Quantifying physical parameterization uncertainties associated with land-atmosphere interactions in the WRF model over Amazon
Quantifying physical parameterization uncertainties associated with land-atmosphere interactions in the WRF model over Amazon
复制标题
量化亚马逊 WRF 模型中与陆地-大气相互作用相关的物理参数化不确定性
DOI：
10.1016/j.atmosres.2021.105761
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发表时间：
2021-11
影响因子：
5.5
通讯作者：
Quan Jiping
中科院分区：
文献类型：
--
作者：
Wang Chen;Qian Yun;Duan Qingyun;Huang Maoyi;Yang Zhao;Berg Larry K.;Gustafson William I.;Feng Zhe;Liu Juxiu;Quan Jiping
天气研究和预报 (WRF) 模型可用于在缺乏足够观测但受到与模型物理参数化相关的不确定性的情况下诊断区域陆地-大气 (L-A) 耦合强度。在这项研究中，我们提出了一个框架来量化和减少与表面通量和 L-A 耦合相关的模型物理参数化不确定性。使用具有不同物理方案的 WRF 模拟集合来模拟亚马逊地区的地表通量和陆地-大气耦合强度。研究的物理参数化包括云微物理（MP）、地表过程（LSM）、行星边界层（PBL）、表面层（SL）和积云（CU）。我们使用 WRF 模型以及 6 个 MP、3 个 LSM、6 个 PBL 和 SL 以及 3 个 CU 的不同组合执行 120 次集成模拟。 GoAMAZON 现场活动的测量结果和卫星数据用于评估模型性能。应用多路方差分析 (ANOVA) 方法来量化不同物理过程对 L-A 耦合的相对重要性。 Tukey 检验用于将没有显着差异的方案分类为一组。根据泰勒技能得分选择能够对相应变量进行最佳模拟的物理套件。结果表明，流程及其相互作用的相对重要性随感兴趣的变量而变化。例如，CU 是调节土壤湿度、2 m 湿度、潜热和净辐射的最重要过程。 LSM 对 2 m 温度显示出主导影响，并且对显热和提升凝结水平也具有最大的影响。最好的物理参数化系综显示的感兴趣变量的范围比先验系综窄得多。这项研究的结果显示了不同物理过程在调节 L-A 相互作用中的作用，量化了物理过程的模型不确定性，并为改进模型物理参数化提供了见解。
The Weather Research and Forecasting (WRF) model can be used to diagnose regional land-atmosphere (L-A) coupling strength in the absence of sufficient observations but subjected to uncertainties associated with model physical parameterizations. In this study, we propose a framework to quantify and reduce model physical parameterization uncertainties associated with surface fluxes and L-A coupling. An ensemble of WRF simulations with different physical schemes is used to simulate surface fluxes and land-atmosphere coupling strength over the Amazon region. The physical parameterizations investigated include cloud microphysics (MP), land surface processes (LSM), planetary boundary layer (PBL), surface layer (SL), and cumulus (CU). We perform 120 ensemble simulations using the WRF model and different combinations of six MPs, three LSMs, six PBLs and SLs and three CUs. The measurements from the GoAMAZON field campaign and satellite data are used to evaluate model performance. A Multi-way analysis of variance (ANOVA) approach is applied to quantify the relative importance of different physics processes on L-A coupling. The Tukey's test is used to sort schemes that have no significant differences into one group. The suite of physics that result in the best simulations of the corresponding variables are selected based on the Taylor skill score. Results show that the relative importance of processes and their interaction vary with the variables of interest. For example, CU was the most important process in modulating soil moisture, 2 m-humidity, latent heat, and net radiation. LSM showed dominant effects on 2 m-temperature and also has the largest impact on sensible heat and the lifting condensation level. The best physical parameterization ensembles show much narrower ranges of the variables of interest than theprioriensemble. Results of this study show the roles of different physical processes in modulating L-A interactions, quantify model uncertainties from physical processes, and provide insights for improving the model physics parameterizations.
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DOI：
10.1080/00224065.1986.11978989
发表时间：
1975-03
期刊：
--
影响因子：
--
作者：
M. Kutner
通讯作者：
M. Kutner
影响因子：
3.2
作者：
J. Srinivasan;G. Smith
通讯作者：
J. Srinivasan;G. Smith
影响因子：
2.9
作者：
D. Bright;S. Mullen
通讯作者：
D. Bright;S. Mullen
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
DOI：
10.1007/978-1-935704-36-2_1
发表时间：
1969
期刊：
Meteorological Monographs
影响因子：
--
作者：
E. Kessler
通讯作者：
E. Kessler