Abstract
A least squares regression method is formulated for obtaining global temperature and geopotential height profiles from satellite radiation measurements, particularly those obtained by the Sate1lite Infra-Red Spectrometer (SIRS) aboard the Nimbus 3 satellite launched Apr. 14, 1969. Regression equations relating temperature and geopotential height to spectral radiance observations are derived. A method accounting for the influence of clouds, mountains, and hot terrain on the solutions is described. Results obtained from Nimbus 3 radiance data are presented. The procedure described herein has been successfully applied to Nimbus 3 SIRS observations on a real-time basis. The temperature and geopotential heights obtained are being used operationally by the National Meteorological Center in their objective constant pressure analyses. Numerous meteorological results are given to demonstrate the usefulness of this new sounding tool. Abstract A least squares regression method is formulated for obtaining global temperature and geopotential height profiles from satellite radiation measurements, particularly those obtained by the Sate1lite Infra-Red Spectrometer (SIRS) aboard the Nimbus 3 satellite launched Apr. 14, 1969. Regression equations relating temperature and geopotential height to spectral radiance observations are derived. A method accounting for the influence of clouds, mountains, and hot terrain on the solutions is described. Results obtained from Nimbus 3 radiance data are presented. The procedure described herein has been successfully applied to Nimbus 3 SIRS observations on a real-time basis. The temperature and geopotential heights obtained are being used operationally by the National Meteorological Center in their objective constant pressure analyses. Numerous meteorological results are given to demonstrate the usefulness of this new sounding tool.

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