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Article The Impact of Coronal Mass Ejections on the Seasonal Variation of the Ionospheric Critical Frequency f0F2

Hussein M. Farid 1 , Ramy Mawad 2,* , Essam Ghamry 3,4 and Akimasa Yoshikawa 4 1 , Space Science & Meteorology Department, Faculty of Science, Cairo University, Giza 12613, Egypt; [email protected] 2 Astronomy and Meteorology Department, Faculty of Science, Al-Azhar University, Nasr City, Cairo 11488, Egypt 3 National Research Institute of Astronomy and Geophysics, Helwan 11421, Cairo, Egypt; [email protected] 4 International Center for Space Science and Education, Kyushu University, Fukuoka 819-0395, Japan; [email protected] * Correspondence: [email protected]

 Received: 21 September 2020; Accepted: 26 October 2020; Published: 30 October 2020 

Abstract: We investigated the relations between the monthly average values of the critical frequency (f0F2) and the physical properties of the coronal mass ejections (CMEs), then we examined the seasonal variation of f0F2 values as an impact of the several CMEs properties. Given that, f0F2 were detected by PRJ18 (Puerto Rico) ionosonde station during the period 1996–2013. We found that the monthly average values of f0F2 are varying coherently with the number (SSN). A similar trend was found for f0F2 with the CMEs parameters such as the CME energy (linear correlation coefficient R = 0.73), width (R = 0.6) and the speed (R = 0.6). The arrived CMEs cause a injection into the , in turn, increasing the density, and consequently, f0F2 values. This happens in the high latitudes followed by the middle and lower latitudes. By examining the seasonal variation of f0F2, we found that the higher correlation between f0F2 and CMEs parameters occurs in the summer, then the equinoxes (spring and autumn), followed by the winter. However, the faster CMEs affect the ionosphere more efficiently in the spring more than in the summer, then the winter and the autumn .

Keywords: ; ionosphere; critical frequency of the F2 layer; solar activity; sunspot number

1. Introduction Several studies were interested in investigating the impact of solar activities upon the ionosphere [1–4]. Among those studies that are concerned with the response of the ionosphere critical frequency (f0F2) to the coronal mass ejections (CMEs) has become of the utmost importance during the past few years [5–7]. Actually, the solar activity is the main source of disturbances and fluctuations in the ’s environment, in particular the and the ionosphere layers. The variability of the ionosphere can be attributed to contributions from lower atmospheric internal waves, geomagnetic and solar activity variations from high as well [8]. In fact, solar ionizing flux varies not only with a longer time scale, the , but also with the shorter time scale, the quasi-27-day rotation of the and even on a day to day basis. Additionally, solar flux-induced variations in the neutral temperature, winds and neutral composition manifest also to ionospheric plasma densities and heights [4]. Indeed, during there is a little X-ray emission and a low number of CMEs, while at the Sun’s atmosphere emits large amounts of X-rays in addition to large numbers

Universe 2020, 6, 200; doi:10.3390/universe6110200 www.mdpi.com/journal/universe Universe 2020, 6, 200 2 of 11 of CMEs. This gives rise to a solar cycle variation in the intensity of ionization of the ionosphere. During solar storms, the ionospheric structure can be drastically modified by energy input from the Sun [9]. The ionosphere is separated into three layers D, E and F, in which the F layer is divided into two layers as well, F1 and F2. Moreover, the ionospheric electron density is highest around the F2 peak, and it has been the subject of many investigations. The widely used f0F2 is a well-defined parameter extracted from ionograms of ground-based ionosondes. Actually, f0F2 has a strong solar activity dependence, but varies with the seasons. This may be attributed to thermospheric winds, neutral winds, dynamo electric fields as well as the distance between the Sun and Earth, which varies seasonally [5]. Nowadays, a general picture was drawn for the ionospheric dynamo, in which, the equatorial electrojet is produced due to Eastward electric field E [10] which interacts with Earth’s magnetic field B causing strong vertical upward E B drift velocity and enhanced f F2 in low latitudes [11]. × 0 CMEs are thought to cause an increase of the electron density in large volumes of the Earth’s ionosphere [6]. In addition, CME events are usually the origin of intense geomagnetic storms and they occur predominantly during the solar maximum phase. That is why they are considered to be the origin of effects [12]. Basically, CMEs are huge explosions of plasma and magnetic fields from the sun’s corona. They eject billions of tons of coronal material having frozen in magnetic fields which are greater than the background solar magnetic field (IMF). Additionally, they are travelling outward from the sun at speeds ranging from 250 (km/s) to as fast as near 3000 km/s. Really, there were good efforts exerted by some researchers in the field such as authors of [6] who studied the direct influences of CMEs properties on f0F2 at mid-latitude ionospheric stations during the period 1996–2013 and found that the energetic, massive and fast CMEs can affect f0F2 more efficiently. Despite this, the authors of [4] found that both positive and negative deviations of f0F2 have no dependency on and location. Moreover, authors of [7] studied the relation between the monthly-averaged values of CME parameters and the monthly maximum values of f0F2 at high, middle, and low latitudes for solar cycles 23 and 24 and found that there is a moderately good correlation between the two time series graphs at high and middle latitudes, but the ionosphere correlation is not clear in lower latitudes, indicating that the impact of CMEs on f0F2 is higher at high latitudes than at the low latitudes. Besides, authors of [13] examined the effect of CMEs and solar winds on the seasonal variation of f0F2 at the Korhogo station during the period 1992–2002, through investigating the geomagnetic activity index Aa, where Aa 40 nT during one, two or three days announcing the CMEs arrival based ≥ on studies of [14–16]. They reported that CMEs affect midday troughs on f0F2 diurnal profiles and the night peaks in winter and spring. Nevertheless, in autumn, CMEs do not affect the nighttime peak on f0F2 diurnal profiles. In addition, CMEs always causes stronger positive storms compared to the effects, assuming that these storms are mainly due to the combination of the phenomena of rapid penetration eastward electric field and equatorward neutral winds during daytime but at night time they are mainly related to neutral winds alone. In the present work, we aim to examine the seasonal variation of f0F2 as a response to the CMEs influences for a long time period (1996 to 2013) at middle latitudes. Besides, we would examine and explain which value of both the monthly average and the monthly maximum f0F2 values which give better results concerning the response to the arriving CMEs. In the next section, we describe the data sources, while in Section3 we introduce the methodology. Section4 shows the results and discussions, and we give the conclusion in Section5.

