Regional 3‐D ionospheric electron density specification on the basis of data assimilation of ground‐based GNSS and radio occultation data

Aa, Ercha; Liu, Siqing; Huang, Wengeng; Shi, Liqin; Gong, Jianhua; Chen, Yanhong; Shen, Hua; Li, Jianyong

doi:10.1002/2016sw001363

Cited by 52 publications

(42 citation statements)

References 62 publications

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“…The locations of the digisondes from GIRO network are shown with blue circles. The horizontal distance of 600 km is

\approx

5.4° of arc length, which is approximately twice smaller than minimal ionospheric correlation distance used in assimilation algorithms (Aa et al, ; Bust et al, ; Yue et al, ). One validation study of COSMIC EDPs with ionosonde data by Krankowski et al () used the distance of 1,500 km, focusing only on the European region, whereas another study by Shaikh et al () that validated their EDP inversion technique used very short distances of 1.5° and 3° of geographic longitude and latitude, respectively.…”

Section: Resultsmentioning

confidence: 93%

Validation of Ionospheric Electron Density Measurements Derived From Spire CubeSat Constellation

Forsythe

Duly²,

Hampton

et al. 2020

Radio Science

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Commercial Global Navigation Satellite System radio occultation ionospheric measurements collected by the Spire CubeSat constellation could significantly improve the determination of the global ionospheric state. However, the systematic validation work is needed before using the Spire data for scientific and assimilative purposes. In this work, the electron density profiles retrieved from Spire total electron content measurements using Abel inversion corrected by horizontal asymmetry are compared to digisonde measurements and Arecibo incoherent scatter radar data. Four events when the radio occultation measurements occurred close to three digisondes showed a strong agreement between these independent measurements. The comparison of F2 layer peak and height obtained from Spire data to digisonde measurements at 34 stations around the globe from Global Ionospheric Radio Observatory network also showed a strong agreement. Additionally, a good agreement was obtained in the comparison of Spire profiles with Arecibo electron density measurements. Spire Measurements and Inversion TechniqueAs of August 2019, the Spire constellation consists of 84 nanosatellites in LEO and around 20-30 satellites devoted to collecting RO measurements. When complete, Spire plans a full constellation of over 100 satellites simultaneously collecting RO measurements. Each satellite is equipped with a tiny, low power, Spire-built GNSS-RO receiver and an upward facing precise orbit determination antenna that produce dual-frequency observations, with 1-Hz raw observation frequency, allowing the derivation of ionospheric sTEC measurements. During the preprocessing of the raw phase observations, outliers are eliminated and cycle slips are

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“…The locations of the digisondes from GIRO network are shown with blue circles. The horizontal distance of 600 km is

\approx

Section: Resultsmentioning

confidence: 93%

Validation of Ionospheric Electron Density Measurements Derived From Spire CubeSat Constellation

Forsythe

Duly²,

Hampton

et al. 2020

Radio Science

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“…To date, different flavors of ionospheric data assimilation schemes have been developed and used in ionospheric studies and characterization. Examples of data assimilation schemes include Kalman filter (Lee et al, 2012;Lin et al, 2015;Scherliess et al, 2004Scherliess et al, , 2006Schunk et al, 2004;Thompson et al, 2006;Yue, Wan, Liu, Zheng, et al, 2007;Yue et al, 2011Yue et al, , 2012, optimal interpolation (Gerzen et al, 2015), a three-dimensional variational (3D-Var) (Aa et al, 2016;Bust et al, 2001Bust et al, , 2004Bust et al, , 2007Bust & Datta-Barua, 2014), and four-dimensional variational (4D-Var, Pi et al, 2003;Ssessanga et al, 2018;Wang et al, 2004). Some of the matured data assimilation schemes have been tested and analyzed to the extent of being included in operational services: Utah State University (USU) Global Assimilation of Ionospheric Measurements (USU-GAIM) algorithm, University of Southern California and Jet Propulsion Laboratory Global Assimilative Ionospheric Model (GAIM), and Applied Research Laboratories, University of Texas at Austin Ionospheric Data Assimilation Four-Dimensional (IDA4D) algorithm (e.g., Bust et al, 2004Bust et al, , 2007Bust & Datta-Barua, 2014;McNamara et al, 2011;Schunk et al, 2003Schunk et al, , 2016Thompson et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

