CC*DNI Instrument: High-Bandwidth Network Connectivity for Remote Sensing Research

科学仪器可以产生大量数据。除了捕获和存储数据之外，让全球研究界快速访问这些数据也很重要。对于多普勒天气雷达等遥感仪器，此类仪器在将其连接到高带宽网络方面面临的挑战是，它们必须放置在实验室外非常适合其传感任务的位置，而这些位置通常不靠近高带宽网络基础设施。例如，雷达理想地放置在没有任何障碍物的位置，这样它就可以在尽可能少的干扰下扫描大气。该项目的总体目标是通过为研究人员提供从传感器到远程存储和计算实时传输高带宽时间序列或光谱数据以及通过光纤无线电传输模拟信号的能力，来改进以遥感为重点的研究。该项目改善了从托管雷达和其他大气传感器的校园塔到麻省大学阿默斯特分校计算机网络的连接。塔楼与主园区网络之间建立光纤连接，塔楼本地存储容量增至 8 TB。这种集成为天气系统研究提供了几种新的实时数据分析模式，并允许捕获更多数据和更及时地访问数据。改善大气观测对一般天气建模，特别是天气预警和预测具有重大影响。因此，该项目有可能支持提高美国社区和整个国家安全的应用程序。此外，该校园网络基础设施为学生提供了新的机会。例如，学生可以获得实时模拟或高带宽时间序列雷达数据来进行实验。

Scientific instruments can produce vast amounts of data. Besides capturing and storing data, it is important to give the global research community fast access to this data. In the case of remote sensing instruments like Doppler weather radar the challenges such instruments face in terms of connecting them to high-bandwidth networks is the fact that they have to be placed outside the lab at locations that are well suited for their sensing tasks, which are often not close to high-bandwidth networking infrastructure. For example, a radar is ideally placed at a location that is free of any obstructions such that it can scan the atmosphere with as little interference as possible.The overarching goal of this project is to improve research that focuses on remote sensing by providing researchers the ability to transmit high-bandwidth time-series or spectral data, and analog signals via radio over fiber, in real time from sensors to remote storage and computing. The project improves connectivity from an on-campus tower hosting radar and other atmospheric sensors to the UMass Amherst computer network. A fiber connection is established between the tower and the main campus network with local storage capacity increases to 8 TB at the tower. This integration permits several new modes of real time data analysis for weather system research and allows for both more data to be captured and for more timely access to data.Improving atmospheric observations has significant impacts on weather modeling in general and weather warning and prediction in particular. Thus this project has the potential to support applications that increase the safety and security of US communities and the nation as a whole. In addition, this campus network infrastructure opens new opportunities for students. For example, students can obtain live analog or high-bandwidth time series radar data to experiment with.