8 citations · 14 across the 5 of their papers we have counts for
5 papers
Structural Forecasting for Short-term Tropical Cyclone Intensity Guidance
Trey McNeely, Pavel Khokhlov, Niccolo Dalmasso +2
Because geostationary satellite (Geo) imagery provides a high temporal resolution window into tropical cyclone (TC) behavior, we investigate the viability of its application to sho…
Detecting Distributional Differences in Labeled Sequence Data with Application to Tropical Cyclone Satellite Imagery
Trey McNeely, Galen Vincent, Kimberly M. Wood +2
Our goal is to quantify whether, and if so how, spatio-temporal patterns in tropical cyclone (TC) satellite imagery signal an upcoming rapid intensity change event. To address this…
Identifying Distributional Differences in Convective Evolution Prior to Rapid Intensification in Tropical Cyclones
Trey McNeely, Galen Vincent, Rafael Izbicki +2
Tropical cyclone (TC) intensity forecasts are issued by human forecasters who evaluate spatio-temporal observations (e.g., satellite imagery) and model output (e.g., numerical weat…
Structural Forecasting for Tropical Cyclone Intensity Prediction: Providing Insight with Deep Learning
Trey McNeely, Niccolò Dalmasso, Kimberly M. Wood +1
Tropical cyclone (TC) intensity forecasts are ultimately issued by human forecasters. The human in-the-loop pipeline requires that any forecasting guidance must be easily digestibl…
Unlocking GOES: A Statistical Framework for Quantifying the Evolution of Convective Structure in Tropical Cyclones
Trey McNeely, Ann B. Lee, Kimberly M. Wood +1
Tropical cyclones (TCs) rank among the most costly natural disasters in the United States, and accurate forecasts of track and intensity are critical for emergency response. Intens…