New insights to aid climate prediction
El Niño Southern Oscillation, or Enso, an anomalous warming of the surface waters in the tropical Pacific Ocean, is famous for producing months-long unusual weather patterns across the globe.
A similar, albeit lesser-known circulation pattern, the Atlantic El Niño, dominates a wide swathe of the Atlantic Ocean. The Atlantic El Niño phenomenon is analogous to the cycles that create Pacific Enso. But unlike its Pacific counterpart, which has proven invaluable for seasonal climate predictions, the Atlantic El Niño is nearly impossible to predict.
The broad shifts in weather regimes known as Enso occur when a massive swath of warm water forms off the coast of South America and extends into the central Pacific. The warmth of the water changes the flow of air in the Pacific. This in turn alters the weather patterns in countries bordering the Pacific and beyond as air movements around the globe adjust to the conditions in the Pacific.
Because the movement of warm and cold waters occurs rather slowly across the vast stretch of the Pacific, climate scientists are able to predict the arrival of Enso and accompanying weird weather conditions up to nine months in advance.
This allows the affected countries to prepare for the heavy rainfall and floods in eastern Africa and drought in southern Africa that an Enso brings at irregular intervals of two to seven years.
But climate scientists have struggled to understand what causes the Atlantic El Niño to emerge. I recently led a study that offers new insights, raising hope for improved climate predictions and better preparation.
The air and ocean waters are essentially interwoven. Waters in the ocean move because winds blow on them.
The air moves faster than the ocean waters below it.
The water responds more slowly. This way, the ocean water forms a distinct pattern of movements, which redistributes heat slowly over a period of several months. Scientists are able use climate models to track the water movements, and predict El Niño events.
Because the El Niño patterns in the Atlantic and Pacific Oceans are considered to be similar, one would expect them to be similarly predictable. This is not so. The Pacific pattern is relatively easy to predict while the Atlantic one is almost completely unpredictable.
And there are additional important differences: the Atlantic events are of smaller magnitude and shorter duration.
The reasons for these differences have puzzled climate scientists for decades.
The key question is how essential the movements of warm and cold waters are for the emergence of the Atlantic El Niño events. Computer climate simulations show that air, rather than ocean water, movements are key to the Atlantic warm events. One set of simulations was conventional, trying to incorporate the detailed air and water movements. The second set reduced the complexity by modelling the ocean simply as a slab of motionless water with a depth of only 50m.
This model was formulated in such a way that the ocean could absorb heat, emit heat, and evaporate moisture into the air, but the movements of warm and cold water within the ocean itself were ignored.
The atmosphere alone accounts for 63% of the Atlantic El Niño events in these simulations.
This implies the movements of water in the ocean, as observed in the Pacific, are of lesser importance in the Atlantic. The Atlantic is “naturally” less predictable.
This is why our new findings, which established a strong connection to the Intertropical Convergence Zone, are important. The zone needs to be represented more realistically in the climate models and this will make them more accurate and reliable.
The African and South American countries bordering the equatorial Atlantic strongly depend upon the ocean for societal development, fisheries, and tourism. They are strongly affected by vagaries in weather systems. Accurate climate predictions are essential.
The equatorial Atlantic is a region of key uncertainties in the climate system: climate models exhibit large errors. And for many parameters, there are large gaps in observations that need to be closed.
Closing the observational gaps is a key step in reducing the climate model errors, and improving seasonal climate predictions.