Assimilation of Atmospheric Infrared Sounder (AIRS) Data in a Regional Model
Shih-Hung Chou, NASA/MSFC, Huntsville, AL; and B. T. Zavodsky, W. M. Lapenta, and G. J. Jedlovec
The NASA Short-term Prediction Research and Transition (SPoRT) Center seeks to accelerate the infusion of NASA Earth Science Enterprise (ESE) observations, data assimilation and modeling research into NWS forecast operations and decision-making. The Atmospheric Infrared Sounder (AIRS), is expected to advance climate research and weather prediction into the 21st century. It is one of six instruments onboard Aqua, a satellite that is part of NASA's Earth Observing System. AIRS, along with two partner microwave sounding instruments, represents the most advanced atmospheric sounding system ever deployed in space. The system is capable of measuring the atmospheric temperature in the troposphere with radiosonde accuracies of 1 K over 1 km-thick layers under both clear and cloudy conditions, while the accuracy of the derived moisture profiles will exceed that obtained by radiosondes.
The purpose of this paper is to describe a procedure designed to optimally assimilate AIRS data at high spatial resolution over the ocean. The AIRS data are emulated as radiosondes and configured in Netcdf format. To achieve best possible results, high-quality Level 4.0 temperature and moisture profiles over the Pacific are used. The assimilation systems used in this study is the ARPS Data Analysis System (ADAS) developed in University of Oklahoma used extensively around the globe. Results will focus on quality control issues associated with AIRS, optimal assimilation strategies, and the impact of the AIRS data on subsequent numerical forecasts produced by the next generation Weather Research and Forecast (WRF) model.
Extended Abstract (780K)
Poster Session 5, Data Assimilation
Thursday, 2 February 2006, 9:45 AM-9:45 AM, Exhibit Hall A2
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