Space environment models are imperative tools for space weather research and operational forecasting. Two major targets in the space weather enterprise are to advance predictive modeling capabilities and to promptly transition new models to space weather operations. Model assessments are essential to build credibility for potential users, while the approach to model validation depends on user priorities. Precise, transparent and up-to-date evaluations of strengths and limitations of space weather models provide vital guidance toward the progress in understanding of space environment phenomena. It also demonstrates potential of new models to improve state-of-the-art operational space weather forecasting. Therefore, a space weather capabilities assessment is one of the Overarching Activities of the COSPAR International Space Weather Action Teams (ISWAT) initiative. ISWAT Action Teams associated with ISWAT domain-focused (S – Space weather origins at the Sun, H - Heliosphere variability, G - coupled Geospace System, plus the newly established cross-domain Sun-to-Geospace - S2G) Clusters, provide pivotal progress in Assessment Overarching Activity. The ISWAT community-wide validation projects include both Modeling Challenges for historic time periods and pre-event real-time ensemble predictions. At the same time, operational space weather forecasting centers perform pre-operational and operational real-time continuous model validations and provide feedback to developers. This Roadmap paper presents a comprehensive overview of successes and lessons learned from validation projects and the transition to operations activities since the previous Space Weather Roadmap (Schrijver et al., 2015) and outlines recommendations for moving forward

Global solar photospheric magnetic maps play a critical role in solar and heliospheric physics research. Routine magnetograph measurements of the field occur only along the Sun–Earth line, leaving the far side of the Sun unobserved. Surface flux transport (SFT) models attempt to mitigate this by modeling the surface evolution of the field. While such models have long been established in the community (with several releasing public full-Sun maps), none are open source. The Open-source Flux Transport (OFT) model seeks to fill this gap by providing an open and user-extensible SFT model that also builds on the knowledge of previous models with updated numerical and data acquisition/assimilation methods along with additional user-defined features. In this first of a series of papers on OFT, we introduce its computational core: the High-performance Flux Transport (HipFT) code ( https://github.com/predsci/hipft ). HipFT implements advection, diffusion, and data assimilation in a modular design that supports a variety of flow models and options. It can compute multiple realizations in a single run across model parameters to create ensembles of maps for uncertainty quantification and is high-performance through the use of multi-CPU and multi-GPU parallelism. HipFT is designed to enable users to write extensions easily, enhancing its flexibility and adaptability. We describe HipFT’s model features, validations of its numerical methods, performance of its parallel and GPU-accelerated code implementation, analysis/postprocessing options, and example use cases.

To model the structure and dynamics of the heliosphere well enough for high-quality forecasting, it is essential to accurately estimate the global solar magnetic field used as inner boundary condition in solar wind models. However, our understanding of the photospheric magnetic field topology is inherently constrained by the limitation of systematically observing the Sun from only one vantage point, Earth. To address this challenge, we introduce global magnetic field maps that assimilate far-side active regions derived from helioseismology into solar wind modeling. Through a comparative analysis between the combined surface flux transport and helioseismic Far-side Active Region Model (FARM) and the base Surface Flux Transport Model without far-side active regions (SFTM), we assess the feasibility and efficacy of incorporating helioseismic far-side information in space weather forecasting. We are employing the Wang-Sheeley-Arge solar wind (WSA) model for statistical evaluation and leveraging the EUropean Heliospheric FOrecasting Information Asset (EUHFORIA), a three-dimensional heliospheric MHD model, to analyze a case study. Using the WSA model, we show that including far-side magnetic data improves solar wind forecasts for 2013 – 2014 by up to 50% in correlation and 3% in root mean square error and mean absolute error, especially near the Earth and Solar TErrestrial RElations Observatory – Ahead (STEREO-A). Additionally, our 3D modeling shows significant localized differences in heliospheric structure that can be attributed to the presence or absence of active regions in the magnetic maps used as input boundaries. This highlights the importance of including far-side information to more accurately model and predict space weather effects caused by solar wind, solar transients, and geomagnetic disturbances.

The Sun's corona is its tenuous outer atmosphere of hot plasma, which is difficult to observe. Most models of the corona extrapolate its magnetic field from that measured on the photosphere (the Sun's optical surface) over a full 27-day solar rotational period, providing a time-stationary approximation. We present a model of the corona that evolves continuously in time, by assimilating photospheric magnetic field observations as they become available. This approach reproduces dynamical features that do not appear in time-stationary models. We used the model to predict coronal structure during the total solar eclipse of 8 April 2024 near the maximum of the solar activity cycle. There is better agreement between the model predictions and eclipse observations in coronal regions located above recently assimilated photospheric data.

