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Öğe İnvestigation of the effect of annual average temperature and precipitation changes on cors-tr stations: the case of kstm station(Konya Teknik Univ, 2024) Acar, Alparslan; Bülbül, Sercan; Başçiftçi, Fuat; Yıldırım, ÖmerIn this study, the effects of meteorological changes on the point positioning of CORS-TR stations were investigated. For this purpose, KURU, SINP, BOYT, CORU, CANK, CMLD, KRBK, KSTM stations were selected. The KSTM station was taken as unknown and adjusted based on other stations. Seasonal normal values of KSTM station in Kastamonu province covering the years 2016-2020 were examined in terms of temperature and precipitation amount. These values were determined according to the minimum, maximum and average value criteria by using T & uuml;rkiye State Meteorological Service data. For the calculations, IGS-standardized RINEX data of the stations for 5 years and 12 months between 2016 and 2020 and for 10 days on the 11th th and 20th th days of each month were used. All calculations were processed with Leica Geo Office v8.x. The calculated coordinates were compared with the current coordinates of CORS-TR at the same epoch and examined according to annual temperature and precipitation. In the analyzes, it was tested by statistical method whether all measurements were compatible. When it was examined whether the temperature changes were statistically significant, it was observed that the test values were calculated according to the temperature changes were below the test distribution limit at 95% confidence interval. When it was examined whether the precipitation changes were statistically significant, it was observed that the test values were calculated according to the precipitation changes were below the test distribution limit at 95% confidence interval.Öğe Association of the Mw 7.5, second Southeastern Turkey earthquake with the ionosphere across the TEC cross section(Springer Science and Business Media B.V., 2024) Eroğlu, Emre; Başçiftçi, FuatApproximately 9 h after the first Kahramanmaras earthquake, which hit on the night connecting February 5–6, earthquake institutes report a second earthquake with almost the same destructiveness. The name of this devastating event that shocks the ground with the break in the Eastern Anatolian Fault Line is Turkey’s second Southeastern earthquake. Mw 7.5, Ekinözü, Kahramanmaras earthquake hits at 10:24 UT on February 6, 2023, from a depth of 7.4 km. The second southeastern earthquake centered in Ekinözü, which caused intense loss of life in 10 provinces in the southeast of the country, is also felt in Syria, Iraq, Egypt, Lebanon, and Cyprus bordering Turkey, just like the first one. This discussion is dedicated to the folks who have suffered unbearable trauma. The discussion tries to detect the precursors of the earthquake through ionospheric TEC anomaly. The bounds of the anomaly are specified using some statistical instruments. The Fourier transformation governs the spectral analysis of the time-domain TEC atlas. Anomaly reading with the aid of the TEC atlas is based on the earthquake, space weather conditions, solar activity, and geomagnetic storm (coincided with the same time period). As a result of the analysis, the TEC anomaly is detected in the ionosphere on February 2 and 3 before the earthquake and on February 11, 15, 16, and 21 after the earthquake. The study likely detects precursors three days before the Ekinözü earthquake. © The Author(s), under exclusive licence to Springer Nature B.V. 2024.Öğe Mathematical modeling of the Southeastern Turkey earthquake (Pazarcık, Mw 7.8) using TEC data(Elsevier Ltd., 2024) Eroğlu, Emre; Başçiftçi, FuatSoutheastern Turkey perished by the Mw 7.8, Kahramanmaras earthquake on February 6, 2023, at 01:17 UT (04:17 LT). The Kahramanmaras-centered event, hit by the break of the East Anatolian Fault Line, is felt in Syria, Egypt, Lebanon, Iraq, and Cyprus on the border of Turkey. Together with Syria, it causes loss of lives and severe damage in 10 cities. This work is dedicated to the people of the region. The study discusses the causality of anomalies by conducting ionospheric anomaly research via the interpolated TEC map obtained from the CODE according to the coordinates of the epicenter of the earthquake (latitude, longitude). The TEC amplitudes are observed by evolving the time-domain TEC map into the frequency-domain with the Fourier transform. The peaks of the amplitudes allow preliminary information for the anomaly days. For the anomaly, the TEC (TECU) boundaries are drawn by the statistical specification. The TEC map outside these boundaries is marked as an anomaly. The causality of abnormalities is tried to be read through the triad of the geomagnetic storm(s), solar activity, and the earthquake effect. One can find seven anomaly days in the paper. January 30, February 2, 3, 11, 15, 16, and 21 are the anomaly days. The essay probably detects the anomaly before 3 days related to the Southeastern earthquake.