2. Data Sources

The ionospheric f0F2 data were obtained from Interactive Data Resource (SPIDR). The data span between 1996 and 2013, consisting of minutely values of f0F2 with 5 min resolution. Table1 summarizes the details of the selected station. Universe 2020, 6, 200 3 of 11

Table 1. The details of the mid-latitude ionosonde station in the Northern hemisphere.

Code Name Latitude Longitude PRJ18 Puerto Rico 18.5 67.2 ◦ − ◦

CME data were taken from the SOHO LASCO CME Catalog obtained from a URL (http: //cdaw.gsfc.nasa.gov/CME_list/), we obtained 20635 CME events during the period 1996 to 2013.

3. Methodology Before introducing a description of the methodology, it is preferred to give a brief note about the detection and the extraction of the data concerning with the ionospheric critical frequency and the coronal mass ejection. The basic idea of the performance of the ionosonde depends on that the ionization in the atmosphere is in the form of several horizontal layers, and consequently, the electron concentration varies with height. By a range of frequencies, usually in the range of 0.1 to 30 MHz, and measuring the time it takes for each frequency to be reflected, it is possible to estimate the concentration and height of each layer of ionization. The frequency at which the wave penetrates the layer without reflection is that the transmitted wave that just exceeds the peak plasma frequency or the critical frequency. The critical frequency is directly proportional to the square root of electron number density of the layer. CMEs are massive plasma cloud associated with the magnetic field. We cannot observe the CME during its onset time of ejection because the solar disk is brighter than it. SOHO/LASCO masks the solar disk, causing an artificial . The CME can be shown as a cone beam that appear outside the occulting disk with a sky-plane angular width called “width” which is typically measured in the field of view (FOV) after the width becomes stable. The SOHO/LASCO catalog estimates the velocity, the mass and the energy corresponding to each CME which may eject in all directions around the sun. Coronal mass ejections are considered as large eruptions of plasma and magnetic fields which are produced from various sources of high intensity plasma emission. These are often associated with the acceleration of energetic . Energetic released by a CME can cause an increase in the number of free electrons in the ionosphere. The higher impact is in the high-latitude regions. The increase in free electrons enhances wave absorption. The higher impact is within the ionospheric D-region. It is leading to Polar Cap Absorption (PCA) events. CMEs may reach Earth within one to five or even seven days according to their speeds [17–22] such that their is so hard that no one can estimate their arriving time accurately and consequently their impact on the ionosphere. As a result, some scientists studied this impact by investigating some of certain events like [2,23,24]. On the other hand, others used the average values for the CMEs parameters and f0F2 for a long time period to achieve a global and deep view upon the expected link between the CMEs and the ionospheric f0F2 [6,7]. We have decided to use the same methodological invariants as that applied in [6] but with some modifications supporting our new goals in this study concerning the seasonal variation of f0F2. We estimated the monthly average values of the CMEs parameters and f0F2 to overcome the problem of the inaccurate estimation of the CME’s travel time. In addition, we divided each year of data-taking into four seasons according to the meteorological temperate seasons as shown in Table2. Universe 2020, 6, x FOR PEER REVIEW 4 of 11

