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Geological and Atmospheric Sciences Publications Geological and Atmospheric Sciences

2010 and Summer Midwestern Severe Reports in Compared to Other Morphologies Jeffrey Dean Duda Iowa State University, [email protected]

William A. Gallus Jr. Iowa State University, [email protected]

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This Article is brought to you for free and open access by the Geological and Atmospheric Sciences at Iowa State University Digital Repository. It has been accepted for inclusion in Geological and Atmospheric Sciences Publications by an authorized administrator of Iowa State University Digital Repository. For more information, please contact [email protected]. Spring and Summer Midwestern Reports in Supercells Compared to Other Morphologies

Abstract This study compares severe weather reports associated with the nine convective system morphologies used in a recent study by Gallus et al. to an additional morphology, . As in that previous study, all convective systems occurring in a 10-state region covering parts of the Midwestern and central plains were classified according to their dominant morphology, and severe weather reports associated with each morphology were then analyzed. Unlike the previous study, which examined systems from 2002, the time period over which the climatology was performed was shifted to 2007 to allow access to radar algorithm information needed to classify a as a supercell. Archived radar imagery was used to classify systems as nonlinear convective events, isolated cells, clusters of cells, broken lines of cells, squall lines with no stratiform , trailing stratiform precipitation, parallel stratiform precipitation, and leading stratiform precipitation, and bow echoes. In addition, the three cellular classifications were subdivided to allow an analysis of severe weather reports for events in which supercells were present and those in which they were not. As in the earlier study, all morphologies were found to pose some risk of severe weather, and differences in the two datasets were generally small. The 2007 climatology confirmed the theory that supercellular systems produce severe weather more frequently than other morphologies, and also produce more intense severe weather. Supercell systems were especially prolific producers of tornadoes and relative to all other morphologies, but also produced severe wind and flooding much more often than nonsupercell cellular morphologies. These results suggest that it is important to differentiate between cellular morphologies containing rotation and those that do not when associating severe weather reports with convective morphology.

Keywords bow echoes, cellular morphology, convective events, convective systems, data sets, isolated cells, radar imagery, severe weather, squall lines, stratiform precipitation, super cell, radar, storms,

Disciplines Atmospheric Sciences | Geology

Comments This article is from Weather and Forecasting 25 (2010): 190, doi: 10.1175/2009WAF2222338.1. Posted with permission.

This article is available at Iowa State University Digital Repository: http://lib.dr.iastate.edu/ge_at_pubs/61 190 WEATHER AND FORECASTING VOLUME 25

Spring and Summer Midwestern Severe Weather Reports in Supercells Compared to Other Morphologies

JEFFREY D. DUDA AND WILLIAM A. GALLUS JR. Department of Geological and , Iowa State University, Ames, Iowa

(Manuscript received 23 July 2009, in final form 18 September 2009)

ABSTRACT

This study compares severe weather reports associated with the nine convective system morphologies used in a recent study by Gallus et al. to an additional morphology, supercell storms. As in that previous study, all convective systems occurring in a 10-state region covering parts of the Midwestern United States and central plains were classified according to their dominant morphology, and severe weather reports associated with each morphology were then analyzed. Unlike the previous study, which examined systems from 2002, the time period over which the climatology was performed was shifted to 2007 to allow access to radar algorithm information needed to classify a storm as a supercell. Archived radar imagery was used to classify systems as nonlinear convective events, isolated cells, clusters of cells, broken lines of cells, squall lines with no stratiform precipitation, trailing stratiform precipitation, parallel stratiform precipitation, and leading stratiform precipitation, and bow echoes. In addition, the three cellular classifications were subdivided to allow an analysis of severe weather reports for events in which supercells were present and those in which they were not. As in the earlier study, all morphologies were found to pose some risk of severe weather, and differences in the two datasets were generally small. The 2007 climatology confirmed the theory that supercellular systems produce severe weather more frequently than other morphologies, and also produce more intense severe weather. Supercell systems were especially prolific producers of tornadoes and hail relative to all other mor- phologies, but also produced severe wind and flooding much more often than nonsupercell cellular mor- phologies. These results suggest that it is important to differentiate between cellular morphologies containing rotation and those that do not when associating severe weather reports with convective morphology.

1. Introduction cipitation, whether the initial convection was linear or areal in coverage (or a combination), and whether sys- Many studies have attempted to classify mesoscale tems merged with others. Baldwin et al. (2005) used 1-h convective systems by organizational mode. Bluestein rainfall amounts to develop an automated classification and Jain (1985) classified squall lines in terms of their procedure that separated rainfall events into stratiform development as broken line, back building, broken areal, nonconvective, convective linear, and convective cellular and embedded areal. Parker and Johnson (2000) con- categories. Other studies used isolated cells as an orga- sidered squall lines with trailing stratiform precipitation, nizational mode (Grams et al. 2006), and Baldwin et al. parallel stratiform precipitation, and leading stratiform (2005) alluded to classifying systems as both isolated cells precipitation. Jirak et al. (2003) used satellite and radar and clusters of multicells. Gallus et al. (2008; hereafter data to separate mesoscale convective systems into four G08) used several of these morphologies and related categories: mesoscale convective complexes, persistent severe weather reports in the midwestern United States elongated convective systems, meso-b circular convec- to morphology type and added clusters of cells, squall tive systems, and meso-b elongated convective systems. lines with no stratiform precipitation, and nonlinear The same study also classified systems by development convective systems to the typology. on radar in terms of the presence of stratiform pre- No matter which classification system is used, classi- fication of convective system morphology can be diffi- Corresponding author address: Jeffrey D. Duda, 3134 Agronomy, cult. Some subjectivity is inherent in the classification Iowa State University, Ames, IA 50011. since some systems exhibit aspects of multiple mor- E-mail: [email protected] phologies (G08) with changes occurring both spatially

