SH015
Machine Learning and Data Assimilation as Emerging Tools for Characterization and Forecasting of Solar Variability and Space Weather Events
Session ID#: 80120
Session Description:
The availability of large amount of observational data and their anticipated growth together with advancement in information processing (such as machine learning, data assimilation, data-driven modeling) offers new opportunities in advancing our fundamental understanding of and forecasting the dynamics of space weather processes from subsurface of the Sun to the heliosphere. Machine learning approach allows us to identify characteristic features, quantify importance of individual properties, speed up data processing, and provide a probability forecast for various events, such as emerging flux, flares, CME eruptions, SEP events, etc. Physics-based forecast of space weather conditions can be done using data-driven modeling and data assimilation approaches that allow us to link observations and models. The goal of the session is to review and discuss advancements and challenges in development and implementation of emerging tools for data analysis and modeling with the ultimate goal to characterize solar variability and predict space weather conditions.
Index Terms:
7536 Solar activity cycle [SOLAR PHYSICS, ASTROPHYSICS, AND ASTRONOMY]
7537 Solar and stellar variability [SOLAR PHYSICS, ASTROPHYSICS, AND ASTRONOMY]
7544 Stellar interiors and dynamo theory [SOLAR PHYSICS, ASTROPHYSICS, AND ASTRONOMY]
7594 Instruments and techniques [SOLAR PHYSICS, ASTROPHYSICS, AND ASTRONOMY]
Primary Convener: Irina Kitiashvili, NASA Ames Research Center, Moffett Field, CA, United States
Conveners: Chun Ming Mark Cheung, Lockheed Martin Solar and Astrophysics Laboratory, Palo Alto, CA, United States, Madhulika Guhathakurta, NASA Headquarters, Washington, DC, United States and Nagi Nicolas Mansour, NASA Ames Research Center, Moffett Field, CA, United States
Primary Liaison: Irina Kitiashvili, NASA Ames Research Center, Moffett Field, CA, United States
Information theoretic approach to discovering causalities in the solar cycle (496953)
Simon Wing, Johns Hopkins University, Baltimore, MD, United States, Jay Johnson, Andrews University, Berrien Springs, NJ, United States and Mausumi Dikpati, NCAR, Boulder, CO, United States
Heliophysics Event List: a unified database framework for a multi-mission space weather monitoring throughout the heliosphere (502063)
Olga Uritskaya1,2, Vadim M Uritsky2,3 and D Aaron Roberts4, (1)NASA Goddard Space Flight Center, Greenbelt, MD, United States, (2)Catholic University of America, Washington, DC, United States, (3)NASA Goddard Space Flight Cent, Greenbelt, MD, United States, (4)NASA Goddard SFC, Code 672, Greenbelt, MD, United States
Cluster Analysis of Spectroscopic Line Profiles in IRIS Observations and RMHD Simulations of the Solar Atmosphere (507218)
Viacheslav M Sadykov1,2, Irina Kitiashvili2 and Alexander G Kosovichev3, (1)Bay Area Environmental Research Institute, Moffett Field, CA, United States, (2)NASA Ames Research Center, Moffett Field, CA, United States, (3)New Jersey Institute of Technology, Physics, Newark, NJ, United States
Comparative Study of Data-driven Coronal Field Models with a Ground-truth Flux Emergence Simulation (518959)
Shin Toriumi, JAXA Japan Aerospace Exploration Agency, Institute of Space and Astronautical Science, Sagamihara, Japan, Shinsuke Takasao, NAOJ National Astronomical Observatory of Japan, Tokyo, Japan, Chun Ming Mark Cheung, Lockheed Martin Solar and Astrophysics Laboratory, Palo Alto, CA, United States, Chaowei Jiang, Chinese Academy of Sciences, SIGMA Weather Group, State Key Laboratory of Space Weather, National Space Science Center, Beijing, China, Yang Guo, Nanjing University, Nanjing, China, Keiji Hayashi, NorthWest Research Associates, Boulder, CO, United States and Satoshi Inoue, Nagoya University, ISEE, Nagoya, Japan
Impact on WSA coronal and solar wind predictions when optimizing its data drivers and model parameters (519075)
Charles Nickolos Arge1, Shaela I Jones1, Carl J Henney2, Grant David Meadors3, Kyle S. Hickmann3 and Humberto C Godinez4, (1)NASA Goddard Space Flight Center, Greenbelt, MD, United States, (2)Air Force Research Laboratory Kirtland AFB, Kirtland AFB, NM, United States, (3)Los Alamos National Laboratory, Los Alamos, NM, United States, (4)Los Alamos National Lab, Los Alamos, NM, United States
