The physical processes affecting the dynamics of the Earth's particle radiation environment are reviewed along with scientific and engineering models developed for its description. The emphasis is on models that are either operational engineering models or R. Vainio ( ) R. Vainio et al. models presently under development for this purpose. Three components of the radiation environment, i.e., galactic cosmic rays (GCRs), solar energetic particles (SEPs) and trapped radiation, are considered separately. In the case of SEP models, we make a distinction between statistical flux/fluence models and those aimed at forecasting events. Models of the effects of particle radiation on the atmosphere are also reviewed. Further, we summarize the main features of the models and discuss the main outstanding issues concerning the models and their possible use in operational space weather forecasting. We emphasize the need for continuing the development of physics-based models of the Earth's particle radiation environment, and their validation with observational data, until the models are ready to be used for nowcasting and/or forecasting the dynamics of the environment.
We have developed a technique to provide short‐term warnings of solar energetic proton (SEP) events that meet or exceed the Space Weather Prediction Center threshold of J (>10 MeV) = 10 pr cm−2 s−1 sr−1. The method is based on flare location, flare size, and evidence of particle acceleration/escape as parameterized by flare longitude, time‐integrated soft X‐ray intensity, and time‐integrated intensity of type III radio emission at ∼1 MHz, respectively. In this technique, warnings are issued 10 min after the maximum of ≥M2 soft X‐ray flares. For the solar cycle 23 (1995–2005) data on which it was developed, the method has a probability of detection of 63% (47/75), a false alarm rate of 42% (34/81), and a median warning time of ∼55 min for the 19 events successfully predicted by our technique for which SEP event onset times were provided by Posner (2007). These measures meet or exceed verification results for competing automated SEP warning techniques but, at the present stage of space weather forecasting, fall well short of those achieved with a human (aided by techniques such as ours) making the ultimate yes/no SEP event prediction. We give some suggestions as to how our method could be improved and provide our flare and SEP event database in the auxiliary material to facilitate quantitative comparisons with techniques developed in the future.
In this work, we present a case study of the relevant timescales responsible for coupling between the changes of the solar wind and interplanetary magnetic field (IMF) conditions and the magnetospheric dynamics during the St. Patrick's Day Geomagnetic Storms in 2013 and 2015. We investigate the behavior of the interplanetary magnetic field (IMF) component Bz, the Perreault‐Akasofu coupling function and the AE, AL, AU, SYM‐H, and ASY‐H geomagnetic indices at different timescales by using the empirical mode decomposition (EMD) method and the delayed mutual information (DMI). The EMD, indeed, allows to extract the intrinsic oscillations (modes) present into the different data sets, while the DMI, which provides a measure of the total amount of the linear and nonlinear shared information (correlation degree), allows to investigate the relevance of the different timescales in the solar wind‐magnetosphere coupling. The results clearly indicate the existence of a relevant timescale separation in the solar wind‐magnetosphere coupling. Indeed, while fluctuations at long timescales (τ > 200 min) show a large degree of correlation between solar wind parameters and magnetospheric dynamics proxies, at short timescales (τ < 200 min) this direct link is missing. This result suggests that fluctuations at timescales lower than 200 min, although triggered by changes of the interplanetary conditions, are mainly dominated by internal processes and are not directly driven by solar wind/IMF. Conversely, the magnetospheric dynamics in response to the solar wind/IMF driver at timescales longer than 200 min resembles the changes observed in the solar wind/IMF features. Finally, these results can be useful for Space Weather forecasting.
Approximately half of the large-scale coronal waves identified in images obtained by the Extreme-Ultraviolet Imaging Telescope (EIT) on the Solar and Heliospheric Observatory from 1997 March to 1998 June were associated with small solar flares with soft X-ray intensities below C class. The probability of a given flare of this intensity having an associated EIT wave is low. For example, of $8,000 B-class flares occurring during this 15 month period, only $1% were linked to EIT waves. These results indicate the need for a special condition that distinguishes flares with EIT waves from the vast majority of flares that lack wave association. Various lines of evidence, including the fact that EIT waves have recently been shown to be highly associated with coronal mass ejections (CMEs), suggest that this special condition is a CME. A CME is not a sufficient condition for a detectable EIT wave, however, because we calculate that $5 times as many front-side CMEs as EIT waves occurred during this period, after taking the various visibility factors for both phenomena into account. In general, EIT wave association increases with CME speed and width.
The ESA-JAXA BepiColombo mission will provide simultaneous measurements from two spacecraft, offering an unprecedented opportunity to investigate magnetospheric The BepiColombo mission to Mercury Edited by Johannes Benkhoff, Go Murakami and Ayako Matsuoka B A. Milillo
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.