International Journal of Geophysics
Volume 2019 (2019), Article ID 2792101, 11 pages
https://doi.org/10.1155/2019/2792101

Research Article

Critical Frequency foF2 Variations at Korhogo Station from 1992 to 2001 Prediction with IRI-2012

Karim Guibula,1,2 Jean Louis Zerbo,1,2 M’Bi Kaboré,1,2 and Frédéric Ouattara¹

¹Laboratoire de Recherche en Energétique et Météorologie de l’Espace (LAREME), Université Norbert Zongo, BP 376, Koudougou, Burkina Faso
²Laboratoire de Matériaux d’Héliophysique et Environnement (LAMHE), Université Nazi Boni, Bobo Dioulasso, 01 BP 1091 Bobo, Burkina Faso

Correspondence should be addressed to Jean Louis Zerbo; jeanlouis.zerbo@gmail.com

Received 16 March 2019; Revised 10 July 2019; Accepted 1 August 2019; Published 20 November 2019

Academic Editor: Filippos Vallianatos

Copyright © 2019 Karim Guibula et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

In this paper we report the foF2 data measured at Korhogo station (Lat. 9.3° N; Long. 354.6° E; dip. 0.6° S) compared to predictions with IRI-2012 subroutine URSI and CCIR for different solar cycle phases (minimum, ascending, maximum, descending) and different geomagnetic activity classes (quiet, fluctuating, recurrent, shock). According to our investigations, predictions with IRI are in agreement with the measured data during daytime and show significant differences between them at night-time and especially before sunrise. Except at solar minimum, the gap between predictions and measured data are more appreciable during recurrent and shock conditions compared to quiet and fluctuating conditions. Our results also show that only URSI model expresses the signature of EXB drift phenomenon at solar maximum phase during the recurrent days and at ascending phase for fluctuating activity.

1. Introduction

International Reference Ionosphere (IRI) is a project jointly created by the Committee on Space Research (COSPAR) and the Union of Radio Sciences International (URSI) in the late 1960s. The purpose of this project is to find an empirical model that can generate ionosphere characteristics whatever the geographical position of the experimenter. The IRI model through its several versions have generated many ionospheric parameters including the critical frequency of F2 layer (foF2) [1]. The IRI model has two subprograms namely URSI (Union of Radio Sciences International) and CCIR (Comité Consultatif International des Radio-communications). Many previous studies had made comparisons between ionosonde measured data and IRI model predictions. Some of them [2] compared the foF2 data from the Grahamstown station (geographic coordinates: Lat. 33.3° S, Long. 26.5° E) with the IRI-2001 prediction during geomagnetic storms and found that IRI-2001 predictions had good agreement with in situ data during geomagnetic storms most of the time, but improvement was still needed. For West African sector [3] IRI-2007 foF2 predictions were compared to data from Ouagadougou ionosonde (Lat: 12.4° N, Long: 358.5° E, Dip: 1.4° N) during quiet activity days. The results of this study revealed that during quiet activity, IRI-2007 predictions were better at solar minimum than at solar maximum. Moreover, during maximum and decreasing solar cycle phases, IRI-2007 did not express the signature of the E × B drift. The same study was carried out in [4] with IRI-2012 and TIEGCM (Thermosphere-Ionosphere-Electrodynamics General Circulation Model). The results showed that model predictions are closer to measured data for solar maximum than at solar minimum and that they were strongly related to periods before sunrise and after sunset. The present study compares foF2 values measured at Korhogo station to those obtained by IRI-2012 using its two subroutines (URSI and CCIR) for different geomagnetic activity classes and solar cycle phases. The purpose of this study is to assess IRI model forecasts during quiet and disturbed periods.

2. Data and Methods

2.1. Data

The ionospheric parameter used in this study is foF2 recorded at the Korhogo ionosonde station (9.3° N, 5.4° W, dip latitude: 0.7° S) from 1992 to 2002.

2.2. Criteria for Determining the Solar Cycle Phases

For the determination of solar phases, we have used the new sunspot number changes which are fully described in [5, 6] following criteria adopted by [7–10]: (1) minimum phase:  < 20; (2) ascending phase: and higher than that of the previous year; (3) maximum phase: (for small solar cycles with maximum sunspot number ( max) less than 100, the maximum phase is obtained by considering max); and (4) decreasing phase: and less than the previous year’s value. Rz is the sunspots number. Table 1 gives an overview of solar phases for the period 1992–2001.

