doi:  10.3878/j.issn.1006-9895.1711.17179
基于EC观测估算最小冠层阻力分布及其在潜热通量插补中的应用

Estimation of Minimum Canopy Resistance by EC Data and Its Application in the Interpolation of Latent Heat Flux
摘要点击 180  全文点击 94  投稿时间:2017-06-13  
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基金:  国家自然科学基金项目41575096、91125016,中国科学院前沿科学重点研究计划QYZDY-SSW-DQC012
中文关键词:  Penman-Monteith模型  最小冠层阻力  潜热通量  数据插补
英文关键词:  Penman-Monteith model  Minimum canopy resistance  Latent heat flux  Data interpolation
           
作者中文名作者英文名单位
刘斌LIU Bin中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室, 北京 100029;中国科学院大学, 北京 100049
谢正辉XIE Zhenghui中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室, 北京 100029;中国科学院大学, 北京 100049
刘双LIU Shuang中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室, 北京 100029;中国科学院大学, 北京 100049
李锐超LI Ruichao中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室, 北京 100029;中国科学院大学, 北京 100049
引用:刘斌,谢正辉,刘双,李锐超.2018.基于EC观测估算最小冠层阻力分布及其在潜热通量插补中的应用[J].大气科学,42(6):1235-1244,doi:10.3878/j.issn.1006-9895.1711.17179.
Citation:LIU Bin,XIE Zhenghui,LIU Shuang,LI Ruichao.2018.Estimation of Minimum Canopy Resistance by EC Data and Its Application in the Interpolation of Latent Heat Flux[J].Chinese Journal of Atmospheric Sciences (in Chinese),42(6):1235-1244,doi:10.3878/j.issn.1006-9895.1711.17179.
中文摘要:
      准确估计水热通量对于认识和理解地气交换与水循环变化过程具有重要意义。利用Penman-Monteith (P-M)模型计算季节尺度水热通量变化的不确定性很大程度上依赖于与冠层变化相关的最小冠层阻力参数,但模型中通常将其设为定值。为此,本文基于多年通量观测采用分段与整体相结合的迭代算法拟合出最小冠层阻力的季节分布。以湖南省宁乡通量观测站为例,针对2012~2015年观测拟合计算最小冠层阻力的季节分布曲线,并利用2016年通量数据进行独立数据验证。结果表明:最小冠层阻力曲线具有鲜明夏低冬高的季节变化特征;利用拟合的具有季节分布的最小冠层阻力改进潜热通量计算,独立数据验证表明其该方法的合理性;相比于原阻力方案得出的潜热模拟结果,其在相关系数、均方根误差和一致性指数都有改进;此外,将该估计方法应用于水热通量的数据插补,较常规统计插补方法,其插补稳定性不随连续缺失数据的增加而降低,而且还能通过模型的微分误差分析量化由于数据输入带来的插补不确定性,在保持通量数据完整性的同时也为数据应用场景提供科学依据。
Abstract:
      Accurate latent heat flux estimation is important for land-atmosphere exchange and water cycle research. The seasonal uncertainty of latent heat flux simulation by Penman-Monteith equation is caused by the minimum canopy resistance, which varies with various canopy conditions but is often set to a fixed value in present modeling studies. To solve the problem, the seasonal curve of the minimum canopy resistance is fitted based on an integral and piecewise fitting method which velies on multi-year measurements of EC (Eddy Covariance) flux. The Ningxiang flux station is taken as an example. Flux data from 2012-2015 are used to fit the seasonal curve of the minimum canopy resistance, and data from 2016 is used to verify the simulated results. It is found that the minimum canopy resistance has a seasonal variation, which is lower in the summer and higher in the winter. The modified simulation shows better results by applying seasonally varying minimum canopy resistance. Also the correlation coefficient, root mean square error and agreement of index are better than those using the original canopy resistance scheme. The modified scheme is then used to interpolate the missing data. Results indicate that the modified scheme is more stable than the traditional interpolating method, and the uncertainty of the input data can be determined by the differential equation. This research is helpful to keep flux data complete, and to provide scientific basis for the data application.
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