A new model for the remote sensing of absorption coefficients of phytoplankton aph (λ) in oceanic and coastal waters is developed and tested with SeaWiFS and MODIS-Aqua data. The model is derived from a rela-tionship...A new model for the remote sensing of absorption coefficients of phytoplankton aph (λ) in oceanic and coastal waters is developed and tested with SeaWiFS and MODIS-Aqua data. The model is derived from a rela-tionship of the remote sensing reflectance ratio Rrs (670)/Rrs (490) and aph (490) and aph (670) (from large in-situ data sets). When compared with over 470 independent in-situ data sets, the model provides accurate retrievals of the aph (λ) across the visible spectrum, with mean relative error less than 8%, slope close to unity and R2 greater than 0.8. Further comparison of the SeaWiFS-derived aph (λ) with in-situ aph (λ) values gives similar and consistent results. The model when used for analysis of MODIS-Aqua imagery, provides more realistic values of the phytoplankton absorption coefficients capturing spatial structures of the massive algal blooms in surface waters of the Arabian Sea. These results demonstrate that the new algorithm works well for both the coastal and open ocean waters observed and suggest a potential of using remote sensing to provide knowledge on the shape of phytoplankton absorption spectra that are a requirement in many inverse models to estimate phytoplankton pigment concentrations and for input into bio-optical models that predict carbon fixation rates for the global ocean.展开更多
The temporal and spatial variabilities of phytoplankton absorption coefficients （a ph （λ）） and their relationships with physical processes in the northern South China Sea were examined, based on in situ data coll...The temporal and spatial variabilities of phytoplankton absorption coefficients （a ph （λ）） and their relationships with physical processes in the northern South China Sea were examined, based on in situ data collected from two cruise surveys during May 14 to 25, 2001 and November 2 to 21, 2002. Significant changes in the surface water in a ph values and B/R ratios （a ph （440）/a ph （675）） were observed in May, which were caused by a phytoplankton bloom on the inner shelf stimulated by a large river plume due to heavy precipitation. This is consistent with the observed one order of magnitude elevation of chlorophyll a and a shift from a pico/nano dominated phytoplankton community to one dominated by micro-algae. Enhanced vertical mixing due to strengthened northeast monsoon in November has been observed to result in higher surface a ph （675） （0.002–0.006 m-1 higher） and less pronounced subsurface maximum on the outer shelf/slope in November as compared with that in May. Measurements of a ph and B/R ratios from three transects in November revealed a highest surface a ph （675） immediately outside the mouth of the Zhujiang （Pearl） River Estuary, whereas lower a ph （675） and higher B/R ratios were featured in the outer shelf/slope waters, demonstrating the respective influence of the Zhujiang River plume and the oligotrophic water of the South China Sea. The difference in spectral shapes of phytoplankton absorption （measured by B/R ratios and bathochromic shifts） on these three transects infers that picoprocaryotes are the major component of the phytoplankton community on the outer shelf/slope rather than on the inner shelf. A regional tuning of the phytoplankton absorption spectral model （Carder et al., 1999） was attempted, demonstrating a greater spatial variation than temporal variation in the lead parameter a 0 （λ）. It was thus implicated that region-based parameterization of ocean color remote sensing algorithms in the northern South China Sea was mandatory.展开更多
