Forecasting Solar Energetic Particle Events and Associated False Alarms

Because of the significant dangers they pose, accurate forecasting of Solar Energetic Particle (SEP) events is vital. Whilst it has long been known that SEP-production is associated with high-energy solar events, forecasting algorithms based upon the observation of these types of solar event suffer from high false alarm rates. Here we analyse the parameters of 4 very high energy solar events which were false alarms, with a view to reaching an understanding as to why SEPs were not detected at Earth. We find that in each case at least two factors were present which have been shown to be detrimental to SEP productio

The reported durations of GOES Soft X-Ray flares in different solar cycles

The Geostationary Orbital Environmental Satellites (GOES) Soft X-ray (SXR) sensors have provided data relating to, inter alia, the time, intensity and duration of solar flares since the 1970s. The GOES SXR Flare List has become the standard reference catalogue for solar flares and is widely used in solar physics research and space weather. We report here that in the cur- rent version of the list there are significant differences between the mean du- ration of flares which occurred before May 1997 and the mean duration of flares thereafter. Our analysis shows that the reported flare timings for the pre-May 1997 data were not based on the same criteria as is currently the case. This finding has serious implications for all those who used flare duration (or fluence, which depends on the chosen start and end times) as part of their analysis of pre-May 1997 solar events, or statistical analyses of large sam- ples of flares, e.g. as part of the assessment of a Solar Energetic Particle fore- casting algorithm

Review of solar energetic particle models

Solar Energetic Particle (SEP) events are interesting from a scientific perspective as they are the product of a broad set of physical processes from the corona out through the extent of the heliosphere, and provide insight into processes of particle acceleration and transport that are widely applicable in astrophysics. From the operations perspective, SEP events pose a radiation hazard for aviation, electronics in space, and human space exploration, in particular for missions outside of the Earth’s protective magnetosphere including to the Moon and Mars. Thus, it is critical to improve the scientific understanding of SEP events and use this understanding to develop and improve SEP forecasting capabilities to support operations. Many SEP models exist or are in development using a wide variety of approaches and with differing goals. These include computationally intensive physics-based models, fast and light empirical models, machine learning-based models, and mixed-model approaches. The aim of this paper is to summarize all of the SEP models currently developed in the scientific community, including a description of model approach, inputs and outputs, free parameters, and any published validations or comparisons with data.</p

Solar energetic particle forecasting algorithms and associated false alarms

Solar energetic particle (SEP) events are known to occur following solar ares and coronal mass ejections (CMEs). However some high-energy solar events do not result in SEPs being detected at Earth, and it is these types of event which may be termed \false alarms". We define two simple SEP forecasting algorithms based upon the occurrence of a magnetically well-connected CME with a speed in excess of 1500 km s-1 (\a fast CME") or a well-connected X-class are and analyse them with respect to historical data sets. We compare the parameters of those solar events which produced an enhancement of >40 MeV protons at Earth (\an SEP event") and the false alarms. We find that an SEP forecasting algorithm based solely upon the occurrence of a well-connected fast CME produces fewer false alarms (28.8%) than one based solely upon a well-connected X-class are (50.6%). Both algorithms fail to forecast a relatively high percentage of SEP events (53.2% and 50.6% respectively). Our analysis of the historical data sets shows that false alarm X-class ares were either not associated with any CME, or were associated with a CME slower than 500 km s-1; false alarm fast CMEs tended to be associated with ares of class less than M3. A better approach to forecasting would be an algorithm which takes as its base the occurrence of both CMEs and ares. We define a new forecasting algorithm which uses a combination of CME and are parameters and show that the false alarm ratio is similar to that for the algorithm based upon fast CMEs (29.6%), but the percentage of SEP events not forecast is reduced to 32.4%. Lists of the solar events which gave rise to >40 MeV protons and the false alarms have been derived and are made available to aid further study

Application of Test Particle Simulations to Solar Energetic Particle Forecasting

Modelling of Solar Energetic Particles (SEPs) is usually carried out by means of the 1D focused transport equation and the same approach is adopted within several SEP Space Weather forecasting frameworks. We present an alternative approach, based on test particle simulations, which naturally describes 3D particle propagation. The SPARX forecasting system is an example of how test particle simulations can be used in real time in a Space Weather context. SPARX is currently operational within the COMESEP Alert System. The performance of the system, which is triggered by detection of a solar flare of class >M1.0 is evaluated by comparing forecasts for flare events between 1997 and 2017 with actual SEP data from the GOES spacecraft

Review of Solar Energetic Particle Models

Solar Energetic Particles (SEP) events are interesting from a scientific perspective as they are the product of a broad set of physical processes from the corona out through the extent of the heliosphere, and provide insight into processes of particle acceleration and transport that are widely applicable in astrophysics. From the operations perspective, SEP events pose a radiation hazard for aviation, electronics in space, and human space exploration, in particular for missions outside of the Earth’s protective magnetosphere including to the Moon and Mars. Thus, it is critical to imific understanding of SEP events and use this understanding to develop and improve SEP forecasting capabilities to support operations. Many SEP models exist or are in development using a wide variety of approaches and with differing goals. These include computationally intensive physics-based models, fast and light empirical models, machine learning-based models, and mixed-model approaches. The aim of this paper is to summarize all of the SEP models currently developed in the scientific community, including a description of model approach, inputs and outputs, free parameters, and any published validations or comparisons with data