TY - JOUR JF - kntu-jgit JO - jgit VL - 9 IS - 4 PY - 2022 Y1 - 2022/3/01 TI - The Improvement of IRI2016 global maps by the integration of Swarm and GPS observations TT - بهبود نقشه‌های جهانی مدل تجربی IRI2016 با تلفیق مشاهدات GPS و Swarm N2 - This paper presents a model, the International Reference Model 2016 (IRI), in order to improve the vertical total electron content (VTEC) maps by combining Swarm observations with global positioning system (GPS) ones. The proposed model consists of two parts: the background model and the corrections. In this paper, the IRI2016 model was selected as the background model and the corrections were modeled by spherical harmonic expansion functions up to the degree and rank 15 in a Sun-fixed reference frame. In the combination of VTECs derived from Swarm and GPS, the systematic biases of Swarm satellites are considered as unknown constant parameters in each epoch of modeling. Besides, in order to take the different accuracy levels of observational groups into consideration, the Helmert variance component estimation method is used. To evaluate the proposed model, the two-dimensional combined global ionosphere maps (GIMs) are constructed on the 28th of September 2017 and the 3rd of January 2018 with 7 and 1 kp-indices values, respectively. The comparison of the combined GIM maps with the International GNSS Service (IGS) GIM maps, shows that the combined model is more compatible with IGS maps, and adding Swarm and GPS observations to the IRI2016 background model can significantly improve the IRI2016 model, especially in oceanic regions. The results show that the root mean square (RMS) and root mean square error (RMSE) maps are decreased about 19% to 45% and 43% to 67% for the day with high Kp-index and about 13% to 40% and 15% to 43% for the day with low kp-index, respectively. SP - 87 EP - 107 AU - Karimi, Sedigheh AU - Sharifi, Mohammad Ali AU - Farzaneh, Saeed AD - University of Tehran KW - Total electron content (TEC) KW - Swarm KW - GPS KW - IRI-2016 model KW - variance component estimation UR - http://jgit.kntu.ac.ir/article-1-863-en.html DO - 10.52547/jgit.9.4.87 ER -