Mesoscale Convective Systems and Their Synoptic-Scale Environment in Finland

182 WEATHER AND FORECASTING VOLUME 30

ARI-JUHANI PUNKKA Finnish Meteorological Institute, Helsinki, Finland

MARJA BISTER Division of Atmospheric Sciences, Department of Physics, University of Helsinki, Helsinki, Finland

(Manuscript received 9 December 2013, in ﬁnal form 14 October 2014)

ABSTRACT

The environments within which high-latitude intense and nonintense mesoscale convective systems (iMCSs and niMCSs) and smaller thunderstorm clusters (sub-MCSs) develop were studied using proximity soundings. MCS statistics covering 8 years were created by analyzing composite radar imagery. One-third of all systems were intense in Finland and the frequency of MCSs was highest in July. On average, MCSs had a duration of 10.8 h and traveled toward the northeast. Many of the linear MCSs had a southwest–northeast line orientation. Interestingly, a few MCSs were observed to travel toward the west, which is a geographically speciﬁc feature of the MCS characteristics. The midlevel lapse rate failed to distinguish the environments of the different event types from each other. However, in MCSs, CAPE and the low-level mixing ratio were higher, the deep-layer-mean wind was stronger, and the lifting condensation level (LCL) was lower than in sub- MCSs. CAPE, low-level mixing ratio, and LCL height were the best discriminators between iMCSs and niMCSs. The mean wind over deep layers distinguished the severe wind–producing events from the nonsevere events better than did the vertical equivalent potential temperature difference or the wind shear in shallow layers. No evidence was found to support the hypothesis that dry air at low- and midlevels would increase the likelihood of severe convective winds. Instead, abundant low- and midlevel moisture was present during both iMCS cases and signiﬁcant wind events. These results emphasize the pronounced role of low- and midlevel moisture on the longevity and intensity of deep moist convection in low-CAPE environments.

1. Introduction and 35 000 km of power lines were damaged (Safety Investigation Authority 2010). From a weather fore- Numerous recent investigations on European meso- caster’s point of view, severe MCSs are a significant scale convective systems (MCSs) have shown that orga- challenge due to their infrequent occurrence in Finland. nized deep moist convection is a frequent phenomenon Severe MCSs are not a part of the daily forecasting over the whole continent (e.g., Morel and Senesi 2002; routine for duty forecasters. Thus, forecasters need to García-Herrera et al. 2005; Lewis and Gray 2010). Oc- learn from previous events and, based on this knowl- casionally, severe and devastating forms of MCSs, such as edge, attempt to issue correct forecasts when a real sit- derechos, occur in Europe (Gatzen 2004; Punkka et al. uation takes place. 2006; Gatzen et al. 2011; Hamid 2012; Törmä et al. 2013). MCS studies conducted in the United States offer ir- In Finland, the total volume of fallen trees during the replaceable information for researchers and weather 2002 derecho was 1 3 106 m3 (Punkka et al. 2006). In late forecasters in Europe. In addition, the ingredients for July and early August 2010, 8 years later, an unusual deep moist convection (Doswell et al. 1996) remain the series of severe MCSs, including two confirmed derechos same regardless of geographic location. However, ear- hit Finland. About 8 3 106 m3 of trees were fallen lier studies have shown that every geographic area has its own special characteristics that can only be identified by conducting area-specific studies. First, Brooks (2009) Corresponding author address: Ari-Juhani Punkka, Finnish Meteorological Institute, Safety Weather Service, P.O. Box 503, showed that the probability of severe weather occurring 00101 Helsinki, Finland. is different for the United States and Europe when E-mail: ari-juhani.punkka@fmi.fi similar values of convective available potential energy

