Computational science is crucial for delivering reliable weather and climate predictions.
However, despite decades of high-performance computing experience, there is serious …

Accelerated progress in climate modeling is urgently needed for proactive and effective
climate change adaptation. The central challenge lies in accurately representing processes …

Extreme weather amplified by climate change is causing increasingly devastating impacts
across the globe. The current use of physics-based numerical weather prediction (NWP) …

There are contrasting views on how to produce the accurate predictions that are needed to
guide climate change adaptation. Here, we argue for harnessing artificial intelligence …

Traditional general circulation models, or GCMs—that is, three-dimensional dynamical
models with unresolved terms represented in equations with tunable parameters—have …

The new generation of heterogeneous CPU/GPU computer systems offer much greater
computational performance but are not yet widely used for climate modeling. One reason for …

We analyse how the representation of deep convection affects the characteristics of
convective precipitation over tropical Africa in global storm‐resolving simulations with the …

Due to the rapidly changing climate, the frequency and severity of extreme weather is
expected to increase over the coming decades. As fully‐resolved climate simulations remain …

There are different strategies for training neural networks (NNs) as subgrid‐scale
parameterizations. Here, we use a 1D model of the quasi‐biennial oscillation (QBO) and …

The land-surface developments of the European Centre for Medium-range Weather
Forecasts (ECMWF) are based on the Carbon-Hydrology Tiled Scheme for Surface …