GPS meteorology

The accurate prediction of the path and intensity of a hurricane is crucial for planning the evacuation of the populated areas and for assessing 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 atmosphere water vapor or perceptible water vapor (PWV) spatial-temporal variations is critical to forecast and localize severe storms. On the other hand, the dynamic perturbations in the atmosphere water content can be measured from the tropospheric delay of GNSS signal propagated from a satellite to a receiver on the ground. By observing PWV spatial-temporal variations during a hurricane event, the nature of PWV of this type of event can be characterized.

This project will use data to produce a geovisualization, predicting hurricane path in US east coast states (Florida, Georgia, North and South Carolina). The path forecasting is based on the 24 hour GNSS observations of stations located at east coast area. As a case study, we adopted one of the most recent destructive and long-lived hurricane along the Florida, Georgia, and South-Carolina coast, namely, Hurricane Matthew, occurred in October 2016. To investigate the potential of GNSS data for retrieving the perturbation of GNSS derived PWV, seven days (5 October-11 October) observations of Continuously Operating Reference Stations (CORS) were used to track the hurricane trace .

The geovisualization will incorporate interactive elements, allowing the user to observe the fluctuation of atmospheric parameters over time (seven days) and the predicted path of maximum rainfall in every one hour prediction period. With forecasting the precipitation in each station, the path of maximum rainfall movement can be displayed over the time. This geovisualization seeks to use certain indicators to show where we can expect the maximum GNSS-derived precipitation as the atmospheric parameters (pressure, temperature, relative humidity) fluctuate.

Hurricane Path Prediction

The accurate prediction of the path and intensity of a hurricane is crucial for planning the evacuation of the populated areas and for assessing 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 atmosphere water vapor or perceptible water vapor (PWV) spatial-temporal variations is critical to forecast and localize severe storms. On the other hand, the dynamic perturbations in the atmosphere water content can be measured from the tropospheric delay of GNSS signal propagated from a satellite to a receiver on the ground. By observing PWV spatial-temporal variations during a hurricane event, the nature of PWV of this type of event can be characterized.