Ionospheric assimilation of radio occultation and ground-based GPS data using non-stationary background model error covariance

Lin, Chia Ying; Matsuo, Tomoko; Liu, J. Y.; Lin, Chien Hung; Tsai, Heng; Araujo-Pradere, E. A.

doi:10.5194/amt-8-171-2015

Cited by 57 publications

(53 citation statements)

References 31 publications

(30 reference statements)

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“…

normalΔ U_{∥_{h_{m}}} ((), t + normalΔ t) = a d j U_{∥_{h_{m}}} ((), t + normalΔ t) - U_{∥_{h_{m}}} ((), t + normalΔ t),

which is only available at h m F 2 , vertically along the magnetic field line using a stationary correction given by the following Gaussian function ( G ) as

G ((), l) = normalexp \frac{{((), l - h_{m} F_{2})}^{2}}{2 c^{2}} .

G is computed along the field line ( l ), and the center of G is located at h m F 2 . Since the major empirical orthonormal functions computed from density profiles of the International Reference Ionosphere model show that the width of the ionospheric main layer is about 200 km [ Lin et al ., ], c is given as 100 km. U ∥ is modified by

U_{∥_{h_{m}}}

mainly within the F 2 layer at the time step t + Δ t .…”

Section: Methodsmentioning

confidence: 99%

Field‐aligned neutral wind bias correction scheme for global ionospheric modeling at midlatitudes by assimilating FORMOSAT‐3/COSMIC h_mF₂ data under geomagnetically quiet conditions

et al. 2015

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This study demonstrates the usage of a data assimilation procedure, which ingests the FORMOSAT-3/COSMIC (F3/C) h m F 2 observations to correct the model wind biases to enhance the capability of the new global Ionosphere Plasmasphere Electrodynamics (IPE) model under geomagnetically quiet conditions. The IPE model is built upon the field line interhemispheric plasma model with a realistic geomagnetic field model and empirical model drivers. The h m F 2 observed by the F3/C radio occultation technique is utilized to adjust global thermospheric field-aligned neutral winds (i.e., a component of the thermospheric neutral wind parallel to the magnetic field) at midlatitudes according to a linear relationship between time differentials of the field-aligned wind and h m F 2 . The adjusted winds are further applied to drive the IPE model. The comparison of the modeled electron density with the observations of F3/C and ground-based GPS receivers at the 2012 March equinox suggests that the modeled electron density can be significantly improved in the midlatitude regions of the Southern Hemisphere, if the wind correction scheme is applied. Moreover, the F3/C observation, the IPE model, and the wind bias correction scheme are applied to study the 2012 Southern Hemisphere Midlatitude Summer Nighttime Anomaly (southern MSNA)/Weddell Sea Anomaly (WSA) event at December solstice for examining the role of the neutral winds in controlling the longitudinal variation of the southern MSNA/WSA behavior. With the help of the wind bias correction scheme, the IPE model better tracks the F3/C-observed eastward movement of the southern MSNA/WSA feature. The apparent eastward movement of the southern MSNA/WSA features in the local time coordinate is primarily caused by the longitudinal variation in the declination angle of the geomagnetic field that controls the field-aligned projection of both geographic meridional and zonal components of the neutral wind. Both the IPE simulations and the F3/C observations show the significant longitudinal variation in the speed of the eastward movement of the southern MSNA/WSA.

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“…

normalΔ U_{∥_{h_{m}}} ((), t + normalΔ t) = a d j U_{∥_{h_{m}}} ((), t + normalΔ t) - U_{∥_{h_{m}}} ((), t + normalΔ t),

which is only available at h m F 2 , vertically along the magnetic field line using a stationary correction given by the following Gaussian function ( G ) as

G ((), l) = normalexp \frac{{((), l - h_{m} F_{2})}^{2}}{2 c^{2}} .

U_{∥_{h_{m}}}

mainly within the F 2 layer at the time step t + Δ t .…”

Section: Methodsmentioning

confidence: 99%

Field‐aligned neutral wind bias correction scheme for global ionospheric modeling at midlatitudes by assimilating FORMOSAT‐3/COSMIC h_mF₂ data under geomagnetically quiet conditions

et al. 2015

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“…While the applications based upon GPS/GNSS require knowledge of TEC, dual‐frequency GPS receivers have transformed the scenario of ionospheric observations from a single station or sparse measurements to global and high‐resolution measurements [ Lin et al , ]. Beginning with a modest number of 60 GPS receivers, the International GNSS Service (IGS) [ Zumberge et al , ] has now become a prime organization managing almost 400 GPS receivers as of now (see http://www.igs.org).…”

Section: Introductionmentioning

confidence: 99%

Characteristics of low‐latitude TEC during solar cycles 23 and 24 using global ionospheric maps (GIMs) over Indian sector