Universe 2020, 6, 200 Table 2. The seasons according to meteorological temperate seasons. 4 of 11 The Seasons The Period NorthernTable Hemisphere 2. The seasons Southern according Hemisphere to meteorological temperate Start seasons. End Winter Summer 1 December 28 February Spring The Seasons Autumn 1 March The Period 31 May NorthernSummer Hemisphere SouthernWinter Hemisphere 1 Start June 31 August End AutumnWinter SummerSpring 1 1 September December 30 28 November February Spring Autumn 1 March 31 May 4. Results and DiscussionsSummer Winter 1 June 31 August Autumn Spring 1 September 30 November 4.1. Monthly Variation 4. Results and Discussion The monthly average value of f0F2, hereafter F, changes drastically, exhibiting frequent 4.1.oscillations, Monthly Variationwith time. In addition, we found that the monthly average value of f0F2 profile has a high coherence with that of the sunspot number (SSN) as shown in Figure 1, we found that its profile has the maximumThe monthly and average the minimum value of fmonthly0F2, hereafter averageF, changes values drastically, 11.3 MHz exhibitingand 3.4 MHz frequent at the oscillations, dates May with2000 time. and July In addition, 2007 respectively. we found that the monthly average value of f0F2 profile has a high coherence with that of the sunspot number (SSN) as shown in Figure1, we found that its profile has the Moreover, we examined the average and maximum monthly values of f0F2 during our selected maximum and the minimum monthly average values 11.3 MHz and 3.4 MHz at the dates May 2000 period. We found that the preferable matching with SSN profile is the monthly average values of f0F2 andas shown July 2007 clearly respectively. in Figure 1 as well.

Monthly maximum value of f F2 0 Monthly average value of f F2 0 25 250 12 250 (B) (A) 200 200 20 10 150 150 Number Sunspot Sunspot Number Sunspot 15 8 100 100

F2 (MHz) 50 0 F2 (MHz) 50 0 F 10

f 6

0 0

4 5 -50 -50

2 -100 0 -100 1996 2000 2004 2008 2012 2016 1996 2000 2004 2008 2012 2016 Year Year FigureFigure 1.1. TheThe timetime seriesseries ofof thethe monthlymonthly averageaverage ((AA)) andand thethe monthlymonthly maximummaximum (B(B)) valuesvalues ofof

ionosphericionospheric critical critical frequency frequencyf 0f0F2F2 (in(in MHz).MHz). TheThe twotwo plotsplots areare comparedcompared withwith the the monthly monthly average average sunspotsunspot number, number, SSN SSN showing showing a a good good agreement. agreement. The The blue blue color color of of the the left left axis axis values, values, smooth smooth curve curve

andand square square points points refer refer to tof 0fF20F2 values,values, whilewhile thethe redred color color of of the the right right axis axis values, values, smooth smooth curve curve and and roundround points points denote denote to to the the sunspot sunspot numbers. numbers.

Moreover, we examined the average and maximum monthly values of f F2 during our selected Using the monthly average f0F2 provides more accurate results than 0the monthly maximum, period.different We from found the that previous the preferable studies performed matching with by [6,7] SSN which profile focused is the monthly on using average the maximum values of valuef0F2 asof shownthe critical clearly frequency, in Figure that1 as is well. referring to the day-time variation in the ionosphere only. However, the averageUsing the values monthly more averagepreciselyf 0reflectF2 provides the total more variation accurate throughout results thanthe day, the the monthly day and maximum, the night, diwhichfferent implies, from the to a previous great extent, studies that performed the total incoming by [6,7] whichforces focusedby the solar on using particles the which maximum may valueenhance of theat the critical night frequency, in the absence that isof referring the solar to ra thediation. day-time Therefore, variation we have in the decided ionosphere to use only. the However, the average values more precisely reflect the total variation throughout the day, the day and monthly average f0F2 values in the present study in order to yield the improved outcomes. the night,CMEs which represent implies, an toimportant a great extent, portion that of theenergetic total incoming particles forcesand massive by the solarplasma particles coming which from maythe Sun. enhance Because at the ofnight this, we in theplotted absence the monthly of the solar aver .age values Therefore, of the CMEs we have widths decided with F to values use the as monthlyshown in average Figure f02.F2 This values figure in theshows present clearly study that in the order CME to yieldangular the width improved is varying outcomes. with the solar CMEs represent an important portion of energetic particles and massive plasma coming from the activity as well as f0F2. The widths become smaller during the quiet Sun phase, while they are greater Sun.during Because the active of this, Sun wephase. plotted At the the same monthly time, average F values values become of smaller the CMEs during widths the quiet with Fphase values of the as shownSun and in higher Figure 2through. This figure the active shows phase clearly of the that Sun. the CME angular width is varying with the solar f activity as well as 0F2. The widths become smaller during the quiet Sun phase, while they are greater Universe 2020, 6, x FOR PEER REVIEW 5 of 11

Actually, F values are linearly proportional to the monthly average values of the CME widths, providing the correlation coefficient R equals 0.6 (Pearson’s chi-squared test χ2 equals 244.01) Universeaccording2020, 6 ,to 200 the following equation: 5 of 11 F (MHz) = 4.1647 + 0.051 × W (degree) (1) during the active Sun phase. At the same time, F values become smaller during the quiet phase of the Where F is the monthly average value of f0F2 (in MHz), and W is the monthly average value of Sunthe and CME higher angular through width the (in active degrees). phase of the Sun.

