Searcharxiv⌕ Search

arXiv subjects

M. J. Wiltberger

Publications and source records attributed to M. J. Wiltberger.

2 recordsLinked to original sources

C-SWIM: A Coupled Space Weather Impact Model for Satellite Fleet Vulnerability and Economic Loss Under a 1-in-100-Year Solar Energetic Particle Event

Modern economies depend critically on satellite infrastructure, yet the aggregate economic consequences of extreme solar energetic particle (SEP) events have not been rigorously assessed. This study develops an integrated framework linking SEP hazard characterization, dynamic geomagnetic cutoff rigidity modeling, radiation dose transport, and fleet-wide failure probability estimation to macroeconomic impact analysis. Using extreme-value analysis of 160 SEP events over 27.4 years (1996-2025), failure probability is estimated for ~10,650 US operational satellites under orbital regime-dependent shielding assumptions. The assessment reveals that ~100 satellites (1.0%) are at Critical risk, concentrated in high-altitude low Earth orbit and highly elliptical orbit, while medium Earth orbit and geosynchronous orbit satellites fall in the Negligible class (P_fail < 10^-9) under the assumed radiation-hardened components and shielding. The expected capital loss across the ~$254B fleet totals ~$5.2B. Three failure scenarios, expanding from Critical satellites only (P_fail > 10^-2), to Critical and Elevated (P_fail > 10^-3), and to all satellites with non-negligible risk (P_fail > 10^-6), yield daily economic impacts of ~$70M, ~$270M, and ~$1.3B, respectively. Earth observation suffers up to 95.6% capacity loss in the worst case, while military services experience 16.1-20.4% disruption across scenarios. Results are first-order estimates: hardware failure counts are conservative because only total ionizing dose is modeled, and daily economic impacts represent upper bounds because operator response and recovery are not included.

physics.space-ph↗

GIC--Related Observations During the May 2024 Geomagnetic Storm in the United States

The May 2024 geomagnetic storm was one of the most severe in the past 20~years. Understanding how large geomagnetic disturbances (GMDs) impact geomagnetically induced currents (GICs) within electrical power grid networks is key to ensuring their resilience. We have assembled and synthesized a large and unique set of GMD-related data, compared model predictions with measurements, and identified empirical relationships for GICs in the contiguous United States for this storm. Measurement data include GIC data from $47$ sites and magnetometer data from $17$ sites. Model data include GIC computed by the Tennessee Valley Authority (TVA) power system operators at $4$ sites, GIC computed using a reference model at $47$ sites, and the difference in the surface magnetic field from a baseline ($Δ\mathbf{B}$) computed at $12$ magnetometer sites from three global magnetospheric models -- the Multiscale Atmosphere-Geospace Environment Model (MAGE), Space Weather Modeling Framework (SWMF), and Open Geospace General Circulation Model (OpenGGCM). GIC measured and computed by TVA had a correlation coefficient $\text{r}>0.8$ and a prediction efficiency between 0.4 and 0.7. The horizontal magnetic field perturbation from a baseline, $ΔB_H$, computed by MAGE, SWMF, and OpenGGCM had a correlation r from $0.21$ to $0.65$. Two empirical relationships were considered: (1) how the correlation between measured GIC site pairs depended on differences in site separation distance, $β$ scaling factor (related to ground conductivity), and geomagnetic latitude; and (2) a regression model for the maximum $\mbox{GIC}$ magnitude at each site given the product of $α$ (related to magnetic latitude) and $β$.

physics.space-ph↗