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.

OKLAHOMA CITY — Artificial intelligence is everywhere from our smartphones to self-driving cars, even at the grocery store. Everything is getting smarter. So, why shouldn't severe weather forecasts ...

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 ...

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.

Weather forecasting has long been a mix of science and intuition. You knew it would rain, but you didn't know exactly when.

As fire-weather risk expands beyond California, utilities are turning to sub-kilometer, asset-level forecasts to support public safety power shutoff decisions they can defend in front of regulators.

ZenaTech Inc. ZenaTech Launches Quantum Computing Project for Traffic Optimization and Weather Forecasting Using Drones 12-Dec-2024 / 14:00 CET/CEST The issuer is solely responsible for the content of ...

PG&E has begun using artificial intelligence to stay ahead of potential fires. The power company's machine learning model will help determine if planned power shut-offs will be necessary to prevent ...

New Delhi: NASA has introduced the Transient Artefact and Continuous Learning System (TACLS) to process satellite data and produce localised flood forecasts in as little as 15 minutes. The automated ...

Successful test results of a new machine learning (ML) technique developed at Georgia Tech could help communities prepare for extreme weather and coastal flooding. The approach could also be applied ...