Evaluation of the Storm Cell Identification and Tracking Algorithm used by the WSR-88D
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The Storm Cell Identification and Tracking (SCIT) algorithm used by the WSR-88D radar identifies storm cells and projects their future movements. It can be extremely useful in making short-term predictions about the impact that a thunderstorm may have on a localized area, allowing people to prepare for an approaching storm. In order to assess the accuracy of the Storm Prediction Forecast algorithm within the SCIT, 48 storms in New York and 24 storms in Kansas were chosen and the error between their forecast tracks and their actual paths was determined. These regions were chosen to look for any significant differences in algorithm performance in two disparate geographical regions and to include a region of the U.S. for which the SCIT algorithm has not been previously evaluated. The storms were chosen based on their severity, all being tornadic at some point during their lifespan. The Storm Position Forecast algorithm acts to predict positions for an identified cell in 15-minute intervals, out to a maximum of 60 minutes. To verify that the algorithm improves with time with respect to a given storm cell, successive scans were also analyzed to verify an improvement in the forecast tracks. Once the errors for each position forecast were calculated, comparisons were done between several different parameters to search for correlations with the errors, including distance to the radar station, dBZ value, lead-time, year and time of day. The errors were broken down further based on direction - where a storm went versus its projection. The most outstanding result discovered was in the separation of error into individual directions. For both the New York and Kansas storms, there was a prominent trend for the storm’s actual path to be to the right of the projected path. The reason for this preferential rightward error can only be hypothesized here and would be an area for further research.
dissertation or thesis