The absorption spectrum of phytoplankton is an important bio-optical parameter for ocean color hyperspectral remote sensing;its magnitude and shape can be aff ected considerably by pigment composition and concentratio...The absorption spectrum of phytoplankton is an important bio-optical parameter for ocean color hyperspectral remote sensing;its magnitude and shape can be aff ected considerably by pigment composition and concentration. We conducted Gaussian decomposition to the absorption spectra of phytoplankton pigment and studied the spectral components of the phytoplankton, in which the package effect was investigated using pigment concentration data and phytoplankton absorption spectra. The decomposition results were compared with the corresponding concentrations of the five main pigment groups (chlorophylls a , b , and c , photo-synthetic carotenoids (PSC), and photo-protective carotenoids (PPC)). The results indicate that the majority of residual errors in the Gaussian decomposition are <0.001 m^-1 , and R 2 of the power regression between characteristic bands and HPLC pigment concentrations (except for chlorophyll b) was 0.65 or greater for surface water samples at autumn cruise. In addition, we determined a strong predictive capability for chlorophylls a , c , PPC, and PSC. We also tested the estimation of pigment concentrations from the empirical specific absorption coeffi cient of pigment composition. The empirical decomposition showed that the Ficek model was the closest to the original spectra with the smallest residual errors.The pigment decomposition results and HPLC measurements of pigment concentration are in a high consistency as the scatter plots are distributed largely near the 1:1 line in spite of prominent seasonal variations. The Wozniak model showed a better fit than the Ficek model for Ch1 a , and the median relative error was small. The pigment component information estimated from the phytoplankton absorption spectra can help better remote sensing of hyperspectral ocean color that related to the changes in phytoplankton communities and varieties.展开更多
海洋初级生产过程是海洋碳循环的重要组成部分,影响生物地球化学循环和全球气候变化。浮游植物作为海洋初级生产的主要贡献者,按粒径大小可分为小型(micro粒级,>20μm)、微型(nano粒级,2~20μm)和微微型(pico粒级,<2μm)。不同粒...海洋初级生产过程是海洋碳循环的重要组成部分,影响生物地球化学循环和全球气候变化。浮游植物作为海洋初级生产的主要贡献者,按粒径大小可分为小型(micro粒级,>20μm)、微型(nano粒级,2~20μm)和微微型(pico粒级,<2μm)。不同粒级浮游植物初级生产力(size-fractionated primary production,PP_(size))对总初级生产力贡献不同,在海洋物质能量流动及碳循环中扮演着不同角色。本文基于2019年南海西部夏季航次12个站位的生物光学剖面数据,研究了南海西部分粒级浮游植物叶绿素a浓度和初级生产力的空间分布及它们对总叶绿素a浓度和总初级生产力的贡献百分比。利用各粒级670nm波段的浮游植物吸收系数[size-fractionated phytoplankton absorption coefficient at 670nm,a_(ph-size)(670)]与光合有效辐射(photosynthetically active radiation,PAR)的乘积[a_(ph-size)(670)×PAR]建立了南海分粒级初级生产力算法,对于小型、微型和微微型浮游植物数据集,log[a_(ph-size)(670)×PAR]与log(PP_(size))之间的决定系数R^(2)分别为0.64、0.76和0.67。交叉验证的结果表明,该算法具有良好的泛化性能。其性能显著优于仅利用浮游植物吸收系数估算分粒级初级生产力的算法,表明PAR是影响分粒级初级生产力变化的重要因素之一。采用基于叶绿素a浓度的算法估算各粒级初级生产力时,针对小型和微微型浮游植物数据集,该算法的性能与本文构建的算法近似;但针对微型浮游植物数据集时,基于叶绿素a浓度的算法性能显著较低,这可能归因于微型浮游植物吸收系数与叶绿素a浓度间的弱相关性。展开更多
Satellite-derived phytoplankton pigment absorption （aph） has been used as a key predictor of phytoplankton photosynthetic efficiency to estimate global ocean net primary production （NPP）. In this study, an aph-bas...Satellite-derived phytoplankton pigment absorption （aph） has been used as a key predictor of phytoplankton photosynthetic efficiency to estimate global ocean net primary production （NPP）. In this study, an aph-based NPP model （AbPM） with four input parameters including the photosynthetically available radiation （PAR）, diffuse attenuation at 490 nm （Ka（490））, euphotic zone depth （Zeu） and the phytoplankton pigment absorption coefficient （aph） 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 carbon- based 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 （fi）, and logarithmic difference （~LOG） between model estimates and in situ data confirm that the two input parameters （Zeu and PAR） approximate the Normal Distribution, and another two input parameters （aph and Ka（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 ANPP 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% c展开更多
