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<h1><span style="font-size:12.0pt">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.<o:p></o:p></span></h1>
<p>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.
<o:p></o:p></p>
<p>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.
<o:p></o:p></p>
<p class="MsoNormal"><span style="font-family:"Arial",sans-serif;color:black">Main Topics:</span><span style="font-size:12.0pt"><o:p></o:p></span></p>
<ul style="margin-top:0in" type="disc">
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<b><span style="font-family:"Arial",sans-serif">Heterogeneous data products and multi-instrument observations</span></b><span style="font-family:"Arial",sans-serif"> – What new data products and multi-instrument observation modalities are available?<o:p></o:p></span></li><li class="MsoNormal" style="color:black;mso-list:l0 level1 lfo1;vertical-align:baseline">
<b><span style="font-family:"Arial",sans-serif">Scientific output from heterogeneous data
</span></b><span style="font-family:"Arial",sans-serif">– What new science results have come from considering multiple or combined datasets, including those from machine learning, numerical modeling, and traditional data analysis?<o:p></o:p></span></li><li class="MsoNormal" style="color:black;mso-list:l0 level1 lfo1;vertical-align:baseline">
<b><span style="font-family:"Arial",sans-serif">Data infrastructure for heterogeneous data</span></b><span style="font-family:"Arial",sans-serif"> – 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?<o:p></o:p></span></li></ul>
<p>Anyone interested in showing a few slides should contact Leslie Lamarche (<a href="mailto:leslie.lamarche@sri.com">leslie.lamarche@sri.com</a>) so topics can be grouped and organized in advance, but all are welcome to participate in the open discussion!<o:p></o:p></p>
<p class="MsoNormal"><span style="font-size:12.0pt"><o:p> </o:p></span></p>
<p class="MsoNormal"><o:p> </o:p></p>
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