98 Spatial verification of convective systems during the 2010 NOAA Hazardous Weather Testbed Spring Experiment

Monday, 24 January 2011
Michelle Harrold, NCAR, Boulder, CO; and T. L. Jensen, B. G. Brown, S. J. Weiss, P. T. Marsh, M. Xue, F. Kong, A. J. Clark, K. W. Thomas, J. S. Kain, M. C. Coniglio, and R. S. Schneider
Manuscript (1.1 MB)

The Hazardous Weather Testbed (HWT) Spring Experiment 2010 provided an opportunity for researchers and forecasters to investigate promising numerical guidance and how it compares to current operations. The Developmental Testbed Center (DTC) collaborated with the HWT Spring Experiment to provide objective evaluation as a supplement to the subjective evaluation that is supplied by the participants.

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. The focus of this presentation is to objectively evaluate select model's performances in forecasting and discriminating between the convective and stratiform regions within the convective system. Throughout the experiment, the models subjectively appeared to perform well in forecasting convection for the short lead times; however, with increasing lead time, there were often discrepancies in timing, location, and convective mode. Specifically, 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 are included as operational baselines.

The objective verification statistics were generated using the DTC's Model Evaluation Tools (MET), a suite of state-of-the-art verification tools. Within MET, a spatial verification package, Method for Object-Based Diagnostic Evaluation (MODE), allows the forecast and observed fields to be directly compared, providing both visual and statistical output. This type of objective analysis provides both the research and forecast communities an assessment of certain strengths and weaknesses of the ensemble member configurations.

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