文摘A new model for the remote sensing of absorption coefficients of phytoplankton aph (λ) in oceanic and coastal waters is developed and tested with SeaWiFS and MODIS-Aqua data. The model is derived from a rela-tionship of the remote sensing reflectance ratio Rrs (670)/Rrs (490) and aph (490) and aph (670) (from large in-situ data sets). When compared with over 470 independent in-situ data sets, the model provides accurate retrievals of the aph (λ) across the visible spectrum, with mean relative error less than 8%, slope close to unity and R2 greater than 0.8. Further comparison of the SeaWiFS-derived aph (λ) with in-situ aph (λ) values gives similar and consistent results. The model when used for analysis of MODIS-Aqua imagery, provides more realistic values of the phytoplankton absorption coefficients capturing spatial structures of the massive algal blooms in surface waters of the Arabian Sea. These results demonstrate that the new algorithm works well for both the coastal and open ocean waters observed and suggest a potential of using remote sensing to provide knowledge on the shape of phytoplankton absorption spectra that are a requirement in many inverse models to estimate phytoplankton pigment concentrations and for input into bio-optical models that predict carbon fixation rates for the global ocean.
基金The National Basic Research Program of China under contract Nos 2009CB421200, 2009CB421201the National Natural Science Foundation of China under contract No40821063High-Tech R&D Program of China under contract Nos2006AA09A302 and 2008AA09Z108
文摘The temporal and spatial variabilities of phytoplankton absorption coefficients （a ph （λ）） and their relationships with physical processes in the northern South China Sea were examined, based on in situ data collected from two cruise surveys during May 14 to 25, 2001 and November 2 to 21, 2002. Significant changes in the surface water in a ph values and B/R ratios （a ph （440）/a ph （675）） were observed in May, which were caused by a phytoplankton bloom on the inner shelf stimulated by a large river plume due to heavy precipitation. This is consistent with the observed one order of magnitude elevation of chlorophyll a and a shift from a pico/nano dominated phytoplankton community to one dominated by micro-algae. Enhanced vertical mixing due to strengthened northeast monsoon in November has been observed to result in higher surface a ph （675） （0.002–0.006 m-1 higher） and less pronounced subsurface maximum on the outer shelf/slope in November as compared with that in May. Measurements of a ph and B/R ratios from three transects in November revealed a highest surface a ph （675） immediately outside the mouth of the Zhujiang （Pearl） River Estuary, whereas lower a ph （675） and higher B/R ratios were featured in the outer shelf/slope waters, demonstrating the respective influence of the Zhujiang River plume and the oligotrophic water of the South China Sea. The difference in spectral shapes of phytoplankton absorption （measured by B/R ratios and bathochromic shifts） on these three transects infers that picoprocaryotes are the major component of the phytoplankton community on the outer shelf/slope rather than on the inner shelf. A regional tuning of the phytoplankton absorption spectral model （Carder et al., 1999） was attempted, demonstrating a greater spatial variation than temporal variation in the lead parameter a 0 （λ）. It was thus implicated that region-based parameterization of ocean color remote sensing algorithms in the northern South China Sea was mandatory.
