Quantifying the Relationship between Embedded Rotation and Extreme Rainfall Rates in Observations of Tropical Storm Imelda (2019)

Previous work on continental convective systems has indicated that there is a positive relationship between short-term rainfall rates and storm-scale to mesoscale rotation. However, little has been done to explore this relationship in dense observing networks or in landfalling tropical cyclone (LTC) environments. In an effort to quantify the relationship between rainfall rates and embedded rotation of this scale, we use several sets of observations that were collected during Tropical Storm Imelda (2019). First, a meteorological overview of the event is presented, and the ingredients that led to its flash flood-producing rainfall are discussed. Then, two analyses that investigate the relationship between rainfall rates and storm-scale to mesoscale rotation in the LTC remnants are examined. The first method relies on products from the Multi -Radar Multi-Sensor system, where two spatial averaging approaches are applied to the 0-2-km accumulated rotation track and gauge bias-corrected quantitative precipitation estimate products over hourly time periods. Using these fields as prox-ies for rotation and rain rates, the results show a positive spatiotemporal relationship between the two products. The sec-ond method time matches subjectively identified radar-based rotation and 5-min surface rain gauge observations. There, we show that nearly twice the amount of rain was recorded by the gauges when storm-scale to mesoscale rotation was pre-sent nearby, and the differences in 5-min rainfall observations between when rotation was present versus not was statisti-cally significant. Together, these results indicate that more rain tended to fall in locations where there was rotation embedded in the system.