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

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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.