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Demonstrates a predictive model for natural disasters using solar incoherence, indicating potential risk assessment benefits.
A first-principles predictive model for 10 Earth-based natural disaster types derived from McCaul's Law of Coherence and Tree-Earth Dendritic Synaptic Theory (TDST). Transfer function: Φ_litho = Φ_solar × 0.679. Each disaster profiled across all 6 pillars (S_a, E_d, R_p, N_r, T_s, F_g). 8 solar incoherence event types mapped. Continuous Φ_solar scan produces disaster risk windows. Time lags: tornado 2h, wildfire 24h, hurricane 7d, drought 90d, earthquake 1yr. Historical retrodiction: 4/6 HIGH, 2/6 MED. Predictive confidence: geomagnetic storm 0.91, drought 0.74, wildfire 0.72, earthquake 0.31. Proposed next step: real-time NOAA SWPC Φ_solar monitor with 90-day pilot validation.
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Justin McCaul (2026) studied this question.
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