Öğe Statistical analysis of the regional and global ionosphere model on intense geomagnetic storm(Springer, 2023) Başçiftçi, Fuat; Bülbül, S.This study evaluated an intense geomagnetic storm two days before, on the day of the magnetic storm (26 August 2018), and two days after, for a total of 5-daily global navigation satellite system (GNSS) measurements. The assessments were carried out for eight continuously operation reference stations-Turkey (CORS-TR) stations located in the province of Konya, Turkey. The change in the ionosphere layer caused by the geomagnetic storm was analyzed in terms of the total electron content (TEC) values. The analysis revealed that positive and negative anomalies had occurred on the day of the magnetic storm, the day before, and the day after. The statistic tests and correlation coefficient were calculated between regional and global ionosphere models. The global model that best fit the regional model was determined by comparing the regional values obtained from the GNSS measurements with the CODE, IRI-2016, and IRI-Plas. Besides, the geomagnetic storm, solar wind parameters (Bz, E, P, N, v), and geomagnetic activity indices (Dst, ap, Kp) were examined. As a result of the study, the global model that best fit the ionosphere model found using the regional TEC values was obtained using CODE TEC values. Moreover, the study demonstrated that magnetic storm-induced changes in the ionosphere could be detected using GNSS stations located in Turkey. Besides, the possible effects of the intense geomagnetic storm were propounded by the TEC anomalies.Öğe Using artificial neural networks in the investigation of four moderate geomagnetic storms (mGSs) that occurred in 2015(Elsevier Ltd, 2023) Başçiftçi, FuatThis essay aims to investigate the four moderate Geomagnetic Storms (mGSs) (storms of March 02, April 11, April 16, and May 13) that occurred in 2015. When examining GSs, Zonal Geomagnetic Indice (ZGi) values are predicted with an Artificial Neural Network model (ANNm). GSs are evaluated with the Solar Wind Parameters (SWp) (Bz, E, P, N, v, T) and the ZGi (Dst, ap, AE) obtained from the OMNI web. The study displays the ZGi estimations of 2015 with their errors, specifies the dual relationships of the variables with the covariance matrix, and exhibits the classified characteristics of the data with the Cluster Analysis. The physical principles govern the ANNm whose inputs are the SWp and outputs are the ZGi. For each event data; training, validation, and testing set ratio are regarded as 70%, 10%, and 20%, respectively. The backpropagation algorithm is determined as Scaled Conjugate Gradient (trainscg). The network performance is evaluated by the Correlation Constant (R) and Root Mean Square Error (RMSE) (nT) scales for each geomagnetic activity. Hereby, the study argues that the model is reliable, with an R-value of up to 89% and an RMSE value of down to 1.34 nT.Öğe Investigation of ionospheric TEC changes potentially related to Seferihisar-Izmir earthquake (30 October 2020, M-W 6.6)(Ist Nazionale Di Oceanografia E Di Geofisica, 2022) Başçiftçi, Fuat; Bülbül, S.It is important to be able to predict the occurrence time of an earthquake in order to take measures against its destructive effects. One of the parameters to be considered in earthquake prediction is ionospheric changes. Numerous studies have shown some changes in the ionosphere layer before or after the earthquake. These changes can be modelled to be detected with different methods and devices. One of the main parameters in examining these methods is the change of the Total Electron Content (TEC). With Global Navigation Satellite Systems (GNSS) observations, the TEC changes in the ionosphere can be determined before, during and after the earthquake. In this study, the changes in the ionosphere caused by the Seferihisar-Izmir earthquake (37.8881?? N 26.7770?? E, 30 October 2020, MW 6.6) were investigated in a 58-day time interval, including pre-earthquake, earthquake day, and post-earthquake. Firstly, the indices of solar activity (F10.7), Geomagnetic Activity (Dst), and Geomagnetic Storm (Kp) that can affect the ionosphere change pre-earthquake, earthquake day, and post-earthquake were examined. Then, the effects of the earthquake on the TEC changes in the ionosphere were investigated with the TEC values obtained from the regional ionospheric TEC (RIM-TEC), obtained from GNSS receivers in the earthquake zone and its surroundings, and global TEC maps (CODE). The indices showed that there were no geomagnetic activities between 29 September and 25 November 2020. In the study carried out, it was concluded that it is more accurate to calculate TEC values regionally rather than from Global TEC maps in the case of major episodic effects such as earthquakes. In addition, in the results about the TEC anomaly, it would seem that there was a maximum anomaly 8 days before the 304th day of 2020.