Ph.D. student Phillip Si and Assistant Professor Peng Chen developed Latent-EnSF, a technique that improves how ML models assimilate data to make predictions.

Weather forecasting is not easy. The truth is that predicting future weather conditions over broad, or even narrow, swaths of Earth's surface comes down to complex microphysical processes, and as ...

The Weather Company is deploying next-generation technologies to improve prediction—and at a very critical time ...

The reauthorization act received unanimous, bipartisan support, but a similar bill passed the House and stalled in the Senate ...

A range of national meteorological services across Europe and ECMWF have launched Anemoi, a framework for creating machine learning (ML) weather forecasting systems. Named after the Greek gods of the ...

After a hurricane passes, scientists routinely evaluate the computer models that predicted its path and power. This year, a ...

Hurricane danger reaches far beyond the coast with flooding rains and violent winds. Forecasting takes more than radar. It ...

Machine Learning-based weather models have the potential to revolutionise global seasonal forecasting, according to new Met ...

AI models can deliver localized forecasts faster and cheaper than traditional models. The challenge is getting this ...

Meteorologists and other environmental scientists rely on numerical forecast models to aid in developing a weather outlook. These models, such as the American GFS model and European ECMWF model, use ...