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Retrieval of Atmospheric Temperature Profiles from Satellite Measurements for Dynamical Forecasting

W. L. SmithNational Environmental Satellite Service, NOAA, Hillcrest Heights, Md.

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H. M. WoolfNational Environmental Satellite Service, NOAA, Hillcrest Heights, Md.

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H. E. FlemingNational Environmental Satellite Service, NOAA, Hillcrest Heights, Md.

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Abstract

The method of real-time retrieval of atmospheric temperature profiles from Nimbus IV Satellite Infrared Spectrometer observations currently used in dynamical weather analysis-forecast operation is described. Each vertical temperature profile is determined by its deviation from a “guess” profile. The deviation is expressed as a linear combination of differences between the measured radiances and those computed from the guess profile. The coefficients are estimated, by matrix inversion, from the weighting functions (i.e., derivatives of atmospheric transmittance functions), which are regularized by the ratio of the expected variance of the measurement errors to the expected variance of the errors in the guess profile. The deviations are iterated until the variance of the radiance residuals is less than the expected variance of the measurement errors.

For weather analysis-forecast operation the dynamical forecast is used as the first guess; therefore, the calculated profiles should differ from the forecast profiles only when the measurable error in the forecast exceeds the instrumental noise level. The retrieved profiles are those which deviate least from the forecast in order to satisfy all the radiance observations. This property is well suited to dynamical forecasting in that it does not tend to produce erroneous atmospheric waves.

Abstract

The method of real-time retrieval of atmospheric temperature profiles from Nimbus IV Satellite Infrared Spectrometer observations currently used in dynamical weather analysis-forecast operation is described. Each vertical temperature profile is determined by its deviation from a “guess” profile. The deviation is expressed as a linear combination of differences between the measured radiances and those computed from the guess profile. The coefficients are estimated, by matrix inversion, from the weighting functions (i.e., derivatives of atmospheric transmittance functions), which are regularized by the ratio of the expected variance of the measurement errors to the expected variance of the errors in the guess profile. The deviations are iterated until the variance of the radiance residuals is less than the expected variance of the measurement errors.

For weather analysis-forecast operation the dynamical forecast is used as the first guess; therefore, the calculated profiles should differ from the forecast profiles only when the measurable error in the forecast exceeds the instrumental noise level. The retrieved profiles are those which deviate least from the forecast in order to satisfy all the radiance observations. This property is well suited to dynamical forecasting in that it does not tend to produce erroneous atmospheric waves.

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