DOI: 10.1175/2009WAF2222338.1

Ó 2010 American Meteorological Society 2010 DUDA AND GALLUS 191 and temporally. For example, Parker and Johnson (2000), Detection Algorithm (MDA) (Stumpf et al. 1998) and Parker (2007), and Storm et al. (2007) noticed that squall the Detection Algorithm (TDA; Mitchell et al. lines with leading stratiform and parallel stratiform pre- 1998). Stumpf et al. (1998) showed the MDA to be a cipitation had a tendency to transform gradually to better identifier and predictor of supercells than the trailing stratiform precipitation squall lines. In addition, recent operational algorithm, the WSR-88D Build 9.0 the assignment of severe weather reports to particular Algorithm, by comparing the probability morphologies also poses challenges (see G08 for a de- of detection and critical success index on a dataset. tailed discussion). Many of the difficulties are related to Mitchell et al. (1998) showed the TDA to be a better the methods used to report storms and how they appear identifier and predictor of tornadoes than the recent in the National Climatic Data Center’s (NCDC) Storm operational algorithm, the WSR-88D Tornadic Vortex Events Database. Such issues include the overreporting Signature Algorithm, by comparing the probability of or underreporting of severe wind and hail events (Trapp detection, false alarm rate, critical success index, and et al. 2006), the affects of population density on the re- Heidke skill score on a different dataset. The MDA may porting of severe wind events (Weiss et al. 2002), the be particularly useful for identifying supercells since methods by which tornadoes are reported (Doswell and a defining characteristic of a supercell is the presence of Burgess 1988; Trapp et al. 2005b; Verbout et al. 2006), a deep, persistent mesocyclone (Doswell and Burgess and the fact that most wind and hail reports are given as 1993). The MDA enables meteorologists to detect rapid point measurements rather than as swaths, as tornado rotation in all kinds of storms including ones in which reports are. the rotation may be difficult to see due to cluttering of Nonetheless, it appears potentially useful to attempt reflectivity, distance from radar, or other reasons. this classification since certain morphologies have been The present study takes the morphologies used in G08 shown to favor producing one or more types of severe and expands them to include supercellular versions of weather. Parker (2007), among others, has shown that the three cellular morphologies. To make use of im- parallel stratiform and leading stratiform lines tend to proved supercell detection algorithms, however, 2007 produce more flooding than other systems. G08 also data were used instead of the 2002 data used in G08. noted the tendency for trailing stratiform lines and non- Two hypotheses are tested: 1) trends in severe weather linear convective events to produce more flooding re- reports associated with each morphology found for the ports, and they also showed that cellular systems tended 2002 dataset in G08 remain true for the 2007 dataset and, to produce more hail and tornado reports. Bow echoes more importantly, 2) supercell morphologies will pro- and trailing stratiform events have been shown to pro- duce more severe weather more frequently and produce duce a greater percentage of all severe wind reports and more intense severe weather than will nonsupercellular tend to have a large wind-to-hail report ratio (Klimowski morphologies. Section 2 outlines the data sources and et al. 2003; G08). One shortcoming of those studies, methodology for the study, while section 3 provides the however, is the exclusion of supercells as a morphology results and analysis of the study. Conclusions and dis- or storm type. G08, for instance, found that although cussion follow in section 4. cellular systems were most common in the summer, most of the severe weather reports associated with them oc- 2. Data and methodology curred in spring, and speculated that the spring events might be supercellular in environments of greater wind To preserve continuity between the present study and shear while summer events might be nonsupercellular. G08, as many aspects as possible of the data collection and Additional data and more detailed analysis are needed methodology used in G08 were followed in the present to identify supercells. study. Radar data came from the University Corporation Supercells have long been known as producers of for Atmospheric Research/Mesoscale and Microscale some of the most intense severe weather (Doswell and Division’s (UCAR/MMM) image archive Burgess 1993; Moller et al. 1994), and several methods for warm precipitation episodes (information on- have been devised to allow forecasters to identify su- line at http://locust.mmm.ucar.edu/case-selection/). The percells using radar or satellite (e.g., Forbes 1981; Johns images are mosaics from various sources, but most are of and Doswell 1992; Burgess and Lemon 1990; Moller composite reflectivity with spatial and temporal resolu- et al. 1994). More recently, teams from the National tions of 2 km 3 2 km and 30 min, respectively. For the Severe Storms Laboratory have written two algorithms few periods in which data from this archive were unavail- that aid in the identification of supercells and tornado able (the longest such period being 24 h), the interactive vortex signatures from the Weather Surveillance Radar- radar feature on the Iowa Environmental Mesonet Web 1988 Doppler (WSR-88D) network: the Mesocyclone site (http://mesonet.agron.iastate.edu) was used instead, 192 WEATHER AND FORECASTING VOLUME 25