Table 1: Distribution of years per solar phase.

Solar phases
Years

Decreasing
1992–1993–1994

Minimum
1995–1996

Increasing
1997–1998

Maximum
1999–2000–2001

2.3. Method for Determining Geomagnetic Activities Classes

To determine geomagnetic activity, we have used the criterion [11] fully described through pixel diagram [12–14]. The pixel diagram displays the daily averages of the geomagnetic index aa as a table. Each horizontal line contains 27 days corresponding to a 27-day Bartels solar rotation. The number in each square is the mean daily value of the aa index. Circles show the days when SSCs were observed. Figure 1 shows an example of pixel diagram used to identify days under the different geomagnetic activity classes. These criteria are: (1) quiet days are given by the days where (white and blue colors in Figure 1), (2) recurrent activity corresponds to the days where during several rotations of Bartel without a magnetic storm; (3) shock activity corresponds to the dates of SSCs with ; (4) fluctuating activity includes all days that do not belong to the other three classes.

Figure 1: Geomagnetic activities days shown in the pixel diagram of year 1983.

2.4. Data Analysis Method

The data analysis will be done through two ways: (1) a qualitative analysis based on a comparison between measured foF2 diurnal profiles and predictions from the IRI model. For that we use foF2 diurnal profiles defined by [15] in equatorial region. These profiles are: “Noon bite out” or “B” profile characterized by a double peak (morning and evening) parted by a trough around midday; “Morning Peak” or “M” profile defined by a single peak at morning; “Reversed” or “R” profile characterized by a single peak at evening; “Dome” or “D” profile characterized by a single maximum around noon; “plateau” or “P” profile characterized by an ionization plateau during daytime. This morphological analysis of the profiles will reveal the ability of the model to predict certain characteristics of the equatorial ionosphere (E × B drift and PRE effects). (2) A quantitative analysis based on a comparison between foF2 measured values and predictions from IRI. Appreciation will be made through the relative deviation of foF2 defined by:

where and are the foF2 IRI-2012 predicted values and Korhogo ionosonde measurement. is the relative deviation with the following appreciation:

 > 10% the model overestimates the measurements;

 < −10% the model underestimates the measurements;

−10% <  < 10% the model’s predictions are in agreement with the measurements.

3. Results

Table 2 gives the occurrence of geomagnetic activity classes per solar phase from 1992 to 2001. According to this table the number of quiet, fluctuating, shock and recurrent days are respectively 1780; 991; 92 and 80. From 1992 to 2001 Korhogo region (West Africa) is mostly under quiet activity. Days under recurrent activity are more important in decreasing phase while shock activity is more significant on solar maximum phase as reviewed by many previous works [11–17]. The studied period (1992–2001) is also characterized by a lack of recurrent activity during solar cycle ascending phase.

Table 2: Occurrence of geomagnetic activity classes per solar phase from 1992–2001.

Solar phases
Quiet
Fluctuating
Shock
Recurrent

Minimum
403
220
4
16

Ascending
486
167
17
0

Maximum
562
300
42
8

Descending
329
304
29
56

3.1. Qualitative Analysis

Figures 2 and 3 give foF2 time variations during quiet and fluctuating activities, respectively. Measured values trends show “B” profile with a predominance of evening peak during all the solar phases except at the maximum phase where the morning peak is more pronounced. However, morning and evening peaks are always well represented by URSI and CCIR predictions but the ionization trough around noon is reproduced only at the ascending phase during the fluctuating days. At solar maximum (Figures 2(c) and 3(c)) night-time peak is not represented by IRI-2012 predictions profile.

(a)

(b)

(c)

(d)

Figure 2: foF2 diurnal variations under quiet time for solar minimum (a), increasing phase (b), maximum solar (c), and decreasing phase (d). Full curves, dashed curves and broken lines are profiles of measured values, given by URSI and CCIR respectively.

(a)

(b)

(c)

(d)

Figure 3: foF2 diurnal variations under fluctuating activity for solar minimum (a), increasing phase (b), maximum solar (c), and decreasing phase (d). Full curves, dashed curves and broken lines are profiles of measured values, given by URSI and CCIR respectively.

