Emerging evidence of a link between clear-air turbulence and El Niño suggests that flights could be a lot bumpier than normal in the year ahead.
El Niño is a natural climate oscillation that warms the upper layers of the tropical Pacific Ocean, shifting atmospheric wind patterns and affecting weather around the world. An El Niño event occurs once every few years on average and lasts around 9 to 12 months. By changing rainfall locations, El Niño is famous for simultaneously causing extreme drought in some countries and severe flooding in others, with catastrophic effects.
But a previously unrecognized impact of El Niño is that it has the potential to modify turbulence on flights. Specifically, El Niño (and its cold counterpart, La Niña) appear to change the windshear in the upper atmosphere. And it is wind shear that generates clear-air turbulence, which is particularly hazardous because it is invisible and undetectable by weather radar.
The Link to Turbulence
New scientific research has investigated the relationship between El Niño and clear-air turbulence. Using 40 years of atmospheric data, the research (which has not yet been peer-reviewed) has calculated that windshear at flight cruising levels over the North Atlantic Ocean increases by around 35% in going from a very strong La Niña event to a very strong El Niño event. Correspondingly, the amount of turbulence in the skies over the North Atlantic increases by around 30%.
Other regions affected by these increases include the USA (as shown in the below image), South America, South-East Asia, Australia, and Africa. Conversely, in East Asia, the relationship is flipped, and El Niño is found to decrease wind shear and turbulence, but La Niña is found to increase them.
These results are consistent with a published analysis of pilot reports of turbulence on flights over the USA. The National Center for Atmospheric Research found that pilot reports of turbulence spiked much higher than normal during the very strong El Niño event of 1997-98.
The Year Ahead
There are signs that a large El Niño event is on the cards in the coming months, according to predictions from NOAA’s Climate Prediction Center. By the time the event peaks between November 2026 and January 2027, there is a 63% chance of a very strong(so-called “super”) El Niño, and a 25% chance of a strong El Niño, implying a combined 88% chance of El Niño being either strong or very strong. There is even a chance this El Niño event could be the strongest on record.
These seasonal predictions, combined with the above research into the link with turbulence, suggest statistically that large parts of the world could experience stronger windshear and increased turbulence probabilities in the year ahead.
Looking Even Further to the Future
Windshear and turbulence are known to be trending upwards on timescales of decades due to climate change. Since the late 1970s over the North Atlantic, windshear has already increased by 15% and severe turbulence by 55%. Further large turbulence increases are projected over the coming decades as the world continues to warm.
Every El Niño event is different, and only time will tell whether this coming El Niño develops as strongly as the predictions suggest. But the science is clearly telling us that the airlines should be planning for bumpier skies on many routes around the world – both later this year due to El Niño, and in the decades to come due to climate change.
Understanding that El Niño increases turbulence is one thing. Having the tools to act on that knowledge in real time is another.
The forecasting challenge is not new. For over three decades, the aviation community has worked to close the gap between what turbulence forecasts can tell you and what crews actually need to act on in real time.
A turbulence forecast can be scientifically correct and still tell a crew almost nothing useful. Knowing that rough air exists somewhere across a 300-mile corridor does not tell you whether it is at FL350 or FL370, or whether it starts in 20 minutes or two hours. The decisions that prevent injuries are made in feet and minutes: which altitude, which heading, when exactly to secure the cabin. It is a problem that traditional forecasting alone was never built to resolve.
What an El Niño year does is widen that gap, and the operational consequences scale with it. A 30%increase in North Atlantic turbulence does not translate only to bumpier rides. It means proportionally more turbulence-related injuries, already the leading cause of non-fatal harm in commercial aviation, and a corresponding rise in fuel costs driven by reactive altitude changes, speed reductions, and contingency fuel loading. Turbulence-attributable fuel burn already represents roughly 1 to 2% of fleet fuel costs; a sustained increase in encounter frequency compounds that burden across an entire season.
A Different Kind of Data
What has changed is the availability of a different kind of data architecture. SkyPath's platform is built around five distinct turbulence data sources: crowdsourced pilot observations, ADS-B vertical rate measurements, eddy dissipation rate data, pilot-filed PIREPs, and AI-driven forecasting, fused through a single unified algorithm that normalizes across aircraft types and updates continuously. It isthe fusion that matters: combined and processed at scale, the underlying dataset spans 9 billion turbulence reports annually, and the system reaches 90%prediction accuracy at 32NM resolution, with 24-hour forward coverage and 100%global reach. The result is a platform that operates simultaneously as areal-time observation network and a predictive tool, the two capabilities reinforcing each other rather than running in parallel.
When a crew receives a notification that turbulence was reported at their altitude and heading minutes ago by another aircraft, cross-validated against the AI forecast and ADS-B data, the decision to adjust altitude or secure the cabin is no longer a matter of interpreting a probabilistic regional forecast. It is a response to a converging picture. That shift, from probability to fused intelligence, is what makes this generation of tools qualitatively different from what came before.
Not a Drill
The coming El Niño is not just another weather event to route around. Based on the forecast, it represents a sustained, multi-regional stress test for every layer of turbulence management in commercial aviation, from atmospheric modelling to cockpit decision-making.
The research mentioned above is specific: a strong El Niño event increases turbulence over the North Atlantic by around 30% compared to a strong La Niña event. That is not a gradual trend. It is what happens within a single season. With the peak forecast between November 2026 and January 2027, the timeline is clear. Airlines that wait for the season to prove the forecasts right will already be behind.
Traditional weather forecasts were not designed for this kind of baseline shift. They tell airlines where turbulence is likely. They do not translate that into the granular, actionable intelligence crews need to make proactive decisions in real time. That gap is precisely what a new generation of data platforms is built to close, delivering route-specific, altitude-specific insights that turn a probability into a plan. The airlines that navigate this period well will not be the ones with better luck. They will be the ones that treated turbulence a s a data problem before the season started, not after the first serious event. The tools exist. The question is whether the industry moves fast enough to use them.
References:
Cheyne, R. (2020) Does El Niño-Southern Oscillation affect global clear-air turbulence? BSc dissertation, University of Reading.
Lee, S.H., Williams, P.D. & Frame, T.H.A. (2019) Increased shear in the North Atlantic upper-level jet stream over the past four decades. Nature 572,639–642.
NCEP(2026) ENSO: Recent Evolution, Current Status and Predictions: 26 May 2026.https://www.cpc.ncep.noaa.gov/products/analysis_monitoring/lanina/enso_evolution-status-fcsts-web.pdf
Prosser, M. C., Williams, P. D., Marlton, G. J., & Harrison, R. G. (2023) Evidence for large increases in clear-air turbulence over the past four decades. Geophysical Research Letters, 50, e2023GL103814.
Prosser, M. (2024) Clear-air turbulence in reanalysis data. PhD thesis, University of Reading.
Williams, P.D. (2017) Increased light, moderate, and severe clear-air turbulence in response to climate change. Adv. Atmos. Sci. 34, 576–586.
Wolff, J. K., and R. D. Sharman (2008) Climatology of Upper-Level Turbulence over the Contiguous United States. J. Appl. Meteor. Climatol., 47, 2198–2214.
.jpg)
.jpg)
