Abstract

This study examines the characteristics of a large number of extreme rain events over the eastern two-thirds of the United States. Over a 5-yr period, 184 events are identified where the 24-h precipitation total at one or more stations exceeds the 50-yr recurrence amount for that location. Over the entire region of study, these events are most common in July. In the northern United States, extreme rain events are confined almost exclusively to the warm season; in the southern part of the country, these events are distributed more evenly throughout the year. National composite radar reflectivity data are used to classify each event as a mesoscale convective system (MCS), a synoptic system, or a tropical system, and then to classify the MCS and synoptic events into subclassifications based on their organizational structures. This analysis shows that 66% of all the events and 74% of the warm-season events are associated with MCSs; nearly all of the cool-season events are caused by storms with strong synoptic forcing. Similarly, nearly all of the extreme rain events in the northern part of the country are caused by MCSs; synoptic and tropical systems play a larger role in the South and East. MCS-related events are found to most commonly begin at around 1800 local standard time (LST), produce their peak rainfall between 2100 and 2300 LST, and dissipate or move out of the affected area by 0300 LST.

1. Introduction

Extreme rainfall is responsible for a variety of societal impacts, including flash flooding that can lead to damage, injury, and death. In an attempt to understand more about how these extreme-rain-producing weather systems are organized and the conditions in which they occur, Schumacher and Johnson (2005, hereafter SJ05) examined radar data and other observations for 116 extreme rain events in the eastern two-thirds of the United States over a 3-yr period. They found that approximately 65% of the events were associated with mesoscale convective systems (MCSs), 27% were caused by synoptically forced weather systems, and 8% resulted from tropical cyclones and their remnants. In addition, although the types of MCSs capable of producing extreme rainfall were varied, they found that two patterns of MCS organization were most frequently observed. These types were dubbed “training line/adjoining stratiform” (TL/AS; Fig. 1a), and “backbuilding/quasi-stationary” (BB; Fig. 1b). In the TL/AS pattern, convective cells typically move in a line-parallel direction, while there is very little motion in the line-perpendicular direction. This combination of motion characteristics leads to prolonged heavy rainfall at locations along the convective line. Backbuilding/quasi-stationary MCSs occur when convective cells repeatedly form upstream of their predecessors and pass over a particular area, leading to large local rainfall totals. This paper will provide more information about the climatological characteristics of these events, including their monthly and diurnal distributions, and information about the amount of rainfall that is typically observed with each type.

Fig. 1.

Schematic diagram of the radar-observed features of the (a) TL/AS and (b) BB patterns of extreme-rain-producing MCSs. Contours (and shading) represent approximate radar reflectivity values of 20, 40, and 50 dBZ. In (a), the low-level and midlevel shear arrows refer to the shear in the surface–925-hPa and 925–500-hPa layers, respectively. No consistent relationship was found between the direction of the shear and the orientation of the convection for BB MCSs; thus, no such vectors are shown in (b). The dash–dot line in (b) represents an outflow boundary; such boundaries were observed in many of the BB MCS cases. The length scale at the bottom is approximate and can vary substantially, especially for BB systems, depending on the number of mature convective cells present at a given time. From Schumacher and Johnson (2005).

Fig. 1.

Schematic diagram of the radar-observed features of the (a) TL/AS and (b) BB patterns of extreme-rain-producing MCSs. Contours (and shading) represent approximate radar reflectivity values of 20, 40, and 50 dBZ. In (a), the low-level and midlevel shear arrows refer to the shear in the surface–925-hPa and 925–500-hPa layers, respectively. No consistent relationship was found between the direction of the shear and the orientation of the convection for BB MCSs; thus, no such vectors are shown in (b). The dash–dot line in (b) represents an outflow boundary; such boundaries were observed in many of the BB MCS cases. The length scale at the bottom is approximate and can vary substantially, especially for BB systems, depending on the number of mature convective cells present at a given time. From Schumacher and Johnson (2005).

The best example of a flash flood “climatology” in the scientific literature is the study by Maddox et al. (1979, hereafter MCH79). They examined the synoptic and mesoscale atmospheric conditions during 151 flash flood events in all parts of the United States and pinpointed four surface and upper-air patterns in which the events typically formed. They also considered the spatial and temporal characteristics of these events. In total, MCH79 found that flash floods are possible during all seasons but are most common in the summer months (Fig. 2). However, this statement is highly dependent on the type of event being considered. “Synoptic” events (those associated with significant large-scale weather systems) are distributed fairly evenly throughout the year with slight maxima in the spring and fall, while “frontal” and “mesohigh” (cool-air outflow boundary) events occur almost exclusively during the warm season. This behavior is not surprising, since the baroclinic conditions necessary for synoptic weather system (i.e., extratropical cyclone) development are most often in place in the spring and fall, whereas MCSs and other convective systems are more prominent in summer. The research to be presented herein will build upon these results by including information about the organization of the systems producing the rainfall, rather than simply the prevailing environmental conditions.

Fig. 2.

Monthly distribution of the flash flood events studied by MCH79.

Fig. 2.

Monthly distribution of the flash flood events studied by MCH79.

Many others have worked to determine the climatological characteristics of flash flood and extreme rain events in different regions of the United States, including Changnon and Vogel (1981) in Illinois, Winkler (1988) in Minnesota, Foufoula-Georgiou and Wilson (1990) in the Midwest, Houze et al. (1990) in Oklahoma, Giordano and Fritsch (1991) in the mid-Atlantic region, Bradley and Smith (1994) in the southern Great Plains, Konrad (1997) in the southeastern United States, Junker et al. (1999) in the Midwest, and Moore et al. (2003) in the central United States. Although these studies have provided important results regionally, few studies have considered an area including the entire part of the country east of the Rockies.