Öğe Investigating and comparing the two superstorms in the 23rd solar cycle(Springer, 2022) Başçiftçi, FuatThe present study investigated two super geomagnetic storms (GSs) that occurred on November 20, 2003 (Dst = –422 nT), and November 08, 2004 (Dst = –374 nT). The investigation was conducted by the zonal geomagnetic indices (ZGi) and the solar wind parameters (SWp) (nT). The analysis of the two super geomagnetic activities based on the artificial neural network model (ANNm) consists of the correlation matrix, the hierarchical cluster appearance, and the ZGi estimation with their errors. In the light of physical principles, the ANNm utilizes SWp as inputs and ZGi as outputs. The comparative estimation conclusions with a high correlation rate and low absolute error are satisfied. The ANNm performance is evaluated using the correlation constant (R) and root mean square error (RMSE) (nT) measures for either GS. The study claims that the network model is reliable, with an R-value of up to 88% and an RMSE value of down to 4.78 nT. The paper may support the Sun–Earth investigations. © 2022, Indian Association for the Cultivation of Science.Öğe An analysis of the latest super geomagnetic storm of the 23RD Solar Cycle (May 15, 2005, Dst: –247 nT).(Maik Nauka/Interperiodica/Springer, 2021) Başçiftçi, FuatA geomagnetic storm is a major disturbance in the Earth's magnetosphere due to the solar wind entering the magnetosphere and ionosphere, lasting about 1-3 days. Storms are known by different categorical names such as weak, moderate, strong (intense), severe (very intense). This study aims to make a mathematical analysis of the latest super geomagnetic storm of the 23rd solar cycle (Dst: -247 nT) which occurred on May 15, 2005. The variables of the study are solar wind parameters (Bz, E, P, N, v, and T) and zonal geomagnetic indices (Dst, ap, and AE). The value range and deviations of variables were defined by the descriptive analysis and the binary relationships of the data were shown by the covariance matrix. A factor analysis was carried out with the help of normal distributions of data and the event (geomagnetic storm) was discussed with linear and nonlinear models. Finally, nonlinear model is also created with solar wind pressure (P), proton density (N), and the ap index. This model explains the storm with an accuracy of 87.5%. In general, this study aims to help the reader understand the storm by presenting models in which parameters and inscription coexist.Öğe TUSAGA-AKTİF İstasyonlarında gürültü analizi, Türkiye’ nin güneydoğusu örneği(2021) Başçiftçi, FuatUydularla Konum Belirleme Sistemi (GNSS, Global Navigation Satellite System) ile nokta konumlarının belirlenmesi sıklıkla kullanılan bir yöntemdir. GNSS ile nokta konumları belirlenirken hem GNSS ölçü hatalarına, hem de GNSS frekanslarını etkileyen gürültülere dikkat edilmesi gerekmektedir. GNSS ölçü hataları uygun ölçme yöntemi, kullanılan ekipmanla vb. giderilebilirken, GNSS sinyallerini etkileyen gürültüler ise analizler sonucu giderilmektedir. Bu çalışmada, Türkiye’nin güneydoğusunda bulunan TUSAGAAktif istasyonlarında gürültü bileşenlerinden arındırılmış hız bileşenleri belirlenmiş ve aralarında farklar yorumlanmıştır. Gerçekleştirilen çalışmada 2013-2019 yılları arasında her haftadan bir gün seçilerek 7 yıllık GNSS verisi Bernese v5.2 Bilimsel GNSS yazılımı ile değerlendirilmiş ve CATS yazılımı ile analiz edilerek hız bileşenleri verilmiştir. Yapılan karşılaştırmalar dikkate alındığında gürültüden arındırılmış ve arındırılmamış hızlar arasında mm altı bir yakınlık olduğundan dolayı aslında temel jeodezik ölçmelerde gürültüden arındırılmış hızların kullanımının pratikte kullanıcılara çok katkı sağlamayacağı ancak ölçü epoğu ile referans epoğu arasındaki farklar arttıkça hata miktarının da artacağından dolayı yüksek doğruluk gerektiren jeodezik çalışmalarda ise gürültüden arındırılmış hızların kullanılmasının hesaplanacak nokta konum ve doğruluğunu büyük oranda etkileyeceği sonucuna varılmıştır.
