Using OSSEs to Evaluate GXS Impact in the Context of International Coordination

Abstract

Abstract The Geostationary Extended Observations (GeoXO) program plans to include a hyperspectral infrared (IR) sounder on its central satellite, expected to launch in the mid-2030s. As part of the follow-on to the GOES program, the NOAA/NASA GeoXO Sounder (GXS) instrument will join several international counterparts in a geostationary orbit. In preparation, the NASA Global Modeling and Assimilation Office (GMAO) assessed the potential effectiveness of GXS both as a single GEO IR sounder and as part of a global ring that includes international partners. Using a global observing system simulation experiment (OSSE) framework, GXS was assessed from a numerical weather prediction (NWP) perspective. Evaluation of the ability of GXS, both alone and as part of a global ring of GEO sounders, to improve weather prediction of thermodynamic variables was performed globally and regionally. GXS dominated regional analysis and forecast improvements and contributed significantly to global increases in forecast skill relative to a Control. However, more sustained global improvements, on the order of 4 days, relied on international partnerships. Additionally, GXS showed the capability to improve hurricane forecast track errors on the time scales necessary for evacuation warnings. The FSOI metric over CONUS showed that the GXS observations provided the largest radiance impact on the moist energy error norm reduction. The high-temporal-resolution atmospheric profile information over much of the Western Hemisphere from GXS provides an opportunity to improve the representation of weather systems and their forecasts. Significance Statement NOAA and NASA are currently planning the GeoXO mission as a follow-on to the GOES program. As part of this process, NASA’s Global Modeling and Assimilation Office has performed several experiments using an observing system simulation experiment (OSSE) framework to assess the potential impact of the GeoXO Sounder (GXS) on numerical weather prediction within the context of international partners launching similar instruments. As part of this assessment, it was found that assimilation of GXS data has the ability to improve both the model analyzed weather and forecasts of the weather, specifically over the domain that GXS observes. Global improvements relied more heavily on a solution consisting of multiple instruments to form a global ring.