气候变化领域集成服务门户(CCPortal): Quantifying physical parameterization uncertainties associated with land-atmosphere interactions in the WRF model over Amazon

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DOI	10.1016/j.atmosres.2021.105761
	Quantifying physical parameterization uncertainties associated with land-atmosphere interactions in the WRF model over Amazon
	Wang C.; Qian Y.; Duan Q.; Huang M.; Yang Z.; Berg L.K.; Gustafson W.I.; Jr.; Feng Z.; Liu J.; Quan J.
发表日期	2021
ISSN	0169-8095
卷号	262
英文摘要	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 the priori ensemble. 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. © 2021 Elsevier B.V.
英文关键词	Amazon region; ANOVA; L-A coupling strength; Model physical parameterization uncertainty; Tukey's Test
来源期刊	Atmospheric Research
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/236631
作者单位	Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650, China; Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA, United States; State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, College of Hydrology and Water Resources, Hohai University, Nanjing, Jiangsu 210098, China; Institute of Urban Meteorology, China Meteorological Administration, Beijing, 100089, China
推荐引用方式 GB/T 7714	Wang C.,Qian Y.,Duan Q.,et al. Quantifying physical parameterization uncertainties associated with land-atmosphere interactions in the WRF model over Amazon[J],2021,262.
APA	Wang C..,Qian Y..,Duan Q..,Huang M..,Yang Z..,...&Quan J..(2021).Quantifying physical parameterization uncertainties associated with land-atmosphere interactions in the WRF model over Amazon.Atmospheric Research,262.
MLA	Wang C.,et al."Quantifying physical parameterization uncertainties associated with land-atmosphere interactions in the WRF model over Amazon".Atmospheric Research 262(2021).