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）是已知积雪区水的液体当量。全球SWE范围的季节和年际变化对全球能量平衡的估计具有强烈而复杂的影响。由于全球能源平衡是用于预测气候变化的全球气候模式的重要组成部分，因此识别和最小化SWE估计中当前的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是高度可变的；即使是在平坦、简单的地面上。因此，要在全球尺度上对SWE进行充分的估计，需要在200-500米的水平分辨率和15天的时间分辨率下进行观测（当积雪融化时甚至更短）。需要在这些分辨率下对SWE进行观测，以充分检验全球气候模式预测SWE的准确性；特别是由于全球气候模式对SWE预测的准确性对这些模式预测未来气候情景的准确性具有重要的连锁效应。然而，目前对SWE的观测不能满足这些水平和时间要求。地面SWE观测的全球分布过于稀疏，虽然卫星观测更接近评估模拟估计值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为测量SWE而设计的；那些用来估计SWE的水平分辨率只有25000米。因此，我们迫切需要弄清楚：“我们如何减少现有卫星传感器对SWE估计的不确定性，我们能否为专门设计用于观测SWE的新传感器提供科学依据？”地面雷达的最新技术进步意味着，使用附着在雪地摩托上的廉价、轻便、低功率雷达系统，第一次可以以每秒50次的速度观测到SWE（精度为10%）。该提案将利用这些技术进步，在当前卫星传感器（25 x 25公里）的足迹范围内进行高水平分辨率测量（~10厘米），这将允许准确评估SWE的不确定性。我们将定期从雪坑观测SWE和其他积雪特性，以对雷达观测的准确性进行双重检查。此外，使用该雷达系统可以观察到积雪在一年的周期中首先积累然后融化的每小时变化。每小时的雷达观测将在整个冬季进行，频率和角度相对于积雪表面的范围。这将模拟潜在的新型传感器，这些传感器已被提议专门测量SWE。目前，设计用于观测SWE的新传感器的能力仅通过理论研究来证明。这项工作将提供第一个能够在大范围积雪条件下测试这些理论研究的数据集。利用计算机模型估计SWE和其他积雪特性（例如温度、颗粒大小和液态水含量的垂直剖面）将提供必要的每小时信息，以便与雷达观测进行解释和比较。周期性的雪坑将再次用于检查模拟估计和雷达观测的准确性。该提案的时间和重点利用了特殊的后勤和科学机会，目前计划在2007- 2010年作为美国宇航局和欧洲航天局正在进行的工作的一部分。它将大大增加目前和未来关于专门用于观测SWE的卫星的建议的价值，更一般地说，它将作为国际极地年的一部分，促进雪科学研究的合作性和国际性。

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