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Using OSSEs to Evaluate the Impacts of Geostationary Infrared Sounders

Erica L. McGrath-SpangleraMorgan State University, Baltimore, Maryland
bNASA Global Modeling and Assimilation Office, Greenbelt, Maryland

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Will McCartycNASA Headquarters, Washington, D.C.

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N. C. PrivéaMorgan State University, Baltimore, Maryland
bNASA Global Modeling and Assimilation Office, Greenbelt, Maryland

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Isaac MoradibNASA Global Modeling and Assimilation Office, Greenbelt, Maryland
dEarth System Science Interdisciplinary Center, University of Maryland, College Park, College Park, Maryland

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Bryan M. KarpowiczbNASA Global Modeling and Assimilation Office, Greenbelt, Maryland
eUniversity of Maryland, Baltimore County, Baltimore, Maryland

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Joel McCorkelfNASA Goddard Space Flight Center, Greenbelt, Maryland

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Abstract

An observing system simulation experiment (OSSE) was performed to assess the impact of assimilating hyperspectral infrared (IR) radiances from geostationary orbit on numerical weather prediction, with a focus on the proposed sounder on board the Geostationary Extended Observations (GeoXO) program’s central satellite. Infrared sounders on a geostationary platform would fill several gaps left by IR sounders on polar-orbiting satellites, and the increased temporal resolution would allow the observation of weather phenomena evolution. The framework for this OSSE was the Global Modeling and Assimilation Office (GMAO) OSSE system, which includes a full suite of meteorological observations. The experiment additionally assimilated four identical IR sounders from geostationary orbit to create a “ring” of vertical profiling observations. Based on the experimentation, assimilation of the IR sounders provided a beneficial impact on the analyzed mass and wind fields, particularly in the tropics, and produced an error reduction in the initial 24–48 h of the subsequent forecasts. Specific attention was paid to the impact of the GeoXO Sounder (GXS) over the contiguous United States (CONUS) as this is a region that is well-observed and as such difficult to improve. The forecast sensitivity to observation impact (FSOI) metric, computed across all four synoptic times over the CONUS, reveals that the GXS had the largest impact on the 24-h forecast error of the assimilated hyperspectral infrared satellite radiances as measured using a moist energy error norm. Based on this analysis, the proposed GXS has the potential to improve numerical weather prediction globally and over the CONUS.

Significance Statement

The purpose of this study is to understand the impact of the proposed geostationary hyperspectral infrared sounder as part of the Geostationary Extended Observations (GeoXO) program on numerical weather prediction. The evaluation was done using a simulated environment, and showed a beneficial impact on the tropical mass and wind fields and an error reduction in the initial 24–48 h forecasts. Over the contiguous United States, the GeoXO Sounder (GXS) performed well and had the largest impact of the assimilated infrared satellite radiances on the 24 h forecast as measured by a moist energy error norm. Based on the results of this study, the proposed GXS has the potential to improve numerical weather prediction.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Erica L. McGrath-Spangler, erica.l.mcgrath-spangler@nasa.gov

Abstract

An observing system simulation experiment (OSSE) was performed to assess the impact of assimilating hyperspectral infrared (IR) radiances from geostationary orbit on numerical weather prediction, with a focus on the proposed sounder on board the Geostationary Extended Observations (GeoXO) program’s central satellite. Infrared sounders on a geostationary platform would fill several gaps left by IR sounders on polar-orbiting satellites, and the increased temporal resolution would allow the observation of weather phenomena evolution. The framework for this OSSE was the Global Modeling and Assimilation Office (GMAO) OSSE system, which includes a full suite of meteorological observations. The experiment additionally assimilated four identical IR sounders from geostationary orbit to create a “ring” of vertical profiling observations. Based on the experimentation, assimilation of the IR sounders provided a beneficial impact on the analyzed mass and wind fields, particularly in the tropics, and produced an error reduction in the initial 24–48 h of the subsequent forecasts. Specific attention was paid to the impact of the GeoXO Sounder (GXS) over the contiguous United States (CONUS) as this is a region that is well-observed and as such difficult to improve. The forecast sensitivity to observation impact (FSOI) metric, computed across all four synoptic times over the CONUS, reveals that the GXS had the largest impact on the 24-h forecast error of the assimilated hyperspectral infrared satellite radiances as measured using a moist energy error norm. Based on this analysis, the proposed GXS has the potential to improve numerical weather prediction globally and over the CONUS.

Significance Statement

The purpose of this study is to understand the impact of the proposed geostationary hyperspectral infrared sounder as part of the Geostationary Extended Observations (GeoXO) program on numerical weather prediction. The evaluation was done using a simulated environment, and showed a beneficial impact on the tropical mass and wind fields and an error reduction in the initial 24–48 h forecasts. Over the contiguous United States, the GeoXO Sounder (GXS) performed well and had the largest impact of the assimilated infrared satellite radiances on the 24 h forecast as measured by a moist energy error norm. Based on the results of this study, the proposed GXS has the potential to improve numerical weather prediction.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Erica L. McGrath-Spangler, erica.l.mcgrath-spangler@nasa.gov
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