Coronal Mass Ejections Parameters Research Articles

CME Arrival Time Prediction Based on Coronagraph Observations and Machine-learning Techniques

The timely and precise prediction of the arrival time of coronal mass ejections (CMEs) is crucial in mitigating their potential adverse effects. In this study, we present a novel prediction method utilizing a deep-learning framework coupled with physical characteristics of CMEs and background solar wind. Time series images from synchronized solar white-light and EUV observations of 156 geoeffective CME events during 2000–2020 are collected for this study, according to the Richardson and Cane interplanetary CME directory and the SOHO/LASCO CME catalog of NASA/CDAW. The CME parameters are obtained from the CDAW website and the solar wind parameters are from OMNI2 website. The observational images are first fed into a convolutional neural network (CNN) to train a regression model as Model A. The results generated by the original CNN are then integrated with 11 selected physical parameters in additional neural network layers of Model B to improve the predictions. Under optimal configurations, Model A achieves a minimum mean absolute error (MAE) of 7.87 hr, whereas Model B yields a minimum MAE of 5.12 hr. During model training, we employed tenfold cross validation to reduce the occasionality of biased data. The average MAE of Model B on 10 folds is 33% lower than that of model A. The results demonstrate that combining the imaging observations with the physical properties of CMEs and background solar wind to train a machine-learning model can benefit the forecasting of CME arrival times.

Novel scaling laws to derive spatially resolved flare and CME parameters from sun-as-a-star observables

Coronal mass ejections (CMEs) are often associated with X-ray (SXR) flares powered by magnetic reconnection in the low corona, while the CME shocks in the upper corona and interplanetary (IP) space accelerate electrons often producing the type II radio bursts. The CME and the reconnection event are part of the same energy release process as highlighted by the correlation between reconnection flux (ϕrec) that quantifies the strength of the released magnetic free energy during the SXR flare, and the CME kinetic energy that drives the IP shocks leading to type II bursts. Unlike the Sun, these physical parameters cannot be directly inferred in stellar observations. Hence, scaling laws between unresolved sun-as-a-star observables, namely SXR luminosity (LX) and type II luminosity (LR), and the physical properties of the associated dynamical events are crucial. Such scaling laws also provide insights into the interconnections between the particle acceleration processes across low-corona to IP space during solar-stellar “flare-CME-type II” events. Using long-term solar data in the SXR to radio waveband, we derived a scaling law between two novel power metrics for the flare and CME-associated processes. The metrics of “flare power” (Pflare = √(LXϕrec)) and “CME power” (PCME = √(LRVCME2)), where VCME is the CME speed, scale as Pflare ∝ PCME0.76 ± 0.04. In addition, LX and ϕrec show power-law trends with PCME with indices of 1.12 ± 0.05 and 0.61 ± 0.05, respectively. These power laws help infer the spatially resolved physical parameters, VCME and ϕrec, from disk-averaged observables, LX and LR during solar-stellar flare-CME-type II events.

Modelling non-radially propagating coronal mass ejections and forecasting the time of their arrival at Earth

We present the study of two solar eruptive events observed on December 7 2020 and October 28 2021. Both events were associated with full halo coronal mass ejections (CMEs) and flares. These events were chosen because they show a strong non-radial direction of propagation in the low corona and their main propagation direction observed in the inner heliosphere is not fully aligned with the Sun-Earth line. This characteristic makes them suitable for our study, which aims to inspect how the non-radial direction of propagation in the low corona affects the time of CMEs’ arrival at Earth. We reconstructed the CMEs using SOHO/LASCO and STEREO/COR observations and modelled them with the 3D MHD model EUHFORIA and the cone model for CMEs. In order to compare the accuracy of forecasting the CME and the CME-driven shock arrival time at Earth obtained from different methods, we also used so-called type II bursts, radio signatures of associated shocks, to find the velocities of the CME-driven shocks and forecast the time of their arrival at Earth. Additionally, we estimated the CME arrival time using the 2D CME velocity obtained from the white light images. Our results show that the lowest accuracy of estimated CME Earth arrival times is found when the 2D CME velocity is used (time difference between observed and modelled arrival time, Δt ≈ −29 h and −39 h, for the two studied events, respectively). The velocity of the type II radio bursts provides somewhat better – but still not very accurate – results (Δt ≈ +21 h and −29 h, for the two studied events, respectively). Employing, as an input to EUHFORIA, the CME parameters obtained from the graduated cylindrical shell (GCS) fittings at consequently increasing heights, results in a strongly improved accuracy of the modelled CME and shock arrival time; Δt changes from 20 h to 10 min in the case of the first event, and from 12 h to 30 min in the case of the second one. This improvement shows that when we increased the heights of the GCS reconstruction we accounted for the change in the propagation direction of the studied CMEs, which allowed us to accurately model the CME flank encounter at Earth. Our results show the great importance of the change in the direction of propagation of the CME in the low corona when modelling CMEs and estimating the time of their arrival at Earth.

