget data. The bias is shown to be significantly reduced in regions where the variability of the cloud cover is well accounted for by ISCCP data.

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