Researchers at the Barcelona Institute for Global Health (ISGlobal) in Spain have developed a statistical climate model that can predict El Nino events up to 30 months in advance.
The model uses predictive factors like sea temperatures at different depths and tropical Pacific winds in a flexible statistical dynamic component scheme to retrospectively predict El Nino Southern Oscillation (ENSO) episodes between 1970 and 2016; the model can forecast all major events within that period 30 months prior to occurrence.
ISGlobal's Desislava Petrova said this advance can more precisely predict ENSO events, through the advent of the Tropical Pacific Observing System, which offers better data quality and coverage.
Said Petrova, "This allows us to make long-term forecasts of this climate phenomenon at a relatively low computational cost."
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Abstracts Copyright © 2019 SmithBucklin, Washington, DC, USA
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