Remote sensing of snow using active and passive microwave systems

雪和冰川融化为世界六分之一以上的人口提供了水，但观察到的变化和融雪供应的模型预测表明，到2050年，加拿大和欧亚大陆一些地区未来的水需求可能无法通过融雪径流来满足(Mankin等人，2015)。雪对商业活动也很重要。例如，2012-13年不列颠哥伦比亚省滑雪业的收入为13亿美元，占全省年度旅游活动的9%。然而，降雪也会带来巨大的经济成本。春季积雪快速融化引发的洪水造成的危险也可能是毁灭性的。例如，最近发生在萨斯喀彻温省南部和埃尔克河流域的2013年洪水预计造成的损失超过60亿美元(Pomeroy等人)。2015年)，使其成为加拿大近代史上损失最大的自然灾害之一。虽然积雪是一种重要的资源，但随着冬季雪季制度随着全球变暖而发生变化，积雪的管理正变得越来越具有挑战性。例如，雪季正在缩短，平均融雪日期在该季节提前(德克森和布朗，2012)。在依赖融雪径流的地区，变化影响到滑雪业、粮食生产和水力发电。雪水当量(SWE)积累对水资源管理者来说至关重要，因为它揭示了雪中储存了多少水。这项提议的目的是增进我们对主动和被动微波遥感系统的了解和使用，改进我们在气候学和水资源应用方面对SWE的估计。提出了三个研究目标。首先，利用雷达测量来估计L、C、X和Ku频率下积雪覆盖地区的SWE。关于下层有机土壤、雪中埋藏的植被和积雪覆盖的森林景观的雷达响应的知识尚不完整，但对于改善存在植被(低矮或高大的树冠)情况下的SWE估计很重要。此外，对雪的干涉成像雷达观测已经显示出对SWE的强烈敏感性(Leinss等人。2015年)，这项提案将在更大范围的雪地环境中证实这些发现。第二，该提案将重点结合不同的卫星多传感器积雪产品。这将提供对现有数据之间的一致和分歧的洞察，并将告知如何减少SWE估计中的不确定性，以创建更稳健的SWE时间序列。第三，研究将使用前两个目标中部署的技术和方法来开发和探索新的科学应用。例如，我的Snowtwets研究项目寻求与学校项目连接以收集积雪深度数据，该项目将绘制多传感器SWE数据地图，并结合众包积雪深度数据，为SWE地图提供强大的多源方法。

Snow and glacier melt provide water for more than one sixth of the world's population yet observed changes and model predictions of snowmelt supply suggest that by 2050 future water demands in several parts of Canada and Eurasia are at risk of not being met by snow melt runoff (Mankin et al., 2015). Snow is also important for business activities. For example, the British Columbia ski industry revenue for 2012-13 was $1.3 billion which represents 9% of all annual provincial tourism activity. Yet snow also attracts significant economic costs. Hazards created by flooding from rapid spring snowmelt can also be devastating. For example, the recent 2013 flood in the South Saskatchewan and Elk river basins have been projected to cost in excess of $6 billion (Pomeroy et al. 2015), making it one of the costliest natural disasters in recent Canadian history. While snow accumulation is an important resource, its management is becoming increasingly challenging as the winter snow season regime changes with global warming. For example, the snow season is shortening with the average snow melt date shifting earlier in the season (Derksen and Brown, 2012). Changes impact the ski industry, food production and the hydroelectric power generation in regions that rely on snowmelt runoff.******Snow water equivalent (SWE) accumulation is of keen importance for water resource managers because it reveals how much water is stored in snow. The goal of this proposal is to increase our understanding and use of active and passive microwave remote sensing systems improve our estimation of SWE, both for climatology and water resources applications. Three research objectives are proposed. First, to exploit the use of radar measurements to estimate SWE in snow covered terrain at L, C, X and Ku frequencies. Knowledge about the radar response from underlying organic soils, buried vegetation within snow and from snow covered forest landscapes is incomplete yet important to improve estimates of SWE in the presence of vegetation (low or tall stand canopies). In addition, interferometric imaging radar observations of snow have demonstrated strong sensitivity to SWE (Leinss et al. 2015) and this proposal will confirm these findings over a wider range of snow environments. Second, the proposal will focus on combining different satellite multi-sensor snow products. This will provide insights into agreements and disagreements between existing data and will inform how the uncertainties in the SWE estimates might be reduced to create a more robust time series of SWE. Third, the research will use techniques and methods deployed in the first two objectives to develop and explore new science applications. For example, my Snowtweets research project, which seeks to connect with school programmes to collect snow depth data, will map multi-sensor SWE data in combination with crowdsourced snow depth data to provide a powerful multi-source approach to SWE mapping.