Coronal holes are recognized as the primary sources of heliospheric open magnetic flux (OMF). However, a noticeable gap exists between in-situ measured OMF and that derived from remote sensing observations of the Sun. In this study, we investigate the OMF evolution and its connection to solar structures throughout 2014, with special emphasis on the period from September to October, where a sudden and significant OMF increase was reported. By deriving the OMF evolution at 1au, modeling it at the source surface, and analyzing solar photospheric data, we provide a comprehensive analysis of the observed phenomenon. First, we establish a strong correlation between the OMF increase and the solar magnetic field derived from a Potential Field Source Surface (PFSS) model ($cc_{\mathrm{Pearson}}=0.94$). Moreover, we find a good correlation between the OMF and the open flux derived from solar coronal holes ($cc_{\mathrm{Pearson}}=0.88$), although the coronal holes only contain $14-32\%$ of the Sun's total open flux. However, we note that while the OMF evolution correlates with coronal hole open flux, there is no correlation with the coronal hole area evolution ($cc_{\mathrm{Pearson}}=0.0$). The temporal increase in OMF correlates with the vanishing remnant magnetic field at the southern pole, caused by poleward flux circulations from the decay of numerous active regions months earlier. Additionally, our analysis suggests a potential link between the OMF enhancement and the concurrent emergence of the largest active region in solar cycle 24. In conclusion, our study provides insights into the strong increase in OMF observed during September to October 2014.

The Wang–Sheeley–Arge (WSA) model has been in use for decades and remains a popular, economical approach to modeling the solar coronal magnetic field and forecasting conditions in the inner heliosphere. Given its usefulness, it is unsurprising that a number of WSA implementations have been developed by various groups with different computational approaches. While the WSA magnetic field model has traditionally been calculated using a spherical harmonic expansion of the solar magnetic field, finite-difference potential field solutions can offer speed and/or accuracy advantages. However, the creation of new versions of WSA requires that we ensure the solutions from these new models are consistent with established versions and that we quantify for the user community to what degree and in what ways they differ. In this paper, we present side-by-side comparisons of WSA models produced using the traditional, spherical harmonic–based implementation developed by Wang, Sheeley, and Arge with WSA models produced using a recently open-sourced finite-difference code from the CORHEL modeling suite called POT3D. We present comparisons of the terminal solar wind speed and magnetic field at the outer boundaries of the models, weighing these against the variation of the WSA model in the presence of small perturbations in the computational procedure, parameters, and inputs. We also compare the footpoints of magnetic field lines traced from the outer boundaries and the locations of open field in the models. We find that the traced field-line footpoints show remarkable agreement, with the greatest differences near the magnetic neutral line and in the polar regions.

The solar magnetic fields emerging from the photosphere into the chromosphere and corona are comprised of a combination of "closed" and "open" fields. The closed magnetic field lines are defined as those having both ends rooted in the solar surface, while the open field lines are those having one end extending out into interplanetary space and the other rooted at the Sun's surface. Since the early 2000's, the amount of total unsigned open magnetic flux estimated by coronal models have been in significant disagreement with in situ spacecraft observations, especially during solar maximum. Estimates of total open unsigned magnetic flux using coronal hole observations (e.g., using extreme ultraviolet (EUV) or Helium (He) I) are in general agreement with the coronal model results and thus show similar disagreements with in situ observations. While several possible sources producing these discrepancies have been postulated over the years, there is still no clear resolution to the problem. This paper provides a brief overview of the problem and summarizes some proposed explanations for the discrepancies. In addition, two different ways of estimating the total unsigned open magnetic flux are presented, utilizing the Wang-Sheeley-Arge (WSA) model, and one of the methods produce surprisingly good agreement with in situ observations. The findings presented here suggest that active regions residing near the boundaries of mid-latitude coronal holes are the probable source of the missing open flux. This explanation also brings in line many of the seemly contradictory facts that have made resolving this problem so difficult.