Multi-spacecraft study with the Icarus model. Modelling the propagation of CMEs to Mercury and Earth

Coronal mass ejections (CMEs) are the main drivers of the disturbances in interplanetary space. Earth-directed CMEs can be dangerous, and understanding the CME interior magnetic structure is crucial for advancing space weather studies. It is important to assess the capabilities of a numerical heliospheric model, as a firm understanding of the nature and extent of its limitations can be used to improve the model and the space weather predictions based on it. The aim of the present study is to test the capabilities of the recently developed heliospheric model Icarus and the linear force-free spheromak model that has been implemented in it. To validate the Icarus space weather modelling tool, two CME events were selected that were observed by two spacecraft located near Mercury and Earth, respectively. This enables us to test the heliospheric model computed with Icarus at two distant locations. The source regions for the CMEs were identified, and the CME parameters were determined and later optimised. Different adaptive mesh refinement levels were applied in the simulations to assess its performance by comparing the simulation results to in situ measurements. The first CME event erupted at 15:25 on July 9, 2013. The modelled time series were in good agreement with the observations both at MESSENGER and ACE. The second CME event started at 10:25 on February 16, 2014, and was more complicated, as three CME interactions occurred in this event. It was impossible to recover the observed profiles without modelling the other two CMEs that were observed, one before the main CME and one afterward. The parameters for the three CMEs were identified and the three CMEs were modelled in Icarus. For both CME studies, AMR level 3 was sufficient to reconstruct small-scale features near Mercury, while at Earth, AMR level 4 was necessary due to the radially stretched grid that was used. The profiles obtained at both spacecraft resemble the in situ measurements well. The current limitations of the space weather modelling tool result in an excessively small deceleration of the CME propagation during the CME--CME interaction as measured by MESSENGER and ACE.

CAMEL. II. A 3D Coronal Mass Ejection Catalog Based on Coronal Mass Ejection Automatic Detection with Deep Learning

Coronal mass ejections (CMEs) are major drivers of geomagnetic storms, which may cause severe space weather effects. Automating the detection, tracking, and three-dimensional (3D) reconstruction of CMEs is important for operational predictions of CME arrivals. The COR1 coronagraphs on board the Solar Terrestrial Relations Observatory spacecraft have facilitated extensive polarization observations, which are very suitable for the establishment of a 3D CME system. We have developed such a 3D system comprising four modules: classification, segmentation, tracking, and 3D reconstructions. We generalize our previously pretrained classification model to classify COR1 coronagraph images. Subsequently, as there are no publicly available CME segmentation data sets, we manually annotate the structural regions of CMEs using Large Angle and Spectrometric Coronagraph C2 observations. Leveraging transformer-based models, we achieve state-of-the-art results in CME segmentation. Furthermore, we improve the tracking algorithm to solve the difficult separation task of multiple CMEs. In the final module, tracking results, combined with the polarization ratio technique, are used to develop the first single-view 3D CME catalog without requiring manual mask annotation. Our method provides higher precision in automatic 2D CME catalog and more reliable physical parameters of CMEs, including 3D propagation direction and speed. The aforementioned 3D CME system can be applied to any coronagraph data with the capability of polarization measurements.

Analysis of SEP Events and Their Possible Precursors Based on the GSEP Catalog

Solar energetic particle (SEP) events are one of the most crucial aspects of space weather. Their prediction depends on various factors including the source solar eruptions such as flares and coronal mass ejections (CMEs). The Geostationary Solar Energetic Particle (GSEP) events catalog was developed as an extensive data set toward this effort for solar cycles 22, 23, and 24. In the present work, we review and extend the GSEP data set by (1) adding “weak” SEP events that have proton enhancements from 0.5 to 10 pfu in the E >10 MeV channel and (2) improving the associated solar source eruptions information. We analyze and discuss spatiotemporal properties such as flare magnitudes, locations, rise times, and speeds and widths of CMEs. We check for the correlation of these parameters with peak proton fluxes and event fluences. Our study also focuses on understanding feature importance toward the optimal performance of machine-learning (ML) models for SEP event forecasting. We implement random forest, extreme gradient boosting, logistic regression, and support vector machine classifiers in a binary classification schema. Based on the evaluation of our best models, we find both the flare and CME parameters are requisites to predict the occurrence of an SEP event. This work is a foundation for our further efforts on SEP event forecasting using robust ML methods.

