Using NPROVS for Evaluation of Suomi NPP Atmospheric Sounding Retrievals against Conventional Radiosonde Observations

The consistent validation and verification of the multiple satellites, sensors and derived product suites operated by NOAA is critical for their optimal integration and impact in weather forecast and climate applications, the primary mission of these programs. The NOAA Products Validation System (NPROVS) (http://www.star.nesdis.noaa.gov/smcd/opdb/poes/NPROVS.php), supported by the NOAA Joint Polar Satellite System (JPSS), deployed at NOAA NESDIS Center for SaTellite Applications and Research (STAR) in April 2008, provides ongoing data access, collocation, monitoring and inter-comparison of these multiple sensor and product suites. NPROVS utilizes global ground truth targets, typically provided by in situ conventional radiosondes and dropsonde observations (RAOBs) to define prevailing atmospheric and surface conditions at a given location and time. These are then collocated to the respective atmospheric sounding profiles derived from polar (NOAA, MetOp, Aqua), geostationary (GOES) and radio occultation (COSMIC) satellites for validation.

We present the initial analysis of ensemble vertical statistics, based on 12 months of NPROVS collocation data, revealing the performance of derived atmospheric temperature and water vapor retrievals from the Suomi-NPP Cross-track Infrared Microwave Sounder Suite (CrIMSS), including the products from the CrIMSS Interface Data Processing Segment (IDPS), the NOAA Unique CrIS/ATMS Processing System (NUCAPS), and the NOAA Microwave Integrated Retrieval System (MiRS). The performance is assessed against collocated conventional RAOBs as the truth for different climate regimes and surface types, for different cloud conditions and for different time-scales including day versus night and seasonal cycle. We will also investigate how their accuracy characterization varies with other commonly used reference datasets, including NWP (NOAA Global Forecast System and Climate Forecast System Re-analysis, and ECMWF analysis) and GPSRO, all of which have their own bias and noise uncertainties. We discuss how such analyses can advance our understanding of the respective retrieval systems and, furthermore, if major geophysical variables derived from the hyper-spectral sounder represent a nominal level of maturity for application in weather and climate monitoring.