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Efficiency of the Satellite Retrieval of Mean Virtual Temperatures as a Function of Layer Thickness

Henry E. FlemingSatellite Research Laboratory, NOAA/NESDIS, Washington, DC

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David S. CrosbySatellite Research Laboratory, NOAA/NESDIS, Washington, DC

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Mitchell D. GoldbergST Systems Corporation (STX), Lanham, Maryland

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Abstract

Layer-mean virtual temperatures retrieved from satellite measurements are more accurate than retrievals at specific pressure not only because an averaging process is involved, but also because of advantages in the retrieval process. In this note, a “retrieval efficiency” is derived to express this advantage over simple averaging as a function of layer thickness. The efficiency is examined for two common cases of retrieval initial guess: a statistical sample mean and a forecast profile obtained from a numerical prediction model. The advantage of the layer-mean retrieval clearly is demonstrated in both cases.

Abstract

Layer-mean virtual temperatures retrieved from satellite measurements are more accurate than retrievals at specific pressure not only because an averaging process is involved, but also because of advantages in the retrieval process. In this note, a “retrieval efficiency” is derived to express this advantage over simple averaging as a function of layer thickness. The efficiency is examined for two common cases of retrieval initial guess: a statistical sample mean and a forecast profile obtained from a numerical prediction model. The advantage of the layer-mean retrieval clearly is demonstrated in both cases.

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