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Modeling The Ionospheric Prereversal Enhancement By Using Coupled Thermosphere‐ionosphere Data Assimilation

Chia-Hung Chen, Chien-Hung Lin, Wen Hua Chen, Tomoko Matsuo
Published 2017 · Geology

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We report that assimilating total electron content (TEC) into a coupled thermosphere-ionosphere model by using the ensemble Kalman filter results in improved specification and forecast of eastward pre-reversal enhancement (PRE) electric field (E-field). Through data assimilation, the ionospheric plasma density, thermospheric winds, temperature and compositions are adjusted simultaneously. The improvement of dusk-side PRE E-field calculation over the prior state is achieved primarily by intensification of eastward neutral wind. The improved E-field calculation promotes a stronger plasma fountain and deepens the equatorial trough. As a result, the horizontal gradients of Pedersen conductivity and eastward wind are increased due to greater zonal electron density gradient and smaller ion drag at dusk, respectively. Such modifications provide preferable conditions and obtain a strengthened PRE magnitude closer to the observation. The adjustment of PRE E-field is enabled through self-consistent thermosphere and ionosphere coupling processes captured in the model. This study suggests that the PRE E-field that is critical in driving the evening equatorial plasma instability could be better forecasted by assimilation of TECs in the 10 minutes cycling.
This paper references
First storm‐time plasma velocity estimates from high‐resolution ionospheric data assimilation
Seebany Datta-Barua (2013)
The F-layer dynamo
H. Rishbeth (1971)
Modeling investigation of the evening prereversal enhancement of the zonal electric field in the equatorial ionosphere
J. Eccles (1998)
Ionospheric Data Assimilation Three‐Dimensional (IDA3D): A global, multisensor, electron density specification algorithm
G. Bust (2004)
Development of a physics-based reduced state Kalman filter for the ionosphere
L. Scherliess (2004)
Construction of correlation functions in two and three dimensions
G. Gaspari (1999)
Simulation of the pre‐reversal enhancement in the low latitude vertical ion drifts
C. Fesen (2000)
Role of thermosphere‐ionosphere coupling in a global ionospheric specification
T. Matsuo (2011)
A model of the high-latitude ionospheric convection pattern
R. A. Heelis (1982)
Global 3‐D ionospheric electron density reanalysis based on multisource data assimilation
X. Yue (2012)
Ionospheric data assimilation and forecasting during storms
A. Chartier (2016)
Electrical coupling of the E- and F-regions and its effect on F-region drifts and winds
R. A. Heelis (1974)
An investigation into the influence of tidal forcing on F region equatorial vertical ion drift using a global ionosphere-thermosphere model with coupled electrodynamics
G. Millward (2001)
Estimation of E × B drift using a global assimilative ionospheric model: An observation system simulation experiment
X. Pi (2003)
High‐latitude ionospheric drivers and their effects on wind patterns in the thermosphere
L. Liuzzo (2013)
Assimilative Modeling of Ionospheric Disturbances with FORMOSAT-3/COSMIC and Ground-Based GPS Measurements
X. Pi (2009)
Ionospheric assimilation of radio occultation and ground-based GPS data using non-stationary background model error covariance
C. Lin (2014)
A thermosphere/ionosphere general circulation model with coupled electrodynamics
A. Richmond (1992)
The prereversal enhancement of the zonal electric field in the equatorial ionosphere
Donald T. Farley (1986)
Electrodynamics in the low and middle latitude ionosphere: a tutorial
R. Heelis (2004)
Electrodynamics of the equatorial evening ionosphere: 2. Conductivity influences on convection, current, and electrodynamic energy flow
A. Richmond (2015)
Electrodynamics of the equatorial evening ionosphere: 1. Importance of winds in different regions
A. Richmond (2015)
Radar and satellite global equatorial F-region vertical drift model
L. Scherliess (1999)
The Data Assimilation Research Testbed: A Community Facility
J. Anderson (2009)
Effects of inferring unobserved thermospheric and ionospheric state variables by using an Ensemble Kalman Filter on global ionospheric specification and forecasting
C. Hsu (2014)
On TIE‐GCM simulation of the evening equatorial plasma vortex
F. S. Rodrigues (2012)
Postsunset vortex in equatorial F‐region plasma drifts and implications for bottomside spread‐F
E. Kudeki (1999)
Assimilation of FORMOSAT-3/COSMIC electron density profiles into a coupled thermosphere/ionosphere model using ensemble Kalman filtering
I. T. Lee (2012)
Global Assimilation of Ionospheric Measurements (GAIM)
R. W. Schunk (2001)
Ionospheric data assimilation with thermosphere‐ionosphere‐electrodynamics general circulation model and GPS‐TEC during geomagnetic storm conditions
C. Chen (2016)
The role of zonal winds in the production of a pre‐reversal enhancement in the vertical ion drift in the low latitude ionosphere
R. A. Heelis (2012)

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