Retrospective predictions of El Niño and La Niña in the past 148 yr. ABOVE, LEFT: Time series of SST anomalies averaged in the NINO3.4 region (5° S–5° N, 120–170° W). The red curve is monthly analysis of ref. 12 and the blue curve is the LDEO5 prediction at 6-month lead. ABOVE, RIGHT: Composite El Niño and La Niña from 24 warm events and 23 cold events. Top panels are observations, and the rest are predictions at different lead times. The colour bar shows the range of SST anomalies in degrees Celsius. © Nature Publishing Group (view larger image)

Chen and his colleagues report in the April 15 issue of the journal Nature that an improved climate model, known as LDEO5, for the first time predicted every major change in the temperature of the tropical Pacific Ocean over the past 150 years with up to two years of advance notice. In addition, their results suggest that ENSO is largely driven by internal relationships between ocean temperature and tropical winds rather than more unpredictable factors such as externally driven wind bursts, making the future of long-term climate prediction much more optimistic.

"No other model has been tested in such a long-term retrospective," said Chen, a senior research scientist at the Lamont-Doherty Earth Observatory, part of The Earth Institute at Columbia University. "In a two-tiered climate forecast system, a good first-tier forecast such as this is absolutely necessary for an accurate second-tier forecast of ENSO's global impacts."

El Niño and its opposite effect La Niña together make up the long-term variation in Pacific Ocean temperature that is thought to be behind events ranging from droughts in western Australia to changes in sardine catches off the coast of Peru. Together ENSO-related climate anomalies have been implicated in the deaths of tens of millions of people. Despite its importance, however, accurate predictions of ENSO have eluded scientists for decades and remain a goal of climate forecasters and public policy experts around the world.

Many theories describe ENSO as a chaotic and subsequently unpredictable force that governs water temperature in the Pacific Ocean between South American and Indonesia. Large-scale fluctuations in water temperature are believed to cause changes in tropical wind patterns that not only affect global climate patterns, but that themselves govern the movement of large masses of warm surface water across thousands of miles. Chen designed LDEO5 specifically to take into account the interrelated nature of the Earth's oceans and atmosphere and, using historical climate data, found that he was able to accurately predict the onset of large El Niño and La Niña events more accurately and with greater advance notice than any previous attempt.

Ultimately, Chen believes his model offers a strong case for a future when forecasters will be able to anticipate global climate change and climate-related disasters. "ENSO is by far the largest and most influential short-term climate fluctuation in the Earth's climate system," said Chen. "A better prediction of ENSO will not only benefit the tropical countries that are directly under the influence of ENSO, but will also improve our ability to manage disastrous floods and droughts in many parts of the world."

The Lamont-Doherty Earth Observatory, a member of The Earth Institute at Columbia University, is one of the world’s leading research centers examining the planet from its core to its atmosphere, across every continent and every ocean. From global climate change to earthquakes, volcanoes, environmental hazards and beyond, Observatory scientists provide the basic knowledge of Earth systems needed to inform the future health and habitability of our planet.

The Earth Institute at Columbia University is one of the world's leading academic centers for the integrated study of Earth, its environment and society. The Earth Institute builds upon excellence in the core disciplines — earth sciences, biological sciences, engineering sciences, social sciences and health sciences — and stresses cross-disciplinary approaches to complex problems. Through its research training and global partnerships, it mobilizes science and technology to advance sustainable development, while placing special emphasis on the needs of the world's poor.