The importance of boundary evolution for solar-wind modelling

The solar wind is a continual outflow of plasma and magnetic field from the Sun's upper atmosphere-the corona-that expands to fills the solar system. Variability in the near-Earth solar-wind conditions can produce adverse space weather that impacts ground- and space-based technologies. Consequently, numerical fluid models of the solar wind are used to forecast conditions a few days ahead. The solar-wind inner-boundary conditions are supplied by models of the corona that are, in turn, constrained by observations of the photospheric magnetic field. While solar eruptions-coronal mass ejections (CMEs)-are treated as time-dependent structures, a single coronal "snapshot" is typically used to determine the ambient solar-wind for a complete model run. Thus, all available time-history information from previous coronal-model solutions is discarded and the solar wind is treated as a steady-state flow, unchanging in the rotating frame of the Sun. In this study, we use 1 year of daily-updated coronal-model solutions to comprehensively compare steady-state solar-wind modelling with a time-dependent method. We demonstrate, for the first time, how the SS approach can fundamentally misrepresent the accuracy of coronal models. We also attribute three key problems with current space-weather forecasting directly to the steady-state approach: (1) the seemingly paradoxical result that forecasts based on observations from 3-days previous are more accurate than forecasts based on the most recent observations; (2) high inconsistency, with forecasts for a given day jumping significantly as new observations become available, changing CME propagation times by up to 17 h; and (3) insufficient variability in the heliospheric magnetic field, which controls solar energetic particle propagation to Earth. The time-dependent approach is shown to alleviate all three issues. It provides a consistent, physical solution which more accurately represents the information present in the coronal models. By incorporating the time history in the solar wind along the Sun-Earth line, the time-dependent approach will provide improvements to forecasting CME propagation to Earth.

Advanced Methods for Analyzing in-Situ Observations of Magnetic Reconnection

There is ample evidence for magnetic reconnection in the solar system, but it is a nontrivial task to visualize, to determine the proper approaches and frames to study, and in turn to elucidate the physical processes at work in reconnection regions from in-situ measurements of plasma particles and electromagnetic fields. Here an overview is given of a variety of single- and multi-spacecraft data analysis techniques that are key to revealing the context of in-situ observations of magnetic reconnection in space and for detecting and analyzing the diffusion regions where ions and/or electrons are demagnetized. We focus on recent advances in the era of the Magnetospheric Multiscale mission, which has made electron-scale, multi-point measurements of magnetic reconnection in and around Earth's magnetosphere.

Global Driving of Auroral Precipitation: 1. Balance of Sources

The accurate determination of auroral precipitation in global models has remained a daunting and rather inexplicable obstacle. Understanding the calculation and balance of multiple sources that constitute the aurora, and their eventual conversion into ionospheric electrical conductance, is critical for improved prediction of space weather events. In this study, we present a semi-physical global modeling approach that characterizes contributions by four types of precipitation-monoenergetic, broadband, electron, and ion diffuse-to ionospheric electrodynamics. The model uses a combination of adiabatic kinetic theory and loss parameters derived from historical energy flux patterns to estimate auroral precipitation from magnetohydrodynamic (MHD) quantities. It then converts them into ionospheric conductance that is used to compute the ionospheric feedback to the magnetosphere. The model has been employed to simulate the 5-7 April 2010 Galaxy15 space weather event. Comparison of auroral fluxes show good agreement with observational data sets like NOAA-DMSP and OVATION Prime. The study shows a dominant contribution by electron diffuse precipitation, accounting for ∼74% of the auroral energy flux. However, contributions by monoenergetic and broadband sources dominate during times of active upstream solar conditions, providing for up to 61% of the total hemispheric power. The study also finds a greater role played by broadband precipitation in ionospheric electrodynamics which accounts for ∼31% of the Pedersen conductance.

