Assessment of uncertainties of ocean color parameters for the ocean Carbon-based Productivity Model
Assessment of uncertainties of ocean color parameters for the ocean Carbon-based Productivity Model
复制标题
海洋碳基生产力模型海洋颜色参数的不确定性评估
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Z. Xuan
中科院分区：
文献类型：
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作者：
Ma Sheng;Xiaofeng Yang;Tao Zui;Li Ziwei;Z. Xuan
随着海洋水色遥感技术的不断发展，一些海洋水色参数可以通过卫星遥感在全球范围内获得。叶绿素浓度（Chl）、颗粒物后向散射系数（bbp）、光合有效辐射（PAR）等与浮游植物净初级生产力（NPP）相关。在此基础上，结合其他辅助数据，建立了碳基产能模型（CbPM）。该模型从bbp中推导出浮游植物碳（C），并利用C和Chl的比率来描述浮游植物生长速率（μ），其具有对光（通过PAR的变化）、营养物和温度的生理依赖性。本文利用蒙特卡罗方法研究了卫星反演参数（叶绿素、光合有效辐射和光合有效辐射）的不确定性如何通过气候变化过程传播。比较了各输入项对NPP随机不确定性的贡献。分析结果表明，在三个参数中，叶绿素对模型输出不确定性的贡献最大。因此，叶绿素的准确性的提高将有最大的潜力，以提高在估算浮游植物NPP的能力。
With the developments of ocean color remote sensing technology, some ocean color parameters can be derived by satellite globally. These terms, including chlorophyll concentration (Chl), particulate backscattering coefficients (bbp), photosynthetically available radiation (PAR), have been proved to be related to NPP of phytoplankton. Based on these parameters with other auxiliary data, a carbon-based productivity model (CbPM) had been developed. The model derives phytoplankton carbon(C) from bbp and utilizes the ratios of C and Chl to describe the phytoplankton growth rates (μ) which has physiological dependencies on light (through variations in PAR), nutrients, and temperature. This paper indicated how the uncertainties in satellite derived parameters (Chl, bbp and PAR) propagated through the CbPM using Monte Carlo method. Comparisons on the individual contributor to the random uncertainty in NPP between these input items were discussed. The analysis results showed that among the three parameters, the biggest contribution to the uncertainty in the model output came from Chl. Therefore, improvements in the accuracy of Chl would have the largest potential to improve the ability of CbPM in estimating NPP of phytoplankton.