Convolutional Neural Networks for Predicting The Impact of Interplanetary Coronal Mass Ejections on The Near-Earth Magnetic Field (521937)
Natasha Flyer, National Center for Atmospheric Research, Computational and Information Systems Lab, Boulder, CO, United States, Anna V Malanushenko, NCAR, High Altitude Observatory (HAO), Boulder, CO, United States and Sarah E Gibson, NCAR, HAO, Boulder, CO, United States
Data Assimilative Optimization of WSA Source Surface and Interface Radii using Particle Filtering (522602)
Grant David Meadors1, Humberto C Godinez2, Kyle S. Hickmann1, Carl J Henney3, Shaela I Jones4 and Charles Nickolos Arge4, (1)Los Alamos National Laboratory, Los Alamos, NM, United States, (2)Los Alamos National Lab, Los Alamos, NM, United States, (3)Air Force Research Laboratory Kirtland AFB, Kirtland AFB, NM, United States, (4)NASA Goddard Space Flight Center, Greenbelt, MD, United States
Data Assimilation techniques for Space Weather: optimal use of data in the sparse and limited coverage of the Solar System (539040)
Dimitrios Millas1, Brecht Laperre1, Maria Elena Innocenti1,2, Giovanni Lapenta1 and Joachim Raeder3, (1)Katholieke Universiteit Leuven, Department of Mathematics, Leuven, Belgium, (2)NASA Jet Propulsion Laboratory, Pasadena, CA, United States, (3)University of New Hampshire, Institute for the Study of Earth, Oceans, and Space, Durham, NH, United States
Data assimilation with an adaptive Kalman filter for short-term forecasts of the F30 and F10.7 cm radio flux (547899)
Tatiana Podladchikova, Skolkovo Institute of Science and Technology, Moscow, Russia, Olena Podladchikova, Observatoire Royal de Belgique, Brussel, Belgium and Astrid Veronig, University of Graz, Institute of Physics, Graz, Austria
Investigating Pre-flare Signatures with K-means Clustering (554808)
Magnus Woods, Bay Area Environmental Research Institute - LMSAL, Palo Alto, CA, United States, Bart De Pontieu, Lockheed Martin Solar and Astrophysics Laboratory, Palo Alto, CA, United States and Alberto Sainz Dalda, Bay Area Environmental Research Institute - LMSAL, Palo Alto, United States
Characterization of Subsurface Flow Dynamics for Forecasting of Solar Activity (561433)
Alexander G Kosovichev1,2 and Viacheslav M Sadykov2,3, (1)New Jersey Institute of Technology, Department of Physics, Edison, NJ, United States, (2)NASA Ames Research Center, Moffett Field, CA, United States, (3)Bay Area Environmental Research Institute, Moffett Field, CA, United States
A Generalized Spectral Kurtosis Solar Image Variability Descriptor (561439)
Gelu M Nita, New Jersey Institute of Technology, Center for Solar-Terrestrial Research, Edison, NJ, United States, Viacheslav M Sadykov, Bay Area Environmental Research Institute, Moffett Field, CA, United States, Alexander G Kosovichev, New Jersey Institute of Technology, Physics, Newark, NJ, United States and Vincent Oria, New Jersey Institute of Technology, Computer Science, Newark, NJ, United States
Implementing General Adversarial Networks for Solar Proton Events (SPE) Data Augmentation (588057)
Juan Alberto Figueroa1, Ian G Richardson1, M. Leila Mays2, Yaireska M Collado-Vega3 and Maria M Kuznetsova2, (1)NASA Goddard Space Flight Center, Greenbelt, MD, United States, (2)NASA/GSFC, Greenbelt, MD, United States, (3)NASA GSFC, Greenbelt, MD, United States
Solar activity modeling: from subgranular scales to the solar cycles (600129)
Irina Kitiashvili1, Alan A Wray1, Viacheslav M Sadykov2, Alexander G Kosovichev3 and Nagi Nicolas Mansour1, (1)NASA Ames Research Center, Moffett Field, CA, United States, (2)New Jersey Institute of Technology, Department of Physics, Edison, NJ, United States, (3)New Jersey Institute of Technology, Physics, Newark, NJ, United States
Forecasting Space Weather Hazards for Astronauts in Deep Space (622778)
Petrus C Martens1, Soukaina Filali Boubrahimi2, Berkay Aydin2 and Rafal Angryk2, (1)Georgia State University, Physics and Astronomy, Atlanta, GA, United States, (2)Georgia State University, Computer Science, Atlanta, GA, United States
