Department Seminar of giora hasson - HF-radar remote sensing of ocean surface current shear using first order Bragg peaks

16 November 2022, 14:00 - 15:00 
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Department Seminar  of giora hasson - HF-radar remote sensing of ocean surface current shear using first order Bragg peaks

 

 

School of Mechanical Engineering Seminar
Wednesday, November 16th, 2022, at 14:00

Wolfson Building of Mechanical Engineering, Room 206

Giora Hasson
Advisor:  Prof. Yaron Yitzhak-Toledo

 

HF-radar remote sensing of ocean surface current shear using first order Bragg peaks

Among the various instrumentations available for measuring sea characteristics, high-frequency (HF) radars show some unique advantages. These shore-based remote-sensing systems enable over-the-horizon monitoring of surface currents, waves and winds. This allows for large real-time measurement coverage areas of tens to hundreds of kilometers. The main approach for surface current mapping utilizes the Bragg scattering from waves propagating toward the radar which are of wavelength of half of the transmitted electromagnetic wave. Similar waves that propagate away from the radar also create a similar scattering signal, but it is commonly neglected as it is assumed to provide redundant information. Through numerical and analytical solutions of an exact wave-shearing current model, we show that this signal contains significant information when the upper layer current has a vertical profile.  We present a new methodology for measuring the vertical shear of the upper layer current using the waves propagating towards and away from a single HF radar. Exploiting this additional information reduces the complexity to estimate the vertical shear and can be leveraged to increase the knowledge of the upper layer momentum budget. The suggested method is examined through a field measurement campaign using HF and in-situ instrument on Israel’s mediterranean continental shelf with good preliminary results.        

 

Join Zoom Meetin https://us02web.zoom.us/j/82108132163?pwd=Z2h4UzNzUS9mbXplT0lMU1pZenFEQT09

 

 

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