FIG. 1. Ten-state domain used in the study (from G08). with settings matched as closely as possible to those of 3:1, and persist for at least 2 h. Cellular systems had to the UCAR image archive. Output from the MDA, which contain identifiable cellular elements. If the elements was accessed both through the NCDC mesocyclone prod- were connected by relatively weaker reflectivities (around uct and level III storm attribute data, was used to iden- 30 dBZ), the systems were classified as CC; if not, or if tify supercells. Severe storm reports were obtained from only very weak reflectivities (less than 10 dBZ) con- NCDC. nected individual cellular elements, the systems were The period of study extended from 1 April 2007 to classified as IC. If the cellular elements were organized 31 August 2007. The domain of the study (Fig. 1) matched in a discontinuous line, the systems were classified as that used in G08 and consisted of a 10-state region from BL. Linear systems were classified according to their the southern Great Plains through the upper Midwest. pattern of stratiform precipitation, and lines with no All convective events that formed within this domain stratiform precipitation, or in which the stratiform pre- and time period were included in the study as long as cipitation was narrower than the convective part of the they met the following radar characteristics (as in G08): line, were classified as NS. Bow echoes were not re- quired to possess stratiform precipitation but did consist 1) areal coverage of reflectivity greater than 10 dBZ of of a line in which part of the line bowed out at a speed at least 6 km 3 6 km, that was clearly faster than the other parts of the line. If 2) at least one pixel of data of at least 30 dBZ within the a system met the three main radar criteria but did not fit area in characteristic 1, and into one of the linear or cellular morphologies, it was 3) temporal maintenance of characteristics 1 and 2 for classified as NL. at least 1 h (at least three frames). In classifying systems, only the dominant morphology All convective systems meeting these criteria were was considered. All severe reports that occurred with classified using visual inspection according to their dom- that system were assigned to that morphology. How- inant morphology. Nine morphologies were used (Fig. 2): ever, if a system displayed properties of a different three were cellular, consisting of isolated cells (ICs), morphology for more than 1 h during any time other clusters of cells (CCs), and broken lines (BLs); five were than the initial and decaying stages of its life, then severe linear, consisting of no stratiform precipitation squall reports that occurred during that time were attributed to lines (NSs), trailing stratiform squall lines (TSs), parallel the other morphology. Some systems in this study did stratiform squall lines (PSs), leading stratiform squall change morphologies, occasionally several times. Effort lines (LSs), and bow echoes (BEs); and the final mor- was taken to prevent duplicated reports, especially hail and phology was the nonlinear convective morphology tornado reports (several of which were found), from being (NL). To be classified as one of the linear morphologies, overcounted. It is recognized that classifying convective a system had to be at least 75 km in length, have an systems by mere visual inspection of radar is subjective, but eccentricity (ratio of major axis to minor axis) of at least the quantitative guidelines used for classification should FEBRUARY 2010 DUDA AND GALLUS 193

FIG. 2. Schematic drawings of systems from the nine morphologies. Abbreviations are as follows: IC, isolated cells; CC, cluster of cells; BL, broken line of cells; NS, squall line with no stratiform precipitation; TS, trailing stratiform precipitation; PS, parallel stratiform precipitation; LS, leading stratiform precipitation; BE, bow echo; and NL, nonlinear convective system (from G08). Storm motion can be assumed left to right in all cases. reduce the subjectivity. Nonetheless, systems exhibit a diameter, hail $ 2 in. in diameter, severe wind gusts spectrum of morphologies, and a given system may ex- [severe being gusts $50 kt (1 kt 5 0.514 m s21)] ,65 kt, hibit characteristics of multiple morphologies both be- severe wind gusts $65 kt, tornadoes, floods, and flash tween successive scans and within one scan, causing floods. In G08, the report of urban/small stream flooding difficulty in the assignment of a morphology. Approxi- was used. However, changes in the way NCDC’s Storm mately 5% of the systems proved difficult to classify, Events Database classified flooding reports caused the either because they evolved rapidly (i.e., did not resemble elimination of the term ‘‘urban/small stream flooding,’’ a particular morphology for at least an hour), or because and consolidated it with other low-impact flooding events they exhibited characteristics of disparate morphologies that no longer appear in the database. Other changes to simultaneously. However, a morphology was still assigned the flooding reports listed in the database include con- to these systems. In fact, an additional morphology was tinuing a flash flood report as a flood report if the defi- suggested by Schumacher and Johnson (2005), called the nition of a flood event is met from an ongoing flash flood training line/adjoining stratiform (TL/AS) morphology. report. This occurred rarely in the study and was ignored. A few of the systems in this study resembled TL/AS If a system met the radar requirements but was not as- characteristics and would have been labeled as such sociated with any reports of severe weather, the system had that morphology been included. However, since the was classified as a nonsevere case. TL/AS morphology was not included in G08, it was not An additional classification of supercells was included employed in this study. in the present study to determine whether or not systems The severe reports were divided into the same cate- that contain supercells produce more frequent or more gories used in G08: hail $ 0.75 in. (1 in. 5 2.54 cm) in violent severe weather than other morphologies. To be diameter but ,1 in. in diameter, hail $ 1in.but,2in.in classified as a supercell system, an event must have been 194 WEATHER AND FORECASTING VOLUME 25

TABLE 1. Number of events classified and producing severe weather or flooding in the current study using 2007 data and from G08, which used data from 2002.

