作为海洋彩色卫星数据产品验证新资源的海洋固有光学特性采样在塔拉海洋考察中进行

P. Jeremy Werdell , Christopher W. Proctor , Emmanuel Boss , Thomas Leeuw , Mustapha Ouhssain
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引用次数: 34

摘要

开发和验证海洋彩色卫星仪器的数据记录需要大量高质量的现场数据。在缺乏广泛的、制度性支持的实地项目的情况下,NASA海洋生物处理小组等组织寻求机会性的数据集,用于其操作卫星校准和验证活动。作为为期两年半的塔拉海洋考察的一部分,公开可用的全球生物地球化学数据集提供了这样一个机会。我们展示了如何使用R/V Tara收集的高光谱吸收和衰减系数的在线测量值来评估近地表叶绿素-a、光谱颗粒后向散射系数、颗粒有机碳和来自NASA中分辨率成像光谱仪的颗粒大小类别。这种流量测量的主要优势在于采样率,在375天的测量中,有165个modisa与原位匹配,而离散水采样只有13个。虽然需要应用生物光学模型来估计光谱学中感兴趣的生物地球化学数量仍然是一个弱点,但我们展示了如何将离散样本与流动测量相结合,以创建足够质量的数据记录,从而对卫星衍生数据产品进行一阶评估。鉴于机构希望快速评估新的卫星任务,我们的结果对如何构建这些任务的校准和验证团队具有重要意义。
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Underway sampling of marine inherent optical properties on the Tara Oceans expedition as a novel resource for ocean color satellite data product validation

Developing and validating data records from operational ocean color satellite instruments requires substantial volumes of high quality in situ data. In the absence of broad, institutionally supported field programs, organizations such as the NASA Ocean Biology Processing Group seek opportunistic datasets for use in their operational satellite calibration and validation activities. The publicly available, global biogeochemical dataset collected as part of the two and a half year Tara Oceans expedition provides one such opportunity. We showed how the inline measurements of hyperspectral absorption and attenuation coefficients collected onboard the R/V Tara can be used to evaluate near-surface estimates of chlorophyll-a, spectral particulate backscattering coefficients, particulate organic carbon, and particle size classes derived from the NASA Moderate Resolution Imaging Spectroradiometer onboard Aqua (MODISA). The predominant strength of such flow-through measurements is their sampling rate—the 375 days of measurements resulted in 165 viable MODISA-to-in situ match-ups, compared to 13 from discrete water sampling. While the need to apply bio-optical models to estimate biogeochemical quantities of interest from spectroscopy remains a weakness, we demonstrated how discrete samples can be used in combination with flow-through measurements to create data records of sufficient quality to conduct first order evaluations of satellite-derived data products. Given an emerging agency desire to rapidly evaluate new satellite missions, our results have significant implications on how calibration and validation teams for these missions will be constructed.

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