Improving current and future satellite observations of snow water equivalent

改进当前和未来的雪水当量卫星观测

• 批准号: NE/E013902/2
• 负责人: Nick Rutter
• 金额: $ 4.44万
• 依托单位: Northumbria University
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2009
• 资助国家: 英国
• 起止时间: 2009 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FE013902%2F2
• 关键词: Improving; current; future; satellite; observations

Snow water equivalent (SWE) is the liquid equivalent of water of a known area of snowpack. Seasonal and inter-annual changes in the global extent of SWE have a strong and complex influence on estimates of the global energy balance. As the global energy balance is an important part of global climate models, which are used to predict climate change, it is vital that current uncertainties in SWE estimates are identified and minimised to reduce their impact on predictions of future climate scenarios. The distribution of SWE can be highly variable over space and time; even over flat, uncomplicated land surfaces. Consequently, to get an adequate estimate of SWE on a global scale, observations are required at a horizontal resolution of 200-500 m and a temporal resolution of 15 days (or even less when snowpacks are melting). Observations of SWE at these resolutions are required to adequately test how well global climate models predict SWE; particularly as the accuracy of SWE predictions by global climate models has an important knock-on effect as to how well such models predict future climate scenarios. However, current observations of SWE do not meet these horizontal and temporal requirements. The global distribution of ground-based SWE observations are too sparse and, although satellite observations more closely match the greater spatial extents required to evaluate modelled estimates, none of the currently available satellite sensors are designed specifically to measure SWE; those that are used to get some estimate of SWE only have a horizontal resolution of 25,000 m. Consequently, we urgently need to find out: 'How can we reduce uncertainty in estimates of SWE from current satellite sensors and can we provide the scientific justification for new sensors specifically designed to observe SWE?' Recent technological advances in ground-based radar has meant that, for the first time, observations of SWE (to an accuracy of 10%) are possible at a rate of up to 50 observations a second using a cheap, lightweight, low-power radar system attached to a snowmobile. This proposal will capitalise on such technological advances to make high horizontal resolution measurements (~10 cm) within the footprint of current satellite sensors (25 x 25 km), which will allow the uncertainty in SWE to be accurately assessed. Observations of SWE and other snowpack properties will be made periodically from snowpits to provide a double check on the accuracy of radar observations. Also, hourly changes in SWE will be observed using this radar system as a snowpack first accumulates and then melts-out throughout an annual cycle. Hourly radar observations will be made throughout the winter at a range of frequencies and angles relative to the snowpack surface. This will mimic potential new sensors which have been proposed to specifically measure SWE. Currently, the abilities of proposed new sensors designed to observe SWE have only been justified by theoretical studies. This work will provide the first data set that is able to test these theoretical studies over a wide range of snowpack conditions. Estimates of SWE and other snowpack properties (e.g. vertical profiles of temperature, grain size and liquid water content) using a computer model will provide essential hourly information to interpret and compare with the radar observations. Periodic snowpits will again be used to double check the accuracy of modelled estimates and radar observations. The timing and focus of this proposal takes advantage of exceptional logistical and scientific opportunities currently scheduled for 2007-10 as part of ongoing work by NASA and the European Space Agency. It will add great value to current and future proposals for satellites dedicated to the observation of SWE and, more generally, it will advance the collaborative and international nature of snow science research as part of the International Polar Year.

