Ensemble-Based Forecast Uncertainty Analysis of Diverse Heavy Rainfall Events

Abstract

This study examines widespread heavy rainfall over 5-day periods in the central and eastern United States. First, a climatology is presented that identifies events in which more than 100 mm of precipitation fell over more than 800 000 km 2 in 5 days. This climatology shows that such events are most common in the cool season near the Gulf of Mexico coast and are rare in the warm season. Then, the focus turns to the years 2007 and 2008, when nine such events occurred in the United States, all of them leading to flooding. Three of these were associated with warm-season convection, three took place in the cool season, and three were caused by landfalling tropical cyclones. Global ensemble forecasts from the European Centre for Medium-Range Weather Forecasts Ensemble Prediction System are used to assess forecast skill and uncertainty for these nine events, and to identify the types of weather systems associated with their relative levels of skill and uncertainty. Objective verification metrics and subjective examination are used to determine how far in advance the ensemble identified the threat of widespread heavy rains. Specific conclusions depend on the rainfall threshold and the metric chosen, but, in general, predictive skill was highest for rainfall associated with tropical cyclones and lowest for the warm-season cases. In almost all cases, the ensemble provides very skillful 5-day forecasts when initialized at the beginning of the event. In some of the events-particularly the tropical cyclones and strong baroclinic cyclones-the ensemble still shows considerable skill in 96-216-h precipitation forecasts. In other cases, however, the skill drops off much more rapidly as lead time increases. In particular, forecast skill at long lead times was the lowest and spread was the largest in the two cases associated with meso-a-scale to synoptic-scale vortices that were cut off from the primary upper-level jet. In these cases, it appears that when the vortex is present in the initial conditions, the resulting precipitation forecasts are quite accurate and certain, but at longer lead times when the model is required to both develop and correctly evolve the vortex, forecast quality is low and uncertainty is large. These results motivate further investigation of the events that were poorly predicted.

Climatology and Environmental Characteristics of Extreme Precipitation Events in the Southeastern United States

“…Based upon the results of past studies (e.g., Maddox et al 1979;Keim 1996;Schumacher and Johnson 2006;Kunkel et al 2012;Prat and Nelson 2014), it is evident that the climatology of EPEs in the SEUS is characterized by a dichotomy between the cool season (;OctoberApril) and warm season (;May-September). For these two portions of the year, EPE environments can generally be viewed as occupying different areas of a hypothetical ''dynamics-thermodynamics'' phase space such that dynamical influences [e.g., quasigeostrophic (QG) forcing of ascent, transport of water vapor by a low-level jet (LLJ)] and thermodynamical influences [e.g., convective available potential energy (CAPE); precipitable water (PW)] tend to be dominant for cool-season and warm-season events, respectively.…”

“…The SEUS can experience this class of event in all seasons in conjunction with a variety of atmospheric phenomena, such as landfalling tropical cyclones (TCs; e.g., Atallah and Bosart 2003;Shepherd et al 2007;Konrad and Perry 2010;Knight and Davis 2009;Villarini and Smith 2010), extratropical baroclinic waves and cyclones (e.g., Maddox et al 1979;Konrad 1997;Moore et al 2012), and mesoscale convective systems (MCSs; e.g., Schumacher and Johnson 2006). Furthermore, the processes associated with EPEs in the SEUS are often influenced by the unique physical geography of the region.…”

“…Although a number of prior studies have investigated the climatological characteristics of EPEs affecting the SEUS in some form (e.g., Maddox et al 1979;Keim 1996;Konrad 1997Konrad , 2001Brooks and Stensrud 2000;Schumacher and Johnson 2006;Kunkel et al 2012), gaps in knowledge pertaining to this class of event remain. One pervasive problem is that many of these studies have used rain gauge observations, which have inherent limitations due to the spacing between observing stations (typically 25-50 km in the SEUS).…”

Geospatial Analysis of Space–Time Patterning of ENSO Forced Daily Precipitation Distributions in the Gulf of Mexico

“…4. The Gulf Coast is at risk of freshwater flooding in the cool season (Lecce 2000;Schumacher and Christopher 2010) and is home to a large potentially vulnerable human population that engages in economic activities vital to national economies (Boruff, Emrich, and Cutter 2005).…”

Key synoptic-scale features influencing the high-impact heavy rainfall in Beijing, China, on 21 July 2012

“…The European Centre for Medium-Range Weather Forecasts (ECMWF) Ensemble Prediction System (EPS) has been used to explore rainfall predictability, and the results showed that precipitation is more predictable during the winter than in the summer and rainfall associated with tropical cyclones is more predictable than the warm-season cases (Buizza et al, 1999;Mullen and Buizza, 2001;Schumacher and Davis, 2010). ECMWF EPS was also used to identify key factors influencing the May 2010 extreme rainfall in Tennessee and Kentucky (Lynch and Schumacher, 2014) and longer-term warm-season rainfall (Schumacher, 2011).…”