Comparing the dynamics of idealized squall lines between NWP and LES models

TL;DR

This study compares idealized squall line simulations between NWP and LES models, revealing both qualitative agreement and quantitative differences influenced by model physics and numerics, informing future model development and understanding.

Contribution

It provides a systematic comparison of NWP and LES models for squall lines, highlighting the impact of physics and numerics on simulation results at different resolutions.

Findings

MicroHH shows more intense circulation than ICON across resolutions.

Differences are mainly due to numerical diffusion and are sensitive to advection schemes.

Qualitative agreement supports applying LES insights to NWP models.

Abstract

Both Numerical Weather Prediction (NWP) models and Large-Eddy Simulation (LES) models are used to simulate convective systems, such as squall lines, but with different purposes. NWP models aim for the most accurate weather forecasts, whereas LES models are typically used to advance our understanding of physical processes. Therefore, these types of models differ in their design. With increasing computer power, the domain sizes and resolutions of these models converge, which raises the question if the model results also converge. We investigated an idealized squall line with the NWP model ICON (ICOsahedral Non-hydrostatic) and the LES model MicroHH. These models differ in their design, mainly because ICON solves the compressible equations on a triangular grid, while MicroHH solves the anelastic equations on a regular grid. The case setup, including resolution, domain size, boundary conditions, and microphysics scheme, is aligned between the models. The models simulate the same squall-line structure and circulation pattern in simulations with both warm and ice microphysics. However, there are quantitative differences with MicroHH having a more intense squall-line circulation than ICON at all resolutions (1 km, 500 m, and 250 m), mainly because MicroHH has less numerical diffusion. The magnitude of the differences is sensitive to the advection scheme and the resolution and less sensitive to the formulation of turbulent diffusion. The quantitative differences between the models across resolutions highlight the importance of model physics and numerics, whereas the good qualitative agreement gives confidence that insights from LES can be applied in NWP.