Extended Abstract (704K)P9.5
Examining the Impact of Spatial and Temporal Resolutions of Phased-Array Radar on EnKF Analysis of Convective Storms Using OSSEs - Modeling Observation Errors
Yasuko Umemoto, University of Oklahoma, Norman, OK; and T. Lei, T. Y. Yu, and M. Xue
The National Weather Radar Testbed (NWRT) in Norman, Oklahoma contains an S-band Phased Array Radar (PAR) that can adaptively scan multiple regions using electronic beam steering. Compared to conventional weather radars such as the WSR-88D, PAR has the potential to increase the warning lead times of severe storms such as tornadoes. One of the ongoing efforts for improving convective-storm analysis and prediction is to assimilate the PAR data into the Advanced Regional Prediction System (ARPS) using an ensemble Kalman filter (EnKF). This procedure has recently been recently enhanced to use proper beam pattern and range weighting functions to assimilate radial by radial observations.
In this study, we extend the earlier Observing System Simulation Experiments (OSSEs) to examine additional capabilities of the PAR in more realistic settings. Conforming earlier results, azimuthal over-sampling and rapid update time are shown to improve the analysis In addition, scanning strategies designed to measure the atmospheric information not only inside the storm, but also in the surrounding clear air regions are examined. In general longer dwell time is required for clear air regions to achieve a similar level of accuracy as in precipitation region. For these experiments, observation errors that are spatially inhomogeneous and scanning strategy-dependent are applied. By properly modeling the expected error in the observations using different scanning strategies, the results of the OSSEs become more robust. An optimal combination of the spatial and temporal resolutions and data precision is sought through the EnKF OSSEs.
Poster Session 9, Data Assimilation Studies
Thursday, 8 October 2009, 1:30 PM-3:30 PM, President's Ballroom
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