A new hybrid modeling approach combines physics-based and machine learning models to extend—and improve—path and intensity predictions of tropical cyclones.
forecasting
Posted inNews
La transmisión de la malaria en África varía con el clima y la hidrología
Los datos sobre las precipitaciones por sí solos no pueden predecir dónde puede aparecer la malaria. Si se tienen en cuenta los procesos hidrológicos, los investigadores pueden hacerse una imagen más precisa de la transmisión.
Posted inFeatures
Sarah Minson: A Collaborative Quake Career
A geophysicist thrives on teamwork at the U.S. Geological Survey.
Posted inFeatures
Tanja Amerstorfer: Forecasting Space Weather
The deputy head of the Austrian Space Weather Office built a supportive network.
Posted inEditors' Highlights
Ocean Impacts on European Winter Weather
State-of-the-art high-resolution models are needed to reveal the ocean’s role in driving extra-tropical weather systems.
Posted inEditors' Highlights
Machine Learning Masters Weather Prediction
Community datasets and evaluation standards are needed to further advance machine learning for weather prediction.
Posted inNews
Malaria Transmission in Africa Shifts with the Climate—and Hydrology
Rainfall data alone can’t predict where malaria may pop up. Factoring in hydrological processes helps researchers paint a more nuanced picture of transmission.
Posted inNews
2024 Could Be Among Most Active Hurricane Seasons Ever
A new NOAA report predicts an extraordinarily active Atlantic hurricane season spurred by record ocean temperatures and a shift to La Niña conditions.
Posted inEditors' Highlights
A Powerful New Model for U.S. Climate–Air Quality Interactions
NOAA’s Geophysical Fluid Dynamics Laboratory has developed a new variable-resolution global chemistry-climate model for research at the nexus of U.S. climate and air quality extremes.
Posted inEditors' Vox
Harmonizing Theory and Data with Land Data Assimilation
Land data assimilation advances scientific understanding and serves as an engineering tool for land surface process studies, reflecting the trend of harmonizing theory and data in the big data era.