Brooks and Stensrud (2000) objectively analyzed hourly precipitation data and found a July maximum for rainfall rates greater than 25.4 mm (1 in.) h−1. Their analysis of the seasonal distribution of this heavy rainfall shows that from October through March, rainfall of this magnitude is mainly confined to the Gulf coast states; from April through September, it occurs relatively frequently in all parts of the country east of the Rocky Mountains. One of the goals of their work was to make forecasters aware of how likely heavy rainfall might be during a particular time of year at a given location, which is a goal of this research as well. An understanding of the regional distribution of extreme rainfall is one key aspect of attaining this goal, with Brooks and Stensrud's work representing an important first step. Though this study will not consider rainfall rate per se, it will hopefully provide additional information (such as diurnal distributions) about where and when extreme rain can be expected.

Also key to this discussion is the variation in extreme rainfall frequency throughout the day. Wallace (1975) examined the diurnal variation of “heavy” precipitation across the United States, and found a nocturnal maximum for rain rates greater than 2.5 mm h−1 in the Great Plains and Midwest, and an afternoon or evening maximum in the East and South. Winkler et al. (1988) examined the seasonal variability of the diurnal distribution for even heavier rainfall, and obtained results similar to Wallace's: in the warm season, heavy precipitation is maximized during the overnight hours in the central part of the country, but an afternoon/evening maximum is evident across the southern and eastern states. Similar results were presented in more recent studies by Dai et al. (1999) and Knievel et al. (2004). Carbone et al. (2002) showed that these features of the diurnal cycle are caused by coherent convective “episodes” that typically form over the Rocky Mountains and propagate eastward.

Radar data can provide a further avenue for attaining information about the diurnal distribution of extreme rainfall, as it is not limited by flood reports nor by the sparsity of the rainfall observing network. Now that data from the Weather Surveillance Radars-1988 Doppler (WSR-88Ds) are readily available, such projects can be undertaken relatively easily. In this study, radar data will be used to observe various temporal characteristics of extreme rainfall events, such as the time of the heaviest rain and the times of precipitation onset and dissipation, aspects not always observable at a high resolution using traditional rain gauges.

In section 2, the data and methods used in the study are presented. The overall and regional monthly frequency distributions of extreme rain events using both a fixed and a spatially varying case selection threshold are presented in section 3. In section 4, these results are broken down by storm type, as determined from radar data. Section 5 includes the diurnal distributions of the events, and section 6 provides information about the rainfall characteristics and the occurrence of flash flooding and severe weather in conjunction with the heavy rainfall in the events.

2. Data and methods

a. Selection of cases

As in SJ05, the National Weather Service (NWS) cooperative high-resolution 24-h rain gauge network will be used to select the “extreme rain events” used in this study. For the month of May 2001, this network had 7923 active stations in the United States. Most of the stations in this network report 24-h rainfall in the morning [0600 or 0700 local standard time (LST)], though some stations report at other times of the day. Events were deemed extreme rain events when one or more of the gauges reported a 24-h rainfall total greater than the 50-yr recurrence amount (Hershfield 1961) for that location (Fig. 3). Events exceeding this threshold are those that have a 2% chance of occurrence in any given year, based on 30 yr of precipitation data. Since the completion of the analysis for the present study, the NWS has released updated precipitation recurrence interval data for parts of the eastern United States and the Ohio Valley. However, since these new data only cover part of the region of study, the older but complete (i.e., Hershfield 1961) thresholds will be used. The region of study will be the same as in SJ05, namely the part of the United States east of the Rocky Mountains, excluding Florida.

Fig. 3.

The 50-yr frequency for 24-h rainfall (in.) in the United States. Adapted from Hershfield (1961); figure courtesy of the Natural Resources Conservation Service of the U.S. Department of Agriculture. Also shown are regions that will be used, which are the same as those used in Karl and Knight (1998). They will be referred to as (clockwise from upper left) plains, North, Northeast, Ohio–Mississippi valley, Southeast, and South.

Fig. 3.

The 50-yr frequency for 24-h rainfall (in.) in the United States. Adapted from Hershfield (1961); figure courtesy of the Natural Resources Conservation Service of the U.S. Department of Agriculture. Also shown are regions that will be used, which are the same as those used in Karl and Knight (1998). They will be referred to as (clockwise from upper left) plains, North, Northeast, Ohio–Mississippi valley, Southeast, and South.

For this study, the 50-yr recurrence threshold was applied over a 5-yr period (1999–2003), which is 2 yr longer than the period used in SJ05. After eliminating bad rainfall data, it yielded 184 extreme rain events. Rainfall data were eliminated when there were no radar echoes in the area during the 24-h reporting period, or when radar and rain gauge data did not seem to match and no other documentation could be found to confirm that a large amount of rain actually fell in that area. For the purpose of this study, an “event” refers to a weather system that produces one or more rainfall observations over the extreme rainfall threshold. This typically represents all or part of the 24-h period in which the rainfall was reported. However, a single event can include multiple 24-h periods if the same weather system is responsible for the precipitation (e.g., a tropical cyclone that produces heavy rainfall over several states in a 2–3-day period).

In addition to the 50-yr recurrence threshold, some data will be presented in section 3 using a fixed case-selection criterion of 125 mm (24 h)−1 (125 mm is equal to approximately 4.92 in.). Though the spatially varying threshold described previously is most relevant for investigating events that are truly extreme for their location, the spatially fixed threshold shows how frequently a particular amount of rain occurs from one region to the next. In the 1999–2003 time period, 382 such events were identified after eliminating bad rainfall reports as described in the previous paragraph.

