In an astonishing development, Google's DeepMind AI, Graphcast, has outperformed traditional weather models with its precise forecast of Cyclone Alfred's path, raising the possibility of a seismic shift in meteorology. When Alfred advanced towards the Australian coastline, traditional models wavered, suggesting varying paths. Yet, 12 days ahead, Graphcast accurately pinpointed its trajectory just 200 kilometers from Brisbane—a feat unmatched by leading meteorological organisations, including the Bureau of Meteorology (BOM).

What sets AI forecasting apart is its novel approach. Conventional models rely on complex equations processed by supercomputers, factoring millions of global observations. In contrast, AI models, like Graphcast, learn from patterns ingrained in decades of weather data without explicit scientific programming. This method is not only expedient and cost-effective but, as demonstrated, can enhance accuracy, particularly in predicting cyclonic paths.

AI's growing prowess could redefine forecasting. While traditional models grapple with computational intensity, AI's rapid processing and lower resource demands mark a potential evolution, despite current challenges in predicting unprecedented extremes. Though meteorologists remain integral to interpreting weather impacts, the future may see AI refining forecast precision and extending predictability beyond current horizons, heralding a new era in weather prediction.

- CyberBeat