92nd American Meteorological Society Annual Meeting (January 22-26, 2012)

Tuesday, 24 January 2012: 9:15 AM
Preliminary Results From Assimilation of AIRS Radiance Data in the Rapid Refresh Model System
La Nouvelle A (New Orleans Convention Center )
Haidao Lin, CIRA/Colorado State Univ. and NOAA/ESRL/GSD, Boulder, CO; and S. S. Weygandt, M. Hu, S. G. Benjamin, and P. Hofmann

NASA's Atmospheric Infrared Sounder (AIRS) provides high-spectral resolution radiance information that has the ability to provide atmospheric temperature and water vapor information at higher resolution and accuracy than previous satellite systems. Previous work has shown that AIRS data can be beneficial for improving model forecasts. Accordingly, we are conducting a series of tests to evaluate the impact of assimilating AIRS radiance data into the NOAA Rapid Refresh (RR) mesoscale model system. The RR is a high frequency (1-hour) cycling assimilation and prediction system that will replace the Rapid Update Cycle (RUC) at the National Centers for Environmental Prediction (NCEP) in the fall of 2011. Like the RUC, the RR provides hourly updated short-term weather forecasts, which are used for aviation, severe weather, and general weather forecasting guidance. The RR utilizes the Gridpoint Statistical Interpolation (GSI) for the analysis component and the Advanced Research WRF (ARW) for the model component.

Satellite data coverage and associated issues with bias correction are key challenges for the assimilation of the AIRS (and other satellite) data within a rapidly cycling regional model with a short data cutoff period. In addition, the radiance data assimilated in the RR regional system are further constrained because the RR has a lower model top and fewer levels in the stratosphere compared to many global models, and there is no ozone information. This may result in unrealistic contributions to the analysis increments from some AIRS channels. To examine these issues for the RR system, we have begun with a base-line retrospective experiment using a 3-hourly cycled RR and AIRS radiance data with a 3-h time window (created from the Global Data Analysis System 6-h window AIRS observation files). Despite the sub-optimality of the radiance assimilation system, we have obtained modest forecast improvements from inclusion of the AIRS radiance data. Our retrospective testing work is complemented by an investigation of the weighting functions, as well as the temperature and water vapor Jacobians for the various channels. This analysis will help document deficiencies, facilitating more effectively use AIRS radiance data in the RR. Our work with the 3-hourly cycle is a prelude to examination of the more complex partially cycled hourly update used in the actual RR. One possible design reconfiguration for this system is to assimilate satellite data during the partial cycle, which would allow for a larger data cutoff period (3h or more). At the Symposium, we will describe results to date, ongoing work, and future plans.

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