A. Chulaki’s research while affiliated with Catholic University of America and other places

Coronal mass ejections (CMEs) drive space weather effects at Earth and the heliosphere. Predicting their arrival is a major part of space weather forecasting. In 2013, the Community Coordinated Modeling Center started collecting predictions from the community, developing an Arrival Time Scoreboard (ATSB). Riley et al. (2018, https://doi.org/10.1029/2018sw001962) analyzed the first 5 years of the ATSB, finding a bias of a few hours and uncertainty of order 15 hr. These metrics have been routinely quoted since 2018, but have not been updated despite continued predictions. We revise analysis of the ATSB using a sample 3.5 times the size of that in the original study. We find generally the same overall metrics, a bias of −2.5 hr, mean absolute error of 13.2 hr, and standard deviation of 17.4 hr, with only a slight improvement comparing between the previously‐used and new sets. The most well‐established, frequently‐submitted model results tend to outperform those from seldomly‐contributed models. These “best” models show a slight improvement over the 11 year span, with more scatter between the models during early times and a convergence toward the same error metrics in recent years. We find little evidence of any correlations between the arrival time errors and any other properties. The one noticeable exception is a tendency for late predictions for short transit times and vice versa. We propose that any model‐driven systematic errors may be washed out by the uncertainties in CME reconstructions in characterization of the background solar wind, and suggest that improving these may be the key to better predictions.

Community Colleges provide a great opportunity to diversify the space sciences or other science, technology, engineering, and math (STEM) !elds due to their large population of underrepresented students. However, since the primary mission of community colleges is teaching, there is a challenge to support undergraduate research training and promote undergraduate research opportunities. Undergraduate research experiences are one of the leading high!impact practices (HIPs) to encourage students to pursue STEM majors, graduate degrees, and careers. Space weather provides the opportunity to engage undergraduate students in real!world research due to the accessibility of space mission data sets within open access data repositories. Space weather's impact on Earth's geospace environment, life, and society also provides a compelling real!world hook to engage students in activities that have a number of impacts including (1) long!term integration of space weather into the undergraduate curricula; (2) experience in analyzing large geospace data sets, which increases students' computational, critical thinking, and analytical skills, useful for any career; and (3) increase in students' interest in and motivation to study STEM, as well as preparing them for choosing a career path in space science and related !elds. The model presented below has the potential to increase the retention, graduation, and transfer rate of community college students to four!year STEM programs, as well as increase representation and inclusion in space sciences and other related STEM !elds.

We present a first-principles-based coronal mass ejection (CME) model suitable for both scientific and operational purposes by combining a global magnetohydrodynamics (MHD) solar wind model with a flux rope-driven CME model. Realistic CME events are simulated self-consistently with high fidelity and forecasting capability by constraining initial flux rope parameters with observational data from GONG, SOHO/LASCO, and STEREO/COR. We automate this process so that minimum manual intervention is required in specifying the CME initial state. With the newly developed data-driven Eruptive Event Generator Gibson-Low (EEGGL), we present a method to derive Gibson-Low (GL) flux rope parameters through a handful of observational quantities so that the modeled CMEs can propagate with the desired CME speeds near the Sun. A test result with CMEs launched with different Carrington rotation magnetograms are shown. Our study shows a promising result for using the first-principles-based MHD global model as a forecasting tool, which is capable of predicting the CME direction of propagation, arrival time, and ICME magnetic field at 1 AU (see companion paper by Jin et al. 2016b).

We present a first-principles-based coronal mass ejection (CME) model suitable for both scientific and operational purposes by combining a global magnetohydrodynamics (MHD) solar wind model with a flux rope-driven CME model. Realistic CME events are simulated self-consistently with high fidelity and forecasting capability by constraining initial flux rope parameters with observational data from GONG, SOHO/LASCO, and STEREO/COR. We automate this process so that minimum manual intervention is required in specifying the CME initial state. With the newly developed data-driven Eruptive Event Generator Gibson-Low (EEGGL), we present a method to derive Gibson-Low (GL) flux rope parameters through a handful of observational quantities so that the modeled CMEs can propagate with the desired CME speeds near the Sun. A test result with CMEs launched with different Carrington rotation magnetograms are shown. Our study shows a promising result for using the first-principles-based MHD global model as a forecasting tool, which is capable of predicting the CME direction of propagation, arrival time, and ICME magnetic field at 1 AU (see companion paper by Jin et al. 2016b).

