Distribution and clustering of fast coronal mass ejections

Abstract

[1] The purpose of this paper is to investigate the statistical properties of high-speed coronal mass ejections (fast CMEs), which play a major role in Space Weather. We study the cumulative distribution of the initial CME speeds applying a new, advanced statistical method based on the scaling properties of averages of maximal speeds selected in time intervals of fixed sizes. This method allows us for the first time to obtain a systematic statistical description of the fast CME speeds. Using this method, we identify a self-similar (power law) high-speed portion of the spectrum of the speed maxima in the range of speeds from about 700 km/s to 2000 km/s. This self-similar range of the speed distribution provides a meaningful definition of "the fast" CMEs and indicates that these CMEs are produced by a process that is the same across the range of scales. The investigation of the temporal behavior of the fast CME events indicates that the time intervals between fast CMEs are not independent, i.e., fast CMEs arrive in clusters. We characterize the fast CMEs clustering by the exponent called the extremal index, which is the inverse of the averaged number of CMEs per cluster. An independent correlation analysis of the tail of the CME distribution confirms and further quantifies the temporal dependence among the fast CME events. To illustrate the predictive capabilities of the method, we identify clusters in the time series of CMEs with speeds greater than 1000 km/s and calculate their statistical characteristics such as the size and duration of the clusters. The method used in this paper can be applied to many other extreme geophysical events.

Extreme Value Analysis of Solar Flare Events

“…EVT has been previously used to model a range of natural phenomena such as extreme wind speeds (Fawcett & Walshaw, ), extreme droughts, and flooding (Canfield et al, ; Katz et al, ) and has even been used for public health and the prediction of extreme outbreaks of pneumonia and influenza (Thomas et al, ). In the area of space weather, EVT has been used to estimate the disturbance storm time ( D s t ) index (Silrergleit, ; Tsubouchi & Omura, ), the daily A a index (Silbergleit, ), speeds of fast coronal mass ejections (Ruzmaikin et al, ), the magnetic index A p (Koons, ), energetic electron fluxes (Koons, ; O'Brien et al, ), relativistic electron fluxes (Meredith et al, ), and the millennial sunspot number series (Acero et al, ). Lastly, EVT has been recently used to estimate Carrington‐like solar flares (Elvidge & Angling, ).…”

“…Of particular interest is the study of the tail of the distribution of the magnitude of solar flares, which describes the occurrence of extreme events such as the Carrington event of 1859 (Carrington, 1859). In the past, it was assumed that the tail of the distribution of flare strengths x follows a power law (Lu & Hamilton, 1991;Riley, 2012); that is, P(X > x) ∝ x −a , or a lognormal distribution Riley & Love, 2017); however, it is suggested that a power law distribution runs the risk of overpredicting extreme events and their occurrence (Roodman, 2015). In addition, in Riley (2012), mathematical and numerical discrepancies have been noted (Parrott, 2012a(Parrott, , 2012bRoodman, 2015), the confidence intervals (CIs) of the predictions are not reported , and fits of straight lines on curved distributions may overestimate the predicted risks as straight lines can be good approximations locally but cannot be accurately used for extrapolating to extremes.…”

Intense solar near‐relativistic electron events at 0.3 AU

“…[2] Major solar energetic particle (SEP) events are generally associated with intense episodes of solar activity when one or more active regions on the Sun produce a series of coronal mass ejections (CMEs) [e.g., Lario et al, 2005;Jiggens and Gabriel, 2009;Ruzmaikin et al, 2011]. Kallenrode and Cliver [2001a] studied the most intense SEP events of the last solar cycles.…”

The Economic Impact of Space Weather: Where Do We Stand?

“…(71,72) However, there is some evidence for clustering of CME eruptions. (57) Although there is a growing realization that vulnerability arises not simply due to low-frequency and high-impact events, but also due to continuing degradation as a consequence of many smaller impacts, (18) understanding the most severe event that might occur is crucial for disaster planning scenarios. (73) The largest solar flare ever recorded in satellite data was on November 4, 2003 (see Table II).…”

“…All relevant space weather phenomena--solar flare intensity, (54)(55)(56) CME speeds, (55,57) and geomagnetic storm strength (55,58) --typically follow powerlaw distributions. (59) Most studies therefore focus on the study of tail indices, although more complex statistical models have also been developed.…”