How Magnetic Erosion Affects the Drag-Based Kinematics of Fast Coronal Mass Ejections

In order to advance our understanding of the dynamic interactions between coronal mass ejections (CMEs) and the magnetized solar wind, we investigate the impact of magnetic erosion on the well-known aerodynamic drag force acting on CMEs traveling faster than the ambient solar wind. In particular, we start by generating empirical relationships for the basic physical parameters of CMEs that conserve their mass and magnetic flux. Furthermore, we examine the impact of the virtual mass on the equation of motion by studying a variable-mass system. We next implement magnetic reconnection into CME propagation, which erodes part of the CME magnetic flux and outer-shell mass, on the drag acting on CMEs, and we determine its impact on their time and speed of arrival at 1 AU. Depending on the strength of the magnetic erosion, the leading edge of the magnetic structure can reach near-Earth space up to ≈ three hours later, compared to the non-eroded case. Therefore, magnetic erosion may have a significant impact on the propagation of fast CMEs and on predictions of their arrivals at 1 AU. Finally, the modeling indicates that eroded CMEs may experience a significant mass decrease. Since such a decrease is not observed in the corona, the initiation distance of erosion may lie beyond the field-of-view of coronagraphs (i.e. 30~mathrm{R}_{odot }).

Deciphering Faint Gyrosynchrotron Emission from a Coronal Mass Ejection Using Spectropolarimetric Radio Imaging

Measurements of the plasma parameters of coronal mass ejections (CMEs), particularly the magnetic field and nonthermal electron population entrained in the CME plasma, are crucial to understand their propagation, evolution, and geo-effectiveness. Spectral modeling of gyrosynchrotron (GS) emission from CME plasma has been regarded as one of the most promising remote-sensing techniques for estimating spatially resolved CME plasma parameters. Imaging the very low flux density CME GS emission in close proximity to the Sun with orders of magnitude higher flux density has, however, proven to be rather challenging. This challenge has only recently been met using the high dynamic range imaging capability of the Murchison Widefield Array (MWA). Although routine detection of GS is now within reach, the challenge has shifted to constraining the large number of free parameters in GS models, a few of which are degenerate, using the limited number of spectral points at which the observations are typically available. These degeneracies can be broken using polarimetric imaging. For the first time, we demonstrate this using our recently developed capability of high-fidelity polarimetric imaging on the data from the MWA. We show that spectropolarimetric imaging, even when only sensitive upper limits on circularly polarization flux density are available, is not only able to break the degeneracies but also yields tighter constraints on the plasma parameters of key interest than possible with total intensity spectroscopic imaging alone.

High Energy Solar Particle Events and Their Relationship to Associated Flare, CME and GLE Parameters

AbstractLarge solar eruptive events, including solar flares and coronal mass ejections (CMEs), can lead to solar energetic particle (SEP) events. During these events, protons are accelerated up to several GeV and pose numerous space weather risks. These risks include, but are not limited to, radiation hazards to astronauts and disruption to satellites and electronics. The highest energy SEPs are capable of reaching Earth on timescales of minutes and can be detected in ground level enhancements (GLEs). Understanding and analyzing these events is critical to future forecasting models. However, the availability of high energy SEP data sets is limited, especially that which covers multiple solar cycles. The majority of analysis of SEP events considers data at energies <100 MeV. In this work, we use a newly calibrated data set using data from Geostationary Operational Environmental Satellite‐high energy proton and alpha detector between 1984 and 2017. Analysis of the SEP events in this time period over three high energy channels is performed, and SEP properties are compared to flare and CME parameters. In addition, neutron monitor (NM) observations are examined for the relevant GLE events. We find that correlations between SEP peak intensity and the CME speed are much weaker than for lower SEP energies. Correlations with flare intensity are broadly similar or weaker. Strong correlations are seen between >300 MeV data and GLE properties from NM data. The results of our work can be utilized in future forecasting models for both high energy SEP and GLE events.

