Wednesday, 15 January 2020
Hall B1 (Boston Convention and Exhibition Center)
To support the real-time understanding of downed power lines in Florida caused by severe convective wind gusts, we investigate the relationship between severe convective wind gusts (> 50 knots) and NEXRAD-derived spatial and temporal storm structure data. Additional variables available from the Level III NEXRAD datasets are selected by implementing Regression- and tree-based methodologies. For a 5 x 5 km grid, available NEXRAD Level III data is integrated with surface wind gust data (SPC, METARS, SPECI, etc). Regression- and tree-based machine learning algorithms are developed to predict the probability of severe convective wind gust events for a given storm cell. These models are then verified using various evaluation metrics, such as receiver-operating-characteristic (ROC) curve, maximum critical success index (CSI), and Brier skill score (BSS).
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