The core problem the project addresses is a translation gap. Space weather forecasters can already issue probabilistic warnings about geomagnetic storms, but satellite operators, insurers, and downstream service providers have limited tools for converting those probabilities into concrete operational and financial consequences. Oughton’s team, working with collaborators at West Virginia University, The Ohio State University, and the Southwest Research Institute, intends to build an end-to-end framework that carries uncertainty from the Sun all the way to society. The goal is a systems-level capability in which a probabilistic forecast of storm occurrence, timing, intensity, and driver type can be propagated through atmospheric physics, orbital mechanics, and economic models to yield quantified estimates of risk and loss.

The physics at stake is well understood but notoriously difficult to quantify. When a coronal mass ejection or a high-speed solar wind stream strikes Earth’s magnetosphere, energy is deposited into the upper atmosphere, heating and expanding the thermosphere. Satellites in Low Earth Orbit, roughly 200 to 2,000 kilometers above the surface, suddenly encounter denser air, and atmospheric drag increases sharply. During extreme historical events, such as the February 2022 incident in which dozens of newly launched Starlink satellites were lost to a modest geomagnetic storm, operators have seen orbital decay accelerate far faster than nominal models predicted. For Very Low Earth Orbit systems, which fly even lower to improve latency and imaging resolution, the drag problem is amplified because the neutral atmosphere is the dominant environmental hazard.

Under the project, the West Virginia University team led by Piyush Mehta will generate calibrated forecasts of geomagnetic storm occurrence, timing, intensity, and driver type. The distinction between driver types matters because coronal mass ejections and co-rotating interaction regions produce different storm profiles, with different onset speeds and durations, and therefore different drag signatures. Rather than issuing a single deterministic forecast, the framework will treat storm forcing as a stochastic process, producing bounded estimates of how a satellite’s drag response will evolve. This uncertainty-aware approach acknowledges a fundamental limitation of space weather prediction: even the best models cannot specify exactly how much energy will reach the upper atmosphere or how the thermosphere will respond at a given altitude and latitude.

Those stochastic drag estimates then feed into the operational layer of the framework. Mrinal Kumar’s group at The Ohio State University will contribute artificial intelligence methods for propagating uncertainty into the quantities that operators actually manage: orbital migration, degraded operational modes, conjunction-management burden, and orbit-correction demand. Conjunction management, the process of assessing and avoiding close approaches between space objects, is already a growing workload for constellation operators, and a major storm can inflate both the collision-avoidance burden and the frequency of station-keeping maneuvers simultaneously. By modeling these effects together rather than in isolation, the project aims to capture the compounding stress that a single storm can place on ground teams, propulsion budgets, and satellite lifetimes.

The final link in the chain is socio-economic. Subhamoy Chatterjee at the Southwest Research Institute will work with Oughton to connect operational disruptions to satellite service degradation, embedded sectoral dependencies, economic losses, and operator mitigation decisions. This is where the framework departs most clearly from traditional space weather research. Communication outages, navigation errors, and Earth-observation gaps do not remain in orbit; they cascade into sectors such as aviation, maritime transport, agriculture, finance, and emergency response, all of which now depend on satellite infrastructure. By embedding these dependencies into the model, the researchers intend to produce estimates of economic consequence that decision-makers outside the space sector can act upon, whether they are insurers pricing risk, regulators drafting resilience requirements, or governments planning for critical-infrastructure protection.

The timing of the award is significant. The number of active satellites has grown dramatically over the past decade, driven by commercial broadband constellations and the falling cost of launch, and many of these spacecraft operate in the drag-sensitive regime where space weather matters most. At the same time, the Sun progresses through its natural activity cycle, and the current period of high activity has delivered repeated reminders that even moderate storms can perturb operations. A severe storm on the scale of historical extremes could, by many expert assessments, cause widespread and prolonged disruption. Yet quantitative, uncertainty-aware estimates of what such a storm would do to today’s mega-constellations, and to the economies that rely on them, remain scarce. The project’s framework is designed to fill precisely that gap.

Artificial intelligence plays a central role throughout. Machine learning models can assimilate vast streams of solar wind, magnetospheric, and thermospheric data and learn relationships that are difficult to capture in first-principles physics codes, which are computationally expensive and still imperfect. But AI predictions are only useful for high-stakes operational decisions if their uncertainty is quantified and calibrated, which is why the project emphasizes uncertainty-aware methods rather than black-box forecasting. The researchers aim to produce forecasts whose stated confidence levels can be trusted, so that an operator deciding whether to lower a satellite’s orbit, safe-mode a spacecraft, or postpone a launch can weigh the true probability of adverse outcomes rather than a falsely precise point estimate.

The funding structure reflects the collaborative nature of the research. Each institution receives its own NSF award, with Oughton’s $499,837 supporting the George Mason component of the work. The linked awards to Mehta at West Virginia University, Kumar at The Ohio State University, and Chatterjee at the Southwest Research Institute formalize a partnership that spans space physics, computer science, and risk economics. This interdisciplinary composition is arguably essential: no single field currently owns the full chain from solar eruptive event to societal loss, and the project’s explicit ambition is to stitch those links together into a single, coherent modeling pipeline.

If the project succeeds, its outputs could reshape how the space industry and its regulators think about space weather risk. Instead of qualitative warnings that a storm is coming, operators and policymakers would have a defensible, probabilistic picture of how a forecast storm would propagate through satellite orbits, operational workloads, service availability, and economic losses, along with a structured way to evaluate mitigation options before the storm arrives. As humanity’s dependence on orbital infrastructure deepens, tools that make the invisible hazard of space weather measurable, and its consequences insurable and governable, may prove to be among the most consequential investments in the resilience of the digital age.