120 250 12 (A) (B) 100 200 10

80 150 Number Sunspot 8

60 100 F2 (MHz) 0

f 6 40 50 CME Width CME (Degree) Width

4 20 0

0 -50 2 1995 2000 2005 2010 2015 2020 0 20406080100120 Year CME Width (Degree) FigureFigure 2. The2. The time time series series of of the the monthly monthlyaverage average valuesvalues of the coronal coronal mass mass ejections ejections (CMEs) (CMEs) angular angular widthswidths (in (in degrees) degrees) and and that that of of the the sunspot sunspotnumber number (SSN)(SSN) ( A),), and and the the relationship relationship between between monthly monthly averageaverage value value of off0 F2f0F2 values values and and the the monthly monthly averageaverage CMEs widths ( (BB).). The The blue blue color color of of the the left left axis axis values,values, smooth smooth curve curve and and square square points points of of plot plot (A ()A refer) refer to to the the CME’s CME’s width, width, while while the the red red color color of of the rightthe axis right values, axis values, smooth smooth curve, curve, and roundand roun pointsd points denote denote to the to sunspotthe sunspot numbers. numbers.

Actually,AccordingF values to Figure are linearly2, f0F2 and proportional CME width to theprofiles monthly match average with the values solar of cycle the CME23 and widths, the providingascending the period correlation of the coe solarfficient cycle R 24. equals This 0.6 trend (Pearson’s emphasizes chi-squared that the test f0F2χ 2profiles equals rely, 244.01) for accordinga great to theextent, following on the solar equation: activity, which is in a good agreement with several works such as [3,5,25] and in particular the CMEs, as presentedF (MHz) by [6,7,13].= 4.1647 One+ 0.051step further,W (degree) Figures 1 and 2 imply with no doubt (1) that the less wide CMEs predominantly reach the Earth ×and can affect the ionosphere, such that the wheremajorityF is theof CMEs, monthly having average angular value widths of f0F2 less (in than MHz), 120 and degrees,W is theseem monthly to have averagea similar value f0F2 time of the CMEprofiles. angular However, width (inthe degrees). wider CMEs have the ability to cause a plasma injection into the ionosphere thanAccording the thinner to ones, Figure in2 turn,, f0F2 incr andeasing CME the widthelectron profiles density, match or f0F2. with Obviously, the solar this cycle happens 23 andin the the ascendinghigh latitudes period followed of the solar by th cyclee middle 24. and This lower trend latitudes. emphasizes that the f0F2 profiles rely, for a great extent,Although on the solar the activity,time profile which of the is in monthly a good aver agreementage values with of severalthe CME works parameters such as expresses [3,5,25] anda in particularhigh coherence the CMEs,with SSN, as presentedincluding the by [CME6,7,13 energy]. One, we step found further, that Figuresthe correlation1 and2 ofimply the monthly with no doubtmaximum that the value less wideof the CMEsCME energy predominantly with the monthly reach the average Earth and value can of afff0F2ect gives the ionosphere,better results, such as an that exception, than using the monthly average CME energy. the majority of CMEs, having angular widths less than 120 degrees, seem to have a similar f0F2 time profiles.AmongHowever, the CME the wider parameters,CMEs havethe CME the energy ability seems to cause to abe plasma the main injection factor that into directly the ionosphere affects the ionosphere through ion production and consequently the critical frequency. Hence, the monthly than the thinner ones, in turn, increasing the electron density, or f0F2. Obviously, this happens in the maximum CME energy values give better results instead of the average ones, which indicates that high latitudes followed by the middle and lower latitudes. the solar particles have a direct effect on the ionosphere. Although the time profile of the monthly average values of the CME parameters expresses a Really, the maximum value of f0F2, which is measured through the day only, expresses its high coherence with SSN, including the CME energy, we found that the correlation of the monthly response to both solar ionizing by radiation, in addition to other factors relating to the lower maximum value of the CME energy with the monthly average value of f0F2 gives better results, as an atmosphere. However, the average value of f0F2, which is measured throughout the day and the night exception,represents than its usingresponse the monthlymainly to average the solar CME plas energy.ma, in addition to other factors from the lower atmosphere.Among the CME parameters, the CME energy seems to be the main factor that directly affects the ionosphereAs a consequence, through ion and production in order to andinvestigate consequently the CMEs the energy critical influences frequency. upon Hence, f0F2, we the plotted monthly maximumthe relation CME between energy the values monthly give bettermaximum results CME instead energy of theand average the monthly ones, average which indicates f0F2 as shown that the solarFigure particles 3, which have displays a direct obviously effect on a the linearly ionosphere. direct correlation based on the following equation: Really, the maximum value of f0F2, which is measured through the day only, expresses its response to both solar ionizing by radiation, in addition to other factors relating to the lower atmosphere. However, the average value of f0F2, which is measured throughout the day and the night represents its response mainly to the solar plasma, in addition to other factors from the lower atmosphere. Universe 2020, 6, 200 6 of 11

As a consequence, and in order to investigate the CMEs energy influences upon f0F2, we plotted the relation between the monthly maximum CME energy and the monthly average f0F2 as shown

FigureUniverse3 ,2020 which, 6, x displaysFOR PEER obviouslyREVIEW a linearly direct correlation based on the following equation: 6 of 11

4 F (MHz) = 4.1127 + 4.1 10− E (erg) (2) F (MHz) = 4.1127 + 4.1×10× −4 ×× E (erg) (2) where E is the monthly average value of CME energy (erg). The correlation coefficient R equals 0.73 where E is the monthly average value of CME energy (erg). The correlation coefficient R equals 0.73 (Pearson’s chi-squared test χ2 equals 178.85). This high value indicates that the CME energy strongly (Pearson’s chi-squared test χ2 equals 178.85). This high value indicates that the CME energy strongly aaffectsffects the the ionospheric ionospheric critical critical frequency. frequency.

