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Model structure and land parameter identification: An inverse problem approach

机译:model structure and land parameter identification: an inverse problem approach

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摘要

[1] Model structures for the parameterization of energy and water exchanges between the atmosphere and the land are explored, and the parameters are identified. Minimizing the root-mean-square error (RMSE) of the calculated air temperature is used as the objective function. Eight parameters are determined within 14 iterations over two urban sites in a subtropical island. The identified values of these parameters can be compared with those listed in the literature. The results show that (1) a proper choice of canopy resistance is important in determining the mean temperature; (2) using a scheme to calculate stomatal resistance from vegetated areas shows improvements in simulating the diurnal variations of the temperature, decreasing the RMSE by 0.4 K; (3) using a scheme to accommodate the effect of evaporation from skin reservoirs during rain events shows improvements in determining the temperature immediately after the rain, decreasing the RMSE by 0.1 K; (4) while incorporating a soil-moisture availability function does not show improvement in the model performance unless an extra water table variable is added, which decreases the RMSE by 0.03 K. Incorporating all of the above model structures, the calculated hourly air temperature has a correlation coefficient of as high as 0.97 with a RMSE of 1.4 K.
机译:[1]探索了大气与陆地之间能量和水交换参数化的模型结构,并确定了参数。将计算出的空气温度的均方根误差(RMSE)最小化用作目标函数。在亚热带岛屿的两个城市站点上的14次迭代中确定了八个参数。这些参数的确定值可以与文献中列出的值进行比较。结果表明:(1)合理选择树冠阻力对于确定平均温度很重要; (2)使用从植被区域计算气孔阻力的方案显示出在模拟温度的昼夜变化方面的改进,使RMSE降低了0.4 K; (3)在雨天使用一种方案来适应皮肤储库蒸发的影响,显示出在雨后立即确定温度方面的改进,将RMSE降低了0.1 K; (4)除非添加额外的地下水位变量,否则合并土壤水分利用度函数不会显示出模型性能的改善,这会使RMSE降低0.03K。合并所有上述模型结构后,计算出的每小时气温为相关系数高达0.97,RMSE为1.4K。

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