Do major world events cluster under specific solar and geomagnetic conditions, and if so, can those conditions be tracked before the event occurs?
That is the question Chaerus is built on.
Not as metaphor. Not as prediction. Not as certainty.
As a measurable, testable, statistical question using publicly available solar wind data, matched-control methodology, and near-real-time geomagnetic observation.
Chaerus begins from a simple premise drawn from nonlinear systems: some environments may resist precise prediction while still showing structure. A system does not have to be random simply because its exact path cannot be forecast. It may move through patterns, thresholds, feedback states, and boundaries that can be observed over time.
Some world events show an association with certain periods of geomagnetic quietude and disturbed solar conditions, varying by event type.
The same signature appears across multiple independently tested event categories. The strength varies by category. The research documents a statistical association. No causal mechanism has been established.
Very few people think of space weather as having an influence on world events or on people. Research outside this project has shown that certain solar and geomagnetic conditions, combined with location and season, can influence biological systems.
Consider how a major weather system develops. No single factor creates it. Sea surface temperatures have been elevated for weeks. Atmospheric pressure gradients have been building. A front stalls in a particular position. Humidity accumulates. None of these factors alone produces the storm. But when they stack within the right window, a relatively small change is enough to trigger a rapid and large-scale transition. A meteorologist cannot say exactly when that transition will occur or what form it will take. But they can observe the accumulated conditions and recognize that the system has entered a state that has preceded major transitions before.
That is not prediction. That is pattern recognition applied to a complex environment under observable stress.
The same logic applies to social, political, and geophysical systems. Any system already under multiple stressors does not require a large trigger to cross a threshold. What matters is the stacking of conditions and the timing. A country under economic strain, drought, political instability, and biological load is not in the same risk state as a stable country facing one of those factors in isolation.
This is what Chaerus and Caemira track. Not that geomagnetic conditions are elevated today and therefore something will happen. But that when solar and geomagnetic conditions, seasonal influences, and existing systemic stressors stack within a particular window, the system has historically shown a higher association with major event clustering.
The research does not claim that a geomagnetic condition determines an event. It does not claim that a specific day can be forecast with certainty. It does not claim causation.
It identifies a recurring field condition associated with major events and makes that condition visible in near-real-time.
This is closer to risk intelligence than prediction.
The signal is probabilistic. It does not say what will happen. It shows when the system is occupying a state that has appeared more often around past event clusters than matched controls.
The value is not certainty. The value is visibility.
Chaerus is not a prediction engine.
The research makes no causal claim. There is no established mechanism that fully explains why world events cluster during geomagnetic quietude. The papers document a statistical relationship under rigorous controls. That is the honest scope of the claim.
What it shows is that the geomagnetic environment is not neutral with respect to when major events occur, and that the structure of that relationship is observable in near-real-time.
That is what Chaerus tracks.
The primary researcher has several papers at various stages of publication, appearing across multiple academic networks.
The foundational matched-control study. Event-day quietude signature across 463 events and 36 geomagnetic features.
Distributed in Social Physics · Environmental Data Analysis
Cross-category replication. The signature tested independently across nine event categories.
Distributed in Social Physics · Scheduled in Environmental Data Analysis
Seven-day pre-event temporal structure analysis.
Distributed in Social Physics · Scheduled in Environmental Data Analysis
Full cross-domain replication spanning civil unrest, armed conflict, financial markets, pandemics, and beyond.
Distributed in Social Physics
A theoretical framework proposing that trauma disrupts neural oscillatory coherence in a manner analogous to a detuned instrument. Individual alpha frequency as a stable neurophysiological baseline; trauma-induced detuning as a measurable state with pathways for restoration.
Distributed in Decision Neuroscience and Econometrics
The geomagnetic studies use the NASA OMNI-2 dataset, a 463-event catalog from 2010 to 2024, solar-regime-matched controls, and Wilcoxon signed-rank tests with Benjamini-Hochberg false discovery rate correction.
The research is independent, unfunded, and not affiliated with any institution.