地表净辐射通量观测、模拟和同化的研究进展
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摘要
地表净辐射通量是陆—气相互作用水热交换过程中的一个重要物理参量,在全球变化背景下,定量研究地表净辐射通量的时空变化对气候变化研究具有重要意义。本文总结了目前定量研究地表净辐射通量的主要方法——观测、模拟和同化,分析了观测和模拟的优势和不足,提出利用数据同化方法可以弥补观测和模拟的不足,并比较分析了目前流行的同化算法的优缺点,利用不同的同化算法构建的同化系统可以同化不同来源的观测数据对模型进行校准,获取时空上连续一致的高精度地表净辐射的预报值。最后,探讨了同化多源遥感数据改进地表净辐射通量的研究中存在的问题、发展方向及其在全球变化研究中的意义。
Surface net radiation is a key variable of energy and water exchange processes in land–atmosphere interactions. Accurate estimation of spatial–time changes on land-surface net radiation flux is a critical study in global warming for climate change research. This study aims to summarize the three main methods for estimating net radiation at present, to analyze the advantages and disadvantages of the different methods used for surface net radiation, and to propose an effective method using data assimilation to improve net radiation at present and in the future. This paper summarizes the main methods, including observation, simulation, and assimilation, used at present for surface net radiation.Observations include ground-based measurement and remote-sensing estimation. Simulation is mainly concerned with the estimation of land-surface process models. The advantages and disadvantages of observation and simulation are analyzed, and the current status and progress of surface net radiation observation and simulation are reviewed in this study. Moreover, a method of data assimilation is proposed to compensate for the shortcomings of observation and simulation. The advantages and disadvantages of popular assimilation algorithms, such as sequential(Kalman filter algorithm and its derivative, particle filter algorithm) and variational(four dimensional variational assimilation algorithm or 4D–Var) assimilation algorithms, are introduced and analyzed in this study. Furthermore, the research progress and existing problems of assimilation algorithms in surface net radiation flux estimation are summarized. At present, progress has been made in estimating the surface net radiation using data assimilation combined with multisource observations. However, problems exist in these methods. A model is calibrated by the observation data of different sources to obtain the continuous and consistent high-precision surface net radiation prediction value in time and space in the process of data assimilation using different assimilation algorithms. The adaptability of different land-surface process models varies in different research areas based on the simulation results of the model, and the precision and accuracy of the different models in describing the surface water thermal process are significant.Based on the assimilation of remote sensing data, the study of assimilating an optical remote sensing data product has been successful in estimating the net radiation of the surface.
Surface net radiation is a key variable of energy and water exchange processes in land–atmosphere interactions. Accurate estimation of spatial–time changes on land-surface net radiation flux is a critical study in global warming for climate change research. This study aims to summarize the three main methods for estimating net radiation at present, to analyze the advantages and disadvantages of the different methods used for surface net radiation, and to propose an effective method using data assimilation to improve net radiation at present and in the future. This paper summarizes the main methods, including observation, simulation, and assimilation, used at present for surface net radiation.Observations include ground-based measurement and remote-sensing estimation. Simulation is mainly concerned with the estimation of land-surface process models. The advantages and disadvantages of observation and simulation are analyzed, and the current status and progress of surface net radiation observation and simulation are reviewed in this study. Moreover, a method of data assimilation is proposed to compensate for the shortcomings of observation and simulation. The advantages and disadvantages of popular assimilation algorithms, such as sequential(Kalman filter algorithm and its derivative, particle filter algorithm) and variational(four dimensional variational assimilation algorithm or 4D–Var) assimilation algorithms, are introduced and analyzed in this study. Furthermore, the research progress and existing problems of assimilation algorithms in surface net radiation flux estimation are summarized. At present, progress has been made in estimating the surface net radiation using data assimilation combined with multisource observations. However, problems exist in these methods. A model is calibrated by the observation data of different sources to obtain the continuous and consistent high-precision surface net radiation prediction value in time and space in the process of data assimilation using different assimilation algorithms. The adaptability of different land-surface process models varies in different research areas based on the simulation results of the model, and the precision and accuracy of the different models in describing the surface water thermal process are significant.Based on the assimilation of remote sensing data, the study of assimilating an optical remote sensing data product has been successful in estimating the net radiation of the surface.
引文
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