3000 250 12 (A) (B) 2500 200 10

2000 150 Sunspot Number

8

1500 100 F2 (MHz) F2 0

f 6 1000 50 CME Energy (erg)

4 500 0

0 -50 2 1996 2000 2004 2008 2012 2016 0 2000 4000 6000 8000 1 104 Year Max CME Energy (erg) FigureFigure 3.3. TheThe timetime seriesseries ofof thethe monthlymonthly averageaverage valuesvalues CMECME energyenergy (in(in erg)erg) andand thatthat ofof sunspotsunspot numbersnumbers (SSN) (SSN) during during the the period period 1996–2013 1996–2013 (A), and(A), theand relationship the relationship between betweenF values F and values themonthly and the maximummonthly maximum CME energy CME (B ).energy The blue (B). colorThe blue of the color left axisof the values, left axis smooth values, curve smooth and curve round and points round of plotpoints (A) of refer plot to (A the) referf0F2, to while the f0F2, the while red color the red of thecolor right of the axis right values, axis smoothvalues, smooth curve and curve square and pointssquare denotepoints todenote the sunspot to the sunspot numbers. numbers.

AlongAlong the the same same lines, lines, the the initial initial speed speed of CME of CME increases increases directly directly with the with solar the activity. solar activity. In general, In thegeneral, CMEs the become CMEs faster become through faster the activethrough Sun the phase active and Sun slower phase during and the slower quiet Sunduring phase. the This quiet arises Sun fromphase. investigating This arises from the relation investigating between the the relati CMEon speedsbetween and the the CME sunspot speeds numbers, and the sunspot SSN as shownnumbers, in FigureSSN as4. shown Furthermore, in Figure the 4. monthly Furthermore, average the of CMEmonthly initial average speed of has CME a linear initial correlation speed has with a linear the monthlycorrelation average with thef0F2, monthly and the average following f0F2, formula and the represents following its formula fitting: represents its fitting:

F (MHz)= 3.88 + 8.26 ×10−33 × V (Km/s) (3) F (MHz)= 3.88 + 8.26 10− V (Km/s) (3) × × Where V (Km/s) is the monthly average value of CME speed. The correlation coefficient R equals where V (Km/s) is the monthly average value of CME speed. The correlation coefficient R equals 0.6 ∼0.6 (Pearson’s chi-squared test χ2 equals 246.12). This high correlation coefficient implies that∼ the (Pearson’sfaster CMEs chi-squared can affect testthe f0F2χ2 equals more 246.12).efficiently This than high slower correlation ones. coefficient implies that the faster CMEsAlthough can affect the the polynomial f0F2 more e ffifittingciently gives than a slowerhigher ones.correlation coefficient than the linear fitting in our pastAlthough figures. the We polynomial preferred fitting using giveslinear a correlation higher correlation in order coe to ffimakecient the than investigations the linear fitting clearer in ourand pastthe results figures. to We be preferredcomparable using in an linear obvious correlation behavior. in orderSpecially, to make the second the investigations order polynomial clearer fitting and the is resultsvery close to be to comparable the performed in an linear obvious fitting. behavior. Specially, the second order polynomial fitting is very close to the performed linear fitting.

1000 250 (A) 12

800 200 (B) 10 Sunspot Number Sunspot

600 150 8

400 100 F2 (MHz)

0 6 f CME Speed (Km/s)

200 50 4

0 0 2 1996 2000 2004 2008 2012 2016 100 200 300 400 500 600 700 800 900 Year CME Speed (Km/s) Figure 4. The time series of the monthly average values CME initial speed (Km/s) and that of the sunspot numbers (SSN) during the period 1996–2013 (A), and the relationship between F values and

Universe 2020, 6, x FOR PEER REVIEW 6 of 11

F (MHz) = 4.1127 + 4.1×10−4 × E (erg) (2) where E is the monthly average value of CME energy (erg). The correlation coefficient R equals 0.73 (Pearson’s chi-squared test χ2 equals 178.85). This high value indicates that the CME energy strongly affects the ionospheric critical frequency.

3000 250 12 (A) (B) 2500 200 10

2000 150 Sunspot Number

8

1500 100 F2 (MHz) F2 0

f 6 1000 50 CME Energy (erg)

4 500 0

0 -50 2 1996 2000 2004 2008 2012 2016 0 2000 4000 6000 8000 1 104 Year Max CME Energy (erg) Figure 3. The time series of the monthly average values CME energy (in erg) and that of sunspot numbers (SSN) during the period 1996–2013 (A), and the relationship between F values and the monthly maximum CME energy (B). The blue color of the left axis values, smooth curve and round

points of plot (A) refer to the f0F2, while the red color of the right axis values, smooth curve and square points denote to the sunspot numbers.

