ONI vs RONI — Why the Way We Measure El Niño Just Changed,
and What It Means for Commodity Markets

Why ENSO Is a Market Signal, Not Just a Weather Story

This is not a climate science tutorial. The reason commodity traders track El Niño and La Niña is blunt: ENSO is among the most powerful systematic drivers of supply disruption across the agricultural and energy complex, and it operates on a known schedule with measurable advance warning. Getting the signal right has direct P&L consequences.

The mechanism

ENSO — El Niño–Southern Oscillation — describes a recurring pattern of sea surface temperature (SST) anomalies in the tropical Pacific Ocean and the atmospheric responses they trigger. When the east-central Pacific runs anomalously warm (El Niño), it disrupts the Walker Circulation: the large-scale atmospheric system that connects Pacific ocean temperature to rainfall patterns across Asia, the Americas, Africa, and Australia. La Niña, the cool phase, produces roughly opposite effects in most regions. The oceanic signal precedes the atmospheric and terrestrial impacts by months, which is what makes ENSO a leading indicator rather than a contemporaneous one.

The commodity impact map

Different commodities respond differently depending on where they are grown and the specific teleconnection pattern in that region. Teleconnections are the atmospheric pathways through which ocean temperature anomalies in one region — the tropical Pacific — produce drought, rainfall, or temperature shifts in distant growing regions thousands of miles away. They are the mechanism that makes a Pacific Ocean event relevant to a coffee farmer in Minas Gerais or a wheat grower in Western Australia. El Niño and La Niña do not produce uniform effects — they produce regionally specific ones, and the same event that dries one growing region can drench another.

Arabica coffee (Brazil, Minas Gerais): El Niño typically produces drier conditions during the critical flowering and fruit-setting periods, elevating supply risk. Brazil represents approximately 35–40% of global arabica supply, making this the single most consequential ENSO-to-coffee-price link. Research indicates that arabica prices show significant asymmetric responses to El Niño at lags of 13–15 months. The reason is the coffee plant's biological cycle. El Niño typically stresses Brazilian growing regions during the September–November flowering window — roughly 3–4 months after a mid-year event onset. From flowering to harvest-ready cherry takes another 8–9 months. By the time the reduced harvest is confirmed and begins appearing in export flows, the cumulative lag from ENSO onset to observable price impact is 13–15 months. This is the biology of the crop, not a market inefficiency. It means a trader who correctly identifies an El Niño event in mid-year has a meaningful position-building window before the supply impact is fully priced — measured in months, not days.

Arabica coffee (Central America, Colombia, Ethiopia): Regional effects diverge sharply. El Niño dries Central America and parts of the Colombian highlands, while bringing increased warmth and moisture to parts of southern Brazil. Ethiopia's long rains (the Kiremt season, June–October) drive the main crop and are sensitive to ENSO-related circulation shifts over East Africa. The same El Niño event can simultaneously stress Central American crops and benefit Brazilian production — requiring region-specific analysis rather than a single "El Niño = bearish coffee" heuristic.

Robusta coffee (Vietnam, Indonesia): The Central Highlands of Vietnam and the Lampung region of Indonesia are the dominant robusta production zones. Vietnam's robusta is sensitive to different ENSO-driven teleconnections than Brazilian arabica, and robusta prices show less clear asymmetric ENSO response than arabica — partly because robusta's growing conditions (lower altitude, higher heat tolerance) differ, and partly because the teleconnection pattern in Southeast Asia operates through a different atmospheric pathway.

Grains: Australian wheat is highly sensitive to El Niño, which produces drier conditions across the wheat belt and is associated with below-average yields in strong events. Indian monsoon crops (rice, pulses) are affected by El Niño's tendency to weaken the South Asian monsoon. US corn belt impacts are more variable, but La Niña's association with drier conditions in the southern plains creates meaningful HRW wheat and cotton supply risk.

