Chandrasekaran Venkatachalam - Fort Collins CO, US Yanting Wang - Aurora CO, US
Assignee:
Colorado State University Research Foundation - Fort Collins CO
International Classification:
G01S 13/95
US Classification:
342 26R, 342188, 342194, 342195
Abstract:
Systems and methods are provided for adaptively estimating the specific differential phase (K) from dual-polarization radar data in the complex domain. Some embodiments adapt for wrapped differential propagation phases by estimating the specific differential phase in the complex domain. Some embodiments adapt for measurement fluctuations and/or spatial scale in making such estimations. Some embodiments also provide for determining the presence of storms cells using the dispersion of the differential propagation phase shift over a subset of bins.
Dynamic And Adaptive Radar Tracking Of Storms (Darts)
Chandrasekaran Venkatachalam - Fort Collins CO, US Gang Xu - Houston TX, US Yanting Wang - Aurora CO, US
Assignee:
Colorado State University Research Foundation - Fort Collins CO
International Classification:
G01S 13/95
US Classification:
342 26 R
Abstract:
Methods and systems for estimating atmospheric conditions are disclosed according to embodiments of the invention. In one embodiment, a method may include receiving reflective atmospheric data and solving a flow equation for motion coefficients using the reflective atmospheric data. Future atmospheric conditions can be estimated using the motion coefficients and the reflective atmospheric data. In another embodiment of the invention, the flow equation is solved in the frequency domain. Various linear regression tools may be used to solve for the coefficients. In another embodiment of the system, a radar system is disclosed that predicts future atmospheric conditions by solving the spectral flow equation.
Chandrasekaran Venkatachalam - Fort Collins CO, US Yanting Wang - Aurora CO, US
International Classification:
G01S 13/95
US Classification:
342 26 R
Abstract:
Embodiments of the invention can predict the ground location and intensity of storm cells for a future time using radar reflectivity data. In some embodiments, a Sinc approximation of the general flow equation can be solved to predict the ground location and intensity of a storm cell. In some embodiments, to solve the Sinc approximation the velocity of a storm cell can be estimated using various techniques including solving the flow equation in the frequency domain. The results can provide efficient prediction of storm cell position in nowcasting applications.
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