Remote sensing of snow using active and passive microwave instruments

使用主动和被动微波仪器遥感雪

• 批准号: 341922-2012
• 负责人: Kelly, Richard
• 金额: $ 2.33万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=595528
• 关键词: Remote; sensing; snow; using; active

The Earth's seasonal snow cover exerts an important effect on climate and on water resources, transportation and agriculture, and related socio-economic activities in many countries of the world. The presence of snow and its albedo effect on the climate system influences climate state and can affect climate dynamics through amplified warming in polar and mountain regions. Snow also accounts for a significant portion of the Earth's useable freshwater. Knowledge of accumulated snow water equivalent (SWE) informs water managers of how much melt can be expected in spring. The long term objectives of this research are to develop improved snow accumulation estimates (SWE or snow depth) from satellite remote sensing instruments for use in river forecasting and for a better understanding of how snow accumulation is changing in the Earth's system. To achieve this, three primary objectives are defined. (1) develop a new high spatial resolution radar remote sensing approach for SWE estimation, particularly in mountain terrain and forested areas, using state of the art ground-based radar measurements of snow. This will require deployment of radar instruments to different landscapes for key periods in the winter snow season (early season freeze, mid-season accumulation and late season melt) to observe and quantify changes in snow and characterize them to develop estimation methods. (2) Leverage recent research developments in retrieval science that combine active and passive microwave remote sensing measurements to enable improved SWE estimates at the passive microwave observation scale. Having enhanced the coarse resolution passive microwave SWE data, the proposal will explore downscaling methods (Bayesian) to to estimate SWE at higher spatial resolution and generate a time series from 1979- present. This links well with a satellite SWE algorithm development and maintenance project funded by the Japan Aerospace Exploration Agency. (3) develop my Web 2.0 initiative, Snowtweets, for leveraging crowdsourced data for augmenting existing in situ snow depth data from established networks (federal, provincial and regional utility levels).

地球季节性积雪对世界许多国家的气候、水资源、交通和农业以及相关社会经济活动产生重要影响。雪的存在及其对气候系统的反照率影响会影响气候状态，并可能通过加剧极地和山区的变暖来影响气候动态。雪还占地球可用淡水的很大一部分。了解累积雪水当量 (SWE) 可以让水资源管理者了解春季预计的融化量。这项研究的长期目标是通过卫星遥感仪器开发改进的积雪估计（SWE或积雪深度），用于河流预报，并更好地了解地球系统中积雪的变化。为了实现这一目标，定义了三个主要目标。 (1) 开发一种新的高空间分辨率雷达遥感方法，用于 SWE 估计，特别是在山区地形和森林地区，使用最先进的地面雷达积雪测量。这将需要在冬季雪季的关键时期（早期结冰、中期积雪和晚期融化）将雷达仪器部署到不同的景观，以观察和量化积雪的变化，并对其进行表征，以开发估计方法。 (2) 利用检索科学的最新研究进展，将主动和被动微波遥感测量相结合，以改进被动微波观测尺度的 SWE 估计。在增强了粗分辨率无源微波 SWE 数据后，该提案将探索降尺度方法（贝叶斯），以更高的空间分辨率估计 SWE，并生成 1979 年至今的时间序列。这与日本宇宙航空研究开发机构资助的卫星 SWE 算法开发和维护项目密切相关。 (3) 开发我的 Web 2.0 计划 Snowtweets，利用众包数据来增强来自已建立网络（联邦、省和地区公用事业级别）的现有原位雪深数据。