Assessing the sensitivity of land-atmosphere coupling strength to boundary and surface layer parameters in the WRF model over Amazon
Assessing the sensitivity of land-atmosphere coupling strength to boundary and surface layer parameters in the WRF model over Amazon
复制标题
评估亚马逊 WRF 模型中陆地-大气耦合强度对边界和表层参数的敏感性
DOI：
10.1016/j.atmosres.2019.104738
复制
发表时间：
2020-04
影响因子：
5.5
通讯作者：
Yan Junhua
中科院分区：
文献类型：
--
作者：
Wang Chen;Qian Yun;Duan Qingyun;Huang Maoyi;Berg Larry K.;Shin Hyeyum H.;Feng Zhe;Yang Ben;Quan Jiping;Hong Songyou;Yan Junhua
在缺乏足够观测资料的情况下，模式工具可用于诊断区域陆-气耦合强度，但受模式物理参数化参数的不确定性影响。不同的敏感性分析（SA）方法可能会导致对潜在敏感性的不同结论。在这项研究中，我们量化模拟的不确定性相关的参数扰动，并使用不同的方法进行参数SA的WRF模型有关的L-A耦合强度在亚马逊地区的模拟。分析中选取了延世大学（YSU）行星边界层（PBL）和修正的MM 5表面层（SL）方案中的20个参数。三种不同的SA方法，莫里斯一次（MOAT）方法，多元自适应回归样条（MARS）方法，和Sobol的方法，分析了7个WRF模拟变量和5个L-A耦合度量。结果表明：1）参数摄动引起的模拟不确定性与观测值相当; 2）3种不同的模拟方法给出了一致的L-A耦合强度结果; 3）20个参数中有6个对所分析度量的总方差贡献了80%~ 95%，且一阶效应占主导地位，而交互效应占主导地位; 4）感兴趣的12个变量/度量显示出对所选参数的类似敏感性模式，这在所使用的所有方法中是一致的。还说明了敏感参数如何在确定L-A耦合强度和相关变量中起作用的物理机制。我们的研究结果将有助于量化L-A耦合强度，并为亚马逊地区的参数校准奠定基础。
Modeling tools can be used to diagnose regional land-atmosphere (L-A) coupling strength in the absence of sufficient observations, but subject to uncertainties associated with parameters in model physical parameterizations. Different sensitivity analysis (SA) approaches may lead to different conclusions about the underlying sensitivities. In this study, we quantify simulation uncertainties related to parameter perturbations, and use different approaches to conduct parameter SA on the WRF model pertaining to L-A coupling strength for simulations over the Amazon region. A total of twenty parameters from the Yonsei University (YSU) planetary boundary layer (PBL) and the revised MM5 surface layer (SL) schemes were selected in this analysis. Three different SA methods, the Morris One-at-A-Time (MOAT) method, the Multivariate Adaptive Regression Splines (MARS) method, and the Sobol’ method, were employed to analyze seven WRF-simulated variables and five L-A coupling metrics. Results show that 1) parameter perturbations cause large simulation uncertainties which are comparable to those in the observations; 2) three different SA methods give consistent L-A coupling strength outcomes; 3) six out of the twenty parameters contribute 80%–95% of the total variance in the metrics analyzed, and first-order effects dominate over interaction effects; 4) the twelve variables/metrics of interest show similar sensitivity patterns to the selected parameters, which is consistent across all the methods used. Physical mechanisms for how the sensitive parameters act in determining the L-A coupling strength and associated variables also are illustrated. Our results will help quantifying L-A coupling strength and establishing a basis for parameter calibration over the Amazon region.
登录
查看更多内容
从定性到定量的逐步敏感性分析：联合地表-地下过程（CSSP）陆地表面模型的陆地水文模型的应用
影响因子：
6.8
作者：
Gan Yanjun;Liang Xin-Zhong;Duan Qingyun;Choi Hyun Il;Dai Yongjiu;Wu Huan
通讯作者：
Wu Huan
影响因子：
2.2
作者：
S. Tucker;C. Senff;A. Weickmann;W. Brewer;R. Banta;S. Sandberg;D. Law;R. Hardesty
通讯作者：
S. Tucker;C. Senff;A. Weickmann;W. Brewer;R. Banta;S. Sandberg;D. Law;R. Hardesty
影响因子：
3.2
作者：
J. Srinivasan;G. Smith
通讯作者：
J. Srinivasan;G. Smith
影响因子：
8
作者：
J. Santanello;P. Dirmeyer;C. Ferguson;K. Findell;A. Tawfik;A. Berg;M. Ek;P. Gentine;B. Guillod;C. V. Heerwaarden;J. Roundy;V. Wulfmeyer
通讯作者：
J. Santanello;P. Dirmeyer;C. Ferguson;K. Findell;A. Tawfik;A. Berg;M. Ek;P. Gentine;B. Guillod;C. V. Heerwaarden;J. Roundy;V. Wulfmeyer
影响因子：
6.4
作者：
Q. Duan;J. Schaake;V. Andréassian;S. Franks;G. Goteti;H. Gupta;Y. Gusev;F. Habets;A. Hall
通讯作者：
Q. Duan;J. Schaake;V. Andréassian;S. Franks;G. Goteti;H. Gupta;Y. Gusev;F. Habets;A. Hall