TY - JOUR
T1 - Improved El niño forecasting by cooperativity detection
AU - Ludescher, Josef
AU - Gozolchiani, Avi
AU - Bogachev, Mikhail I.
AU - Bunde, Armin
AU - Havlin, Shlomo
AU - Schellnhuber, Hans Joachim
PY - 2013/7/16
Y1 - 2013/7/16
N2 - 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 earlywarning 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.
AB - 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 earlywarning 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.
KW - Climate
KW - Cross-correlations
KW - Dynamic networks
KW - ENSO
KW - Spring barrier
UR - http://www.scopus.com/inward/record.url?scp=84880358929&partnerID=8YFLogxK
U2 - 10.1073/pnas.1309353110
DO - 10.1073/pnas.1309353110
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C2 - 23818627
AN - SCOPUS:84880358929
SN - 0027-8424
VL - 110
SP - 11742
EP - 11745
JO - Proceedings of the National Academy of Sciences of the United States of America
JF - Proceedings of the National Academy of Sciences of the United States of America
IS - 29
ER -