| 基于浮游植物吸收的海洋初级生产力模型的不确定性分析 |
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| 引用本文： | 陶醉,马胜,杨晓峰,王琰.基于浮游植物吸收的海洋初级生产力模型的不确定性分析[J].海洋学报(英文版),2017,36(6):112-121. |
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| 作者姓名： | 陶醉 马胜 杨晓峰 王琰 |
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| 作者单位： | 中国科学院遥感与数字地球研究所遥感国家重点实验室, 中国 北京, 100101,洛斯达遥感技术有限公司, 中国 北京, 100120,中国科学院遥感与数字地球研究所遥感国家重点实验室, 中国 北京, 100101,国家环境保护环境影响评价数值模拟重点实验室, 中国 北京, 100012 |
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| 基金项目： | The National Natural Science Fundation of China under contract No. 41501389; the Foundation of State Key Laboratory of Remote Sensing Science in China under contract No. OFSLRSS201509. |
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| 摘 要： | Satellite-derived phytoplankton pigment absorption(a_(ph)) has been used as a key predictor of phytoplankton photosynthetic efficiency to estimate global ocean net primary production(NPP). In this study, an a_(ph)-based NPP model(Ab PM) with four input parameters including the photosynthetically available radiation(PAR), diffuse attenuation at 490 nm(K_d(490)), euphotic zone depth(Z_(eu)) and the phytoplankton pigment absorption coefficient(a_(ph)) is compared with the chlorophyll-based model and carbon-based model. It is found that the Ab PM has significant advantages on the ocean NPP estimation compared with the chlorophyll-based model and carbonbased model. For example, Ab PM greatly outperformed the other two models at most monitoring sites and had the best accuracy, including the smallest values of RMSD and bias for the NPP estimate, and the best correlation between the observations and the modeled NPPs. In order to ensure the robustness of the model, the uncertainty in NPP estimates of the Ab PM was assessed using a Monte Carlo simulation. At first, the frequency histograms of simple difference(δ), and logarithmic difference(δ~(LOG)) between model estimates and in situ data confirm that the two input parameters(Z_(eu) and PAR) approximate the Normal Distribution, and another two input parameters(a_(ph) and K_d(490)) approximate the logarithmic Normal Distribution. Second, the uncertainty in NPP estimates in the Ab PM was assessed by using the Monte Carlo simulation. Here both the PB(percentage bias), defined as the ratio of ΔNPP to the retrieved NPP, and the CV(coefficient of variation), defined as the ratio of the standard deviation to the mean are used to indicate the uncertainty in the NPP brought by input parameter to Ab PM model. The uncertainty related to magnitude is denoted by PB and the uncertainty related to scatter range is denoted by CV.Our investigations demonstrate that PB of NPP uncertainty brought by all parameters with an annual mean of5.5% covered a range of –5%–15% for the global ocean. The PB uncertainty of Ab PM model was mainly caused by a_(ph); the PB of NPP uncertainty brought by a_(ph) had an annual mean of 4.1% for the global ocean. The CV brought by all the parameters with an annual mean of 105% covered a range of 98%–134% for global ocean. For the coastal zone of Antarctica with higher productivity, the PB and CV of NPP uncertainty brought by all parameters had annual means of 7.1% and 121%, respectively, which are significantly larger than those obtained in the global ocean. This study suggests that the NPPs estimated by Ab PM model are more accurate than others, but the magnitude and scatter range of NPP errors brought by input parameter to Ab PM model could not be neglected,especially in the coastal area with high productivity. So the improving accuracy of satellite retrieval of input parameters should be necessary. The investigation also confirmed that the SST related correction is effective for improving the model accuracy in low temperature condition.
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| 关 键 词： | 海洋初级生产力 浮游植物吸收 卫星遥感 不确定性 蒙特卡洛模拟 |
| 收稿时间： | 2016/4/8 0:00:00 |
| 修稿时间： | 2016/7/28 0:00:00 |
Assessing the uncertainties of phytoplankton absorption-based model estimates of marine net primary productivity |
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| TAO Zui,MA Sheng,YANG Xiaofeng and WANG Yan.Assessing the uncertainties of phytoplankton absorption-based model estimates of marine net primary productivity[J].Acta Oceanologica Sinica,2017,36(6):112-121. |
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| Authors: | TAO Zui MA Sheng YANG Xiaofeng and WANG Yan |
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| Institution: | 1.State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China2.Beijing North-Star Digital Remote Sensing Technology Co. Ltd., Beijing 100120, China3.State Environmental Protection Key Laboratory of Numerical Modeling for Environment Impact Assessment, Beijing 100012, China |
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| Abstract: | Satellite-derived phytoplankton pigment absorption (a ph) has been used as a key predictor of phytoplankton photosynthetic efficiency to estimate global ocean net primary production (NPP). In this study, an a ph-based NPP model (AbPM) with four input parameters including the photosynthetically available radiation (PAR), diffuse attenuation at 490 nm (K d(490)), euphotic zone depth (Z eu) and the phytoplankton pigment absorption coefficient (a ph) is compared with the chlorophyll-based model and carbon-based model. It is found that the AbPM has significant advantages on the ocean NPP estimation compared with the chlorophyll-based model and carbonbased model. For example, AbPM greatly outperformed the other two models at most monitoring sites and had the best accuracy, including the smallest values of RMSD and bias for the NPP estimate, and the best correlation between the observations and the modeled NPPs. In order to ensure the robustness of the model, the uncertainty in NPP estimates of the AbPM was assessed using a Monte Carlo simulation. At first, the frequency histograms of simple difference (δ), and logarithmic difference (δ LOG) between model estimates and in situ data confirm that the two input parameters (Z eu and PAR) approximate the Normal Distribution, and another two input parameters (a ph and K d(490)) approximate the logarithmic Normal Distribution. Second, the uncertainty in NPP estimates in the AbPM was assessed by using the Monte Carlo simulation. Here both the PB (percentage bias), defined as the ratio of ΔNPP to the retrieved NPP, and the CV (coefficient of variation), defined as the ratio of the standard deviation to the mean are used to indicate the uncertainty in the NPP brought by input parameter to AbPM model. The uncertainty related to magnitude is denoted by PB and the uncertainty related to scatter range is denoted by CV. Our investigations demonstrate that PB of NPP uncertainty brought by all parameters with an annual mean of 5.5% covered a range of–5%–15% for the global ocean. The PB uncertainty of AbPM model was mainly caused by a ph; the PB of NPP uncertainty brought by a ph had an annual mean of 4.1% for the global ocean. The CV brought by all the parameters with an annual mean of 105% covered a range of 98%–134% for global ocean. For the coastal zone of Antarctica with higher productivity, the PB and CV of NPP uncertainty brought by all parameters had annual means of 7.1% and 121%, respectively, which are significantly larger than those obtained in the global ocean. This study suggests that the NPPs estimated by AbPM model are more accurate than others, but the magnitude and scatter range of NPP errors brought by input parameter to AbPM model could not be neglected, especially in the coastal area with high productivity. So the improving accuracy of satellite retrieval of input parameters should be necessary. The investigation also confirmed that the SST related correction is effective for improving the model accuracy in low temperature condition. |
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| Keywords: | marine net primary production phytoplankton pigment absorption satellite remote sensing uncertainty analysis Monte Carlo simulation |
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