Estimating the Transit Speed and Time of Arrival of Interplanetary Coronal Mass Ejections Using CME and Solar Flare Data

The dependence of Interplanetary Coronal Mass Ejections’ (ICMEs) transit speed on the corresponding Coronal Mass Ejections’ (CMEs) initial speed is investigated. It is shown that the transit speed and transit time depend not only on the CME’s initial speed, but also on the longitude of the solar source. The longitudinal dependence of the expected transit speeds and times are obtained from the analysis of 288 CMEs, associated with solar flares, observed from 1995 to 2020. A model, estimating the transit and maximum speeds, as well as the time of arrival of an ICME to Earth, based on the initial CME speed and the longitude of the associated solar flare has been created. It is shown that taking into account the longitude of the solar source in addition to the initial CME speed significantly improves the quality of the model, especially for events in the central part of the solar disk (E10°–W10°). The simplicity of the described model makes it accessible to a wide range of users and provides opportunities for further improvement as the statistics and the number of input parameters increase.

Explicit IMF B y -Dependence of Energetic Protons and the Ring Current

The most important parameter driving the solar wind-magnetosphere interaction is the southward (B z ) component of the interplanetary magnetic field (IMF). While the dawn-dusk (B y ) component of the IMF is also known to play an important role, its effects are usually assumed to be independent of its sign. Here we demonstrate for the first time a seasonally varying, explicit IMF B y -dependence of the ring current and Dst index. Using satellite observations and a global magnetohydrodynamic model coupled with a ring current model, we show that for a fixed level of solar wind driving the flux of energetic magnetospheric protons and the growth-rate of the ring current are greater for B y  < 0 (B y  > 0) than for B y  > 0 (B y  < 0) in Northern Hemisphere summer (winter). While the physical mechanism of this explicit B y -effect is not yet fully understood, our results suggest that IMF B y modulates magnetospheric convection and plasma transport in the inner magnetosphere.

How a Realistic Magnetosphere Alters the Polarizations of Surface, Fast Magnetosonic, and Alfvén Waves

System-scale magnetohydrodynamic (MHD) waves within Earth's magnetosphere are often understood theoretically using box models. While these have been highly instructive in understanding many fundamental features of the various wave modes present, they neglect the complexities of geospace such as the inhomogeneities and curvilinear geometries present. Here, we show global MHD simulations of resonant waves impulsively excited by a solar wind pressure pulse. Although many aspects of the surface, fast magnetosonic (cavity/waveguide), and Alfvén modes present agree with the box and axially symmetric dipole models, we find some predictions for large-scale waves are significantly altered in a realistic magnetosphere. The radial ordering of fast mode turning points and Alfvén resonant locations may be reversed even with monotonic wave speeds. Additional nodes along field lines that are not present in the displacement/velocity occur in both the perpendicular and compressional components of the magnetic field. Close to the magnetopause, the perpendicular oscillations of the magnetic field have the opposite handedness to the velocity. Finally, widely used detection techniques for standing waves, both across and along the field, can fail to identify their presence. We explain how all these features arise from the MHD equations when accounting for a non-uniform background field and propose modified methods that might be applied to spacecraft observations.

Magnetopause ripples going against the flow form azimuthally stationary surface waves

Surface waves process the turbulent disturbances which drive dynamics in many space, astrophysical and laboratory plasma systems, with the outer boundary of Earth’s magnetosphere, the magnetopause, providing an accessible environment to study them. Like waves on water, magnetopause surface waves are thought to travel in the direction of the driving solar wind, hence a paradigm in global magnetospheric dynamics of tailward propagation has been well-established. Here we show through multi-spacecraft observations, global simulations, and analytic theory that the lowest-frequency impulsively-excited magnetopause surface waves, with standing structure along the terrestrial magnetic field, propagate against the flow outside the boundary. Across a wide local time range (09–15h) the waves’ Poynting flux exactly balances the flow’s advective effect, leading to no net energy flux and thus stationary structure across the field also. Further down the equatorial flanks, however, advection dominates hence the waves travel downtail, seeding fluctuations at the resonant frequency which subsequently grow in amplitude via the Kelvin-Helmholtz instability and couple to magnetospheric body waves. This global response, contrary to the accepted paradigm, has implications on radiation belt, ionospheric, and auroral dynamics and potential applications to other dynamical systems.

The magnetopause surface waves (SW) that drive global plasma dynamics are thought, like waves on water, to travel with the driving solar wind. Here, the authors show that impulsively-excited SW, with standing structure along the geomagnetic field, are stationary by propagating against this flow.