Dashora

Suresh

2015

JGR Space Physics

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The characteristics of quiet time equatorial and low-latitude total electron content over the Indian sector using global ionospheric map (GIM) data (1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014) are obtained filtering out the solar flare and storm effects. The results are examined and interpreted in the context of large number of previous studies. The newly found features from this study are as follows. Marked difference in nature of equinoctial asymmetry is noted between solar cycles 23 and 24. Long absence of winter anomaly both during low and high solar activity (HSA) in LL (low-latitude) regions is found. Climatology of the diurnal cycle is provided in four categories using new criteria for demarcation of solar activity levels. Highest correlation (~77%) between GIM ionospheric electron content (IEC) and PI (solar EUV proxy index) is noted over equator in contrast to previous studies. The minimum positive contribution of PI in variation of IEC requires minimum of 2 years of data, and if more than 7-8 years of data are used, it saturates. Root-mean-square width of PI can be used to define the HSA. Strong QBO (quasi-biennial oscillations) in IEC is noted in tune with the one in PI over both LL locations but QBO remains surprisingly subdued over equator. The semiannual oscillations in GIM-IEC are found to be stronger at all locations during high solar activity and weaker between 2005 and 2011, whereas the annual oscillations are found to be substantially stronger only during HSA-23 and weakest over southern LL location throughout 17 years.

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“…Lin et al [2015] developed a location-dependent background correlation model by using sample statistics from an ensemble of model outputs, and they suggested that this model can yield considerably higher quality assimilation analysis than the Gaussian function correlation model. Lin et al [2015] developed a location-dependent background correlation model by using sample statistics from an ensemble of model outputs, and they suggested that this model can yield considerably higher quality assimilation analysis than the Gaussian function correlation model.…”

Section: Observation and Background Error Covariancementioning

confidence: 99%

Three‐dimensional ionospheric tomography reconstruction using the model function approach in Tikhonov regularization

et al. 2016

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Ionospheric tomography is based on the observed slant total electron content (sTEC) along different satellite‐receiver rays to reconstruct the three‐dimensional electron density distributions. Due to incomplete measurements provided by the satellite‐receiver geometry, it is a typical ill‐posed problem, and how to overcome the ill‐posedness is still a crucial content of research. In this paper, Tikhonov regularization method is used and the model function approach is applied to determine the optimal regularization parameter. This algorithm not only balances the weights between sTEC observations and background electron density field but also converges globally and rapidly. The background error covariance is given by multiplying background model variance and location‐dependent spatial correlation, and the correlation model is developed by using sample statistics from an ensemble of the International Reference Ionosphere 2012 (IRI2012) model outputs. The Global Navigation Satellite System (GNSS) observations in China are used to present the reconstruction results, and measurements from two ionosondes are used to make independent validations. Both the test cases using artificial sTEC observations and actual GNSS sTEC measurements show that the regularization method can effectively improve the background model outputs.

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Ionospheric assimilation of radio occultation and ground-based GPS data using non-stationary background model error covariance

Cited by 57 publications

References 31 publications

Field‐aligned neutral wind bias correction scheme for global ionospheric modeling at midlatitudes by assimilating FORMOSAT‐3/COSMIC h_mF₂ data under geomagnetically quiet conditions

Field‐aligned neutral wind bias correction scheme for global ionospheric modeling at midlatitudes by assimilating FORMOSAT‐3/COSMIC h_mF₂ data under geomagnetically quiet conditions

Characteristics of low‐latitude TEC during solar cycles 23 and 24 using global ionospheric maps (GIMs) over Indian sector

Three‐dimensional ionospheric tomography reconstruction using the model function approach in Tikhonov regularization

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Ionospheric assimilation of radio occultation and ground-based GPS data using non-stationary background model error covariance

Cited by 57 publications

References 31 publications

Field‐aligned neutral wind bias correction scheme for global ionospheric modeling at midlatitudes by assimilating FORMOSAT‐3/COSMIC hmF2 data under geomagnetically quiet conditions

Field‐aligned neutral wind bias correction scheme for global ionospheric modeling at midlatitudes by assimilating FORMOSAT‐3/COSMIC hmF2 data under geomagnetically quiet conditions

Characteristics of low‐latitude TEC during solar cycles 23 and 24 using global ionospheric maps (GIMs) over Indian sector

Three‐dimensional ionospheric tomography reconstruction using the model function approach in Tikhonov regularization

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Field‐aligned neutral wind bias correction scheme for global ionospheric modeling at midlatitudes by assimilating FORMOSAT‐3/COSMIC h_mF₂ data under geomagnetically quiet conditions

Field‐aligned neutral wind bias correction scheme for global ionospheric modeling at midlatitudes by assimilating FORMOSAT‐3/COSMIC h_mF₂ data under geomagnetically quiet conditions