Germany is utilizing supercomputing to demo the impact of weather phenomena on ocean circulation

Extreme events such as cyclones will change as a result of climate change - and their effects should be better considered in climate models, say the authors. Photo: Viks_jin/NASA/Adobe Stock
Extreme events such as cyclones will change as a result of climate change - and their effects should be better considered in climate models, say the authors. Photo: Viks_jin/NASA/Adobe Stock

The impact of climate change on atmospheric synoptic variability (ASV) will have significant consequences on ocean circulation and ecosystems. Even though ASV is often considered as background noise in climate models, it is important to comprehend its complete influence on the ocean. The future changes in ASV will result in a shallower mixing layer in subtropical regions and a deeper mixing layer in equatorial regions.

A recent study conducted by GEOMAR in Kiel, Germany, has explored how changes in weather patterns may affect the tropical Pacific Ocean and its ecosystems in the future. The researchers conducted simulations based on complex supercomputer models to show that these changes will have significant consequences on ocean circulation. The authors stress the need to consider this while creating future climate models.

The strength of the wind has a crucial influence on ocean circulation, especially during extreme weather events such as storm fronts, tropical storms, and cyclones. Due to climate change, these weather patterns are expected to change in the future, particularly in terms of the average energy input into the ocean from mid-latitude storms, which is expected to decrease while equatorial regions will become more active. Scientists refer to these distinct weather patterns as "Atmospheric Synoptic Variability" (ASV).

Dr. Olaf Duteil from the GEOMAR Helmholtz Centre for Ocean Research in Kiel and Professor Dr. Wonsun Park from the IBS Center for Climate Physics and Pusan National University in Korea have now conducted a modeling study to investigate the integrated effects of long-term changes in these weather patterns on the Pacific basin for the first time. According to their supercomputing results, it is crucial to consider these changes while creating climate models.

From a climate perspective, weather is generally regarded as "noise" and is not systematically analyzed in long-term climate projections, according to the two researchers. However, to better understand the influence of climate change on the ocean, it is essential to take into account the cumulative effect of short-term changes in weather patterns rather than just focusing on average atmospheric properties such as mean wind speeds, says Duteil.

According to the researchers, the Atmospheric Synoptic Variability (ASV) will play a vital role in the future mixing of the ocean's layers. Depending on the weather phenomena, the amount of kinetic energy input into the ocean can be either less or more, leading to less or more mixing, respectively. The study predicts that the reduction of ASV in subtropical regions will cause a shallowing of the mixing layer in the ocean. However, the mixing layer will become deeper at the equator with an increase in ASV.

The research findings also indicate that a decrease in ASV in the future will weaken the subtropical and tropical cells, affecting large-scale ocean circulation systems. These systems connect mid-latitudes and equatorial latitudes via upper ocean pathways, driven by the trade winds north and south of the equator. The study further highlights that these cells regulate the upwelling of equatorial waters and play a vital role in determining the surface temperature of the oceans, thus influencing primary productivity in the tropics.

The study emphasizes the importance of accurately quantifying ASV and weather patterns in climate models, which could improve our understanding of future upper ocean circulation and mean properties. The lead author, Duteil, suggests that this quantification should be used to enhance our confidence in projections of future climate, especially while analyzing large ensembles of climate models.