Summary

In 2019, the National Academies of Sciences, Engineering, and Medicine were approached by officials from the National Environmental Satellite, Data, and Information Service (NESDIS) of the National Oceanic and Atmospheric Administration (NOAA), the Heliophysics Division of the National Aeronautics and Space Administration (NASA), and the Geospace Section at the National Science Foundation (NSF) to organize a workshop that would examine the operational and research “infrastructure” that supports the space weather enterprise, including an analysis of existing and potential future measurement gaps and opportunities for future enhancements. That workshop (Phase I) focused on space weather operations, including measurement continuity needs, and a proceedings summarizing the workshop was published in 2021.¹

Subsequently, NASA, NOAA, and NSF requested a follow-on workshop that would focus on the research agenda and observations needed to improve scientific understanding of the Sun–Earth interactions that cause space weather. A summary of the workshop is presented in this proceedings.

CURRENT SPACE WEATHER EFFORTS

The U.S. space weather community includes a number of stakeholders both in and outside the federal government. NASA is currently establishing a Space Weather Program within its Heliophysics Division. This reflects the newly broadened role of Heliophysics in the research-to-operations/operations-to-research (R2O2R) process, providing space weather information to lunar and planetary endeavors as well as developing new applications for impact mitigation. For example, the HERMES instrument package to be placed on the lunar-orbiting Gateway will make space weather measurements to support lunar operations and demonstrate technologies needed to conduct a human mission to Mars. The Heliophysics System Observatory (HSO) provides observations for basic and applications-focused research as well as real-time operations.

NSF is carrying out a variety of space weather efforts housed in multiple NSF directorates; for example, the Directorate of Geosciences supports the Coupling, Energetics, and Dynamics of Atmospheric

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¹ National Academies of Sciences, Engineering, and Medicine, 2021, Planning the Future Space Weather Operations and Research Infrastructure: Proceedings of a Workshop, Washington, DC: The National Academies Press, https://doi.org/10.17226/26128.

Regions (CEDAR); Geospace Environment Modeling (GEM); and Solar, Heliospheric, and Interplanetary Environment (SHINE) programs as well as facilities such as the National Center for Atmospheric Research (NCAR). The Directorate for Mathematical and Physical Sciences supports the National Solar Observatory, and the Division of Physics supports plasma physics research. NSF also supports a wide network of observing facilities, including solar telescopes, magnetometer networks, radars, neutron monitors, and networks of citizen-science measurements. Although the NSF-supported observing network is primarily ground-based, NSF also supports balloon-based instrumentation as well as CubeSats and public–private partnerships with the space industry. An important priority for NSF is the development of the space science workforce.

The Department of Defense Space Weather Program has recently been reorganized within the U.S. Space Force under Space Domain Awareness. The goal of that effort is to create a holistic picture of the environment within which operations are conducted, with the inclusion of specific system impacts. Reaching that goal will involve development of an integrated software suite consisting of data, models, and applications as well as interagency agreements, which are being established to facilitate sharing of data between agencies, using open architectures, and enabling all participating agencies to improve their capabilities (e.g., those concerning commercial space traffic management).²

The NOAA space weather charter complements those of the other agencies and focuses on capacity building to advance space weather policy, services, research, and operations. NOAA’s plans for improvement of space weather services involves (1) sustaining fundamental observations, (2) providing accurate models and forecast products, (3) transitioning scientific and technological advances into operations, and (4) supporting the private sector to fill data and technology gaps and to provide value-added services. NOAA’s new operations paradigm combines the establishment of dedicated operational observing systems with modeling and service improvements to provide forecasts, warnings, and data. Furthermore, space weather has recently become a third pillar in NOAA’s NESDIS structure, which aims to provide an integrated, digital understanding of Earth’s environment.

