Dusan Odstrcil

We describe the 24‐member Coronal Mass Ejection (CME) ensemble prediction system that is used operationally at the UK's Met Office Space Weather Operations Center (MOSWOC) to forecast the arrival time of CMEs at Earth. The ensemble system was built on ad‐hoc assumptions and there is the need to investigate whether the technique can be improved using a more systematic approach. For this, we used 80 documented CMEs from the NASA CCMC CME scoreboard for the years 2016–2022 to develop a new 81‐member ensemble system. Eighteen CMEs did not arrive at Earth but were forecast by MOSWOC. We also include these false alarms in the comparison of our ensemble systems. A major result of this study is that the ensemble spread of the arrival times is a poor indicator of the forecast error. We also found that the number of ensemble members with an arrival time does not correspond well to the error of the predicted arrival time. We chose an error window of 24 hr around the observed arrival time for the validation of arrival times. Even with such a generous error range only about 40% of the arrival times fall into that window. Those numbers are consistent between our operational CME forecasting system and the new candidate. This new system does not necessarily lead to a massive improvement of the predicted arrivals of CMEs (errors can still be larger than 1 day). Despite that, we argue that the proposed new ensemble based system provides a better basis for the future.

Numerical models are essential for advancing fundamental research in heliophysics and for operational forecasting of space weather events. Open science can accelerate progress, but applying an open science approach to numerical models requires careful consideration; models are not data analysis software and often demand substantial domain expertise, experience, and computational resources to be used correctly. This commentary distills the recommendations from Corti et al. (2026), https://doi.org/10.22541/essoar.176824639.92354528/v2 and proposes a pathway for advancing heliophysics and space weather modeling through open science. Rather than focusing on open science policies and practices, we recommend concrete actions to make models usable by the broader community (open use), increase confidence and transparency throughout the Research‐to‐Operations‐to‐Research (R2O2R) pipeline (open validation), enable collaborative model improvement (open development), and strengthen partnerships (open collaboration). Together, these recommendations address several of the open science challenges experienced by contributing authors in developing, validating, using, and hosting advanced models, as identified during the 2024 Open Science Workshop held at College Park, USA. The recommendations also highlight the importance of a culture of shared responsibility, adherence to best practices, and proper recognition of prior work. The Heliophysics Open Modeling Environment will serve as a platform for modelers and model users to work together, facilitate community modeling, and increase the scientific return on modeling investment.

We present a community‐wide effort to develop a strategy and action plan to advance heliophysics and space weather modeling through open science. While open science has the potential to enhance the quality and pace of scientific discovery, its application to scientific modeling requires more careful consideration regarding open data and open software guidelines, as scientific models differ significantly from data analysis software. We gathered feedback from modeling teams worldwide through a living survey and discussion sessions at the 2024 Open Science Workshop in College Park, USA, and at the 2025 COSPAR ISWAT Working Meeting in Cape Canaveral, USA. We complement these findings with lessons learned from almost 25 years of experience at the Community Coordinated Modeling Center in enabling open use of models. We identify key roadblocks in current open science practices and guidelines and offer recommendations for future progress across four overlapping themes: open use of models and simulation results, open validation, open development, and open collaboration. An essential outcome of the discussion is the need for model developers and model users to speak with a united voice and promote the role of models in future open science efforts. We introduce a new cross‐domain community initiative called the Heliophysics Open Modeling Environment (HOME), which will be integrated as an overarching activity within COSPAR ISWAT. HOME will serve as a platform for modelers and model users to work together, facilitate community modeling, improve the scientific return on modeling investment, and advance understanding, modeling, and forecasting in heliophysics and space weather.

We present a community effort to assess how open science can advance heliophysics and space weather modeling. Open science has the potential to enhance the quality and pace of scientific discovery, but its application to scientific modeling requires more careful consideration with respect to open data and open software guidelines, as complex scientific models are not ordinary software. We gathered feedback from modeling teams worldwide through a living survey and discussion sessions at the Open Science Workshop in College Park, USA, in 2024, and the COSPAR ISWAT Initiative Working Meeting in Cape Canaveral, USA, in 2025. We complement these findings with lessons learned from almost 25 years of experience at the Community Coordinated Modeling Center in enabling open use of models. We identify key roadblocks in current open science practices and guidelines and offer recommendations for future progress. Our findings are organized into four overlapping themes: open use of models and simulation results, open validation, open development, and open collaboration. An essential outcome of the discussion is the need for model developers and users to speak with a united voice and promote the role of models in future open science efforts. We introduce a new cross-domain community initiative called Heliophysics Open Modeling Environment (HOME), which will be integrated as an overarching activity within the COSPAR ISWAT Initiative. HOME will serve as a platform for modelers and model users to work together, facilitate community modeling, improve the scientific return on modeling investment, and advance innovation in heliophysics and space weather.

