Evaluating the rate of total electron content (TEC) production in ionosphere F2-layer to highlight winter anomaly by running thermosphere-Ionosphere- electrodynamics general circulation model

1 Institut de Recherche en Sciences Appliquées et Technologies (IRSAT), Centre National de la Recherche Scientifique et Technologique (CNRST), 03 BP 7047 Ouagadougou 03, Ouagadougou, Burkina Faso. 2 Centre Universitaire de Gaoua, Université Nazi BONI, 01 BP 1091 Bobo-Dioulasso 01, Burkina Faso. 3 Laboratoire de Recherche en Météorologie de l’Espace (LAREME), Université Norbert ZONGO, Koudougou, Burkina Faso. 4 UFR/ST, Université Nazi Boni, 01 BP 1091 Bobo-Dioulasso 01, Burkina Faso.


INTRODUCTION
Ionosphere layer is the part of atmosphere that reflects radio waves. It lies between 50 and 800 km in the upper atmosphere. Ionosphere behaves like an obstacle for radio waves propagation. The property of this layer is due to its concentration in particles, essentially N 2 , O 2 , and O (Rishbeth and Gariott, 1969). These molecules and atoms are the major constituents of ionosphere layer (Bauer and Jackson, 1962;Bauer et al., 1964;Van Zandt et al., 1960;Van Zandt and Knecht 1964). The ultraviolet rays and X-rays coming from the Sun hit these particles and cause their ionization. This phenomenon creates different ions like O + , NO + , O 2+ and e -. The concentration of the different particles gives to the ionosphere some characteristics like its capacity to reflect or transmit the waves. Although the ions density is important in the ionosphere, this layer stays neutral electrically, and moves like a plasma. To investigate ionosphere layer, many models have been developed (Roble et al., 1988;Bilitza et al., 2014;Qian et al., 2010;Jin and Park, 2007;Bittencourt and Chryssafidis, 1994). All of them aim to carry out ionosphere parameters. Some models are based on data recorded on different stations while others use both data and mathematical simulation. In the study, we use Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIEGCM) to carry out the Total Electron Content (TEC) in the F2-layer of the ionosphere. TIEGCM is a numerical model developed at High Altitude Observatory of National Center for Atmospheric Research (Richmond et al., 1992). The model uses input of 144 discrete values for longitudes and 72 values for latitudes. Running the model helps to get 90 output parameters that are obtained by a software program. Thermosphere General Circulation Model (TGCM) is the original version of TIEGCM. TGCM has been developed by Dickinson et al. (1981Dickinson et al. ( , 1984 and Roble et al. (1982), but gets a major development by coupling the ionosphere to the thermosphere (Roble et al., 1987(Roble et al., , 1988. This gives the Thermosphere-Ionosphere General Circulation Model (TIGCM). The implementation of self-consistent electrodynamics leads to the Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIEGCM) (Richmond et al., 1992;Richmond, 1995). In a previous study (Nanema et al., 2020), seasonal anomaly phenomenon has been highlighted by use of International Reference Ionosphere (IRI) model. The present study deals with electron bulk surface density in the ionosphere F2-layer. The objective of this study is to compare the rate of electrons production between summer (very intensive solar radiations period) and winter (less intensive solar radiations period) under low altitudes. It will help to highlight the winter anomaly phenomenon. The study takes place at Ouagadougou station, located in West Africa. Maximum phase is considered in this study.

METHODOLOGY
The methodology of the study is based on the following core assumptions and principles (Zerbo et al., 2011;Ouattara et al., 2012;Gnabahou and Ouattara, 2012): (i) a season is characterized by its characteristic month (March for spring, June for summer, September for autumn and December for winter); (ii) maximum phase solar cycle is determined by Rz > 100 (where Rz is the yearly average of Zürich sunspot number); (iii) quiet days is determined by its Aa ≤ 20 nT and the five quietest days of a month describe all the season; (iv) the located station in this study is Ouagadougou (latitude: 12,4°N, and longitude: 358,5°E). The nearest values for latitude and longitude to Ouagadougou geographic characteristics in TIEGCM table of data are 12°N and 0° respectively.
Using the principle (ii), the following Equation 1 gives the expression of the TEC: (2) Ouagadougou is located in West Africa, at longitude 358.5°E. Using the following approximation: 358.5° ~ 0°, Equation (2) becomes (3) as follows: The last approximation is possible because of the proximity of Ouagadougou station to the Zero Meridian. The model is run in these conditions. The evaluation of TEC parameter for the whole season is done by integrating the different TEC(h) values all daylong. TEC value is given by Equation 4 as follows: So, for the whole season, all the production of electrons due to the ionization in F2-layer is given by TEC calculated in Equation 4.

RESULTS AND DISCUSSION
Using the (ii) principle, the maximum phase of solar cycle 22 is 1990. In this year, by help of (iii) condition, the five quietest days are shown in Table 1. For each characteristic month, TEC(h) can be generated by use of Equation 2. Equation 4 shows the area defined by TEC(h) profile and x-axis. This area defines the total value of TEC for the whole season.
In Figure 1, two areas are represented on the graph. The major part of TEC value on summer is hidden by that on winter, except from 04.00 LT to 07.00 LT. Table 2 is obtained by using Equation 1. Figure 2 presents the comparison of TEC production between summer and winter at maximum solar phase,   1990 4, 10, 16, 17, 31 16, 17, 20, 21, 30 2, 3, 27, 29, 30 10, 11, 19, 21, 29 Figure 1. Total electron content variability at maximum solar phase. (a) From 00.00 LT to 03.00 LT and from 08.00 LT to 24.00 LT, TEC on winter hides TEC on summer. During this period, the rate of TEC production is around 35% superior in winter than in summer. (b) From 04.00 LT to 07.00 LT, TEC on winter is lower than TEC on summer. Winter anomaly is not shown during this period. The rate of TEC production is around 20% superior in summer than in winter.
(c) During all the year, the rate of TEC production is around 32% superior in winter than in summer.
Solar radiations are less intensive in winter than in summer. The rate of TEC production is higher in winter than in summer. This shows an anomaly in TEC production, according to the intensity of solar radiation. This is the winter anomaly phenomenon which is well reproduced by TIEGCM from 00.00 LT to 03.00 LT and from 08.00 LT to 24.00 LT. This phenomenon has previously been highlighted by other authors (Yonezawa and Arima, 1959;Shapley and Beynon, 1965;Rishbeth et al., 2000;Rishbeth and Muller-Wodarg, 2006). Solar radiation intensity cannot explain the apparition of winter anomaly. Other phenomena take place in atmosphere layer ionization. From 04.00 LT to 07.00 LT, TEC value in summer is higher than in winter. During this period, winter anomaly phenomenon does not appear.

Conclusion
This study is focused on the use of TIEGCM, a numerical model, to investigate ionosphere F2-layer by determining the total electron content parameter. A mathematical approach is used to evaluate the rate of seasonal TEC production at different seasons. This evaluation helps to highlight winter anomaly, a phenomenon that has been found already by different authors in previous studies. The rate of TEC production in winter is 32% higher than in summer. The study also shows that during a short period, the winter anomaly phenomenon is not observed. The result found in this study correlates with the other studies. This study also shows that solar radiations intensity is not the only cause of ionization in atmosphere layer; different phenomena can initiate it. In future studies, examination of these phenomena will be the target of our works.