A GPS-IPW Based Methodology for Forecasting Heavy Rain Events

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Virginia Tech


The mountainous western Virginia is the source of the headwater streams for the New, the Roanoke, and the James rivers. The region is prone to flash flooding, typically the result of localized precipitation. Fortunately, within the region, there is an efficient system of instruments for real-time data gathering with IFLOWS (Integrated Flood Observing and Warning System) gages, WSR-88D Doppler radar, and high precision GPS (Global Positioning System) receiver. The focus of this research is to combine the measurements from these various sensors in an algorithmic framework to determine the flash flood magnitude. It has been found that the trend in the GPS signals serves as a precursor for rain events with a lead-time of 30 minutes to 2 hours. The methodology proposed herein takes advantage of this lead-time as the trigger to initiate alert related calculations. It is shown here that the sum of the rates of change of total cloud water, water vapor contents and logarithmic profiles of partial pressure of dry air and temperature in an atmospheric column is equal to the rain rate. The total water content is measurable as the profiles of integrated precipitable water (IPW) from the GPS, the vertically integrated liquid (VIL) from the radar (representing different phases of the atmospheric water) and the pressure and temperature profiles are available. An example problem is presented illustrating the involving the calculations.



radiosode, statistical analysis, GOES satellite