CEDAR email: COSPAR-22-C1.7: Information Theory and Machine Learning for Geospace Research

[Wing, Simon]

We would like to draw your attention and invite you to consider submitting an abstract to session C1.7 in Scientific Commission C to be held at the COSPAR 2022 - 44th General Assembly in Athens, July 16–24 2022.
 Abstract submission deadline Feb 11, 2022:
https://www.cosparathens2022.org/attending/registration-abstract-submission/<https://urldefense.proofpoint.com/v2/url?u=https-3A__www.cosparathens2022.org_attending_registration-2Dabstract-2Dsubmission_&d=DwMFaQ&c=XYzUhXBD2cD-CornpT4QE19xOJBbRy-TBPLK0X9U2o8&r=Ijg4y-a7p0a8QnkrC30AmAL_kDhaSHx_x97HBeACb6g&m=5NjfyIUk7cdp05AMhSfY0kqP4HkqBtwY7F3_tZWf8yA&s=1mW-9hXVCbIVoCbSwjOoAT6nXdTAuDDPNbklVuzAUGQ&e=>
 COSPAR-22-C1.7: Information Theory and Machine Learning for Geospace Research
Session details (https://www.cospar-assembly.org/admin/sessioninfo.php?session=1030):
Recent works point to a considerable importance of information theory and machine leaning in Space Physics and Space Weather. Information-theoretic measures have been used to shed light on the storm-substorm interaction and the solar wind drivers of the outer radiation belt through the general perspective of quantifying information transfer, including linear and nonlinear mechanisms. Machine learning techniques have been applied to the forecasting of geomagnetic indices, relativistic electrons at geosynchronous orbits, solar flares occurrence, coronal mass ejection propagation time, solar wind speed. We invite contributions of information theory for uncovering relevant yet complex processes interlinking different geospace subsystems, variables and spatio-temporal scales. We solicit contributions of machine learning for space weather forecasting and on open challenges for the community related to the combination of physics-based and machine learning approaches, known as gray box. Studies combining information theory and machine learning in geospace would be of particular interest.

Confirmed Solicited Speakers: Joe Borovsky (Space Science Institute, USA), Jakob Bortnik (UCLA, USA), Adnane Osmane (University of Helsinki, Finland), Jorge Amaya (KU Leuven, Belgium)
We look forward to receiving your contributions and thank you very much for your attention.
 Sincerely yours,
 The session conveners: Georgios Balasis (NOA, Greece), Simon Wing (JHUAPL, USA), Enrico Camporeale (NOAA, USA), Jay Johnson (Andrews University, USA), Giovanni Lapenta (KU Leuven, Belgium)


Simon Wing
240-228-8075
simon.wing at jhuapl.edu<mailto:simon.wing at jhuapl.edu>




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