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Assimilating GOES Brightness Temperatures. Part II: Assigning Water Vapor Wind Heights Directly from Weighting Functions

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  • a Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin—Madison, Madison, Wisconsin
  • | b Office of Research and Applications, NOAA/NESDIS, Madison, Wisconsin
  • | c Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin—Madison, Madison, Wisconsin
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Abstract

An unsolved problem with water vapor wind estimates from the upper-tropospheric 6.7-μm water vapor band on the Geostationary Operational Environmental Satellite (GOES) Imager (channel 3) is its exact placement in the vertical column. Satellite water vapor observations are known to be depth-averaged assessments of the upper-tropospheric moisture. Details about the effective averaging of upper-tropospheric observations, valid for GOES or those of other satellite platforms, are not retrieved as part of the observation. However, details about the vertical placement can be accurately estimated from forward radiative models that mimic the instrument spectral characteristics. A new method has been developed to assimilate satellite radiances or brightness temperatures directly into a numerical forecast model. A by-product of the new scheme is knowledge of the weighting functions that describe the assignment value given to each vertical layer. As a consequence, given water vapor wind data, these weighting functions allow the guessed wind field to be “intelligently” modified. In this study the vertical and horizontal characteristics of these weighting functions are examined. Statistics for a 16-day period are presented that show how weighted average wind components from the initial model forecast fields, computed using the weighting functions, compare with GOES water vapor wind observations.

Corresponding author address: Gary S. Wade, Office of Research and Applications, NOAA/NESDIS, 1225 West Dayton St., Madison, WI 53706. gary.s.wade@noaa.gov

Abstract

An unsolved problem with water vapor wind estimates from the upper-tropospheric 6.7-μm water vapor band on the Geostationary Operational Environmental Satellite (GOES) Imager (channel 3) is its exact placement in the vertical column. Satellite water vapor observations are known to be depth-averaged assessments of the upper-tropospheric moisture. Details about the effective averaging of upper-tropospheric observations, valid for GOES or those of other satellite platforms, are not retrieved as part of the observation. However, details about the vertical placement can be accurately estimated from forward radiative models that mimic the instrument spectral characteristics. A new method has been developed to assimilate satellite radiances or brightness temperatures directly into a numerical forecast model. A by-product of the new scheme is knowledge of the weighting functions that describe the assignment value given to each vertical layer. As a consequence, given water vapor wind data, these weighting functions allow the guessed wind field to be “intelligently” modified. In this study the vertical and horizontal characteristics of these weighting functions are examined. Statistics for a 16-day period are presented that show how weighted average wind components from the initial model forecast fields, computed using the weighting functions, compare with GOES water vapor wind observations.

Corresponding author address: Gary S. Wade, Office of Research and Applications, NOAA/NESDIS, 1225 West Dayton St., Madison, WI 53706. gary.s.wade@noaa.gov

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