DOI: 10.1175/WAF-D-13-00146.1

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(CAPE) and deep-layer wind shear are present. Second, organized deep moist convection and convective the synoptic-scale patterns that are conducive for the straight-line winds. This will be done by creating three formation of MCSs vary from area to area. This can lead populations of cases: days with intense MCSs, days with to differences in the average direction of MCS move- nonintense MCSs, and days with sub-MCS-scale clusters ment (Punkka and Bister 2005; Lewis and Gray 2010; of thunderstorms (explained in section 2 in detail). For Parker and Johnson 2000; Coniglio and Stensrud 2004). each population, composite weather maps, proximity Third, most MCS studies have been conducted in envi- soundings, and corresponding box-and-whiskers plots ronments with high average CAPE values. James and are analyzed (section 4). The best discriminators be- Markowski (2010) showed that dry air above the cloud tween the three groups of days will be identified with base may decrease the downdraft and cold pool intensity the aid of sounding analysis. Finally, the corresponding in a low-CAPE environment. These results encourage sounding analysis will be done for the days with significant conducting area-specific MCS studies in Finland and and insignificant amounts of wind-related emergency other areas. callouts. While most MCS studies are based on satellite data (e.g., Maddox 1980), the precipitation structures below 2. Data and methods cold cirrus clouds can only be studied with the aid of radar reflectivity data. Therefore, the scarcity of Euro- The study period covered eight warm seasons from pean radar data–based MCS studies is surprising. Most April to September 2000–07. In addition, four cold studies only have data from one or two Doppler radars seasons from October to March were examined in order (e.g., Schiesser et al. 1995; Hagen et al. 2000; Rigo and to create a general overview of the wintertime MCS Llasat 2007; Davini et al. 2011; Goudenhoofdt and frequency. Two main data sources were used in this Delobbe 2012), which ultimately hinders the tracking of study: composite radar reflectivity imagery for MCS convective systems and increases the number of partly detection and proximity soundings for describing the tracked MCSs. The only studies that utilize data from MCS environment. Moreover, to determine the synoptic- more than two radars and that the authors are aware of scale weather pattern within which the different types of are Punkka and Bister (2005) and Walther and Bennartz events occur, the composite maps of mean sea level (2006). Punkka and Bister (2005) studied the occurrence pressure, 300-hPa geopotential height, and 700-hPa spe- of MCSs in Finland and nearby regions by utilizing data cific humidity were produced based on reanalysis data. from seven radars. Walther and Bennartz (2006) used a. MCS detection and radar data data from the Advanced Weather Radar Network for the Baltic Sea Region (BALTRAD; Michelson et al. The extent of the study area was dictated by the 2010), which includes numerous individual radars. Finnish radar network coverage (Fig. 1), which is roughly However, as the main focus of their study was the oc- confined between the latitudes of 608 and 708N. During currence of stratiform and convective precipitation over the study period, the network experienced two updates. the Baltic Sea region, they did not consider MCSs. One In 2000, the network consisted of six C-band radars but potential reason for the scarcity of radar-based Euro- a year later, a seventh C-band radar was deployed in pean MCS studies might be the difficulties encountered northern Finland (Fig. 1). In 2005, another C-band radar in cross-border radar data exchange. was added to the network in western Finland. In the United States, MCS research has advanced The spatial and temporal resolutions of the pseudo– from climatological (e.g., Maddox 1980; Bluestein and constant altitude plan position indicator (CAPPI) com- Jain 1985; Bluestein et al. 1987; Geerts 1998) and posite images were 1 km 3 1 km and 30 min, corre- structural investigations (e.g., Smull and Houze 1985, spondingly. Reflectivity values between 18 and 40 dBZ 1987; Houze et al. 1990; Parker and Johnson 2000) to- were classified as stratiform precipitation and values ward studies concentrating on forecasting issues, such as exceeding 40 dBZ were labeled as convective pre- MCS initiation, sustenance, longevity, and severity (e.g., cipitation. This definition is the same as used by Punkka Gale et al. 2002; Jirak et al. 2003; Coniglio et al. 2004, and Bister (2005) and is very similar to the definitions 2007, 2010; Kuchera and Parker 2006; Cohen et al. 2007; used in other radar data–based studies by Houze et al. Jirak and Cotton 2007; Lombardo and Colle 2012). For (1990), Schiesser et al. (1995), Geerts (1998), Hilgendorf the time being, corresponding studies are unfortunately and Johnson (1998), Hagen et al. (2000), Parker and exceedingly rare in Europe. Johnson (2000), and Goudenhoofdt and Delobbe (2012). In addition to compiling the statistics of MCS occur- The generic and widely used MCS definition originally rence (section 3), this study aims to provide weather proposed by Houze (1993) can be applied to radar data forecasters with new methods to assist in forecasting as follows:

