从空中观测到的海洋颜色测量路易斯安那州大陆架的沿海海面盐度

V. Maisonet, J. Wesson, D. Burrage, S. Howden
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引用次数: 6

摘要

我们已经展示了机载辐射和辐照度传感器探测Atchafalaya羽流和相应颜色锋的持续盐度梯度的能力,这是由原位船载测量和STARRS观测到的。我们使用D’sa等人2006年的经验算法Acdom (412) =3D 0.227}(Rrs510/Rrs555)−2.022(1)。他们的研究与我们的研究在相同的地区(路易斯安那大陆架)和一年中的时间(3月)进行,使用类似的光学设备。这项研究产生了一个海洋颜色盐度模型,可以以88%的精度测量路易斯安那大陆架的海面盐度。基于两个光通道的盐度多元线性回归为Atchafalaya羽流地区大尺度海岸盐度提供了一个很好的定性代理(y=−3D0.0082 - x+0.34, R2=3D0.90, n=3D5220)。然后,我们根据5月和11月的数据开发了两种算法。这样做是为了创建两个盐度的季节性方程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Measuring coastal sea-surface salinity of the Louisiana shelf from aerially observed ocean color
We have demonstrated the ability of airborne radiance and irradiance sensors to detect the persistent salinity gradient of the Atchafalaya plume and corresponding color fronts as observed by in-situ shipboard measurements as well as STARRS. We used an empirical algorithm Acdom (412) =3D 0.227}(Rrs510/Rrs555)−2.022 (1) for CDOM from D'Sa et al. 2006. Their study was conducted in the same region (Louisiana Shelf) and time of year (March) as our study and it was performed with similar optical equipment. This study resulted in an Ocean Color Salinity model that can measure with ~88% accuracy the Sea-Surface Salinity of the Louisiana shelf. A multi-linear regression for salinity, based on two of the optical channels, provides an excellent qualitative proxy for large scale coastal salinity in the Atchafalaya plume region (y=−3D0.0082⋆x+0.34, R2=3D0.90, n=3D5220). We then developed two algorithms from the May and November data. This was done to create two seasonal equations for salinity.
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