Assimilation of Megha-Tropiques SAPHIR Observations in the NOAA Global Model

Erin E. Jones Riverside Technology, Inc., and NOAA/NESDIS/STAR, College Park, Maryland

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Kevin Garrett Riverside Technology, Inc., and NOAA/NESDIS/STAR, College Park, Maryland

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Sid-Ahmed Boukabara NOAA/NESDIS/STAR, College Park, Maryland

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Abstract

The National Oceanic and Atmospheric Administration (NOAA) Global Data Assimilation System/Global Forecast System (GDAS/GFS) was extended to assimilate brightness temperatures from the Sondeur Atmosphérique du Profil d’Humidité Intertropicale par Radiométrie (SAPHIR) passive microwave water vapor sounder on board the Megha-Tropiques satellite. Quality control procedures were developed to assess the SAPHIR data quality for assimilating clear-sky observations over ocean surfaces, and to characterize observation biases and errors. A 6-week impact experiment was performed using the GDAS/GFS data assimilation system. The addition of SAPHIR observations on top of the current global observing system improved analysis and forecast humidity root-mean-square error (RMSE) results at the upper levels of the troposphere by about 6%, mostly at 100 hPa, when verified against European Centre for Medium-Range Weather Forecasts (ECMWF) analysis, though some degradation to the forecast humidity was seen at 150–200 hPa. The forecast impacts were predominant at earlier lead times between 24 and 96 h. Verification using global radiosonde observations also showed a reduction of the humidity RMSE from 4% to 6% between 500 hPa and the surface when assimilating SAPHIR, while temperature and wind speed RMSEs were reduced by up to 9% and 7% near the tropical tropopause, respectively. Other conventional forecast skill parameters including the 500-hPa geopotential height anomaly correlation showed neutral impact when assimilating SAPHIR.

For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Erin E. Jones, erin.jones@noaa.gov

Abstract

The National Oceanic and Atmospheric Administration (NOAA) Global Data Assimilation System/Global Forecast System (GDAS/GFS) was extended to assimilate brightness temperatures from the Sondeur Atmosphérique du Profil d’Humidité Intertropicale par Radiométrie (SAPHIR) passive microwave water vapor sounder on board the Megha-Tropiques satellite. Quality control procedures were developed to assess the SAPHIR data quality for assimilating clear-sky observations over ocean surfaces, and to characterize observation biases and errors. A 6-week impact experiment was performed using the GDAS/GFS data assimilation system. The addition of SAPHIR observations on top of the current global observing system improved analysis and forecast humidity root-mean-square error (RMSE) results at the upper levels of the troposphere by about 6%, mostly at 100 hPa, when verified against European Centre for Medium-Range Weather Forecasts (ECMWF) analysis, though some degradation to the forecast humidity was seen at 150–200 hPa. The forecast impacts were predominant at earlier lead times between 24 and 96 h. Verification using global radiosonde observations also showed a reduction of the humidity RMSE from 4% to 6% between 500 hPa and the surface when assimilating SAPHIR, while temperature and wind speed RMSEs were reduced by up to 9% and 7% near the tropical tropopause, respectively. Other conventional forecast skill parameters including the 500-hPa geopotential height anomaly correlation showed neutral impact when assimilating SAPHIR.

For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Erin E. Jones, erin.jones@noaa.gov
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