b. National composite radar reflectivity data

Each extreme rain event's life cycle was then observed using composite radar reflectivity data from the WSI Corporation NOWrad product. Data from the WSR-88Ds are used to generate this dataset, which has pixel resolution of 2 km × 2 km and temporal resolution of 15 min. Each event was classified as either an MCS, a synoptic system, or a tropical system, based on the radar observations. Convective systems with a region of reflectivity ≥40 dBZ extending more than 100 km in at least one direction and with durations between 3 and 24 h were classified as MCSs, consistent with the criteria of Orlanski (1975) and Parker and Johnson (2000). Events characterized by the strong large-scale ascent commonly associated with synoptic-scale features (i.e., extratropical cyclones) and/or lasting longer than 24 h were classified as synoptic. Thus, elongated (longer than ∼1000 km) prefrontal squall lines and other convective systems that persisted for longer than 24 h were classified as synoptic systems rather than MCSs, though mesoscale aspects (and sometimes even individual MCSs) clearly played an important role in the heavy rainfall. Events were classified as tropical if they were the direct result of a tropical cyclone or its remnants. While mesoscale processes may be important in all three of these classifications, the distinctions that have been drawn are motivated in part by operational forecasting concerns. Though the ingredients necessary for the development of extreme rainfall are the same regardless of the strength of forcing (e.g., Doswell et al. 1996), there are some different challenges involved with forecasting the rainfall associated with a strongly forced, elongated squall line compared with a landfalling tropical cyclone or an MCS occurring in an outwardly benign large-scale setting (e.g., Maddox and Deitrich 1982).

Synoptic and MCS events were also arranged into subclassifications based on their organizational structures and system evolutions. These subclassifications include distinguishing between convective and nonconvective synoptic systems, as well as breaking the MCS events into seven categories identified by Parker and Johnson (2000) and SJ05: TL/AS, BB, trailing stratiform (TS), parallel stratiform (PS), leading stratiform (LS), multiple MCSs, and other MCSs. The subclassifications are based on the dominant pattern of organization at the time when the system was producing the extreme rainfall. The details and methods of classifying events are the same as described in SJ05.

Additionally, several temporal characteristics of each event (as inferred from the radar data) were recorded. These include the time of heavy rain onset (the time of the first echo ≥45 dBZ in the area where extreme rainfall was reported), the time of peak rainfall (the hour in which high reflectivities were most persistent over the area), and the time when all radar echoes ended or moved out of the area. These times were cross-checked with hourly precipitation observations where available and adjusted if necessary.

c. Flash flood and severe weather reports

Though rain gauge observations were used as an objective way to select events for this study, it is also helpful to know whether the events selected actually caused flash floods, damage, or injury. In addition, since flash-flood-producing storms in the past have been associated with other types of severe weather (e.g., Smith et al. 2001; Rogash and Racy 2002), the proximity of severe wind, hail, and tornadoes to extreme rainfall could also be useful information. To this end, two online databases were surveyed to determine whether flash flooding and/or severe weather was reported in conjunction with the extreme rainfall. The first is the National Climatic Data Center (NCDC) Storm Events database (information online at http://www4.ncdc.noaa.gov/cgi-win/wwcgi.dll?wwEvent~Storms), which has written accounts of flash flooding, river flooding, severe weather, and several other weather-related phenomena. The second source is the preliminary storm reports archive from the Storm Prediction Center (SPC; information available online at http://www.spc.noaa.gov/climo/). This database provides a map of all tornadoes, severe wind, and severe hail reports on a given day. Both databases include the time of occurrence and a brief description of each event.

For each extreme rain event, the NCDC database was used to determine if flash flooding occurred at or near the location where the extreme rainfall totals were observed. Similarly, the SPC archive was used to find the locations and times of any nearby severe weather reports. If tornadoes were reported, the NCDC database was then checked to find their Fujita scale ratings. If flash flooding, severe wind, severe hail, tornadoes, or significant tornadoes (F2 or greater) were reported in conjunction with the extreme-rain-producing storm system at approximately the same time as the heavy rainfall was occurring, a “yes” was assigned for that phenomenon for that event. These determinations were made as accurately as possible using the available datasets.

3. Monthly frequency distributions

a. Fixed threshold

Using the criteria already described, there were 382 events in the years 1999–2003 where 125 mm of rain was reported in 24 h at one or more gauge. As one might expect, rainfall of this magnitude occurs most frequently in the southern part of the country (where moisture from the Gulf of Mexico is abundant) and is less frequent to the north (Fig. 4). [The regions used are the same as those used in Karl and Knight (1998) and the names that will be used are given in the caption for Fig. 3.] Such events can occur in all seasons in the southern United States, but are mainly confined to the warm season in the northern part of the country.

Fig. 4.

Monthly frequency distribution of 125 mm (24 h)−1 events in 1999–2003, by region (125 mm is equal to approximately 4.92 in.). The total distribution is shown at the bottom. Ordinates are scaled equally for the regional graphs and range from 0 to 30 events. The total number of events in each region is shown below that region's graph.

Fig. 4.

Monthly frequency distribution of 125 mm (24 h)−1 events in 1999–2003, by region (125 mm is equal to approximately 4.92 in.). The total distribution is shown at the bottom. Ordinates are scaled equally for the regional graphs and range from 0 to 30 events. The total number of events in each region is shown below that region's graph.

In total, such events are most common during June and July. In the South and Southeast regions, there are relative minima in July and August, with relative maxima before and after. The summer minima are likely attributable to the onset of the Bermuda high and the northward migration of the jet stream during the summer. Bradley and Smith (1994), studying rainfall in Oklahoma and northern Texas, found a similar bimodal distribution in 125 mm (24 h)−1 events over a 43-yr period. In contrast, July is the peak month for 125 mm (24 h)−1 events in the North and Ohio–Mississippi valley region. Rainfall of this magnitude is relatively rare in the plains and Northeast regions. Nearly all such events in the plains region occur in the warm season, and those in the Northeast are most frequently observed in March, August, and September.

