Sensitivity of organized convective storms to model grid spacing in current and future climates.

Mesoscale convective systems (MCSs) are complexes of thunderstorms that become organized and cover hundreds of kilometres over several hours. MCSs are prolific rain producers in the tropics and mid-latitudes and are the major cause of warm-season flooding. Traditionally, climate models have difficulties in simulating MCSs partly due to the misrepresentation of complex process interactions that operate across a large range of scales. Significant improvements in simulating MCSs have been found in kilometre-scale models that explicitly simulate deep convection. However, these models operate in the grey zone of turbulent motion and have known deficiencies in simulating small-scale processes (e.g. entrainment, vertical mass transport). Here, we perform mid-latitude idealized ensemble MCS simulations under current and future climate conditions in three atmospheric regimes: hydrostatic (12 km horizontal grid spacing; Δx), non-hydrostatic (Δx = 4, 2 and 1 km) and large eddy scale (Δx = 500 m and 250 m). Our results show a dramatic improvement in simulating MCS precipitation, movement, cold pools, and cloud properties when transitioning from 12 km to 4 km Δx. Decreasing Δx beyond 4 km results in modest improvements except for up- and downdraft sizes, average vertical mass fluxes, and cloud top height and temperature, which continue to change. Most important for climate modelling is that Δx = 4 km simulations reliably capture most MCS climate change signals compared to those of the Δx = 250 m runs. Significantly different climate change signals are found in Δx = 12 km runs that overestimate extreme precipitation changes by up to 100%. This article is part of a discussion meeting issue 'Intensification of short-duration rainfall extremes and implications for flash flood risks'.

Challenges and outlook for convection-permitting climate modelling.

Climate projections at very high resolution (kilometre-scale grid spacing) are becoming affordable. These 'convection-permitting' models (CPMs), commonly used for weather forecasting, better represent land-surface characteristics and small-scale processes in the atmosphere such as convection. They provide a step change in our understanding of future changes at local scales and for extreme weather events. For short-duration precipitation extremes, this includes capturing local storm feedbacks, which may modify future increases. Despite the major advance CPMs offer, there are still key challenges and outstanding science issues. Heavy rainfall tends to be too intense; there are challenges in representing land-surface processes; sub-kilometre scale processes still need to be parametrized, with existing parametrization schemes often requiring development for use in CPMs; CPMs rely on the quality of lateral boundary forcing and typically do not include ocean-coupling; large CPM ensembles that comprehensively sample future uncertainties are costly. Significant progress is expected over the next few years: scale-aware schemes may improve the representation of unresolved convective updrafts; work is underway to improve the modelling of complex land-surface fluxes; CPM ensemble experiments are underway and methods to synthesize this information with larger coarser-resolution model ensembles will lead to local-scale predictions with more comprehensive uncertainty context for user application. Large-domain (continental or tropics-wide) CPM climate simulations, potentially with additional earth-system processes such as ocean and wave coupling and terrestrial hydrology, are an exciting prospect, allowing not just improved representation of local processes but also of remote teleconnections. This article is part of a discussion meeting issue 'Intensification of short-duration rainfall extremes and implications for flash flood risks'.