A New Metric to Diagnose Precipitation Distribution in Transitioning Tropical Cyclones

Abstract

A new coupled dynamic and thermodynamic metric is developed based on the Eady Moist Baroclinic Growth Rate (EMBGR), to discriminate between left-of-track (LOT) and right-of-track (ROT) precipitation distributions in transitioning tropical cyclones (TCs). LOT events pose a major flood risk even when a TC tracks along a coastline or just offshore, as flash flooding can occur hundreds of kilometers inland from the cyclone center. The EMBGR can improve human-produced quantitative precipitation forecasts (QPF) because it is dependent on relatively well-forecast large-scale mass fields. The ability of the EMBGR to identify precipitation distribution is first explored in a case study of TC Matthew (2016), using reanalysis and numerical model forecasts. Subsequently, a composite analysis of 36 years (1979–2014) of United States landfalling TCs using reanalysis data shows that the EMBGR is an effective discriminator between LOT and ROT distributions. The utility of the EMBGR is quantified using a pattern correlation analysis for both TC Matthew and the composites. Finally, a conceptual schematic is developed for LOT cases so that forecasters can most effectively utilize the EMBGR to improve human QPF skill during transitioning TCs.