Geomanyetik fırtına zamanlarında İstanbul üzerindeki iyonosferik elektron yoğunluğunun istatistiksel olarak incelenmesi ve GPS haberleşmesi üzerine etkisi

As being the conducting layer of the atmosphere, ionosphere plays a very important role in the propagation of the radio waves in the atmosphere and thus, in the long-distance communication over the globe and with the satellites in space. Especially, with the advances in GPS satellite technology, the predictions of the variations in the electron density of ionosphere become critically important in many of the areas that these technologies are used ranging from the military and navigation applications to aircraft traffic control systems and extending to the cellphones which are one of the extremely essential part of our daily lives, to even target finding in golf playing. Needless to say, finding the loss during the earthquakes and other hazardous natural phenomena is one other very important application of GPS information. The variations in ionospheric electron density occur in response to the variations in the solar radiation which changes over the solar cycle with the solar activity, and in the magnetosphere with the magnetic storm and magnetospheric substorm activity as well as due to the propagation of the waves into the ionospheric levels from the lower regions of the atmosphere. Variations in one of these factors cause both temporal and spatial variations in electron density. While the neutral winds in the thermosphere move electrons from one place to another, thus causing latitudinal and longitudinal variations in the electron density, the more periodic variations, such as daily, seasonal, and annual, occur in response to the variations in solar radiation input of the atmosphere. On the other hand, solar and magnetospheric activities, which are described under the term of Space Weather, cause irregular and non-periodic variations and thus result in unpredictable variations in the electron density. Electrons in the ionosphere are produced as result of ionization of the neutral atoms of the atmosphere at heights from approximately 60 km to 1000 km. The energetic particles from the Sun and from the magnetosphere in addition to the daily solar radiation are the major source of the ionization in the Earth's atmosphere. Solar photons create ionization that peak around the noon when the energy of the photons is the strongest, producing daily variation of the electron density. The seasonal and annual variations are the other two predictable variations caused by the solar radiation amount reaching the ionosphere. During the solar storms, the energetic particles enter the atmosphere, give rise to magnetic storm and magnetospheric substorms, and causing northern and southern lights (auroae) over the high latitudes and other phenomena over the equatorial regions. Depending on the energy of the particles, these generate ionization as well. The effect of the magnetic and magnetospheric storms on the electron density have been studied quiet widely. The effects and the physical mechanisms that cause these effects were to found to vary with the latitude, i.e. equatorial versus high latitudes, time of the day (universal time, UT), and magnetic local time (MLT). The background variations when there are no magnetic storms or magnetospheric storms are called quiet day variations while the variations in the presence of magnetic storm or magnetospheric substorm are called active day variations. Studies show both positive and/or negative effects when the total electron density or total electron content of the ionosphere (TEC) is higher or lower than that occurring during the quiet days. In general, positive effects are seen towards noon and the negative effects are observed in the afternoon after 16:00 UT. The effects of the magnetospheric storms and substorms are still an active area of research and mostly concentrated on the equatorial and high latitudes. Studies on the mid-latitude electron density variations, especially during the magnetospheric activity, are very limited. Also, most of the results obtained are based on the case studies while a complete statistical study is not available. Ionospheric electron density is measured using ionosonde radars from the ground and satellites in space. The ionosondes are high frequency (HF) radars that send radio signal to the ionosphere and measures the electron density using the reflected signal. They are indeed the oldest methods to measure electron density and gives amount of electrons at a fixed location. Despite oldest, they still operate and widely available over the globe and thus makes the global variation of ionospheric studies possible. They are the techniques that measure the electron density from ground. Recently, with the GPS technology, it is possible to obtain TEC using signal delays which is another active research area. In the absence of ionosonde observations, these provide good estimation of ionospheric electron density. In addition, there are several ionospheric models, such as International Reference Ionosphere (IRI), that give predictions of ionospheric parameters including electron density and TEC. Recently other models that include ionosphere-magnetosphere coupling possible become available such as TIEGCM, CTIPe, etc. While IRI does not include the effects of magnetospheric activity, TIEGCM and CTIPe type coupled models are expected to give better agreements with the observations. In this thesis study, it is our purpose to investigate the ionospheric electron density variation during the magnetospheric disturbances over Istanbul using both ionosonde and available ionospheric models, namely IRI and TIEGCM and determine the effects of variations in TEC on GPS range and time delays. In addition to case studies, this study presents the statistical investigation of the substorm time ionospheric electron density. The main motivation for our work comes from the fact that mid-latitude variations of electron density are not investigated in our region. Recently, we established an ionosonde radar within ITU campus in October 2012 and provides electron density and TEC data since then. One of our goals in this study is to present the observations of ITU ionosonde in order to understand the variability of ionosphere over Istanbul during the magnetic activities and then determine the differences from the variations seen during the quiet days. The strength and the time of the differences is important for the predictions of the electron density over a region. The comparisons were made with the results from the ionospheric models to determine how much and when the models differ the most from the observations and thus bring out the points that need to be improved in the models to decrease the discrepancies. As practical side of our study, we study the effects of the magnetospheric substorms on the GPS range delay and time delay predictions. Also, we compare ionosonde TEC observations during one of the geomagnetic activity event, March 17, 2015, with those obtained from GPS signal delay data. If we highlight our study; the first work is magnetospheric activity time analysis which was done by using 3 years of ionosonde data from 2013 to 2015, determine the variations in electron density during the magnetospheric storms.First recognize the differences in case studies, then expand data set to cover the magnetospheric storms that occur during these 3 years. The parameters we used are the F2 layer critical frequency (foF2), height of the maximum electron density in F2 layer (hmF2) and TEC. This study addresses the variations during the substorms statistically. Secondly, model comparisons are represented and lastly estimation of time and range delay and the estimation of TEC using GPS signals are given. Chapter 1 introduces the ionosphere, its structure, and its effects on the radio propagation and information on the GPS and how it is used to obtain TEC. Chapter 2 presents some literature work on the ionospheric electron density variations and GPS comparisons. In Chapter 3, we present the results from ionosonde data during the magnetospheric activity. A case study was presented and followed by statistical results. In Chapter 4, comparisons with the results from IRI and TIE-GCM models were presented. Chapter 5 will give summary of conclusions and suggestions for a future work.