No. (%) of No. (%) of systems systems that that produced No. of No. of systems produced nonflooding No. of severe nonflooding Dataset classified severe weather severe weather reports severe reports 2002 949 671 (71) 623 (56) 10 800 9678 2007 909 553 (61) 493 (54) 9253 7642

classified as cellular and must have contained at least supercells, a comparison was performed first to examine one supercell. Although it has been shown that non- the generality of the G08 results. Table 1 shows that the cellular systems likely contain embedded supercells sample sizes from the 10-state region in the 2 yr were (e.g., Miller and Johns 2000), those will not be consid- roughly similar, although the 2007 dataset had more ered in this study to keep the focus of the study on the nonsevere cases (events that did not produce any severe system morphologies and not individual convective el- reports) and fewer total severe reports. However, the ements. If at least one supercell was found within a sys- 2007 events produced an average of 10.2 reports of se- tem, all reports for that system were attributed to the vere weather per system, a value slightly less than the supercell morphology. 11.4 found in G08 for the 2002 systems, with BE systems Because a supercell has been defined as a storm typically producing the largest average of about 22.5 reports per possessing a mesocyclone for at least 15 min (Glickman system in 2007 (not shown). 2000), in the present study any identifiable cellular ele- The contribution from each morphology toward the ment from a cellular system that was flagged by the MDA total number of systems is shown in Fig. 3. The three consistently for a period of at least 15 min was consid- most common systems were the same in both datasets ered a supercell. Because radar volume scans are gener- (NL, IC, and CC), although the largest single contribu- ally produced at a rate of one volume scan every 4–6 min, tors were CC systems for the 2007 dataset, contributing the minimum number of scans in which a cellular ele- nearly 28% to the total number of systems, and NL ment had to be flagged as a mesocyclone to be consid- systems from G08, consisting of 29% of all systems. Note ered a supercell was chosen to be four. Several levels of that LS systems were relatively rare, a result similar to rotation are marked by the MDA, including UNCO and G08. Parker and Johnson (2000), in defining leading 3DCO, which correspond to uncorrelated rotation at stratiform systems as a morphology, indicated that lead- one isolated elevation angle and correlated rotation at ing stratiform lines could also possess trailing or parallel two adjacent elevation angles of the radar, respectively, stratiform precipitation. It is likely, then, that some sys- and MESO, which corresponds to correlated rotation at tems were classified as TS or PS instead of LS even if three or more adjacent elevation angles. Only the MESO some leading stratiform precipitation was present. level was used to mark a cell as possessing a mesocyclone. Regarding broad morphological types, cellular sys- Because supercells may fluctuate in strength over time, a tems dominated in both studies, consisting of 61% of all one-scan break in a sequence of four consecutive scans systems in 2007 and 49% in 2002. Although linear sys- flagging a cell with MESO was allowed in the defining of tems composed about the same percentage of all systems supercells. An analysis of how many individual supercells (24% and 22% for 2002 and 2007, respectively), the a supercell system contained was not performed. Systems order of frequency between nonlinear and linear sys- that were only partially inside the domain were only tems differed between the two studies. Nonlinear sys- classified as a supercell system if any supercells that oc- tems consisted of a greater portion of all systems in the curred within the system occurred within the domain. 2002 dataset (29%) than they did in 2007 (15%). This process was used for both severe systems and those Shown in Fig. 4 is the percentage of the total number that did not produce severe weather. of severe storm reports produced by each morphology for both datasets. In both , cellular systems con- tributed the most severe reports, followed by linear 3. Results systems. The larger sample size of the cellular morpho- logical types, as well as the fact that a number of cellular a. Comparison with G08 events contained supercells (section 3b), probably plays Because a different sample of cases than that analyzed some role in that outcome. Of note, the contribution of in G08 had to be used to allow for the identification of storm reports from linear systems in both years (Fig. 4) FEBRUARY 2010 DUDA AND GALLUS 195

FIG. 4. As in Fig. 3, but for percentage contribution of each morphology to the total number of severe storm reports.

FIG. 3. Percentage contribution of each morphology to the total number of events for the (top) 2007 and (bottom) 2002 data from substantial disparities in the percentages of total re- G08. Shading implies general morphological type: nonlinear (dark ports contributed by NL, BE, BL, and CC systems and gray), cellular (medium gray), and linear (light gray). Numbers in parentheses indicate the number of events that occurred for each different rankings of the top three most productive morphology. systems, as CC, BL, and BE systems were the top three (inthatorder)in2007comparedtoCC,NL,andICin 2002. is noticeably larger than the fraction of systems iden- Shown in Fig. 5 is the percentage of systems that tified as linear (Fig. 3). This result likely reflects both produced at least one report of severe weather by the relatively large sizes and the increased organization morphology for both datasets. Linear systems were of the linear systems. Also common between the two more likely to be associated with at least one severe datasets is that CC systems contributed the most re- weather report than cellular and nonlinear systems, ports, producing 33% of all severe reports in 2007 and again likely due to both their larger sizes and increased 22% in 2002, and that LS systems contributed the organization. In fact, about 75% of all linear systems fewest number of total severe reports, again results in the 2007 dataset (85% in G08) produced severe likely reflecting the relative numbers of those types of weather, compared to around 55% for cellular and non- systems. Differences between the two datasets include linear systems (66% in G08). When only nonflooding 196 WEATHER AND FORECASTING VOLUME 25

FIG. 5. Percentage of systems from each morphology that produced (top) at least one report of severe weather and (bottom) at least one nonflooding report of severe weather for both years (2007, dark; 2002, light). severe reports were considered, all percentage values (Fig. 6). A general increase can be seen in the number of decreased somewhat due to the presence of systems that all systems from April through August, while severe- produced only flooding reports. The NL and linear storm-report-producing systems only increase in num- morphologies contained more flooding-only systems ber through and then tend to remain constant. than did others. The associated stratiform precipitation These trends suggest that although fewer convective and large areal coverage of the NL and linear systems systems occur in the spring, a greater proportion of them likely explains at least some of this difference. Another produce severe weather compared to those that occur in explanation is that NL systems are generally poorly or- the summer. ganized convective systems and often develop in regions To best compare the frequency with which the systems of weak vertical wind shear. Thus, given that surface of each morphology produced severe weather, reports wind speeds during the convective season are generally were normalized as in G08 to determine the average weak, winds at all levels of the atmosphere are weak, number of reports produced per system for each mor- meaning that any convection would be slow moving and phology (Figs. 7–10). Tests of statistical significance hence pose a heightened risk of flooding. were applied via the Wilcoxon rank sums test, and a There is good agreement between the 2 yr in the threshold p value of 0.05 was used to determine statis- temporal patterns of the number of convective events tically significant differences in means. Figure 7 shows FEBRUARY 2010 DUDA AND GALLUS 197

