Global kilometer-scale models are the future of Earth system models as they can explicitly simulate organized convective storms and their associated extreme weather. Here, we comprehensively examined tropical mesoscale convective system (MCS) characteristics in the DYAMOND (DYnamics of the atmospheric general circulation modeled on non-hydrostatic domains) models for both summer and winter phases by applying eight different feature trackers to the simulations and satellite observations. Although different trackers produce substantial differences (a factor of 2-3) in observed MCS frequency and their contribution to total precipitation, model-observation differences in MCS statistics are more consistent among the trackers. DYAMOND models are generally skillful in simulating tropical mean MCS frequency, with multi-model mean biases of 2.9% over land and -0.5% over ocean. However, most models underestimate the MCS precipitation amount (23%) and their contribution to total precipitation (17%) relative to observations. These biases show large inter-model variability, but are generally smaller over land (13%) than over ocean (21%) on average. MCS diurnal cycle and cloud shield characteristics are better simulated than precipitation. Most models overestimate MCS precipitation intensity and underestimate stratiform rain contribution (up to a factor of 2), particularly over land. Models also predict a wide range of precipitable water in the tropics compared to reanalysis and satellite observations, and many models simulate a greater sensitivity of MCS precipitation intensity to precipitable water. The MCS metrics developed in this work provide process-oriented diagnostics for future model development efforts.

The spatiotemporal scale used to calculate extreme precipitation intensities can introduce strong biases when investigating their physical origin, impacts, and sensitivity to climate. Besides, the contribution of Mesoscale Convective Systems (MCSs) to tropical precipitation extremes remains loosely quantified on various scales, in particular on kilometer scales. Here we analyze the co-occurrence of extreme precipitation at convective and mesoscale levels to compare their properties in terms of precipitation morphology and regional predominance. Using a storm tracking algorithm, we contrast the occurrence and rain statistics for various types of convective systems across ten global storm-resolving models and one geostationary satellite product. We find a large statistical independence between rain extremes on these two scales, as they occur in distinct regions. Heavy km-scale events occur mostly over continents, over margins of convective zones, 40\% of which are produced by MCSs in observations. Their intensity is independent from the area of rain features. Conversely, heavy mesoscale rain intensities scale with the area of rain features, occur more frequently over oceans and a third of these events are produced by MCSs. More generally, a continuum between these extremes emerges from the wider variety of convective systems, quantified here as deep, very-deep and mesoscale convective systems. Compared to observations, models consistently underestimate the precipitating surface and show high variability in the contribution of convective systems to precipitation extremes at each scale. This diagnostic can serve as an evaluation criterion for the ability of GSRMs to represent how individual convective systems produce realistic heavy rain distributions.

Deep convective systems are ubiquitous over the tropical oceans and are central to the Earth radiation budget due to their upper-level cloud shields. Possible evolution of the morphology of these cloud shields with climate change remain poorly understood. In this study, the sensitivity of the cloud shield to environmental conditions is therefore investigated using a large dataset of atmopsheric profiles from renalaysis and satellite observations. The initial environmental conditions in stability, thermodynamics, and dynamics are explored. Multilinear regression between morphology and environment is used in a 2D phase space linked to the life cycle of the systems, namely the time to reach the maximum extension and the associated maximum area. Dynamical drivers show stronger morphological control than the thermodynamic factors. The result reveals an overwhelming role for wind shear over a deep tropospheric layer in explaining the scale dependence of cloud shield morphology. In particular, the variability of the shield growth rate is very well explained by deep layer shear (R2>0.8). The depth of the systems is also strongly related to dynamics and secondly to water vapor loading. These results feed the debate on the relative role of deep- vs. low-level shear in influencing deep convection and extend previous precipitation-centric considerations to the cloud shield of the systems. Possible underlying mechanisms are discussed, and the need to extend previous theoretical considerations on idealised convective geometry towards the whole spectrum of deep convective systems populating the tropical oceans is emphasised.