Exploratory Statistical Sensitivity Analysis of Correspondences Between a Historical Text and Multi-Domain Observational Records: A Surrogate- and Monte Carlo-Based Framework (AGU 2025 Draft)

This upload contains the full LaTeX source, figures, bibliography, and compiled PDF for an exploratory statistical study submitted in AGU (JGR: Atmospheres) format. The study investigates nine pre-specified correspondences between statements in a historical text and multi-domain observational datasets (astrophysical, solar, and atmospheric). The methodological framework includes:- Pre-specified hypotheses (n = 9)- Null models (Gaussian and log-normal distributions)- Bootstrap resampling (N = 10,000)- Surrogate timing tests (N = 10,000)- Monte Carlo pseudo-text sampling (N = 10^6)- Bonferroni correction for multiple comparisons This work is strictly exploratory in nature. No causal, predictive, or metaphysical claims are made. All results are conditional on model assumptions and are intended to evaluate statistical sensitivity under explicit null frameworks. Datasets used include NASA, Fermi/GBM, SDO, and MERRA-2 public archives. This version corresponds to the AGU 2025 submission draft and is intended for open scientific reproducibility and peer review discussion.