P1.44
Pre-Flight CrIS SDR Algorithm Performance Assessment
Vladimir Zavyalov, Space Dynamics Laboratory, Logan, UT; and G. Bingham, H. Johnson, N. S. Pougatchev, M. P. Esplin, G. W. Cantwell, D. Ferguson, and L. Chidester
The Cross-track Infrared Sounder (CrIS) is one of the primary sensors now under development for the National Polar-orbiting Operational Environmental Satellite System (NPOESS) program, which is the follow-on to the current DMSP and POES meteorological satellite system. CrIS is an interferometeric sounding sensor measuring upwelling earth radiances, and these data are used to reconstruct vertical profiles of atmospheric temperature, moisture, and pressure. The CrIS mission is to collect upwelling infrared spectra at very high spectral resolution and with excellent radiometric precision. The Utah State University/Space Dynamics Laboratory (SDL) team is conducting an independent study as part of the Internal Government Study (IGS) team to ensure that CrIS Sensor Data Record (SDR) science and operational algorithms provide accurately calibrated radiances as an independent sounding product and as an input to the three Cross-track Infrared Microwave Sounder Suite (CrIMSS) Environmental Data Records (EDRs). The team has developed a systematic approach to test many aspects of the CrIS SDR algorithms. Algorithm-specific tests are designed to check the algorithm performance on the Government Resource for Algorithm Verification, Independent Test, and Evaluation (GRAVITE) environment. Synthetic data are used to isolate and access the impact of different controllable sources of errors on the accuracy of the SDR. Proxy data are used to provide an increased confidence in the algorithm performance on semi-real-world data. To generate the CrIS-like interferograms (RDR product), we are using an independent CrIS instrument model developed at SDL. EDU3 and FM1 test data are used to verify the ability of the SDR algorithms to correct artifacts and imperfections induced by the instrument under different test conditions. In this study we demonstrate and discuss the results of these tests. The Principal Component Analysis (PCA) tools developed at SDL are used to identify PC signature and instrument artifacts/features in spectral domain. At the proxy data generation phase the PCA filter is used for filtering heritage instrument-specific noise.
Poster Session 1, 4th NPOESS Symposium Poster Session
Tuesday, 22 January 2008, 9:45 AM-11:00 AM, Exhibit Hall B
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