Is There a Dynamic Difference between Stealthy and Standard Coronal Mass Ejections?

Stealthy coronal mass ejections (CMEs), lacking low coronal signatures, may result in significant geomagnetic storms. However, the mechanism of stealthy CMEs is still highly debated. In this work, we investigate whether there are differences between stealthy and standard CMEs in terms of their dynamic behaviors. Seven stealthy and eight standard CMEs with low speeds are selected. We calculate two-dimensional speed distributions of CMEs based on the cross-correlation method, rather than the unidimensional speed, and further obtain more accurate distributions and evolution of CME mechanical energies. Then we derive the CME driving powers and correlate them with CME parameters (total mass, average speed, and acceleration) for standard and stealthy CMEs. Besides, we study the forces that drive CMEs, namely, the Lorentz force, gravitational force, and drag force due to the ambient solar wind near the Sun. The results reveal that both standard and stealthy CMEs are propelled by the combined action of those forces in the inner corona. The drag force and gravitational force are comparable with the Lorentz force. However, the impact of the drag and Lorentz forces on the global evolution of stealthy CMEs is significantly weaker than that on standard CMEs.

Statistical Analysis of the Link between the Decrease in the Global Solar Magnetic Field in Cycle 24 and the Coronal Mass Ejection Parameters

Statistical Analysis of the Link between the Decrease in the Global Solar Magnetic Field in Cycle 24 and the Coronal Mass Ejection Parameters

Numerical Research on the Effect of the Initial Parameters of CME Flux-rope Model on Simulation Results. III. Different Initial Energy of CMEs

In numerical studies, the initial parameters of coronal mass ejections (CMEs) have great influence on the simulation results. In our previous work, it has been proved that when the initial velocity is constant, the initial total mass mainly determines the propagation of the CME. On this basis, we carry out further research from the perspective of CME initial energy. We introduced a graduated cylindrical shell model into a 3D interplanetary total variation diminishing magnetohydrodynamic model to study the effect of different parameters of CMEs on simulation results. In this paper, we simulate several CME cases with different initial parameters and study the simulation results with a different initial energy composition. Actually, in interplanetary space, the kinetic energy of the CME always plays a dominant role. In order to study the effect of the initial thermal energy and magnetic energy on the propagation process of the CME, in this simulation, we adjust the initial parameters to make the thermal energy and magnetic energy reach the same level as the kinetic energy or an even higher level. Our results show that the initial total energy of the CME basically determines its arrival time at Earth, which indicates that the kinetic energy, thermal energy, and magnetic energy have similar effects on the propagation of the CMEs. Moreover, when the total energy keeps constant, the decrease of initial density will lead to the enhancement of CME expansion, which may make the front of the CME reach Earth earlier.

Modeling of Solar Wind Disturbances Associated with Coronal Mass Ejections and Verification of the Forecast Results

Solar wind (SW) disturbances associated with coronal mass ejections (CMEs) cause significant geomagnetic storms, which may lead to the malfunction or damage of sensitive on-ground and space-based critical infrastructure. CMEs are formed in the solar corona, and then propagate to the Earth through the heliosphere as Interplanetary CME (ICME) structures. We describe the main principles in development with the online, semi-empirical system known as the Space Monitoring Data Center (SMDC) of the Moscow State University, which forecasts arrival of ICMEs to Earth. The initial parameters of CMEs (speeds, startup times, location of the source) are determined using data from publicly available catalogs based on solar images from space telescopes and coronagraphs. After selecting the events directed to Earth, the expected arrival time and speed of ICMEs at the L1 point are defined using the Drag-Based model (DBM), which describes propagation of CMEs through the heliosphere under interaction with the modeled quasi-stationary SW. We present the test results of the ICME forecast in the falling phase of Cycle 24 obtained with the basic version of SMDC in comparison with results of other models, its optimization and estimations of the confidence intervals, and probabilities of a successful forecast.

Coronal mass ejection and solar activity for cycle 23 and 24; a comparative analysis of observational parameters

We analyzed sunspot tracers [sunspot number (SSN) and sunspot area (SSA)] and Coronal Mass Ejection (CME) observed parameters for cycle 23 and 24, comparing sunspot tracers time series with time series for CME parameters [Initial speed and Acceleration] for All and segregated CMEs for possible similarities in their variation pattern. A comparison of CME time series with solar activity (especially SSAT and SSN which seem to reflect the true general activity cycle) shows that fast CMEs follow the solar activity cycle but slow CMEs don’t. Also, CMEs with positive and negative acceleration follow the solar cycle but lags behind b 3monhs for cycle 24. However, the CME acceleration does not follow the solar cycle. CME distribution show that Slow CMEs increases in initial speed from one cycle to the other with a corresponding decrease in acceleration for CMEs with fast speeds. There is an almost insignificant increase in acceleration for CMEs with positive and negative acceleration. These charges are perhaps due to effect of solar wind.

