16B.1
On the synoptic-scale makings of the most extreme warm-season precipitation events

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Friday, 3 July 2015: 10:30 AM
Salon A-5 (Hilton Chicago)
Shawn M. Milrad, Embry-Riddle Aeronautical University, Daytona Beach, FL; and J. R. Gyakum and E. H. Atallah

Previous work has examined the synoptic and mesoscale precursor characteristics of heavy (top 10%) warm-season precipitation events, using an ingredients-based methodology (lift, moisture, instability). These events were synoptically classified into four types: 1) Strong trough/cyclone, 2) warm front, 3) cold front, and 4) convective. The question remains, however, what separates the most extreme (top 1%) events from other high-end rainfall events? Using state-of-the-art NCEP Climate Forecast System Reanalysis (CFSR, 0.5 grid spacing) and Global Ensemble Forecast System (GEFS, 50 km grid spacing) reforecast data, the unique synoptic-scale precursors and structures associated with the most extreme warm-season rainfall events from 1979-2014 are investigated, and compared to lesser events. Initial results suggest that several days prior to the most extreme precipitation events, an anomalously strong downstream anticyclone helps to establish a persistent warm, moist, low-stability air mass. The intensity and persistence of the downstream anticyclone advects high-θe air poleward, which results in higher-θe air and a less stable environment at precipitation onset time (compared to lesser events). Moreover, the upstream mid-tropospheric trough is of similar average intensity between the most extreme events (top 1%) and slightly lesser events (top 10%). This result suggests that the downstream anticyclone is the distinguishing synoptic-scale contributor to the most extreme rainfall events, through moisture transport and air mass destabilization. GEFS reforecast data is used to show that for a subset (1983-2014) of extreme events, ensemble members that do a better job forecasting the intensity of the downstream anticyclone at 1-3 day lead times result in more accurate QPF.