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SPACEBORNE QUANTITATIVE ASSESSMENT OF PRIMARY PRODUCTION VARIATIONS IN THE ARCTIC OCEAN OVER THE PREVIOUS DECADE

机译:在前十年中,星载量定量评估北极海洋的主要生产变化

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Spaceborne one month averaged data, predominantly from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and partly from the Moderate Resolution Imaging Spectroradiometer (MODIS), were used to investigate changes in primary production (PP) by phytoplankton in the Arctic Ocean from 1998 till 2010. Several PP retrieval algorithms were tested against the collected in situ data, and it was shown that the algorithm by Behrenfeld and Falkowski gave the best results (with the coefficient of correlation, r equal to 0.8 and 0.75, respectively, for the pelagic and shelf zones. Based on the performed test, the Behrenfeld and Falkowski algorithm was further applied for determining both the annual PP in the Arctic and the PP trend over the aforementioned time period. The results of our analysis indicate that PP in the Arctic has increased by ~15.9% over 13 years. This finding, as well as the absolute annual values of PP remotely quantified in the present study, is at odds with analogous numerical assessments by other workers. These disagreements are thought to be due to differences in the applied methodologies of satellite data processing, such as cloud masking and determination of phytoplankton concentration within (i) overcast areas, and (ii) areas of massive growth of coccolithophore algae, as well as (iii) in the shelf zone prone to a significant influence of land and river runoff. Hindcast (a decadal long) and forecast projections of PP variations are performed.
机译:四个月的一个月平均数据,主要来自海域视野传感器(SEAWIF),部分来自中度分辨率的成像光谱仪(MODIS),用于研究北极浮游植物的原发性生产(PP)的变化从1998年到2010年的海洋。测试几种PP检索算法对原地数据的收集测试,并且显示Behrenfeld和Falkowski的算法分别给出了最佳结果(具有相差的系数,分别等于0.8和0.75,对于骨质和架子区域。基于执行的测试,进一步应用BEANFELD和FALKOWSKI算法来确定北极中的年度PP和上述时间段的PP趋势。我们的分析结果表明了PP 13年来,北极增加了〜15.9%。这种发现,以及在本研究中远程量化的PP的绝对年值,是与类似数值的赔率其他工人的评估。这些分歧被认为是由于卫星数据处理的应用方法的差异,例如云掩蔽和浮游植物浓度在(i)覆盖区域内的植物抑制,以及(ii)含有Coccolthophore藻类的大规模生长的区域,以及( iii)在架子区容易发生土地和河流径流的重大影响。 Hindcast(Decadal Long)和PP变化的预测预测。

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