A Process-Based Tracking Algorithm and the Resulting 27-Year Reference Dataset for Evaluating European Warm-Season Mesoscale Convective Systems in Climate Models

Process-based evaluation of Mesoscale Convective System (MCS) in European climate models is complicated by a critical challenge: the conflation of self-sustaining, propagat- ing convection with synoptic-scale frontal precipitation. Datasets that mix these phys- ically distinct phenomena risk misinterpreting model skill. To address this, we introduce the Evolution-based Mesoscale Convective System Model Assessment (EMMA)-Tracker, a new algorithm designed to use standard model output variables. We apply this tracker to Integrated Multi-satellitE Retrievals for GPM (IMERG) precipitation and ECMWF Reanalysis v5 (ERA5)-derived lifted index to generate a 27-year (1998–2024) warm-season MCS climatology that serves as a reference dataset. The tracker’s core novelty is a set of physics-based post-processing filters, based on MCS characteristic environment and movement, that isolate coherently propagating systems. The resulting climatology shows MCS hotspots are concentrated over major orography (Alps, Dinaric Alps) with an af- ternoon initiation peak. While these MCSs contribute moderately (10–30%) to total sea- sonal precipitation, their role becomes dominant for heavy hourly precipitation. The MCS contribution systematically increases with intensity, accounting for over 60% of heavy precipitation across most of continental Europe. The EMMA-Tracker provides a robust benchmark to enable targeted, process-based evaluation of organized convection in cli- mate models.