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FIG. 1. The area of study (thin black line), operational weather radars (black dots), and rawinsonde stations (open black circles). d a continuous area of stratiform precipitation (18– direction of MCS motion. The initiation of an MCS was 40 dBZ), with a long axis of more than 100 km in an declared when the 100-km condition was met for the first arbitrary direction exists for at least four consecutive time. The time of decay was defined to be the time when hours; the system no longer fulfilled the condition. The time d during the lifetime of the system, convective pre- when the area of the most intense echoes was largest was cipitation (over 40 dBZ) is present during at least called the time of maximum intensity. two consecutive hours; and In this study, MCS duration means the elapsed time d an MCS is classified as intense if the maximum between the time of the first and last MCS detections. reflectivity exceeds 50 dBZ for at least two consecutive About 10% of the MCSs initiated and decayed beyond hours. the radar range. The inclusion of partially sampled MCSs mainly affects the statistics of MCS duration, This definition allows fairly modest mesoscale pre- which is discussed in section 3b in more detail. Hence, in cipitation areas to be included in the MCS dataset. The the following sections no distinction is made between study approach differs from that often taken in studies completely and partially tracked MCSs. based on satellite data (e.g., Maddox 1980; Anderson and Arritt 1998; Morel and Senesi 2002). Very few, if any, of b. Proximity soundings and wind-related emergency the MCSs analyzed in this study could be classified as callouts mesoscale convective complexes (MCCs), which are Three types of days were of particular interest during frequently the focus of satellite data–based studies. the study period: By using composite reflectivity loops, the MCSs were manually identified. Several figures were collected dur- 1) days with at least one intense MCS (iMCS hereafter), ing the tracking process, including the time of initi- 2) days with at least one nonintense MCS but no intense ation, time of decay, time of maximum intensity, and the MCSs (niMCS hereafter), and

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3) days with no MCSs but sub-MCS-scale thunderstorms and thunderstorm clusters with at least 100 detected cloud-to-ground lightning strikes over the study domain (sub-MCS hereafter). Lightning data were retrieved from the Nordic Lightning Detection System (Mäkelä 2011). During the study period, 382 iMCS days, 569 niMCS days, and 245 sub-MCS days were recorded. The differences in the environment between the above-mentioned classes were studied with the aid of rawinsonde observations from seven sounding stations (Fig. 1). The definition for proximity soundings (Brooks FIG. 2. Average monthly numbers of all MCSs (gray) and iMCSs et al. 1994) was as follows: (black) in Finland during 2000–07. The data from October to March (asterisk) are based on four cold seasons. d the sounding should be launched within 3 h of the time of the maximum intensity, d the sounding should be located within 200 km of the were classified as intense, which demonstrates that nearest 40- or 50-dBZ echo, and excluding cold-season cases (Punkka and Bister 2005) d the most unstable parcel in the sounding should have results in only 2% of intense MCSs being neglected. 2 at least a modest amount (.50 J kg 1) of convective a. Annual and monthly distribution available potential energy and should not show signs of contamination from earlier convective activity. The occurrence of MCSs varies considerably from year to year (not shown). For example, in 2000, only 146 The raw sounding data were analyzed with the General warm-season MCSs were detected but 4 yr later there Meteorological Package/National Skew-T Hodograph were 356 MCSs. The numbers of iMCSs in 2000 and 2004 Analysis and Research Program (GEMPAK/NSHARP) were 51 and 146, respectively. The peak season for the (DesJardins and Petersen 1985). In total, 131 proximity occurrence of MCSs is midsummer: July and August soundings for iMCSs, 53 for niMCSs, and 105 sub-MCSs (Fig. 2). On average, almost 60 MCSs per month are were found. Box-and-whiskers plots of various thermo- observed in July. Also, iMCSs reach their maximum dynamic and kinematic parameters were created in order frequency in July and August, when about 50% of all to illustrate the differences between the three classes. MCSs qualify as being intense. There are no substantial In addition, daily information of the locations and differences compared to the results presented by times of wind-related emergency callouts for the years Punkka and Bister (2005) for the years 2000–01. 2001–07 were retrieved from a Ministry of Interior Figure 2 shows that the changes in the monthly mean database (PRONTO; available online at https://prontonet. MCS occurrence are large during early summer and fall. fi). Most of these callouts were due to fallen trees on This is particularly true for iMCSs, as these types of main and side roads. Only days with at least 10 callouts systems are virtually absent from December to March. were regarded as significant (SIG hereafter) wind These abrupt changes are probably related to the rapid damage days. The remaining days were classified as changes in insolation during the intermediate seasons. nonsignificant (NONSIG hereafter). The dataset of the These results are consistent with many MCS SIG cases consisted of 68 proximity soundings and the and convective storm studies conducted in central and NONSIG dataset included 176 soundings. The SIG western Europe. In the United Kingdom (Gray and (NONSIG) dataset consisted of 8 (38) niMCS, 13 (70) Marshall 1998; Lewis and Gray 2010) and in Belgium sub-MCS, and 47 (68) iMCS soundings. (Goudenhoofdt and Delobbe 2012), convective pre- 3. MCS occurrence cipitation is maximized during midsummer. In contrast, in the continental United States, the peak in MCS oc- During the 8-yr study period, 1782 warm-season me- currence has been observed to occur earlier, during soscale convective systems were detected, out of which April–July (Houze et al. 1990; Geerts 1998; Bentley and 649 (36%) were classified as intense. To quantify the Sparks 2003). frequency of cold-season (October–March) MCSs, the b. Duration composite reflectivity data from four winter periods were also examined. Including four cold seasons added In this study, the average duration of an MCS was 218 MCSs to the dataset. Only seven cold-season MCSs 10.8 h. The average duration for the intense MCSs

