CN117592316B - Method, system and device for reconstructing air-sea carbon flux based on remote sensing data assimilation - Google Patents
Method, system and device for reconstructing air-sea carbon flux based on remote sensing data assimilation Download PDFInfo
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Abstract
本发明公开一种基于遥感资料同化的海气碳通量重构方法、系统及装置，方法包括：基于溶解无机碳、溶解有机碳及颗粒有机碳中相关海洋碳影响因素，构建三维碳循环模型；获取海洋盐度数据，结合海洋总碱度与海洋盐度数据的相关性，建立海洋总碱度参数化模型；获取遥感二氧化碳分压数据，将遥感二氧化碳分压数据与三维碳循环模型进行耦合，结合总碱度参数化模型，得到模拟二氧化碳分压模型，进而得到二氧化碳分压数据；基于二氧化碳分压数据，得到海气界面间二氧化碳分压差，进而得到海气碳通量数据。本方法解决了现有遥感资料中海气碳通量数据的缺失问题，显著提高了碳循环相关参数的模拟精度，为海洋研究提供了数据支撑。
The present invention discloses a method, system and device for reconstructing air-sea carbon flux based on remote sensing data assimilation, the method comprising: constructing a three-dimensional carbon cycle model based on relevant ocean carbon influencing factors in dissolved inorganic carbon, dissolved organic carbon and particulate organic carbon; acquiring ocean salinity data, combining the correlation between ocean total alkalinity and ocean salinity data, and establishing an ocean total alkalinity parameterization model; acquiring remote sensing carbon dioxide partial pressure data, coupling the remote sensing carbon dioxide partial pressure data with the three-dimensional carbon cycle model, combining the total alkalinity parameterization model, obtaining a simulated carbon dioxide partial pressure model, and then obtaining carbon dioxide partial pressure data; based on the carbon dioxide partial pressure data, obtaining the carbon dioxide partial pressure difference between the air-sea interface, and then obtaining air-sea carbon flux data. This method solves the problem of missing air-sea carbon flux data in existing remote sensing data, significantly improves the simulation accuracy of carbon cycle related parameters, and provides data support for ocean research.
Description
技术领域Technical Field
本发明涉及海气测量领域，尤其涉及一种基于遥感资料同化的海气碳通量重构方法、系统及装置。The present invention relates to the field of sea-air measurement, and in particular to a sea-air carbon flux reconstruction method, system and device based on remote sensing data assimilation.
背景技术Background technique
海洋与大气之间的能量及物质交换是生物地球循环的重要研究内容，在相互制约的海洋系统中，海气碳通量是实现海洋与大气之间相互作用的重要途径，大气中的碳很大一部分以二氧化碳的形式进入海洋，同时海气碳通量表示了海洋与大气之间的能量交换幅度，在一定程度上影响了全球气候变化，因此对海气碳通量的研究具有重要的现实意义。The exchange of energy and matter between the ocean and the atmosphere is an important research topic in the biogeo-cyclical system. In the mutually constrained marine system, the air-sea carbon flux is an important way to achieve the interaction between the ocean and the atmosphere. A large part of the carbon in the atmosphere enters the ocean in the form of carbon dioxide. At the same time, the air-sea carbon flux represents the energy exchange between the ocean and the atmosphere, which affects global climate change to a certain extent. Therefore, the study of the air-sea carbon flux has important practical significance.
截止目前，在现有技术中海洋碳通量的常规观测方法主要有遥感、箱法及直接测量法等，基于遥感的观测方法通过观测大气二氧化碳含量的变化情况计算碳通量，但是此种方法无法直接观测且所得的海气碳通量相关数据容易受天气影响，存在数据缺失的情况；基于箱法的观测精度受测量仪器影响较大，测量范围小且误差较大；直接测量法无法进行长期原位的海气碳通量观测。Up to now, the conventional observation methods of ocean carbon flux in the existing technology mainly include remote sensing, box method and direct measurement method. The observation method based on remote sensing calculates carbon flux by observing the changes in atmospheric carbon dioxide content, but this method cannot directly observe and the obtained sea-air carbon flux related data is easily affected by the weather, and there are data missing; the observation accuracy based on the box method is greatly affected by the measuring instrument, the measurement range is small and the error is large; the direct measurement method cannot conduct long-term in-situ sea-air carbon flux observations.
因此，目前海气碳通量的计算方式存在局限性导致计算结果非常不精准，因此对海洋数据的相关研究造成严重影响。Therefore, the current method of calculating the air-sea carbon flux has limitations, which leads to very inaccurate calculation results, thus causing serious impact on related research on ocean data.
发明内容Summary of the invention
本发明针对现有技术中的缺点，提供了一种基于遥感资料同化的海气碳通量重构方法、系统及装置。In view of the shortcomings of the prior art, the present invention provides a method, system and device for reconstructing air-sea carbon flux based on remote sensing data assimilation.
为了解决上述问题，本发明通过下述技术方案得以解决：In order to solve the above problems, the present invention is solved by the following technical solutions:
一种基于遥感资料同化的海气碳通量重构方法，包括以下步骤：A method for reconstructing air-sea carbon flux based on remote sensing data assimilation comprises the following steps:
基于海洋碳影响因素，构建三维碳循环模型，其中，海洋碳影响因素包括溶解无机碳、溶解有机碳及颗粒有机碳；Based on the factors affecting ocean carbon, a three-dimensional carbon cycle model is constructed, where the factors affecting ocean carbon include dissolved inorganic carbon, dissolved organic carbon and particulate organic carbon;
获取海洋盐度数据，基于海洋总碱度及海洋盐度数据，构建海洋总碱度参数化模型；Obtain ocean salinity data, and build a parameterized model of ocean total alkalinity based on ocean total alkalinity and ocean salinity data;
获取遥感二氧化碳分压数据，将遥感二氧化碳分压数据及海洋总碱度参数化模型耦合至三维碳循环模型中，得到模拟二氧化碳分压模型，进而得到二氧化碳分压数据；Acquire remote sensing carbon dioxide partial pressure data, couple the remote sensing carbon dioxide partial pressure data and the ocean total alkalinity parameterized model to the three-dimensional carbon cycle model to obtain a simulated carbon dioxide partial pressure model, and then obtain carbon dioxide partial pressure data;
基于二氧化碳分压数据，得到海气界面间二氧化碳分压差，基于海气界面间二氧化碳分压差构建模拟海气碳通量模型，进而得到海气碳通量数据。Based on the carbon dioxide partial pressure data, the carbon dioxide partial pressure difference between the sea and air interface is obtained. Based on the carbon dioxide partial pressure difference between the sea and air interface, a simulated air-sea carbon flux model is constructed to obtain the air-sea carbon flux data.
