The Portable Model for multi-scale Atmospheric Prediction (PMAP): Sub-kilometre simulations of recent extreme weather

The Portable Model for multi-scale Atmospheric Prediction (PMAP) is a numerical model currently under development at ECMWF and ETH aimed at large-eddy simulation (LES) of atmospheric flows at the weather-system scale. It builds on a non-hydrostatic, locally conserving, finite-volume, 3D semi-implicit dynamical core coupled to state-of-the-art physics parametrizations. Written entirely in Python, it leverages the GT4Py domain-specific language to achieve high performance and portability – running straightforwardly on laptops and GPU accelerated HPC systems alike. The systematic separation of concerns between domain science (physics, numerics) and performance engineering (parallelisation, hardware optimisation) provides new avenues for model development, setup, and refinement, which we present in two related contributions.

In this second contribution, we present two examples that demonstrate the benefits of resolving small-scale processes for simulating real weather and showcase how PMAP can flexibly be used as a research tool for atmospheric dynamics. (i) First, we demonstrate the benefits of sub-kilometer spatial resolution for accurately simulating the intensification of Hurricane Melissa in late October 2025 as compared to an operational km-scale model. (ii) Second, we present results from a process study of storm Éowyn, which brought record-strong winds to the British Isles in January 2025. LES of the low-level jet along the storm’s bent-back front not only accurately predicts peak wind speeds, but also resolves individual wind gusts in close agreement with observations. We highlight a range of diagnostic tools implemented in PMAP that make such analyses straightforward. Moreover, we demonstrate how the model can be employed to shed light on the atmospheric dynamical processes leading to the storm’s rapid intensification. Specifically, we show the importance of latent heat release by performing modified latent heating experiments, which in the PMAP framework are straightforward to set up, and quantitatively corroborate the crucial impact of cloud microphysical processes for the rapid intensification of Éowyn.