P7.9 Spatial verification of convective systems during the Hazardous Weather Testbed 2010 Spring Experiment

Wednesday, 13 October 2010
Grand Mesa Ballroom ABC (Hyatt Regency Tech Center)
Michelle Harrold, NCAR, Boulder, CO; and T. L. Jensen, B. G. Brown, S. J. Weiss, P. T. Marsh, M. Xue, F. Kong, A. Clark, K. W. Thomas, J. S. Kain, M. C. Coniglio, and R. Schneider

The Hazardous Weather Testbed (HWT) Spring Experiment provides an opportunity for researchers and forecasters to investigate promising numerical guidance and how it compares to current operations. Since 2008, the Developmental Testbed Center (DTC) has collaborated with the HWT Spring Experiment to provide objective evaluation as a supplement to the subjective evaluation that is supplied by the participants.

For the HWT Spring Experiment 2010, the DTC evaluated output from the Center for Analysis and Prediction of Storms (CAPS) Storm-Scale Ensemble Forecast (SSEF) system, the High-Resolution Rapid Refresh (HRRR) model, and the North American Mesoscale (NAM) model. This presentation will focus on objectively evaluating model performance in forecasting the convective and stratiform regions in the convective system. The models subjectively appeared to perform well in forecasting convection for the short lead times throughout the experiment; however, with increasing lead time, there were often discrepancies in timing, location, and convective mode. This study will provide a focused evaluation of select SSEF members to determine how the dynamic core, microphysical scheme, and use of assimilated radar reflectivity affect the ensemble's ability to accurately forecast the timing, location, and structure of the convective and stratiform regions. The HRRR and NAM will be included as operational baselines.

The objective evaluation will be performed using the DTC's Model Evaluation Tools (MET) spatial verification package, Method for Object-Based Diagnostic Evaluation (MODE). Within MODE, the forecast and observed fields can be directly compared, providing both visual and statistical output. This analysis should provide both the research and forecast communities with an assessment of some strengths and weaknesses of the ensemble member configurations.

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