This analysis shows the frequency at which 125 mm (24 h)−1 rainfall events occur in the United States and in what months they are most likely to occur in different regions. As mentioned in the previous chapter, 125 mm is a significant amount of precipitation for one day in any area, and these results provide information about where and when this much rain might be expected to fall. However, as these results show, it does not represent a truly extreme amount in all areas, and it happens so rarely in others that any generalizations made about the events that cause it would not be very meaningful. Therefore, the spatially varying extreme rain threshold (Fig. 3) is applied, which yields the cases (“extreme rain events”) that will be considered in the rest of the study.

b. Spatially varying threshold

The application of this threshold provides a sample (totaling 184 events) that is much more suitable for further study, since the number of events is more appropriately balanced throughout the country. The shapes of the monthly frequency distributions (Fig. 5) are mostly similar to those for the 125 mm (24 h)−1 events, and the consideration of more events in the plains and North regions leads to more meaningful results with substantial warm-season maxima. Interestingly, in an area-weighted sense, there are more extreme rain events in the regions that are farther from the Gulf of Mexico and the Atlantic Ocean. However, as will be discussed later, a single event (such as a hurricane) occurring in these coastal areas has the potential to produce a much greater amount of total precipitation than the events that typically occur in the central part of the country. The overall monthly frequency distribution (bottom of Fig. 5) generally resembles the findings of MCH79 (Fig. 2).

Fig. 5.

As in Fig. 4, but for extreme rain events as defined in the text. Ordinates range from 0 to 15 events on the regional graphs.

Fig. 5.

As in Fig. 4, but for extreme rain events as defined in the text. Ordinates range from 0 to 15 events on the regional graphs.

4. Results obtained using radar analysis

Since the monthly frequency distributions of extreme rain events vary greatly throughout the United States, it is likely that the types of weather systems responsible for these events also vary both seasonally and from region to region. With this in mind, national composite radar data were used to classify each event as synoptic, MCS, or tropical (as explained in SJ05 and in section 2). This analysis, which extends the results of SJ05 by 2 yr, shows that nearly two-thirds of all extreme rain events considered were associated with MCSs, and one-quarter were associated with synoptic weather systems (Table 1). Since almost all of the synoptic events also involved the repeated passage of deep convective cells, even more than two-thirds of the extreme rain events can be attributed to such convective processes.

Table 1.

Weather systems associated with extreme rain events, by region. Numbers in parentheses represent the percentage of events (rounded to the nearest whole percent) in a given region that are caused by the respective storm type. The sum of the regional values for each storm type does not necessarily equal the total in the right-hand column, because events spanning more than one region are counted in both regions but only once in the overall total.

Weather systems associated with extreme rain events, by region. Numbers in parentheses represent the percentage of events (rounded to the nearest whole percent) in a given region that are caused by the respective storm type. The sum of the regional values for each storm type does not necessarily equal the total in the right-hand column, because events spanning more than one region are counted in both regions but only once in the overall total.
Weather systems associated with extreme rain events, by region. Numbers in parentheses represent the percentage of events (rounded to the nearest whole percent) in a given region that are caused by the respective storm type. The sum of the regional values for each storm type does not necessarily equal the total in the right-hand column, because events spanning more than one region are counted in both regions but only once in the overall total.

MCSs were the most common extreme rain producers in every region except the Southeast, where tropical systems caused the most extreme rain events. In the plains and North regions, MCSs accounted for a large majority of the events, and the distribution in the Ohio–Mississippi valley region was very similar to the overall distribution. In the Northeast and South regions, MCSs were still the most common extreme rain producers, but synoptic and tropical systems played a larger role in those regions than in the region of study as a whole.

Though the overall percentage of tropical events was relatively low, the three events in the period of study that caused the most widespread and destructive flooding were all tropical cyclones: Hurricane Floyd (1999) along the East Coast, Tropical Storm Allison (2001) in the Gulf coast states, and Hurricane Isidore (2002) in the Gulf coast states and extending into the Ohio Valley. So, while there may be relatively few extreme rain events associated with tropical cyclones, the potential for damage and injury is much greater when they do occur. (The likelihood that a given landfalling tropical cyclone will produce extreme rain is much higher than that for a given MCS or synoptic system as well.)

The MCS and synoptic events were divided into subclassifications, as described in section 2 and in SJ05. The number of events grouped into each subclassification is given in Table 2. (This table is identical to Table 2 of SJ05, except that the 5-yr period 1999–2003 is considered instead of the 3-yr period 1999–2001.) Synoptic events that were dominated by convective storms were responsible for many more cases of extreme precipitation than those where nonconvective processes produced most of the rainfall. The TL/AS pattern was the most common MCS type, followed by the BB and TS types. This result is slightly different from that presented in SJ05; in that paper (covering the 1999–2001 time period), there were two more BB events than TS events. In this period of study, there were an equal number of BB and TS events.

Table 2.

Number of extreme rain events associated with the subclassifications of synoptic systems and MCSs.

Number of extreme rain events associated with the subclassifications of synoptic systems and MCSs.
Number of extreme rain events associated with the subclassifications of synoptic systems and MCSs.

The approximate location and storm type of each extreme rain event from 1999 to 2003 is shown in Fig. 6. These panels allow for comparison between years within the sample and help to illustrate where certain storm types are most prevalent. In 1999, the extreme rain events were heavily concentrated in the Dakotas, Iowa, and Illinois. There were also several tropical cyclones that affected the East Coast, including Hurricanes Dennis, Floyd, and Irene. In 2000, the events were more evenly distributed throughout the area of study, though there were several events in both Wisconsin and Illinois. Several major synoptic events affected the South in 2001, as did Tropical Storm Allison. In 2002, Minnesota was impacted by a large number of extreme rain events that caused major flooding. Hurricane Isidore also caused significant flooding after it produced widespread heavy rain from Louisiana northward to Indiana. Finally, in 2003, the center of activity moved eastward, with several extreme rain events in Tennessee, Virginia, and North Carolina, and relatively few in the plains.

Fig. 6.

Approximate locations and storm types of all extreme rain events in (a) 1999, (b) 2000, (c) 2001, (d) 2002, and (e) 2003. Lettering system is as follows: AS, TL/AS; MM, multiple MCSs; O, other MCSs; SC, synoptic/convective; SN, synoptic/nonconvective; and T, tropical. The BB, TS, LS, and PS systems are lettered accordingly. Cases where widespread extreme rainfall was reported are outlined.

