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| Abnormal temperature spikes can also lead to unpredictable results during the El Niño period, Dmitry Aleksandrov believes. Photo Credit: Ilya Safarov |
Scientific Frontline: Extended "At a Glance" Summary: El Niño Atmospheric and Oceanic Balance Modeling
The Core Concept: El Niño is a natural climate phenomenon characterized by an abnormal increase in sea surface temperatures in the central and eastern equatorial Pacific Ocean, driven by disruptions in standard atmospheric and ocean circulation patterns. Recent mathematical modeling demonstrates how external environmental noise can push this system out of balance and trigger extreme fluctuations.
Key Distinction/Mechanism: Unlike standard views focusing solely on periodic warming, this mathematical approach integrates external environmental noise—such as wind gusts, humidity variations, pressure changes, and ocean currents—into the classic Vallis model to calculate various potential behavior scenarios and intensity thresholds rather than strict temporal prediction dates.
Origin/History: El Niño phenomena have been documented across historical, geological, and paleoclimatic studies spanning at least 300,000 years, with recurring cycles occurring every two to ten years, including notable active cycles in 1957–1958, 1982–1983, 1997–1998, and 2015–2016.
Major Frameworks/Components:
- The classic Vallis model, which accounts for east-west temperature differences, ocean-atmosphere heat exchange, and air mass movement speeds.
- External environmental noise parameters, including fluctuations in atmospheric pressure, humidity, wind gusts, and ocean currents.
- Continuous warm ocean currents originating off the Peruvian coast and extending toward Southeast Asia, influenced by trade wind strength and anomalous convection zones.
Branch of Science: Earth Science, Physics, Meteorology, Climatology, Oceanography.
Future Application: Improved incorporation of unpredictable El Niño dynamics into global climate simulation models to better forecast extreme weather events, climate change feedback loops, and regional atmospheric shifts.
Why It Matters: Understanding how minor external perturbations can destabilize atmospheric-oceanic systems enables scientists to better predict the behavioral intensity and global climatic repercussions of El Niño events, ultimately aiding long-term climate modeling and disaster preparedness.
"We used the classic Vallis model, which describes El Niño. This is a simple model, it takes into account the temperature difference between the east and west coasts, the heat exchange between the Pacific Ocean and the atmosphere, and the speed of air masses movement. We also took into account external noise - parameters that also affect atmospheric and oceanic processes, such as pressure changes, humidity, wind gusts, and ocean currents," says Dmitry Aleksandrov, Head of the Ural Federal University's Laboratory of Multi-Scale Mathematical Modeling.
According to UrFU physicists' calculations, external factors have a serious influence on this phenomenon. For example, the stronger the wind, the greater the temperature amplitude. Moreover, this can throw the system out of balance and cause unpredictable weather conditions.
"Our calculations have shown that the higher the intensity of the noise, the more unpredictable the consequences, the stronger the disturbances, the more intense El Niño will be. Sometimes a slight push is needed for the system to get out of equilibrium: a change in humidity or ocean currents. With the help of the model, we have managed to show how the process will develop under the influence of one or another factor. That is, we have not predicted the time of El Niño appearance or what will be its consequences for the global climate, we have calculated possible scenarios of this phenomenon and showed that under some conditions there will be one version of events, and under a different set of parameters - another," adds the physicist.
On the one hand, scientists still cannot predict when El Niño will come again, but, on the other hand, they have learned to predict how El Niño will behave. This is important because El Niño affects the climate as much as climate change affects the phenomenon. While El Niño was once thought to affect only South America, scientists are now certain that the abnormally warm water surface is having an effect throughout much of the Pacific Ocean, up to the 180th meridian. Moreover, global weather changes are more noticeable during El Niño periods: large-scale changes in ocean temperature, precipitation, atmospheric circulation, and vertical air movement over the tropical Pacific Ocean.
The essence of the process is this: there is a continuous warm current that originates off the coast of Peru and extends to the archipelago southeast of the Asian continent. It is an elongated area of heated water, about the size of the United States. The heated water evaporates intensely and releases energy into the atmosphere. Clouds form over the heated ocean. Typically, trade winds (constant easterly winds in the tropical zone) move a layer of this warm water away from the U.S. coast toward Asia. Near Indonesia, the current stops, and monsoon rains fall on southern Asia. During El Niño, the current is warmer than usual near the equator, so the trade winds are weaker or not blowing at all. The heated water spreads out to the sides and flows back to the U.S. coast. An anomalous zone of convection emerges. Rain and hurricanes hit Central and South America.
"We assume that extreme El Niño phenomena may become more frequent in the future and contribute to climate change, just as climate change affects El Niño occurrences. That is why El Niño is the process that should be taken into account in global climate models, but this is not done yet, because nobody knows how to take into account such unpredictable and complicated phenomenon," says Dmitry Aleksandrov.
Reference material: What Is: El Niño, La Niña, and a Climate in Flux
Published in journal: Physica D: Nonlinear Phenomena
Title: How random noise induces large-amplitude oscillations in an El Ni n ̃ o model
Authors: D.V. Alexandrov, I.A. Bashkirtseva, and L.B. Ryashko
Source/Credit: Ural Federal University
Edited by: Scientific Frontline
Reference Number: phy082422_01
