
The atmospheric “predictability desert” has historically left a significant gap between short-term weather reports and seasonal outlooks, often leaving decision-makers in the dark for critical planning windows. The challenge of predicting temperature and precipitation weeks in advance is being addressed by treating machine learning as a sophisticated post-processing layer. This strategic shift moves away from the traditional reliance on ever-larger