作为一种可实施方式，所述构建海洋总碱度参数化模型，包括以下步骤：As an implementable method, the construction of the ocean total alkalinity parameterized model includes the following steps:
基于海洋盐度数据，对海洋总碱度进行多项式拟合，通过平衡参数量及拟合精度之间的关系，得到海洋总碱度参数化模型，表示如下：Based on the ocean salinity data, a polynomial fitting of the total alkalinity of the ocean is performed. By balancing the relationship between the parameter quantity and the fitting accuracy, a parameterized model of the total alkalinity of the ocean is obtained, which is expressed as follows:
其中，表示海洋总碱度，/>表示海洋盐度数据，/>、/>、/>、/>表示常量。in, represents the total alkalinity of the ocean,/> Represents ocean salinity data, /> 、/> 、/> 、/> Represents a constant.
作为一种可实施方式，所述将遥感二氧化碳分压数据及海洋总碱度参数化模型耦合至三维碳循环模型中，得到模拟二氧化碳分压模型，进而得到二氧化碳分压数据，包括以下步骤：As an implementable method, coupling the remote sensing carbon dioxide partial pressure data and the ocean total alkalinity parameterized model to the three-dimensional carbon cycle model to obtain a simulated carbon dioxide partial pressure model, and then obtaining the carbon dioxide partial pressure data, includes the following steps:
基于遥感二氧化碳分压数据与三维碳循环模型中溶解无机碳线性模型进行同化，得到溶解无机碳变化模型；Based on the assimilation of remote sensing carbon dioxide partial pressure data with the dissolved inorganic carbon linear model in the three-dimensional carbon cycle model, a dissolved inorganic carbon change model was obtained;
基于碳酸-碳酸盐系统平衡方程并结合海洋总碱度，得到海洋总碱度参数；Based on the carbonic acid-carbonate system equilibrium equation and combined with the total alkalinity of the ocean, the total alkalinity parameter of the ocean is obtained;
基于海洋总碱度参数及溶解无机碳变化模型，建立模拟二氧化碳分压模型，得到二氧化碳分压数据。Based on the ocean total alkalinity parameters and dissolved inorganic carbon change model, a simulation carbon dioxide partial pressure model was established to obtain carbon dioxide partial pressure data.
作为一种可实施方式，所述溶解无机碳变化模型，表示如下：As an implementable embodiment, the dissolved inorganic carbon change model is expressed as follows:
其中，表示遥感二氧化碳分压数据，/>表示三维碳循环模型的二氧化碳分压数据，/>表示溶解无机碳，p1表示常量。in, Represents remote sensing carbon dioxide partial pressure data, /> The carbon dioxide partial pressure data of the three-dimensional carbon cycle model is shown. represents dissolved inorganic carbon, and p1 represents a constant.
作为一种可实施方式，所述模拟二氧化碳分压模型，表示如下：As an implementable embodiment, the simulated carbon dioxide partial pressure model is expressed as follows:
其中，表示二氧化碳在海水中的溶解度，/>、/>表示海水中二氧化碳的平衡常数，/>表示逸度常数，/>表示温度，/>表示大气压，/>表示模拟二氧化碳分压数据，表示海洋总碱度参数。in, represents the solubility of carbon dioxide in seawater,/> 、/> represents the equilibrium constant of carbon dioxide in seawater,/> represents the fugacity constant, /> Indicates temperature, /> represents atmospheric pressure, /> represents the simulated carbon dioxide partial pressure data, Represents the total alkalinity parameter of the ocean.
作为一种可实施方式，所述海气界面间二氧化碳分压差，通过以下计算方式得到：As an implementable method, the carbon dioxide partial pressure difference between the sea and air interfaces is obtained by the following calculation method:
所述模拟海气碳通量模型，表示如下：The simulated air-sea carbon flux model is expressed as follows:
其中，表示气体传输系数，/>，/>表示海水中二氧化碳的溶解度，/>表示海气界面间二氧化碳分压差，/>表示海平面10米处风速，/>表示施密特数，/>表示表层海水的二氧化碳分压数据，/>表示海面大气的二氧化碳分压数据，/>表示海气碳通量数据。in, represents the gas transmission coefficient, /> ,/> Indicates the solubility of carbon dioxide in seawater, /> represents the difference in partial pressure of carbon dioxide between the air and sea interface,/> Indicates the wind speed at 10 meters above sea level, /> represents the Schmidt number, /> Indicates the carbon dioxide partial pressure data of surface seawater, /> Indicates the carbon dioxide partial pressure data of the sea surface atmosphere, /> Represents air-sea carbon flux data.
一种基于遥感资料同化的海气碳通量重构系统，包括海洋碳模型建立模块、碱度模型构建模块、分压数据计算模块及海气碳通量计算模块；A sea-air carbon flux reconstruction system based on remote sensing data assimilation, including an ocean carbon model building module, an alkalinity model building module, a partial pressure data calculation module and a sea-air carbon flux calculation module;
所述海洋碳模型建立模块，基于海洋碳影响因素，构建三维碳循环模型，其中，海洋碳影响因素包括溶解无机碳、溶解有机碳及颗粒有机碳；The ocean carbon model building module constructs a three-dimensional carbon cycle model based on ocean carbon influencing factors, wherein the ocean carbon influencing factors include dissolved inorganic carbon, dissolved organic carbon and particulate organic carbon;
所述碱度模型构建模块，获取海洋盐度数据，基于海洋总碱度及海洋盐度数据，构建海洋总碱度参数化模型；The alkalinity model construction module obtains ocean salinity data and constructs a parameterized model of ocean total alkalinity based on the ocean total alkalinity and ocean salinity data;
所述分压数据计算模块，获取遥感二氧化碳分压数据，将遥感二氧化碳分压数据及海洋总碱度参数化模型耦合至三维碳循环模型中，得到模拟二氧化碳分压模型，进而得到二氧化碳分压数据；The partial pressure data calculation module obtains remote sensing carbon dioxide partial pressure data, couples the remote sensing carbon dioxide partial pressure data and the ocean total alkalinity parameterized model to the three-dimensional carbon cycle model, obtains a simulated carbon dioxide partial pressure model, and then obtains carbon dioxide partial pressure data;
所述海气碳通量计算模块，基于二氧化碳分压数据，得到海气界面间二氧化碳分压差，基于海气界面间二氧化碳分压差构建模拟海气碳通量模型，进而得到海气碳通量数据。The air-sea carbon flux calculation module obtains the carbon dioxide partial pressure difference between the air and sea interfaces based on the carbon dioxide partial pressure data, constructs a simulated air-sea carbon flux model based on the carbon dioxide partial pressure difference between the air and sea interfaces, and then obtains the air-sea carbon flux data.
