Forecasting GOES 15 >2 MeV Electron Fluxes From Solar Wind Data and Geomagnetic Indices

The flux of > 2 MeV electrons at geosynchronous orbit is used by space weather forecasters as a key indicator of enhanced risk of damage to spacecraft in low, medium or geosynchronous Earth orbits. We present a methodology that uses the amount of time a single input dataset (solar wind data or geomagnetic indices) exceeds a given threshold to produce deterministic and probabilistic forecasts of the > 2 MeV flux at GEO exceeding 1000 or 10000 cm ‐2 s ‐1 sr ‐1 within up to 10 days. By comparing our forecasts with measured fluxes from GOES 15 between 2014 and 2016, we determine the optimum forecast thresholds for deterministic and probabilistic forecasts by maximising the ROC and Brier Skill Scores respectively. The training dataset gives peak ROC scores of 0.71 to 0.87 and peak Brier Skill Scores of ‐0.03 to 0.32. Forecasts from AL give the highest skill scores for forecasts of up to 6‐days. AL, solar wind pressure or SYM‐H give the highest skill scores over 7‐10 days. Hit rates range over 56‐89% with false alarm rates of 11‐53%. Applied to 2012, 2013 and 2017, our best forecasts have hit rates of 56‐83% and false alarm rates of 10‐20%. Further tuning of the forecasts may improve these. Our hit rates are comparable to those from operational fluence forecasts, that incorporate fluence measurements, but our false alarm rates are higher. This proof‐of‐concept shows that the geosynchronous electron flux can be forecast with a degree of success without incorporating a persistence element into the forecasts

Variability of Quasilinear Diffusion Coefficients for Plasmaspheric Hiss

In the outer radiation belt, the acceleration and loss of high‐energy electrons is largely controlled by wave‐particle interactions. Quasilinear diffusion coefficients are an efficient way to capture the small‐scale physics of wave‐particle interactions due to magnetospheric wave modes such as plasmaspheric hiss. The strength of quasilinear diffusion coefficients as a function of energy and pitch angle depends on both wave parameters and plasma parameters such as ambient magnetic field strength, plasma number density, and composition. For plasmaspheric hiss in the magnetosphere, observations indicate large variations in the wave intensity and wave normal angle, but less is known about the simultaneous variability of the magnetic field and number density. We use in situ measurements from the Van Allen Probe mission to demonstrate the variability of selected factors that control the size and shape of pitch angle diffusion coefficients: wave intensity, magnetic field strength, and electron number density. We then compare with the variability of diffusion coefficients calculated individually from colocated and simultaneous groups of measurements. We show that the distribution of the plasmaspheric hiss diffusion coefficients is highly non‐Gaussian with large variance and that the distributions themselves vary strongly across the three phase space bins studied. In most bins studied, the plasmaspheric hiss diffusion coefficients tend to increase with geomagnetic activity, but our results indicate that new approaches that include natural variability may yield improved parameterizations. We suggest methods like stochastic parameterization of wave‐particle interactions could use variability information to improve modeling of the outer radiation belt

Attention-Based Machine Vision Models and Techniques for Solar Wind Speed Forecasting Using Solar EUV Images

Abstract: Extreme ultraviolet images taken by the Atmospheric Imaging Assembly on board the Solar Dynamics Observatory make it possible to use deep vision techniques to forecast solar wind speed—a difficult, high‐impact, and unsolved problem. At a 4 day time horizon, this study uses attention‐based models and a set of methodological improvements to deliver an 11.1% lower RMSE and a 17.4% higher prediction correlation compared to the previous work testing on the period from 2010 to 2018. Our analysis shows that attention‐based models combined with our pipeline consistently outperform convolutional alternatives. Our study shows a large performance improvement by using a 30 min as opposed to a daily sampling frequency. Our model has learned relationships between coronal holes' characteristics and the speed of their associated high‐speed streams, agreeing with empirical results. Our study finds a strong dependence of our best model on the phase of the solar cycle, with the best performance occurring in the declining phase

Attention-Based Machine Vision Models and Techniques for Solar Wind Speed Forecasting Using Solar EUV Images