-The new EEGGL tool recently developed at the CCMC in collaboration with the University of Michigan, provides a capability to simulate the CME as well as its magnetic field evolution at 1 AU -Based on the magnetogram and evaluation of the CME initial location and speed, the user may choose the active region from which the CME originates and then the EEGGL tools provides the parameters of the Gibson-Low magnetic configuration to parameterize the CME. -The recommended parameters may be used then to drive the CME propagation from the low solar corona to 1 AU using the global code for simulating the solar corona and inner heliosphere. -At the CCMC The Community Coordinated Modeling Center (CCMC) provides the capability for CME runs-on-request, to the heliophysics community. -EEGGL is a new animal in the CCMC Zoo, which is well integrated with the other animals (Donki, STEREOCat).

We present and demonstrate a new tool, EEGGL (Eruptive Event Generator using Gibson-Low configuration) for simulating CMEs (Coronal Mass Ejections). CMEs are among the most significant space weather events, producing the radiation hazards (via the diffuse shock acceleration of the Solar Energetic Particles – SEPs), the interplanetary shock waves as well as the geomagnetic activity due to the drastic changes of the interplanetary magnetic field within the “magnetic clouds” ("flux ropes”). Some of this effects may be efficiently simulated using the “cone model”, which is employed in the real-time simulations of the ongoing CMEs at the NASA-Goddard Space Flight Center. The cone model provides a capability to predict the location, time, width and shape of the hydrodynamic perturbation in the upper solar corona (at ~0.1 AU), which can be used to drive the heliospheric simulation (with the ENLIL code, for example). At the same time the magnetic field orientation in this perturbation is uncertain within the cone model, which limits the capability of the geomagnetic activity forecast. The new EEGGL tool http://ccmc.gsfc.nasa.gov/analysis/EEGGL/recently developed at the Goddard Space Flight Center in collaboration with the University of Michigan provides a new capability for both evaluating the magnetic field configuration resulting from the CME and tracing the CME through the solar corona. In this way not only the capability to simulate the magnetic field evolution at 1 AU may be achieved, but also the more extensive comparison with the CME observations in the solar corona may be achieved. Based on the magnetogram and evaluation of the CME initial location and speed, the user may choose the active region from which the CME originates and then the EEGGL tools provides the parameters of the Gibson-Low magnetic configuration to parameterize the CME. The recommended parameters may be used then to drive the simulation of CME propagation from the low solar corona to 1 AU using the global code for simulating the solar corona and inner heliosphere. The Community Coordinated Modeling Center (CCMC) provides the capability for CME runs-on-request, to the heliophysics community.

of the major types of solar eruption, coronal mass ejections (CMEs) not only impact space weather, but also can have significant societal consequences. CMEs cause intense geomagnetic storms and drive fast mode shocks that accelerate charged particles, potentially resulting in enhanced radiation levels both in ions and electrons. Human and technological assets in space can be endangered as a result. CMEs are also the major contributor to generating large amplitude Geomagnetically Induced Currents (GICs), which are a source of concern for power grid safety. Due to their space weather significance, forecasting the evolution and impacts of CMEs has become a much desired capability for space weather operations worldwide. Based on our operational experience at Space Weather Research Center at NASA Goddard Space Flight Center (http://swrc.gsfc.nasa.gov), we present here some of the insights gained about accurately predicting CME impacts, particularly in relation to space weather operations. These include: 1. The need to maximize information to get an accurate handle of three-dimensional (3-D) CME kinetic parameters and therefore improve CME forecast; 2. The potential use of CME simulation results for qualitative prediction of regions of space where solar energetic particles (SEPs) may be found; 3. The need to include all CMEs occurring within a ~24 h period for a better representation of the CME interactions; 4. Various other important parameters in forecasting CME evolution in interplanetary space, with special emphasis on the CME propagation direction. It is noted that a future direction for our CME forecasting is to employ the ensemble modeling approach.

The Community Coordinated Modeling Center at NASA, Goddard Space flight Center, provides access to state-of-the-art space weather models to the research community. The majority of the models residing at the CCMC are comprehensive computationally intensive physics-based models. The CCMC also provides free services and tools to assist the research community in analyzing the results from the space weather model simulations. We present an overview of the available tools and services at the CCMC: the Runs-On-Request system, the online visualization, the Kameleon access and interpolation library and the Metrics Challenge tools suite.