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/E013902/1
• 负责人: Nick Rutter
• 金额: $ 26.38万
• 依托单位: University of Sheffield
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2007
• 资助国家: 英国
• 起止时间: 2007 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FE013902%2F1
• 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）是已知积雪面积的水的液体当量。季节性和年际变化的全球范围内的SWE有一个强大的和复杂的影响，估计全球能源平衡。由于全球能量平衡是用于预测气候变化的全球气候模式的重要组成部分，因此识别并最大限度地减少SWE估计中的当前不确定性以减少其对未来气候情景预测的影响至关重要。SWE的分布在空间和时间上变化很大，甚至在平坦、不复杂的陆地表面上也是如此。因此，为了在全球范围内充分估计SWE，需要在200-500米的水平分辨率和15天的时间分辨率（或当积雪融化时甚至更少）下进行观测。需要在这些分辨率下对SWE进行观测，以充分测试全球气候模型对SWE的预测能力;特别是全球气候模型对SWE预测的准确性对这些模型对未来气候情景的预测能力具有重要的连锁效应。然而，目前的观测结果不符合这些横向和时间的要求。地面SWE观测的全球分布过于稀疏，尽管卫星观测更接近于评估模拟估计所需的更大空间范围，但目前可用的卫星传感器都不是专门用于测量SWE的;用于获得SWE估计值的那些传感器的水平分辨率仅为25，000米。因此，我们迫切需要找出：“我们如何才能减少目前卫星传感器对SWE估计的不确定性，我们能否为专门用于观察SWE的新传感器提供科学依据？”地面雷达最近的技术进步意味着，第一次，SWE的观测（精度为10%）可以使用连接到雪地车的廉价，轻便，低功率雷达系统以每秒50次观测的速度进行观测。该提案将利用这些技术进步，在目前卫星传感器的覆盖范围（25 x 25公里）内进行高水平分辨率测量（~10厘米），这将使SWE的不确定性得到准确评估。将定期从雪坑观测SWE和其他积雪特性，以双重检查雷达观测的准确性。此外，SWE的每小时变化将使用该雷达系统进行观察，因为积雪首先积累，然后在整个年度周期中融化。在整个冬季，将以相对于积雪表面的一系列频率和角度进行每小时的雷达观测。这将模拟已提出专门测量SWE的潜在新传感器。目前，所提出的新传感器的能力，旨在观察SWE只证明了理论研究。这项工作将提供第一个数据集，能够在广泛的积雪条件下测试这些理论研究。使用计算机模型估计SWE和其他积雪特性（例如温度、粒度和液态水含量的垂直分布）将提供基本的每小时信息，以解释和与雷达观测进行比较。定期的雪坑将再次被用来仔细检查模型估计和雷达观测的准确性。这项建议的时间和重点利用了目前计划在2007-10年进行的特殊后勤和科学机会，这是美国航天局和欧洲航天局正在进行的工作的一部分。它将为目前和未来专门用于观测SWE的卫星的建议增加巨大价值，更广泛地说，它将促进雪科学研究的合作性和国际性，作为国际极地年的一部分。

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