作为一种可实施方式，所述分压数据计算模块，被设置为：As an implementable embodiment, the voltage division data calculation module is configured as follows:
基于遥感二氧化碳分压数据与三维碳循环模型中溶解无机碳线性模型进行同化，得到溶解无机碳变化模型；Based on the assimilation of remote sensing carbon dioxide partial pressure data with the dissolved inorganic carbon linear model in the three-dimensional carbon cycle model, a dissolved inorganic carbon change model was obtained;
基于碳酸-碳酸盐系统平衡方程并结合海洋总碱度，得到海洋总碱度参数；Based on the carbonic acid-carbonate system equilibrium equation and combined with the total alkalinity of the ocean, the total alkalinity parameter of the ocean is obtained;
基于海洋总碱度参数及溶解无机碳变化模型，建立模拟二氧化碳分压模型，得到二氧化碳分压数据；Based on the ocean total alkalinity parameters and dissolved inorganic carbon change model, a simulation model for carbon dioxide partial pressure was established to obtain carbon dioxide partial pressure data;
其中，所述溶解无机碳变化模型，表示如下：Wherein, the dissolved inorganic carbon change model is expressed as follows:
其中，表示遥感二氧化碳分压数据，/>表示三维碳循环模型的二氧化碳分压数据，/>表示溶解无机碳，p1表示常量；in, Represents remote sensing carbon dioxide partial pressure data, /> The carbon dioxide partial pressure data of the three-dimensional carbon cycle model is shown. represents dissolved inorganic carbon, and p1 represents a constant;
其中，所述模拟二氧化碳分压模型，表示如下：Wherein, the simulated carbon dioxide partial pressure model is expressed as follows:
其中，表示二氧化碳在海水中的溶解度，/>、/>表示海水中二氧化碳的平衡常数，/>表示逸度常数，/>表示温度，/>表示大气压，/>表示模拟二氧化碳分压数据，表示海洋总碱度参数。in, represents the solubility of carbon dioxide in seawater,/> 、/> represents the equilibrium constant of carbon dioxide in seawater,/> represents the fugacity constant, /> Indicates temperature, /> represents atmospheric pressure, /> represents the simulated carbon dioxide partial pressure data, Represents the total alkalinity parameter of the ocean.
一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，所述计算机程序被处理器执行时实现如下所述的方法：A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following method is implemented:
基于海洋碳影响因素，构建三维碳循环模型，其中，海洋碳影响因素包括溶解无机碳、溶解有机碳及颗粒有机碳；Based on the factors affecting ocean carbon, a three-dimensional carbon cycle model is constructed, where the factors affecting ocean carbon include dissolved inorganic carbon, dissolved organic carbon and particulate organic carbon;
获取海洋盐度数据，基于海洋总碱度及海洋盐度数据，构建海洋总碱度参数化模型；Obtain ocean salinity data, and build a parameterized model of ocean total alkalinity based on ocean total alkalinity and ocean salinity data;
获取遥感二氧化碳分压数据，将遥感二氧化碳分压数据及海洋总碱度参数化模型耦合至三维碳循环模型中，得到模拟二氧化碳分压模型，进而得到二氧化碳分压数据；Acquire remote sensing carbon dioxide partial pressure data, couple the remote sensing carbon dioxide partial pressure data and the ocean total alkalinity parameterized model to the three-dimensional carbon cycle model to obtain a simulated carbon dioxide partial pressure model, and then obtain carbon dioxide partial pressure data;
基于二氧化碳分压数据，得到海气界面间二氧化碳分压差，基于海气界面间二氧化碳分压差构建模拟海气碳通量模型，进而得到海气碳通量数据。Based on the carbon dioxide partial pressure data, the carbon dioxide partial pressure difference between the sea and air interface is obtained. Based on the carbon dioxide partial pressure difference between the sea and air interface, a simulated air-sea carbon flux model is constructed to obtain the air-sea carbon flux data.
一种基于遥感资料同化的海气碳通量重构装置，包括存储器、处理器以及存储在所述存储器中并在所述处理器上运行的计算机程序，所述处理器执行所述计算机程序时实现如下所述的方法：A device for reconstructing air-sea carbon flux based on remote sensing data assimilation comprises a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, the following method is implemented:
基于海洋碳影响因素，构建三维碳循环模型，其中，海洋碳影响因素包括溶解无机碳、溶解有机碳及颗粒有机碳；Based on the factors affecting ocean carbon, a three-dimensional carbon cycle model is constructed, where the factors affecting ocean carbon include dissolved inorganic carbon, dissolved organic carbon and particulate organic carbon;
获取海洋盐度数据，基于海洋总碱度及海洋盐度数据，构建海洋总碱度参数化模型；Obtain ocean salinity data, and build a parameterized model of ocean total alkalinity based on ocean total alkalinity and ocean salinity data;
获取遥感二氧化碳分压数据，将遥感二氧化碳分压数据及海洋总碱度参数化模型耦合至三维碳循环模型中，得到模拟二氧化碳分压模型，进而得到二氧化碳分压数据；Acquire remote sensing carbon dioxide partial pressure data, couple the remote sensing carbon dioxide partial pressure data and the ocean total alkalinity parameterized model to the three-dimensional carbon cycle model to obtain a simulated carbon dioxide partial pressure model, and then obtain carbon dioxide partial pressure data;
基于二氧化碳分压数据，得到海气界面间二氧化碳分压差，基于海气界面间二氧化碳分压差构建模拟海气碳通量模型，进而得到海气碳通量数据。Based on the carbon dioxide partial pressure data, the carbon dioxide partial pressure difference between the sea and air interface is obtained. Based on the carbon dioxide partial pressure difference between the sea and air interface, a simulated air-sea carbon flux model is constructed to obtain the air-sea carbon flux data.
本发明由于采用了以上技术方案，具有显著的技术效果：The present invention has significant technical effects due to the adoption of the above technical solution:
通过本发明的方法解决了现有基于遥感资料获取海气碳通量的方法中存在的数据缺失问题，同时还避免了在获取遥感资料过程中的天气状况及环境问题对数据的影响。The method of the present invention solves the data missing problem existing in the existing method of obtaining sea-air carbon flux based on remote sensing data, and also avoids the influence of weather conditions and environmental problems on the data in the process of obtaining remote sensing data.
