Estimating Particulate Inorganic Carbon Concentrations of the Global Ocean From Ocean Color Measurements Using a Reflectance Difference Approach
Estimating Particulate Inorganic Carbon Concentrations of the Global Ocean From Ocean Color Measurements Using a Reflectance Difference Approach
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使用反射差法通过海洋颜色测量估算全球海洋的颗粒无机碳浓度
DOI：
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发表时间：
2017
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通讯作者：
W. Balch
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作者：
C. Mitchell;Chuanmin Hu;B. Bowler;D. Drapeau;W. Balch
本文提出了一种利用海洋水色数据估算颗粒无机碳（PIC）浓度的新算法。PIC通过海洋碳酸盐泵在全球碳循环中发挥着重要作用，因此通过卫星遥感准确估计PIC浓度对于观测全球范围的变化至关重要。根据实地和卫星观测建立了一个广泛的全球数据集，以调查事先知情同意浓度与绿色、红色和近红外波段遥感反射率差异之间的关系。定义了三个颜色指数：两个是Rrs（667）在Rrs（547）和NIR中的Rrs（748 nm或869 nm）之间的基线上的相对高度，一个是Rrs（547）和Rrs（667）之间的差异。所有三个颜色指数被发现解释超过90%的方差在现场测量的PIC。但是，由于缺乏可用的Rrs（近红外）在标准的海洋颜色数据产品，大多数的进一步分析，这里提出的是使用的颜色指数确定从只有两个波段。发现新的双波段颜色指数算法比目前用于生成全球PIC数据产品的标准算法更准确地检索PIC浓度。将新算法应用于卫星图像显示了实地测量所揭示的全球范围的模式。新算法更能抵抗大气校正误差和太阳闪烁校正中的残余误差，如卫星获得的PIC图像中的斑点和斑块减少所示。
A new algorithm for estimating particulate inorganic carbon (PIC) concentrations from ocean color measurements is presented. PIC plays an important role in the global carbon cycle through the oceanic carbonate pump, therefore accurate estimations of PIC concentrations from satellite remote sensing are crucial for observing changes on a global scale. An extensive global dataset was created from field and satellite observations for investigating the relationship between PIC concentrations and differences in the remote sensing reflectance (Rrs) at green, red and near-infrared (NIR) wavebands. Three color indices were defined: two as the relative height of Rrs(667) above a baseline running between Rrs(547) and an Rrs in the the NIR (either 748 nm or 869 nm), and one as the difference between Rrs(547) and Rrs(667). All three color indices were found to explain over 90% of the variance in field-measured PIC. But, due to the lack of availability of Rrs(NIR) in the standard ocean color data products, most of the further analysis presented here was done using the color index determined from only two bands. The new two-band color index algorithm was found to retrieve PIC concentrations more accurately than the current standard algorithm used in generating global PIC data products. Application of the new algorithm to satellite imagery showed patterns on the global scale as revealed from field measurements. The new algorithm was more resistant to atmospheric correction errors and residual errors in sun glint corrections, as seen by a reduction in the speckling and patchiness in the satellite-derived PIC images.