title: Long-term prediction of the Arctic ionospheric TEC based on time-varying periodograms.
abstract: Knowledge of the polar ionospheric total electron content (TEC) and its future variations is of scientific and engineering relevance. In this study, a new method is developed to predict Arctic mean TEC on the scale of a solar cycle using previous data covering 14 years. The Arctic TEC is derived from global positioning system measurements using the spherical cap harmonic analysis mapping method. The study indicates that the variability of the Arctic TEC results in highly time-varying periodograms, which are utilized for prediction in the proposed method. The TEC time series is divided into two components of periodic oscillations and the average TEC. The newly developed method of TEC prediction is based on an extrapolation method that requires no input of physical observations of the time interval of prediction, and it is performed in both temporally backward and forward directions by summing the extrapolation of the two components. The backward prediction indicates that the Arctic TEC variability includes a 9 years period for the study duration, in addition to the well-established periods. The long-term prediction has an uncertainty of 4.8-5.6 TECU for different period sets.
authors.affiliation: Department of remote sensing and photogrammetry, Finnish Geodetic Institute, Masala, Finland.
authors.forename: Jingbin
authors.initials: J
authors.lastname: Liu
authors.affiliation: Conrad Blucher Institute for surveying & science, Texas A & M University Corpus Christi, Corpus Christi, United States of America.
authors.forename: Ruizhi
authors.initials: R
authors.lastname: Chen
authors.affiliation: Chinese Antarctic center of surveying and mapping, Wuhan University, Wuhan, China.
authors.forename: Zemin
authors.initials: Z
authors.lastname: Wang
authors.affiliation: Chinese Antarctic center of surveying and mapping, Wuhan University, Wuhan, China.
authors.forename: Jiachun
authors.initials: J
authors.lastname: An
authors.affiliation: Department of remote sensing and photogrammetry, Finnish Geodetic Institute, Masala, Finland.
authors.forename: Juha
authors.initials: J
authors.lastname: Hyyppä
mesh_terms: D001110:Arctic Regions; D001272:Atmosphere / Q000737:chemistry*; D004583:Electrons; D004784:Environmental Monitoring; D040362:Geographic Information Systems; D007477:Ions / Q000032:analysis*; D008956:Models, Chemical; D010507:Periodicity
chemical_list: D007477:Ions