The 1997-98 Super El Niño: A Retrospective

Published: May 16, 2026 · 9 min read

"The Fish Just Disappeared"

Peruvian fishermen were the first to notice something was wrong. It was April 1997. Anchoveta — the small, oily fish that supports Peru's entire fishing industry — were vanishing from their usual grounds. The water felt warm. Too warm.

They'd seen this before. They even had a name for it: El Niño, "the Christ Child," because the warm water tended to arrive around Christmas. But this time was different. The water wasn't just warm — it was hot. And it kept getting hotter all through the year, not stopping in the usual weeks but persisting for months.

By December 1997, sea surface temperatures in the eastern equatorial Pacific had surged to +2.6 °C above normal — at the time, the highest ever recorded. The 1997-98 event had become, and remains today, one of the three strongest El Niños in the instrumental record, alongside 1982-83 and 2015-16.

What made this one different from previous super El Niños was that scientists actually saw it coming. Barely. The TAO buoy array — a string of 70 moored buoys across the equatorial Pacific — had been deployed just a few years earlier in the early 1990s. For the first time, we had real-time subsurface ocean data. We weren't flying blind anymore. Combine that with the new TOPEX/Poseidon satellite altimeter measuring sea surface height from orbit, and you had an observing system that would have been science fiction during the last big one in 1982-83.

How It Unfolded — Faster Than Anyone Expected

March 1997: the Pacific looks normal. Temperatures near average, trade winds blowing steadily westward. Nothing worth writing home about.

By June 1997, the Niño-3.4 index had shot past +1.0 °C. By November, it hit +2.6 °C. That's an insane rate of warming — 3 °C in a few months across a region the size of the United States. The trigger? A series of westerly wind bursts in April and May, driven by the Madden-Julian Oscillation, that sent powerful downwelling Kelvin waves racing eastward across the Pacific.

What was happening below the surface was even more dramatic. At thermocline depth — roughly 100-150 meters down — temperatures were running 5 to 8 °C above normal. The thermocline itself got pushed down by a hundred meters or more in the eastern Pacific. NOAA's Warm Water Volume index, which tracks how much >20 °C water is sitting in the equatorial band, went completely off the charts. The ocean had turned into a giant heat battery, and it was about to discharge into the atmosphere.

What It Did to the Planet

The 1997-98 El Niño produced a stunning array of extreme weather events across every inhabited continent:

South America. Coastal Peru and Ecuador experienced catastrophic rainfall. The Piura River in Peru reached its highest level in 60 years, flooding entire towns. In Ecuador, rainfall in some coastal areas reached 15-20 times normal, causing over 500 deaths and displacing tens of thousands. The flooding also triggered a major outbreak of waterborne diseases, including cholera and leptospirosis.

Southeast Asia and Australia. Indonesia experienced one of its most severe droughts on record. Combined with the El Niño-driven drying, agricultural and peatland fires burned uncontrollably across Sumatra and Kalimantan from July through November. The resulting haze spread across Singapore, Malaysia, and as far as Thailand, causing over 20 million people to suffer from respiratory problems. The total economic damage from the fires and haze was estimated at $4.5 billion in Indonesia alone. In Australia, the drought dried out vast areas of the eastern and northern regions, creating conditions for destructive bushfires.

North America. California experienced a powerful winter storm season, with a series of atmospheric rivers delivering heavy rain and snow. While the precipitation helped refill reservoirs after a multi-year drought, it also caused flooding and landslides in coastal communities. The southern United States experienced cool and wet conditions, while the northern tier saw an unusually warm winter. The Atlantic hurricane season was suppressed, producing only seven named storms and three hurricanes.

Africa. Southern Africa experienced severe drought, with South Africa, Zimbabwe, and Mozambique suffering major crop failures. The maize harvest in South Africa dropped by 25% relative to the previous year. Conversely, eastern Africa — particularly Somalia, Kenya, and Ethiopia — experienced torrential rainfall and flooding that displaced hundreds of thousands of people and contributed to a major Rift Valley fever outbreak.

Pacific Islands. Drought conditions affected Papua New Guinea, Fiji, and Samoa, with water shortages becoming critical on several islands. In Papua New Guinea, the drought was so severe that it caused widespread crop failure and led to reports of frost at highland elevations, a rare occurrence.

The Price Tag: $35-45 Billion

NOAA estimates the total economic damage at $35 to 45 billion globally. That's roughly equivalent to the GDP of Bolivia, wiped out by a patch of warm water in the Pacific.

