Recursive AI Weather Forecasting

Enhance Climate Resilience with High-Resolution Forecasting

Accurate weather forecasting is critical across industries to mitigate the growing effects of climate change. However, many existing systems lack the granularity and reliability required for local decision-making. According to the World Meteorological Organization, since 1970, weather-related disasters have caused over 2 million deaths and $3.64 trillion in economic losses globally.

Recursive AI Weather Forecasting uses cutting-edge machine learning and physics-based modeling to deliver precise, high-resolution predictions. With a native resolution of 300 meters (scalable to 100 meters), it offers unparalleled accuracy for temperature, wind, and rainfall forecasts to support critical industries.

Highlights

• Temperature Predictions: Achieve reliable forecasts with an average error margin of ±1℃.

Impact: Enables energy providers to optimize heating and cooling systems, reducing costs and minimizing energy waste, while helping communities prepare for extreme temperatures.

• Wind Predictions: Support renewable energy initiatives with precise wind forecasts.

Impact: Improves wind turbine placement and operations, stabilizing energy grids and maximizing renewable energy production efficiency.

• Rainfall Predictions: Provide highly accurate rainfall forecasts with a 30% lower error rate compared to global standards in Japan.

Impact: Assists farmers in optimizing irrigation schedules and planting strategies, increasing crop yields and ensuring sustainable resource use.

• Flood Risk Management: Deliver hyper-localized flood predictions for proactive measures.

Impact: Reduces property damage and saves lives by enhancing disaster preparedness and response, cutting potential economic losses by significant margins.

Implementation