Tuesday, 24 January 2012: 5:15 PM
Pre-Launch to Post-Launch Transition and Evaluation of CrIMSS EDR Algorithm and Products
Room 343/344 (New Orleans Convention Center )
The Cross-track Infrared Sounder (CrIS) and the Advanced Technology Microwave Sounder (ATMS) planned to be flown aboard the Joint Polar Satellite System (JPSS) form the next generation operational sounding system to derive many geophysical parameters. These instruments provide high quality hyper-spectral InfraRed (IR) and Microwave (MW) observations to enable generation of high-quality atmospheric sounding products. Algorithms to process CrIS and ATMS observations into Sensor Data Records (SDRs), and process SDRs into geophysical parameter retrievals (Environmental Data Records, EDRs) have been developed. The Northrop Grumman Aerospace System (NGAS) has adapted the Atmospheric Environmental and Research (AER) CrIS and ATMS (CrIMSS) EDR algorithm to retrieve Atmospheric Vertical Temperature Profiles (AVTP), Atmospheric Vertical Moisture Profiles (AVMP), atmospheric pressure profiles and many other ancillary EDR products. During the pre-launch phase, these algorithms were evaluated using many types of proxy CrIS and ATMS SDR data sets, matched EDR products from Infrared Atmospheric Sounder Interferometer (IASI) retrievals, and other correlative measurements. Post-launch EDR products were also generated using the CrIMSS EDR algorithm tuned for real observations and utilizing the first-light CrIS/ATMS SDRs. This paper discusses the lessons learned through pre-launch efforts, and how they have helped in the post-launch phase in fine-tuning the EDR algorithm, and in the evaluation of first-light AVTP, AVMP and other EDR products. The empirical bias-tuning procedures employed by different agencies, evaluation of the EDR algorithm with different sets of proxy SDRs during the pre-launch, and corresponding post-launch efforts in fine-tuning the EDR algorithm are presented. First-light SDR and EDR products, their evaluation with the European Center for Medium Range Weather Forecast (ECMWF) analysis fields, and other correlative data sets are discussed. Future directions towards further refinements to the EDR algorithm and long term evaluation plans are presented.
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