Role of neutral wind in the performance of artificial neural‐network based TEC models at diverse longitudes in the low latitudes. Issue 3 (28th March 2015)

• Record Type: Journal Article
• Authors: Sur, D.; Ray, S.; Paul, A.
• Is Part Of: Journal of geophysical research. Volume 120:Issue 3(2015:Mar.)
• Page Start: 2316
• Page End: 2332
• Publication Date: 2015-03-28
• Subjects: equatorial ionosphere -- TEC models; Magnetospheric physics -- Periodicals; Space environment -- Periodicals; Cosmic physics -- Periodicals; Planets -- Atmospheres -- Periodicals; Heliosphere (Astrophysics) -- Periodicals; Geophysics -- Periodicals; 523.01
• DOI: 10.1002/2014JA020594
• Languages: English
• ISSNs: 2169-9380

Abstract

Abstract: The equatorial ionosphere is characterized by (i) large values of total electron content (TEC) and sharp latitudinal gradients of TEC, (ii) steep temporal variation of TEC, (iii) large diurnal variation of TEC, and (iv) postsunset secondary enhancement of TEC. These features cause major limitations in the accuracy of standard ionospheric TEC models in this region. Three artificial neural‐network (ANN) based models have been developed based on real‐time low‐latitude TEC data along 77°E, 88°E, and 121°E longitudes in the region between the magnetic equator and locations beyond the northern crest of equatorial ionization anomaly to predict the vertical TEC values. ANN models have shown more accurate predictions than other standard ionospheric TEC models like International Reference Ionosphere, Parameterized Ionospheric Model, and NeQuick. The effects of the neutral wind in the variation of TEC are significant and have been incorporated as inputs to these ANN models. The outputs with neutral wind incorporated shows better correspondence with measured TEC than the models without neutral wind inputs. The longitudinally separated models have been used to find any longitudinal differences in TEC along equatorial regions. The causes behind the longitudinal differences in TEC and its diurnal variations in these regions have been explained in terms of the geomagnetic declination and inclination angles along with the role of zonal wind. Key Points: Development of ANN‐based TEC models at different longitudes Improved performance of TEC models incorporating neutral wind Explanation of longitudinal variability of TEC using zonal wind