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: 2014
• 资助国家: 加拿大
• 起止时间: 2014-01-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=549544
• 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).

地球的季节性积雪对世界许多国家的气候和水资源、交通和农业以及相关的社会经济活动产生了重要影响。雪的存在及其对气候系统的反照率效应会影响气候状态，并可能通过放大极地和山区的变暖来影响气候动态。雪也占了地球上可用淡水的很大一部分。积雪水当量(SWE)的知识可告知水管理人员春季可预期融化多少。这项研究的长期目标是改进卫星遥感仪器的积雪估算(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情况。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，用于估计SWE，特别是在山区和林区，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(初季冰冻、季中积雪和季末融化)的不同地貌部署雷达仪器，以观察和量化雪的变化并确定其特征，以制定估计方法。(2)利用恢复科学的最新研究进展，将主动和被动微波遥感测量结合起来，以改进被动微波观测尺度上的SWE估计。在增强了粗分辨率被动微波SWE数据后，该提议将探索降尺度方法(贝叶斯)，以在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有很好的联系。(3)开发我的网络2.0倡议--Snowtweet，利用众包数据，从已建立的网络(联邦、省和地区公用事业级别)扩大现有的现场积雪深度数据。