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  • 标题:Towards Wind Vector and Wave Height Retrievals Over Inland Waters Using CYGNSS
  • 本地全文:下载
  • 作者:Eric Loria ; Andrew O'Brien ; Valery Zavorotny
  • 期刊名称:Earth and Space Science
  • 电子版ISSN:2333-5084
  • 出版年度:2021
  • 卷号:8
  • 期号:7
  • 页码:n/a-n/a
  • DOI:10.1029/2020EA001506
  • 语种:English
  • 出版社:John Wiley & Sons, Ltd.
  • 摘要:GNSS Reflectometry (GNSS‐R) measurements over inland water bodies, such as lakes, rivers, and wetlands exhibit strong coherent signals. The strength of the coherent reflections is highly sensitive to small‐scale surface roughness. For inland waters, this roughness is primarily due to wind‐driven surface waves. The sensitivity of the coherent reflections to surface roughness can be leveraged to estimate wave height profiles across inland waters. Coupled with a wind wave model, an approach to retrieve a wind vector is described using a forward model, which is potentially able to predict scattered power profiles for different wind speeds and directions and choosing the minimum‐squared error solution. The ability for spaceborne or airborne GNSS‐R to measure an inland water wind vector and wave heights could contribute to scientific applications focused on understanding nearshore ecosystems, monitoring climate change effects on inland waters, sediment resuspension, biomass production, fish habitat, and others. This paper presents a novel approach to potentially retrieve wind vector and wave heights over inland waters using GNSS‐R and discusses the issues with performing such retrievals using simulation and very few available raw signals recorded from CYGNSS satellites.
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