The oceans are losing their memory – climate change reduces the stability and self-similarity of sea temperatures

An uncertain future: due to climate change, the world’s oceans are in danger of losing their memories – the inertia and self-similarity that have so far characterized the ocean’s reaction to climate influences. As a result, sea temperatures could fluctuate unexpectedly in the coming decades, researchers predicted in the journal Science Advances. This could become a problem for weather forecasts, climate forecasts, and the marine ecosystem.

The oceans are important climatic insulators on our planet: because their huge volumes of water absorb large amounts of heat and react very slowly to changes, the seas stabilize the climate and have a balancing effect on fluctuations. Above all, the thermally stagnant deep water acts like a memory of the sea: it ensures that the sea remains similar to itself.

Self-similarity as an indicator

“Ocean memory – the persistence of sea conditions – is an important predictability of the climate system,” Hui Shi and colleagues from the Farallon Institute in California explain. Because the subjective similarity of sea temperatures from year to year allows climate forecasters to predict cyclical or constant climate changes such as El Nino, monsoons, or marine heat waves over a period of up to two years.

But this could end in the future. As Shi and her team have discovered, the world’s oceans are at risk of losing their memory. “We discovered this phenomenon when we studied changes in sea surface temperatures from year to year as a simple indicator of ocean memory,” Shi says.

Simulation in two model groups in parallel

In their study, the researchers used two different sets of ocean climate models (CMIP6 and CESM1-LE), which they first compared with observational data for historical trends in surface temperatures, heat flux, and radiative flux from pre-industrial times to the present. day. From this they determined the so-called autocorrelation lag 1 – the intensity of variability and the auto-similarity of the typical temperatures of the ocean region and the relevant season.

After calibrating the models, the team extended the simulated time period to the year 2100, using scenarios for varying degrees of climate change in line with those of the IPCC.

Changes in autocorrelation (1) in sea temperatures were determined using the CESM1-LE cluster model. © Shi et al. / Science Advances, CC-by 4.0

Increased ocean ‘amnesia’

It turns out that as the oceans warm up, the self-similarity of temperature evolution decreases—the ocean’s memory gets weaker, the team found. Different sea regions will change their temperatures in the future in a more unpredictable way than has been the case until now. The researchers report that “stochastic effects affect deviations in surface temperature more effectively and noise increases at the expense of continuous signals.”

In other words, “It’s as if the ocean is progressing to amnesia,” says Shi. In concrete terms, this means that the ocean region’s response to past weather events and climate fluctuations has been a relatively good indicator of how it will respond to the same events in the near future. But as climate change increases, this self-similarity continues to decline, simulations show.

Memory Fade ranges up to 100 percent

According to predictions, the memory of the oceans is waning all over the world and in all seas. However, low self-similarity is particularly evident in parts of the North Atlantic and Pacific Oceans, the eastern South Atlantic, the South China Sea, and some areas of the Indian Ocean. Some areas experience memory loss of up to 100 percent,” Shi and her colleagues say.

“Despite some differences, the CMIP6 and CESM1-LE models consistently show some marine areas where by the end of this century mean annual sea surface temperature will not be a significant guide to the mean for the following year,” the researchers wrote. At the same time, according to their results, the “noise” increases due to shorter and stronger fluctuations, which reduces the predictability.

The upper layer of the sea is crucial

Shi and her husband identified changes in the ocean’s mixed surface layer as the main reason for the ocean’s diminishing predictability. This layer of warm surface water, which is about 50 meters thick on average, stores an especially large amount of heat and plays a crucial role in how the oceans interact with the atmosphere: the deeper this layer, the greater its ability to store heat and inertia in the face of the changes.

However, measurements in recent years have shown that the mixed layer of the oceans is getting thinner and thinner, while at the same time the exchange of heat and nutrients with the deeper waters below is decreasing. This is also a major factor in diminishing inertia and self-similarity in the oceans, Shi and colleagues found: a thinner, more detached surface layer from the rest of the seawater is also subject to stronger and unexpected fluctuations.

“Of course, other processes such as changes in ocean currents and energy exchange between the ocean and the atmosphere also contribute,” the research team emphasizes. But the biggest factor in the increasing “amnesia” of the oceans is the flattening of the mixed layer. In some areas, they account for as much as two-thirds of the impact.

Effects on weather forecasts and ecosystems

According to the research team, the memory of the fading oceans can have important consequences in a number of ways. On the one hand, this will make it more difficult to predict weather fluctuations such as monsoons or El Nino and marine heat waves. Weather events on Earth such as torrential rain or heat waves may be less predictable under these conditions.

At the same time, increased and unpredictable fluctuations in sea temperatures can also affect marine ecosystems and their inhabitants. Because, the team explains, long-lived species with slow reproduction often depend on relatively stable environmental conditions. Unpredictable changes can further affect fisheries and fish stock prospects. (Advances of Science, 2022; doi: 10.1126/sciadv.abm3468)

Source: University of Hawaii at Manoa

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