Energy: El Niño correlates with warmer-than-normal winters across the northern US, suppressing heating demand and acting as a seasonal bearish signal for natural gas. La Niña produces colder winters across the northern tier — the inverse. The correlation is well-established but not deterministic at the individual-month level.

How ONI Works — and the Structural Problem It Has in a Warming World

The Oceanic Niño Index (ONI) is the 3-month running mean of sea surface temperature anomalies in the Niño-3.4 region of the Pacific Ocean (5°N–5°S, 120°W–170°W). An event is classified as El Niño or La Niña when the ONI exceeds ±0.5°C for five consecutive overlapping 3-month seasons. These rules are unchanged under RONI — the classification framework is the same. What changes is what the number means.

The baseline problem

An "anomaly" requires a reference. ONI measures departures from a 30-year climatological average, following World Meteorological Organization practice. That baseline is updated every five years — the current standard uses 1991–2020. The underlying assumption is that 30 years is long enough to average out ENSO variability itself, leaving a stable reference point.

That assumption held reasonably well for most of the 20th century. It is increasingly problematic now. The global tropical ocean is warming due to climate change, and it is warming faster than the 30-year rolling baseline can absorb. The result is a systematic upward bias in ONI values: years that would have been classified as Neutral against a fixed climatology register as weak El Niño events against a baseline that has not caught up with actual warming trends.

What this means in practice

Consider the following: if the entire tropical Pacific is 0.5°C warmer than it was in 1991 — as part of a long-term climate trend — an ONI reading of +0.6°C looks like a weak El Niño. But if the rest of the tropics warmed by the same 0.5°C, then the east-central Pacific isn't anomalously warm relative to its surroundings. The Walker Circulation hasn't changed. No ENSO teleconnection has been triggered. The commodity impacts that traders are expecting won't materialize.

This is not a theoretical concern. It is the documented cause of several recent misclassifications. Three El Niño winters — 1958–59, 2014–15, and 2019–20 — are no longer classified as El Niño under RONI. The atmospheric coupling that should accompany a true El Niño event was absent or weak in each case. RONI, by comparing the Niño-3.4 region to the rest of the tropics rather than to its own historical average, correctly identified that those years did not represent a genuine ENSO signal.

What RONI Measures and Why It Asks a Better Question

The Relative Oceanic Niño Index (RONI) starts with the same Niño-3.4 SST anomaly data as ONI. The key difference is what it compares that value against.

The RONI formula subtracts the average SST anomaly across the entire global tropical belt (20°S–20°N) from the Niño-3.4 anomaly. The result is then scaled so that the overall variability matches ONI — preserving the familiar numerical range while removing the background warming component. The same thresholds (±0.5°C) and the same duration requirement (five consecutive overlapping seasons) are unchanged.

Why the relative question is physically correct

The atmospheric circulation patterns that produce ENSO's commodity-relevant teleconnections — the Walker Circulation, trade wind anomalies, monsoon shifts — are driven by temperature contrasts, not by absolute temperature. A uniformly warm tropical ocean does nothing to shift rainfall patterns. What matters to the atmosphere is whether the east-central Pacific is warmer or cooler relative to the broader tropics.

When global warming raises ocean temperatures across the entire tropical belt equally, it doesn't create an ENSO-type circulation anomaly. ONI counts that uniform warming as part of the El Niño signal. RONI removes it. The result is an index that more faithfully represents the physical mechanism that actually drives the weather patterns commodity traders care about.

The transition is official

NOAA's Climate Prediction Center began officially using RONI as the primary standard for ENSO advisories and event classifications in 2025–26. Historical ENSO records are being retroactively reevaluated using RONI. CPC will maintain RONI values for the full historical record, but RONI is now the governing index for official advisories — not a supplementary index.

The Historical Reclassifications — What Changed and Why It Matters

The transition to RONI is not purely prospective. Historical ENSO classifications have changed. For commodity traders who rely on historical analog years, this matters directly.