同时基于本发明的方法，通过数据同化提高了二氧化碳分压计算的准确性，进而提高碳循环相关参数的模拟精度，为海洋研究提供有力支持。At the same time, based on the method of the present invention, the accuracy of carbon dioxide partial pressure calculation is improved through data assimilation, thereby improving the simulation accuracy of carbon cycle related parameters, providing strong support for marine research.
附图说明BRIEF DESCRIPTION OF THE DRAWINGS
为了更清楚地说明本发明实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动性的前提下，还可以根据这些附图获得其他的附图。In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.
图1是本发明方法的流程示意图；Fig. 1 is a schematic flow diagram of the method of the present invention;
图2是本发明系统的整体示意图；FIG2 is an overall schematic diagram of the system of the present invention;
图3是本发明海洋总碱度拟合示意图；FIG3 is a schematic diagram of the total alkalinity of the ocean according to the present invention;
图4是本发明模型耦合结果与实测资料对比示意图。FIG. 4 is a schematic diagram showing the comparison between the coupling results of the model of the present invention and the measured data.
具体实施方式Detailed ways
下面结合实施例对本发明做进一步的详细说明，以下实施例是对本发明的解释而本发明并不局限于以下实施例。The present invention is further described in detail below in conjunction with embodiments. The following embodiments are for explanation of the present invention but the present invention is not limited to the following embodiments.
实施例1：Embodiment 1:
一种基于遥感资料同化的海气碳通量重构方法，如图1所示，包括以下步骤：A method for reconstructing air-sea carbon flux based on remote sensing data assimilation, as shown in FIG1 , includes the following steps:
S100、基于海洋碳影响因素，构建三维碳循环模型，其中，海洋碳影响因素包括溶解无机碳、溶解有机碳及颗粒有机碳；S100. Construct a three-dimensional carbon cycle model based on the factors affecting ocean carbon, where the factors affecting ocean carbon include dissolved inorganic carbon, dissolved organic carbon and particulate organic carbon;
S200、获取海洋盐度数据，基于海洋总碱度及海洋盐度数据，构建海洋总碱度参数化模型；S200, obtaining ocean salinity data, and constructing an ocean total alkalinity parameterization model based on the ocean total alkalinity and ocean salinity data;
S300、获取遥感二氧化碳分压数据，将遥感二氧化碳分压数据及海洋总碱度参数化模型耦合至三维碳循环模型中，得到模拟二氧化碳分压模型，进而得到二氧化碳分压数据；S300, obtaining remote sensing carbon dioxide partial pressure data, coupling the remote sensing carbon dioxide partial pressure data and the ocean total alkalinity parameterized model to a three-dimensional carbon cycle model, obtaining a simulated carbon dioxide partial pressure model, and then obtaining carbon dioxide partial pressure data;
S400、基于二氧化碳分压数据，得到海气界面间二氧化碳分压差，基于海气界面间二氧化碳分压差构建模拟海气碳通量模型，进而得到海气碳通量数据。S400, based on the carbon dioxide partial pressure data, obtain the carbon dioxide partial pressure difference between the sea and air interfaces, and construct a simulated sea-air carbon flux model based on the carbon dioxide partial pressure difference between the sea and air interfaces, thereby obtaining the sea-air carbon flux data.
通过本发明的方法解决了基于遥感资料得到的海气碳通量数据存在缺失的问题，避免遥感资料受到海洋天气及环境的影响，同时基于数据拟合提高碳通量数据计算的准确率，为海洋环境研究提供数据支撑。The method of the present invention solves the problem of missing sea-air carbon flux data obtained based on remote sensing data, avoids the remote sensing data from being affected by marine weather and environment, and improves the accuracy of carbon flux data calculation based on data fitting, providing data support for marine environmental research.
三维碳循环模型是本领域通用的碳循环模型，三维碳循环模型描述了大气、海洋和生物圈之间碳的交换和转化过程，包括生物泵、溶解泵和生物地球化学过程。而海洋总碱度参数化方案主要用于描述海洋总碱度与pCO2的关系，可以通过调整海洋总碱度来优化遥感pCO2数据的准确性。海洋总碱度参数化方案在海气通量计算中起到关键作用。将三维碳循环模型和海洋总碱度参数化方案的计算结果与遥感pCO2数据相结合，可以提高数据的准确性和可靠性。这有助于更好地了解全球碳循环过程，为气候变化研究提供有力支持。考虑到海洋碳的存在形式，因此对碳循环模型的影响主要包括溶解无机碳DIC、溶解有机碳DOC及颗粒有机碳POC，三种存在形式的大致比例为2000:38:1。The three-dimensional carbon cycle model is a common carbon cycle model in this field. The three-dimensional carbon cycle model describes the exchange and transformation process of carbon between the atmosphere, ocean and biosphere, including biological pump, dissolution pump and biogeochemical process. The total alkalinity parameterization scheme of the ocean is mainly used to describe the relationship between the total alkalinity of the ocean and pCO2. The accuracy of remote sensing pCO2 data can be optimized by adjusting the total alkalinity of the ocean. The total alkalinity parameterization scheme of the ocean plays a key role in the calculation of sea-air flux. Combining the calculation results of the three-dimensional carbon cycle model and the total alkalinity parameterization scheme of the ocean with remote sensing pCO2 data can improve the accuracy and reliability of the data. This helps to better understand the global carbon cycle process and provide strong support for climate change research. Considering the existence form of marine carbon, the impact on the carbon cycle model mainly includes dissolved inorganic carbon DIC, dissolved organic carbon DOC and particulate organic carbon POC. The approximate ratio of the three forms is 2000:38:1.
