Sealing Every Step: A Pre-Registered Search for GOES-16 Lightning Precursors of Tornado Touchdown, and a Positive Control the Instrument Did Not Pass

Abstract

We report, in full, a line of research that asked whether the spatial arrangement of lightning observed from geostationary orbit (GOES-16 Geostationary Lightning Mapper, GLM) changes at the moment a violent tornado touches down, and then asked whether our instrument could recover even the best-known lightning signal of severe storms, the lightning jump. Every test was sealed (design, case list and code fixed by SHA-256 before any data were read), the AI partner wrote a sealed prediction before each run, each test was run once, and the verdict was taken from a pre-stated rule (R reproduced / F not reproduced / U unresolved). The flash-arrangement hypothesis H_spread (the mean ternary shell index of flashes rises after touchdown) was never established: U in three tracked tests (the closest, OOS-4, combined p = 0.0106 against a 0.01 threshold), and F with a tracking-free moving-disk reader on 40 new EF3 tornadoes (n = 26, combined p = 0.106, mean effect +0.059, 95% CI [-0.018, +0.137]). The effect estimate changed sign with the reader radius. Four sealed positive controls then tested the instrument: lightning jumps did not stand out before touchdown (p = 0.924) or before the first severe report (p = 0.807), did not separate severe from matched non-severe storms (McNemar p = 0.773), and a faithful cell-based reproduction of the Schultz 2-sigma algorithm, with its activation threshold re-derived for GLM by the original definition (35.2 flashes/min), reached literature-level scores (POD 0.31, FAR 0.63, CSI 0.26) that a timing-shuffled null matched (CSI 0.283; p = 0.906). We therefore do not claim that no precursor exists; we claim that with GLM total lightning, these readers and these anchors, none is visible, and that the instrument has not been shown sensitive enough for absence to mean much. The record of how each negative was protected from optimistic re-reading is the main contribution. Data and code. Scripts (AGPL-3.0-or-later), all seals with SHA-256 files, case sheets, prediction texts and result files are provided as Bridge_Paper_Lightning_scripts.zip. GLM data: NOAA GOES-16 on AWS (noaa-goes16). AI use. Designs, code, analyses and text were produced by Kurado (Claude Opus 5.5, Anthropic) working with M. Watabe, who chose every direction and supplied all data.