Physics of Space Weather Phenomena: A Review

In the last few decades, solar activity has been diminishing, and so space weather studies need to be revisited with more attention. The physical processes involved in dealing with various space weather parameters have presented a challenge to the scientific community, with a threat of having a serious impact on modern society and humankind. In the present paper, we have reviewed various aspects of space weather and its present understanding. The Sun and the Earth are the two major elements of space weather, so the solar and the terrestrial perspectives are discussed in detail. A variety of space weather effects and their societal as well as anthropogenic aspects are discussed. The impact of space weather on the terrestrial climate is discussed briefly. A few tools (models) to explain the dynamical space environment and its effects, incorporating real-time data for forecasting space weather, are also summarized. The physical relation of the Earth’s changing climate with various long-term changes in the space environment have provided clues to the short-term/long-term changes. A summary and some unanswered questions are presented in the final section.

Joint Geoeffectiveness and Arrival Time Prediction of CMEs by a Unified Deep Learning Framework

Fast and accurate prediction of the geoeffectiveness of coronal mass ejections (CMEs) and the arrival time of the geoeffective CMEs is urgent, to reduce the harm caused by CMEs. In this paper, we present a new deep learning framework based on time series of satellites’ optical observations that can give both the geoeffectiveness and the arrival time prediction of the CME events. It is the first time combining these two demands in a unified deep learning framework with no requirement of manually feature selection and get results immediately. The only input of the deep learning framework is the time series images from synchronized solar white-light and EUV observations. Our framework first uses the deep residual network embedded with the attention mechanism to extract feature maps for each observation image, then fuses the feature map of each image by the feature map fusion module and determines the geoeffectiveness of CME events. For the geoeffective CME events, we further predict its arrival time by the deep residual regression network based on group convolution. In order to train and evaluate our proposed framework, we collect 2400 partial-/full-halo CME events and its corresponding images from 1996 to 2018. The F1 score and Accuracy of the geoeffectiveness prediction can reach 0.270% and 75.1%, respectively, and the mean absolute error of the arrival time prediction is only 5.8 h, which are both significantly better than well-known deep learning methods and can be comparable to, or even better than, the best performance of traditional methods.

Mesoscale Structures in Earth's Magnetotail Observed Using Energetic Neutral Atom Imaging

Mesoscale structures in Earth's magnetotail are a primary feature of particle transport to the inner magnetosphere during storms and substorms. We demonstrate that such structures can be observed in energetic neutral atom (ENA) data which can provide remote, global images of the magnetosphere. In particular, we present localized regions of increased ion temperatures that appear in equatorial ion temperature maps calculated from Two Wide-angle Imaging Neutral-atom Spectrometers (TWINS) ENA data. These regions are associated with a dipolarization front with bursty ion flows measured by Magnetospheric MultiScale (MMS) and are concurrent with substorm features observed in field aligned currents (FAC) from Active Magnetosphere and Planetary Electrodynamics Response Experiment measurements. We conduct a magnetohydrodynamics simulation of the same event and show simulated ion temperatures, ion flows, and FACs that agree with the measurements. However, the observed plasma heating is less intense in the simulated results than in the TWINS and MMS data, indicating that some heating processes may be missing from the model.

Assessing the Quality of Models of the Ambient Solar Wind

In this paper we present an assessment of the status of models of the global Solar Wind in the inner heliosphere. We limit our discussion to the class of models designed to provide solar wind forecasts, excluding those designed for the purpose of testing physical processes in idealized configurations. In addition, we limit our discussion to modeling of the 'ambient' wind in the absence of coronal mass ejections. In this assessment we cover use of the models both in forecast mode and as tools for scientific research. We present a brief history of the development of these models, discussing the range of physical approximations in use. We discuss the limitations of the data inputs available to these models and its impact on their quality. We also discuss current model development trends.

