14th Symposium on Integrated Observing and Assimilation Systems for the Atmosphere, Oceans, and Land Surface (IOAS-AOLS)


Assimilation of simulated infrared brightness temperatures as part of an OSSE employing the Ensemble Kalman Filter

Jason A. Otkin, CIMSS/Univ. of Wisconsin, Madison, WI; and W. E. Lewis

The Advanced Baseline Imager (ABI) to be launched onboard the GOES-R satellite in 2016 will provide valuable observations of the atmospheric state at high spatial, temporal, and spectral resolutions. To better understand the potential impact of these observations on the accuracy of atmospheric analyses used by numerical weather prediction models, several Observation System Simulation Experiments (OSSEs) are being performed for a case study tracking the evolution of two large thunderstorm complexes that developed across the central U.S. For these experiments, different combinations of simulated ABI infrared radiances for both clear and cloudy-sky conditions, along with various simulated conventional observations, will be assimilated using the Data Assimilation Research Testbed (DART) data assimilation system, which employs the Ensemble Kalman Filter (EnKF) methodology. By using an EnKF system, it is much easier to assimilate satellite radiances since there is no need to develop adjoint and tangent linear models. Overall, the preliminary results show that the assimilation of satellite radiances has a positive impact on the analysis, particularly for clouds, relative to what can be achieved by only assimilating conventional observations.

Recorded presentation

Session 10B, Experiments involving observations, real or hypothetical: data impact tests and observing system simulation experiments (OSSEs) IV
Wednesday, 20 January 2010, 4:00 PM-5:30 PM, B306

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