PolarGlobe: A web-wide virtual globe system for visualizing multidimensional,time-varying,big climate data

The increasing research interest in global climate change and the rise of the public awareness have generated a significant demand for new tools to support effective visualization of big climate data in a cyber environment such that anyone from any location with an Internet connection and a web browser can easily view and comprehend the data. In response to the demand, this paper introduces a new web-based platform for visualizing multidimensional, time-varying climate data on a virtual globe. The web-based platform is built upon a virtual globe system Cesium, which is open-source, highly extendable and capable of being easily integrated into a web environment. The emerging WebGL technique is adapted to support interactive rendering of 3D graphics with hardware graphics acceleration. To address the challenges of transmitting and visualizing voluminous, complex climate data over the Internet to support real-time visualization, we develop a stream encoding and transmission strategy based on video-compression techniques. This strategy allows dynamic provision of scientific data in different precisions to balance the needs for scientific analysis and visualization cost. Approaches to represent, encode and decode processed data are also introduced in detail to show the operational workflow. Finally, we conduct several experiments to demonstrate the performance of the proposed strategy under different network conditions. A prototype, PolarGlobe, has been developed to visualize climate data in the Arctic regions from multiple angles.     

Real-time storm detection and weather forecast activation through data mining and events processing

Each year across the USA, destructive weather events disrupt transportation and commerce, resulting in both loss of lives and property. Mitigating the impacts of such severe events requires innovative new software tools and cyberinfrastructure through which scientists can monitor data for specific severe weather events such as thunderstorms and launch focused modeling computations for prediction and forecasts of these evolving weather events. Bringing about a paradigm shift in meteorology research and education through advances in cyberinfrastructure is one of the key research objectives of the Linked Environments for Atmospheric Discovery (LEAD) project, a large-scale, interdisciplinary NSF funded project spanning ten institutions. In this paper we address the challenges of making cyberinfrastructure frameworks responsive to real-time conditions in the physical environment driven by the use cases in mesoscale meteorology. The contribution of the research is two-fold: on the cyberinfrastructure side, we propose a model for bridging between the physical environment and e-Science¹ workflow systems, specifically through events processing systems, and provide a proof of concept implementation of that model in the context of the LEAD cyberinfrastructure. On the algorithmic side, we propose efficient stream mining algorithms that can be carried out on a continuous basis in real time over large volumes of observational data. ¹ e-Science is used to describe computationally intensive science that is typically carried out in highly distributed network     

高端计算机网络共享系统支撑的科学和工程革新

科学和工程研究被计算、信息和通讯技术的持续进步推动着，被今天自身研究增加的复杂性、范围和尺度的挑战拉动着。数字计算、数据、信息和网络以及计算机模拟技术的应用，正在形成替代和拓展理论/分析、实验/观察2个经典的研究方法去创建新的学科的趋势。近来多种趋势表明一个如何创造、传播和存储科学和工程知识更伟大、更迅速的真正变革即将到来，美国应当把握这个机遇、承担责任，去整合和拓展数字革命的成果，服务于下一代的科学和工程研究及相关教育。高端计算机网络共享系统的关键在于将数据、信息、工具、仪器，包括超级计算、存储以及交流等综合性的知识资源完全服务于具体的研究群体，提供新的途径，使研究人员在发现和探索研究上获得更多更好的信息，使得研究小组跨时间、区域、部门甚至学科间实现共享和协作。坚持美国学术研究团体所使用的高端科学计算必须是最先进的，国际科学基金会与其它适当团体机构间的合作应该为创造和维持现代数据驱动科学研究所必需的重要数据资料档案库负主要责任2个原则，并通过建立NSF内部组织、科学和工程组织来保障系统的实施。这是美国国家科学基金会(NSF)信息基础设施（Cyberinfrustructure）高级咨询组的报告《通过信息基础设施促进科学和工程的革命》的主要内容。 