Scientists have found a new way to predict El Nino and La Nina events much earlier. A study highlighted by NOAA combines two artificial intelligence methods to forecast a key climate indicator up to a year and a half in advance. The method predicted extreme El Nino and La Nina events with about 85 per cent accuracy, a strong result for such long-range forecasts. El Nino and La Nina, together known as ENSO, shape weather around the world. They influence rainfall, drought, hurricanes and even food prices. Better long-range forecasts can help farmers, water managers and disaster planners prepare. The research is part of a wave of NOAA-backed studies using new tools to understand the climate, alongside new hurricane flight patterns and atmospheric river findings. For India, ENSO is closely watched because El Nino is often linked to weaker monsoons, while La Nina can bring stronger rains. An 18-month lead time would give policymakers far more room to plan for water, crops and power demand. The study shows how deep learning can pull patterns from vast climate data that older models miss. Researchers say the approach could also improve forecasts of other slow-moving climate shifts.