the difference in the average numbers of tornadoes per system between combined cellular and combined non- cellular morphologies was not statistically significant in either (p 5 0.1065 and p 5 0.0575 in 2002 and 2007, respectively). Further analysis was performed to determine which morphologies produced the most intense tornadoes. An average of the enhanced Fujita (EF) scale rating (F-scale rating for the 2002 G08 dataset) was computed for the tornadoes produced by the systems in each morphology. Due to the large number of EF0 tornadoes FIG. 6. Breakdown by of the number of systems in each produced by many systems, the average ratings are all of the 2 yr, and the number of severe-storm-report-producing below 1.0 (Fig. 7). In general for both years, cellular systems. systems had the highest average tornado intensity rating. The difference was significant in 2002 (p 5 0.0007), but that BL and PS systems were the leading producers of not in 2007 (p 5 0.1368), when cellular morphologies tornadoes, although the differences were not statistically were combined and tested against the noncellular mor- significant, as p values were greater than 0.5000 in all phologies combined. Exceptions include PS and BE tests. G08 mentioned that BL systems often occur near systems in 2007, which earned the highest average rat- baroclinic boundaries, which would likely be regions of ings in that year, and LS systems in 2002. However, these enhanced vertical wind shear. One noticeable difference PS, BE, and LS systems produced only 15, 3, and between the datasets is that PS systems did not produce 14 tornadoes, respectively, compared to 50 or more for tornadoes in 2007 as frequently as in 2002, but ranked each of the cellular morphologies, and the small sample third in average number in 2007 behind BL and CC size may be affecting the results. In fact, as will be dis- systems. In general, the systems in the 2002 dataset as- cussed in section 3b, the differences in tornado ratings sociated with the most tornadoes produced about twice between PS and BE systems and supercellular systems in as many tornadoes as those in the 2007 dataset, even 2007 were not statistically significant. though the average number of tornadoes produced by The 2007 and 2002 datasets agree well for the average all of the systems combined was nearly identical (0.39 for number of reports of hail of all sizes per system for the 2002 compared to 0.38 for 2007). Otherwise, the num- cellular morphologies (Fig. 8). BL systems were the bers agree fairly well between the two datasets. Except most productive of all morphologies, although not sig- for PS systems, it is clear that cellular systems produced nificantly (p values in all tests comparing BL systems to more tornadoes per event than other systems, although BE, CC, or TS systems for the average numbers of

FIG. 7. Average number of reports of tornadoes per system (left-side axis) and average (E)F-scale rating (right-side axis) for the 2007 and 2002 datasets for each morphology. 198 WEATHER AND FORECASTING VOLUME 25

FIG. 8. Average numbers of reports per system for hail for the 2007 (dark) and 2002 (light) datasets: (a) $0.75 in. but ,1 in., (b) $1 in. but ,2 in., (c) $2 in. in diameter, and (d) in all size ranges for each morphology. reports of hail per system for all sizes were greater than shorter time and smaller distance scales than flooding) 0.6000). There is less agreement between the two data- reports per system (Fig. 10b) was nearly the same in both sets for the linear morphologies, particularly for LS, PS, years for TS and PS systems, but differed much more for and BE systems, as the average numbers of hail reports flooding reports (Fig. 10a). Also, a large disparity be- per system differed by up to 90% for these morphol- tween 2002 and 2007 existed for the average number of ogies. Again, caution should be used in interpreting reports of flash flooding for BL systems, a disparity ab- these results due to small sample sizes. sent for flooding reports. A similar pattern of behavior As in G08, BE systems produced the greatest aver- can be seen for LS systems. Systems that usually have age number of reports of severe wind (Fig. 9), with TS significant stratiform precipitation (NL, TS, LS, PS, and systems ranking second. The difference in the average BE) were all among the top four or five morphologies for numbers of total reports of wind between BE and TS average numbers of flooding reports per system in both systems was statistically significant (p 5 0.0108 and p 5 datasets. Overall though, there is a general disagreement 0.0027 for 2007 and 2002, respectively), as well as be- between the leading producers of flooding reports. One tween TS systems and BL systems (which ranked third area of agreement, however, and a finding supported by in average numbers of total reports of wind) in 2007 Parker (2007), is that PS systems produced the greatest (p 5 0.0129), but not in 2002 (p 5 0.2725). The struc- average number of reports of flash flooding per system in tures of the BE and TS systems likely explain the high both datasets, although not significantly ( p values were amounts of severe wind reports, with rear-inflow jets greater than 0.5000 in both tests comparing PS to TS transporting momentum downward in both types of systems). However, LS systems, which produced the systems (e.g., Smull and Houze 1987; Duke and Rogash most average reports of flooding per system in G08, were 1992). Strong downdrafts and resulting large-scale cold associated with far fewer reports in 2007, while BE and outflows, in association with the acceleration produced NL systems produced far more reports of all types of from mesohighs under the downdrafts produced by flooding in 2007 than in G08. these systems, could also explain the high amount of severe wind reports. There is rather good agreement b. Supercellular versus nonsupercellular systems between the 2007 and 2002 events for the other mor- phologies as well. A key difference between the present study and that The average number of flooding reports per system in of G08 is the inclusion of supercell morphologies in the both years is shown in Fig. 10. The average number of 2007 dataset. The remainder of this section discusses the flash flooding (flash flooding typically occurs suddenly on differences between 2007 systems that were classified as FEBRUARY 2010 DUDA AND GALLUS 199

