SI2-SSI: Lidar Radar Open Software Environment (LROSE)

SI2-SSI：激光雷达开放软件环境（LROSE）

• 批准号: 1661663
• 负责人: Michael Bell
• 金额: $ 250万
• 依托单位: Colorado State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-15 至 2022-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1661663&HistoricalAwards=false
• 关键词: SI2; SSI; Lidar; Radar; Open

Modern radars and lidars are a diverse class of instruments, capable of detecting molecules, aerosols, birds, bats and insects, winds, moisture, clouds, and precipitation. Scientists and engineers use them to perform research into air quality and pollution, dangerous biological plumes, cloud physics, cloud extent, climate models, numerical weather prediction, road weather, aviation safety, severe convective storms, tornadoes, hurricanes, floods, and movement patterns of birds, bats and insects. Radars and lidars are critical for protecting society from high impact weather and understanding the atmosphere and biosphere, but they are complex instruments that produce copious quantities of data that pose many challenges for researchers, students, and instrument developers. This project will develop a new set of tools called the Lidar Radar Open Software Environment (LROSE) to meet these challenges and help address the 'big data' problem faced by users in the research and education communities. This project will open new avenues of scientific investigation, including data assimilation to improve weather forecasts, and help to maximize returns on NSF investments in weather and climate research by providing better software tools to researchers, students, and educators. Improving the effectiveness of NSF research will provide significant scientific and societal benefits through an improved understanding of many diverse scientific topics that are relevant to public safety, national defense, and the global economy.The LROSE project will develop a 'Virtual Toolbox' with a set of software tools needed for a diverse set of scientific applications. LROSE will be packaged so that it can be run on a virtual machine (VM), either locally or in the cloud, and stocked with core algorithm modules for those typical processing steps that are well understood and documented in the peer-reviewed literature. LROSE will enable the user community to use the core toolset to develop new research modules that address the specific needs of the latest scientific research. Through the VM Toolbox and a core software framework, other developers of open-source radar software can then provide their own compatible software tools to the set. By combining the open source approach with recent developments in virtual machines and cloud computing, we will develop a system that is both highly capable and easy to run on virtually any hardware, without the complexity of a compilation environment. The LROSE project will build on existing prototypes and available software elements, while facilitating community development of new techniques and algorithms to distribute a suite of documented software modules for performing radar and lidar analysis. These modules will each implement accredited scientific methods referencing published papers. The infrastructure and modules will allow researchers to run standard procedures, thereby improving the efficiency and reproducibility of the analyses, and encourage researchers to jointly develop new scientific approaches for data analysis. The use of collaborative open source methods will lead to a suite of available algorithmic modules that will allow scientists to explore radar and lidar data in new, innovative ways. Researchers will benefit from the improved toolset for advancing understanding of weather and climate, leading to a positive outcome in the advancement of scientific knowledge and societal benefits.

现代雷达和激光雷达是一种多样化的仪器，能够检测分子，气溶胶，鸟类，蝙蝠和昆虫，风，水分，云和降水。科学家和工程师利用它们对空气质量和污染，危险的生物羽流，云物理，云范围，气候模型，数值预测，道路天气，航空安全，严重的对流风暴，龙卷风，飓风，洪水，洪水和运动模式，鸟类和昆虫的运动模式进行研究。雷达和激光雷达对于保护社会免受高影响的天气和了解气氛和生物圈至关重要，但是它们是复杂的工具，它们会产生大量数据，这些数据对研究人员，学生和仪器开发人员构成许多挑战。该项目将开发一套称为LIDAR RADAR OPEN软件环境（LROSE）的新工具，以应对这些挑战并帮助解决研究和教育社区中用户所面临的“大数据”问题。该项目将开放科学研究的新途径，包括数据同化以改善天气预测，并通过向研究人员，学生和教育者提供更好的软件工具，从而帮助最大程度地提高NSF的天气和气候研究投资回报。提高NSF研究的有效性将通过对与公共安全，国防和全球经济相关的许多多样化的科学主题的了解，从而为科学和社会福利提供巨大的利益。Lrose项目将开发“虚拟工具箱”，并使用一系列多样化的科学应用程序开发一套软件工具。 Lrose将被打包，以便可以在本地或云中的虚拟机（VM）上运行，并在Peer-Respewew的文献中备有核心算法模块的库存算法模块。 Lrose将使用户社区能够使用核心工具集开发新的研究模块，以满足最新科学研究的特定需求。通过VM工具箱和核心软件框架，其他开源雷达软件的开发人员可以为该集合提供自己的兼容软件工具。通过将开源方法与虚拟机和云计算的最新开发方法相结合，我们将开发一个系统，该系统既有能力又易于在任何硬件上易于运行，而没有编译环境的复杂性。 Lrose项目将基于现有的原型和可用的软件元素，同时促进了新技术和算法的社区开发，以分发一套已记录的软件模块，用于执行雷达和激光雷达分析。这些模块将每个模块都实施参考已发表论文的认可的科学方法。基础设施和模块将使研究人员能够运行标准程序，从而提高分析的效率和可重复性，并鼓励研究人员共同开发新的科学方法进行数据分析。协作开源方法的使用将导致一系列可用的算法模块，这些模块将使科学家以新的创新方式探索雷达和激光雷达数据。研究人员将从改进的工具集中受益，以促进对天气和气候的了解，从而在进步科学知识和社会利益方面取得积极成果。