Biases in Model-Simulated Surface Energy Fluxes During the Indian Monsoon Onset Period
Biases in Model-Simulated Surface Energy Fluxes During the Indian Monsoon Onset Period
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DOI：
10.1007/s10546-018-0395-x
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发表时间：
2019-02-01
影响因子：
4.3
通讯作者：
Evans, Jonathan
中科院分区：
文献类型：
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作者：
Chakraborty, Tirthankar;Sarangi, Chandan;Evans, Jonathan
我们在印度-恒河盆地中部的半天然草原上使用涡动协方差测量，研究诺亚陆面模型模拟的两个季风爆发期的能量通量偏差：一个是降雨期（2016年），一个是完全干燥期（2017年）。在使用默认参数的初步运行中，离线Noah LSM高估了中午（当地时间1000-1400）的感热通量（H）279%（2016年）和108%（2017年），低估了中午的潜热通量（LE）56%（2016年）和67%（2017年）。从高亚洲再分析数据集可以看出，模拟能量通量中的这些差异会传播到天气研究和预报模型耦合模拟中并被放大。一维诺亚模拟与修改后的网站特定的植被参数，不仅提高了分区的能量通量（波文比为0.9，在修改后的运行与3.1的默认运行），但也减少了高估的模型模拟的土壤和皮肤温度。因此，在未来的研究中，使用周围的网站参数是必要的，以减少在短期和长期模拟在这一地区的不确定性。最后，我们研究如何在模型模拟的偏见可以归因于缺乏封闭的测量表面能量预算。当2016年将感热通量闭合后方法用于LE时，偏差最小; 0.17，表明在评估陆面模型时考虑涡度协方差站点的表面能量不平衡的重要性。
We use eddy-covariance measurements over a semi-natural grassland in the central Indo-Gangetic Basin to investigate biases in energy fluxes simulated by the Noah land-surface model for two monsoon onset periods: one with rain (2016) and one completely dry (2017). In the preliminary run with default parameters, the offline Noah LSM overestimates the midday (1000-1400 local time) sensible heat flux (H) by 279% (in 2016) and 108% (in 2017) and underestimates the midday latent heat flux (LE) by 56% (in 2016) and 67% (in 2017). These discrepancies in simulated energy fluxes propagate to and are amplified in coupled Weather Research and Forecasting model simulations, as seen from the High Asia Reanalysis dataset. One-dimensional Noah simulations with modified site-specific vegetation parameters not only improve the partitioning of the energy fluxes (Bowen ratio of 0.9 in modified run versus 3.1 in the default run), but also reduce the overestimation of the model-simulated soil and skin temperature. Thus, use of ambient site parameters in future studies is warranted to reduce uncertainties in short-term and long-term simulations over this region. Finally, we examine how biases in the model simulations can be attributed to lack of closure in the measured surface energy budget. The bias is smallest when the sensible heat flux post-closure method is used for LE in 2016; 0.17 , showing the importance of taking into account the surface energy imbalance at eddy-covariance sites when evaluating land-surface models.