海洋中的溶解无机碳DIC含量的影响因素包括盐度、海洋生物的光合作用、有机物的再矿化及碳酸钙的溶解与沉淀。随盐度的变化而变化，一般情况下，海洋中盐度越高，溶解无机碳DIC也越高，而海水盐度与降水、蒸发、淡水输入及海冰的形成融化等过程密切相关，在海洋学的相关研究中，溶解无机碳线性模型其实是呈线性关系的，通常通过归一化处理校正至同一盐度水平进行溶解无机碳DIC的比较，归一化的过程表示如下：The factors affecting the content of dissolved inorganic carbon DIC in the ocean include salinity, photosynthesis of marine organisms, remineralization of organic matter, and dissolution and precipitation of calcium carbonate. It changes with the change of salinity. Generally speaking, the higher the salinity in the ocean, the higher the dissolved inorganic carbon DIC. The salinity of seawater is closely related to precipitation, evaporation, fresh water input, and the formation and melting of sea ice. In the relevant research of oceanography, the linear model of dissolved inorganic carbon is actually a linear relationship. It is usually compared by normalization to the same salinity level. The normalization process is expressed as follows:
其中，表示归一化的溶解无机碳，/>表示盐度；in, represents the normalized dissolved inorganic carbon, /> Indicates salinity;
海洋生物光合作用的实质是将海水中的溶解无机碳DIC经过生物化学过程转化为有机碳，因此，海洋生物光合作用的强弱将对海洋中DIC的含量产生影响，在光合作用较强的海域或区间内，海水DIC的含量一般较低，反之较高；海洋有机物的再矿化过程会产生二氧化碳，从而快速水解得到HCO3-及CO3 2-离子，从而增加海洋中DIC的含量，海洋有机物再矿化过程的影响对于中深层水体DIC的含量尤为重要；海洋钙质生物生长过程中利用海洋中的CO3 2-离子合成其CaCO3壳体或骨骼，合成过程可导致海水DIC含量的降低，当CaCO3壳体或骨骼输送进入中深层海洋后会溶解，导致海洋水体中DIC含量的增加。The essence of marine biological photosynthesis is to convert dissolved inorganic carbon DIC in seawater into organic carbon through biochemical processes. Therefore, the strength of marine biological photosynthesis will affect the DIC content in the ocean. In sea areas or intervals with strong photosynthesis, the DIC content in seawater is generally lower, and vice versa. The remineralization process of marine organic matter will produce carbon dioxide, which will quickly hydrolyze to obtain HCO3- and CO 3 2- ions, thereby increasing the DIC content in the ocean. The impact of the remineralization process of marine organic matter is particularly important for the DIC content in mid- and deep-layer water bodies. During their growth, marine calcareous organisms use CO 3 2- ions in the ocean to synthesize their CaCO 3 shells or skeletons. The synthesis process can lead to a decrease in the DIC content in seawater. When the CaCO 3 shells or skeletons are transported into the mid- and deep-layer oceans, they will dissolve, leading to an increase in the DIC content in the ocean water body.
影响溶解有机碳DOC的变化因素有四个，其中，产生溶解有机碳DOC的过程有浮游植物排泄、颗粒有机碳POC溶解及底质溶出，消耗溶解有机碳DOC的过程有DOC的氧化分解，溶解有机碳DOC浓度随时间变化的表达式如下所示：There are four factors that affect the change of dissolved organic carbon DOC. Among them, the processes of producing dissolved organic carbon DOC include phytoplankton excretion, particulate organic carbon POC dissolution and bottom dissolution, and the processes of consuming dissolved organic carbon DOC include DOC oxidation and decomposition. The expression of dissolved organic carbon DOC concentration changing with time is as follows:
细菌对溶解有机碳DOC的无机化速度函数关系式表示如下：The functional relationship of the inorganicization rate of dissolved organic carbon DOC by bacteria is expressed as follows:
底质的溶出公式，表示如下：The dissolution formula of the substrate is expressed as follows:
其中，表示溶解有机碳的氧化分解速度，/>表示底质中溶解有机碳的溶出速度，/>表示模型中底层的厚度，/>表示细菌分解溶解有机碳的溶解氧半饱和常数，表示溶解有机碳的分解速度，/>表示0°C时溶出速率，/>表示温度系数，/>表示氧抑制系数。in, Indicates the oxidative decomposition rate of dissolved organic carbon, /> Indicates the dissolution rate of dissolved organic carbon in the substrate, /> Indicates the thickness of the bottom layer in the model, /> The dissolved oxygen half-saturation constant for bacterial decomposition of dissolved organic carbon, Indicates the decomposition rate of dissolved organic carbon, /> Indicates the dissolution rate at 0°C, /> represents the temperature coefficient, /> represents the oxygen inhibition coefficient.
影响颗粒有机碳POC的产生的因素包括浮游植物死亡、浮游动物死亡及浮游动物排泄，消耗的因素包括浮游动物摄食、颗粒有机碳POC的氧化分解及颗粒有机碳POC的溶解沉降作用，颗粒有机碳POC浓度随时间变化的表达式如下所示：The factors that affect the generation of particulate organic carbon (POC) include the death of phytoplankton, the death of zooplankton and the excretion of zooplankton. ... feeding of zooplankton, the oxidation and decomposition of particulate organic carbon (POC) and the dissolution and sedimentation of particulate organic carbon (POC). The expression of the change of the concentration of particulate organic carbon (POC) over time is as follows:
其中，表示细菌对颗粒有机碳的分解速度，/>表示颗粒有机碳溶解的比率，表示颗粒有机碳的沉降速度，/>表示颗粒有机碳0℃时的分解速度，/>表示温度系数，/>表示颗粒有机碳氧化分解相关的半饱和常数。in, Indicates the rate at which bacteria decompose particulate organic carbon, /> represents the ratio of particulate organic carbon dissolution, represents the settling velocity of particulate organic carbon, /> Indicates the decomposition rate of particulate organic carbon at 0°C, /> represents the temperature coefficient, /> Represents the half-saturation constant related to the oxidative decomposition of particulate organic carbon.
也就是说，以上影响因素形成的模型即为三维碳循环模型，而三维碳循环模型输出的也是溶解无机碳、溶解有机碳及颗粒有机碳。In other words, the model formed by the above influencing factors is the three-dimensional carbon cycle model, and the output of the three-dimensional carbon cycle model is also dissolved inorganic carbon, dissolved organic carbon and particulate organic carbon.
在步骤S200中，获取海洋盐度数据，基于海洋总碱度及海洋盐度数据，构建海洋总碱度参数化模型，包括以下步骤：In step S200, ocean salinity data is obtained, and a parameterized model of ocean total alkalinity is constructed based on the ocean total alkalinity and the ocean salinity data, including the following steps:
基于海洋盐度数据，对海洋总碱度进行多项式拟合，通过平衡参数量及拟合精度之间的关系，得到海洋总碱度参数化模型，表示如下：Based on the ocean salinity data, a polynomial fitting of the total alkalinity of the ocean is performed. By balancing the relationship between the parameter quantity and the fitting accuracy, a parameterized model of the total alkalinity of the ocean is obtained, which is expressed as follows:
其中，表示海洋总碱度，/>表示海洋盐度数据，/>、/>、/>、/>表示常量。in, represents the total alkalinity of the ocean,/> Represents ocean salinity data, /> 、/> 、/> 、/> Represents a constant.