Fig. 6.

Approximate locations and storm types of all extreme rain events in (a) 1999, (b) 2000, (c) 2001, (d) 2002, and (e) 2003. Lettering system is as follows: AS, TL/AS; MM, multiple MCSs; O, other MCSs; SC, synoptic/convective; SN, synoptic/nonconvective; and T, tropical. The BB, TS, LS, and PS systems are lettered accordingly. Cases where widespread extreme rainfall was reported are outlined.

Figure 6 also illustrates that the distribution of the MCS subclassifications varied from region to region. This distribution is quantified in Table 3. In the Northeast, other MCSs, which tend to be less organized than the other MCS types, played a large role. In the plains and the North regions, there were fewer MCS events classified as other than in the overall distribution. These contrasts likely come about because low-level jets, boundaries, and other mesoscale forcings required for organized MCSs are fairly common in the central United States, while they are less common in the eastern part of the country (e.g., Laing and Fritsch 1997). It is also important to note, however, that there were only seven MCS events in the Northeast region, so most of the results from this region should be interpreted with caution.

Table 3.

Distribution of extreme-rain-producing MCS types by region. Numbers in parentheses represent the percentage of MCS events in that region associated with the respective storm type. For example, the entry in the upper left indicates that TL/AS systems accounted for 36.4% of plains MCS cases.

Distribution of extreme-rain-producing MCS types by region. Numbers in parentheses represent the percentage of MCS events in that region associated with the respective storm type. For example, the entry in the upper left indicates that TL/AS systems accounted for 36.4% of plains MCS cases.
Distribution of extreme-rain-producing MCS types by region. Numbers in parentheses represent the percentage of MCS events in that region associated with the respective storm type. For example, the entry in the upper left indicates that TL/AS systems accounted for 36.4% of plains MCS cases.

The monthly frequency distribution of extreme rain events, separated by storm type, shows that most of the events occurring in the summer months are caused by MCSs, but nearly all of the cool-season events are associated with synoptic systems (Fig. 7 and Table 4). This result is not surprising, considering that the strongly baroclinic conditions that are prevalent in the cool season are supportive of strong synoptic systems, and MCSs typically occur in the weaker forcing and greater moisture of the warm season in the United States. However, it expands upon Fritsch et al.'s (1986) finding that 30%–70% of the total warm season precipitation in the Midwest results from MCSs by showing that 74% of extreme warm season (April–September) precipitation events in the entire eastern United States result from MCSs (Table 4). Although this does not speak to the proportion of the total amount of precipitation that results from extreme-rain-producing MCSs, it further emphasizes the important role that MCSs play in determining the warm-season precipitation characteristics of the United States.

Fig. 7.

Monthly frequency distribution of all extreme rain events, separated by storm type.

Fig. 7.

Monthly frequency distribution of all extreme rain events, separated by storm type.

Table 4.

Monthly frequency distribution of extreme rain events, including MCS subclassifications.

Monthly frequency distribution of extreme rain events, including MCS subclassifications.
Monthly frequency distribution of extreme rain events, including MCS subclassifications.

It was shown above that nearly all extreme rain events in the plains and the North regions occur during the warm season. In addition, nearly all of them are associated with MCSs. As such, the monthly frequency distributions for these regions (Figs. 8a and 8b) show an expected result: MCS-caused events that occur between May and September are the dominant extreme-rain-producing phenomena in these locations. Each of these regions did receive a few synoptic events (mainly in the spring and early summer). At locations this far north, temperatures are typically too cold and the necessary moisture is unavailable for extreme precipitation to occur outside of the warm season. Though extratropical cyclones certainly affect these regions during the winter, they usually bring snow instead of rain.

Fig. 8.

Monthly frequency distribution of all extreme rain events, separated by storm type, for the (a) plains, (b) North, (c) Ohio–Mississippi valley, (d) Northeast, (e) Southeast, and (f) South regions.

Fig. 8.

Monthly frequency distribution of all extreme rain events, separated by storm type, for the (a) plains, (b) North, (c) Ohio–Mississippi valley, (d) Northeast, (e) Southeast, and (f) South regions.

Slightly farther south and east in the Ohio–Mississippi valley region, synoptic systems play a greater role. Here, MCSs still produce the majority of the extreme rain events and are maximized in July, but cool-season synoptic events are also important (Fig. 8c). Because the temperatures and dewpoints in this region, on average, are higher than those farther north, some extratropical cyclones that traverse this region during the autumn and winter bring long-lived convective systems rather than heavy snow.

In the northeastern United States, extreme rainfall appears to occur on a different annual cycle, with nearly all of the events occurring in August and September (Fig. 8d). (Note once again, however, that there are relatively few Northeast events in the sample from which to draw these conclusions.) August had the maximum for MCS-related extreme rain events in the Northeast. Only 1 month later, however, MCSs, synoptic systems, and tropical systems all contributed equally. Though MCSs do play an important role in the Northeast, the number of extreme rain events in that region is also strongly dependent on tropical cyclones, an effect that will be discussed below.

The monthly frequency distribution in the Southeast region (Fig. 8e) is unique because it is strongly modulated by tropical cyclone activity. September is the most active month in this region, mainly because several tropical systems affected this region in September 1999–2003. Since tropical cyclone activity is extremely variable from year to year, it is possible that the results found here would be completely different if another 5-yr period were chosen for study. Thus, generalizations made about the monthly distribution in the Southeast region (and to some extent, the Northeast region) may not be as robust as those made about other regions.

Finally, in the South region, extreme rain events occur most often in the late spring, with a secondary maximum in autumn. Most of the springtime events result from MCSs, while all three types play an important role in the fall (Fig. 8f). Extreme rain events can occur in all months of the year in the South, as evidenced by the wintertime synoptic events.

