Sea Surface Roughness Trends Estimation using Power Waveforms of BeiDou MEO Satellite Reflected Signals

Author

Mohammad Shohidul Islam, S M Injamamul Haque Masum, Md. Farid Uddin, Md. Naim Islam Talukder, Sultana Easmin Siddika


Abstract

 The sea surface is a crucial climate regulator and the boundary where air and water interact. It fuels global weather systems and tempers climate change by absorbing heat and carbon dioxide, while its microscopic marine life generates a major portion of Earth's breathable oxygen. Sea surface roughness monitoring is essential for assessing ocean conditions and improving sea-state and marine weather forecasting. This study proposes a remote sensing approach to characterize sea surface roughness from the power waveforms of BeiDou MEO Satellite Reflected Signals. The waveforms are simulated using a Z-V scattering model, with sea surface slope variances (upwind and crosswind) first derived from a wave spectrum model. The resulting power waveform characteristics, particularly their amplitude patterns, are then analyzed to identify variations in sea surface roughness under different ocean conditions. The results demonstrate a clear relationship between waveform characteristics and sea surface conditions, indicating the potential of GNSS-reflectometry for sea-state monitoring. The findings also provide a basis for future retrieval of other important ocean parameters using reflected GNSS signals.



Keywords

Power waveforms, estimation, sea roughness trend, scattering model, reflected signals



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References


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