Impacts of CMEs on Earth Based on Logistic Regression and Recommendation Algorithm

Coronal mass ejections (CMEs) are one of the major disturbance sources of space weather. Therefore, it is of great significance to determine whether CMEs will reach the earth. Utilizing the method of logistic regression, we first calculate and analyze the correlation coefficients of the characteristic parameters of CMEs. These parameters include central position angle, angular width, and linear velocity, which are derived from the Large Angle and Spectrometric Coronagraph (LASCO) images. We have developed a logistic regression model to predict whether a CME will reach the earth, and the model yields an F1 score of 30% and a recall of 53%. Besides, for each CME, we use the recommendation algorithm to single out the most similar historical event, which can be a reference to forecast CMEs geoeffectiveness forecasting and for comparative analysis.

An Insight into the Coupling of CME Kinematics in Inner and Outer Corona and the Imprint of Source Regions

Abstract Despite studying coronal mass ejections (CMEs) for several years, we do not yet have a complete understanding of their kinematics. To this end, it is essential to understand the change in kinematics of the CMEs as they travel from the inner corona (<3 R ⊙) up to the higher heights of the outer corona. We conduct a follow-up statistical study of several 3D kinematic parameters of 59 CMEs previously studied by Majumdar et al. (2020). The source regions of these CMEs are identified and classified as active regions (ARs), active prominences (APs), or prominence eruptions (PEs). We study several statistical correlations between different kinematic parameters of the CMEs. We show that the CMEs’ average kinematic parameters change as they propagate from the inner to the outer corona, indicating the importance of a region where the common practice is to perform averaging. We also find that the CME parameters in the outer corona are highly influenced by those in the inner corona, indicating the importance of the inner corona in the understanding of the kinematics. Furthermore, we find that the source regions of the CMEs tend to have a distinct imprint on the statistical correlations between different kinematic parameters, and that an overall correlation tends to wash away this crucial information. The results of this work supports the possibility of different dynamical classes for the CMEs from ARs and prominences, which gets manifested in their kinematics.

Numerical Research on the Effect of the Initial Parameters of a CME Flux-rope Model on Simulation Results. II. Different Locations of Observers

Abstract In numerical studies of the initiation and propagation of coronal mass ejections (CMEs), it has been proven that the shape, size, and plasma parameters of CMEs could significantly affect simulation results and subsequent space weather predictions. In our previous research, we proposed a new way to initiate a CME based on the graduated cylindrical shell model, and studied the effect of different initial parameters of CMEs on the simulation results when the observer is aligned with the initial propagation direction of the CME. In this paper, we investigate the influence of the different initial parameters of CMEs on simulation results at the observational points with different longitudes and latitudes. Our results indicate that as long as the initial mass of the CME remains unchanged, the initial geometric thickness will have a different influence in the latitudinal and longitudinal directions. The deflection of the CMEs always occurs in both latitudinal and longitudinal directions, when the CMEs interact with the background solar wind structures, such as the corotating interaction region, in the heliosphere.

Use of the DBM Model to the Predict of Arrival of Coronal Mass Ejections to the Earth

This paper analyzes the results of modeling coronal mass ejection (CME) propagation in 2010–2011 obtained using input data from different sources: CME catalogs SEEDS and CACTus, and predictions of the velocity of quasi-stationary solar wind fluxes, as an environment, through which CMEs propagate. As the model of quasi-stationary solar wind fluxes, the model for predicting the velocity of the solar wind of the Space Weather Forecast Center of the Skobeltsyn Institute of Nuclear Physics of Moscow State University, operating online, is used. The CME prediction is carried out using the Simple Drag-Based Model. A comparison was performed between the ICME arrival time and their velocities obtained when modeling with data from the open ICME catalogs: the Richardson and Cane ICME catalog and the GMU CME List. Based on the comparison, it was concluded that a more accurate prediction for the growth phase of the 24th solar activity cycle was obtained using data on CME parameters from the CACTus database. The obtained errors in predicting the ICME parameters are comparable with the errors of other existing models.

