P008-08
Solar wind proxy determination at Mars using an artificial neural network

Monday, 7 December 2020: 05:58
Virtual
Suranga Ruhunusiri, Department of Physics and Astronomy, University of Iowa, Iowa City, IA, United States, Jasper S Halekas, University of Iowa, Department of Physics and Astronomy, Iowa City, IA, United States, Jared R Espley, Goddard Space Flight Center, Greenbelt, MD, United States, Francis Gerard Eparvier, University of Colorado at Boulder, Boulder, CO, United States, David Brain, Laboratory for Atmospheric and Space Physics, University of Colorado Boulder, Boulder, CO, United States, Christian Xavier Mazelle, University Paul Sabatier Toulouse III, Toulouse Cedex 09, France, Yuki Harada, Kyoto University, Kyoto, Japan, Gina A DiBraccio, NASA Goddard Space Flight Center, Greenbelt, MD, United States, Yaxue Dong, University of Colorado at Boulder, Laboratory for Atmospheric and Space Physics, Boulder, CO, United States, Yingjuan Ma, University of California Los Angeles, Los Angeles, CA, United States, Edward Thiemann, Laboratory for Atmospheric and Space Physics, Boulder, CO, United States and David L Mitchell, Space Sciences Laboratory, University of California Berkeley, Berkeley, CA, United States
Recorded Presentation
Abstract:
We introduce a novel method to determine solar wind parameters or proxies upstream of Mars using spacecraft measurements of plasma parameters near Mars. Specifically, we develop an artificial neural network (ANN) that can simultaneously infer seven solar wind proxies: ion density, ion speed, ion temperature, and interplanetary magnetic field magnitude and its three vector components. We use spacecraft measurements of ion moments, magnetic field magnitude, magnetic field components in Mars’ magnetosheath, and the solar extreme ultraviolet flux as inputs to the ANN. The ANN was trained and tested using data from the Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft. The ANN is capable of determining solar wind ion density, ion speed, ion temperature, and the interplanetary magnetic field magnitude with high accuracies; for more than 80% of the instances, all these proxies, when compared with MAVEN spacecraft's in situ measurement of the solar wind parameters, have percentage differences of 50% or less. The ANN can infer magnetic field orientations with moderate accuracies; for more than 50% of the instances, magnetic field cone and clock angle proxies, when compared with these angle values derived from in situ measurements, have differences of 30o or less. Since Mars lacks a dedicated solar wind monitor, unlike at Earth, this technique is useful for obtaining solar wind parameters during times when a Mars orbiter does not traverse through the solar wind upstream of Mars. Knowledge of the solar wind proxies is essential for investigating how the solar wind influences plasma dynamics and atmospheric escape at Mars.
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