A Feasibility Study for Probabilistic Convection Initiation Forecasts Based on Explicit Numerical Guidance
Kain, John S. ; Coniglio, Michael C. ; Correia, James ; Clark, Adam J. ; Marsh, Patrick T. ; Ziegler, Conrad L. ; Lakshmanan, Valliappa ; Miller Jr., Stuart D. ; Dembek, Scott R. ; Weiss, Steven J. ; Kong, Fanyou ; Xue, Ming ; Sobash, Ryan A. ; Dean, Andrew R. ; Jirak, Israel L. ; Melick, Christopher J.
The 2011 Spring Forecasting Experiment in the NOAA Hazardous Weather Testbed (HWT) featured a significant component on convection initiation (CI). As in previous HWT experiments, the CI study was a collaborative effort between forecasters and researchers, with equal emphasis on experimental forecasting strategies and evaluation of prototype model guidance products. The overarching goal of the CI effort was to identify the primary challenges of the CI forecasting problem and to establish a framework for additional studies and possible routine forecasting of CI. This study confirms that convection-allowing models with grid spacing ~4 km represent many aspects of the formation and development of deep convection clouds explicitly and with predictive utility. Further, it shows that automated algorithms can skillfully identify the CI process during model integration. However, it also reveals that automated detection of individual convection cells, by itself, provides inadequate guidance for the disruptive potential of deep convection activity. Thus, future work on the CI forecasting problem should be couched in terms of convection-event prediction rather than detection and prediction of individual convection cells.
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