SWQU: Composable Next Generation Software Framework for Space Weather Data Assimilation and Uncertainty Quantification

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This project seeks to develop the next generation of software for space weather modeling and prediction by bringing together experts in geospace sciences, uncertainty quantification, and software development, management, and sustainability. The electronic technologies that govern modern life are deeply dependent on satellite technologies such as the Global Positioning System (GPS), which helps us navigate cities and manages air-traffic all over the world. These satellites are also the de facto timing standard of technology and commerce, used to synchronize banking transactions worldwide, our smart-phones, and the internet. Yet, the accuracy and robustness of their signals are highly vulnerable to geospace disturbances. Satellite orbits have to be controlled precisely and to do so, geospace disturbances have to be predicted in advance. Space weather models with quantifiable predictive capability are the tools that are needed, and are presently largely absent, to continue to advance the satellite technologies and everything that depends on them. The composable software framework to be developed under this project will serve as a foundation that can be expanded on and improved over time, growing both the space weather prediction capabilities and the space weather modeling community.Composable software is the crucible of computational science, allowing scientists to add their contribution to the numerical realm without having to repeat the work of others. The goal of this project is to build a next-generation framework for space weather uncertainty quantification and data assimilation, as the foundation of the growing body of computational tools for the field. The "must-haves" for this framework will be modern dispatch-based composability, reproducibility, ease-of-use, performance, portability, and extendability to today's and tomorrow's heterogeneous and novel architectures. This project will produce computationally scalable algorithms and open-source Julia-based software framework for data-driven models of space weather with the following properties: i) Composability: Software is composable when features and behaviors work together. For example, if uncertainty quantification can be applied to a program without a rewrite, the program and the uncertainty quantification compose; ii) Sustainability: Software is sustainable when the author of the program can leave the project, and new members of the project can maintain the software; iii) Portability: Software is portable when it can perform on heterogeneous hardware with a variety of underlying architectures; iv) Reproducibility: Software is reproducible today and into the future when a convenient and backward compatible pathway exists for users to readily examine, run, share, and modify code.This award is made as a part of the joint NSF-NASA pilot program on Next Generation Software for Data-driven Models of Space Weather with Quantified Uncertainties (SWQU). It is supported by NSF Division of Atmospheric and Geospace Sciences, Division of Mathematical Sciences, Office of Advanced Cyberinfrastructure, and Office of Multidisciplinary Activities. All software developed as a result of this award will be made available by the awardee free of charge for non-commercial use; the software license will permit modification and redistribution of the software free of charge for non-commercial use.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.