Probabilistic Drag-Based Ensemble Model (DBEM) Evaluation for Heliospheric Propagation of CMEs

The Drag-based Model (DBM) is a 2D analytical model for heliospheric propagation of Coronal Mass Ejections (CMEs) in ecliptic plane predicting the CME arrival time and speed at Earth or any other given target in the solar system. It is based on the equation of motion and depends on initial CME parameters, background solar wind speed, \(w\) and the drag parameter \(\gamma \). A very short computational time of DBM (< 0.01 s) allowed us to develop the Drag-Based Ensemble Model (DBEM) that takes into account the variability of model input parameters by making an ensemble of n different input parameters to calculate the distribution and significance of the DBM results. Thus the DBEM is able to calculate the most likely CME arrival times and speeds, quantify the prediction uncertainties and determine the confidence intervals. A new DBEMv3 version is described in detail and evaluated for the first time determining the DBEMv3 performance and errors by using various CME–ICME lists and it is compared with previous DBEM versions, ICME being a short-hand for interplanetary CME. The analysis to find the optimal drag parameter \(\gamma \) and ambient solar wind speed \(w\) showed that somewhat higher values (\(\gamma \approx 0.3 \times 10^{-7}\) km−1, \(w \approx \) 425 km s−1) for both of these DBEM input parameters should be used for the evaluation than the previously employed ones. Based on the evaluation performed for 146 CME–ICME pairs, the DBEMv3 performance with mean error (ME) of −11.3 h, mean absolute error (MAE) of 17.3 h was obtained. There is a clear bias towards the negative prediction errors where the fast CMEs are predicted to arrive too early, probably due to the model physical limitations and input errors (e.g. CME launch speed). This can be partially reduced by using larger values for \(\gamma \) resulting in smaller prediction errors (\(\mathrm{ME} =-3.9\) h, MAE = 14.5 h) but at the cost of larger prediction errors for single fast CMEs as well as larger CME arrival speed prediction errors. DBEMv3 showed also slight improvement in the performance for all calculated output parameters compared to the previous DBEM versions.

Relationship between solar energetic particle intensities and coronal mass ejection kinematics using STEREO/SECCHI field of view

Solar energetic particles (SEPs) accelerated from shocks driven by coronal mass ejections (CMEs) are one of the major causes of geomagnetic storms on Earth. Therefore, it is necessary to predict the occurrence and intensity of such disturbances. For this purpose we analyzed in detail 38 non-interacting halo and partial halo CMEs, as seen by the Solar and Heliospheric Observatory/Large Angle and Spectrometric Coronagraph, generating SEPs (in &gt; 10 MeV, &gt; 50 MeV, and &gt; 100 MeV energy channels) during the quadrature configuration of the Solar TErrestrial RElations Observatory (STEREO) twin spacecrafts with respect to the Earth, which marks the ascending phase of solar cycle 24 (i.e., 2009–2013). The main criteria for this selection period is to obtain height–time measurements of the CMEs without significant projection effects and in a very large field of view. Using the data from STEREO/Sun Earth Connection Coronal and Heliospheric Investigation (STEREO/SECCHI) images we determined several kinematic parameters and instantaneous speeds of the CMEs. First, we compare instantaneous CME speed and Mach number versus SEP fluxes for events originating at the western and eastern limb; we observe high correlation for the western events and anticorrelation for the eastern events. Of the two parameters, the Mach number offers higher correlation. Next we investigated instantaneous CME kinematic parameters such as maximum speed, maximum Mach number, and the CME speed and Mach number at SEP peak flux versus SEP peak fluxes. Highly positive correlation is observed for Mach number at SEP peak flux for all events. The obtained instantaneous Mach number parameters from the emperical models was verified with the start and end time of type II radio bursts, which are signatures of CME-driven shock in the interplanetary medium. Furthermore, we conducted estimates of delay in time and distance between CME, SEP, and shock parameters. We observe an increase in the delay in time and distance when SEPs reach peak flux with respect to CME onset as we move from the western to the eastern limb. Western limb events (longitude 60°) have the best connectivity and this decreases as we move towards the eastern limb. This variation is due to the magnetic connectivity from the Sun to the Earth, called the Parker spiral interplanetary magnetic field. Comparative studies of the considered energy channels of the SEPs also throw light on the reacceleration of suprathermal seed ions by CME-driven shocks that are pre-accelerated in the magnetic reconnection.