Global UltraViolet Imager

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

<p>For the purpose of building a regional (bound 20\textendash60\textdegreeN in latitude and 110\textendash160\textdegreeE 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\textendash18 March 2015). Assimilations were run under the following data combinations (cases): (1) GPS-STEC\textquoterights only; (2) GPS-STEC\textquoterights and NmF2\textquoterights from five ionosondes; (3) only NmF2\textquoterights from five ionosondes; and (4) GPS-STEC\textquoterights and NmF2\textquoterights 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 (<em>F</em><sub>2</sub> 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.</p>
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Space Weather
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