基金Supported by the National Natural Science Foundation of China(Nos.91638201,41276184,41771388 41471308,41571361,41701402)the Strategic Priority Research Program of Chinese Academy of Sciences(No.XDA2003030201)+2 种基金the National Key Research and Development Program of China(Nos.2017YFB0503005,2016YFC1400903,2016YFB0501502)the High Resolution Earth Observation Systems of National Science and Technology Major Projects(No.41-Y20A31-9003-15/17)the China-Sri Lanka Joint Research and Demonstration Center for Water Technology,and the State Development and Reform Commission’s Special Financial Projects(No.2017ST000602)
文摘The absorption spectrum of phytoplankton is an important bio-optical parameter for ocean color hyperspectral remote sensing;its magnitude and shape can be aff ected considerably by pigment composition and concentration. We conducted Gaussian decomposition to the absorption spectra of phytoplankton pigment and studied the spectral components of the phytoplankton, in which the package effect was investigated using pigment concentration data and phytoplankton absorption spectra. The decomposition results were compared with the corresponding concentrations of the five main pigment groups (chlorophylls a , b , and c , photo-synthetic carotenoids (PSC), and photo-protective carotenoids (PPC)). The results indicate that the majority of residual errors in the Gaussian decomposition are <0.001 m^-1 , and R 2 of the power regression between characteristic bands and HPLC pigment concentrations (except for chlorophyll b) was 0.65 or greater for surface water samples at autumn cruise. In addition, we determined a strong predictive capability for chlorophylls a , c , PPC, and PSC. We also tested the estimation of pigment concentrations from the empirical specific absorption coeffi cient of pigment composition. The empirical decomposition showed that the Ficek model was the closest to the original spectra with the smallest residual errors.The pigment decomposition results and HPLC measurements of pigment concentration are in a high consistency as the scatter plots are distributed largely near the 1:1 line in spite of prominent seasonal variations. The Wozniak model showed a better fit than the Ficek model for Ch1 a , and the median relative error was small. The pigment component information estimated from the phytoplankton absorption spectra can help better remote sensing of hyperspectral ocean color that related to the changes in phytoplankton communities and varieties.
文摘海洋初级生产过程是海洋碳循环的重要组成部分,影响生物地球化学循环和全球气候变化。浮游植物作为海洋初级生产的主要贡献者,按粒径大小可分为小型(micro粒级,>20μm)、微型(nano粒级,2~20μm)和微微型(pico粒级,<2μm)。不同粒级浮游植物初级生产力(size-fractionated primary production,PP_(size))对总初级生产力贡献不同,在海洋物质能量流动及碳循环中扮演着不同角色。本文基于2019年南海西部夏季航次12个站位的生物光学剖面数据,研究了南海西部分粒级浮游植物叶绿素a浓度和初级生产力的空间分布及它们对总叶绿素a浓度和总初级生产力的贡献百分比。利用各粒级670nm波段的浮游植物吸收系数[size-fractionated phytoplankton absorption coefficient at 670nm,a_(ph-size)(670)]与光合有效辐射(photosynthetically active radiation,PAR)的乘积[a_(ph-size)(670)×PAR]建立了南海分粒级初级生产力算法,对于小型、微型和微微型浮游植物数据集,log[a_(ph-size)(670)×PAR]与log(PP_(size))之间的决定系数R^(2)分别为0.64、0.76和0.67。交叉验证的结果表明,该算法具有良好的泛化性能。其性能显著优于仅利用浮游植物吸收系数估算分粒级初级生产力的算法,表明PAR是影响分粒级初级生产力变化的重要因素之一。采用基于叶绿素a浓度的算法估算各粒级初级生产力时,针对小型和微微型浮游植物数据集,该算法的性能与本文构建的算法近似;但针对微型浮游植物数据集时,基于叶绿素a浓度的算法性能显著较低,这可能归因于微型浮游植物吸收系数与叶绿素a浓度间的弱相关性。
基金The National Natural Science Fundation of China under contract No.41501389the Foundation of State Key Laboratory of Remote Sensing Science in China under contract No.OFSLRSS201509
文摘Satellite-derived phytoplankton pigment absorption （aph） has been used as a key predictor of phytoplankton photosynthetic efficiency to estimate global ocean net primary production （NPP）. In this study, an aph-based NPP model （AbPM） with four input parameters including the photosynthetically available radiation （PAR）, diffuse attenuation at 490 nm （Ka（490））, euphotic zone depth （Zeu） and the phytoplankton pigment absorption coefficient （aph） 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 carbon- based 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 （fi）, and logarithmic difference （~LOG） between model estimates and in situ data confirm that the two input parameters （Zeu and PAR） approximate the Normal Distribution, and another two input parameters （aph and Ka（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 ANPP 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% c
