A dataset of tracked mesoscale precipitation systems in the tropics

Abstract

Mesoscale Convective Systems (MCSs) are often quantified via surface-based radar network, geostationary satellite, or low earth orbit satellite observations. However, each of these has drawbacks for detecting cloud systems such as a lack of global coverage, a lack of variables to quantify deep convective cloud and precipitation properties, and a lack of continuous observations of individual MCSs, respectively. To generate a dataset of tropical Tracked IMERG Mesoscale Precipitation Systems (TIMPS), we use the Forward in Time tracking algorithm to track precipitation systems in the Integrated Multi-satellitE Retrievals for the Global Precipitation Mission (IMERG). IMERG is a global gridded precipitation product that incorporates observations from a constellation of satellites with passive microwave sensors and other sources, allowing the TIMPS dataset to have continuous temporal precipitation information for MCSs in a global tropical strip with data every 30 min in time and 0.1° in space. TIMPS are provided in a publicly available data base with a variety of variables including MCS size, motion, and precipitation properties, estimations of MCS life cycle stages, and their proximity to the nearest tropical cyclone. By combining the TIMPS dataset with the University of Washington Convective Features database, we also provide snapshots of information from more spatially detailed space-borne radar coverage. The TIMPS dataset provides the means for detailed long-term and large-scale study of MCSs in all regions of the tropics with applications such as composite studies of MCS life cycles and the evaluation of model performance.