EAGER: Collaborative Research: Mapping Melting Glacial Surfaces with GNSS Reflectometry

第一部分：非技术性的全球导航卫星系统（GNSS），如全球定位系统（GPS）不断向地球发送信号。 虽然许多人可能熟悉使用GPS信号进行定位和导航，但这些信号也可用于感测地球环境。 冰雪表面不断被全球导航卫星系统广播的无线电信号淹没。 当信号从冰或雪表面反射回来，然后到达接收器时，它就像一种雷达，其中雷达发射器是自由的，覆盖地球仪，总是开着的，不受降水的影响。 这项工作将建立和部署一个全球导航卫星系统反射计（GNSS-R）系统，专门用于探测冰川表面的反射。 这项工作的目标是找出信号如何根据表面类型而变化，特别是使用GNSS作为雷达是否可以有效地监测冰雪融化和冰川表面的冻结。在该系统中，将使用两个GNSS天线和接收器，一个面向上用于定位，一个面向下用于收集表面反射。 在南极洲美国麦默多站附近的麦克默多冰架上的冰跑道附近建立GNSS-R系统，该系统将监测信号的变化，因为它交替反射表面冰，融水和雪。 通过现场的摄像机图像和激光雷达勘测，将全球导航卫星系统“雷达”信号及其反射区域（从几何学可知，因为全球导航卫星系统卫星和接收器位置已知）与地表类型联系起来。 如果GNSS-R发展到与现有的冰冻表面特征描述方法相当或更好的程度，它将在从局部消融监测到飞机跑道安全评估等应用中找到一席之地。 第二部分：技术描述拟议的研究旨在回答以下问题：全球导航卫星系统（GNSS）反射计（GNSS-R）能否用于以高时空分辨率可靠地绘制恶劣冰川环境中的积雪、冰和地表水？ 我们的工作假设是，GNSS-R可以区分冷雪，湿雪，裸冰，湿冰和地表水，从而产生观测结果，可以告知冰川表面如何积累和消融。 该项目将通过进行全球导航卫星系统R仪器设计、实地试验和信号处理以及与其他方法包括目前使用的单天线干涉反射法进行比较来检验这一假设。其目的是开发全球导航卫星系统R仪器和数据处理技术，作为一种有效的高时空分辨率方法，用于确定与南极冰盖气候变化有关的雪、积雪和融冰表面的构成特征。GNSS-R接收器系统将在信号与表面（在这种情况下为冰川）相互作用后捕获信号，以推断表面的可变成分。被动雷达回波强度将用于表征表面类型，无论是雪，积雪，冰，还是水。该奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

Part I: Nontechnical Global navigation satellite systems (GNSS) such as the Global Positioning System (GPS) are continuously transmitting signals toward Earth. While many people may be familiar with using the GPS signals for positioning and navigation, these signals are also usable for sensing Earth’s environment. Ice and snow surfaces are continuously awash with radio signals broadcast from GNSS. When the signal bounces off the ice or snow surface and then arrives at a receiver, it acts as a form of radar, in which the radar transmitter is free, covers the globe, is always on, and is unaffected by precipitation. This work will build and deploy a GNSS reflectometry (GNSS-R) system specifically to detect reflections off glaciated surfaces. The goal of the work is to find out how the signal changes depending on surface type, and specifically, whether using GNSS as a radar can be effective for monitoring snow and ice melt and freeze on a glaciated surface. In this system, two GNSS antennas and receivers will be used, one facing upward for positioning, and one directed downward to collect the surface reflections. Setting up the GNSS-R system near the ice runways on the McMurdo Ice Shelf, near to the US McMurdo Station, Antarctica, the system will monitor for variations in the signal as it reflects off alternately surface ice, meltwater, and snow. With camera images and lidar surveys at the site will relate the GNSS “radar” signal and the area it bounced from (knowable from geometry because the GNSS satellite and receiver locations are known) to the surface type. If GNSS-R is developed to the point of being comparable to or better than existing ways of characterizing frozen surfaces, it would find a niche in applications ranging from local ablation monitoring to assessment of aircraft runway safety. Part II: Technical Description The proposed research aspires to answer the question: Can global navigation satellite system (GNSS) reflectometry (GNSS-R) be used to reliably map snow-cover, ice, and surface water in a harsh glaciated environment at high spatio-temporal resolution? Our working hypothesis is that GNSS-R can differentiate among cold snow, wet snow, bare ice, wet ice, and surface water in a way that will yield observations that can inform how glacial surfaces accumulate and ablate. This project will test this hypothesis by conducting GNSS-R instrument design, field trial and signal processing, and comparison with other methods, including the single-antenna interferometric reflectometry (GNSS-IR) method currently in use. The objective is to develop GNSS-R instrumentation and data-processing techniques as an effective high-spatiotemporal-resolution method of characterizing the composition of snow, firn and melting ice surfaces relevant to climate change on the Antarctic Ice Sheet. The GNSS-R receiver system will capture the signal after it has interacted with the surface (glaciated in this case), in order to infer variable compositions of the surface. Passive radar return intensity will be used to characterize the surface type, whether snow, firn, ice, or water.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.