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Data Assimilation Retrieval of Electron Density Profiles From Ionosonde Virtual Height Data
Author(s) -
Forsythe Victoriya V.,
Azeem Irfan,
Blay Ryan,
Crowley Geoff,
Makarevich Roman A.,
Wu Wanli
Publication year - 2021
Publication title -
radio science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.371
H-Index - 84
eISSN - 1944-799X
pISSN - 0048-6604
DOI - 10.1029/2021rs007264
Subject(s) - ionosonde , data assimilation , covariance , inversion (geology) , remote sensing , geodesy , ionosphere , kalman filter , incoherent scatter , meteorology , electron density , algorithm , radar , computer science , geology , mathematics , geophysics , physics , electron , statistics , paleontology , telecommunications , quantum mechanics , structural basin
A new method is developed to retrieve electron density profiles from a raw virtual height ionosonde traces. A Kalman filter is used for the assimilative inversion scheme together with the newly developed data‐driven vertical covariance model. The detailed mathematical formalism for the derivation of the Jacobian that takes into account the effect of the magnetic field is presented. The incoherent scatter radar measurements from Arecibo observatory are employed as the known truth to simulate the virtual height data. The results show that the data assimilative inversion technique accurately retrieves the vertical structure of the ionospheric density at the bottom side of the profile and reconstructs the vertical and temporal small‐scale density variations. A comparison with the results obtained by the POLynomial ANalysis (POLAN) inversion algorithm is presented. The assimilative inversion systematically outperforms the accuracy of the POLAN algorithm, on average reducing the percent errors in the electron density by half. Additionally, the simultaneous data ingestion is compared to the sequential assimilation of the virtual height data.