Assimilation of Multiple Data Types to a Regional Ionosphere Model With a 3D‐Var Algorithm (IDA4D)

et al. 2019

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For the purpose of building a regional (bound 20–60°N in latitude and 110–160°E in longitude) ionospheric nowcast model, we investigated the performance of IDA4D (Ionospheric Data Assimilation Four‐Dimension) technique considering International Reference Ionosphere model as the background. The data utilized in assimilation were slant total electron content (STEC) from 27 ground GPS (Global Positioning System) receiver stations and NmF2 (ionospheric F2 peak density) from five ionosondes and COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate) Data Analysis Archive Center. The period analyzed covered both geomagnetic quiet and disturbed days (15–18 March 2015). Assimilations were run under the following data combinations (cases): (1) GPS‐STEC's only; (2) GPS‐STEC's and NmF2's from five ionosondes; (3) only NmF2's from five ionosondes; and (4) GPS‐STEC's and NmF2's from both five ionosondes and COSMIC. Results showed that under case 1 the root‐mean‐square error (RMSE) in STEC reduced by 44% over the background International Reference Ionosphere values and on averaged over all ionosonde stations in the analysis RMSE values of foF2 (F2 layer critical frequency) reduced by 21%. Furthermore, foF2 RMSE values under Case 2 were 36% smaller than those under Case 1. Under Case 4, IDA4D performance improved even further in areas not covered by GPS and ionosonde measurements. Therefore, IDA4D is a potential candidate for regional ionosphere modeling that exhibits improved performance with assimilation of different data types.

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“…The Jet Propulsion Laboratory and University of Southern California have cooperatively constructed another Global Assimilation Ionospheric Model (JPL/USC GAIM), which uses a traditional Kalman filter method to estimate the three-dimensional density state, and a four-dimensional variational approach (4DVAR) to estimate ionospheric drivers such as neutral winds and the equatorial E×B drift [Pi et al, 2003;Wang et al, 2004;Mandrake et al, 2005]. Some studies use sophisticated empirical models to define the a priori state in order to implement data assimilation, such as Ionospheric Data Assimilation Three-Dimensional (IDA3D) [Bust et al, 2004[Bust et al, , 2007, Electron Density Assimilative Model (EDAM) [Angling and Cannon, 2004;Angling and Khattatov , 2006], North American/United States TEC (NATEC/USTEC) [Fuller-Rowell et al, 2006], and China assimilation TEC Model (CNTEC) [Aa et al, 2015[Aa et al, , 2016. Moreover, there are extensive studies that described the development of ionospheric and thermospheric data assimilation models/procedures [e.g., Pi et al, 2009; D R A F T September 9, 2018, 10:…”

Section: Introductionmentioning

confidence: 99%

SHPTS: towards a new method for generating precise global ionospheric TEC map based on spherical harmonic and generalized trigonometric series functions

Yuan

Wang

et al. 2014

J Geod

179

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To take maximum advantage of the increasing Global Navigation Satellite Systems (GNSS) data to improve the accuracy and resolution of global ionospheric TEC map (GIM), an approach, named Spherical Harmonic plus generalized Trigonometric Series functions (SHPTS), is proposed by integrating the spherical harmonic and the generalized trigonometric series functions on global and local scales, respectively. The SHPTS-based GIM from January 1st, 2001 to December 31st, 2011 (about one solar cycle) is validated by the ionospheric TEC from raw global GPS data, the GIM released by the current Ionospheric Associate Analysis Center (IAAC), the TOPEX/Poseidon satellite and the DORIS. The present results show that the SHPTS-based GIM over the area where no real data are available has the same accuracy level (approximately 2–6 TECu) to that released by the current IAAC. However, the ionospheric TEC in the SHPTS-based GIM over the area covered by real data is more accurate (approximately 1.5 TECu) than that of the GIM (approximately 3.0 TECu) released by the current IAAC. The external accuracy of the SHPTS-based GIM validated by the TOPEX/Poseidon and DORIS is approximately 2.5–5.5 and 1.5–4.5 TECu, respectively. In particular, the SHPTS-based GIM is the best or almost the best ranked, along with those of JPL and UPC, when they are compared with TOPEX/Poseidon measurements, and the best (in addition to UPC) when they are validated with DORIS data. With the increase in the number of GNSS satellites and contributing stations, the performance of the SHPTS-based GIM can be further improved. The SHPTS-based GIM routinely calculated using global GPS, GLONASS and BDS data will be found at the website http://www.gipp.org.cn.Peer ReviewedPostprint (published version

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Regional 3‐D ionospheric electron density specification on the basis of data assimilation of ground‐based GNSS and radio occultation data

Cited by 52 publications

References 62 publications

Validation of Ionospheric Electron Density Measurements Derived From Spire CubeSat Constellation

Validation of Ionospheric Electron Density Measurements Derived From Spire CubeSat Constellation

Assimilation of Multiple Data Types to a Regional Ionosphere Model With a 3D‐Var Algorithm (IDA4D)

SHPTS: towards a new method for generating precise global ionospheric TEC map based on spherical harmonic and generalized trigonometric series functions

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