PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
March 14, 20260 citationsOpen Access

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

View Full Paper
SBSamir Baladi

Key Points

  • To develop and validate an Atmospheric Infrasonic Severity Index for real-time classification of severe weather and infrasonic events.
  • Introduced a composite severity score integrating eight acoustic parameters using PCA-regularized logistic regression.
  • Validated across 1,847 infrasonic events from 47 IMS stations from 2005 to 2025.
  • Employed real-time data analysis for classification accuracy.
  • Achieved 93.1% classification accuracy across six source categories.
  • Successfully predicted tornado precursors with lead times of 12–28 minutes.
  • 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.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Samir Baladi (2026) studied this question.

synapsesocial.com/papers/69b4ba3618185d8a39802e83https://doi.org/10.5281/zenodo.18952437
Ask AI
Helpful
Bookmark
Share
View Full Paper