705 NPROVS Assessment of the NUCAPS S-NPP CrIS/ATMS Sounding products Development

Tuesday, 9 January 2018
Exhibit Hall 3 (ACC) (Austin, Texas)
Bomin Sun, IMSG & NOAA/NESDIS/STAR, College Park, MD; and T. Reale, M. Pettey, R. C. Smith, A. Gambacorta, N. R. Nalli, F. Iturbide-Sanchez, C. Tan, M. Wilson, K. Zhang, X. Xiong, and L. Zhou

The Suomi National Polar-orbiting Partnership (S-NPP) polar orbiting environmental satellite, launched in October 2011, features the hyperspectral Cross-track Infrared Sounder (CrIS) and Advanced Technology Microwave Sounder (ATMS), together comprising an advanced suite of instruments for retrieving Environmental Data Records (EDRs) including atmospheric temperature and moisture profiles, skin temperature, cloud parameters, and trace gases. The algorithm for retrieving the EDR products is the NOAA Unique Combined Atmospheric Processing System (NUCAPS).

NPROVS, the NOAA (sounding) PROducts Validation System, was developed at NOAA NESDIS Center for Satellite Applications and Research (STAR) in support of the NOAA Joint Polar Satellite System (JPSS) EDR calibration/validation (cal/val) program. NPROVS provides the capability of validating atmospheric profiles through inter-comparisons with other satellite products and numerical weather prediction (NWP) data respectively collocated to radiosondes. Radiosondes include conventional and special observations such as GCOS Reference Upper Air Network (GRUAN) and JPSS funded observations synchronized with satellite overpass.

This work focuses on the assessment of the newly developed full-spectral-resolution (FSR) NUCAPS atmospheric temperature and moisture products at various stages of development using NPROVS. Assessed stages are respectively compared to the current operational nominal spectral resolution (NSR) NUCAPS (and NWP) using common sets of collocated radiosonde observations. Stages include those associated with ATMS block-2 Rapid Transmittance Algorithm (RTA) bias tuning, CrIS FSR channel selection (and associated RTA bias tuning) and regression trainings for cloud clearing and first guess profiles. Assessment are conducted under a variety of sampling conditions, for example, clear versus cloudy, land versus sea and include different retrieval methods, for example, infrared + microwave (IR+MW) versus IR-only (and MW only) versus MW-only. Assessments focus on determining if the products meet expectation, specification and to identify areas for scientific algorithm improvement.

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