FIG. 9. As in Fig. 8, but for wind gusts of magnitude (a) $50 kt but ,65 kt, (b) $65 kt, and (c) from all wind ranges. 200 WEATHER AND FORECASTING VOLUME 25

FIG. 10. As in Fig. 8, but for (a) flooding, (b) flash flooding, and (c) all flooding reports. FEBRUARY 2010 DUDA AND GALLUS 201 supercellular and all other systems, emphasizing differ- ences between the supercellular and nonsupercellular cellular systems. Using the methodology outlined ear- lier, 207 supercell systems (23% of all systems) were classified. Of those 207 supercell systems, the majority were CC, numbering 118 (57%), while IC events totaled 47 (23%), and BL events produced the remaining 42 (20%). These numbers are all greater than the numbers of LS and PS systems present in the 2007 dataset and are comparable to several other morphologies. A breakdown of the contributions from each mor- phology to the total number of systems and to the number of severe storm reports can be seen in Fig. 11. Of all of the cellular systems, 37% contained a supercell. Nonsupercellular versions of the IC and CC morphol- ogies were more common than the supercellular ver- sions, whereas BL events were fairly evenly divided between those with and those without supercells. Of all of the supercellular morphologies, CC systems were most common, representing 13% of all systems. When only storm reports are considered, however, a significant change occurs. All of the supercellular morphologies contribute a larger percentage to the number of severe storm reports than they did to the number of all systems. In fact, supercellular CC systems produced the most se- vere reports (29%) of all morphologies, and the three supercell morphologies together accounted for 51% of all storm reports. Nonsupercellular cellular morphologies only accounted for 6% of severe reports. When com- bined with the fact that about 91% of all supercellular systems produced severe weather (Fig. 12, Table 2), it is clear that supercellular systems pose an especially large severe weather risk. These results support the specula- tion in G08 that higher frequencies of severe reports in spring from cellular events despite fewer numbers of FIG. 11. Percentage contribution of each morphology in the 2007 cellular events than in summer likely implied the pres- dataset to the total number of (top) systems and (bottom) severe ence of supercells in spring. storm reports. Shading as in Fig. 3 except that additional light gray A breakdown by month and morphology of the num- color distinguishes supercellular systems from nonsupercellular systems. Numbers in parentheses indicate the number of events ber of systems to occur (Fig. 13) shows that surprisingly, that occurred for each morphology. with the exception of NS, PS, and TS systems, all systems had a peak of occurrence late in the period, either in July or August. Most systems were rarest in April, likely events and severe reports during August. This difference because cooler conditions common in the early spring do in results suggests August 2007 may have been unusually not typically favor convection nearly as much as do the favorable for supercell and severe weather. warmer conditions common during the summer . Indeed, the was frequently located over the Of note in Fig. 13, far more supercellular CC systems northern part of the domain during this period with occurred in August than in any other month, with a stronger than normal flow aloft likely enhancing the similar enhanced maximum in supercellular BL events. shear needed for supercell development. An archive of The supercellular CC systems also produced much se- severe storm events dating back to 2000 maintained by vere weather in August with an average of about 22 the Storm Prediction Center (information online at http:// reports per system, the second greatest of any morphol- www.spc.noaa.gov) supports this assertion by showing ogy that month (not shown). These results differ greatly more August days in 2007 with severe weather within from G08, which found relatively small numbers of CC the 10-state region, (21 days) than in any other year. 202 WEATHER AND FORECASTING VOLUME 25

FIG. 12. As in Fig. 5, but for 2007 only, and separating cellular events into supercells and nonsupercells.

August 2002 in contrast had slightly fewer days than 0.67. This result is surprising since supercellular CC sys- normal with severe weather in this region. tems (and all supercellular morphologies) were associ- The average number of tornadoes produced by super- ated with larger average numbers of tornadoes, and the cellular systems was much greater than that from any supercellular CC morphology also was responsible for the other morphology (Fig. 14a, Table 3). The difference was strongest tornado (the Greensburg, Kansas, storm, which statistically significant (Table 4). Unless otherwise noted, was rated as an EF5), and six EF3s (the largest number of all of the following results were statistically significant, EF3s produced by any morphology). These results imply often with p values less than 0.0001. NS and PS systems that supercellular CC systems also produce many F0 were the next largest producers of tornadoes per event, tornadoes and may also reflect the small sample size of PS but still produced about 0.4 tornadoes less per system and BE systems. It is also possible that some weak tor- (roughly 40%) than even the least productive super- nadoes that occurred in the PS and BE systems were cellular system (IC). Supercellular BL systems produced mistakenly reported as wind damage due to the frequent the greatest average number of tornadoes per system at occurrence of severe wind occurring throughout them. 1.55. The largest average number of tornadoes produced Thus these systems may have produced some EF0 and per system for the nonsupercellular cellular morphologies EF1 tornadoes that did not appear in Storm Data,re- was 0.16 by nonsupercellular CC systems, a 90% re- ducing the average intensity value computed in this study. duction from the supercellular BL morphology. The However, the p value for the Wilcoxon test between su- average tornado intensity rating for supercellular CC percell CC systems and PS systems was 0.3648, and thus systems was 0.63, the highest among the three super- the difference was not significant. The differences were cellular morphologies. However, PS systems produced also not significant between PS systems and the other the largest average rating for all morphologies, 0.80, with supercell systems, nor between BE systems and the su- BE systems producing the second highest average rating, percell systems (p values ranged from 0.0673 to 0.6132). It

TABLE 2. Percentage of the total amount of storm reports or systems assigned to each morphology.

