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

Developed by a team led by Daniel Klocke at the Max Planck Institute for Meteorology in Germany, the model reaches a spatial resolution of 1.25 kilometers -- a level many atmospheric scientists have ...

Deep learning is increasingly being used to emulate cloud and convection processes in climate models, offering a faster ...

We've been watching temperatures climb, extreme weather events intensify, and ice sheets shrink. Every weather forecast and ...

Simply sign up to the Climate change myFT Digest -- delivered directly to your inbox. Scientists in Europe are creating an ...

Nvidia (NVDA) announced two new NVIDIA NIM microservices that can accelerate climate change modeling simulation results by 500x in NVIDIA Earth-2. Earth-2 is a digital twin platform for simulating and ...

The Madden–Julian Oscillation (MJO), as a key driver of global weather and climate anomalies, is an important source of subseasonal predictability. However, most climate models still struggle to ...

Hybrid climate modeling has emerged as an effective way to reduce the computational costs associated with cloud-resolving models while retaining their accuracy. The approach retains physics-based ...

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