NOAA’s long-term support for NASA’s crewed missions was continued by the recently signed NASA–NOAA Interagency Agreement on providing space radiation environment support to all human spaceflight missions, including the International Space Station and Lunar (Artemis) and Martian crewed missions. NOAA’s Office of Space Commerce is prototyping an Open-Architecture Data Repository (OADR) environment to facilitate research-to-operations (R2O) efforts related to space traffic management.

A central element of the U.S. national space weather effort is the National Space Weather Strategy and Action Plan (NSW-SAP), which was put in place in 2019. U.S. space weather activities are overseen by the Space Weather Operations, Research, and Mitigation Subcommittee in the Office of Science and Technology Policy. The PROSWIFT Act, signed into law on October 21, 2020, codifies U.S. policy to prepare and protect against the social and economic impacts of space weather. It mandated the establishment of a Space Weather Interagency Working Group to coordinate executive branch actions to improve understanding and prediction of space weather phenomena, and a Space Weather Advisory Group to receive advice from academia, the commercial sector, and space weather end users. In addition, the National Academies’ Space Weather Roundtable and NASA’s Space Weather Council help support communication and coordination among the agencies in the space weather effort.

Priorities in updating the 2019 NSW-SAP include the R2O2R Framework, benchmarks, activity scales, hazard mapping, human exploration, space situational awareness, aviation, and continuity of satellite observations. The intent expressed in the NSW-SAP is to provide a formal interagency structure to ensure an effective space weather R2O2R process.

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² This report frequently references the term, “space traffic management”; however, other terms in common use are “space traffic awareness” and “space traffic coordination.”

The U.S. commercial sector, particularly electric power and aviation industries, has a long history of using space weather observations and forecasts in decision making. For example, the North American Electric Reliability Corporation (NERC) has developed mandatory standards for grid operators for risk assessment and mitigation, especially concerning extreme events, thus guiding old and new operators in the field. Space industry, on the other hand, is booming and bringing new actors to the field, which has created a need to educate new satellite providers and operators on how to adapt to and mitigate space weather hazards. For most space weather applications, having the longest possible forecast lead time, ideally 72 hours in advance, is of key importance. However, there are significant challenges in reaching this objective, including the availability of the required observations, the level of scientific understanding of processes that underlie space weather phenomena, and the intrinsic time scales of the processes themselves.³

RESEARCH NEEDS

Space weather lies at the intersection of the natural space environment (object of fundamental scientific research) and hazards to human systems and technology (addressed by operational communities interested in engineering risk mitigation). This intersection includes applied science and engineering as well as R2O activities.

Space weather impacts can be broken into five categories: (1) hazards affecting space-borne technology caused by direct drivers from the Sun (e.g., solar flares and radio bursts); (2) radiation effects (e.g., on technology and humans aboard spacecraft and aircraft); (3) ionospheric effects (e.g., affecting satellite communication, navigation, and high-frequency [HF] radio communications); (4) thermospheric expansion (orbital changes and collision hazards of satellites and other objects); and (5) geomagnetically induced currents (GICs) (which can lead to damage to power systems on the ground).

Reaching the level of understanding required to predict geospace system behavior requires a systems approach involving coordinated and concurrent space-borne and ground-based measurements combined with advanced data science, modernized data infrastructure, and modeling tools. For example, in order to better understand the behavior of coronal mass ejections (one of the key drivers of space weather), it is important to track their evolution in real time and in three dimensions as they travel toward and impact Earth. However, such level of coordination is not reflected in the current infrastructure: While past and current NASA space missions have been combined into the Heliophysics System Observatory, this system has not been strategically planned from a systems-science perspective. As each new mission is evaluated on its individual science goals, any systems science approaches have been and will be on an ad hoc basis. Furthermore, the ground-based measurements suffer from a similar lack of coordination. Since systems science requires an extensive, simultaneously operational fleet, it would greatly benefit from international collaboration.

