Understanding shock dynamics in the inner heliosphere with modeling and type II radio data: A statistical study

We study two methods of predicting interplanetary shock location and strength in the inner heliosphere: (1) the ENLIL simulation and (2) the kilometric type II (kmTII) prediction. To evaluate differences in the performance of the first method, we apply two sets of coronal mass ejections (CME) parameters from the cone-model fitting and flux-rope (FR) model fitting as input to the ENLIL model for 16 halo CMEs. The results show that the ENLIL model using the actual CME speeds from FR-fit provided an improved shock arrival time (SAT) prediction. The mean prediction errors for the FR and cone-model inputs are 4.90±5.92 h and 5.48±6.11 h, respectively. A deviation of 100 km s−1 from the actual CME speed has resulted in a SAT error of 3.46 h on average. The simulations show that the shock dynamics in the inner heliosphere agrees with the drag-based model. The shock acceleration can be divided as two phases: a faster deceleration phase within 50 Rs and a slower deceleration phase at distances beyond 50 Rs. The linear-fit deceleration in phase 1 is about 1 order of magnitude larger than that in phase 2. When applying the kmTII method to 14 DH-km CMEs, we found that combining the kmTII method with the ENLIL outputs improved the kmTII prediction. Due to a better modeling of plasma density upstream of shocks and the kmTII location, we are able to provide a more accurate shock time-distance and speed profiles. The mean kmTII prediction error using the ENLIL model density is 6.7±6.4 h; it is 8.4±10.4 h when the average solar wind plasma density is used. Applying the ENLIL density has reduced the mean kmTII prediction error by ∼2 h and the standard deviation by 4.0 h. Especially when we applied the combined approach to two interacting events, the kmTII prediction error was drastically reduced from 29.6 h to −4.9 h in one case and 10.6 h to 4.2 h in the other. Furthermore, the results derived from the kmTII method and the ENLIL simulation, together with white-light data, provide a valuable validation of shock formation location and strength. Such information has important implications for solar energetic particle acceleration.Fil: Xie, H.. NASA. Goddard Space Flight Center; Estados Unidos. Department of Physics. Catholic University of America; Estados UnidosFil: St. Cyr, O.C.. NASA. Goddard Space Flight Center; Estados UnidosFil: Gopalswamy, N.. NASA. Goddard Space Flight Center; Estados UnidosFil: Odstrcil, D.. George Mason University. Department of Computational and Data Sciences; Estados UnidosFil: Cremades Fernandez, Maria Hebe. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Tecnológica Nacional. Facultad Regional de Mendoza; Argentin

An Asymmetric Cone Model for Halo Coronal Mass Ejections

Due to projection effects, coronagraphic observations cannot uniquely determine parameters relevant to the geoeffectiveness of CMEs, such as the true propagation speed, width, or source location. The Cone Model for Coronal Mass Ejections (CMEs) has been studied in this respect and it could be used to obtain these parameters. There are evidences that some CMEs initiate from a flux-rope topology. It seems that these CMEs should be elongated along the flux-rope axis and the cross section of the cone base should be rather elliptical than circular. In the present paper we applied an asymmetric cone model to get the real space parameters of frontsided halo CMEs (HCMEs) recorded by SOHO/LASCO coronagraphs in 2002. The cone model parameters are generated through a fitting procedure to the projected speeds measured at different position angles on the plane of the sky. We consider models with the apex of the cone located at the center and surface of the Sun. The results are compared to the standard symmetric cone model

Solar Flares and Coronal Mass Ejections: A Statistically Determined Flare Flux-CME Mass Correlation

In an effort to examine the relationship between flare flux and corresponding CME mass, we temporally and spatially correlate all X-ray flares and CMEs in the LASCO and GOES archives from 1996 to 2006. We cross-reference 6,733 CMEs having well-measured masses against 12,050 X-ray flares having position information as determined from their optical counterparts. For a given flare, we search in time for CMEs which occur 10-80 minutes afterward, and we further require the flare and CME to occur within +/-45 degrees in position angle on the solar disk. There are 826 CME/flare pairs which fit these criteria. Comparing the flare fluxes with CME masses of these paired events, we find CME mass increases with flare flux, following an approximately log-linear, broken relationship: in the limit of lower flare fluxes, log(CME mass)~0.68*log(flare flux), and in the limit of higher flare fluxes, log(CME mass)~0.33*log(flare flux). We show that this broken power-law, and in particular the flatter slope at higher flare fluxes, may be due to an observational bias against CMEs associated with the most energetic flares: halo CMEs. Correcting for this bias yields a single power-law relationship of the form log(CME mass)~0.70*log(flare flux). This function describes the relationship between CME mass and flare flux over at least 3 dex in flare flux, from ~10^-7 to 10^-4 W m^-2.Comment: 28 pages, 16 figures, accepted to Solar Physic