The monthly frequency distributions of the individual MCS subclassifications are generally similar to the overall distribution for MCSs, with a few notable differences (Table 4). For instance, the BB MCSs are almost completely confined to the months of June and July, whereas TL/AS systems are more spreadout through the year. This result likely comes about because BB systems only occur when there is weak upper-level forcing (SJ05), and such conditions are usually observed only in the summer in the United States. On the other hand, the boundaries that typically force TL/AS MCSs are observed throughout more of the year.

5. Diurnal distributions

To understand the driving forces behind the convection, knowing the time of day at which it is most likely to occur is crucial. The results of previous work regarding the diurnal characteristics of convection in general and of extreme rainfall in particular were discussed in the introduction, and the results to be presented here should provide further insights into the diurnal cycle of precipitation. As briefly mentioned in section 2, three times in the life cycle of each extreme rain event will be discussed in the following. The onset time used here is the hour of heavy rain onset as determined using the radar data (the time of the first echo ≥45 dBZ at the extreme rainfall location for most systems), the peak time is the hour when the heaviest rain was falling at the station(s) where extreme rain was reported (inferred from the radar data and cross-checked with hourly precipitation data when available), and the end time is the hour when all radar echoes dissipated or moved out of the area. Synoptic, tropical, and multiple MCS cases have been eliminated from the diurnal distributions because their long durations make pinpointing onset and peak rainfall times difficult, and possibly not even meaningful. Thus, the discussion to follow pertains only to extreme-rain-producing MCSs. The diurnal characteristics will be presented in an overall sense, and then both by region and by storm type, since each of these perspectives is helpful in its own way.

In general agreement with past studies regarding heavy rainfall and flash floods, the storms producing extreme rainfall in this sample most often developed in the late afternoon and evening, peaked after dark, and dissipated or moved out of the area in the early morning hours (Fig. 9). The onset time for the “average” extreme rain event was around 1800 LST, with a peak between 2100 and 2300 LST and an end time around 0300 LST. This supports previous findings that most flash flood events are nocturnal (e.g., MCH79); although a peak rainfall time of 2100 LST may not be long after sunset during the summer, the flooding can occur up to 6 h after the causative rainfall—well after dark. Events began at all times of the day, but relatively few developed between 0200 and 1000 LST, with an associated minimum in rainfall peaks between 0500 and 1300 LST. As a whole, the diurnal cycle presented in Fig. 9 is very similar to that found by Jirak et al. (2003) for a large population of MCSs. These findings also agree with a conceptual model where convective storms form as a result of daytime heating, increase in coverage and intensity (and take on the structures that allow them to produce large local rainfall totals) as the low-level jet intensifies after dark, and either dissipate or move with greater speed in the early morning hours. Such processes have been described in part by Wallace (1975), MCH79, SJ05, and others. It should be noted that the end time presented in these results does not necessarily indicate the complete dissipation of the convective system, only that precipitation has ended at the location where extreme rainfall was reported. The MCSs responsible for extreme rainfall totals often persisted for several additional hours after leaving the area where they initially produced the heavy rains.

Fig. 9.

Diurnal frequency distribution for heavy rain onset, peak rainfall, and rainfall end for all 122 MCS-related extreme rain events, excluding the three classified as multiple MCS events. Number of events is smoothed with a 3-h running mean.

Fig. 9.

Diurnal frequency distribution for heavy rain onset, peak rainfall, and rainfall end for all 122 MCS-related extreme rain events, excluding the three classified as multiple MCS events. Number of events is smoothed with a 3-h running mean.

The diurnal frequency distributions in the plains and North regions are very similar to the overall distribution, with heavy rain beginning in the late afternoon/evening, peaking in the nighttime hours, and ending in the early morning (Figs. 10a and 10b). In the Ohio–Mississippi valley region (Fig. 10c), the most common onset, peak, and end times were similar to those in the sample as a whole, but the distributions of these times are broader than in the plains and North regions. This indicates that extreme-rain-producing convection in the Ohio–Mississippi valley may occur at a wider variety of times than in the regions farther north and west. The South region (Fig. 10d), along with a similarly wide diurnal distribution, had an average peak time at 2100 UTC but a somewhat later end time, suggesting that extreme rain events in the South have, on average, a longer duration than those in other regions. (Recall, however, that the amount of rain required for an event in the South to be “extreme” is greater than in other regions, so there may be an inherent bias toward longer-duration events in the South.) There were too few MCS events in the Northeast and Southeast regions to make meaningful conclusions about their diurnal distributions.

Fig. 10.

Diurnal frequency distribution for heavy rain onset, peak rainfall, and rainfall end for MCS-related extreme rain events, for the (a) plains, (b) North, (c) Ohio–Mississippi valley, and (d) South regions. Number of events is smoothed with a 3-h running mean.

Fig. 10.

Diurnal frequency distribution for heavy rain onset, peak rainfall, and rainfall end for MCS-related extreme rain events, for the (a) plains, (b) North, (c) Ohio–Mississippi valley, and (d) South regions. Number of events is smoothed with a 3-h running mean.

A possible explanation for the broader diurnal distributions observed in the South and Ohio–Mississippi valley regions is a change from a nocturnal rainfall regime to an afternoon regime as one moves from west to east across these regions (e.g., Wallace 1975). To test this idea, the diurnal distributions were calculated separately for the events occurring in the western parts of these regions and those occurring on the eastern side. Interestingly, these distributions were nearly indistinguishable. This similarity may be because the diurnal cycle for very heavy rainfall in these areas is different from that for the lighter rainfall rates studied by Wallace (1975). Crysler et al. (1982) showed that in Tennessee and West Virginia, intense rainfalls of short durations occurred most frequently during the afternoon and evening, but those lasting longer (with greater overall rainfall totals) typically occurred during the night and early morning hours.