The damage spread across everything: crops failed from drought in Indonesia and southern Africa, floods destroyed infrastructure in Peru and Ecuador, fires burned out of control in Sumatra and Kalimantan, hydropower output crashed in drought-stricken regions, and healthcare systems got overwhelmed by cholera and Rift Valley fever outbreaks. Commodity markets felt it too — palm oil prices spiked after Indonesian production tanked, copper mining in Chile got disrupted by flooding.

But the single hardest-hit sector? Peruvian fisheries. The anchoveta fishery — normally the biggest single-species fishery on the planet, pulling in 8 to 10 million tons a year — collapsed to near zero. The warm, nutrient-poor water pushed the anchoveta schools so far south and deep that the fleet couldn't reach them. It took two full years for the fishery to recover. For the coastal communities that depend on it, those two years were devastating.

What We Learned (the Hard Way)

The 1997-98 event was the first El Niño that dynamical models predicted with any real skill. It wasn't perfect — in spring 1997, some models said "weak event" and others said "monster," with no way to tell who was right. But the TAO buoy array and TOPEX/Poseidon satellite data gave forecasters something they'd never had before: real-time eyes on the ocean.

That observing system proved its worth. NOAA's Mike McPhaden, who ran the TAO project at the time, later wrote that the 1997-98 event "validated two decades of investment in ocean observing" and directly led to the operational ENSO forecasting systems we rely on today. If the buoys hadn't been there, we would have been as blindsided as we were in 1982-83, when a super El Niño hit with essentially zero warning.

The event also kicked off serious research into the MJO-westerly wind burst connection. Before 1997, wind bursts were seen as random weather noise. After 1997, they were recognized as a key trigger mechanism — the spark that can ignite a full-blown El Niño. This insight drove the push toward subseasonal-to-seasonal (S2S) prediction, which tries to bridge the gap between 10-day weather forecasts and 3-month seasonal outlooks.

The model spread problem — some weak, some strong, no consensus — led directly to the multi-model ensemble approach that's standard practice today. Instead of betting on one model, forecasters now average across dozens. It's less precise in any single case, but it's dramatically more reliable overall.

One other thing 1997-98 taught us: the "spring predictability barrier" is real and it's brutal. Every March through May, ENSO forecast skill drops off a cliff because the ocean-atmosphere coupling in the tropical Pacific is at its weakest. We still haven't solved this one. If someone figures out how to beat the spring barrier, that's a Nobel-worthy breakthrough.

Why It Still Matters

Twenty-eight years later, the 1997-98 El Niño is still the benchmark. It's the event scientists reach for when they want to understand what a "worst case" looks like. The observing system it validated — TAO buoys, satellite altimetry, coupled forecast models — is the same backbone we use today, just upgraded.

But the hard truth is that prediction hasn't advanced as much as we'd hoped since 1997. We're better at seeing an El Niño coming once it's started. We're not much better at knowing, in March, whether a weak warming will fizzle out or explode into the next super event. The spring barrier remains. Climate models have gotten faster and higher-resolution, but they still can't reliably tell you in April what December will look like.

If there's one lesson that governments actually absorbed from 1997-98, it's that climate prediction is worth paying for. NOAA estimated that improved El Niño forecasts save the U.S. economy roughly $300-500 million per year in agriculture, energy, and disaster preparedness — a return that dwarfs the cost of the observing system. The World Meteorological Organization built its entire climate services framework partly on the momentum from this event.

Next time a super El Niño hits — and one will — the question isn't whether we'll see it coming. It's whether we'll act on the warning.

Regional Economic Impact Comparison

The economic toll of El Niño isn't evenly distributed. Some regions absorb glancing blows while others take direct hits. The map below shows how 1997-98 super el niño varies across the most vulnerable regions — and why preparedness investments produce vastly different returns depending on where you are.

The most vulnerable countries are those where agriculture accounts for a large share of GDP AND the climate is strongly teleconnected to ENSO. A country like Peru, where the fishing industry alone represents ~2% of GDP and is directly disrupted by El Niño warming, feels the impact faster and harder than a diversified economy with weaker ENSO links.

For the 2026-2027 event, the economic exposure is compounded by already-strained fiscal positions in many developing countries following the pandemic recovery period. Limited fiscal space means less capacity to absorb shocks through government spending — making early warning and preparedness even more critical.

Explore more at the El Niño Guide — comprehensive climate science explained.