海洋中的海洋总碱度变化与海洋盐度数据具有非常高的相关性，根据观测所得海洋盐度数据，通过多项式拟合，得到多项式拟合参数，进而通过平衡参数及计算量得到海洋总碱度参数化模型。The change of total alkalinity in the ocean is highly correlated with the ocean salinity data. Based on the observed ocean salinity data, polynomial fitting parameters are obtained through polynomial fitting, and then the parameterized model of total ocean alkalinity is obtained through balance parameters and calculation amounts.
比如，在一个具体的实施例中，具体多项式拟合过程如下所示：For example, in a specific embodiment, the specific polynomial fitting process is as follows:
二次多项式拟合结果，表示如下：The quadratic polynomial fitting results are expressed as follows:
三次多项式拟合结果，表示如下：The cubic polynomial fitting results are expressed as follows:
四次多项式拟合结果，表示如下：The quartic polynomial fitting results are expressed as follows:
也就是说，、/>、/>、/>表示常量如公式中所示，多项式拟合结果图如图3所示，通过将拟合结果精度与拟合参数量达到平衡，选择三次多项式拟合结果作为海洋总碱度参数化模型。That is to say, 、/> 、/> 、/> The constants are shown in the formula, and the polynomial fitting result is shown in Figure 3. By balancing the accuracy of the fitting results and the amount of fitting parameters, the cubic polynomial fitting results are selected as the parameterized model of total ocean alkalinity.
在步骤S300中，所述将遥感二氧化碳分压数据及海洋总碱度参数化模型耦合至三维碳循环模型中，得到模拟二氧化碳分压模型，进而得到二氧化碳分压数据，包括以下步骤：In step S300, the remote sensing carbon dioxide partial pressure data and the ocean total alkalinity parameterized model are coupled to the three-dimensional carbon cycle model to obtain a simulated carbon dioxide partial pressure model, and then obtain carbon dioxide partial pressure data, including the following steps:
获取遥感二氧化碳分压数据，基于遥感二氧化碳分压数据与三维碳循环模型中溶解无机碳线性模型进行同化，得到溶解无机碳变化模型，表示如下：The remote sensing carbon dioxide partial pressure data was obtained, and the dissolved inorganic carbon change model was obtained based on the assimilation of the remote sensing carbon dioxide partial pressure data with the dissolved inorganic carbon linear model in the three-dimensional carbon cycle model, which is expressed as follows:
其中，表示遥感二氧化碳分压数据，/>表示三维碳循环模型的二氧化碳分压数据，/>表示溶解无机碳，p1表示常量；in, Represents remote sensing carbon dioxide partial pressure data, /> The carbon dioxide partial pressure data of the three-dimensional carbon cycle model is shown. represents dissolved inorganic carbon, and p1 represents a constant;
基于碳酸-碳酸盐系统平衡方程并结合海洋总碱度，得到海洋总碱度参数；Based on the carbonic acid-carbonate system equilibrium equation and combined with the total alkalinity of the ocean, the total alkalinity parameter of the ocean is obtained;
基于海洋总碱度参数及溶解无机碳变化模型，建立模拟二氧化碳分压模型，得到二氧化碳分压数据。Based on the ocean total alkalinity parameters and dissolved inorganic carbon change model, a simulation carbon dioxide partial pressure model was established to obtain carbon dioxide partial pressure data.
在此实施例中，主要用到了三维碳循环模型中溶解无机碳线性模型，由于三维碳循环模型在本领域是个公知的模型并且非常复杂，因此，通过遥感二氧化碳分压数据与三维碳循环模型中溶解无机碳线性模型进行同化，得到溶解无机碳变化模型。pCO2的主要影响因素有DIC溶解无机碳、温度、海洋总碱度及淡水，在基于碳酸盐的体系中，海洋总碱度、溶解无机碳、海水pH及模拟二氧化碳分压数据，通过任意选择已知量，搭建模拟二氧化碳分压数据模型，进而得到二氧化碳分压数据。In this embodiment, the dissolved inorganic carbon linear model in the three-dimensional carbon cycle model is mainly used. Since the three-dimensional carbon cycle model is a well-known model in the art and is very complex, the dissolved inorganic carbon change model is obtained by assimilating the remote sensing carbon dioxide partial pressure data with the dissolved inorganic carbon linear model in the three-dimensional carbon cycle model. The main influencing factors of pCO2 are DIC dissolved inorganic carbon, temperature, total alkalinity of the ocean and fresh water. In a carbonate-based system, total alkalinity of the ocean, dissolved inorganic carbon, pH of seawater and simulated carbon dioxide partial pressure data are used to build a simulated carbon dioxide partial pressure data model by arbitrarily selecting known quantities, and then obtain carbon dioxide partial pressure data.
本实施例中，所述模拟二氧化碳分压模型，表示如下：In this embodiment, the simulated carbon dioxide partial pressure model is expressed as follows:
计算过程中涉及到的相关参数，表示如下：The relevant parameters involved in the calculation process are expressed as follows:
其中，表示遥感二氧化碳分压数据，/>表示三维碳循环模型的二氧化碳分压数据，/>表示溶解无机碳，/>表示二氧化碳在海水中的溶解度，/>、/>表示海水中二氧化碳的平衡常数，/>表示逸度常数，/>表示温度，/>表示大气压，/>表示模拟二氧化碳分压数据，/>表示海洋总碱度参数。in, Represents remote sensing carbon dioxide partial pressure data, /> The carbon dioxide partial pressure data of the three-dimensional carbon cycle model is shown. represents dissolved inorganic carbon,/> represents the solubility of carbon dioxide in seawater,/> 、/> represents the equilibrium constant of carbon dioxide in seawater,/> represents the fugacity constant, /> Indicates temperature, /> represents atmospheric pressure, /> Represents simulated carbon dioxide partial pressure data, /> Represents the total alkalinity parameter of the ocean.
参见附图4所示，附图4给出了遥感二氧化碳分压数据、耦合后二氧化碳分压数据、未耦合二氧化碳分压数据分别与实测二氧化碳分压数据之间的误差的明显对比。Referring to FIG. 4 , FIG. 4 shows a clear comparison of the errors between the remote sensing carbon dioxide partial pressure data, the coupled carbon dioxide partial pressure data, the uncoupled carbon dioxide partial pressure data and the measured carbon dioxide partial pressure data.