Probabilistic Solar Wind Forecasting Using Large Ensembles of Near-Sun Conditions With a Simple One-Dimensional "Upwind" Scheme

Long lead-time space-weather forecasting requires accurate prediction of the near-Earth solar wind. The current state of the art uses a coronal model to extrapolate the observed photospheric magnetic field to the upper corona, where it is related to solar wind speed through empirical relations. These near-Sun solar wind and magnetic field conditions provide the inner boundary condition to three-dimensional numerical magnetohydrodynamic (MHD) models of the heliosphere out to 1 AU. This physics-based approach can capture dynamic processes within the solar wind, which affect the resulting conditions in near-Earth space. However, this deterministic approach lacks a quantification of forecast uncertainty. Here we describe a complementary method to exploit the near-Sun solar wind information produced by coronal models and provide a quantitative estimate of forecast uncertainty. By sampling the near-Sun solar wind speed at a range of latitudes about the sub-Earth point, we produce a large ensemble (N = 576) of time series at the base of the Sun-Earth line. Propagating these conditions to Earth by a three-dimensional MHD model would be computationally prohibitive; thus, a computationally efficient one-dimensional "upwind" scheme is used. The variance in the resulting near-Earth solar wind speed ensemble is shown to provide an accurate measure of the forecast uncertainty. Applying this technique over 1996-2016, the upwind ensemble is found to provide a more "actionable" forecast than a single deterministic forecast; potential economic value is increased for all operational scenarios, but particularly when false alarms are important (i.e., where the cost of taking mitigating action is relatively large).

Probabilistic Solar Wind and Geomagnetic Forecasting Using an Analogue Ensemble or "Similar Day" Approach

Effective space-weather prediction and mitigation requires accurate forecasting of near-Earth solar-wind conditions. Numerical magnetohydrodynamic models of the solar wind, driven by remote solar observations, are gaining skill at forecasting the large-scale solar-wind features that give rise to near-Earth variations over days and weeks. There remains a need for accurate short-term (hours to days) solar-wind forecasts, however. In this study we investigate the analogue ensemble (AnEn), or "similar day", approach that was developed for atmospheric weather forecasting. The central premise of the AnEn is that past variations that are analogous or similar to current conditions can be used to provide a good estimate of future variations. By considering an ensemble of past analogues, the AnEn forecast is inherently probabilistic and provides a measure of the forecast uncertainty. We show that forecasts of solar-wind speed can be improved by considering both speed and density when determining past analogues, whereas forecasts of the out-of-ecliptic magnetic field [ B N ] are improved by also considering the in-ecliptic magnetic-field components. In general, the best forecasts are found by considering only the previous 6 - 12 hours of observations. Using these parameters, the AnEn provides a valuable probabilistic forecast for solar-wind speed, density, and in-ecliptic magnetic field over lead times from a few hours to around four days. For B N , which is central to space-weather disturbance, the AnEn only provides a valuable forecast out to around six to seven hours. As the inherent predictability of this parameter is low, this is still likely a marked improvement over other forecast methods. We also investigate the use of the AnEn in forecasting geomagnetic indices Dst and Kp. The AnEn provides a valuable probabilistic forecast of both indices out to around four days. We outline a number of future improvements to AnEn forecasts of near-Earth solar-wind and geomagnetic conditions.

Tools and techniques for computational reproducibility

When reporting research findings, scientists document the steps they followed so that others can verify and build upon the research. When those steps have been described in sufficient detail that others can retrace the steps and obtain similar results, the research is said to be reproducible. Computers play a vital role in many research disciplines and present both opportunities and challenges for reproducibility. Computers can be programmed to execute analysis tasks, and those programs can be repeated and shared with others. The deterministic nature of most computer programs means that the same analysis tasks, applied to the same data, will often produce the same outputs. However, in practice, computational findings often cannot be reproduced because of complexities in how software is packaged, installed, and executed-and because of limitations associated with how scientists document analysis steps. Many tools and techniques are available to help overcome these challenges; here we describe seven such strategies. With a broad scientific audience in mind, we describe the strengths and limitations of each approach, as well as the circumstances under which each might be applied. No single strategy is sufficient for every scenario; thus we emphasize that it is often useful to combine approaches.

Ultraviolet and extreme ultraviolet spectroscopy of the solar corona at the Naval Research Laboratory

We review the history of ultraviolet and extreme ultraviolet spectroscopy with a specific focus on such activities at the Naval Research Laboratory and on studies of the extended solar corona and solar-wind source regions. We describe the problem of forecasting solar energetic particle events and discuss an observational technique designed to solve this problem by detecting supra-thermal seed particles as extended wings on spectral lines. Such seed particles are believed to be a necessary prerequisite for particle acceleration by heliospheric shock waves driven by a coronal mass ejection.

