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Energy balance closure in the Southwest Amazon forest site-a statistical approach

机译:西南亚马逊森林站点的能量平衡关闭-一种统计方法

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Energy balance closure is the main indicator of the quality of energy flux measurements obtained by the eddy covariance technique. Many researchers use a simple linear regression model between energy balance components to evaluate closure. However, these studies typically fail to verify the appropriateness of the statistical assumptions of regression analysis, which can lead to erroneous conclusions if the model is not satisfactory. Thus, the aim of this study was to calibrate and validate simple and robust with bootstrap and cross-validation linear regression models to verify the efficiency of energy balance closure in the Amazon ecosystem. Measurements of net radiation and latent, sensible, and ground heat fluxes were made from January to December 2008 in a tropical rain forest area in South West Amazonia in an experimental site belonging to the network of flux towers of the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA). The results demonstrated that simple linear regression models are not appropriate for analyzing energy balance closure. However, robust linear regression models with bootstrap and cross-validation improved the fit to the data. Despite the better fit, there was an increase in energy balance closure residuals suggesting that the eddy covariance technique is underestimating the values of energy fluxes in Amazon forest areas more than what were reported in previous researches.
机译:能量平衡的闭合是通过涡度协方差技术获得的能量通量测量质量的主要指标。许多研究人员在能量平衡组件之间使用简单的线性回归模型来评估闭合。但是,这些研究通常无法验证回归分析的统计假设是否适当,如果模型不令人满意,则可能导致错误的结论。因此,本研究的目的是通过自举和交叉验证线性回归模型来校准和验证简单而强大的功能,以验证亚马逊生态系统中能量平衡封闭的效率。 2008年1月至2008年12月,在西南亚马逊热带雨林地区的一个大型生物圈-大气实验通量塔网络的实验点,对净辐射和潜热,感热和地面热通量进行了测量。在亚马逊(LBA)。结果表明,简单的线性回归模型不适用于分析能量平衡的闭合性。但是,具有自举和交叉验证的鲁棒线性回归模型改善了对数据的拟合度。尽管拟合效果更好,但能量平衡闭合残差有所增加,这表明,涡度协方差技术低估了亚马逊森林地区的能量通量值,其结果比以往的研究报告要多。

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