Multi-satellite missions are necessary for understanding the processes that take place over vast regions of space at many different scales, and technological advances now enable missions to study conditions and processes from the smallest scale to mesoscales and the entire magnetosphere–ionosphere–thermosphere system.⁴ However, such missions require substantial investments in inter-calibration of the observing instruments as well as developing robust methods to incorporate data into interpretive models. Constellations covering a range of scales are important for understanding processes that extend from the solar atmosphere

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³ T. Pulkkinen, 2007, “Space Weather: Terrestrial Perspective,” Living Reviews Solar Physics 4:1, https://doi.org/10.12942/lrsp2007-1.

⁴ Note that the small scale and mesoscale definitions are region-dependent with the ionospheric small to mesoscales being from tens of meters to 1,000 km, and magnetospheric scales ranging from tens of kilometers to a few Earth radii.

and inner heliosphere to the near-Earth space environment. Similarly, it was noted by some participants that a dense network of ground-based and space-based geophysical observatories, including those operated by the private sector, will be required to provide high-confidence, long lead-time predictions of GICs and other hazards to power systems and other technological assets.

Extreme events are rare, and their impacts are neither well understood nor well represented by existing models. Currently available data sets, which are dominated by quiet space weather, pose challenges for machine learning models as well as validation of physics-based models when they try to address very high activity periods. Continuous monitoring of space weather is needed to observe rare space weather events. However, observation of such events was said to provide a unique opportunity to increase knowledge of their impacts on the space environment, on the upper atmosphere, and on the ground- and space-based technological systems.

These considerations point to the following detailed research needs:

• Tracking the entire system: The NASA gap analysis report lists top observational priorities: solar and solar wind observations, including observations off the Sun–Earth line and the solar wind near Earth; plasma sheet electron and ion injections/bursts from the magnetotail into geosynchronous orbit and medium earth orbit regions; ring current and radiation belt electron acceleration processes; ionospheric and thermospheric key parameters; and ionospheric D- and E-region energetic particle precipitation as well as E- and F-region cusp and auroral region precipitation.
• Understanding global couplings: Significant efforts are being devoted to finding ways to couple regimes (e.g., solar wind to magnetosphere), physical transitions (e.g., plasma-dominated versus magnetic-pressure-dominated plasmas, high versus low Alfvén speed plasmas, collisional versus collisionless plasmas), and spatial scales (e.g., magnetohydrodynamic versus kinetic plasmas). Such multi-scale and multi-step processes are important in understanding the physics of space weather, but they are not well observed or well modeled. This is especially true for the ionosphere, which is coupled to the magnetosphere and solar wind from above, but also to the thermosphere and even the stratosphere from below; the forcing from below is an important, but often neglected, aspect of space weather.
• Real-time monitoring: Such monitoring is critical for both nowcasting and forecasting, but it creates extra challenges for data downlinking systems and capacity and also places additional requirements on research-focused missions, which generally are not concerned with real-time monitoring.
• Validating models: Observing system simulation experiments (OSSEs) can be invaluable in providing cost–benefit analyses of adding additional measurements to improve model performance. In addition, OSSEs can be conducted to identify missing physics and to improve the assessment of model errors and error sources.
• Reaching out to neighboring fields: For example, collaboration with plasma physics researchers, data scientists, and Earth scientists would be beneficial for gaining new numerical and computational tools to space weather science.

MODELING AND VALIDATION

Current operational space weather models include large, physics-based models that treat the system elements from the Sun to the upper atmosphere and ground. Experiences from the terrestrial weather community indicate that the way to improve the accuracy of predictions is to increase model resolution (computational power), improve representation of physical processes (scientific understanding), and use advanced data assimilation techniques (new analysis methods).

Data needs are still pressing, because—despite the large data sets already acquired—the data are often not well matched to modeling needs. The lack of suitable data arises either because of the quality or format of available data or because the models need measurements that are not made at all, are not made at the right locations, or are not made at sufficient cadence. Since even large data sets contain only a small number of extreme events, the lack of data remains a challenge for many of the new data analysis and model-development methodologies being employed. In particular, the space weather community does not yet have the data needed to create standardized data products suited for machine learning applications. As the need is to acquire simultaneous observations from as many locations as possible, data buys from private companies operating instruments onboard commercial satellites offer a potential solution for some of the data sparsity issues, assuming that the required instruments and data products would be available.