雪水当量（SWE）是液体等效于已知的积雪区域的水。 SWE全球范围的季节性和年际变化对全球能源平衡的估计具有很大且复杂的影响。由于全球能源平衡是用于预测气候变化的全球气候模型的重要组成部分，因此必须确定和最小化SWE估算中当前的不确定性，以减少其对未来气候场景的预测的影响。在空间和时间上，SWE的分布可能是高度可变的。甚至在平坦的，简单的陆地表面上。因此，为了在全球范围内获得适当的SWE估计，需要在200-500 m的水平分辨率和15天的时间分辨率下进行观察（甚至在雪堆融化时甚至更少）。需要在这些决议下对SWE进行观察，以充分测试全球气候模型如何预测SWE；特别是因为通过全球气候模型对SWE预测的准确性具有重要的敲门效果，即这种模型如何预测未来的气候情况。但是，当前对SWE的观察结果不符合这些水平和时间要求。基于地面的SWE观测值的全球分布太稀疏了，尽管卫星观测结果更加与评估建模估计所需的更大的空间范围相匹配，但当前可用的卫星传感器均未专门设计用于测量SWE；那些用于获得SWE的估计值的人的水平分辨率为25,000 m。因此，我们迫切需要找出：“我们如何减少当前卫星传感器的SWE估计值的不确定性，我们可以为专门设计用于观察SWE的新传感器提供科学理由？”地面雷达的最新技术进步意味着，首次使用便宜，轻巧，轻巧的低功率雷达系统以每秒50次观察到SWE（准确性为10％），这是可能的。该建议将利用这种技术进步，以在当前卫星传感器（25 x 25 km）的足迹内进行高水平分辨率测量（〜10 cm），这将使SWE中的不确定性准确地评估。将通过雪贴定期对SWE和其他积雪特性进行观察，以对雷达观测的准确性进行双重检查。同样，使用该雷达系统将SNEG的每小时变化作为积雪首先积累，然后在整个年度周期中融化。每小时雷达观察结果将在整个冬季以相对于积雪表面的各种频率和角度进行。这将模仿已提出特殊测量SWE的潜在新传感器。当前，旨在观察SWE的新传感器的能力仅通过理论研究证明是合理的。这项工作将提供第一个能够在广泛的积雪条件下测试这些理论研究的数据集。使用计算机模型的SWE和其他积雪特性（例如温度，晶粒尺寸和液体水含量的垂直轮廓）的估计将提供必不可少的小时信息，以解释和比较雷达观测值。周期性的积雪将再次用于仔细检查建模估计值和雷达观测值的准确性。该提案的时机和重点利用了目前定于2007 - 10年度的卓越后勤和科学机会，作为NASA和欧洲航天局正在进行的工作的一部分。这将为致力于观察SWE的卫星的当前和未来提案提供巨大的价值，更一般而言，它将推动雪科学研究的合作和国际性质，这是国际极性年的一部分。

项目成果

Microstructure representation of snow in coupled snowpack and microwave emission models

• DOI: 10.5194/tc-11-229-2017
• 发表时间: 2016-07
• 期刊: The Cryosphere
• 作者: M. Sandells;R. Essery;N. Rutter;L. Wake;L. Leppänen;J. Lemmetyinen

Snow stratigraphic heterogeneity within ground-based passive microwave radiometer footprints: Implications for emission modeling

地基无源微波辐射计足迹内的雪地层异质性：对发射建模的影响

• DOI: 10.1002/2013jf003017
• 发表时间: 2014
• 期刊: Earth Surface
• 作者: Rutter N

Recording microscale variations in snowpack layering using near-infrared photography

使用近红外摄影记录积雪分层的微尺度变化

• DOI: 10.3189/002214310791190938
• 发表时间: 2017
• 期刊: Journal of Glaciology
• 影响因子: 3.4
• 作者: Tape K

Brief communication: Improved measurement of ice layer density in seasonal snowpacks

简短交流：改进季节性积雪中冰层密度的测量

• DOI: 10.5194/tc-10-2069-2016
• 发表时间: 2016
• 期刊: The Cryosphere
• 作者: Watts T

Understanding Snow Microstructure for Microwave Remote Sensing

了解微波遥感中的雪微观结构

• DOI: 10.1002/2014eo470005
• 发表时间: 2014
• 期刊: Eos, Transactions American Geophysical Union
• 作者: Sandells;Hörhold;N. Rutter
• 通讯作者: N. Rutter