Along the same lines, the initial speed of CME increases directly with the solar activity. In general, the CMEs become faster through the active Sun phase and slower during the quiet Sun phase. This arises from investigating the relation between the CME speeds and the sunspot numbers, SSN as shown in Figure 4. Furthermore, the monthly average of CME initial speed has a linear correlation with the monthly average f0F2, and the following formula represents its fitting:

F (MHz)= 3.88 + 8.26 ×10−3 × V (Km/s) (3) Where V (Km/s) is the monthly average value of CME speed. The correlation coefficient R equals ∼0.6 (Pearson’s chi-squared test χ2 equals 246.12). This high correlation coefficient implies that the faster CMEs can affect the f0F2 more efficiently than slower ones. Although the polynomial fitting gives a higher correlation coefficient than the linear fitting in our past figures. We preferred using linear correlation in order to make the investigations clearer and Universethe results2020, to6, 200be comparable in an obvious behavior. Specially, the second order polynomial fitting7 of 11is very close to the performed linear fitting.

1000 250 (A) 12

800 200 (B) 10 Sunspot Number Sunspot

600 150 8

400 100 F2 (MHz)

0 6 f CME Speed (Km/s)

200 50 4

0 0 2 1996 2000 2004 2008 2012 2016 100 200 300 400 500 600 700 800 900 Year CME Speed (Km/s)

UniverseFigureFigure 2020 4.,4. 6 , Thex FOR time PEER series REVIEW of thethe monthlymonthly averageaverage valuesvalues CMECME initialinitial speedspeed (Km(Km/s)/s) andand thatthat ofof thethe 7 of 11 sunspotsunspot numbersnumbers (SSN)(SSN) duringduring thethe periodperiod 1996–20131996–2013 ((AA),), andand thethe relationshiprelationship betweenbetween FF valuesvalues andand thethe monthly monthly average average CMEs CMEs initial initial speeds speeds ( B(B).). The The blue blue color color of of the the left left axis axis values, values, smooth smooth curve curve and and roundround points points of of plot plot ( A(A)) refer refer to tof 0fF20F2 values,values, whilewhile thethe redred colorcolor ofof thethe rightright axisaxis values,values, smoothsmooth curve,curve, andand square square points points denote denote to to the the sunspot sunspot numbers. numbers. 4.2. Seasonal Variation 4.2. Seasonal Variation The that leads to the ion production in the ionosphere is attributed not only to the The solar energy that leads to the ion production in the ionosphere is attributed not only to the solar radiation, but also to the solar particles [26]. This fact is generally valid during all seasons, solar radiation, but also to the solar particles [26]. This fact is generally valid during all seasons, but but may be strong or slightly varying according to the season, in other words, the seasonal variation. may be strong or slightly varying according to the season, in other words, the seasonal variation. These seasonal variations. These, in general, occur due to the tilt in the rotation axis of the Earth and These seasonal variations. These, in general, occur due to the tilt in the rotation axis of the Earth and the rotation of the Earth around the Sun. As a result, the Earth leans toward the Sun in the summer the rotation of the Earth around the Sun. As a result, the Earth leans toward the Sun in the summer while it leans away from the Sun in winter, the equinox occurs in between as well. During the summer, while it leans away from the Sun in winter, the equinox occurs in between as well. During the the northern hemisphere, especially high latitudes, receives more solar radiation than the southern summer, the northern hemisphere, especially high latitudes, receives more solar radiation than the hemisphere due to the tilt angle and vice versa in the winter for the same northern hemisphere. southern hemisphere due to the tilt angle and vice versa in the winter for the same northern This situation is similar in the case of solar plasma, including the solar wind and CMEs. In other words, hemisphere. This situation is similar in the case of solar plasma, including the solar wind and CMEs. during the summer season, the northern hemisphere, especially high and mid-latitudes, is subjected to In other words, during the summer season, the northern hemisphere, especially high and mid- plasma injection more than during the winter season. latitudes, is subjected to plasma injection more than during the winter season. Actually, the terrestrial northern hemisphere faces the heliospheric equator in the summer, Actually, the terrestrial northern hemisphere faces the heliospheric equator in the summer, which inclines by ~7.25 on the ecliptic, as a result, one can expect that the CMEs parameters can affect which inclines by ~7.25°◦ on the ecliptic, as a result, one can expect that the CMEs parameters can f0F2 values in the mid-latitude region, tropical zone, in the summer season more efficiently than the affect f0F2 values in the mid-latitude region, tropical zone, in the summer season more efficiently than spring and the autumn then the winter. the spring and the autumn then the winter. Figure5 introduces a sketch which illustrates the impact of the Earth’s inclination with respect Figure 5 introduces a sketch which illustrates the impact of the Earth’s inclination with respect to the ecliptic plane on the area hit by the solar plasma. It shows clearly that the shorter path of the to the ecliptic plane on the area hit by the solar plasma. It shows clearly that the shorter path of the CME’s plasma is to the pole and it occurs during the summer season, while the middle path happens CME’s plasma is to the pole and it occurs during the summer season, while the middle path happens through the equinoxes, spring and autumn, and the longer path occurs during the winter season. through the equinoxes, spring and autumn, and the longer path occurs during the winter season.