From Predicting Solar Activity to Forecasting Space Weather: Practical Examples of Research-to-Operations and Operations-to-Research

The successful transition of research to operations (R2O) and operations to research (O2R) requires, above all, interaction between the two communities. We explore the role that close interaction and ongoing communication played in the successful fielding of three separate developments: an observation platform, a numerical model, and a visualization and specification tool. Additionally, we will examine how these three pieces came together to revolutionize interplanetary coronal mass ejection (ICME) arrival forecasts. A discussion of the importance of education and training in ensuring a positive outcome from R2O activity follows. We describe efforts by the meteorological community to make research results more accessible to forecasters and the applicability of these efforts to the transfer of space-weather research.We end with a forecaster "wish list" for R2O transitions. Ongoing, two-way communication between the research and operations communities is the thread connecting it all.Comment: 18 pages, 3 figures, Solar Physics in pres

Space Weather Application Using Projected Velocity Asymmetry of Halo CMEs

Halo coronal mass ejections (HCMEs) originating from regions close to the center of the Sun are likely to be responsible for severe geomagnetic storms. It is important to predict geo-effectiveness of HCMEs using observations when they are still near the Sun. Unfortunately, coronagraphic observations do not provide true speeds of CMEs due to the projection effects. In the present paper, we present a new technique allowing estimate the space speed and approximate source location using projected speeds measured at different position angles for a given HCME (velocity asymmetry). We apply this technique to HCMEs observed during 2001-2002 and find that the improved speeds are better correlated with the travel times of HCMEs to Earth and with the magnitudes ensuing geomagnetic storms.Comment: accepted for [publication in Solar Physic

Machine learning-based investigation of the association between CMEs and filaments

YesIn this work we study the association between eruptive filaments/prominences and coronal mass ejections (CMEs) using machine learning-based algorithms that analyse the solar data available between January 1996 and December 2001. The Support Vector Machine (SVM) learning algorithm is used for the purpose of knowledge extraction from the association results. The aim is to identify patterns of associations that can be represented using SVM learning rules for the subsequent use in near real-time and reliable CME prediction systems. Timing and location data in the NGDC filament catalogue and the SOHO/LASCO CME catalogue are processed to associate filaments with CMEs. In the previous studies which classified CMEs into gradual and impulsive CMEs, the associations were refined based on CME speed and acceleration. Then the associated pairs were refined manually to increase the accuracy of the training dataset. In the current study, a data- mining system has been created to process and associate filament and CME data, which are arranged in numerical training vectors. Then the data are fed to SVMs to extract the embedded knowledge and provide the learning rules that could have the potential, in the future, to provide automated predictions of CMEs. The features representing the event time (average of the start and end times), duration, type and extent of the filaments are extracted from all the associated and not-associated filaments and converted to a numerical format that is suitable for SVM use. Several validation and verification methods are used on the extracted dataset to determine if CMEs can be predicted solely and efficiently based on the associated filaments. More than 14000 experiments are carried out to optimise the SVM and determine the input features that provide the best performance

Prediction Space Weather Using an Asymmetric Cone Model for Halo CMEs

Halo coronal mass ejections (HCMEs) are responsible of the most severe geomagnetic storms. A prediction of their geoeffectiveness and travel time to Earth's vicinity is crucial to forecast space weather. Unfortunately coronagraphic observations are subjected to projection effects and do not provide true characteristics of CMEs. Recently, Michalek (2006, {\it Solar Phys.}, {\bf237}, 101) developed an asymmetric cone model to obtain the space speed, width and source location of HCMEs. We applied this technique to obtain the parameters of all front-sided HCMEs observed by the SOHO/LASCO experiment during a period from the beginning of 2001 until the end of 2002 (solar cycle 23). These parameters were applied for the space weather forecast. Our study determined that the space speeds are strongly correlated with the travel times of HCMEs within Earth's vicinity and with the magnitudes related to geomagnetic disturbances

4pi Models of CMEs and ICMEs

Coronal mass ejections (CMEs), which dynamically connect the solar surface to the far reaches of interplanetary space, represent a major anifestation of solar activity. They are not only of principal interest but also play a pivotal role in the context of space weather predictions. The steady improvement of both numerical methods and computational resources during recent years has allowed for the creation of increasingly realistic models of interplanetary CMEs (ICMEs), which can now be compared to high-quality observational data from various space-bound missions. This review discusses existing models of CMEs, characterizing them by scientific aim and scope, CME initiation method, and physical effects included, thereby stressing the importance of fully 3-D ('4pi') spatial coverage.Comment: 14 pages plus references. Comments welcome. Accepted for publication in Solar Physics (SUN-360 topical issue