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The combined use of optical remote sensing data and unattended flow-through fluorometer measurements in the Baltic Sea

机译:波罗的海光学遥感数据与无人值守流通荧光计测量的结合使用

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摘要

Global algorithms for chlorophyll-a (chl-a) concentration and primary productivity retrieval from satellite observations are often not applicable to areas that are turbid and rich in coloured dissolved organic matter (CDOM), such as the Baltic Sea. Such a turbid (Case 2) water area, with its unique optical properties, often requires a parametrization to local conditions. Water quality algorithms are also sensitive to other naturally occurring phenomena, such as temporal variations in the atmospheric properties. Therefore, adequate reference data are essential for the estimation of water quality algorithm accuracy. In this study, a comparison with Sea-viewing Wide Field of view Sensor (SeaWiFS) data and high-frequency flow-through fluorometer measurements is made. These so-called 'ship of opportunity' data are measured with an automated continuous sampling system onboard several merchant and passenger ships in the Baltic Sea (SOOP, the Alg@line-system). The study is concentrated on the monitoring of spring blooms in the years 1999 and 2000. By combining Alg@line observations with satellite instrument observations, the strengths of both data sources are obtained. The Alg@line-fluorometer data ensure a sufficient amount of field samples to parametrize remote sensing chl-a algorithms. Information with a full spatial coverage on chl-a fluctuations can be obtained through the use of remote sensing data.
机译:从卫星观测中获取叶绿素a(chl-a)浓度和初级生产力的全球算法通常不适用于浑浊且富含有色溶解有机物(CDOM)的地区,例如波罗的海。这种浑浊的(案例2)水域具有独特的光学特性,通常需要根据当地情况进行参数化。水质算法对其他自然现象也很敏感,例如大气特性的时间变化。因此,充足的参考数据对于估算水质算法的准确性至关重要。在这项研究中,与海视宽视场传感器(SeaWiFS)数据和高频流通荧光计的测量结果进行了比较。这些所谓的“机会之船”数据是通过波罗的海的几艘商船和客船上的自动连续采样系统(SOOP,Alg @ line-system)进行测量的。该研究集中于1999年和2000年的春季开花监测。通过将Alg @ line观测与卫星仪器观测相结合,可以获得这两个数据源的优势。 Alg @ line荧光计数据可确保有足够的现场样本来参数化遥感chl-a算法。可以通过使用遥感数据获得关于chl-a波动的完整空间覆盖信息。

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