A plethora of coronal models, from empirical to more complex magnetohydrodynamic (MHD) ones, are being used for reconstructing the coronal magnetic field topology and estimating the open magnetic flux. However, no individual solution fully agrees with coronal hole observations and in situ measurements of open flux at 1 au, as there is a strong deficit between the model and observations contributing to the known problem of the missing open flux. In this paper, we investigate the possible origin of the discrepancy between modeled and observed magnetic field topology by assessing the effect on the simulation output by the choice of the input boundary conditions and the simulation setup, including the choice of numerical schemes and the parameter initialization. In the frame of this work, we considered four potential field source surface-based models and one fully MHD model, different types of global magnetic field maps, and model initiation parameters. After assessing the model outputs using a variety of metrics, we conclude that they are highly comparable regardless of the differences set at initiation. When comparing all models to coronal hole boundaries extracted by extreme-ultraviolet filtergrams, we find that they do not compare well. This mismatch between observed and modeled regions of the open field is a candidate contributing to the open flux problem.

To address Objective II of the National Space Weather Strategy and Action Plan "Develop and Disseminate Accurate and Timely Space Weather Characterization and Forecasts" and US Congress PROSWIFT Act 116-181, our team is developing a new set of open-source software that would ensure substantial improvements of Space Weather (SWx) predictions. On the one hand, our focus is on the development of data-driven solar wind models. On the other hand, each individual component of our software is designed to have accuracy higher than any existing SWx prediction tools with a dramatically improved performance. This is done by the application of new computational technologies and enhanced data sources. The development of such software paves way for improved SWx predictions accompanied with an appropriate uncertainty quantification. This makes it possible to forecast hazardous SWx effects on the space-borne and ground-based technological systems, and on human health. Our models include (1) a new, open-source solar magnetic flux model (OFT), which evolves information to the back side of the Sun and its poles, and updates the model flux with new observations using data assimilation methods; (2) a new potential field solver (POT3D) associated with the Wang-Sheeley-Arge coronal model, and (3) a new adaptive, 4-th order of accuracy solver (HelioCubed) for the Reynolds-averaged MHD equations implemented on mapped multiblock grids (cubed spheres). We describe the software and results obtained with it, including the application of machine learning to modeling coronal mass ejections, which makes it possible to improve SWx predictions by decreasing the time-of-arrival mismatch. The tests show that our software is formally more accurate and performs much faster than its predecessors used for SWx predictions.

AbstractA new method to nowcast spectral irradiance in extreme ultraviolet (EUV) and far ultraviolet (FUV) bands is presented here, utilizing only solar photospheric magnetograms and the Mg II index (i.e., the core‐to‐wing ratio). The EUV and FUV modeling outlined here is a direct extension of the SIFT (Solar Indices Forecasting Tool) model, based on Henney et al. (2015, https://doi.org/10.1002/2014sw001118). SIFT estimates solar activity indices using the earth‐side solar photospheric magnetic field sums from global magnetic maps generated by the ADAPT (Air Force Data Assimilative Photospheric Flux Transport) model. Utilizing strong and weak magnetic field sums from ADAPT maps, Henney et al. (2015, https://doi.org/10.1002/2014sw001118) showed that EUV & FUV observations can also be well modeled using this technique. However, the original forecasting method required a recent observation of each SIFT model output to determine and apply a 0‐day offset. The new method described here expands the SIFT and ADAPT modeling to nowcast the observed Mg II index with a Pearson correlation coefficient of 0.982. By correlating the Mg II model‐observation difference with the model‐observation difference in the EUV & FUV channels, Mg II can be used to apply the 0‐day offset correction yielding improvements in modeling each of the 37 studied EUV & FUV bands. With daily global photospheric magnetic maps and Mg II index observations, this study provides an improved method of nowcasting EUV & FUV bands used to drive thermospheric and ionospheric modeling.

This white paper advocates the importance of multi-height measurements of the vector magnetic field in the solar atmosphere. As briefly described in this document, these measurements are critical for addressing some of the most fundamental questions in solar and heliospheric physics today, including: (1) What is the origin of the magnetic field observed in the solar atmosphere? (2) What is the coupling between magnetic fields and flows throughout the solar atmosphere? Accurate measurements of the photospheric and chromospheric three-dimensional magnetic fields are required for a precise determination of the emergence and evolution of active regions. Newly emerging magnetic flux in pre-existing magnetic regions causes an increase in the topological complexity of the magnetic field, which leads to flares and coronal mass ejections. Measurements of the vector magnetic field constitute also the primary product for space weather operations, research, and modeling of the solar atmosphere and heliosphere. The proposed next generation Ground-based solar Observing Network Group (ngGONG), a coordinated system of multi-platform instruments, will address these questions and provide large datasets for statistical investigations of solar feature behavior and evolution and continuity in monitoring for space-weather focused endeavors both research and operational. It will also enable sun-as-a-star investigations, crucial as we look toward understanding other planet-hosting stars.

