From the University of New South Wales and the “chicken or the egg” department comes this claim that El Niño events will increase in intensity. Meanwhile the milquetoast La Nada of the present continues.
New method shows how historical ENSO activity is affected by external forcings
New research shows El Niño Southern Oscillation (ENSO) phenomena have been more active and intense during the 30-year period between 1979-2009 than at any time during the past 600 years.
At the same time, this result suggests that the intensity and activity of El Niño and La Ninas appears to increase as global average temperatures increase.
The results of this new research, published in Climate of the Past, is a significant step towards understanding where current ENSO activity sits in the context of the past according to researchers from UNSW’s Centre of Excellence for Climate System Science, the University of Hawaii International Pacific Research Centre and the NOAA Geophysical Fluid Dynamics Laboratory.
“Our research suggests in a warming world we are likely to see more extreme El Niño and La Nina events, which over the past decade in Australia have been related to extreme flooding, persistent droughts and dangerous fire seasons,” said lead author Dr Shayne McGregor from UNSW
“Importantly, this study not only tells us how ENSO activity has behaved in the past in relation to global average temperature, it also opens the window for climate models to be able to estimate more accurately how this activity will change in the future.”
The researchers used a newly defined method they had developed and measurements from lake sediment and old coral cores along with tree rings across a wide variety of locations to determine how ENSO events had changed across the Pacific over hundreds of years. From these proxies, the researchers were able to determine the state of the climate over a wide area at the same time, revealing changes in ENSO activity.
As part of the research, the team brought together the different proxy reconstructions of past climate and, where the time periods of these proxies overlapped with current instrumental data, used these periods to determine how accurately they represented contemporary ENSO activity.
Once the effectiveness of the proxies was confirmed the researchers used this information to extrapolate the climate and activity of ENSO over the past 600 years.
They then further tested the robustness of this approach by comparing their real-world data with that produced by two multi-century-long climate model simulations.
“By applying these observations and finding which climate models reproduce past changes, we will have a better idea of which climate models are more likely to reproduce the ENSO response to climate change in the future,” said co-author Prof Matt England from the ARC Centre of Excellence for Climate System Science.
While the research shows how external warming factors have impacted ENSO cycles, one important question remains.
“We still don’t know why. Understanding this relationship will be vital to help us get a clear idea of the future changes to global climate,” said Dr McGregor.
It is vital to understand how the El Niño–Southern Oscillation (ENSO) has responded to past changes in natural and anthropogenic forcings, in order to better understand and predict its response to future greenhouse warming. To date, however, the instrumental record is too brief to fully characterize natural ENSO variability, while large discrepancies exist amongst paleo-proxy reconstructions of ENSO. These paleo-proxy reconstructions have typically attempted to reconstruct ENSO’s temporal evolution, rather than the variance of these temporal changes. Here a new approach is developed that synthesizes the variance changes from various proxy data sets to provide a unified and updated estimate of past ENSO variance. The method is tested using surrogate data from two coupled general circulation model (CGCM) simulations. It is shown that in the presence of dating uncertainties, synthesizing variance information provides a more robust estimate of ENSO variance than synthesizing the raw data and then identifying its running variance. We also examine whether good temporal correspondence between proxy data and instrumental ENSO records implies a good representation of ENSO variance. In the climate modeling framework we show that a significant improvement in reconstructing ENSO variance changes is found when combining information from diverse ENSO-teleconnected source regions, rather than by relying on a single well-correlated location. This suggests that ENSO variance estimates derived from a single site should be viewed with caution. Finally, synthesizing existing ENSO reconstructions to arrive at a better estimate of past ENSO variance changes, we find robust evidence that the ENSO variance for any 30 yr period during the interval 1590–1880 was considerably lower than that observed during 1979–2009.
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