Work Description
Title: Dissecting Earth's Magnetosphere: 3D Energy Transport in a Simulation of a Real Storm Event Open Access Deposited
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(2023). Dissecting Earth's Magnetosphere: 3D Energy Transport in a Simulation of a Real Storm Event [Data set], University of Michigan - Deep Blue Data. https://doi.org/10.7302/wveb-jk73
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Files (Count: 4; Size: 619 GB)
Thumbnailthumbnail-column | Title | Original Upload | Last Modified | File Size | Access | Actions |
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README.md | 2023-10-18 | 2023-10-18 | 10.8 KB | Open Access |
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package_structure.md | 2023-10-16 | 2023-10-16 | 4 KB | Open Access |
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tools_and_scripts.tar.gz | 2023-10-16 | 2023-10-16 | 279 MB | Open Access |
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DBD_Brenner_magnetosphere.zip | 2023-10-17 | 2023-10-17 | 619 GB | Open Access |
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Dataset Title: Data to Support "Dissecting Earth's Magnetosphere: 3D Energy Transport in a Simulation of a Real Storm Event"
Dataset Creators: A. Brenner
Dataset Contact: Austin Brenner aubr@umich.edu
Key Points:
- Simulation results are used to quantify the global energy dynamics of Earth's magneotsphere in terms of energy pathways.
- Externally during main phase most energy lost is from the closed region due to magnetopause erosion while most energy gained is through the lobe boundary.
- Internally, large amounts of energy is recirculated at the cusp from the closed to open field, then passed back to the closed region in the tail.
Abstract:We present new analysis methods of 3D MHD output data from the Space Weather Modeling Framework during a simulated storm event. Earth's magnetosphere is identified in the simulation domain and divided based on magnetic topology and the bounding magnetopause definition.
Volume energy contents and surface energy fluxes are analyzed for each subregion to track the energy transport in the system as the driving solar wind conditions change. Two energy pathways are revealed, one external and one internal.
The external pathway between the magnetosheath and magnetosphere has magnetic energy flux entering the lobes and escaping through the closed field region and is consistent with previous work and theory.
The internal pathway, which has never been studied in this manner, reveals magnetically dominated energy recirculating between open and closed field lines. The energy enters the lobes across the dayside magnetospheric cusps and escapes the lobes through the nightside plasmasheet boundary layer. This internal circulation directly controls the energy content in the lobes and the partitioning of the total energy between lobes and closed field line regions. Qualitative analysis of four-field junction neighborhoods indicate the internal circulation pathway is controlled via the reconnection X-line(s), and by extension, the IMF orientation. These results allow us to make clear and quantifiable arguments about the energy dynamics of Earth's magnetosphere, and the role of the lobes as an expandable reservoir that cannot retain energy for long periods of time but can grow and shrink in energy content due to mismatch between incoming and outgoing energy flux.
Methodology: The simulation output data was collected from the SWMF (https://github.com/MSTEM-QUDA/SWMF). Output data is included here and was processed using the python tools described in package_structure.md.
Contents:
- tools_and_scripts.tar.gz: contains python tools described in package_structure.md, and additional input and output files in jgr2023, which includes it's own README file
- DBD_Brenner_Magnetosphere.zip: contains binary tecplot .plt output files of 3D BATS-R-US output from the SWMF simulation. Details on how to install tecplot are below, and processing tools can be found in tools_and_scripts.tar.gz/global_energetics/.
Related Publication: A. Brenner, T. I. Pulkkinen, Q. Al Shidi, G. Toth, Dissecting Earth's Magnetosphere: 3D Energy Transport in a Simulation of a Real Storm Event. JGR Space Physics, 2023. DOI:10.22541/essoar.169111711
Use and Access: This data set is made available under a Creative Commons Public Domain liscense (CC0 1.0).