Why RONI Produces Better Commodity-Relevant Signals

The case for RONI is not just that it corrects a measurement artifact. It is that the corrected measurement is more tightly aligned with the physical mechanisms that actually drive commodity price outcomes.

Better alignment with atmospheric teleconnections

Research by L'Heureux et al. (2024) tested RONI and ONI against observed atmospheric patterns, specifically looking at precipitation anomalies and 200-hPa geopotential height (a measure of upper-level circulation) over key regions. The finding: ENSO teleconnections — the atmospheric signals that translate ocean temperature anomalies into actual weather in growing regions — are more sharply defined against RONI than ONI. In particular, teleconnections over Australia and the contiguous United States, two of the most important commodity-producing regions, explain more observed variance when computed with the relative index. For the first half of the year, RONI's forecast skill for precipitation is measurably improved. For the second half, the two indices perform comparably. Overall, RONI is not dramatically superior in every case — but it is more reliable in the cases that matter most, and the improvement is directionally consistent.

Decoupling climate change from ENSO trading signals

As global ocean temperatures rise, ONI will increasingly conflate secular warming with ENSO-phase strength. This has a direct consequence for commodity analysis: the "El Niño premium" embedded in supply risk models will become progressively inflated if ONI is used as the index. RONI removes this conflation by design. An analyst using RONI is measuring the ENSO-specific component of tropical Pacific temperature — the component that actually drives Walker Circulation anomalies and crop-relevant weather patterns. The background warming component is subtracted out, leaving a cleaner signal.

Arabica and robusta: different exposures, different analysis

Recent research (González-González et al., 2025) using satellite-derived gross primary productivity data across Latin American coffee and cacao regions confirms that ENSO exposure varies meaningfully by growing region and crop type. El Niño-driven drought stress is widespread across arabica growing areas in Central America and the Colombian highlands. La Niña's wetness-related stress is more localized to lowland areas. Cacao growing in lowland areas shows higher overall ENSO sensitivity than mountain-grown arabica — a finding that affects how ENSO-related supply risk should be allocated across different crop positions.

For traders managing positions across both arabica and robusta, RONI enables a more precise attribution: the ENSO-specific signal (what RONI captures) versus the background warming trend (what ONI additionally picks up). Robusta's price behavior appears more closely tied to direct temperature warming trends in producing regions, while arabica's supply asymmetry is more clearly tied to the ENSO cycle — the atmospheric circulation shifts that RONI better represents. Using RONI allows an analyst to separate these two drivers rather than conflating them in a single temperature metric.

The ONI–RONI gap is itself a tradeable signal

When ONI reads materially higher than RONI, the difference represents background tropical warming that ONI is counting as El Niño signal. In practical terms: apparent El Niño conditions are partially overstated. The actual atmospheric coupling — and the commodity supply risk it implies — is closer to what RONI indicates. Conversely, when RONI reads higher than ONI, ENSO conditions may be understated in absolute temperature terms. Monitoring the gap between the two indices provides an additional layer of information that either index alone cannot supply.

Navigating the Transition — A Practical Framework

RONI is days-to-weeks old as the official ENSO standard. The entire body of published commodity research — academic studies, bank research notes, seasonal forecast products — was built on ONI. The transition will take years to fully propagate through the analytical literature. In the meantime, analysts need to operate with both indices and understand what each tells them.

The corollary is worth stating explicitly: because ENSO updates monthly and arabica price responses lag 13–15 months, the decision window following a reliable ENSO signal is measured in quarters, not days. The data is slow by nature. That is a feature — it gives analysts who correctly interpret a RONI signal meaningful time to position before the full price impact materializes. The urgency most market participants feel around real-time ENSO data is largely misplaced.

The broader implication for the field is a transition that will take years to fully propagate. Published research will continue to use ONI as a basis for comparison with prior literature. Official NOAA and CPC communications will migrate to RONI. The practitioner who understands both — and can translate between them — will be working with a more reliable signal than the majority of the market, which tends to follow the most recent headline index reading without examining what it measures.