在步骤S400中，基于二氧化碳分压数据，得到海气界面间二氧化碳分压差，基于海气界面间二氧化碳分压差构建模拟海气碳通量模型，进而得到海气碳通量数据，包括以下步骤：In step S400, based on the carbon dioxide partial pressure data, the carbon dioxide partial pressure difference between the air and sea interface is obtained, and a simulated air-sea carbon flux model is constructed based on the carbon dioxide partial pressure difference between the air and sea interface to obtain the air-sea carbon flux data, including the following steps:
本实施例中，海气碳通量数据具体计算公式如下所示：In this embodiment, the specific calculation formula of the sea-air carbon flux data is as follows:
其中，表示气体传输系数，/>，/>表示海水中二氧化碳的溶解度，/>表示海气界面间二氧化碳分压差，/>表示海平面10米处风速，/>表示施密特数，/>表示表层海水的二氧化碳分压数据，/>表示海面大气的二氧化碳分压数据，/>表示海气碳通量数据；in, represents the gas transmission coefficient, /> ,/> Indicates the solubility of carbon dioxide in seawater, /> represents the difference in partial pressure of carbon dioxide between the air and sea interface,/> Indicates the wind speed at 10 meters above sea level, /> represents the Schmidt number, /> Indicates the carbon dioxide partial pressure data of surface seawater, /> Indicates the carbon dioxide partial pressure data of the sea surface atmosphere, /> represents the air-sea carbon flux data;
若>0，/>为正值，此时海洋向大气释放二氧化碳，则该海域为大气中二氧化碳的源，若/><0，/>为负值，此时海洋向大气吸收二氧化碳，该海域为大气中二氧化碳的汇。like >0,/> is a positive value, the ocean releases carbon dioxide into the atmosphere, and the sea area is the source of carbon dioxide in the atmosphere. <0,/> When it is a negative value, the ocean absorbs carbon dioxide from the atmosphere and the sea area becomes a sink of carbon dioxide in the atmosphere.
实施例2：Embodiment 2:
一种基于遥感资料同化的海气碳通量重构系统，如图2所示，包括海洋碳模型建立模块100、碱度模型构建模块200、分压数据计算模块300及海气碳通量计算模块400；A sea-air carbon flux reconstruction system based on remote sensing data assimilation, as shown in FIG2 , includes an ocean carbon model establishment module 100 , an alkalinity model construction module 200 , a partial pressure data calculation module 300 and a sea-air carbon flux calculation module 400 ;
所述海洋碳模型建立模块100，所述海洋碳模型建立模块，基于海洋碳影响因素，构建三维碳循环模型，其中，海洋碳影响因素包括溶解无机碳、溶解有机碳及颗粒有机碳；The ocean carbon model building module 100, the ocean carbon model building module, builds a three-dimensional carbon cycle model based on ocean carbon influencing factors, wherein the ocean carbon influencing factors include dissolved inorganic carbon, dissolved organic carbon and particulate organic carbon;
所述碱度模型构建模块200，获取海洋盐度数据，基于海洋总碱度及海洋盐度数据，构建海洋总碱度参数化模型；The alkalinity model building module 200 acquires ocean salinity data and builds a parameterized model of ocean total alkalinity based on the ocean total alkalinity and ocean salinity data;
所述分压数据计算模块300，获取遥感二氧化碳分压数据，将遥感二氧化碳分压数据及海洋总碱度参数化模型耦合至三维碳循环模型中，得到模拟二氧化碳分压模型，进而得到二氧化碳分压数据；The partial pressure data calculation module 300 obtains remote sensing carbon dioxide partial pressure data, couples the remote sensing carbon dioxide partial pressure data and the ocean total alkalinity parameterized model to the three-dimensional carbon cycle model, obtains a simulated carbon dioxide partial pressure model, and then obtains carbon dioxide partial pressure data;
所述海气碳通量计算模块400，基于二氧化碳分压数据，得到海气界面间二氧化碳分压差，基于海气界面间二氧化碳分压差构建模拟海气碳通量模型，进而得到海气碳通量数据。The air-sea carbon flux calculation module 400 obtains the carbon dioxide partial pressure difference between the air and sea interfaces based on the carbon dioxide partial pressure data, constructs a simulated air-sea carbon flux model based on the carbon dioxide partial pressure difference between the air and sea interfaces, and then obtains the air-sea carbon flux data.
在一个实施例中，所述分压数据计算模块300，被设置为：In one embodiment, the voltage division data calculation module 300 is configured as follows:
基于遥感二氧化碳分压数据与三维碳循环模型中溶解无机碳线性模型进行同化，得到溶解无机碳变化模型；Based on the assimilation of remote sensing carbon dioxide partial pressure data with the dissolved inorganic carbon linear model in the three-dimensional carbon cycle model, a dissolved inorganic carbon change model was obtained;
基于碳酸-碳酸盐系统平衡方程并结合海洋总碱度，得到海洋总碱度参数；Based on the carbonic acid-carbonate system equilibrium equation and combined with the total alkalinity of the ocean, the total alkalinity parameter of the ocean is obtained;
基于海洋总碱度参数及溶解无机碳变化模型，建立模拟二氧化碳分压模型，得到二氧化碳分压数据；Based on the ocean total alkalinity parameters and dissolved inorganic carbon change model, a simulation model for carbon dioxide partial pressure was established to obtain carbon dioxide partial pressure data;
其中，所述溶解无机碳变化模型，表示如下：Wherein, the dissolved inorganic carbon change model is expressed as follows:
其中，表示遥感二氧化碳分压数据，/>表示三维碳循环模型的二氧化碳分压数据，/>表示溶解无机碳，p1表示常量；in, Represents remote sensing carbon dioxide partial pressure data, /> The carbon dioxide partial pressure data of the three-dimensional carbon cycle model is shown. represents dissolved inorganic carbon, and p1 represents a constant;
其中，所述模拟二氧化碳分压模型，表示如下：Wherein, the simulated carbon dioxide partial pressure model is expressed as follows:
其中，表示二氧化碳在海水中的溶解度，/>、/>表示海水中二氧化碳的平衡常数，/>表示逸度常数，/>表示温度，/>表示大气压，/>表示模拟二氧化碳分压数据，表示海洋总碱度参数。in, represents the solubility of carbon dioxide in seawater,/> 、/> represents the equilibrium constant of carbon dioxide in seawater,/> represents the fugacity constant, /> Indicates temperature, /> represents atmospheric pressure, /> represents the simulated carbon dioxide partial pressure data, Represents the total alkalinity parameter of the ocean.
在不脱离本发明的精神和范围的情况下做出的各种变化和变型，所有等同的技术方案也属于本发明的范畴。Various changes and modifications can be made without departing from the spirit and scope of the present invention, and all equivalent technical solutions also belong to the scope of the present invention.
本说明书中的各个实施例均采用递进的方式描述，每个实施例重点说明的都是与其他实施例的不同之处，各个实施例之间相同、相似的部分互相参见即可。The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.