Percent that Percent of all Percent of Percent of Percent of Percent of Percent Percent produced severe weather all tornado all hail all wind all flooding of all of severe severe weather reports reports reports reports reports systems systems Supercell events 90.8 51.0 68.2 67.2* 44.2 19.6 22.8* 34.0* All nonsupercell events 52.0 48.9 31.8 32.7* 55.8 80.4 76.8* 65.6* Nonsupercell cellular 36.9 5.9 9.6 6.2 3.5 8.7 38.2 23.1 events

* Cases where the two percentages do not add to 100% because four hail reports occurred with a CC and IC system for which data were unavailable to classify each as supercellular or nonsupercellular. FEBRUARY 2010 DUDA AND GALLUS 203

FIG. 13. Breakdown by morphology and month of the number of systems occurring. should also be noted that of the 207 supercellular systems hail greater than 1 in. in diameter (Fig. 14b). The most identified, 28% produced at least one tornado (not productive morphology was supercellular BL systems, shown). This result is very similar to the 26% rate found which produced the greatest average number of all three in a study of over 5000 MDA detections from 54 different size ranges of hail per system and, thus, for total hail radar sites nationwide during the period 1992–99 (Trapp reports. The average number of reports of hail per sys- et al. 2005a), and supports recent findings that tornadoes tem for the supercellular systems generally was at least are relatively rare, even when storms contain persistent double the rate for linear systems and roughly an order rotation. of magnitude larger than the rate for nonsupercellular Supercellular systems produced the most reports, on cellular systems (a statistically significant difference; see average, of all three size ranges of hail, and especially for Table 4) and NL events.

FIG. 14. Average number of reports per system for (a) tornadoes, (b) hail, (c) wind, and (d) flooding by morphology. 204 WEATHER AND FORECASTING VOLUME 25

TABLE 3. As in Table 2, but for average numbers of reports per system for the various types of severe weather and for each type of morphology.

Tornado No. (rating) Hail Wind Flooding All reports Supercell events 1.13 (0.56) 14.16 5.99 1.53 22.80 All nonsupercell events 0.16 (0.28) 2.04 2.43 1.86 6.49 Nonsupercell cellular events 0.10 (0.12) 0.78 0.29 0.40 1.57

BE systems produced the greatest average number of theless, all cellular morphologies were less likely to severe wind reports per system (Fig. 14c), which is con- produce flooding than nonlinear or linear systems, and sistent with G08 and not surprising (e.g., Klimowski et al. the morphologies most likely to produce flooding re- 2003). However, supercellular BL and supercellular CC mained BE, PS, TS, and NL, (although the difference systems produced the second and third greatest averages, between NL and the next lowest average, that from su- producing more severe wind reports per system than TS percellular CC systems, was not significant, with p 5 systems, events found in G08 to be the second largest 0.7941) as shown earlier in Fig. 10. producer. The difference between BE systems and su- The sometimes large differences between super- percellular BL systems was not significant (p 5 0.0764 for cellular systems and nonsupercellular systems are sum- total wind reports), however. Likewise, the difference marized in Table 2. Supercellular systems produced between supercellular BL systems and TS systems was severe weather more frequently than other types of not significant (p 5 0.1742), although it was significant systems. Despite consisting of only 23% of all systems between BE and TS systems (p 5 0.0108). Perhaps the and 34% of all severe systems, supercellular systems higher averages for supercellular BL and supercellular produced over half of all severe weather reports, more CC systems is related to wind gusts produced by rear- than two-thirds of all tornadoes and hail reports, and flank downdrafts associated with the supercells in those produced a substantial number of wind reports com- systems (e.g., Markowski 2002; Finley and Lee 2008). pared to the nonsupercellular systems. Wind reports were roughly an order of magnitude less The total number of reports produced by nonsuper- common with NL systems, and even less likely with cellular cellular systems was tiny compared to that of the nonsupercellular cellular events (Fig. 14c, Table 3). supercellular systems. The 33 tornadoes produced by the As with tornadoes, hail, and wind reports, flood re- three nonsupercellular cellular morphologies were only ports were more common per event in supercellular 14% of the 234 tornadoes produced by the supercellular systems than in nonsupercellular cellular events (Fig. 14d). systems. The nonsupercellular cellular systems produced This result is perhaps more surprising than that for tor- only about 10% as many hail and wind reports as the nadoes, hail, and wind, and suggests that the supercells supercellular cellular systems and produced only six re- may possess greater rates, or cover larger areas than ports of hail greater than or equal to 2 in. in diameter and the nonsupercellular cellular events. The analysis of eight reports of wind greater than or equal to 65 kt (not radar data from 2007 did suggest that many supercells shown). Those numbers compare to 164 and 153 reports were larger in size than the nonsupercells, and often of hail at least 2 in. in diameter and wind gusts of at least persisted longer, both factors that could lead to larger 65 kt, respectively, for supercells. Results differed less accumulations of rainfall and possible flooding. None- for flooding but nonsupercellular cellular systems still

TABLE 4. The p values for various tests of statistical significance using the Wilcoxon test. Values in boldface indicate those deemed not significant using a threshold p value of 0.05.