Abstract: Extreme ultraviolet images taken by the Atmospheric Imaging Assembly on board the Solar Dynamics Observatory make it possible to use deep vision techniques to forecast solar wind speed—a difficult, high‐impact, and unsolved problem. At a 4 day time horizon, this study uses attention‐based models and a set of methodological improvements to deliver an 11.1% lower RMSE and a 17.4% higher prediction correlation compared to the previous work testing on the period from 2010 to 2018. Our analysis shows that attention‐based models combined with our pipeline consistently outperform convolutional alternatives. Our study shows a large performance improvement by using a 30 min as opposed to a daily sampling frequency. Our model has learned relationships between coronal holes' characteristics and the speed of their associated high‐speed streams, agreeing with empirical results. Our study finds a strong dependence of our best model on the phase of the solar cycle, with the best performance occurring in the declining phase

Quantifying the daily economic impact of extreme space weather due to failure in electricity transmission infrastructure

Extreme space weather due to coronal mass ejections has the potential to cause considerable disruption to the global economy by damaging the transformers required to operate electricity transmission infrastructure. However, expert opinion is split between the potential outcome being one of a temporary regional blackout and of a more prolonged event. The temporary blackout scenario proposed by some is expected to last the length of the disturbance, with normal operations resuming after a couple of days. On the other hand, others have predicted widespread equipment damage with blackout scenarios lasting months. In this paper we explore the potential costs associated with failure in the electricity transmission infrastructure in the U.S. due to extreme space weather, focusing on daily economic loss. This provides insight into the direct and indirect economic consequences of how an extreme space weather event may affect domestic production, as well as other nations, via supply chain linkages. By exploring the sensitivity of the blackout zone, we show that on average the direct economic cost incurred from disruption to electricity represents only 49% of the total potential macroeconomic cost. Therefore, if indirect supply chain costs are not considered when undertaking cost-benefit analysis of space weather forecasting and mitigation investment, the total potential macroeconomic cost is not correctly represented. The paper contributes to our understanding of the economic impact of space weather, as well as making a number of key methodological contributions relevant for future work. Further economic impact assessment of this threat must consider multiday, multiregional events.The authors acknowledge partial financial support from American International Group during the research and especially thank Brad Fischtrom, Siddhartha Dalal, and their team for providing useful comments and insights as the research progressed. We also thank attendees of the workshop held at the Cambridge Judge Business School in July 2015. Three anonymous reviewers are acknowledged for providing useful comments and feedback on the paper. Oughton was partially supported by the UK Engineering and Physical Science Research Council under grant EP/N017064/1: Multiscale InfraSTRucture systems AnaLytics. Horne and Thomson would like to acknowledge the support of the Natural Environment Research Council (NERC). This paper is published by permission of the Executive Director, British Geological Survey (NERC)

Modeling Inner Proton Belt Variability at Energies 1 to 10 MeV Using BAS-PRO

Abstract: Geomagnetically trapped protons forming Earth's proton radiation belt pose a hazard to orbiting spacecraft. In particular, solar cell degradation is caused by non‐ionising collisions with protons at energies of several megaelectron volts (MeV), which can shorten mission lifespan. Dynamic enhancements in trapped proton flux following solar energetic particle events have been observed to last several months, and there is a strong need for physics‐based modeling to predict the impact on spacecraft. However, modeling proton belt variability at this energy is challenging because radial diffusion coefficients are not well constrained. We address this by using the British Antarctic Survey proton belt model BAS‐PRO to perform 3D simulations of the proton belt in the region 1.15 ≤ L ≤ 2 from 2014 to 2018. The model is driven by measurements from the Radiation Belt Storm Probes Ion Composition Experiment and Magnetic Electron Ion Spectrometer instruments carried by the Van Allen Probe satellites. To investigate sensitivity, simulations are repeated for three different sets of proton radial diffusion coefficients D LL taken from previous literature. Comparing the time evolution of each result, we find that solar cycle variability can drive up to a ∼75% increase in 7.5 MeV flux at L = 1.3 over four years due to the increased importance of collisional loss at low energies. We also show how the anisotropy of proton pitch angle distributions varies with L and energy, depending on D LL . However we find that phase space density can vary by three orders of magnitude at L = 1.4 and μ = 20 MeV/G due to uncertainty in D LL , highlighting the need to better constrain proton D LL at low energy

