SM004
Data-Based Modeling and Uncertainty Quantification for Space Weather II Posters

Monday, 7 December 2020: 04:00-20:59
Poster
Primary Convener:  Bharat Kunduri, Virginia Polytechnic Institute and State University, Blacksburg, VA, United States
Conveners:  Mervyn P Freeman, British Antarctic Survey, Cambridge, United Kingdom and Steven Morley, Los Alamos National Laboratory, Los Alamos, NM, United States
Primary Liaison:  Bharat Kunduri, Virginia Tech, Blacksburg, VA, United States
Chairs:  Mervyn P Freeman, British Antarctic Survey, Cambridge, United Kingdom, Steven Morley, Los Alamos National Laboratory, Los Alamos, NM, United States and Bharat Kunduri, Virginia Tech, Blacksburg, VA, United States
OSPA Liaison:  Bharat Kunduri, Virginia Tech, Blacksburg, VA, United States
 
How the Madrigal Database Can Help with the Latest Scientific Requirements (681296)
William Rideout and Phillip Erickson, MIT Haystack Observatory, Westford, United States
 
Data-Driven HASDM Density Model using Machine Learning (685086)
Richard Licata1, Piyush Mehta1 and W Kent Tobiska2, (1)West Virginia University, Morgantown, WV, United States, (2)Space Environment Technologies, Pacific Palisades, CA, United States
 
SET HASDM Database available to the research community as the new density benchmark (716994)
Bruce R Bowman1, W Kent Tobiska1, Dave Bouwer2, Alfredo Cruz3, Marcin Pilinski4, Piyush Mehta5 and Richard Licata6, (1)Space Environment Technologies, Pacific Palisades, CA, United States, (2)Space Environment Technologies, Hawthorne, CA, United States, (3)Space Environment Technologies, Space Weather Division, Pacific Palisades, United States, (4)Atmospheric and Space Technology Research Associates LLC, Boulder, CO, United States, (5)University of Kansas, Overland Park, KS, United States, (6)West Virginia University, Morgantown, WV, United States
 
Evaluating Thermospheric Densities Derived from Orbital Drag Data (767328)
Valerie Bernstein, University of Colorado at Boulder, Boulder, CO, United States, Marcin Pilinski, Laboratory for Atmospheric and Space Physics, Boulder, CO, United States and Eric K Sutton, University of Colorado at Boulder, Space Weather Technology, Research, and Education Center, Boulder, CO, United States
 
Two decades of SuperDARN convection mapping: effects of an ever evolving network (690912)
Maria-Theresia Walach, Lancaster University, Department of Physics, Lancaster, United Kingdom, Adrian Grocott, Lancaster University, Physics Department, Lancaster, United Kingdom, Frances Allana Staples, University College London, London, United Kingdom and Evan G Thomas, Dartmouth College, Hanover, NH, United States
 
Deterministic and probabilistic forecasting of the >2 MeV flux at GEO using geomagnetic and solar wind parameters. (754830)
Colin Forsyth, University College London, Mullard Space Science Laboratory, London, United Kingdom, Clare Watt, Northumbria University, Newcastle-upon-Tyne, United Kingdom, Michaela Mooney, Mullard Space Science Laboratory, Dorking, RH5, United Kingdom, Jonathan Rae, Northumbria University, Newcastle, United Kingdom, Samuel Walton, UCL Mullard Space Science Laboratory, Dorking, United Kingdom and Richard B Horne, British Antarctic Survey, Cambridge, United Kingdom
 
Ensemble data assimilation techniques for electron phase space density in the radiation belts (758670)
Angelica Maria Maria Castillo Tibocha, Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, Potsdam, Germany, Jana de Wiljes, University of Potsdam, Institute of Mathematics, Potsdam, Germany, Yuri Shprits, GFZ German Research Centre for Geosciences, Potsdam, Germany and Nikita Aseev, University of California Los Angeles, Los Angeles, CA, United States
 
Evaluating Auroral Forecasts Against Satellite Observations (725075)
Michaela Mooney1,2, Michael S Marsh2, Colin Forsyth3, Michael Sharpe2, Teresa Hughes2, Jonathan Rae4, David Jackson2 and Suzy Bingham2, (1)Mullard Space Science Laboratory, Dorking, RH5, United Kingdom, (2)Met Office, Exeter, United Kingdom, (3)Mullard Space Science Lab., Dorking, United Kingdom, (4)Northumbria University, Newcastle, United Kingdom
 
Statistical Distribution of Magnetic Perturbations and Solar Wind Drivers Using SWARM Data and Machine Learning (711142)
Yining Shi, University of Michigan, Ann Arbor, CO, United States, Mark B. Moldwin, University of Michigan Ann Arbor, Department of Climate and Space Sciences and Engineering, Ann Arbor, MI, United States and Mateo Amprimo, University of Michigan, Ann Arbor, United States
 
Statistical quantification of the variation in return period, amplitude and duration of space within and between successive solar cycles. (669167)
Aisling Bergin, University of Warwick, Coventry, CV4, United Kingdom, Sandra C Chapman, University of Warwick, Centre for Fusion, Space and Astrophysics, Department of Physics, Coventry, CV4, United Kingdom, Nicholas W Watkins, University of Warwick, Centre for Fusion, Space and Astrophysics, Department of Physics, Coventry, United Kingdom and Nicholas Moloney, Imperial College London, Department of Physics, London, United Kingdom
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