The Hibiscus Coast may soon benefit from more accurate long-term weather forecasts thanks to advancements in artificial intelligence (AI).

Google's NeuralGCM model, combining machine learning with traditional atmospheric physics, is setting new standards in climate forecasting.

Developed with the European Centre for Medium-Range Weather Forecasts (ECMWF), NeuralGCM outperforms older models.

Using Google's AI tensor processing units, it can simulate 70,000 days of climate data in just 24 hours.

In comparison, the X-SHiELD model from the US National Oceanic and Atmospheric Administration can only simulate 19 days.

NeuralGCM's accuracy is notable. It identifies nearly as many tropical cyclones as traditional trackers and detects double the number found by X-SHiELD.

The model also has a 15-50% lower error rate in predicting temperature and humidity.

Despite these advances, experts like Peter Dueben from ECMWF and Cédric M. John from Queen Mary University of London note that further improvements are needed.

Future work will focus on better understanding the effects of CO₂ on global temperatures and simulating unusual climate scenarios.

Google's commitment to environmental efforts includes satellite missions to track methane emissions and partnerships with NASA for air quality monitoring, highlighting its dedication to using technology for a sustainable future.