Relation between Coronal Mass Ejections and Sunspot Number during Solar Cycle 24

In this study, we report a statistical study for the relationship between coronal mass ejections (CMEs) and sunspot number (SSN) that were registered during the period 2008-2017 for the solar cycle 24. SSN was extracted from Sunspot Index and Long-term Solar Observations (SILSO), while CMEs number from observations made by the Large Angle and Spectrometric Coronagraph (LASCO) on board the Solar and Heliospheric Observatory mission (SOHO). The present period was adopted to conduct the investigation and obtain the mutual correlation between SSN and CMEs. The relationship between CME, the speed of halo CME, and partial halo CMEs for solar cycle 24 were studied. The analysis of results indicated that the average speed of halo CMEs is almost faster than the average speed of partial halo CMEs.Test results of the annual correlation between SSN and CMEs are simple and can be represented by a linear regression equation. Finally, Gaussian fit as a function of time was performed to compare behavior of numbers the CME and SSN with the years and the results show that the center of the peaks agrees with 2014.

1862 development of ionospheric storms; all these phenomena have been a subject of intensive space weather research and are worth being predicted accurately in practical space weather forecast [10].
A halo CME surrounds the occulting disk of the observation coronagraph in the plane's projection. Halo CMEs were first registered by Howard et al. (1982). Only a handful of CMEs were recorded by the Solwind coronagraph on board the P78-1 mission. Halo CMEs represent only about 3% of all CMEs. They also represent an energetic population because most CMEs that generate large SEPs and major geomagnetic storms are halos. A halo CME is usually created from close to the center of the disk, while about 10% are created close to the limb. In the halos of the limbs, the disorder that appears on the opposite side is likely to be unexpected [11].
On the photosphere the cooler and the active regions are Sunspots that releases a lower intensity of light in every directions. The sunspots advanced when concentrated magnetic field lines begin to emerge from the photosphere directed toward the solar corona. Because a condition called ‗frozen-in' magnetic field the isolation of the plasma within these field lines stayed from the surrounding solar surface. The solar convection below the flux tube hampered by the orientation and force of the local magnetic field, resulting in fewer plasma particles within this region. Both pressure and temperature within the flux tube decrease while magnetic pressure keeps the flux tube from collapsing inward. Solar convection under the flux tube is impeded by the direction and force of the local magnetic field, which has reduced the number of plasma molecules in this region. Temperature and pressure drop in the flux tube and the magnetic pressure stops the breakdown into the flux tube [12].
CMEs are the most spectacular phenomenon of solar activity. They occur in regions of closed magnetic fields that overlie magnetic inversion lines [13]. A study on CME is an important topic that is related directly to the space environment [14]. The sunspot cycle is an important form of solar variability that indicates the extent of closed magnetic field structure on the sun and hence is important to the study of the origin of coronal mass ejections. The solar wind is a stream of charged particles released from the upper atmosphere of the Sun. This plasma consists of mostly electrons, protons and alpha particles. The magnetic field of the Sun, as well as different structures, waves and turbulent fluctuations on a wide range of scales are embedded within the solar wind. Webb & Howard [15] studied CMEs from 1973 to 1989 concluding that CME occurrence frequency tends to follow the solar activity cycle in both amplitude and phase. Gopalswamy et al. (2009) [16] have also studied CME occurrence in relation to sunspot number and found that the correlation between them is quite weak during the maximum phase period of solar cycle as compared to that in both ascending as well as descending phase. Researchers have studied the solar cycle that ended in December 2008 which is known as solar cycle 23. This cycle was longer than normal. The present solar cycle 24 started in December 2008 and is expected to have a shorter time period.‖ In this paper we performed a statistical study for the relationship between CMEs and SSN from January 2008 to December 2017 for this cycle, depending on available observational data.

MATERIALS AND METHODS Data Selection
In this research, the SSNs data were obtained from Sunspot Index and Long-term Solar Observations (SILSO), which is supported by the International Council for Science World Data System [17]. Meanwhile, the data on CMEs and halo CMEs were downloaded from the Coordinated Data Analysis Workshops ( CDAW) catalog [18, 19] during the period from January 2008 to December 2017 through solar cycle 24.

RESULTS AND DISCUSSION
In this study, the statistical analysis was conducted to investigate the behaviors of SSN and CMEs and derive the mutual correlation between these parameters for the annual time during the period from January 2008 to December 2017 through solar cycle 24. Although the solar cycle number 24 started in December 2008, data were taken before that to increase the sample number which gives better statistics in the curve fitting. The speed of full halo CMEs and partial halo CMEs for solar cycle 24 were analyzed alongside the SSN and CME number. The angular width of 360 o was considered for full halo CMEs, while 121-359 o was considered for partial halo CMEs. Other sizes of angular widths could be narrow (~ 5 to 120 o ) or spike (less than ~ 5 o ); and CMEs with these widths were not considered in the present research.
The size and speed of CMEs are important parameters to determine when attempting to predict if and when the CMEs will impact the Earth. These properties of CMEs can be estimated using observations from an instrument known as a coronagraph, such as the one in LASCO which blocks the bright light of the solar disk thus allowing the outer solar atmosphere (chromosphere and corona) to be observed.
A total of 6452.3 SSN and 15,946 CMEs were observed during the period from January 2008 to December 2017 through solar cycle 24. Out of these CMEs, 324 were full halo and 1040 were partial halo. This means that halo CMEs represented only about 2% of all CMEs, and partial halo represented only about 7% of all CMEs in this time period. Table-1 shows the values of the observed SSNs and CMEs for the selected period. The number of CMEs that have a speed greater than or equal to 1000 km.s -1 was 203 including 109 halo CME and 54 partial haloes during the period from January 2008 to December 2017 through solar cycle 24.
The total number of occurrence of CME in all months in 2014 were 2478 events, but when we sum the total sunspot number in all months in 2014, the result was found to be 1363.3. The solar activity in 2014 was at its maximum in 2014. Therefore, it is higher than in other years in cycle 24.
The total sunspot number without means was calculated by summing the total sunspot number in ten years and the result was 6452.3, while the total number of occurrence of CMEs in ten years was 15,946 events (see Table-1). So, it is noted that the total sunspot number was smaller than the total number of occurrence of CME in cycle 24. It is important to know the exact relationship between sunspots number and CME and provide a tool to replace the study of one of these events. The number of occurrence of CME slightly increases towards sunspots maxima and slightly decreases towards sunspots minima.
The highest percentage of halo CMEs were 3.9%, 2.8% recorded in 2012, 2014 respectively.    Then, a more complicated curve-fitting procedure was performed for the data in Figure-1 Figure-5 shows the results of both fits. In Table-2 the  statistics of both fits are given. An important note that should be made here is, the Gaussian fit as a function of time can only be valid for comparison between CME and SSN number in this case, and the relations found from curve fitting should not be assumed as a general case because the Gaussian depends on time (in years) and these parameters has a cyclic role in the solar cycle. Nevertheless, a fair comparison can be deduced from this fitting as seen from Table-2. It can be clearly seen that the Gaussian fit gave good approximation for both numbers of CME and SSN. Both fittings gave centers in 2014 with a relatively low standard deviation of less than 3%. Furthermore, the constants that describe the behavior of the Gaussian, namely b and c, were close in general, with again less than 3% deviation. The constant that describes the height of Gaussian peak, the parameter a, was different since it describes the difference between the peaks of each curve.