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Collaborative Research: Sublimation of Snow (SOS)

Collaborative Research: Sublimation of Snow (SOS)
合作研究:雪的升华(SOS)
批准号:
2139836
负责人:
Jessica Lundquist
金额:
$47.06万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-01-15 至 2024-12-31

项目摘要

项目成果

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中文摘要
翻译
积雪在水资源中起着至关重要的作用,特别是对于那些从山区降雪的季节性融化中获得水的地区。 然而,融化并不是积雪耗尽的唯一方式。 雪的升华是指雪直接变成水蒸气的过程。 升华的影响还没有得到很好的理解,也不是特定的大气条件,导致或多或少的升华。 该项目将通过在2022-23冬季在科罗拉多部署一套先进的仪器来帮助解决与这些主题相关的问题。 该项目的结果将是一个数据集,可用于确定数值模型是否正确处理升华,如果不是,如何改进它们。 研究小组将与相关的利益攸关方团体(如水资源管理人员)进行沟通,并制作短视频,以公众可以理解的清晰语言解释困难的概念。 学生将直接参与实地活动,从而培养下一代观测和数据分析科学家。研究团队将在2022-23冬季在科罗拉多的凯特尔池塘进行雪升华(SOS)实地活动。 雪的升华在水资源中起着重要的作用,但控制升华速率的物理学还没有完全理解。 该项目将重点关注风在升华中的作用,无论是在湍流至关重要的低风条件下,还是在吹雪因素时的大风条件下。 SOS实地活动被嵌入到能源部赞助的一个更大的活动中,称为地表大气综合实地实验室(SAIL),该实验室将提供雷达和激光雷达的遥感测量。 SOS将提供四个通量塔(NCAR集成表面通量系统,ISFS)用于湍流和潜热通量测量,沿着还有许多其他仪器,将提供雪深、密度和含水量、土壤和积雪温度以及吹雪特性。 三个关键的科学问题将得到解决:是什么控制了复杂地形中积雪的近地表边界层的特征,以及这些特征如何随着时间的推移而演变? 在一个冬季,不同的边界层状态发生的频率如何,在每个过程中有多少雪升华发生,以及这如何影响总的季节性质量和能量平衡? 什么样的测量和分析策略对于量化山谷中的雪升华最为可靠?该奖项反映了NSF的法定使命,并被认为是值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估的支持。
英文摘要
Snowpack plays a vital role in water resources, especially for regions that get water from the seasonal melt of mountain snowfall. However, melting is not the only way that the snowpack is depleted. Sublimation of snow refers to the process by which snow changes directly to water vapor. The impact of sublimation is not well understood, nor are the specific atmospheric conditions that lead to more or less sublimation. This project will help to address questions related to those topics by deploying a set of advanced instrumentation in Colorado in the 2022-23 winter season. The result of this project will be a dataset that can be used to determine whether numerical models are handling sublimation correctly, and if not, how to improve them. The research team will communicate with relevant stakeholder groups, such as water managers, and develop short videos that explain difficult concepts in clear language accessible to the general public. Students will be directly involved in the field campaign, thereby training the next generation of observational and data analysis scientists.The research team will conduct the Sublimation of Snow (SOS) field campaign in Kettle Ponds, Colorado during the 2022-23 winter season. Snow sublimation plays a significant role in water resources but the physics that govern rates of sublimation are not fully understood. This project will focus on the role of wind in sublimation, both in low-wind conditions where turbulence is crucial, and in higher-wind conditions when blowing snow factors in. The SOS field campaign is embedded within a larger DOE-sponsored campaign called the Surface Atmosphere Integrated Field Laboratory (SAIL) which will provide remote sensing measurements from radars and lidars. SOS will contribute four flux towers (NCAR Integrated Surface Flux Systems, ISFS) for turbulence and latent heat flux measurements, along with a number of other instruments that will provide snow depth, density, and water content, soil and snowpack temperatures, and blowing snow characteristics. Three key science questions will be addressed: What governs the characteristics of the near-surface boundary layer over snow in complex terrain, and how these characteristics evolve through time? Over a winter season, how frequently do different boundary layer regimes occur, how much snow sublimation occurs during each, and how does this affect the total seasonal mass and energy balance? What measurement and analysis strategies are most robust for quantifying snow sublimation in a mountain valley?This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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Managing Forests for Snow, Water, and Sustainable Ecosystems
  • 批准号:
    1703663
  • 项目类别:
    Standard Grant
  • 资助金额:
    $30.0万
  • 财政年份:
    2017
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    2014
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Collaborative Research: Process Dynamics in the Intermittent Snow Zone
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    1215771
  • 项目类别:
    Standard Grant
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    2012
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Using mesoscale climate simulations to reduce input data errors in energy balance snow hydrology models
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    0838166
  • 项目类别:
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  • 资助金额:
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  • 负责人:
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