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INCOIS’s new product to forecast El Niño and La Niña conditions


Why is it in the news?

  • Indian National Center for Ocean Information Services (INCOIS), based in Hyderabad, has introduced a novel tool called the Bayesian Convolutional Neural Network (BCNN) to forecast El Niño and La Niña conditions up to 15 months in advance.
  • The June 5 bulletin predicts a 70-90% probability of La Niña conditions from July to September, persisting until February 2025.
ENSO

·        ENSO refers to a climate phenomenon involving temperature changes in the central and eastern tropical Pacific Ocean, affecting global weather patterns with its warm (El Niño), cool (La Niña), and neutral phases.

About BCNN

  • The BCNN utilizes Artificial Intelligence (AI), deep learning, and machine learning (ML) technologies to enhance ENSO phase predictions.
  • It calculates the Niño3.4 index value, derived from sea surface temperature anomalies in specific equatorial regions, to generate forecasts.
  • BCNN combines dynamic modelling with AI, providing more accurate forecasts compared to traditional statistical and dynamic models.
  • BCNN can predict El Niño and La Niña emergence up to 15 months ahead, surpassing the 6 to 9-month forecasts of other models.
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