Space weather forecasting remains a major challenge in heliophysics, as geomagnetic storms continue to pose significant risks to satellite operations, power ...

Weather forecasting traditionally relies on numerical weather prediction (NWP) systems that integrate global observations, data assimilation (DA), and physics-based models. However, further advances ...

A research team focused on the extreme rainfall event of "21·7" in Henan in 2021. By analyzing anomalous physical characteristics and understanding multi-model forecast biases, they significantly ...

The temperature of rivers is something most people think about only if they plan to go swimming, kayaking or spend a day ...

Accurate streamflow forecasting is critical for water resources management, flood mitigation and hydropower operations worldwide. Traditional hydrological models based on physical processes often ...

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.

A new system for forecasting weather and predicting future climate uses artificial intelligence (AI) to achieve results comparable with the best existing models while using much less computer power, ...

A new open-source machine learning system cuts flash food forecasting time to just 15 minutes. The tool automates complex ...

As the world grapples with the energy crisis and environmental concerns, the focus on renewable energy sources has intensified. Lithium-ion batteries, with their high energy density and low pollution, ...

Forecasting inflation has become a major challenge for central banks since 2020, due to supply chain disruptions and economic uncertainty post-pandemic. Machine learning models can improve forecasting ...