The Polarimeter to Unify the Corona and Heliosphere (PUNCH) mission is a NASA Small Explorer to determine the cross-scale processes that unify the solar corona and heliosphere. PUNCH has two science objectives: (1) understand how coronal structures become the ambient solar wind, and (2) understand the dynamic evolution of transient structures, such as coronal mass ejections, in the young solar wind. To address these objectives, PUNCH uses a constellation of four small spacecraft in Sun-synchronous low Earth orbit, to collect linearly polarized images of the K corona and young solar wind. The four spacecraft each carry one visible-light imager in a 1 + 3 configuration: a single Narrow Field Imager solar coronagraph captures images of the outer corona at all position angles, and at solar elongations from 1.5° (6 R _⊙ ) to 8° (32 R _⊙ ); and three separate Wide Field Imager heliospheric imagers together capture views of the entire inner solar system, at solar elongations from 3° (12 R _⊙ ) to 45° (180 R _⊙ ) from the Sun. PUNCH images include linear-polarization data, to enable inferring the three-dimensional structure of visible features without stereoscopy. The instruments are matched in wavelength passband, support overlapping instantaneous fields of view, and are operated synchronously, to act as a single “virtual instrument” with a 90 ^∘ wide field of view, centered on the Sun. PUNCH launched in March of 2025 and began science operations in June of 2025. PUNCH has an open data policy with no proprietary period, and PUNCH Science Team Meetings are open to all.

Interpreting multi-spacecraft heliospheric observations of the evolving solar wind (SW) streams with propagating and interacting coronal mass ejections (CMEs) is challenging. Numerical simulations can provide global context and suggest what may and may not be observed. The heliospheric three-dimensional (3D) magnetohydrodynamic (MHD) ENLIL model can provide a near-real-time prediction of heliospheric space weather, and it is used at NASA Community Coordinated Modeling Center (CCMC), NOAA Space Weather Prediction Center (SWPC), and UK Meteorological Office (MetOffice). However, this version does not show its full potential, especially in the case of multi-CME events observed by various spacecraft. We describe tools developed to interpret remote observations and in-situ measurements better and apply them to multi-CME events observed by ACE, STEREO-A, Parker Solar Probe (PSP), BepiColombo, and Solar Orbiter. We present some results on 1) global structures of the SW speed and density at the ecliptic, 2) the evolution of SW parameters at the spacecraft, 3) magnetic field connectivity at the spacecraft, 4) automatic detection of shock parameters and alert plots, and 5) synthetic white-light (WL) imaging. This paper is not on model initialization or analyzing specific CME events, but it describes features not used at space weather prediction centers and provided by NASA/CCMC Run-On-Request service. This paper advertises new tools and shows their benefits when applied to selected heliospheric space weather events observed at near-Earth, PSP, Solar Orbiter, and STEREO-A spacecraft.

Energetic electrons of Jovian origin have been observed for decades throughout the heliosphere, as far as 11 au, and as close as 0.5 au, from the Sun. The treatment of Jupiter as a continuously emitting point source of energetic electrons has made Jovian electrons a valuable tool in the study of energetic electron transport within the heliosphere. We present observations of Jovian electrons measured by the EPI-Hi instrument in the Integrated Science Investigation of the Sun instrument suite on Parker Solar Probe at distances within 0.5 au of the Sun. These are the closest measurements of Jovian electrons to the Sun, providing a new opportunity to study the propagation and transport of energetic electrons to the inner heliosphere. We also find periods of nominal connection between the spacecraft and Jupiter in which expected Jovian electron enhancements are absent. Several explanations for these absent events are explored, including stream interaction regions between Jupiter and Parker Solar Probe and the spacecraft lying on the opposite side of the heliospheric current sheet from Jupiter, both of which could impede the flow of the electrons. These observations provide an opportunity to gain a greater insight into electron transport through a previously unexplored region of the inner heliosphere.

One of the critical models in space weather forecasting is the Enlil solar wind prediction model that can inform space weather forecasters the direction and speed of coronal mass ejections CMEs. The Enlil code calculates the propagation of the solar wind throughout the 3D heliosphere, but current visualization capabilities in the forecasting offices are restricted to 2D planes intersecting Earth. This limits forecasters to only be able to view CME properties that are traveling directly in the plane of the Earth. Here, we present an update on a new visualization capability being developed to take advantage of the full Enlil 3D data volume and interactively visualize the CME expansion out of the plane of the Earth.  We have been collaborating closely with researchers and forecasters at the Met Office in the UK and the Space Weather Prediction Center (SWPC) in the USA to develop a tool to enable full view of the heliosphere in a manner that can be tailored to these different types of users. To accomplish this, we are deploying the Enlil solar wind model into a scalable Cloud-based model staging platform computing environment, which will allow the full 3D Enlil output to reside in-situ with the visualization engine.  We will discuss our progress in deploying and running the Enlil model in the Cloud-based testbed environment, the process of interacting directly with space weather forecasters to design a new interactive 3D visualization tool that meets their needs, and will demonstrate use of the actual visualization tool, which is deployed and running in the Amazon Web Services (AWS) Cloud environment.