The space weather community is becoming increasingly multidisciplinary, as optimal use of new methods, such as ensemble modeling, data assimilation, or machine learning, requires bringing in experts from computer science, Earth sciences, space technology, and other fields. While these methods have been applied in other fields to other data sets, their application to space weather prediction problems requires development of dedicated data sets as well as methods tuned to the specific problem (i.e., substantial cross-disciplinary learning between the discipline scientists and the methodology developers). Furthermore, due to the large system size, ensemble models, data assimilation, and machine learning applications often need computing and data storage resources that push the current capacity of even the largest supercomputing facilities.

In particular, space weather must address the following modeling and validation issues:

• Ensemble modeling, data assimilation, and machine learning are methodologies that have the potential to significantly improve space weather predictions. However, each of these methodologies is currently limited in its application. Ensemble modeling is currently limited by computing and data storage resources; data assimilation will require development of solutions suited for the sparse space physics data; and machine learning is currently limited both by data quality and data quantity, particularly concerning extreme events. Machine learning models for space weather produce best results when aimed at both understanding the underlying physical phenomena and producing the more typical machine learning “black box” predictions.
• Data scarcity is a real issue: The “too often, too quiet” problem arises because space weather data sets are dominated by quiet conditions, containing only as rare occurrences storms that are of relevance to severe space weather. This creates a serious problem for any machine learning algorithm, and it also poses challenges for defining meaningful metrics that assess the ability of a model to predict interesting but rare events.
• Interdisciplinary teams, courses, and programs are needed to train the next generation of space physicists. In particular, it is important to see that a sufficient fraction of the community is equipped with the machine learning skills and knowledge they will need in their research and applied work.

RESEARCH INFRASTRUCTURE

Capabilities have steadily increased in spacecraft development, launch systems, modeling and data analytics, instrumentation, and commercial data product services. This has led to a changed vision for the future science missions’ infrastructure and operations: on top of the science priorities to increase understanding of the solar–terrestrial environment, the R2O2R cycles should be included in the planning from the beginning. These emerging trends will play a major role in shaping future architectures. Central themes on the topic of infrastructure are the need for resources and the need to plan ahead.

A key theme that appeared across sessions was the need to increase the operational infrastructure by incorporating data from scientific or (future) commercial missions into operations. This will require, for example, inter-calibration of science instruments so that data sets from different missions can be incorporated into operational models. Preplanning and coordination between the science and operations agencies are needed to address potential issues regarding calibration, data uniformity, and latency.

NOAA has established a Program of Record⁵ that identifies the essential observations that must continuously be obtained. These include observations of the Sun, the solar wind, the geostationary environment, and the ionosphere. While academic research can often use data after the fact, some key information about the Sun and the heliosphere needs to be provided in (near) real-time to enable operational decisions.

Commercial data buys have the potential to produce new data products at substantially lower cost and on a faster schedule than existing contractual mechanisms, as launch services, data services, spacecraft systems, and operations are all becoming more commoditized. Moreover, the space weather research community could greatly benefit from gaining access to already existing infrastructure instead of building new infrastructure. An example of such opportunities would be the use of commercial and Department of Defense communication networks to provide data downlink and reduced-latency services.

While commercial data acquisition may offer valuable opportunities, the use of such data faces significant challenges. First and foremost, the vendors must be offered an appealing value proposition to hosting an instrument or providing data, as the task requires additional effort and customization on their part. A further challenge of providing NASA-funded custom instruments to commercial spacecraft is that the U.S. government procurement processes are not well suited to engaging with commercial providers, who tend to move faster and have different commitment processes. Regardless of the instrument developer, there may be proprietary concerns that limit getting the necessary metadata needed to validate and calibrate the data sets. Lastly, after acquisition, resources must be allocated for archiving, validation, verification, and distribution of the data. Cost–benefit analyses will be needed to weigh the issues related to rideshare instrument data quality and the possibly non-optimal distribution of observing locations.

