Linear time series modelling of GPS-Derived TEC over the Andaman region | |
| Author | Sai Suraj Puram |
| Call Number | AIT Thesis no.RS-17-07 |
| Subject(s) | Geographic information system Linear |
| Note | A Thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Remote Sensing and Geographic Information Systems |
| Publisher | Asian Institute of Technology |
| Abstract | This research presents a linear time series model to represent the climatology of the Ionospheric activities and to investigate the characteristics of daily averaged VTEC by using linear time series decomposition model. The GPS-TEC observation data at the Bangalore International GNSS Service (IGS) station (geographic lat -13.02° N, long 77.57° E; geomagnetic latitude 4.4° N) has been utilized for processing of TEC data during an extended period (2009-2016) in the 24th solar cycle. Several factors were considered here such as Solar flux F10.7p index, geomagnetic Ap index, periodic oscillations were mainly considered here in this study for construction of linear time series model. The correlation coefficient (0.94) is found between the GPS-TEC observations and the modeled TEC values. Hence it shows that the model can clearly represent more definitive variation of the daily averaged TEC. The factors resembles that the TEC is mostly influenced by the solar activity which is the most pre-determinant of TEC. It reaches ~32 TECU in High Solar Activity (HSA) (2014) period and it is minimum value ~13 TECU in Low Solar Activity (LSA) (2009) period. The magnitudes of Semi-Annual variation is reflected high during solar maximum years. The Geomagnetic affect on TEC are relatively small, with the maximum of ~4.6 TECU (in March 2015). Further, the linear model is validated at different latitudes over the northern low latitude region during 2015period. The impact of different factors aforementioned on TEC at different latitudes shows apparent variations at varying latitudes. The accuracy of the model has been assessed by comparing the IRI-2016 and SPIM model TEC measurements. The performance of the SPIM model is marked to be overestimating the Observed TEC, modeled TEC and IRI-2016 model values. |
| Year | 2017 |
| Type | Thesis |
| School | School of Engineering and Technology |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Remote Sensing (RS) |
| Chairperson(s) | Tripathi, Nitin Kumar; |
| Examination Committee(s) | Raju, Durairaju Kumaran;Sarawut Ninsawut;Ratnam, Venkata; |
| Scholarship Donor(s) | Asian Institute of Technology Fellowship; |
| Degree | Thesis (M.Eng.) - Asian Institute of Technology Fellowship, 2017 |
| Contributor(s) | Asian Institute of Technology. Thesis; no. RS-17-07 |