FigureFigure 5. 5.A A sketch sketch shows shows the the path path of of the the CME’s CME’s plasma, plasma through, through the the magnetosphere, magnetosphere, directed directed into theinto leftthe panel left panel (A): during (A): during the equinoxes; the equinoxes; the middle the panel middle (B): panel during (B summer): during for summer the southern for the hemisphere; southern thehemisphere; right panel the (C ):right during panel summer (C): during for the summer northern for hemisphere. the northern The he shortestmisphere. path The to shortest the pole path is during to the thepole summer is during season, the summer while the season, longest while one isthe during longest the one winter is during season. the winter season.

FigureFigure6 6shows shows a a high high correlation correlation between between the the monthly monthly average average CME CME energy energy and and the the monthly monthly averageaveragef 0fF2,0F2, which which exhibits exhibits seasonal seasonal variation: variation: (R (R= 0.76)= 0.76 in) in summer, summer, (R (R= 0.64) = 0.64) in winter,in winter, (R =(R0.59) = 0.59) in in spring, then (R = 0.35) in autumn, in the northern hemisphere. However, we found that using the monthly maximum values of CME energy gives better results and the correlation coefficient values R increase as follows: (R = 0.82) in summer, (R = 0.80) in autumn, (R = 0.75) in spring, then (R = 0.67) in winter. Additionally, The CMEs width and initial speed display a similar seasonal variation trend as shown in Figures 7 and 8, but with slight discrepancies: for the CMEs width, the correlation coefficients are (R = 0.69) in summer, (R = 0.68) in spring, (R = 0.62) in autumn, then (R = 0.60) in winter, in the northern hemisphere. At the same time, for the CME speed, the correlation coefficients are (R = 0.72) in spring, (R = 0.65) in winter, (R = 0.64) in summer, then (R = 0.46) in autumn, in the northern hemisphere. Table 3 summarizes the values of the correlation coefficients R.

Universe 2020, 6, 200 8 of 11 spring, then (R = 0.35) in autumn, in the northern hemisphere. However, we found that using the monthly maximum values of CME energy gives better results and the correlation coefficient values R increase as follows: (R = 0.82) in summer, (R = 0.80) in autumn, (R = 0.75) in spring, then (R = 0.67) in winter. Additionally, The CMEs width and initial speed display a similar seasonal variation trend as shown in Figures7 and8, but with slight discrepancies: for the CMEs width, the correlation coe fficients are (R = 0.69) in summer, (R = 0.68) in spring, (R = 0.62) in autumn, then (R = 0.60) in winter, in the northern hemisphere. At the same time, for the CME speed, the correlation coefficients are (R = 0.72) in spring, (R = 0.65) in winter, (R = 0.64) in summer, then (R = 0.46) in autumn, in the northern hemisphere. TableUniverseUniverse3 summarizes 2020 2020, 6, ,6 x, xFOR FOR PEER the PEER values REVIEW REVIEW of the correlation coe fficients R. 8 8of of 11 11

Figure 6. The seasonal variation of the monthly average f0F20 with the monthly average CME energy FigureFigure 6. 6.The The seasonal seasonal variation variation of of the the monthly monthly average averagef0 fF2F2 with with the the monthly monthly average average CME CME energy energy (left panel) and the monthly maximum CME energy (right panel). The season points and its fitting (left(leftpanel) panel) and and the the monthly monthly maximum maximum CME CME energy energy (right (rightpanel). panel). The The season season points points andits and fitting its fitting line arelineline colorized are are colorized colorized as in asthe as in in figure’s the the figure’s figure’s caption caption caption of each of of seasoneach each season season word’s word’s word’s color. color. color.

Figure 7. The seasonal variation of the monthly average f 0F2 as a response to the monthly average FigureFigure 7: 7: The The seasonal seasonal variation variation of of the the monthly monthly average average f0 fF20F2 as as a a response response to to the the monthly monthly average average CMECMECME widthwidth width variation.variation. variation. TheThe The seasonseason season pointspoints points andand and itsits its fittingfittin fittingg lineline line areare are colorizedcolorized colorized asas as inin in thethe the figure’sfigure’s figure’s captioncaption caption ofof of eacheacheach seasonseason season word’sword’s word’s color.color. color.

FigureFigure 8. 8. The The seasonal seasonal variation variation of of the the monthly monthly average average f 0fF20F2 as as a a response response to to the the monthly monthly average average CMECME initial initial speed speed variation. variation. The The season season points points and and its its fitting fitting line line are are colorized colorized as as in in the the figure’s figure’s captioncaption of of each each season season word’s word’s color. color.

Universe 2020, 6, x FOR PEER REVIEW 8 of 11

Figure 6. The seasonal variation of the monthly average f0F2 with the monthly average CME energy (left panel) and the monthly maximum CME energy (right panel). The season points and its fitting line are colorized as in the figure’s caption of each season word’s color.

