Models for magnetospheric mass density and average ion mass including radial dependence
Analytical models for magnetospheric mass density, ρm, and average ion mass, M, were created from a database of ρm and electron density, ne, values from six spacecraft missions by making use of the Eureqa nonlinear genetic regression algorithm. All values of ρm were determined from Alfvén frequencie...
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Frontiers Media S.A.
2022-12-01
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Online Access: | https://www.frontiersin.org/articles/10.3389/fspas.2022.1049684/full |
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author | Richard E. Denton Kazue Takahashi Kyungguk Min David P. Hartley Yukitoshi Nishimura Matthew C. Digman Matthew C. Digman |
author_facet | Richard E. Denton Kazue Takahashi Kyungguk Min David P. Hartley Yukitoshi Nishimura Matthew C. Digman Matthew C. Digman |
author_sort | Richard E. Denton |
collection | DOAJ |
description | Analytical models for magnetospheric mass density, ρm, and average ion mass, M, were created from a database of ρm and electron density, ne, values from six spacecraft missions by making use of the Eureqa nonlinear genetic regression algorithm. All values of ρm were determined from Alfvén frequencies, and the values of ne were determined from plasma wave or spacecraft potential data. Models of varying complexity are listed. The most complex models appearing in this paper are capable of modeling ρm within a factor of 1.81, and M within a factor of 1.34 if ne is used as an input parameter, or within a factor of 1.45 if ne is not used. The most important parameters for modeling ρm are L, the solar EUV index F10.7, magnetic local time, MLT, the geomagnetic activity index Kp, and the solar wind dynamic pressure, Pdyn. The very simplest model for M depends on Kp. In more complex models for M including ne, the most important parameters are ne with L, F10.7, and Pdyn or Kp. In more complex models for M not including ne, the most important parameters are Kp, MLT, F10.7, L, and the auroral electrojet index, AE. Explanations for most of the dependencies are given. We also demonstrate the danger of calculating spatial dependence without taking account of different conditions sampled in different regions. Here we avoid that problem by using multivariant models. |
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institution | Directory Open Access Journal |
issn | 2296-987X |
language | English |
last_indexed | 2024-04-13T04:59:11Z |
publishDate | 2022-12-01 |
publisher | Frontiers Media S.A. |
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series | Frontiers in Astronomy and Space Sciences |
spelling | doaj.art-b0b0c6335c20430f89bd518d9ce228da2022-12-22T03:01:23ZengFrontiers Media S.A.Frontiers in Astronomy and Space Sciences2296-987X2022-12-01910.3389/fspas.2022.10496841049684Models for magnetospheric mass density and average ion mass including radial dependenceRichard E. Denton0Kazue Takahashi1Kyungguk Min2David P. Hartley3Yukitoshi Nishimura4Matthew C. Digman5Matthew C. Digman6Department of Physics and Astronomy, Dartmouth College, Hanover, NH, United StatesApplied Physics Laboratory, Johns Hopkins University, Laurel, MD, United StatesDepartment of Astronomy and Space Science, Chungnam National University, Daejeon, South KoreaPhysics and Astronomy, University of Iowa, Iowa City, IA, United StatesCenter for Space Physics, Boston University, Boston, MA, United StatesDepartment of Physics and Astronomy, Dartmouth College, Hanover, NH, United StatesDepartment of Physics, Extreme Gravity Institute, Montana State University, Bozeman, MT, United StatesAnalytical models for magnetospheric mass density, ρm, and average ion mass, M, were created from a database of ρm and electron density, ne, values from six spacecraft missions by making use of the Eureqa nonlinear genetic regression algorithm. All values of ρm were determined from Alfvén frequencies, and the values of ne were determined from plasma wave or spacecraft potential data. Models of varying complexity are listed. The most complex models appearing in this paper are capable of modeling ρm within a factor of 1.81, and M within a factor of 1.34 if ne is used as an input parameter, or within a factor of 1.45 if ne is not used. The most important parameters for modeling ρm are L, the solar EUV index F10.7, magnetic local time, MLT, the geomagnetic activity index Kp, and the solar wind dynamic pressure, Pdyn. The very simplest model for M depends on Kp. In more complex models for M including ne, the most important parameters are ne with L, F10.7, and Pdyn or Kp. In more complex models for M not including ne, the most important parameters are Kp, MLT, F10.7, L, and the auroral electrojet index, AE. Explanations for most of the dependencies are given. We also demonstrate the danger of calculating spatial dependence without taking account of different conditions sampled in different regions. Here we avoid that problem by using multivariant models.https://www.frontiersin.org/articles/10.3389/fspas.2022.1049684/fullmagnetospheremass densityaverage ion massmodelsAlfvén wavesion composition |
spellingShingle | Richard E. Denton Kazue Takahashi Kyungguk Min David P. Hartley Yukitoshi Nishimura Matthew C. Digman Matthew C. Digman Models for magnetospheric mass density and average ion mass including radial dependence Frontiers in Astronomy and Space Sciences magnetosphere mass density average ion mass models Alfvén waves ion composition |
title | Models for magnetospheric mass density and average ion mass including radial dependence |
title_full | Models for magnetospheric mass density and average ion mass including radial dependence |
title_fullStr | Models for magnetospheric mass density and average ion mass including radial dependence |
title_full_unstemmed | Models for magnetospheric mass density and average ion mass including radial dependence |
title_short | Models for magnetospheric mass density and average ion mass including radial dependence |
title_sort | models for magnetospheric mass density and average ion mass including radial dependence |
topic | magnetosphere mass density average ion mass models Alfvén waves ion composition |
url | https://www.frontiersin.org/articles/10.3389/fspas.2022.1049684/full |
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