The diurnal frequency distributions by storm type generally follow the overall distribution, though some storm types have wider distributions than others (Fig. 11). The TL/AS (Fig. 11a) and PS (Fig. 11d) distributions have typical onset, peak, and end times that are similar to the overall MCS distributions, while the other MCS (Fig. 11e) category has a distribution that is less straightforward. The most meaningful comparison may be between the distributions for BB (Fig. 11b) and TS (Fig. 11c) MCSs, since they have exactly the same number of events in the sample. The TS distributions for onset, peak, and end times have a slightly higher amplitude and are somewhat narrower than those for the BB systems, indicating that perhaps TS MCSs are modulated by the diurnal cycle to a greater extent than are BB MCSs. The reason for this is not entirely clear, but it may be that MCSs that take on the TS structure are more likely to be forced by diurnal processes over the western United States, such as in the “rain streaks” described by Carbone et al. (2002), while BB MCSs are more tied to mesoscale processes such as outflow boundaries. This would still lead to the nocturnal maximum for BB MCSs that is observed, but one that is less distinct than for some of the other MCS types.

Fig. 11.

Diurnal frequency distribution of heavy rain onset, peak rainfall, and rainfall end for (a) TL/AS, (b) BB, (c) TS, (d) PS, and (e) other MCS extreme rain events. Number of events is smoothed with a 3-h running mean.

Fig. 11.

Diurnal frequency distribution of heavy rain onset, peak rainfall, and rainfall end for (a) TL/AS, (b) BB, (c) TS, (d) PS, and (e) other MCS extreme rain events. Number of events is smoothed with a 3-h running mean.

The diurnal frequency distributions of extreme rain events suggest that some storm types (e.g., TL/AS and TS MCSs) and the convective systems in some regions (mainly in the northern part of the country) operate on a fairly consistent diurnal cycle, and other types and other regions have less predictable diurnal characteristics (e.g., BB MCSs and those in the South region). These results imply that in the northern United States, where there is also a strong seasonal cycle for extreme rainfall, the ingredients for extreme precipitation only come into place at very specific times of year and times of day. Or, in other words, a relatively rare set of circumstances (e.g., sufficient moisture, the presence of a low-level jet, or a boundary with a particular orientation), which only occurs in certain months and at certain times, is needed for extreme rainfall to occur in the northern part of the country. In other regions, a wider variety of conditions (less dependent on the diurnal and seasonal cycles) may support such events. The same may apparently be said for a few of the storm types.

6. Rainfall, flash flooding, and severe weather information

a. Rainfall characteristics

In this section, the maximum rainfall total reported during each event is considered. Every event selected for this study has exceeded a certain threshold to ensure that it is extreme for its area, however, there is still a question of which events tend to cause the most rainfall and have the most potential to cause serious damage. Certainly, these values are highly dependent on the density of the rain gauge network in the vicinity of the event—a high-resolution gauge network is more likely to capture the most extreme part of the storm than a lower-resolution network—but the objective statistics to be shown here agree generally with our own subjective ideas about which events were the most severe.

Of the MCS-related extreme rain events, BB systems tended to produce higher maximum 24-h rainfall totals than the other MCS types (Table 5, far-right column), with an average maximum report of 199.6 mm (7.9 in.). The reason that BB systems, on average, are capable of producing higher rainfall totals is that they appear to have no inherent temporal limit on their backbuilding and echo training effects. One can imagine such behavior lasting for many hours, as long as the moisture source for the convection is not removed. In contrast, forward-propagating linear MCSs usually have a convective line with certain motion characteristics, which can also result in extreme rainfall but only for the duration that the length of the line allows. (However, these statistics do not give any information about the overall rainfall coverage, which may be greater in the forward-propagating linear MCSs even though the extreme rainfall coverage is less.)

Table 5.

Average maximum 24-h rainfall total by region and storm type for several types of extreme rain events. For example, the upper-left entry indicates that the maximum reported rainfall averaged over all plains TL/AS events is 135.5 mm. The top entry in the “all regions” column, for instance, shows that the average maximum reported rainfall for all TL/AS events is 165.0 mm.

Average maximum 24-h rainfall total by region and storm type for several types of extreme rain events. For example, the upper-left entry indicates that the maximum reported rainfall averaged over all plains TL/AS events is 135.5 mm. The top entry in the “all regions” column, for instance, shows that the average maximum reported rainfall for all TL/AS events is 165.0 mm.
Average maximum 24-h rainfall total by region and storm type for several types of extreme rain events. For example, the upper-left entry indicates that the maximum reported rainfall averaged over all plains TL/AS events is 135.5 mm. The top entry in the “all regions” column, for instance, shows that the average maximum reported rainfall for all TL/AS events is 165.0 mm.

For purposes of comparison, the rainfall statistics for synoptic and tropical systems have been included in Table 5. Tropical cyclone–related extreme rain events were relatively rare but were by far the most devastating. The rainfall statistics show that the average maximum rainfall report for tropical events is over 70 mm greater than that for the BB MCSs.

Information about the storm types that caused the highest rainfall totals in each region is also shown in Table 5. The important data in this table are in the columns; intercomparing between regions is not helpful because the spatially varying threshold makes the average maximum rainfall in the South inherently higher than that in the North. The BB systems produced the highest rainfall totals (of the MCS types) everywhere but the Southeast region. In the Southeast, however, there were only one or two examples of each MCS subclassification, and therefore these results are likely insignificant.

b. Flash flooding

The main reason that rain gauge observations, as opposed to flash flood reports, were chosen as the criteria for selecting cases for this study is that flash flood reports are dependent on so many factors other than rainfall itself. First, using flash flooding adds the hydrological component to the problem, which introduces a great deal of complexity. Second, if flash flooding occurs, whether or not it actually gets reported depends on where it occurs and whether anyone was there to observe it. The rainfall observations are not perfect either, and the observing network has large gaps, but they provide a much more objective (and meteorological) approach to selecting cases.

