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Automated Detection Algorithm for Mesoscale Heated Regions in TWINS Ion Temperature Maps.
A M Keesee1,2, R Katus3, J Tibbetts1
1Department of Physics and Astronomy University of New Hampshire Durham NH USA.
This study introduces an algorithm to identify ion temperature enhancements in Earth's magnetotail using energetic neutral atom imaging. The algorithm effectively detects events like dipolarizing flux bundles and substorm onsets, aiding space weather research.
Area of Science:
- Space Physics
- Magnetospheric Dynamics
- Plasma Physics
Background:
- Earth's magnetotail is crucial for magnetosphere dynamics, especially during geomagnetic activity.
- Energetic neutral atom (ENA) imaging offers global insights into ion dynamics within the magnetotail.
- Previous ENA observations revealed enhanced ion temperatures linked to magnetic reconnection and flow channels.
Purpose of the Study:
- To develop and validate an algorithm for identifying ion temperature enhancements in magnetotail ENA data.
- To correlate algorithm-identified events with known magnetospheric phenomena.
- To enable new scientific studies and model validation using ENA data.
Main Methods:
- Utilized data from NASA's Two Wide-angle Imaging Neutral-atom Spectrometers (TWINS) mission.
- Developed an algorithm to process ENA-derived equatorial ion temperature maps.
- Validated algorithm results against THEMIS dipolarizing flux bundle (DFB) data and SuperMAG substorm onset data.
Main Results:
- The algorithm successfully identifies intervals with ion temperature enhancements.
- Successful correlation was found between algorithm outputs and DFB events and substorm onsets when sufficient ENA data was available.
- Demonstrated the algorithm's applicability to simulation data for comparative studies and model validation.
Conclusions:
- The developed algorithm is a valuable tool for analyzing magnetotail ion dynamics from ENA observations.
- This method enhances our ability to study phenomena like magnetic reconnection and substorms.
- The algorithm facilitates comparative studies between observational data and simulations, advancing space weather research.
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