The Committee on Space Research (COSPAR) International Space Weather Action Teams (ISWAT) has the objective of addressing key problems in space weather research and forecasting. To accomplish this objective, several teams comprised of experts from a variety of fields and specialties have formed to specifically focus on challenging space weather problems, linking physical domains of the Sun-Earth system and addressing roadblocks slowing progress in space weather research and forecasting. The S2 Cluster is focused primarily on the solar magnetic field, heating of the corona, and solar spectral irradiance. The goal of this paper is to describe the central objectives of the six S2 Action Teams, summarize the current state of knowledge of the topic that each team is focusing on, identify key science gaps that need to be addressed in each area, supply key recommendations for the community to focus on to facilitate progress, provide a likely picture of progress in the next five years and plausible timelines of achievement beyond that, and finally link the S2 Cluster efforts to other ISWAT research domains.

These tar files, scripts, and datasets were used in the paper "Nowcasting Solar EUV with Magnetic Fields and MgII," submitted for publication to the Space Weather Journal. More information on what is included in this archive can be found the the ReadMe file.

Ground-based synoptic solar observations provide critical contextual data used to model the large-scale state of the heliosphere. The next decade will see a combination of ground-based telescopes and space missions that will study our Sun's atmosphere microscopic processes with unprecedented detail. This white paper describes contextual observations from a ground-based network needed to fully exploit this new knowledge of the underlying physics that leads to the magnetic linkages between the heliosphere and the Sun. This combination of a better understanding of small-scale processes and the appropriate global context will enable a physics-based approach to Space Weather comparable to Terrestrial Weather forecasting.

We present a report of recent progress on the topic of understanding solar coronal mass ejection (CME) onset from both modeling and observational viewpoints, as carried out from 2019 to the present by the NASA Living with a Star Focused Science Topic team on "Understanding the Onset of Major Solar Eruptions." Following the typical Focused Science Topic paradigm, a number of research groups were selected and joined together to tackle this problem. The work being carried out by this team explores the role of topology and of helicity transport in creating an environment favorable to CME eruption and in then providing the energy required for CME onset. The team investigated CME energization and initiation via photospheric shearing, via flux rope formation, and via magnetic flux emergence. This article will highlight recent progress made by six American research groups working in these areas. We do not intend to present an exhaustive review of these topics, but rather summarize the ideas from these research groups regarding ongoing and upcoming challenges to the questions of how, when, and why coronal mass ejections erupt from the sun.

To address Objective II of the National Space Weather Strategy and Action Plan 'Develop and Disseminate Accurate and Timely Space Weather Characterization and Forecasts' and US Congress PROSWIFT Act 116–181, our team is developing a new set of open-source software that would ensure substantial improvements of Space Weather (SWx) predictions. On the one hand, the focus is on the development of data-driven models. On the other hand, each individual component of our software will have higher accuracy with a dramatically improved performance. This is done by the application of new computational technologies and enhanced data sources. The development of such software paves way for improved SWx predictions accompanied with an appropriate uncertainty quantification. This will make it possible to forecast hazardous SWx effects on the space-borne and ground-based technological systems, and on human health. Our models involve (1) a new, open-source solar magnetic flux model (OFT), which evolves information to the back side of the Sun and its poles, and updates the model flux with new observations using data assimilation methods; (2) a new potential field solver (POT3D) associated with the Wang-Sheeley-Arge coronal model, and (3) a new adaptive, 4-th order of accuracy solver (HelioCubed) for the Reynolds-averaged MHD equations implemented on mapped multiblock grids (cubed spheres). We describe the software and results obtained with it, including the appication of machine learning to modeling coronal mass ejections, which makes it possible to improve SWx predictions by decreasing the time-of-arrival mismatch. The test show that our software is formally more accurate and performs much faster than its predecessors used for SWx predictions.

The concept of surface-flux transport (SFT) is commonly used in evolving models of the large-scale solar surface magnetic field. These photospheric models are used to determine the large-scale structure of the overlying coronal magnetic field, as well as to make predictions about the fields and flows that structure the solar wind. We compare predictions from two SFT models for the solar wind, open magnetic field footpoints, and the presence of coronal magnetic null points throughout various phases of a solar activity cycle, focusing on the months of April in even-numbered years between 2012 and 2020, inclusively. We find that there is a solar-cycle dependence to each of the metrics considered, but there is not a single phase of the cycle in which all the metrics indicate good agreement between the models. The metrics also reveal large, transient differences between the models when a new active region is rotating into the assimilation window. The evolution of the surface flux is governed by a combination of large-scale flows and comparatively small-scale motions associated with convection. Because the latter flows evolve rapidly, there are intervals during which their impact on the surface flux can only be characterized in a statistical sense, thus their impact is modeled by introducing a random evolution that reproduces the typical surface flux evolution. We find that the differences between the predicted properties are dominated by differences in the model assumptions and implementation, rather than the selection of a particular realization of the random evolution.