#This work was done using anaconda environment/package manager tool
https://www.anaconda.com
#The primary tool used for analysis is Tecplot, specifically
Tecplot360ex2020r1 it is a licsenced software, details can be found
at https://www.tecplot.com/products/tecplot-360/
#Once tecplot is installed and the licsence is obtained, in order to
run pytecplot you will need to follow the installation procedure, a
hardcopy of the installation procedure is included here but the most
recent should be available at https://www.tecplot.com/docs/pytecplot/install.html
Note that pytecplot itself is simply installed with pip and is listed
in the included packages below
#Not all packages listed here are neccessarily used and alternate
versions were not tested since this is for archival purposes only
#pip was used to install all python packages, for details on what
specific packages are used see the import statements in the python
scripts
packages in environment:
#
Name Version Build Channel
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alabaster 0.7.12 pypi_0 pypi
babel 2.9.1 pypi_0 pypi
backcall 0.2.0 pypi_0 pypi
basesystem-amzn2-aarch64 10.0 5
binutils_impl_linux-64 2.36.1 h193b22a_2 conda-forge
bzip2 1.0.8 hb9a14ef_8 intel
ca-certificates 2021.5.30 ha878542_0 conda-forge
certifi 2021.5.30 py38h578d9bd_0 conda-forge
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future 0.18.2 pypi_0 pypi
gcc 11.2.0 h702ea55_1 conda-forge
gcc_impl_linux-64 11.2.0 h82a94d6_9 conda-forge
glibc-amzn2-aarch64 2.26 5
glibc-common-amzn2-aarch64 2.26 5
glibc-minimal-langpack-amzn2-aarch64 2.26 5
h5py 3.4.0 pypi_0 pypi
imagesize 1.2.0 pypi_0 pypi
intelpython 2021.3.0 7 intel
ipython 7.28.0 pypi_0 pypi
jedi 0.18.0 pypi_0 pypi
jinja2 3.0.1 pypi_0 pypi
kernel-headers_linux-64 2.6.32 he073ed8_14 conda-forge
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latex 0.7.0 pypi_0 pypi
ld_impl_linux-64 2.36.1 hea4e1c9_2 conda-forge
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libgcc-devel_linux-64 11.2.0 h0952999_9 conda-forge
libgcc-ng 11.2.0 h1d223b6_9 conda-forge
libgomp 11.2.0 h1d223b6_9 conda-forge
libsanitizer 11.2.0 he4da1e4_9 conda-forge
libstdcxx-ng 11.2.0 he4da1e4_9 conda-forge
markupsafe 2.0.1 pypi_0 pypi
matplotlib 3.4.3 pypi_0 pypi
matplotlib-inline 0.1.3 pypi_0 pypi
matplotlib-label-lines 0.4.1 pypi_0 pypi
networkx 2.6.3 pypi_0 pypi
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pexpect 4.8.0 pypi_0 pypi
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pillow 8.3.2 pypi_0 pypi
pip 21.1.1 py38ha59826b_0 intel
progress 1.6 pypi_0 pypi
prompt-toolkit 3.0.20 pypi_0 pypi
protobuf 3.18.0 pypi_0 pypi
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pytecplot 1.4.0 pypi_0 pypi
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python_abi 3.8 2_cp38 conda-forge
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requests 2.26.0 pypi_0 pypi
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setuptools 52.0.0 py38h0d5a7d4_0 intel
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six 1.16.0 pypi_0 pypi
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sphinx 4.2.0 pypi_0 pypi
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sqlite 3.35.5 hb9a14ef_1 intel
sysroot_linux-64 2.12 he073ed8_14 conda-forge
system-release-amzn2-aarch64 2 5
tables 3.6.1 pypi_0 pypi
tcl 8.6.10 1 intel
tempdir 0.7.1 pypi_0 pypi
tex 1.8 pypi_0 pypi
tk 8.6.10 h8e2d9d6_3 intel
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tzdata-amzn2-aarch64 2020d 5
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xz 5.2.5 h74280d8_2 intel
zlib 1.2.11.1 h047b5d8_3 intel
zope-interface 5.4.0 pypi_0 pypi