本领域内的技术人员应明白，本发明的实施例可提供为方法、装置、或计算机程序产品。因此，本发明可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且，本发明可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
本发明是参照根据本发明的方法、终端设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理终端设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理终端设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。The present invention is described with reference to the flowchart and/or block diagram of the method, terminal device (system), and computer program product according to the present invention. It should be understood that each process and/or box in the flowchart and/or block diagram, as well as the combination of the processes and/or boxes in the flowchart and/or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing terminal device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device produce a device for implementing the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理终端设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device that implements the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.
这些计算机程序指令也可装载到计算机或其他可编程数据处理终端设备上，使得在计算机或其他可编程终端设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程终端设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce computer-implemented processing, so that the instructions executed on the computer or other programmable terminal device provide steps for implementing the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.
需要说明的是：It should be noted:
说明书中提到的“一个实施例”或“实施例”意指结合实施例描述的特定特征、结构或特性包括在本发明的至少一个实施例中。因此，说明书通篇各个地方出现的短语“一个实施例”或“实施例”并不一定均指同一个实施例。The "one embodiment" or "embodiment" mentioned in the specification means that the specific features, structures or characteristics described in conjunction with the embodiment are included in at least one embodiment of the present invention. Therefore, the phrases "one embodiment" or "embodiment" appearing in various places throughout the specification do not necessarily refer to the same embodiment.
此外，需要说明的是，本说明书中所描述的具体实施例，其零、部件的形状、所取名称等可以不同。凡依本发明专利构思所述的构造、特征及原理所做的等效或简单变化，均包括于本发明专利的保护范围内。本发明所属技术领域的技术人员可以对所描述的具体实施例做各种各样的修改或补充或采用类似的方式替代，只要不偏离本发明的结构或者超越本权利要求书所定义的范围，均应属于本发明的保护范围。In addition, it should be noted that the shapes and names of the parts and components of the specific embodiments described in this specification may be different. Any equivalent or simple changes made based on the structure, features and principles described in the patent concept of the present invention are included in the protection scope of the patent of the present invention. The technicians in the technical field of the present invention can make various modifications or supplements to the specific embodiments described or replace them in a similar manner, as long as they do not deviate from the structure of the present invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.
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Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104217098A (en) * | 2014-07-14 | 2014-12-17 | 浙江大学 | Sea-area carbon budget computing method based on combination of sailing section monitoring and satellite remote sensing |
| WO2017110889A1 (en) * | 2015-12-25 | 2017-06-29 | 国立大学法人東京大学 | Precise method of measuring carbonate-based parameters of sea water, and measuring device for use in said method |
| CN108896501A (en) * | 2018-07-07 | 2018-11-27 | 中国科学院南京地理与湖泊研究所 | A kind of remote sensing estimation method of the effective Sea―going flux of river dissolved organic carbon |
| CN109375286A (en) * | 2018-09-12 | 2019-02-22 | 广州海洋地质调查局 | A kind of automatic measuring device and method of sea air flux |
| CN114547885A (en) * | 2022-02-21 | 2022-05-27 | 清华大学 | Method, device, equipment and storage medium for quantitative inversion of carbon emissions |
| CN115290512A (en) * | 2022-07-15 | 2022-11-04 | 大连海事大学 | A color remote sensing method and device for estimating ocean surface particulate organic carbon concentration |
| CN116626155A (en) * | 2023-04-04 | 2023-08-22 | 厦门大学 | On-line observation method of carbon dioxide flux at water-air interface in estuary/bay area |
| CN116825220A (en) * | 2023-08-25 | 2023-09-29 | 青岛海洋地质研究所 | Assessment method of marine organic carbon degradation process based on continuity distribution function |
| CN117078276A (en) * | 2023-07-17 | 2023-11-17 | 深圳市北研生态环境科技有限公司 | Marine carbon sink data investigation system and method |
| CN117251989A (en) * | 2023-08-22 | 2023-12-19 | 中国科学院新疆生态与地理研究所 | Meteorological site carbon water flux information determination method, system and electronic equipment |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2751209C (en) * | 2009-02-02 | 2018-08-21 | Planetary Emissions Management | System of systems for monitoring greenhouse gas fluxes |
-
2024
- 2024-01-18 CN CN202410074905.7A patent/CN117592316B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104217098A (en) * | 2014-07-14 | 2014-12-17 | 浙江大学 | Sea-area carbon budget computing method based on combination of sailing section monitoring and satellite remote sensing |
| WO2017110889A1 (en) * | 2015-12-25 | 2017-06-29 | 国立大学法人東京大学 | Precise method of measuring carbonate-based parameters of sea water, and measuring device for use in said method |
| CN108896501A (en) * | 2018-07-07 | 2018-11-27 | 中国科学院南京地理与湖泊研究所 | A kind of remote sensing estimation method of the effective Sea―going flux of river dissolved organic carbon |
| CN109375286A (en) * | 2018-09-12 | 2019-02-22 | 广州海洋地质调查局 | A kind of automatic measuring device and method of sea air flux |
| CN114547885A (en) * | 2022-02-21 | 2022-05-27 | 清华大学 | Method, device, equipment and storage medium for quantitative inversion of carbon emissions |
| CN115290512A (en) * | 2022-07-15 | 2022-11-04 | 大连海事大学 | A color remote sensing method and device for estimating ocean surface particulate organic carbon concentration |
| CN116626155A (en) * | 2023-04-04 | 2023-08-22 | 厦门大学 | On-line observation method of carbon dioxide flux at water-air interface in estuary/bay area |
| CN117078276A (en) * | 2023-07-17 | 2023-11-17 | 深圳市北研生态环境科技有限公司 | Marine carbon sink data investigation system and method |
| CN117251989A (en) * | 2023-08-22 | 2023-12-19 | 中国科学院新疆生态与地理研究所 | Meteorological site carbon water flux information determination method, system and electronic equipment |
| CN116825220A (en) * | 2023-08-25 | 2023-09-29 | 青岛海洋地质研究所 | Assessment method of marine organic carbon degradation process based on continuity distribution function |
Non-Patent Citations (3)
| Title |
|---|
| MONITORING OF SINKING FLUX OF OCEAN PARTICULATE ORGANIC CARBON USING REMOTE SENSING METHODS;Tao Zui.etc;《IEEE》;20161231;全文 * |
| 利用卫星遥感技术估算区域性海-气CO_2通量研究综述;许苏清;陈立奇;;极地研究;20150915(03);全文 * |
| 海洋颗粒有机碳浓度水色遥感研究进展;王桂芬;曹文熙;殷建平;周雯;孙兆华;杨倩;;热带海洋学报;20121115(06);全文 * |
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