Understanding weather and climate dynamics using high-resolution global cloud resolving models

We introduce the 'Understanding weather and climate dynamics using high-resolution global cloud resolving models' project that brings together researchers from CICESE (Mexico), DTU (Denmark) and EPCC (UK) at the intersection of atmospheric science and high-performance computing to establish strategic international collaboration in using high-resolution global cloud resolving models. The project aims to advance understanding of atmospheric physics and dynamics at sub-km scale, whilst developing novel model implementations to analyse wind patterns. In alignment with NERC priorities, selected use cases focus on environmental hazards (e.g. resulting from storms) to improve resilience to extreme weather events and on improving wind resource assessment for wind energy systems which contribute to achieving net-zero targets.

We present the results from the physics scheme sensitivity studies at three diverse Mexican locations: La Rumorosa, Merida, and Oaxaca. MPAS-Atmosphere model is used with a publicly available non-uniform mesh configuration with coarsest resolution of 60 km and finest resolution of 3 km over the area of interest. The vertical grid employs 20 m spacing within the first 200 m above ground level, facilitating detailed comparisons of wind speed, temperature, and relative humidity between model output and meteorological station data collected at heights ranging from 20 to 80 m above ground.

This work lays the foundation for further collaboration moving to finer mesh resolutions and investigating performance of GPU-enabled MPAS to leverage next generation computing infrastructure, along with MPAS-LES and 3DPBL schemes for analysing the wake effects and atmospheric interactions of wind farm clusters.