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FIG. 3. Cumulative frequency distribution of MCS durations in Finland during 2000–07. The iMCSs are shown by the solid line and niMCSs by the dashed line.

(10.1 h) was 1 h shorter than for the nonintense MCSs convective systems varied from 6 to 12 h in the central (11.1 h). The shortest MCS durations during the warm United States. In the southeastern United States (Geerts season were recorded during July and August. 1998), the duration minimum did not take place in The frequency distribution of MCS durations is midsummer but in March–June. slightly skewed toward short durations; the mode and c. Time of initiation, decay, and maximum intensity the median of the MCS duration are 4 and 8.5 h, correspondingly. The skewed distribution is also illustrated in Many iMCSs initiate during the afternoon and early Fig. 3. The cumulative frequency distribution shows that evening (Fig. 4), between 1000 and 1700 UTC (local approximately 70% of the iMCSs have a duration of less time in summer is UTC 1 3 h). Because of their strong than 10 h. Moreover, iMCSs with a duration of less than dependency on the diurnal cycle, they tend to decay in 10 h are more common than the corresponding niMCSs. the evening or in the very early hours of the morning, As a result of the limited areal extent of the radar between 1600 and 2200 UTC. For niMCSs, a clear ini- coverage, 10% of the MCSs analyzed in this study were tiation peak is observed during nighttime and morning initiated and decayed beyond the radar range. The du- hours and a less pronounced decay peak is visible rations of the partly and fully tracked systems were 12 around midday and in the afternoon. The reasons for and 9 h, respectively. The dataset also includes some these peaks are unknown. In the 2000–01 data (Punkka MCSs with exceptionally long durations. In most in- and Bister 2005), these peaks for the niMCSs were not stances, these cases are related to slow-moving, or even particularly strong. stationary, low pressure systems. The related mesoscale There is also a pronounced afternoon and evening precipitation areas have convective precipitation for peak in the distribution of the time of maximum iMCS only a few hours but the stratiform precipitation remains over the study domain for signiﬁcantly longer. The proximity sounding data are only analyzed from the times and locations when the MCSs have (intense) convective precipitation (40 or 50 dBZ) associated with them. Thus, the results based on these data are not af- fected by the extended length of the stratiform precipitation in some cases. The results for MCS duration are in rough agreement with previous European studies. Schiesser et al. (1995) found that MCSs in Switzerland have an average duration of 8 h. Rigo and Llasat (2007) reported that MCSs in Catalonia usually remained within the radar mea- FIG. 4. Time of initiation (solid lines) and dissipation (dashed surement range for less than 10 h. Parker and Johnson lines) for iMCSs (black) and niMCSs (gray) in Finland during (2000) showed that the average lifetimes of quasi-linear 2000–07.

