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Magnetotelluric sampling and geoelectric hazard estimation: Are national-scale surveys sufficient?

At present, the most reliable information for inferring storm-time ground electric fields along electrical transmission lines comes from coarsely sampled, national-scale magnetotelluric (MT) data sets, such as that provided by the EarthScope USArray program. An underlying assumption in the use of such data is that they adequately sample the spatial heterogeneity of the surface relationship between geomagnetic and geoelectric fields. Here, we assess the degree to which the density of MT data sampling affects geoelectric hazard assessments. For electrical transmission networks in each of four focus regions across the contiguous United States, we perform two parallel band-limited (10 1 –10 3 s) hazard analyses: one using only USArray-style (∼70-km station spacing) MT data, and one incorporating denser (≪70-km station spacing) MT data. We find that the use of USArray-style MT sampling alone provides a useful first-order estimate of integrated geoelectric fields along electrical transmission lines. However, we also find that the use of higher density MT data can in some areas lead to order-of-magnitude differences in line-averaged electric field estimates at the level of individual transmission lines and can also yield significant differences in subregional hazard patterns. As we demonstrate using variogram plots, these differences reflect short-spatial-scale variability in Earth conductivity, which in turn reflects regional lithotectonic structure and history. We also provide a cautionary example in the use of electrical conductivity models to predict dense MT data; although valuable for hazard applications, models may only be able to reproduce surface geoelectric fields as captured by the MT data from which they were derived.

AGU Space Weather↗

Major space weather risks identified via coupled physics–engineering–economic modeling

Space weather poses an important but under-quantified threat to society. While severe geomagnetic storms are recognized as potential global catastrophes, their socio-economic impacts remain poorly quantified. We present a novel physics-engineering-economic framework that links geophysical drivers to power grid geoelectric fields, transformer vulnerability, and macroeconomic consequences. Using the United States as an example, we estimate daily economic losses for a 250-year geomagnetic storm from transformer thermal heating of 1.81 billion USD (95 percent confidence interval: 1.65 to 1.96 billion USD), disrupting power for approximately 5.1 million people and 135,000 businesses. These estimates are conservative lower bounds, reflecting only transformer thermal heating effects and excluding voltage collapse, cascading failures, and restoration costs. The true societal risk could be substantially higher. Nonetheless, this contribution provides the first nationwide end-to-end coupling from space physics to potential macroeconomic loss, with quantified uncertainties. Our results demonstrate that coupled socio-economic modeling of space weather is feasible and essential, and the framework is scalable and transferable, offering a template for assessing space weather risk to critical infrastructure in other countries.

AGU Advances↗