CEDAR email: CEDAR 2024 Workshop Session: Auroral Science with Heterogeneous Datasets

[Leslie Lamarche]

We cordially invite participation in the “Auroral science and studies of coupled MIT dynamics using hybrid heterogeneous data, data assimilation, and data-driven models” session taking place at CEDAR 2024 on Friday, June 14 10:00-12:00 PT.

This workshop focuses on ionospheric responses in the auroral zone contributing to system-science characterizations of the coupled magnetosphere-ionosphere-thermosphere (MIT). The heterogeneous nature of this response requires the use of a variety of observations from diverse platforms. Recent and ongoing development of new tools for incorporating data from distributed multi-instrument, multi-platform heterogeneous sources is facilitating improved understanding of auroral dynamics, new science from combining observations in novel ways, and the inclusion of these derived datasets into state-of-the art models and data assimilation techniques. Machine learning studies are being conducted using available databases to explore relationships between ionospheric flows, field-aligned currents, and conductivity patterns. Physics-based and data-driven ionospheric modeling using data reconstructions of ionospheric energy inputs from multiple, distributed, and heterogeneous measurements, including simultaneous use of in situ and remote sensing techniques, has been used for system science related to non-ideal arcs and the dynamics that govern them as well as MIT coupling dynamics both across spatial and temporal scales and altitude regimes.

This workshop aims to gather interested members of the community together to share recent research and discuss results and future developments in a collaborative setting. It will be structured as a series of short (3-5 minute) presentations within a shared slide deck that highlight recent research with significant time at the end for moderated group discussion that will reflect on these contributions.
Main Topics:

  *   Heterogeneous data products and multi-instrument observations – What new data products and multi-instrument observation modalities are available?
  *   Scientific output from heterogeneous data – What new science results have come from considering multiple or combined datasets, including those from machine learning, numerical modeling, and traditional data analysis?
  *   Data infrastructure for heterogeneous data – What currently exists and what are the needs so these data products can be efficiently created, shared, and attributed to maximize scientific output and collaboration?

Anyone interested in showing a few slides should contact Leslie Lamarche (leslie.lamarche at sri.com<mailto:leslie.lamarche at sri.com>) so topics can be grouped and organized in advance, but all are welcome to participate in the open discussion!


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