Improving hurricane prediction models using GPS data

GPS satellites orbiting the Earth

Exploiting a flaw in the system

GPS was originally designed for positioning, navigation, and timing (PNT) applications which measures the transmitted time of the radio signals from a satellite in the space to a receiver on the ground. But this story is not about improving GPS accuracy in navigation applications, rather it is a clever use of the GPS signal delay to collect data for monitoring the atmosphere for use in weather event predictions.

The transmitted GPS signal contains not only the range information, which is the primary factor of interest, but also error sources, such as atmospheric delay including tropospheric delay. The delay in GPS signals reaching Earth-based receivers due to the presence of water vapor is nearly proportional to the quantity of water vapor integrated along the signal path.

GPS is capable of seamless monitoring of the moisture in the atmosphere with high temporal and spatial resolution. Excellent GPS data availability enables unique opportunities for data analysis and experimental studies in GPS-meteorology.

This week’s guest, Hoda Tahami, is a third year PhD student in Dr. Jihye Park’s geomatics research group in the Department of Civil and Construction Engineering. Using geomatics – the science of gathering, storing, processing, and delivering spatially referenced information – Hoda is working to improve weather models for hurricane prediction.

GPS Meteorology: Estimating vertically integrated atmospheric water vapor, or perceptible water, from Global Positioning System (GPS) radio signals collected by a regional network of ground-based geodetic GPS receiver.

Using GPS signal data for hurricane prediction

Data from Hurricane Matthew that hit Florida in 2016 has been used to explore the idea of using GPS data to predict the path and intensity of hurricanes. “I found a clear correlation between [signal delay] and other atmospheric variables, like temperature, precipitation, and water vapor,” says Hoda. This information can be used for weather models, which rely on quality observational data. Weather models are computer programs that apply physics to observations to make predictions. The set of observations forming the starting point for the model simulation are called the initial conditions. Hoda hopes that this new set of data can be used as an initial condition for existing atmospheric models.

This new set of GPS-based data provides an increase in temporal and spatial resolution. While many satellite data sources provided data every few hours or even just once or twice a day, Hoda explains, “The time scale in my data is in seconds. We average it to five minutes, then use it to make one to twenty-four hour predictions.” This new set of data can be used to complement existing data sets – each with their own caveats – used by agencies like the National Hurricane Service, National Oceanic and Atmospheric Administration (NOAA), and the National Weather Service.

More information about the proposed model can be found at: https://www.ion.org/publications/abstract.cfm?articleID=15074

Hoda Tahami with her poster at the Graduate Research Showcase at Oregon State University

Finding a love for geospatial research

Hoda began her career in civil engineering with a bachelor’s degree at K. N. Toosi University of Technology in Tehran, Iran. This was Hoda’s first experience with geospatial data and geographic information systems (GIS), which piqued her interest and led her to pursue a Master’s degree specializing in GIS. Due to the state-of-the-art geospatial research resources available, Hoda chose to pursue her doctorate degree at Oregon State.

Join us on Sunday, May 5 at 7 PM on KBVR Corvallis 88.7 FM or stream live to learn more about Hoda’s geospatial research and journey to graduate school.

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