Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of uncertainty. Researchers have developed a lightweight machine learning framework that ...

Global climate models capture many of the processes that shape Earth's weather and climate. Based on physics, chemistry, ...

Hybrid climate modeling has emerged as an effective way to reduce the computational costs associated with cloud-resolving ...

Deep learning is increasingly being used to emulate cloud and convection processes in climate models, offering a faster alternative to computationally intensive cloud-resolving simulations. However, ...

A Georgia Tech-led review paper recently published in Nature Reviews Physics is exploring the ways machine learning is revolutionizing the field of climate physics — and the role human scientists ...

The History of Failed Apocalyptic Forecasts Let's be real, we've heard it all before. Such doomsday predictions have been ...

Vassili Kitsios is a senior research scientist at CSIRO, a co-chair of the Machine Learning for Climate and Weather Working Group of the Australian Climate Community Earth System Simulator National ...

Fifty years into the project of modeling Earth’s future climate, we still don’t really know what’s coming. Some places are warming with more ferocity than expected. Extreme events are taking ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...