From the Potsdam Institute for Climate Impact Research (PIK) where breakthroughs happen even before they have a proven track record. It appears he was able to predict one event last year in 2012 from the method run in 2011, but just one success does not a breakthrough make, especially when we are dealing with a chaotic system and the method depends on “inspecting emerging teleconnections”. Only time will tell if his idea has any skill. Hansen has already tried and failed on predicting El Niño. -Anthony
Breakthrough in El Nino forecasting
In order to extend forecasting from six months to one year or even more, scientists have now proposed a novel approach based on advanced connectivity analysis applied to the climate system. The scheme builds on high-quality data of air temperatures and clearly outperforms existing methods. The study will be published this week in the Proceedings of the National Academy of Sciences.
“Enhancing the preparedness of people in the affected regions by providing more early-warning time is key to avoiding some of the worst effects of El Niño,” says Hans Joachim Schellnhuber, director of the Potsdam Institute for Climate Impact Research and co-author of the study by Josef Ludescher et al (Justus-Liebig Universität Giessen). The new approach employs network analysis which is a cutting-edge methodology at the crossroads of physics and mathematics. Data from more than 200 measurement points in the Pacific, available from the 1950s on, were crucial for studying the interactions between distant sites that cooperate in bringing about the warming.
Extending the forecasting time but also enhancing the reliability
According to Schellnhuber a new algorithm was developed and tested which does not only extend the forecasting time but also enhances the reliability. In fact, the novel method correctly predicted the absence of an El Niño-event in the last year. This forecast was made in 2011 already, whereas conventional approaches kept on predicting a significant warming far into 2012.
El Niño is part of a more general oscillation of the Pacific ocean-atmosphere system called ENSO, which also embraces anomalous cold episodes dubbed La Niña which can inflict severe damages as well. The present study focuses on the warming events only. However, an El Niño-year is followed by a La Niña-year, as a rough rule.
Climate change: a factor for ENSO changes?
“It is still unclear to which extent global warming caused by humankind’s emissions of greenhouse gases will influence the ENSO pattern,” says Schellnhuber. “Yet the latter is often counted among the so-called tipping elements in the Earth system, meaning that at some level of climate change it might experience a relatively abrupt transformation.” Certain data from the Earth’s past suggest that higher mean global temperatures could increase the amplitude of the oscillation, so correct forecasting would become even more important.
Article: Ludescher, J., Gozolchiani, A., Bogachev, M.I., Bunde, A., Havlin, S., Schellnhuber, H.J. (2013): Improved El Niño forecasting by cooperativity detection. Proceedings of the National Academy of Sciences (early online edition) [DOI:10.1073/pnas.1309353110]
Weblink to the article once it is published: http://www.pnas.org/cgi/doi/10.1073/pnas.1309353110
Improved El Niño forecasting by cooperativity detection
Contributed by Hans Joachim Schellnhuber, May 30, 2013 (sent for review March 12, 2013)
Although anomalous episodic warming of the eastern equatorial Pacific, dubbed El Niño by Peruvian fishermen, has major (and occasionally devastating) impacts around the globe, robust forecasting is still limited to about 6 mo ahead. A significant extension of the prewarning time would be instrumental for avoiding some of the worst damages such as harvest failures in developing countries. Here we introduce a unique avenue toward El Niño prediction based on network methods, inspecting emerging teleconnections. Our approach starts from the evidence that a large-scale cooperative mode—linking the El Niño basin (equatorial Pacific corridor) and the rest of the ocean—builds up in the calendar year before the warming event. On this basis, we can develop an efficient 12-mo forecasting scheme, i.e., achieve some doubling of the early-warning period. Our method is based on high-quality observational data available since 1950 and yields hit rates above 0.5, whereas false-alarm rates are below 0.1.
Preprint here: http://arxiv.org/ftp/arxiv/papers/1304/1304.8039.pdf (h/t to Dr. Leif Svalgaard)