With this in mind, one way to determine whether the thresholds developed for selecting extreme rain events are appropriate is to see if the cases selected were actually associated with flash flooding. If the extreme rain events were not responsible for flash flooding, then studying them would not get us any closer to solving the “flash flood problem.” Since only 24-h rainfall is being used here, and since rain rate also plays a role, it is possible that many of the events meeting the extreme rain criteria could be longer-duration events that produce copious amounts of rainfall but occur over long enough periods of time that they do not cause flooding. However, almost all of the cases used in this study did in fact cause flash flooding.

In total, 90.2% of MCS cases and 89.1% of all extreme rain events had corresponding flash flood reports (Table 6). The high percentage of cases with flash flooding was fairly consistent across the subclassifications as well, as the only types with significantly lower percentages were those with only a few cases to consider.

Table 6.

Number and percentage of extreme rain event types associated with flash flood (FF) reports.

Number and percentage of extreme rain event types associated with flash flood (FF) reports.
Number and percentage of extreme rain event types associated with flash flood (FF) reports.

c. Severe weather

Although severe weather is not as directly related to the events studied in this project as flash flooding, operational forecasters have to issue warnings for both while the events are occurring. A full treatment of how and why each of these types of systems produce severe weather is beyond the scope of this study, but data about how often each storm type produces hail, severe winds, and tornadoes may yield some information about the convective processes that are at work in each of them. More detailed information regarding the timing of severe weather in relation to heavy rainfall can be found in Wallace (1975), Maddox et al. (1986), and Rogash and Racy (2002).

In total, just under half of the extreme rain events also produced at least one severe wind report (58 mph or greater, as defined by the NWS; 1 mph = 0.447 m s−1), 42% produced severe hail (0.75 in. or greater; 1 in. = 25.4 mm), almost one-quarter spawned a tornado, and less than 5% produced a significant (rated F2 or higher on the Fujita scale) tornado (Table 7). The fact that so many extreme-rain-producing systems also caused severe winds seems to be somewhat of a contradiction, since severe windstorms typically require a dry layer aloft but heavy rain events need a deep moist layer. However, since organized MCSs and synoptic systems are responsible for so many of these events, it is possible that they attain a state whereby they can produce both extreme rainfall and strong straight-line winds, such as the wet microbursts described by Atkins and Wakimoto (1991) and others. This topic is suggested for future investigation. Tornadoes (and significant tornadoes) have been previously documented in conjunction with flash flood events (e.g., Rogash and Racy 2002), and a number of events of this type are found in this sample. However, the spatial and temporal resolutions of the radar data used herein do not allow for a more detailed analysis of any supercell structures that may have been embedded in the extreme-rain-producing MCSs.

Table 7.

As in Table 6 except for severe hail, winds, tornadoes, and significant tornadoes.

As in Table 6 except for severe hail, winds, tornadoes, and significant tornadoes.
As in Table 6 except for severe hail, winds, tornadoes, and significant tornadoes.

7. Summary and conclusions

Using rain gauge observations from the part of the United States east of the Rocky Mountains (excluding Florida) in 1999–2003, it was found that 184 events exceeded the 50-yr recurrence interval for 24-h precipitation accumulation. These cases were deemed extreme rain events. The overall characteristics of these events are generally consistent with past studies of heavy precipitation and flash floods:

  • Extreme rain events in the complete area of study occurred most frequently in July.

  • In the northern part of the country, extreme rain events were confined almost exclusively to the warm season; in the South, such events were generally less dependent on season.

As in SJ05, national composite radar reflectivity data were then used to make a quantitative determination about what types of weather systems are most often responsible for producing extreme rainfall totals. These radar data were observed over the life cycle of each extreme rain event to classify it as a synoptic system, a mesoscale convective system (MCS), or a tropical system. The synoptic and MCS events were also put into previously established subclassifications based on their radar-indicated organizational structures. Several results have emerged from this work:

  • The radar analysis showed that nearly two-thirds of all extreme rain events were associated with MCSs, and 25% resulted from synoptic weather systems.

  • The three most common patterns of MCS organization leading to extreme rainfall were TL/AS, BB, and TS.

  • In the plains and North regions, an even larger proportion of the events was associated with MCSs, and in the Southeast, tropical systems played a large role.

  • In almost the entire area of study, MCSs were the dominant summertime extreme rain producers. Seventy-four percent of summertime extreme rain events in the entire domain were caused by MCSs. In contrast, synoptically forced systems produced the most extreme rain events outside the warm season.

  • Extreme rainstorms typically have an onset time around 1800 LST, peak between 2100 and 2300 LST, and dissipate or move out of the affected area by 0300 LST. These results are consistent with past work showing that flash floods are most commonly nocturnal.

Other information about the extreme rain events in the sample, such as their rainfall production and whether they were accompanied by flash flooding or severe weather was also noted:

  • Tropical systems produced by far the most precipitation of any of the storm types. Of the MCS-related extreme rain events, BB MCSs tended to produce the highest maximum 24-h rainfall totals.

  • Nearly 90% of the extreme rain events had corresponding flash flood reports.

  • Just under half of the extreme-rain-producing storms also produced at least one severe wind report, 42% produced severe hail, almost one-quarter spawned a tornado, and less than 5% produced a significant tornado.

Acknowledgments

Precipitation data were provided by the National Climatic Data Center. The WSI NOWrad data were obtained from the Global Hydrology Resource Center at the Global Hydrology and Climate Center, Huntsville, Alabama. The authors thank David Ahijevych for assistance in obtaining additional radar data. The authors also thank three anonymous reviewers for their helpful suggestions. This research was supported by National Science Foundation Grant ATM-0071371, and the first author was partially supported by a one-year American Meteorological Society Graduate Fellowship.

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Footnotes

Corresponding author address: Russ Schumacher, Dept. of Atmospheric Science, Colorado State University, Fort Collins, CO 80523. Email: rschumac@atmos.colostate.edu