There is a growing appreciation that the environmental conditions that we call space weather impact the technological infrastructure that powers the coupled economies around the world. With that comes the need to better shield society against space weather by improving forecasts, environmental specifications, and infrastructure design. We recognize that much progress has been made and continues to be made with a powerful suite of research observatories on the ground and in space, forming the basis of a Sun-Earth system observatory. But the domain of space weather is vastextending from deep within the Sun to far outside the planetary orbits -and the physics complex -including couplings between various types of physical processes that link scales and domains from the microscopic to large parts of the solar system. Consequently, advanced understanding of space weather requires a coordinated international approach to effectively provide awareness of the processes within the Sun-Earth system through observation-driven models. This roadmap prioritizes the scientific focus areas and research infrastructure that are needed to significantly advance our understanding of space weather of all intensities and of its implications for society. Advancement of the existing system observatory through the addition of small to moderate state-of-the-art capabilities designed to fill observational gaps will enable significant advances. Such a strategy requires urgent action: key instrumentation needs to be sustained, and action needs to be taken before core capabilities are lost in the aging ensemble. We recommend advances through priority focus (1) on observation-based modeling throughout the Sun-Earth system, (2) on forecasts more than 12 hrs ahead of the magnetic structure of incoming coronal mass ejections, (3) on understanding the geospace response to variable solar-wind stresses that lead to intense geomagnetically-induced currents and ionospheric and radiation storms, and (4) on developing a comprehensive specification of space climate, including the characterization of extreme space storms to guide resilient and robust engineering of technological infrastructures. The roadmap clusters its implementation recommendations by formulating three action pathways, and outlines needed instrumentation and research programs and infrastructure for each of these. An executive summary provides an overview of all recommendations.

Presented is an analysis of the occurrence of postsunset Equatorial Plasma Bubbles (EPBs) detected using a Global Positioning System (GPS) receiver at Vanimo. The three year data set shows that the EPB occurrence maximizes (minimizes) during the equinoxes (solstices), in good agreement with previous findings. The Vanimo ionosonde station is used with the GPS receiver in an analysis of the day-to-day EPB occurrence variability during the 2000 equinox period. A superposed epoch analysis (SEA) reveals that the altitude, and the change in altitude, of the F layer height is ∼1 standard deviation (1 ) larger on the days for which EPBs were detected, compared to non-EPB days. These results are then compared to results from the Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM), which show strong similarities with the observations. The TIEGCM is used to calculate the flux-tube integrated Rayleigh-Taylor (R-T) instability linear growth rate. A SEA reveals that the modeled R-T growth rate is 1 higher on average for EPB days compared to non-EPB days, and that the upward plasma drift is the most dominant contributor. It is further demonstrated that the TIEGCM's success in describing the observed daily EPB variability during the scintillation season resides in the variations caused by geomagnetic activity (as parameterized by Kp) rather than solar EUV flux (as parameterized by F 10.7 ). Geomagnetic activity varies the modeled high-latitude plasma convection and the associated Joule heating that affects the low-latitude F region dynamo, and consequently the equatorial upward plasma drift.

Solar flares are extremely energetic phenomena in our Solar System. Their impulsive, often drastic radiative increases, in particular at short wavelengths, bring immediate impacts that motivate solar physics and space weather research to understand solar flares to the point of being able to forecast them. As data and algorithms improve dramatically, questions must be asked concerning how well the forecasting performs; crucially, we must ask how to rigorously measure performance in order to critically gauge any improvements. Building upon earlier-developed methodology (Barnes et al. 2016, Paper I), international representatives of regional warning centers and research facilities assembled in 2017 at the Institute for Space-Earth Environmental Research, Nagoya University, Japan to -for the first time -directly compare the performance of operational solar flare forecasting methods. Multiple quantitative evaluation metrics are employed, with focus and discussion on evaluation methodologies given the restrictions of operational forecasting. Numerous methods performed consistently above the "no skill" level, although which method scored top marks is decisively a function of flare event definition and the metric used; there was no single winner. Following in this paper series we ask why the performances differ by examining implementation details (Leka et al. 2019, Paper III), and then we present a novel analysis method to evaluate temporal patterns of forecasting errors in (Park et al. 2019, Paper IV). With these works, this team presents a well-defined and robust methodology for evaluating solar flare forecasting methods in both research and operational frameworks, and today's performance benchmarks against which improvements and new methods may be compared.

The feasibility of predicting the daily occurrence of Global Positioning System scintillation events using forecasts of common geophysical indices to drive a physics‐based model of the system is demonstrated over a 5 month period for the African and Asian longitude sectors. The output from the Wing Kp model, which uses solar wind data to predict the geomagnetic activity level up to 4 h in advance, was used to drive the National Center for Atmospheric Research thermosphere/ionosphere model, from which the strength of the Rayleigh‐Taylor instability growth rate was calculated to determine the likelihood of scintillation. It is found that the physics‐based model demonstrates superior skill to an empirical scintillation model (Wideband Model (WBMOD)) in forecasting scintillation suppression events during seasons when scintillation is common. However, neither of the models driven in this way possess the ability to forecast isolated scintillation events during transitional and off‐peak seasons.

to quantitatively compare the performance of today's operational solar flare forecasting facilities. Building upon Paper I of this series (Barnes et al. 2016), in Paper II (Leka et al. 2019 we described the participating methods for this latest comparison effort, the evaluation methodology, and presented quantitative comparisons. In this paper we focus on the behavior and performance of the methods when evaluated in the context of broad implementation differences. Acknowledging the short testing interval available and the small number of methods available, we do find that forecast performance: 1) appears to improve by including persistence or prior flare activity, region evolution, and a human "forecaster in the loop"; 2) is hurt by restricting data to disk-center observations; 3) may benefit from long-term statistics, but mostly when then combined with modern data sources and statistical approaches. These trends are arguably weak and must be viewed with numerous caveats, as discussed both here and in Paper II. Following this present work, we present in Paper IV a novel analysis method to evaluate temporal patterns of forecasting errors of both types (i.e., misses and false alarms; Park et al. 2019). Hence, most importantly, with this series of papers we demonstrate the techniques for facilitating comparisons in the interest of establishing performance-positive methodologies.