General Description: The magSum data file includes the values for the magnetic sums of photospheric magnetic flux on the Earth-side of the Sun (also referred to as magnetic indices, MIs) based on ADAPT (Air Force Data Assimilative Photospheric Flux Transport) global solar magnetic maps (Henney et al. 2012 and Henney et al. 2015; plus see, e.g., Arge et al. 2010; Hickmann et al. 2015). The solar MIs data is typically used as a measure of solar activity (see, e.g., Parker et al. 1997; Chapman and Boyden 1986). In addition, the solar magSum data is applied as an input to the SIFT (Solar Indices Forecasting Tool) model to forecast/estimate, e.g., the solar radio flux at 10.7 cm (i.e., F10.7), Mg II index, sunspot number (SSN), and EUV/FUV irradiance variability (see Henney et al. 2012 and Henney et al. 2015). To read more about SIFT real-time forecasts, see https://nso.edu/data/nisp-data/sift-forecasts/. The ADAPT maps used here were generated using input magnetograph data from ground-based instruments from the National Solar Observatory, specifically the Kitt Peak Vacuum Telescope [KPVT] and the Vector SpectroMagnetograph [VSM]. The magnetic sums are the absolute magnetic field of the Earth side pixels from ADAPT global maps within two bins: values greater than 20 G and less than 150 G (representing a plage index, M_P) and greater than or equal to 150 G (representing an active region index, M_A).

Drawing connections between heliospheric spacecraft and solar wind sources is a vital step in understanding the evolution of the solar corona into the solar wind and contextualizing \textit{in situ} timeseries. Furthermore, making advanced predictions of this linkage for ongoing heliospheric missions, such as Parker Solar Probe (PSP), is necessary for achieving useful coordinated remote observations and maximizing scientific return. The general procedure for estimating such connectivity is straightforward (i.e. magnetic field line tracing in a coronal model) but validating the resulting estimates difficult due to the lack of an independent ground truth and limited model constraints. In its most recent orbits, PSP has reached perihelia of 13.3$R_\odot$ and moreover travels extremely fast prograde relative to the solar surface, covering over 120 degrees longitude in three days. Here we present footpoint predictions and subsequent validation efforts for PSP Encounter 10, the first of the 13.3$R_\odot$ orbits, which occurred in November 2021. We show that the longitudinal dependence of \textit{in situ} plasma data from these novel orbits provides a powerful method of footpoint validation. With reference to other encounters, we also illustrate that the conditions under which source mapping is most accurate for near-ecliptic spacecraft (such as PSP) occur when solar activity is low, but also requires that the heliospheric current sheet is strongly warped by mid-latitude or equatorial coronal holes. Lastly, we comment on the large-scale coronal structure implied by the Encounter 10 mapping, highlighting an empirical equatorial cut of the Alfv\`{e}n surface consisting of localized protrusions above unipolar magnetic separatrices.

Placed at L4, the Sun, Corona, & Heliosphere Assessment for Space Exploration Readiness (SunCHASER) is a mission concept that will follow (or chase) high-energy processes around the west limb, combining solar remote sensing & in situ observations, and overseeing the entire solar radiation hemisphere.SunCHASER's remote sensing is essential for ~90% of current physicsbased and empirical solar energetic particle (SEP) event forecasting techniques.Without SunCHASER, there cannot be a basis for SEP event all-clear forecasting.It establishes and maintains a space weather (SWx) radiation safe zone that supports all near-term human missions to the Moon and Mars.SunCHASER latitude in-situ coverage also provides a unique opportunity for solar wind-, interplanetary-and interstellar-dust science.In combination with existing and planned observatories at L1 and L5, the three locations provide 240° longitude coverage of resolving photospheric magnetic field structure and safe Earth-directed CME viewing.A ~14°inclination of both L4 and L5 out of the ecliptic guarantees continuous viewing of both solar poles and continuous in-situ presence on both sides of the heliographic equator, with >3.6° elevation.Extended observations in both longitude and latitude will revolutionize global solar wind modeling and immediate validation, and enables the development of local helioseismology, with potential for long-term solar activity forecasting.