Dr. Raghu Murtugudde, ESSIC and AOSC Professor, and an undergraduate student, have uncovered a major new finding about El Niño – the cyclical climate event that can appear every two to seven years, sometimes with major global weather impacts such as massive flooding and severe droughts.
The study, published online last month in Nature Climate Change, reveals a previously unrecognized sign of a looming El Niño that can be detected up to 18 months in advance, nine months earlier than current forecasting models allow, according to IndiaWest.
Murtugudde and Nandini Ramesh, who was an undergraduate student at the Divecha Centre for Climate Change, Indian Institute of Science, Bangalore when the research was performed, told IndiaWest their new clue to the beginning of an El Niño lies in the discharge of massive volumes of sub-surface warm water from the equatorial western Pacific Ocean north of Australia.
“Our new study shows that during the time between two El Niños warm waters accumulate below the surface at that point in the Pacific and then begin to discharge towards the west nearly 18 months before the December-January appearance of a new El Niño, when surface warming occurs at the International Dateline,” Murtugudde told IndiaWest.
“We found that this immaculate conception of El Niño with a gestation period of 18 months remains identical for all flavors [types] of El Niño and appears to be the most fundamental process that drives El Niños,” Murtugudde said.
Scientists have known for four decades that El Niño events appear when waters in the tropical eastern Pacific start to warm, according to the article. However, researchers have struggled to understand the early steps in this process even as they have watched three significant shifts, or flavors, in El Niños during the past 40 years, with the latest occurring since 2000.
“This is an exciting result that provides a new paradigm for understanding and predicting El Niños and for understanding the impact of global warming on El Niños,” said Murtugudde told IndiaWest. “It has the potential for offering a way forward to predict El Niño with a significant lead time of over a year and also provides a caution against simple models that use statistical approaches of surface expressions of El Niño to make El Niño predictions.”
