Start
July 21, 2020 - 12:00 pm
End
July 21, 2020 - 1:00 pm
Categories
Convective Meteorology (Mesoscale Dynamics)School of Meteorology Colloquium
Verification of the Tornado and Lightning Plumes and Evaluation of a New Kernel for the Tornado and Lightning Plumes
Ian Gesell
Tuesday, July 21st
12:00 PM Central Time (US and Canada)
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Forecasting a Continuum of Environmental Threats (FACETs) is a proposed framework that could modify the current watch/warning system to communicate hazardous weather information to serve the public. A key part of FACETs is Probabilistic Hazard Information (PHI). Currently warnings are yes/no (binary). PHI changes this by putting threat probabilities onto grids. PHI plumes for tornado, lightning, wind, and hail were created by NWS forecasters as part of experiments in the NOAA Hazardous Weather Testbed (HWT) in 2016 and 2017. These probabilistic plumes were produced using the storm size and speed to determine the width and length of the plumes. A Gaussian smoother from the center point was then used to provide a visualization of the forecast threat area and region of uncertainty in the HWT. Since these forecasts are probabilistic, a method of forecast verification is needed to determine the accuracy of these plumes instead of binary verification.
This study first examines event distances for both lightning and tornado hazards, and then applies verification methods used for other probabilistic forecasts to define an appropriate reference class. The verification data used for the lightning plumes was the National Lightning Detection Network. The tornado plumes were verified by tracking the mesocyclone coordinates using start and end time from the Storm Events Database or using tornado warnings. This study uses four different tornado and lightning cases from the 2017 HWT PHI experiment. For each case, the maximum probability of the plumes at all timesteps for a case were merged together. Attributes and ROC diagrams were created for the forecaster data. Practically perfect plumes were created for comparison to the forecaster plumes to better understand what an ideal forecast could be following the same forecasting constraints and/or rules. Multiple thresholds of distance were used to determine the appropriate definition of “an event’” for the probabilistic hazard. For each of the tornado and lightning cases, it was found that using a 7.5 km radial distance away from the mesocyclone coordinates or the NLDN flashes was where the attributes diagrams indicated the plumes were most accurate. Epanechnikov, Quartic, and Triangular kernels were applied to the forecaster and practically perfect created probabilities to see if there was a better kernel than Gaussian for either of the tornado or lightning plumes. It was found that for the tornado plumes the Gaussian kernel provided the best results. However, for lightning the Epanechnikov kernel was the best kernel to use to apply to the probabilities.
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