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IG FIG. 5. Time of max intensity for niMCSs (dashed line) and iMCSs F . 7. Average elapsed time between the initiation and max (solid line) in Finland during 2000–07. intensity for iMCSs in Finland during 2000–07.

d. MCS line orientation and direction of MCS motion intensity (Fig. 5). The peak is located between 1100 and 1700 UTC and is consistent with the known daily cycle Roughly 80% of the MCSs in this study moved toward of deep moist convection. The maximum intensity dis- the sector between northwest and east (Fig. 9). The most tribution for niMCSs does not have a pronounced di- common direction of motion is northeast and there are urnal cycle but a narrow morning maximum is evident slightly more iMCSs than niMCSs that move toward the between 0300 and 0700 UTC. This is probably associ- north. The iMCSs that have a component of motion ated with niMCSs that initiated during the preceding toward the west is a geographic-specific feature (Punkka night. et al. 2006; Järvi et al. 2007). These situations are related The time of initiation only has a minor effect on MCS to a highly meridionally elongated upper-level flow durations (Fig. 6). The noon and afternoon iMCSs have, structure, which is discussed further in section 5. The however, durations that are a few hours shorter than the synoptic-scale pattern also affects the orientation of intense systems that initiate during other times of the linear MCSs. The most common convective line orien- day. Moreover, the afternoon iMCSs reach their maxi- tations in this study are southwest–northeast, south– mum intensity within 3–4 h after initiation whereas north, and southeast–northwest (Fig. 10). nocturnal iMCSs require 5–6 h to reach their maximum intensity (Fig. 7). The time of day may also help predict 4. MCS environment whether the MCS will become intense or not. About 50% of the MCSs that initiate during the afternoon will a. Synoptic-scale environment be classified as intense (Fig. 8). For nocturnal MCSs, the A common perception of Finnish weather forecasters corresponding fraction is only 20%–30%. is that episodes of widespread deep moist convection occur most frequently during warm and moist southerly or southeasterly airflow from the Baltic countries and

FIG. 6. Dependence of average duration on the time of initiation for niMCSs (gray bars) and iMCS (black bars) in Finland during FIG. 8. Fraction of iMCSs as a function of initiation time in Finland 2000–07. during 2000–07.

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FIG. 10. Line orientation of linear convective systems in Finland during 2000–07. The S–N (N–S) orientation describes a south– north-oriented line that has a motion component toward the east (west). Correspondingly, a SW–NE (NE–SW)-oriented line has a motion component toward the east (west).

FIG. 9. Distribution of the direction of motion of niMCSs (dashed line) and iMCSs (solid line) in Finland during 2000–07. southerly surface-level flow. In the niMCS cases, a low pressure area is located partly over Finland. The sub- Russia. This particular weather pattern takes place MCS fields greatly deviate from the MCS cases, having when an area of low pressure is located south, southwest, an upper-level ridge west of Finland and a surface ridge or west of Finland. Recently, this perception has been of high pressure stretching from western Europe to supported by results of several case studies of significant Scandinavia. This pattern would lead to westerly convective weather events in Finland (e.g., Punkka et al. surface-level flow. 2006; Järvi et al. 2007; Rauhala and Punkka 2008; Törmä Distinctions between the iMCS and sub-MCS days are et al. 2013). also observed in other composite maps. For example, To identify synoptic situations that are associated with maps for the 850- and 925-hPa levels suggest that cooling the development of MCSs, National Centers for Envi- (warming) and drying (moistening) of the lower tropo- ronmental Prediction–National Center for Atmospheric sphere would occur prior to the sub-MCS (iMCS) events Research (NCEP–NCAR) reanalysis data (Kalnay (not shown). Differences in moisture also appear at the et al. 1996) were used to create composite maps (http:// 700-hPa level where the iMCS environment is most www.esrl.noaa.gov/psd/data/composites/nssl/day/) for humid and the sub-MCS environment driest (Fig. 11). the July and August iMCS, niMCS, and sub-MCS days. The role of humidity above cloud base will be discussed This geographic-relative compositing technique has se- in more detail in the following sections. vere limitations due to its smoothing effect on the re- b. Proximity soundings: Thermodynamic parameters sulting fields. Thus, this technique does not allow the MCS environment or the different stages of the MCS life The SIG class proximity soundings are those that were cycle to be closely examined. The synoptic-scale launched during the sub-MCS or MCS days that had at weather patterns of individual cases may deviate sub- least 10 wind damage reports. The soundings in the stantially from the composite. Individual events feature NONSIG class were from the sub-MCS or MCS days more pronounced anomalies (of, e.g., moisture and with fewer than 10 wind damage reports (see section 2 for temperature) and the orientation of the mean flow over details). A Student’s t test was performed to determine if the study region may differ as well (e.g., southeasterly the datasets were statistically different from each other. flow instead of southwesterly). We recognize that many of the parameters discussed in The composite 300-hPa geopotential height field this study are not free to vary independently. For ex- suggests that in the MCS cases an upper-level trough is ample, dry low-level air affects the values of CAPE and located to the west of the study area (Fig. 11). In the the lifting condensation level (LCL) height. iMCS, the mean sea level pressure field shows that a low The iMCS and SIG classes have the highest median 2 pressure is located west of Finland, which would lead to values of most unstable CAPE, about 800 J kg 1 (Fig. 12a).