All supercell events Type of severe IC supercell vs CC supercell vs BL supercell vs vs all cellular All supercell events weather IC nonsupercell CC nonsupercell BL nonsupercell nonsupercell events vs all other events 0.75 in. # hail , 1 in. 0.0000 0.0000 ,0.0001 0.0000 0.0000 1 in. # hail , 2 in. 0.0000 0.0000 ,0.0001 0.0000 0.0000 Hail $ 2 in. ,0.0001 ,0.0001 ,0.0001 0.0000 0.0000 50 kt # wind , 65 kt ,0.0001 0.0000 ,0.0001 0.0000 0.0000 Wind $ 65 kt ,0.0001 ,0.0001 0.0011 0.0000 ,0.0001 Tornado No. ,0.0001 ,0.0001 0.0291 ,0.0001 ,0.0001 Tornado rating 0.5234 0.0152 0.0539 0.0019 0.0017 Flood 0.0015 0.0005 0.3086 ,0.0001 0.3807 Flash flood 0.0165 ,0.0001 0.0163 ,0.0001 0.0104 FEBRUARY 2010 DUDA AND GALLUS 205 produced less than half of the reports per case associated atively rare in occurrence, along with PS events. with supercellular events. Monthly trends were also generally similar in both years, In terms of average numbers of severe reports per event, although storms and severe weather reports were more supercellular systems far exceeded nonsupercellular cel- frequent in August 2007 than in August 2002. The big- lular events, as well as all other systems (Table 3), for gest differences in the average number of reports for every type of report except flooding. As was alluded to tornadoes, hail, and wind between the two datasets oc- earlier, several configurations of comparisons were tested curred with BL, PS, LS, and BE systems, and for flooding for statistical significance, and those results are presented with BL, NL, and BE events. Some of the differences are in Table 4. It is clear that the differences in the average likely related to small sample sizes for PS, LS, and BE number of reports per system between the supercellular morphologies in one or both of the years. systems and the nonsupercellular systems for nearly all The classification of cellular systems as supercells or types of severe weather were statistically significant, with nonsupercells revealed dramatic differences in the fre- many p values being exceptionally small. The higher quency of storm reports from each morphology. Super- average for flooding in nonsupercellular systems likely cellular systems produced much more severe weather of reflects the much larger sizes of the top flood-producing all types than did nonsupercellular cellular morphol- systems, BE and PS. The average tornado rating (on the ogies, and most differences were statistically significant, EF scale) of all supercellular systems was 0.56, twice that as determined by a Wilcoxon rank sums test. In addition, of all other systems, and far larger than the 0.07 average for tornadoes and hail, the three supercellular mor- for nonsupercellular cellular systems. Thus, it is clear that phologies all were associated with more storm reports supercellular systems in 2007 were more likely to produce per system than any other morphology. For severe wind, severe weather than their nonsupercellular counterparts, BE systems were the most prolific producers of reports, supporting our hypothesis. but CC and BL supercells were next most prolific. For flooding, however, PS and TS systems were among the morphologies producing the most reports per system in 4. Conclusions and discussion both years, with BL also ranking high in 2002 and BE and The present study expanded the work done by G08, in NL ranking high in 2007. All of these morphologies tend which all convective events that occurred within a 10-state to include large areas of rainfall, which should enhance domain that included the Midwest and Great Plains the flood risk, as discussed in G08. The division of the between April and August 2007 were classified accord- cellular morphologies into those with rotation and those ing to their dominant morphology, with supercells added without also revealed that the nonsupercellular cellular as a morphology. To allow the classification of super- morphologies generally produced the fewest severe storm cells, a different dataset had to be used from that used in reports per system and had the highest rates of non- G08, and this also allowed a comparison between storms severe systems, less than nonlinear events and the five occurring in 2007 and those occurring in 2002. Systems linear morphologies. had to meet specific radar criteria to be classified into the Future work should include expanding the areal cov- nine morphologies defined by G08. All severe reports, erage of the study to that of the entire continental United which were obtained from NCDC’s Storm Events Da- States to develop a climatology of severe weather and tabase, were attributed to the dominant morphology convective events for all portions of the country, especially that characterized each system during its lifetime. Then, because differences in reporting strategies among Na- using MDA output via level III storm attribute data tional Weather Service offices and radar coverage would and the mesocyclone product from NCDC, supercells likely influence the results. In addition, future studies were separated from their nonsupercellular counter- should expand the time period to include all portions of parts based on the existence of a persistent mesocyclone the year, add additional years, add additional morphol- in a recognizable cellular element from one of the cel- ogies [such as TL/AS from Schumacher and Johnson lular morphologies (IC, CC, and BL). (2005)], and allow systems from all morphologies (not It was found that, in general, similar trends were just cellular ones) to be eligible to contain supercells. present in the 2007 data compared to those in 2002 However, if the last task is undertaken, substantial presented in G08, with NL, IC, and CC morphologies thought must be given to the value of classifying an most common. NL events were noticeably less common entire system as supercellular based on the presence of in 2007, however, than in 2002. Cellular systems pro- just one or two supercells, particularly if the majority of duced the most severe reports in both years, especially severe storm reports are associated with the individual CC events. LS systems in both years contributed the supercells. It might be advantageous in such an analysis fewest number to the total severe reports and were rel- to focus on the morphologies of individual elements and 206 WEATHER AND FORECASTING VOLUME 25 not on entire systems, a philosophical change from G08 convective system morphology during IHOP 2002. Wea. Fore- and the current study. casting, 21, 288–306. Jirak, I. L., W. R. Cotton, and R. L. McAnelly, 2003: Satellite and Acknowledgments. Thanks are given to Nathan Snook radar survey of mesoscale convective system development. and Elise Johnson for their advice and input on the meth- Mon. Wea. Rev., 131, 2428–2449. odology used in G08. Thanks also to Daryl Herzmann Johns, R. H., and C. A. 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