8A.3 Convective-scale EnKF analyses of a developing convective system: Results from OSSEs and real-data experiments

Tuesday, 6 November 2012: 4:00 PM
Symphony I (Loews Vanderbilt Hotel)
Ryan A. Sobash, University of Oklahoma, Norman, OK; and D. J. Stensrud

The vast majority of studies that utilize the ensemble Kalman filter (enKF) for convective-scale data assimilation have analyzed isolated convective storms (e.g. supercells) over a small domain. Thus, more complex convective evolutions, such as those associated with cell mergers and upscale growth into a mesoscale convective system (MCS), have been understudied. In this work, observing system simulation experiments (OSSEs) of a developing convective system were performed, capturing the evolution from multiple, initially isolated, convective cells into a squall line during a 2.5 hour period. Synthetic radar observations were extracted from a truth simulation using an WSR-88D volume coverage pattern and assimilated using the enKF into experiments using a 50-member ensemble.

This presentation will focus on specific results from the OSSEs that are unique to the upscale growth scenario simulated herein. The analysis root mean squared error (RMSE), as measured by direct comparison to the truth simulation, increased during two periods of cell mergers. The increase in RMSE is partially mitigated by tuning the covariance localization parameter, especially in the vertical. Hypotheses why these analyses may be particularly sensitive to the localization, especially the vertical localization, during the cell merger phase will be presented. Further, producing accurate analyses of the developing surface cold pool is particularly important for convective systems that undergo upscale growth. The representation of the cold pool in the OSSEs was particularly sensitive to the additive noise (Dowell et al. 2009) parameters used to maintain ensemble spread. Reducing the amount of additive noise decreased the RMSE within the cold pool, but increased RMSE elsewhere within the convective system. Finally, findings from the OSSEs will be compared to preliminary results from a real-data case study (using a realistic mesoscale environment) of a developing MCS to gauge their robustness.

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