论文标题
SAR图像波光谱可使用粘性波模型检索油脂 - 层海冰的厚度
SAR image wave spectra to retrieve the thickness of grease-pancake sea ice using viscous wave models
论文作者
论文摘要
由油脂和煎饼冰（GPI）组成的年轻海冰，以及被认为是海冰冰冻南极洲最常见形式的薄层，现在也正在成为北极中的“新正常”。调查以确定GPI的增加如何影响远北和全球的气候，需要特定的工具来监视GPI的厚度分布。卫星SAR成像的定向波谱用于确定波散的波散变化，因为波列进入GPI场。然后，通过将色散数据与冰盖海洋中的两个波传播模型拟合来估算冰盖厚度：凯勒的模型和封闭式包装（CP）模型。 对于这两个模型，都得出并讨论了GPI粘度随冰厚度的函数的经验构成方程。 2015年11月1日，在Beaufort Sea拍摄的Sentinel-1 C频带SAR图像显示了GPI厚度检索的示例，2019年3月在Weddell Sea中拍摄的三个Cosmoskymed X Band SAR图像。估计的GPI厚度与并发的SMOS测量值保持一致。
Young sea ice composed of grease and pancake ice (GPI), as well as thin floes, considered to be the most common form of sea ice fringing Antarctica, is now becoming the 'new normal' also in the Arctic. Investigations to determine how an increase in GPI is affecting the climate in the far north and globally, require specific tools to monitor the GPI's thickness distribution. Directional wave spectra from satellite SAR imagery are used to determine the change in wave dispersion as a wave train enters GPI fields. The ice cover thickness is then estimated by fitting the dispersion data with two models of wave propagation in ice cover ocean: the Keller's model and the close-packing (CP) model. For both models, an empirical constitutive equation for GPI viscosity as a function of the ice thickness is derived and discussed. Examples of GPI thickness retrievals are shown for a Sentinel-1 C band SAR image taken in the Beaufort Sea on 1 November 2015, and three CosmoSkyMed X band SAR images taken in the Weddell Sea on March 2019. The estimated GPI thicknesses are consistent with concurrent SMOS measurements and the available local samplings.
