For farmers, every planting decision carries risks, and many of those risks are increasing with climate change. One of the most consequential is weather, which can damage crop yields and livelihoods.

Researchers in China conceived a new PV forecasting approach that integrates causal convolution, recurrent structures, attention mechanisms, and the Kolmogorov–Arnold Network (KAN). Experimental ...

Predicting tropical cyclones (TCs) accurately is crucial for disaster mitigation and public safety. Although the forecasting accuracy of TC tracks has improved substantially in recent decades, ...

The observational track of Typhoon "Danas" (solid line) along with forecasted paths (dashed lines) depicted on the FY-4B satellite visible light imagery at 08:00 BST on July 6, 2025. The dashed lines ...

Google DeepMind, a London-based AI research lab, has been in the business of machine learning-based weather forecasting for several years, but back in June announced a new experimental AI model ...

Thanks to A.I., companies like WindBorne hope to usher in a golden age of forecasting. But they rely in part on government data — and the agency that provides it is in turmoil. A WindBorne weather ...

ECMWF has been developing the Artificial Intelligence Forecasting System (AIFS) to run side by side with its traditional physics-based Integrated Forecasting System (IFS) to advance numerical weather ...

Accurately predicting solar irradiance and wind flow patterns is requisite for renewable energy forecasting—but precision alone simply isn't enough. The data must be actionable, fast, and seamlessly ...