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首页> 外文期刊>Journal of great lakes research >Verification and Application of a Bio-optical Algorithm for Lake Michigan Using SeaWiFS: a 7-year Inter-annual Analysis
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Verification and Application of a Bio-optical Algorithm for Lake Michigan Using SeaWiFS: a 7-year Inter-annual Analysis

机译:验证和应用SeaWiFS的密歇根湖生物光学算法的应用:为期7年的年度分析

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In this paper we utilize 7 years of SeaWiFS satellite data to obtain seasonal and inter-annual time histories of the major water color-producing agents (CPAs), phytoplankton chlorophyll (chl), dissolved organic carbon (doc), and suspended minerals (sm) for Lake Michigan. We first present validation of the Great Lakes specific algorithm followed by correlations of the CPAs with coincident environmental observations. Special attention is paid to the satellite observations of the extensive episodic event of sediment resuspension and calcium carbonate precipitation out of the water. We then compare the obtained time history of the CPA 's spatial and temporal distributions throughout the lake to environmental observations such as air and water temperature, wind speed and direction, significant wave height, atmospheric precipitation, river runoff, and cloud and lake ice cover. Variability of the onset, duration, and spatial extent of both episodic events and seasonal phenomena are documented from the SeaWiFS time series data, and high correlations with relevant environmental driving factors are established. The relationships between the CPAs retrieved from satellite data and environmental observations are then used to speculate on the future of Lake Michigan under a set of climate change scenarios.
机译:在本文中,我们利用7年的SeaWiFS卫星数据来获取主要水色生成剂(CPA),浮游植物叶绿素(chl),溶解性有机碳(doc)和悬浮矿物质(sm)的季节和年际时间历史。 )前往密歇根湖。我们首先介绍大湖区特定算法的验证,然后将CPA与同时发生的环境观察结果进行关联。卫星观测对沉积物再悬浮和碳酸钙从水中析出的广泛性事件特别关注。然后,我们将获得的CPA在整个湖泊中的时空分布的时间历史与环境观测值进行比较,例如空气和水温,风速和风向,显着的波高,大气降水,河流径流以及云层和湖泊冰盖。从SeaWiFS时间序列数据中记录了突发事件和季节性现象的发作,持续时间和空间范围的变化,并建立了与相关环境驱动因素的高度相关性。然后使用从卫星数据中获取的CPA与环境观测值之间的关系来推测密歇根湖在一系列气候变化情景下的未来。

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