Figure 4 is devoted to foF2 time variations during recurrent activity. At minimum solar phase (Figure 4(a)) measured data profiles exhibit a trough around 1100 LT. However this trough is not reproduced by IRI profile. At the maximum solar (Figure 4(c)), all foF2 profiles present “B” profile and at decreasing phase (Figure 4(d)) measured foF2 values exhibit “B” profile with a predominance of evening peak while foF2 predicted by URSI and CCIR present “R” profile. For measured foF2 profile there are night-time peaks around 2100 LT all the time. However, these peaks are only reproduced at maximum phase by CCIR model.

(a)

(b)

(c)

Figure 4: foF2 diurnal variations under recurrent activity for solar minimum (a), increasing phase (b), maximum solar (c), and decreasing phase (d). Full curves, dashed curves and broken lines are profiles of measured values, given by URSI and CCIR respectively.

Figure 5 presents the profile of foF2 during shock activity. At solar minimum phase (Figure 5(a)), measured foF2 profile has an irregular variation which is characterized by the presence of an ionization trough at 1000 LT when predictions with IRI-2012 subroutine URSI and CCIR present “R” profile. At the solar ascending phase (Figure 5(b)), measured values exhibit “B” profile with predominance of evening peak while URSI and CCIR predictions respectively present “B” and “P” profiles. At solar maximum phase (Figure 5(c)) all the profiles are “M” profile. During solar decreasing phase (Figure 5(d)) the measured data exhibit “P” profile; those given by URSI and CCIR show “R” profile.

(a)

(b)

(c)

(d)

Figure 5: foF2 diurnal variations under shock activity for solar minimum (a), increasing phase (b), maximum solar (c), and decreasing phase (d). Full curves, dashed curves and broken lines are profiles of measured values, given by URSI and CCIR respectively.

3.2. Quantitative Analysis

Figures 6 and 7 show ΔfoF2 profile for, respectively, quiet and fluctuating activities. From 0800 LT to 2000 LT, ΔfoF2 varies between −10% and 10% for all solar phases, which testifies that IRI-2012 predictions are in agreement with the measured data from Korhogo ionosonde station. This agreement is much more expressed with CCIR during all solar phases except at solar ascending phase (Figures 6(b) and 7(b)) for during fluctuating days. ΔfoF2 night-time profile shows that URSI overestimates measurements around 0600 LT during all solar phases. This profile is much more observed at solar minimum (Figures 6(a) and 7(a)) where Δursi reaches a maximum of 70% at 0600 LT. For quiet activity (Figure 6) CCIR model estimations are better than those of URSI most of the time. But this is not always the case during fluctuating activity days (Figure 7).

(a)

(b)

(c)

(d)

Figure 6: ΔfoF2 variations under quiet time for solar minimum (a), increasing phase (b), maximum solar (c), and decreasing phase (d). Full curves and dashed curves are the relative deviation of foF2 respectively with URSI and CCIR.

(a)

(b)

(c)

(d)

Figure 7: ΔfoF2 variations under fluctuating activity for solar minimum (a), increasing phase (b), maximum solar (c), and decreasing phase (d). Full curves and dashed curves are the relative deviation of foF2 respectively with URSI and CCIR.

Figure 8 shows ΔfoF2 evolution during shock activity. The different panels of this Figures (8(a)–8(d)) show that URSI model overestimates measurements between 0400 LT and 0800 LT for all the solar phases. This trend is more seen at minimum phase where Δursi reaches a peak of 90% at 0600 LT. At solar minimum both IRI programs overestimate measurements from 2200 LT to 0200 LT where ΔfoF2 exceed 100% around 0100 LT. Between 0800 LT and 1800 LT, ΔfoF2 profile shows that model predictions are in agreement with the measurements (ΔfoF2 between −10% and 10%) during all solar phases except at minimum and ascending phases where predictions underestimate data (ΔfoF2 ˂ −10%) around 1400 LT. Between 0200 LT and 0400 LT, one can also note a significant underestimation with URSI. During daytime, URSI model predictions are closer to in situ measurement than CCIR model for shock activity most of the time.

