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March 14, 20261 citationsOpen Access

INFRAS-CLOUD: Infrasonic Network for Real-time Atmospheric Signatures — Continuous Low-frequency Observatory for Unresolved Dynamics

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SBSamir Baladi

Key Points

  • To develop and validate an Atmospheric Infrasonic Severity Index (AISI) for classifying severe weather events.
  • Used eight acoustic parameters to compile the AISI via PCA-regularized logistic regression.
  • Validated the AISI across 1,847 events from 47 IMS stations over 20 years.
  • Released as an open-source Python package.
  • Achieved 93.1% classification accuracy across six categories of severe weather.
  • Detected tropical cyclone signals at ranges up to 4,200 km.
  • Estimated volcanic energy within 10% of seismic benchmarks.

Abstract

INFRAS-CLOUD presents a physics-informed eight-parameter Atmospheric Infrasonic Severity Index (AISI) for real-time classification of severe weather, volcanic, and ocean-atmosphere infrasonic events. Eight governing acoustic parameters — spectral peak frequency (fₚ), microbarom amplitude (Pᵤb), azimuthal arrival angle (θ), stratospheric ducting efficiency (Dₛtr), phase velocity (vₚh), inter-station coherence (γ²), atmospheric absorption coefficient (αₐir), and signal-to-noise ratio (SNR) — are integrated via PCA-regularized logistic regression into a single composite severity score (AISI). Validated across 1, 847 events from 47 International Monitoring System (IMS) stations spanning 2005–2025, INFRAS-CLOUD achieves 93. 1% classification accuracy across six source categories (tropical cyclones, tornadoes, volcanic explosions, microbaroms, mountain-associated waves, anthropogenic). Key results include: tornado precursor lead times of 12–28 minutes prior to NWS confirmation; tropical cyclone detection at ranges up to 4, 200 km; volcanic energy estimation within 10% of independent seismic benchmarks (Hunga Tonga 2022: 38 ± 4 MT TNT) ; and stratospheric wind inversion accurate to ±7. 8 m/s without radiosonde requirements. The AISI framework is released as an open-source Python package (pip install infrascloud) under MIT License.

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Cite This Study

Samir Baladi (2026) studied this question.

synapsesocial.com/papers/69b4ad7918185d8a39800bd9https://doi.org/10.5281/zenodo.18952438
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