Yeah, whether the current (2026) El Niño ranks as a record depends on the metric, region, and baseline used by different agencies.

Britain’s Met Office has described this year’s event as “unprecedented”, citing absolute (raw) sea- surface temperatures in the central equatorial Pacific that have surpassed levels from previous El Niños.

Japan’s Meteorological Agency (JMA) declared it the strongest on record. In September 2026, the sea-surface temperature anomaly in the Niño 3 region (eastern Pacific) reached +4.0°C, exceeding the previous high of +3.6°C from December 1997 (records back to 1949). JMA states the strongest conditions are virtually certain to continue into boreal winter.

U.S. NOAA (which primarily monitors the neighboring Niño 3.4 region in the east- central Pacific) has not yet called it the outright record in its books.

It defines El Niño via temperatures at least 0.5°C above normal plus atmospheric coupling (e.g., weakened trade winds and shifted rainfall). Due to accelerating climate change and widespread ocean warming, NOAA now emphasizes the Relative Oceanic Niño Index (RONI). RONI uses a 30- year baseline but measures how warm the east- central Pacific is relative to the rest of the tropical oceans, because that contrast better drives the weather impacts of interest.

NOAA projects a high chance (about 83% for the October- December 2026 average) that the three- month RONI anomaly will reach +2.5°C or higher. That threshold would make it the strongest in NOAA’s records (back to 1950), surpassing the major events of 1982- 83, 1997- 98, and 2015- 16.

As of early October discussions, it was strengthening, with recent Niño-region anomalies already very high (e.g., conventional weekly Niño 3.4 readings around +3°C or more in some reports).

Why the rankings differ

• Regions: JMA focuses on Niño 3 (farther east); NOAA on Niño 3.4 (east- central).
• Absolute temperatures vs. anomalies: Raw warmth can set records more easily in a warming climate; anomalies measure departure from a baseline.
• Traditional vs. relative indices: Older Oceanic Niño Index (ONI) approaches have been adjusted or supplemented by RONI (and similar relative measures used by other agencies) to better isolate the ENSO signal from background tropical warming. This can change how strong past and present events appear relative to one another.

Climate scientist Emily Becker of the University of Miami noted that by any measure it is a very strong El Niño; only after it ends will its full ranking in historical context become clear. It remains an important opportunity to study a powerful event amid ongoing global warming.⁠

In short, Japan and the UK are already treating aspects of it as record or unprecedented, while NOAA sees a strong- to- very- strong event with a high (but not yet locked- in) probability of setting a RONI- based record.

The Relative Oceanic Niño Index (RONI) is NOAA’s Climate Prediction Center (CPC) primary metric for monitoring and classifying El Niño and La Niña events, adopted officially in February 2026.

It improves on the traditional Oceanic Niño Index (ONI) by better accounting for background tropical ocean warming due to climate change.

Why RONI Was Introduced

Traditional ONI measures sea- surface temperature (SST) anomalies in the Niño 3.4 region relative to a fixed (but periodically updated) 30- year climatology. In a warming climate, this baseline lags, which can distort classifications,especially in real time,and weaken the link between the index and actual atmospheric impacts (e.g., rainfall shifts and teleconnections).

RONI addresses this by focusing on the relative warmth or coolness of the Niño 3.4 region compared to the broader tropics, which better captures the ocean-atmosphere contrast that drives ENSO effects.

How RONI Is Calculated

1. Start with the Niño 3.4 anomaly: Compute the monthly SST anomaly in the Niño 3.4 region (5°N-5°S, 120°- 170°W), relative to a 30- year base period (currently 1991- 2020 in many operational products; the base period follows WMO standards and is updated periodically). This is the same starting point as the traditional ONI. Data typically come from Extended Reconstructed SST (ERSST) versions (v5 or v6).⁠
2. Subtract the tropical- mean anomaly: Subtract the average SST anomaly over the entire global tropics (20°S–20°N) for the same period. This removes the broad-scale tropical warming signal, isolating the Pacific’s relative anomaly.⁠
3. Apply a scaling (rescaling) factor: Multiply the difference by a factor so that the overall variance (standard deviation) of the relative index matches that of the traditional Niño 3.4/ONI series. The scaling is often computed separately by calendar month or season (largest in March- May, smallest in July- August) using a historical reference period (e.g., 1950- 2020). The formula is approximately:$$\text{Relative Ni}\tilde{\text{n}}\text{o 3.4}=(\text{Ni}\tilde{\text{n}}\text{o 3.4 anomaly}-\text{Tropical-mean anomaly})\times \frac{{\sigma }_{\text{ONI}}}{{\sigma }_{(\text{ONI}-\text{TropAve})}}$$​​where $\sigma$σ denotes the standard deviation.
4. Form the seasonal index: RONI is the three- month running mean (overlapping seasons: DJF, JFM, FMA, etc.) of the relative Niño 3.4 values.

Classification Rules (Unchanged from ONI)

• El Niño: RONI ≥ +0.5°C.
• La Niña: RONI ≤ −0.5°C.
• Neutral: between −0.5°C and +0.5°C.
• A full “episode” requires the threshold to be met for at least five consecutive overlapping three- month seasons. Strength categories (weak, moderate, strong, very strong) follow similar incremental thresholds (e.g., ≥ +2.0°C often considered very strong/historic in forecasts).

Key Advantages and Effects

• Reduced sensitivity to base period: Classifications of past events are more stable across different climatologies and less affected by the long- term warming trend.
• Better physical relevance: More closely tied to the relative SST gradients that influence atmospheric circulation, rainfall, and teleconnections (e.g., sharper relationships with precipitation and upper- level heights over places like Australia and the U.S.).
• Real- time reliability: Less lag from updating climatologies.
• Impacts on historical record: Some events are reclassified (e.g., certain weak El Niños disappear or weaken; some La Niñas strengthen or become continuous; the 2023- 24 El Niño often appears moderate rather than strong under RONI). Overall variance is preserved by the scaling, so extremes are not systematically damped or amplified across the whole record.

RONI is based on work by van Oldenborgh et al. (2021) and formalized/extended for operational use by L’Heureux et al. (2024) in the Journal of Climate. NOAA maintains both RONI and traditional ONI data for continuity, with RONI now primary for advisories and forecasts. Official values and historical tables are available on the CPC website (updated monthly, with recent values potentially provisional due to data filtering).

In short, RONI keeps the familiar structure and thresholds of ONI while measuring the ENSO- relevant contrast rather than absolute regional anomalies, making it more robust in a warming world.