气候变化领域集成服务门户(CCPortal): Snow processes in mountain forests: Interception modeling for coarse-scale applications

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DOI	10.5194/hess-24-2545-2020
	Snow processes in mountain forests: Interception modeling for coarse-scale applications
	Helbig N.; Moeser D.; Teich M.; Vincent L.; Lejeune Y.; Sicart J.-E.; Monnet J.-M.
发表日期	2020
ISSN	1027-5606
起始页码	2545
结束页码	2560
卷号	24 期号:5
英文摘要	Snow interception by the forest canopy controls the spatial heterogeneity of subcanopy snow accumulation leading to significant differences between forested and nonforested areas at a variety of scales. Snow intercepted by the forest canopy can also drastically change the surface albedo. As such, accurately modeling snow interception is of importance for various model applications such as hydrological, weather, and climate predictions. Due to difficulties in the direct measurements of snow interception, previous empirical snow interception models were developed at just the point scale. The lack of spatially extensive data sets has hindered the validation of snow interception models in different snow climates, forest types, and at various spatial scales and has reduced the accurate representation of snow interception in coarse-scale models. We present two novel empirical models for the spatial mean and one for the standard deviation of snow interception derived from an extensive snow interception data set collected in an evergreen coniferous forest in the Swiss Alps. Besides open-site snowfall, subgrid model input parameters include the standard deviation of the DSM (digital surface model) and/or the sky view factor, both of which can be easily precomputed. Validation of both models was performed with snow interception data sets acquired in geographically different locations under disparate weather conditions. Snow interception data sets from the Rocky Mountains, US, and the French Alps compared well to the modeled snow interception with a normalized root mean square error (NRMSE) for the spatial mean of ≤10% for both models and NRMSE of the standard deviation of ≤13%. Compared to a previous model for the spatial mean interception of snow water equivalent, the presented models show improved model performances. Our results indicate that the proposed snow interception models can be applied in coarse land surface model grid cells provided that a sufficiently fine-scale DSM is available to derive subgrid forest parameters. © 2020 Author(s).
语种	英语
scopus关键词	Climate models; Forestry; Mean square error; Statistics; Climate prediction; Coarse-scale models; Digital surface models; Interception models; Land surface modeling; Root mean square errors; Snow water equivalent; Spatial heterogeneity; Snow; climate conditions; coniferous forest; forest canopy; heterogeneity; interception; land surface; modeling; montane forest; snow accumulation; Alps; Rocky Mountains; United States
来源期刊	Hydrology and Earth System Sciences
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/159403
作者单位	Helbig, N., WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland; Moeser, D., USGS New Mexico Water Science Center, Albuquerque, NM, United States; Teich, M., Austrian Federal Research Centre for Forests, Natural Hazards and Landscape (BFW), Innsbruck, Austria, Department of Wildland Resources, Utah State University, Logan, UT, United States; Vincent, L., Université Grenoble Alpes, Université de Toulouse, Méteó-France, CNRS, CNRM, Centre d'Études de la Neige, Grenoble, France; Lejeune, Y., Université Grenoble Alpes, Université de Toulouse, Méteó-France, CNRS, CNRM, Centre d'Études de la Neige, Grenoble, France; Sicart, J.-E., Université Grenoble Alpes, CNRS, IRD, Grenoble INP, Institut des Geósciences de l'Environnement (IGE)-UMR 5001, Grenoble, 38000, France; Monnet, J.-M., Université Grenoble Alpes, INRAE, LESSEM, St-Martin-d'Hères, 38402, France
推荐引用方式 GB/T 7714	Helbig N.,Moeser D.,Teich M.,et al. Snow processes in mountain forests: Interception modeling for coarse-scale applications[J],2020,24(5).
APA	Helbig N..,Moeser D..,Teich M..,Vincent L..,Lejeune Y..,...&Monnet J.-M..(2020).Snow processes in mountain forests: Interception modeling for coarse-scale applications.Hydrology and Earth System Sciences,24(5).
MLA	Helbig N.,et al."Snow processes in mountain forests: Interception modeling for coarse-scale applications".Hydrology and Earth System Sciences 24.5(2020).