(a)

(b)

(c)

(d)

Figure 8: ΔfoF2 variations under shock activity for solar minimum (a), increasing phase (b), maximum solar (c), and decreasing phase (d). Full curves and dashed curves are the relative deviation of foF2 respectively with URSI and CCIR.

Figure 9 shows ΔfoF2 variations during recurrent activity. As a reminder, the period of the study is characterized by an absence of recurrent days at the ascending phase. At solar minimum (Figure 9(a)), CCIR model predictions are in agreement with the measurements (ΔfoF2 between -10% and 10%) but with URSI there is an overestimation around 0600 LT (ΔfoF2 reaches a maximum of 20%) and an underestimation around 0300 LT where ΔfoF2 reaches a minimum of (−20%). At solar maximum phase (Figure 9(b)), CCIR and URSI predictions agree with the measurements except around 0400 LT and 2100 LT where there is an underestimation (ΔfoF2 reaches a minimum of −30% at 0400 LT and −20% to 2100 LT). Similarly, URSI overestimates data around 0600 LT (ΔfoF2 reaching 30%). During decreasing phase (Figure 8(c)), model (CCIR and URSI) predictions are in agreement with the measurements except between 0400 and 0600 LT where IRI two programs underestimate data (ΔfoF2 reaches a minimum of −20% around 0300 LT) and between 0500 LT and 0800 LT where the URSI model overestimates measurements (Δursi reaches a peak of about 50%).

(a)

(b)

(c)

Figure 9: ΔfoF2 variations under recurrent activity for solar minimum (a), maximum solar (b), and decreasing phase (c). Full curves and dashed curves are the relative deviation of foF2 respectively with URSI and CCIR.

4. Discussion and Conclusion

May previous works argue that for equatorial regions foF2 diurnal profiles lead to the nature and intensity of electric currents in the E region [18–20]. Thus, it appears that the profile “D” expresses the absence of electrojet while the profiles “P” and “M” respectively show the presence of electrojet of medium and low intensity and the profile “B” indicates the presence of high intensity electrojet. The “R” profile characterizes the presence of counter electrojet [18]. Taking into account this assertion, we retain from previous results that: (1) during quiet and fluctuating activity days, the model still provides the presence of the counter electrojet and the average electrojet. Strong electrojet presence is only expected in the ascending phase during fluctuating days; (2) during recurrent activity: at solar maximum phase IRI two subroutines provide strong electrojet presence while at solar decreasing phase they provide counter electrojet presence; (3) during shock activity both programs indicate moderate electrojet presence at maximum phase.

From an electrodynamic point of view, it is well known that the ionization trough around midday in the equatorial region is the signature of the vertical drift E × B [21–23]. Therefore, the previous results show that: (1) during quiet and fluctuating activities days URSI model expresses the signature of E × B drift at ascending and descending solar phases, contrary to the CCIR model which does not show the effect of this drift. However, in the past, [3] had already shown that IRI-2007 does not express the signature of the E × B drift at the Ouagadougou station during the maximum and decreasing phases during quiet activity. Therefore, our results show that IRI-2012 better expresses the signature of the E×B drift compared to IRI-2007.

The night peaks are known to carry the signature of the pre-reversal of the zonal electric field (PRE) [21, 24]. From this assertion, we can say that only the URSI model expresses the signature of the PRE at solar maximum phase for disturbed activity.

Quantitative analysis indicates that during all periods of geomagnetic activity, the IRI model estimates are in agreement with the experimental values during the day but before sunrise the model estimates deviate more from the measured values. This gap is very important around 0600 TL including solar minimum. In general, CCIR predictions are better than those of the URSI model. Around 0600 LT, the foF2 values given by URSI program are better during shock activity than in quiet and fluctuating activity periods during all solar phases except minimum phase.

Data Availability

The sunspot data used to support the findings of our study are available at: http://www.sidc.be/silso/datafiles. The geomagnetic aa index data used to support the findings of this study are available at http://isgi.unistra.fr/data_download.php. The foF2 data used to support the findings of this study are available from the co-author Prof. Frédéric Ouattara (fojals@yahoo.fr) upon request.

Conflicts of Interest

The authors declare no conflicts of interest.

Acknowledgments

The authors thank Brest Telecom for providing Korhogo ionosonde data and ISGI data centre for providing the aa indices.

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