Mesoscale Convective Systems in a Global Kilometer-Scale Model: Evaluation and Contribution to Precipitation and Cloudiness Climatologies

Année de publication

2026

This study investigates the contribution of mesoscale convective systems (MCSs) to cold cloudiness and rainfall accumulation as simulated by a global model at kilometer-scale resolution. The realism of MCSs simulated by the convection-permitting model AROME-Global, developed at CNRM, in a 120-day global simulation is first assessed through comparisons with satellite observations. A detection and tracking algorithm is applied to infrared brightness temperatures derived from geostationary satellites as well to those computed from the model outputs. The spatial distribution of simulated MCSs is consistent with observations, although there are too numerous. Simulated systems display realistic morphological features but tend to be longer lived, do not reach observed sizes, and travel shorter distances than observed. At the scale of the tropics, AROME-Global shows weak biases in terms of rain amount and cold cloudiness, although it exhibits higher regional biases. Two highly biased regions (with biases of opposite signs) are analyzed: the Indian Ocean (IO) and the eastern Pacific intertropical convergence zone (ITCZ-EP). The IO rainfall deficit is attributed to MCSs that are too small and insufficiently precipitating, while the ITCZ-EP excess stems from an overestimation of small, weakly precipitating MCSs. These findings highlight that large-scale biases in MCS cloudiness and precipitation fields in AROME-Global are strongly tied to the statistical and morphological representations of tropical MCSs. Significance Statement Mesoscale convective systems (MCSs) are organized deep convective systems that contribute significantly to rainfall and cold cloudiness in the tropics. In this study, the ability of the global convective-permitting AROME-Global model in simulating MCS-related cloudiness and rain amount is assessed. In spite of weak biases at the scale of the tropics in terms of rain and radiation budget and rain, regional biases can be high. Simulated MCSs exhibit a realistic spatial distribution, although they are too numerous, have lifetimes that are too short, and underestimate the extent of cold cloud shields. Regional biases in rainfall and cold cloudiness can be attributed to biases in individual MCS properties showing some compensating behaviors.</div>

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