Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2019WR026129 |
Resolving Small-Scale Forest Snow Patterns Using an Energy Balance Snow Model With a One-Layer Canopy | |
Mazzotti, Giulia1,2; Essery, Richard3; Moeser, C. David4; Jonas, Tobias1 | |
2020 | |
发表期刊 | WATER RESOURCES RESEARCH |
ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2020 |
卷号 | 56期号:1 |
文章类型 | Article |
语种 | 英语 |
国家 | Switzerland; Scotland; USA |
英文摘要 | Modeling spatiotemporal dynamics of snow in forests is challenging, as involved processes are strongly dependent on small-scale canopy properties. In this study, we explore how local canopy structure information can be integrated in a medium-complexity energy balance snow model to replicate observed snow patterns at very high spatial resolutions. Snow depth distributions simulated with the Flexible Snow Model (FSM2) were tested against extensive experimental data acquired in discontinuous subalpine forest stands in Eastern Switzerland over three winters. While the default canopy implementation in FSM2 fails to capture the observed snow depth variability, performance is considerably improved when local canopy cover fraction and hemispherical sky view fraction are additionally accounted for (30% reduction in root mean square error). However, realistic snow depth distribution patterns throughout the season are only achieved if effective temperatures of near and distant canopy elements are discerned and if a mechanism to mimic preferential deposition of snow in canopy gaps is included. We demonstrate that by diversifying the canopy structure input in order to reflect respective portions of the canopy relevant to different processes, even a simple model based on widely used process parameterizations and canopy metrics can be applied for high-resolution simulations of the sub-canopy snow cover with just a few modifications. The presented approaches could be implemented in commonly used land surface models, allowing upscaling experiments and development of sub-grid parameterizations without necessitating complex high-resolution models. |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000520132500039 |
WOS关键词 | INCOMING LONGWAVE RADIATION ; TURBULENT HEAT FLUXES ; LEAF-AREA INDEX ; STRUCTURE METRICS ; ACCUMULATION ; COVER ; LIDAR ; INTERCEPTION ; IMPACTS ; MELT |
WOS类目 | Environmental Sciences ; Limnology ; Water Resources |
WOS研究方向 | Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/280458 |
专题 | 资源环境科学 |
作者单位 | 1.WSL Inst Snow & Avalanche Res SLF, Davos, Dorf, Switzerland; 2.ETHZ, Lab Hydraul Hydrol & Glaciol, Zurich, Switzerland; 3.Univ Edinburgh, Sch Geosci, Edinburgh, Midlothian, Scotland; 4.US Geol Survey, New Mexico Water Sci Ctr, Albuquerque, NM USA |
推荐引用方式 GB/T 7714 | Mazzotti, Giulia,Essery, Richard,Moeser, C. David,et al. Resolving Small-Scale Forest Snow Patterns Using an Energy Balance Snow Model With a One-Layer Canopy[J]. WATER RESOURCES RESEARCH,2020,56(1). |
APA | Mazzotti, Giulia,Essery, Richard,Moeser, C. David,&Jonas, Tobias.(2020).Resolving Small-Scale Forest Snow Patterns Using an Energy Balance Snow Model With a One-Layer Canopy.WATER RESOURCES RESEARCH,56(1). |
MLA | Mazzotti, Giulia,et al."Resolving Small-Scale Forest Snow Patterns Using an Energy Balance Snow Model With a One-Layer Canopy".WATER RESOURCES RESEARCH 56.1(2020). |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论