Figure 7: The seasonal variation of the monthly average f0F2 as a response to the monthly average UniverseCME2020 ,width6, 200 variation. The season points and its fitting line are colorized as in the figure’s caption of9 of 11 each season word’s color.

FigureFigure 8. 8.The The seasonal seasonal variation variation of of the the monthly monthly average averagef 0fF20F2 asas a a response response to to the the monthly monthly average average CMECME initial initial speed speed variation. variation. The The season season points points and itsand fitting its fitting line are line colorized are colorized as in the as figure’s in the captionfigure’s ofcaption each season of each word’s season color. word’s color.

Table 3. The correlation coefficient values (R) and Pearson’s chi-squared test χ2 of the linear relations between the monthly average f0F2 and each of the monthly maximum CME energy and the monthly average values of the CME width and speed.

Max CME Energy Average CME Energy CME Width CME Speed Seasons R χ2 R χ2 R χ2 R χ2 Winter 0.67 33.244 0.64 36.431 0.61 38.765 0.65 35.593 Spring 0.75 52.89 0.59 79.476 0.68 64.845 0.72 58.644 Summer 0.82 31.656 0.76 41.242 0.69 51.213 0.64 57.484 Autumn 0.80 21.987 0.35 55.283 0.62 38.906 0.46 49.43

Actually, our selected ionosonde station is in the northern hemisphere of the Earth, localized approximately in the middle latitudes. Therefore, the correlation is the strongest in the summer season which may be attributed to that the number of electron density varies not only seasonal but also with respect to the latitudinal variations. However, the CME speed has a behavior that is different from the CME energy and width. The highest impact happens during equinoxes in the spring season, and this impact increases in the autumn season. This finding is also supported by the fact that the rate of electron density in equinox is faster than that in winter and summer season which leads to higher TEC at equinox months. Further, during this period, the Sun is directly above the equator, which leads to a higher value of TEC during the equinox at low latitude regions than at mid or high latitude [27].

5. Conclusions

The data of f0F2 used in this work were collected from the ionosonde station PRJ18 (Puerto Rico) located approximately in the mid-latitude region. We estimated the monthly average values of f0F2 during the period 1996–2013 and the corresponding monthly average values of the CME’s parameters. By investigating the average and the maximum monthly values of f0F2, we pointed out that the most preferable values, giving better results, are the monthly average ones. The average values reflect the total variation in the electron density throughout the day and the night that indicates the total incoming forces by solar particles. We also found that the monthly average value of f0F2 changes dramatically with time. It has a high coherence with the sunspot number (SSN). This behavior emphasizes that the f0F2 profiles rely, for a great extent, on the solar activity. Moreover, CME’s parameters are found to be varying with SSN in the same coherence behavior, like f0F2. Further, by examining the correlations between each of the monthly average values of the Universe 2020, 6, 200 10 of 11

CMEs’ physical properties and that of f0F2, throughout the period of study, we found that relations are linear with the correlation coefficients equal approximately to 0.73, 0.6 and 0.6 for the CME energy, angular width and initial speed respectively. The wide CMEs are more frequent during the active Sun, while they become less frequent during the quiet Sun. The CMEs’ speed and energy exhibit a similar behavior with the solar activity as well. As a result, the wider, energetic, and faster CMEs can increase the electron density in the ionosphere due to the plasma injection, giving rise to high values of f0F2. We also conclude that the highest impact of the CMEs on the seasonal variation is found to be in the summer, then equinoxes (spring and autumn) followed by winter. This is attributed to the direction of the Earth’s inclined rotational axis, with respect to the heliospheric equator. During the summer solstice the terrestrial exposed area to the Sun is the greatest in the northern hemisphere, in addition, the north pole is the nearest one which has a shorter path for the plasma more than in the winter which has a longer path, giving rise to more plasma injection happening in the summer. This is valid for the CMEs energy and angular width. However, the CMEs speed shows a different behavior in which the faster CMEs raise the values of f0F2 more efficiently in the spring, the winter and the summer, followed by the autumn season, respectively.

Author Contributions: Conceptualization, R.M. and H.M.F.; Data curation, R.M. and H.M.F.; Formal analysis, R.M. and H.M.F.; Funding acquisition, A.Y.; Investigation, R.M. and H.M.F.; Methodology, R.M.; Software, R.M.; Writing—original draft, H.M.F.; Writing—review & editing, R.M., H.M.F. and E.G. All authors have read and agreed to the published version of the manuscript. Funding: This research work was funded by the International Center for Space Weather Science and Education, Kyushu University, Japan. Acknowledgments: The foF2 data used in the present paper are from Space Physics Interactive Data Resource, available online at http://www.ngdc.noaa.gov/stp/spidr.html. CME data were taken from SOHO LASCO CME Catalog obtained from http://cdaw.gsfc.nasa.gov/CME_list/. This work was supported by JSPS KAKENHI Grant Number JP20H01961 and JP15H05815. Conflicts of Interest: The authors declare no conflict of interest.

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