Assessing the role of oxygen on ring current formation and evolution through numerical experiments

Low O⁺/H⁺ ratio produced stronger ring currentInclusion of physics-based ionospheric outflow leads to a reduction in the CPCPOxygen presence is linked to a nightside reconnection point closer to the Earth.

Ensemble downscaling in coupled solar wind-magnetosphere modeling for space weather forecasting

Advanced forecasting of space weather requires simulation of the whole Sun-to-Earth system, which necessitates driving magnetospheric models with the outputs from solar wind models. This presents a fundamental difficulty, as the magnetosphere is sensitive to both large-scale solar wind structures, which can be captured by solar wind models, and small-scale solar wind "noise," which is far below typical solar wind model resolution and results primarily from stochastic processes. Following similar approaches in terrestrial climate modeling, we propose statistical "downscaling" of solar wind model results prior to their use as input to a magnetospheric model. As magnetospheric response can be highly nonlinear, this is preferable to downscaling the results of magnetospheric modeling. To demonstrate the benefit of this approach, we first approximate solar wind model output by smoothing solar wind observations with an 8 h filter, then add small-scale structure back in through the addition of random noise with the observed spectral characteristics. Here we use a very simple parameterization of noise based upon the observed probability distribution functions of solar wind parameters, but more sophisticated methods will be developed in the future. An ensemble of results from the simple downscaling scheme are tested using a model-independent method and shown to add value to the magnetospheric forecast, both improving the best estimate and quantifying the uncertainty. We suggest a number of features desirable in an operational solar wind downscaling scheme.

KEY POINTS

Solar wind models must be downscaled in order to drive magnetospheric models Ensemble downscaling is more effective than deterministic downscaling The magnetosphere responds nonlinearly to small-scale solar wind fluctuations.

An investigation of the magnetosphere–ionosphere response to real and idealized co-rotating interaction region events through global magnetohydrodynamic simulations

This study investigates the role of interplanetary magnetic field (IMF) B z fluctuations periodicity in the transfer of solar wind mass and energy to the magnetosphere during the co-rotating interaction region/high-speed stream event of 10 November 2003 through global modelling simulations using the space weather modelling framework. To do so, we used both solar wind observations and a variety of idealized inputs as upstream boundary conditions, describing different solar wind configurations for which relative contribution of the peak-to-noise ratio in the input B z power spectrum to the periodicity transfer is examined. Fast Fourier transforms of both input to and the response of the magnetosphere reveal that the transfer of IMF B z periodicity to the magnetosphere is unaltered by other solar wind parameters, although the size of the peak-to-noise ratio of the input signal is the controlling factor that determines this transfer. The global magnetosphere simulation suggests that a threshold amount of power (peak-to-noise ratio) of approximately 10 in the input signal is needed for the magnetosphere to react to the periodicity in the input B z , while for the cross-polar cap potential, the threshold amount is significantly smaller.

Coronal Holes

Coronal holes are the darkest and least active regions of the Sun, as observed both on the solar disk and above the solar limb. Coronal holes are associated with rapidly expanding open magnetic fields and the acceleration of the high-speed solar wind. This paper reviews measurements of the plasma properties in coronal holes and how these measurements are used to reveal details about the physical processes that heat the solar corona and accelerate the solar wind. It is still unknown to what extent the solar wind is fed by flux tubes that remain open (and are energized by footpoint-driven wave-like fluctuations), and to what extent much of the mass and energy is input intermittently from closed loops into the open-field regions. Evidence for both paradigms is summarized in this paper. Special emphasis is also given to spectroscopic and coronagraphic measurements that allow the highly dynamic non-equilibrium evolution of the plasma to be followed as the asymptotic conditions in interplanetary space are established in the extended corona. For example, the importance of kinetic plasma physics and turbulence in coronal holes has been affirmed by surprising measurements from the UVCS instrument on SOHO that heavy ions are heated to hundreds of times the temperatures of protons and electrons. These observations point to specific kinds of collisionless Alfvén wave damping (i.e., ion cyclotron resonance), but complete theoretical models do not yet exist. Despite our incomplete knowledge of the complex multi-scale plasma physics, however, much progress has been made toward the goal of understanding the mechanisms ultimately responsible for producing the observed properties of coronal holes.