Single station modelling and comparison with ionosonde foF2 over Karachi from 1983 to 2007
Autor: | Weimin Zhen, Ghulam Murtaza, Tong Xu, Muhammad Atiq, Mehak Abdul Jabbar, Farrukh Chishtie, Muhammmad Ayyaz Ameen, Muneeza Salman Ali |
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Rok vydání: | 2019 |
Předmět: |
Atmospheric Science
Daytime 010504 meteorology & atmospheric sciences Mean squared error Anomaly (natural sciences) Aerospace Engineering Flux Astronomy and Astrophysics Regression analysis Geodesy 01 natural sciences International Reference Ionosphere Standard deviation Geophysics Space and Planetary Science 0103 physical sciences General Earth and Planetary Sciences 010303 astronomy & astrophysics Ionosonde 0105 earth and related environmental sciences Mathematics |
Zdroj: | Advances in Space Research. 64:2104-2113 |
ISSN: | 0273-1177 |
Popis: | In this study, we develop a single station model (SSM) based upon derived solar radio flux (F10.7P) using ionosonde foF2 data over Karachi (24.95 ° N, 67.14 ° E) over a period of 1983–2007. The station is positioned at the northern Equatorial Ionization Anomaly (EIA) crest region. For the development of this SSM, six regression models are proposed which can be categorised as (i) sunspot number (R) against foF2, (ii) R and geomagnetic index (Ap) against foF2 and (iii) current and prior month indices against foF2. This is an initial study based on a large set of ground observations of foF2 over Karachi. A significant saturation between foF2 against R at daytime is observed in all the months for the entire dataset. Analysis shows that the local statistical models are better than International Reference Ionosphere (IRI-2016) which has least accuracy with higher Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) in comparison to the local models. The developed SSM is in good agreement with observations with lower RMSE and MAE values as compared to the mentioned local models. Based on this validation, our SSM is used to forecast and compare ionosonde foF2 over Sonmiani (25.19 ° N, 66.74 ° E) showing a standard deviation of 0.4956 MHz from the observed data supporting our error assessments for the year 2018 while IRI-2016 for the same shows standard deviation as 1.1088 MHz. On the basis of our results, it is proposed that IRI may make use of F10.7P for predicting foF2. |
Databáze: | OpenAIRE |
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