A Simple Way to Measure El Niño — Three Numbers, No Supercomputer Needed

This research note presents a simple measurement framework for detecting and characterizing El Niño events using only three structural numbers derived from NOAA ONI data (1950–2025). The method requires no supercomputer — 200 lines of Python, 1 second of CPU time, and publicly available data. Key findings: - Event-level detection: 92% sensitivity (23/25 events detected using 5+ consecutive overlapping seasons with ONI ≥ +0.5°C threshold) - Structural asymmetry: El Niño and La Niña are not symmetric opposites — the three numbers reveal a unidirectional threshold where warm extremes (El Niño) produce clear signals while cool extremes (La Niña) barely register - Top 10 anomaly months: 8/10 are El Niño, only 2 are La Niña - The measurement instrument Ô (curl, helicity, balance) — originally developed for LLM jailbreak detection — generalizes to climate data, confirming a cross-domain structural invariant This is the first empirical leg of the Ô cross-domain measurement framework.