> ## Content Index > Fetch the complete content index at: https://www.riskmarketnews.com/llms.txt > Use this file to discover other available public pages before exploring further. # Space Weather Models May Be Measuring the Wrong Risk - URL: https://www.riskmarketnews.com/space-weather-models-may-be-measuring-the-wrong-risk/ - Published: 2026-08-27T14:09:40.000Z - Updated: 2026-08-27T14:09:40.000Z - Description: A new model of solar-storm risk exposes a fundamental problem: the metric used to measure the hazard may not capture the forces that actually cause trillions of dollars in physical losses. - Author: Risk Market News - Tags: Models The standard metric used to model extreme solar storms may not adequately measure the physical forces that actually destroy infrastructure, creating potentially enormous uncertainty around a risk that could produce trillions of dollars in losses. [A new report from Mission Space ](https://www.mission.space/?ref=riskmarketnews.com)detailing new Solar Storm Economic Exposure Model estimates that space weather produces $20.6 billion in annualized expected losses globally and that a Carrington-class solar storm ([the most intense geomagnetic storm in recorded history](https://www.nesdis.noaa.gov/about/k-12-education/space-weather/what-was-the-carrington-event?ref=riskmarketnews.com)) could generate roughly $2.4 trillion in losses today. But the report also exposes a fundamental weakness underneath those numbers: both the frequency of extreme storms and the relationship between storm intensity and physical damage remain deeply uncertain. According to the report, the center of the problem is **Dst**, or disturbance storm time, a standard measure of geomagnetic storm intensity and one of the foundations for estimating the frequency of extreme events. But Dst is not what damages transformers. Physical damage is more directly related to how rapidly Earth's magnetic field changes — known as **dB/dt** — and the resulting geoelectric fields and geomagnetically induced currents that can flow through transmission systems. “Dst is a proxy for the wrong quantity,” Mission Space says. The distinction isn't academic and translates into really financial loss. An August 1972 solar storm registered a Dst of only −154 nT but produced a 64% voltage collapse on the North Dakota-Manitoba interconnection. It also caused Intelsat IV F-2 to lose 5% of its solar-panel output — roughly two years of normal degradation — while a DSCS II satellite suffered a mission-ending power failure. Mission Space calls the event “the clearest demonstration in the record that Dst is a poor proxy for damage.” That creates a familiar catastrophe-modeling problem: estimating the probability of the hazard is only useful if the hazard metric maps reliably onto the mechanism that produces physical loss. In this case, even the probability is unsettled. Published estimates of Carrington-class storm frequency range from 0.46% to 12% per decade — a factor of 26\. Running those assumptions through SSEEM moves annualized expected loss from approximately $5.9 billion to $35.3 billion without changing the underlying exposure. Mission Space calls the recurrence rate “the single largest source of uncertainty in the paper.” ![](https://storage.ghost.io/c/5f/d8/5fd861a0-e273-43de-ac77-c473390d89d5/content/images/2026/08/MissonSpace.png) The severity assumption may now be changing as well. Research published in *Nature* in July [analyzed more than one million solar-wind observations ](https://www.nature.com/articles/s41586-026-10757-4?utm%5Fsource=chatgpt.com)and concluded that the apparent saturation of Earth's geomagnetic response during extreme conditions is partly an artifact created by measurement uncertainty. Correcting for it suggests that extreme geomagnetic impacts could be twice as large as previously thought. Mission Space applies that finding as a sensitivity rather than its base case. The result nearly doubles its Carrington-class loss estimate from $2.4 trillion to $4.8 trillion, while annualized expected loss rises from 420.6 billion to 437.8 billion. The new result, the report notes, “has not been absorbed into commercial catastrophe models, national benchmarks or the NERC planning standard.” Meanwhile, the vulnerability side of the model is constrained by another problem: there isn't enough loss data. Thirty-one of SSEEM's 45 severity cells carry low confidence because commercial satellite operators generally do not publish storm-attributable equipment anomalies, propellant consumption or revenue impacts. The model therefore relies heavily on structured judgment for orbital losses. “What would change this analysis most is not a better model but disclosure,” the report says. The largest modeled physical exposure, however, remains firmly on Earth. Power grids account for $12.9 billion, or roughly 62%, of current annualized expected loss. Geomagnetically induced currents can overheat transformer components and degrade insulation, with some failures not appearing until weeks or months after a storm — potentially causing historical loss records to undercount the damage. And the severity of a physical loss increasingly depends on how quickly the equipment can be replaced. Large-transformer delivery times have increased from less than 12 months before 2020 to 36 to 60 months, while 82% of large transformers used in the U.S. are imported. Existing spare programs were generally designed around conventional equipment failures rather than a correlated event damaging transformers across multiple substations simultaneously. ## Sign up for Risk Market News Risk, models and markets Subscribe Email sent! Check your inbox to complete your signup. No spam. Unsubscribe anytime. Insurance introduces another disconnect between modeled economic loss and physical damage. Transformer damage is generally covered, but business-interruption policies typically require physical damage at the insured location. A factory shut down because distant grid equipment fails may therefore suffer a significant economic loss without triggering coverage. Aviation rerouting, satellite station-keeping and GNSS-related agricultural disruption present similar problems. “Coverage follows breakage; the loss does not,” Mission Space says. That leaves insurers, infrastructure owners and investors confronting an unusually difficult modeling problem: the probability of the extreme event remains disputed, its potential severity may have just doubled, and the standard measure of the hazard may not adequately describe the physical mechanism producing the loss. The consequences are growing because the amount of capital sitting in the path of that risk is expanding rapidly. The commercial satellite industry generated $303 billion in revenue in 2025, while a record 4,434 satellites were launched during the year, up 65% from 2024, bringing the operational fleet to more than 14,000 satellites, according to the[ Satellite Industry Association's 2026 industry report](https://sia.org/affordability-productivity-drive-historic-satellite-industry-growth-satellite-industry-association-releases-29th-annual-state-of-the-satellite-industry-report/?utm%5Fsource=chatgpt.com). That growth has already moved decisively into public capital markets: SpaceX completed its IPO in June, pricing shares at $135 and raising $75 billion in the initial offering at a roughly $1.77 trillion valuation, the largest IPO on record. The result is a widening gap between the speed at which financial exposure is accumulating in space and the maturity of the models available to measure how much of that capital could be lost in an extreme solar event.