Extended Abstract (740K)J3.4
Ensemble Kalman filter assimilation of Doppler radar data with a compressible nonhydrostatic model
Mingjing Tong, University of Oklahoma, Norman, OK; and M. Xue
An ensemble Kalman filter system for assimilation Doppler radar data for the initialization and prediction of convective storms is developed, based on a nonhydrostatic compressible model. The system has been tested with OSSE data sets. Issues including the ensemble size, covariance localization, the perturbation methods and their effects on analysis quality are examined. The relative role of radial velocity and reflectivity data in recovering the full flow and cloud fields will be compared. Hopefully, results from real data experiments will be also available by the due date of extended abstract or the time of conference.
Joint Session 3, Data Assimilation and observational network design: Part III (Joint between the Symposium on Forecasting the Weather and Climate of the Atmosphere and Ocean and the 20th Conference on Weather Analysis and Forecasting/16th Conference on Numerical Weather Prediction) (ROOM 3AB)
Monday, 12 January 2004, 4:00 PM-5:30 PM, Room 3AB
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