TitleAssimilation of Multiple Data Types to a Regional Ionosphere Model With a 3D‐Var Algorithm (IDA4D)
Publication TypeJournal Article
Year of Publication2019
AuthorsMengist, CKindie, Ssessanga, N, Jeong, S‐H, Kim, J‐H, Kim, YHa, Kwak, Y‐S
JournalSpace Weather
Date Published06/2019

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.

Short TitleSpace Weather

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