Resolving Mesoscale Convective Systems: Grid Spacing Sensitivity in the Tropics and Midlatitudes

Abstract

Mesoscale convective systems (MCSs) are a critical global water cycle component and drive extreme precipitation events in tropical and midlatitude regions. However, simulating deep convection remains challenging for modern numerical weather and climate models due to the complex interactions of processes from microscales to synoptic scales. Recent models with kilometer-scale horizontal grid spacings $\left(\Delta x\right)$ offer notable improvements in simulating deep convection compared to coarser-resolution models. Still, deficiencies in representing key physical processes, such as entrainment, lead to systematic biases. Additionally, evaluating model outputs using process-oriented observational data remain difficult. This study presents an ensemble of MCS simulations with $\Delta x$ spanning the deep convective gray zone ($\Delta x$ from 12 km to 125 m) in the Southern Great Plains of the U.S. and the Amazon Basin. Comparing these simulations with Atmospheric Radiation Measurement (ARM) wind profiler observations, we find greater $\Delta x$ sensitivity in the Amazon Basin compared to the Great Plains. Convective drafts converge structurally at sub-kilometer scales, but some deficiencies remain. In both regions, simulated up and downdrafts are too deep and extreme downdrafts are not strong enough. Furthermore, Amazonian updrafts are too strong. Overall, we observe higher $\Delta x$ sensitivity in the tropics, including an artificial buildup in vertical kinetic energy at scales of $5\Delta x$, suggesting a need for $\Delta x\le$ 250 m in this region. Nevertheless, bulk convergence—agreement of storm-average statistics—is achievable with kilometer-scale simulations within a $\pm$10% error margin with $\Delta x=$ 1 km providing a good balance between accuracy and computational cost.