Machine Learning in Heliophysics and Space Weather Forecasting: A White Paper of Findings and Recommendations
New Jersey Institute of Technology（新泽西理工学院）；Georgia State University（佐治亚州立大学）；Academy of Athens（雅典学院）；NASA Ames Research Center（美国国家航空航天局艾姆斯研究中心）；Bay Area Environmental Research Institute（湾区环境研究所）；University of Colorado, Boulder（科罗拉多大学博尔德分校）；Rutgers, The State University of New Jersey（罗格斯，新泽西州立大学）；National Radio Astronomy Observatory（美国国家射电天文台）；National Solar Observatory（美国国家太阳天文台）；California Institute of Technology（加州理工学院）；Montclair State University（蒙特克莱尔州立大学）
Gelu Nita, Manolis Georgoulis, Irina Kitiashvili, Viacheslav Sadykov, Enrico Camporeale, Alexander Kosovichev, Haimin Wang, Vincent Oria, Jason Wang, Rafal Angr… 展开作者
Gelu Nita, Manolis Georgoulis, Irina Kitiashvili, Viacheslav Sadykov, Enrico Camporeale, Alexander Kosovichev, Haimin Wang, Vincent Oria, Jason Wang, Rafal Angryk, Berkay Aydin, Azim Ahmadzadeh, Xiaoli Bai, Timothy Bastian, Soukaina Filali Boubrahimi, Bin Chen, Alisdair Davey, Sheldon Fereira, Gregory Fleishman, Dale Gary, Andrew Gerrard, Gregory Hellbourg, Katherine Herbert, Jack Ireland, Egor Illarionov, Natsuha Kuroda, Qin Li, Chang Liu, Yuexin Liu, Hyomin Kim, Dustin Kempton, Ruizhe Ma, Petrus Martens, Ryan McGranaghan, Edward Semones, John Stefan, Andrey Stejko, Yaireska Collado-Vega, Meiqi Wang, Yan Xu, Sijie Yu
The authors of this white paper met on 16-17 January 2020 at the New Jersey Institute of Technology, Newark, NJ, for a 2-day workshop that brought together a group of heliophysicists, data providers, expert modelers, and computer/data scientists. Their objective was to discuss critical developments and prospects of the application of machine and/or deep learning techniques for data analysis, modeling and forecasting in Heliophysics, and to shape a strategy for further developments in the field. The workshop combined a set of plenary sessions featuring invited introductory talks interleaved with a set of open discussion sessions. The outcome of the discussion is encapsulated in this white paper that also features a top-level list of recommendations agreed by participants.
A Machine Learning-Ready Data Processing Tool for Near Real-Time Forecasting
Southwest Research Institute（西南研究院）；The University of Texas at San Antonio（德克萨斯大学圣安东尼奥分校）；Space Weather Prediction Center, NOAA（美国国家海洋和大气管理局空间天气预测中心）；Cooperative Institute for Research in Environmental Sciences, University of Boulder（科罗拉多大学环境科学合作研究所）
Deep Learning for Space Weather Prediction: Bridging the Gap between Heliophysics Data and Theory
NASA, Goddard Space Flight Center（美国国家航空航天局戈达德太空飞行中心）；Columbia University（哥伦比亚大学）；Trident Vantage Systems, LLC（三叉戟优势系统有限责任公司）；Catholic University of America（美国天主教大学）；Atmosphere and Space Technology Research Associates（大气与空间技术研究联合公司）；ADNET Systems, Inc.（ADNET系统公司）
Deep learning-based method for weather forecasting: A case study in Itoshima
Joint Graduate School of Mathematics for Innovation, Kyushu University（九州大学创新数学联合研究生院）；International Institute for Carbon-Neutral Energy Research, Kyushu University（九州大学国际碳中和能源研究所）；Institute of Tropical Agriculture, Kyushu University（九州大学热带农业研究所）；Faculty of Agriculture, Kyushu University（九州大学农学院）
Benchmarking Physics-Informed Time-Series Models for Operational Global Station Weather Forecasting
Department of Computer Science and Engineering, Hong Kong University of Science and Technology, Hong Kong SAR China（香港科技大学计算机科学与工程系）；Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China（南方科技大学计算机科学与工程系）；School of Computer and Information Sciences, University of Newcastle, Newcastle, Australia（新castle大学计算机与信息科学学院）；Hangzhou Innovation Institute of Beihang University, Hangzhou, China（北京航空航天大学杭州创新研究院）；Shanghai Artificial Intelligence Laboratory, Shanghai, China（上海人工智能实验室）
FengWu-GHR: Learning the Kilometer-scale Medium-range Global Weather Forecasting
Shanghai AI Laboratory（上海人工智能实验室）；Hong Kong University of Science and Technology（香港科技大学）；Nanjing University of Information Science and Technology（南京信息工程大学）；National Meteorological Information Center of CMA（中国气象局国家气象信息中心）；National Meteorological Center of CMA（中国气象局国家气象中心）
University of Cambridge（剑桥大学）；Vector Institute（矢量研究所）；University of Toronto（多伦多大学）；Microsoft Research（微软研究院）；British Antarctic Survey（英国南极调查局）；The Alan Turing Institute（阿兰·图灵研究所）；European Centre for Medium-Range Weather Forecasts（欧洲中期天气预报中心）；Google Deepmind（谷歌DeepMind）
