The Preliminary Study on the Prediction of a Hurricane Path by GNSS Derived PWV Analysis

Hoda Tahami Jihye Park, Yunsoo Choi

Peer Reviewed

Abstract: The accurate prediction of the path and intensity of a hurricane is crucial for an evacuation plan and the assessment of its impact. Since the evolution of severe weather phenomena is associated with notable transient changes in water contents in the low atmosphere, the accurate monitoring of precipitible water vapor (PWV) is critical to forecast and localize severe storms. The dynamic perturbations in the atmosphere water content can be measured from the tropospheric delay of GNSS signals propagated from a satellite to a receiver on the ground. By observing the spatial-temporal variations of PWV during a hurricane, the nature of PWV for this type of event can be characterized. This study focused on the PWV observation associated with a hurricane for tracking its trace. In addition, the authors extended the analysis to the prediction of its path by generating dynamical-statistical model of hurricane intensity variations before a hurricane. This prediction model quantifies the relationship between a spatial-temporal hurricane intensification, the PWV Rate Of Change (PROC), and meteorological variables that can be estimated in near real time. As a case study, we adopted one of the recent, destructive, and long-lived hurricane along the Florida, Georgia, North Carolina and South Carolina coast, namely, Hurricane Matthew, occurred in October 2016. Based on the statistical characterization of the duration and intensity of PWV fluctuations before, during, and after the hurricane events, multiple events were identified. The experimental results showed that the most severe events happened in descending trend of PWV after its long ascending period and the most intense part of the event occurred after sharp ascents of PWV. By tracking the trace of the hurricane, it can be further extended to predict the path of the hurricane by utilizing the behavior of the PROC as a significant indicator of predicting different intensity and duration of the event.
Published in: Proceedings of the ION 2017 Pacific PNT Meeting
May 1 - 4, 2017
Marriott Waikiki Beach Resort & Spa
Honolulu, Hawaii
Pages: 500 - 513
Cite this article: Park, Hoda Tahami Jihye, Choi, Yunsoo, "The Preliminary Study on the Prediction of a Hurricane Path by GNSS Derived PWV Analysis," Proceedings of the ION 2017 Pacific PNT Meeting, Honolulu, Hawaii, May 2017, pp. 500-513.
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