Physics‐based reconstruction of the 3‐D density distribution in the entire quiet time plasmasphere from measurements along a single pass of an orbiter

Котова, Г. А.; Веригин, М. И.; Безруких, В. В.

doi:10.1002/2015ja021281

Cited by 10 publications

(7 citation statements)

References 47 publications

(60 reference statements)

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“…The plasmapause is derived from the zero parallel force surface (Lemaire, 1989) in the dynamic kinetic model of the plasmasphere by Pierrard and Stegen (2008), which is based on a kinetic approach. Verigin et al (2012) and Kotova et al (2015) created a physics-based reconstruction of the density in Earth's plasmasphere, and the plasmapause was described as the last closed streamline but with a rather flexible shape. Verigin et al (2012) and Kotova et al (2015) created a physics-based reconstruction of the density in Earth's plasmasphere, and the plasmapause was described as the last closed streamline but with a rather flexible shape.…”

Section: Introductionmentioning

confidence: 99%

“…Pierrard et al () gave a detailed review of the physics‐based models of the plasmasphere a decade ago. Verigin et al () and Kotova et al () created a physics‐based reconstruction of the density in Earth's plasmasphere, and the plasmapause was described as the last closed streamline but with a rather flexible shape. These physics‐based models increased our physical understanding of the plasmasphere.…”

Section: Introductionmentioning

confidence: 99%

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Development of a 3‐D Plasmapause Model With a Back‐Propagation Neural Network

et al. 2019

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Several empirical models have been previously developed to study the characteristics of the global plasmasphere. A three-dimensional solar wind-driven global dynamic plasmapause model was developed in this study using a back-propagation neural network based on multisatellite measurements. Our database contains 37,859 plasmapause crossing events from 4 January 1995 to 31 December 2015 covering all 24 magnetic local times (MLTs) from −66 • to 79 • magnetic latitudes. This model is parameterized by solar wind speed V sw , interplanetary magnetic field B z , SYM-H, and AE indices with smooth MLTs and latitude dependence. As the first 3-D empirical model, this model corresponds to the true plasmapause structure and is useful for observing space weather and other applications especially for predicting the shape of the plasmapause by forecasting the input parameters. Moreover, the proposed model is not only highly sensitive to these parameters, but also to their changes over days, seasons, and years; this means that the diurnal, seasonal, and annual variations of the parameters can be captured by the model. Therefore, this model can provide a more accurate plasmapause position compared with previous models and can also be used as a basic reference to develop other models such as a global plasmaspheric density model. Key Points:• A new solar wind-driven 3-D dynamic plasmapause model based on multisatellites is constructed using a back-propagation neural network • This model can potentially be used to forecast the configuration of the plasmasphere • This model has higher precision than previous models

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Development of a 3‐D Plasmapause Model With a Back‐Propagation Neural Network

et al. 2019

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“…For a detailed review of the physics-based models of the plasmasphere, please refer to Pierrard et al [2009]. After the review of Pierrard et al [2009], a physicsbased reconstruction of the density in the plasmasphere was presented by Verigin et al [2012] and Kotova et al [2015], where the plasmapause was described as the last closed stream line but with rather flexible shape. model (GCPM) to characterize the core plasma density and composition in the inner magnetosphere.…”

Section: Introductionmentioning

confidence: 99%

“…[] and Kotova et al . [], where the plasmapause was described as the last closed stream line but with rather flexible shape.…”

Section: Introductionmentioning

confidence: 99%

A new solar wind‐driven global dynamic plasmapause model: 2. Model and validation

Zhang

Ruan

et al. 2017

JGR Space Physics

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A new solar wind‐driven global dynamic plasmapause (NSW‐GDP) model has been constructed based on the largest currently available database containing 49,119 plasmapause crossing locations and 3957 plasmapause profiles (corresponding to 48,899 plasmapause locations), from 18 satellites during 1977–2015 covering four solar cycles. This model is compiled by the Levenberg‐Marquardt method for nonlinear multiparameter fitting and parameterized by VSW, BZ, SYM‐H, and AE. Continuous and smooth magnetic local time dependence controlled mainly by the solar wind‐driven convection electric field ESW is also embedded in this model. Compared with previous empirical models based on our database, this new model improves the forecasting accuracy and capability for the global plasmapause. The diurnal, seasonal, and solar cycle variations of the plasmapause can be captured by the new model. The NSW‐GDP model can potentially be used to forecast the global plasmapause shape with upstream solar wind and interplanetary magnetic field parameters and corresponding predicted values of SYM‐H and AE and can also be used as input parameters for other inner magnetospheric coupling models, such as dynamic radiation belt and ring current models and even MHD models.

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“…Using the INTERBALL‐1 data, Kotova et al () found that the observed values of L PP correspond rather satisfactorily with “best fitted positions” of their 3‐D semiempirical model of the plasmapause. The latter 6‐parametric semiempirical model was already used in an earlier study by Kotova et al ().…”

Section: Experimental Datamentioning

confidence: 99%

Experimental Study of the Plasmasphere Boundary Layer Using MAGION 5 Data

et al. 2018

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The in situ cold plasma measurements onboard MAGION 5 were carried out with very good time resolution, and this permitted to analyze thin plasmasphere boundary layer (PBL) near the plasmapause. In this layer the plasma density N is decreasing exponentially with L: N~exp((LPP − L)/WB), where WB corresponds to the characteristic width of the PBL, the distance in L within which the density varies by a factor of e, and LPP is the position of the plasmapause. The density in the boundary layer is inversely proportional to the volume of the unit magnetic flux tube, whereas its width is proportional to the volume of magnetic flux tube. The characteristic width of the PBL linearly depends on the time elapsed since the most recent maximum value of KP. Empirical relation for the dependence of the PBL width on most recent maximum value of KP and on the lapse time between this maximum and the plasmapause observations is proposed.

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Physics‐based reconstruction of the 3‐D density distribution in the entire quiet time plasmasphere from measurements along a single pass of an orbiter

Cited by 10 publications

References 47 publications

Development of a 3‐D Plasmapause Model With a Back‐Propagation Neural Network

Development of a 3‐D Plasmapause Model With a Back‐Propagation Neural Network

A new solar wind‐driven global dynamic plasmapause model: 2. Model and validation

Experimental Study of the Plasmasphere Boundary Layer Using MAGION 5 Data

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