‘Stadium wave’ may explain pause in global warming
A new climate model offers a plausible explanation for why there has been a hiatus in warming of global surface temperatures since 1998.
Several ideas have been put forward to explain the hiatus, including what the Intergovernmental Panel on Climate Change (IPCC) refers to as “unpredictable climate variability” that is associated with large-scale circulation regimes in the atmosphere and ocean. The most familiar of these regimes is El Niño/La Niña, which are parts of an oscillation in the ocean-atmosphere system.
A new paper published in the journal Climate Dynamics suggests that this “unpredictable climate variability” behaves in a more predictable way than previously assumed.
The authors of the study say a climate signal propagates across the Northern Hemisphere through a network of ocean, ice, and atmospheric circulation regimes that self-organize into a collective tempo, much like a “stadium wave” where sports fans stand and sit as a “wave” propagates through the stands.
The stadium wave hypothesis offers an explanation for the warming hiatus and suggests why climate models didn’t predict it. Further, the hypothesis also predicts how long the hiatus might last.
Researchers identified two key ingredients to the propagation and maintenance of this stadium wave signal: the Atlantic Multidecadal Oscillation (AMO) and sea ice extent in the Eurasian Arctic shelf seas.
The AMO sets the signal’s tempo, while the sea ice bridges communication between ocean and atmosphere. The oscillatory nature of the signal can be thought of in terms of “braking,” in which positive and negative feedbacks interact to support reversals of the circulation regimes.
As a result, climate regimes—multiple-decade intervals of warming or cooling—evolve in a spatially and temporally ordered manner.
While not strictly periodic in occurrence, the repetition is regular and the order of quasi-oscillatory events remains consistent. The thesis shows the stadium wave signal has existed for at least 300 years.
The new study analyzed indices derived from atmospheric, oceanic, and sea ice data since 1900. The linear trend was removed from all indices to focus only the multi-decadal component of natural variability.
A multivariate statistical technique called Multi-channel Singular Spectrum Analysis (MSSA) was used to identify patterns of variability shared by all indices analyzed, which characterizes the ‘stadium wave.’ The removal of the long-term trend from the data effectively removes the response from long term climate forcing such as anthropogenic greenhouse gases.
The stadium wave periodically enhances or dampens the trend of long-term rising temperatures, which may explain the recent hiatus in rising global surface temperatures.
“The stadium wave signal predicts that the current pause in global warming could extend into the 2030s,” says study co-author Marcia Wyatt, an independent scientist.
“This prediction is in contrast to the recently released IPCC AR5 Report that projects an imminent resumption of the warming, likely to be in the range of a 0.3 to 0.7 degree Celsius rise in global mean surface temperature from 2016 to 2035,” adds study co-author Judith Curry, chair of the School of Earth and Atmospheric Sciences at the Georgia Institute of Technology (Georgia Tech).
Previous work on the “wave” shows the models fail to capture the stadium-wave signal. That this signal is not seen in climate model simulations may partially explain the models’ inability to simulate the current stagnation in global surface temperatures.
External focus skews results
“Current climate models are overly damped and deterministic, focusing on the impacts of external forcing rather than simulating the natural internal variability associated with nonlinear interactions of the coupled atmosphere-ocean system,” Curry says.
The study also provides an explanation for seemingly incongruous climate trends, such as how sea ice can continue to decline during this period of stalled warming, and when the sea ice decline might reverse.
After temperatures peaked in the late 1990s, hemispheric surface temperatures began to decrease, while the high latitudes of the North Atlantic Ocean continued to warm and Arctic sea ice extent continued to decline. According to the stadium wave hypothesis, these trends mark a transition period whereby the future decades will see the North Atlantic Ocean begin to cool and sea ice in the Eurasian Arctic region begin to rebound.
Most interpretations of the recent decline in Arctic sea ice extent have focused on the role of anthropogenic greenhouse gas forcing, with some allowance for natural variability. Declining sea ice extent over the last decade is consistent with the stadium wave signal, and the wave’s continued evolution portends a reversal of this trend of declining sea ice.
Sea ice will recover
“The stadium wave forecasts that sea ice will recover from its recent minimum, first in the West Eurasian Arctic, followed by recovery in the Siberian Arctic,” Wyatt says. “Hence, the sea ice minimum observed in 2012, followed by an increase of sea ice in 2013, is suggestive of consistency with the timing of evolution of the stadium-wave signal.”
The stadium wave holds promise in putting into perspective numerous observations of climate behavior, such as regional patterns of decadal variability in drought and hurricane activity, the researchers say, but a complete understanding of past climate variability and projections of future climate change requires integrating the stadium-wave signal with external climate forcing from the sun, volcanoes and anthropogenic forcing.
“How external forcing projects onto the stadium wave, and whether it influences signal tempo or affects timing or magnitude of regime shifts, is unknown and requires further investigation,” Wyatt says.
“While the results of this study appear to have implications regarding the hiatus in warming, the stadium wave signal does not support or refute anthropogenic global warming. The stadium wave hypothesis seeks to explain the natural multi-decadal component of climate variability.”
Source: Georgia Tech
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