A Global High-resolution Mesoscale Convective System Database using Satellite-derived Cloud Tops, Surface Precipitation, and Tracking
A new methodology is developed to construct a global high-resolution (~10-km, hourly) mesoscale convective system (MCS) database by tracking MCS jointly using geostationary satellite infrared brightness temperature (Tb) and precipitation feature (PF) characteristics from the Integrated Multi-satellitE Retrievals for GPM (IMERG) precipitation datasets. Independent validation shows that the satellite-based MCS dataset is able to reproduce important MCS statistics derived from ground-based radar network observations in the U.S. and China. We show that by carefully considering key PF characteristics in addition to Tb signatures, the new method significantly improves upon previous Tb-only methods in detecting MCSs in the midlatitudes for all seasons. Results show that MCSs account for over 50% of annual total rainfall across the majority of the tropical belt and in select regions of the subtropics and midlatitudes, with a strong seasonality over many regions of the globe. The tracking database allows Lagrangian aspects such as MCS lifetime and translational speed and direction to be analyzed. The longest-lived MCSs preferentially occur over the subtropical oceans. The land MCSs have higher cloud-tops associated with more intense convection, and oceanic MCSs have much higher rainfall production. While MCSs are observed in many regions of the globe, there are fundamental differences in their dynamic and thermodynamic structures that warrant better understanding of processes that control their evolution. This global database provides significant opportunities for observational and modeling studies of MCSs, their characteristics and roles in regional and global water and energy cycles, as well as their hydrologic and other impacts.