Formation of electron radiation belts at Saturn by Z-mode wave acceleration

At Saturn electrons are trapped in the planet’s magnetic field and accelerated to relativistic energies to form the radiation belts, but how this dramatic increase in electron energy occurs is still unknown. Until now the mechanism of radial diffusion has been assumed but we show here that in-situ acceleration through wave particle interactions, which initial studies dismissed as ineffectual at Saturn, is in fact a vital part of the energetic particle dynamics there. We present evidence from numerical simulations based on Cassini spacecraft data that a particular plasma wave, known as Z-mode, accelerates electrons to MeV energies inside 4 RS (1 RS = 60,330 km) through a Doppler shifted cyclotron resonant interaction. Our results show that the Z-mode waves observed are not oblique as previously assumed and are much better accelerators than O-mode waves, resulting in an lectron energy spectrum that closely approaches observed values without any transport effects included

Adherence to treatment in children and adolescents with cystic fibrosis:a cross-sectional, multi-method study investigating the influence of beliefs about treatment and parental depressive symptoms

Background: Adherence to treatment is often reported to be low in children with cystic fibrosis. Adherence in cystic fibrosis is an important research area and more research is needed to better understand family barriers to adherence in order for clinicians to provide appropriate intervention. The aim of this study was to evaluate adherence to enzyme supplements, vitamins and chest physiotherapy in children with cystic fibrosis and to determine if any modifiable risk factors are associated with adherence. Methods: A sample of 100 children (≤18 years) with cystic fibrosis (44 male; median [range] 10.1 [0.2-18.6] years) and their parents were recruited to the study from the Northern Ireland Paediatric Cystic Fibrosis Centre. Adherence to enzyme supplements, vitamins and chest physiotherapy was assessed using a multi-method approach including; Medication Adherence Report Scale, pharmacy prescription refill data and general practitioner prescription issue data. Beliefs about treatments were assessed using refined versions of the Beliefs about Medicines Questionnaire-specific. Parental depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale. Results: Using the multi-method approach 72% of children were classified as low-adherers to enzyme supplements, 59% low-adherers to vitamins and 49% low-adherers to chest physiotherapy. Variations in adherence were observed between measurement methods, treatments and respondents. Parental necessity beliefs and child age were significant independent predictors of child adherence to enzyme supplements and chest physiotherapy, but parental depressive symptoms were not found to be predictive of adherence. Conclusions: Child age and parental beliefs about treatments should be taken into account by clinicians when addressing adherence at routine clinic appointments. Low adherence is more likely to occur in older children, whereas, better adherence to cystic fibrosis therapies is more likely in children whose parents strongly believe the treatments are necessary. The necessity of treatments should be reinforced regularly to both parents and children

Can asthma control be improved by understanding the patient's perspective?

Clinical trials show that asthma can be controlled in the majority of patients, but poorly controlled asthma still imposes a considerable burden. The level of asthma control achieved reflects the behaviour of both healthcare professionals and patients. A key challenge for healthcare professionals is to help patients to engage in self-management behaviours with optimal adherence to appropriate treatment. These issues are particularly relevant in primary care, where most asthma is managed. An international panel of experts invited by the International Primary Care Respiratory Group considered the evidence and discussed the implications for primary care practice

Observations of discrete harmonics emerging from equatorial noise

A number of modes of oscillations of particles and fields can exist in space plasmas. Since the early 1970s, space missions have observed noise-like plasma waves near the geomagnetic equator known as ‘equatorial noise’. Several theories were suggested, but clear observational evidence supported by realistic modelling has not been provided. Here we report on observations by the Cluster mission that clearly show the highly structured and periodic pattern of these waves. Very narrow-banded emissions at frequencies corresponding to exact multiples of the proton gyrofrequency (frequency of gyration around the field line) from the 17th up to the 30th harmonic are observed, indicating that these waves are generated by the proton distributions. Simultaneously with these coherent periodic structures in waves, the Cluster spacecraft observes ‘ring’ distributions of protons in velocity space that provide the free energy for the waves. Calculated wave growth based on ion distributions shows a very similar pattern to the observations