New ways of doing business and managing programs will be needed in order to increase the efficiency of the manufacturing and operation of satellite constellations, as well as the efficiency of their data delivery. Novel approaches to building instruments that can be effectively used for both research and space weather observations should be examined. Systems-level approaches are needed to address gaps arising from the sparse fleet, including coverage across the multiple scales. The large data volumes now being produced require new capabilities for managing, storing, and accessing the data, including techniques for processing data onboard the spacecraft.

Resources and agency coordination will be needed, especially to ensure that instruments will be available and operational as needed. Commercial and other operators will need to be supported and incentivized to support space weather measurements. While cited as not particularly glamorous work, this is necessary to obtain the ground- and space-based infrastructure needed for accurate space weather predictions.

The particular infrastructure needs for space weather include the following:

• Monitoring the solar source: Space weather forecasts need more complete (i.e., three-dimensional) coverage of the Sun and heliosphere, along with more comprehensive high-resolution (in both time and energy) measurements of the solar wind. For predicting and understanding the solar corona, it is critically important to continuously monitor the photospheric magnetic field. Such 4π steradian

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⁵ See, for example, National Oceanic & Atmospheric Administration, “Space Weather Program Formulation,” https://www.nesdis.noaa.gov/sites/default/files/SessionIII_Talaat_Elsayed_SECOND_SpaceWeatherProgramFormulation_0.pdf, accessed July 8, 2022, or NOAA National Satellite and Information Service, 2021, “NOAA’s Current and Future Space Weather Architecture,” https://www.nationalacademies.org/event/09-30-2021/docs/DDD4B18BA6DB94017EF5F3F2581987716BB4581A1EFC.

• coverage can be obtained by out-of-the-ecliptic architectures that can provide three-dimensional reconstruction of incoming transients. The L4 and L5 vantage points offer unique views, with the L5 monitors more useful for measuring active regions likely to launch coronal mass ejections Earthward, and L4 being more useful for monitoring Earthward-heading solar energetic particles.
• Observing solar wind heavy ion composition: Knowledge about the heavy ion composition of the solar wind is a significant gap in current in situ plasma measurements. The composition measurements are key in differentiating high-speed streams from interplanetary coronal mass ejections (ICMEs), in identifying the internal structure of the ICME, and in constraining the models of coronal mass ejection initiation, energization, heating, release, and propagation. They are essential to improve scientific understanding of solar wind structures, which will enable better nowcasting and the quantification of the total mass and pressure of a space weather event.
• Bridging the gap in heliophysics between the Sun and geospace: Currently a major gap exists between the study of the Sun and of geospace. To bridge the gap and to predict space weather events from the solar transients to the geospace effects requires new architectures that fuse research in both areas. Such architectures would resolve both the solar source and the solar wind upstream of Earth in scales relevant for the geospace environment.
• Collecting multipoint observations of the magnetosphere–ionosphere–thermosphere system: This is a critical need for space weather science and application development, in particular for improving empirical and physics-based models. However, studies of where, what kind, and how many measurements are needed for major advances in the predictions have not been done in a comprehensive way.
• Transitioning science missions to operational ones: The completion of the prime science phase of a science mission offers opportunities to continue monitoring the Sun–Earth system with additional observation points. Designing science missions from the outset with both scientific and operational targets in mind would ease the transition process. For example, the CCOR (Compact Coronagraph) was developed in a collaboration between the Naval Research Laboratory and NOAA to be flown on both the Space Weather Follow On-Lagrange 1 (SWFO-L1) mission and GOES-R at geosynchronous orbit. This interagency collaboration is intended to continue a critical space weather measurement series initiated by the ESA/NASA Solar and Heliospheric Observatory (SOHO) white light coronagraph launched in 1995. The project is a model for interagency coordination as well as instrument development and deployment within agency budgets.