Subject of Research: AI-enabled, uncertainty-aware characterization of space weather risks to Low Earth Orbit satellites and their socio-economic impacts

Article Title: Oughton to receive funding for project on space weather satellite risk characterization and socio-economic impacts

Article References: Oughton to receive funding for project on space weather satellite risk characterization and socio-economic impacts. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: space weather, geomagnetic storms, satellites, Low Earth Orbit, artificial intelligence, uncertainty quantification, atmospheric drag, National Science Foundation, George Mason University, satellite operations, socio-economic impacts, conjunction management

Geomagnetic storms are dramatic phenomena triggered by explosive solar activity, specifically coronal mass ejections (CMEs), which release vast amounts of charged particles into space. These high-energy particles interact with Earth’s magnetosphere, leading to disturbances that can augment the density of the upper atmosphere. This increased density results in heightened atmospheric drag on satellites, adversely affecting their speed, altitude, and operational lifespan. Understanding these dynamics has become crucial amidst our reliance on satellite technology for navigation, communication, and security—a reality that underscores the urgency for adaptations in satellite design.

The essence of the new study reveals a paradoxical situation: while the baseline density of the upper atmosphere is projected to decline due to ongoing carbon dioxide emissions, the impact of future geomagnetic storms may paradoxically present a greater relative change in atmospheric density. Through sophisticated computer modeling, researchers demonstrated that during future geomagnetic events, the atmospheric density will peak at levels significantly lower than those of present-day storms, due to the changed baseline conditions.

The implications of these findings are manifold. As explained by lead author Nicolas Pedatella, who is a scientist with NSF NCAR, the future will see a redefined interaction between solar energy and the atmosphere. This means that the anticipated changes could have profound ramifications for the satellite industry, necessitating a recalibration in satellite engineering to withstand and perform optimally under these new atmospheric conditions. This information is invaluable for engineers tasked with designing satellites intended for an environment that is evolving due to climate change.

A critical aspect of this study involved analyzing historical data alongside advanced simulations from the Community Earth System Model Whole Atmosphere Community Climate Model with thermosphere-ionosphere eXtension, a tool that encompasses the entire atmospheric spectrum from the surface of Earth up to the thermosphere. This model was crucial for understanding how alterations in the lower atmosphere, primarily due to greenhouse gas concentrations, can reverberate throughout the upper atmospheric layers.

Researchers examined a particularly notable geomagnetic superstorm that occurred on May 10-11, 2024, recognized for its striking intensity. By comparing how this storm would have impacted the atmosphere in 2016 relative to its future influence in years marked by solar minimum phases—namely 2040, 2061, and 2084—the study provides a stark reminder of the ongoing atmospheric evolution driven by human activity. The simulations indicated that, by mid-century, the upper atmosphere would experience a significant decrease in density throughout geomagnetic storm events.

In layman’s terms, this means that as carbon dioxide and other greenhouse gases accumulate in the atmosphere, the foundations of what we considered ‘normal’ operational conditions for satellites will shift dramatically. Specifically, in future storm scenarios, while the overall density of the atmosphere may be reduced, the relative impact of any given storm could be more pronounced. This suggests that satellites may face more extreme challenges as a direct result of their operational environments being fundamentally transformed by climate change.

Notably, the research identified that geomagnetic storms, which presently double atmospheric density at their peak, could almost triple this density increase in the coming decades. This indicates a more considerable effect on a thinner atmosphere—resulting in a scenario where satellites not only endure higher drag forces but also experience more complicated orbital dynamics. This line of inquiry sheds light on the interconnectedness of Earth’s atmospheric layers and stresses the necessity for interdisciplinary studies that consider atmospheric composition and solar activity collectively.

Pedatella emphasized the critical nature of further research. Not only should scientists investigate varying types of geomagnetic storms, but they should also look into the interaction between these events and the atmospheric conditions that fluctuate in tandem with the solar cycle. The research team’s ability to utilize cutting-edge modeling allows for exploration into these complex relationships, which are essential for predicting future atmospheric behavior and its implications for technology.

As the satellite industry and research institutions work together to navigate the changing landscape of space weather, the study represents a significant leap forward in our understanding of how climate change may redefine solar impacts on our atmosphere. The urgency for deeper research into geomagnetic storms and their ramifications is underscored by our reliance on satellites for everyday functions. Ultimately, the findings not only call for immediate reflection but also pave the way for proactive measures to ensure the safety and longevity of satellite operations amidst an evolving atmosphere.

Understanding these outcomes becomes increasingly pivotal for future explorations and technology designed to operate in a technologically sensitive environment. As we venture further into the complexities of atmospheric science and its ramifications, this research provides a potent reminder that, while atmospheric transformations can be daunting, they also offer pathways for innovation and resilience within our satellite technologies.

Subject of Research: Geomagnetic storms and their effects on the upper atmosphere and satellite operations due to rising carbon dioxide levels.

Article Title: Impact of Increasing Greenhouse Gases on the Ionosphere and Thermosphere Response to a May 2024-Like Geomagnetic Superstorm

News Publication Date: 14-Jun-2025

Web References: Link to the DOI

References: Geophysical Research Letters

Image Credits: National Center for Atmospheric Research

Keywords

Geomagnetic storms, carbon dioxide emissions, satellite operations, atmospheric density, solar activity, climate change, upper atmosphere, National Science Foundation, advanced modeling, space weather, navigation systems, technological resilience.