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FIG. 11. Reanalysis composite maps for the (top) 300-hPa height (gpm), (middle) mean sea level pressure (hPa), and (bottom) 700-hPa 2 speciﬁc humidity (kg kg 1). Maps for (left) iMCS, (middle) niMCS, and (right) sub-MCS days. Image provided by the NOAA/ESRL/ Physical Sciences Division, Boulder, CO, from their website (http://www.esrl.noaa.gov/psd/).

2 The niMCS class has the lowest value of around 500 J kg 1. The low-level mixing ratio (defined as being within Since the MCS intensity is directly determined from, and the lowest 100 hPa of the atmosphere) distributions thus is directly related to, the radar reflectivity in this study, (Fig. 12b) have many similarities with the CAPE dis- it is not surprising that intense systems occur in situations tribution (Fig. 12a). The iMCS and SIG classes possess 2 with higher CAPE. According to parcel theory, more the highest median values of around 9 g kg 1 whereas energy leads to more intense updrafts, which enhance the sub-MCS and the NONSIG soundings are notice- hydrometeor production or even hail formation inside the ably drier. The low-level moisture differences between updraft regions, and, eventually, leads to higher radar re- the iMCS and niMCS, the iMCS and sub-MCS, as well as flectivities. the SIG and NONSIG classes are significant at the 99% The above-mentioned CAPE values are considerably confidence level. The 850–500-hPa lapse rate is not able lower than in studies concerning the central United to discriminate any classes from each other and the 2 States (e.g., Bluestein and Jain 1985; Bluestein et al. median values are around 6.5 K km 1 in every class 1987; Parker and Johnson 2000). Brooks (2009) studied (Fig. 12c). This is also confirmed by statistical tests that environments of severe convective weather in Europe show that lapse-rate distributions are not significantly and the United States and also observed much lower different. CAPE values in Europe. Moreover, Jirak and Cotton The distributions of maximum vertical equivalent

(2007) showed that the amount of CAPE could distin- potential temperature differences Due (Fig. 12d) largely guish rather well between MCS and sub-MCS cases in resemble the CAPE distributions (Fig. 12a). The abso- the central United States. lute Due values are, however, noteworthy. For the SIG

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21 FIG. 12. Box-and-whiskers plots for proximity soundings for different event classes. (a) Most unstable CAPE (J kg ), 2 2 (b) mixing ratio (g kg 1) of the lowest 100 hPa, (c) 850–500-hPa lapse rate (K km 1), (d) max vertical equivalent potential temperature difference (K), (e) LCL height (m) for the layer-mean (lowest 100 hPa) air parcel, (f) 500-hPa relative humidity (%), and (g) 700-hPa relative humidity (%). The extreme values are located at the tips of the whiskers. The center bar contains 50% of the cases and the horizontal line inside the bar shows the parameter median value.

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21 21 FIG. 13. As in Fig. 12, but for (a) 0–3-km bulk wind shear (m s ) and (b) LFC–EL mean wind (m s ).

class, the median Due value is slightly above 10 K and the c. Proximity soundings: Kinematic parameters 75% percentile value is around 15 K. Both values are considerably lower than the rule of thumb of 20 K used In this study, the 0–3-km bulk wind shear (Fig. 13a)is for forecasting severe straight-line winds in the United a better discriminator than the 0–6-km bulk wind shear; States (Atkins and Wakimoto 1991). In addition to the it is able to discriminate the iMCS cases from the sub- results concerning the direction that MCSs travel in MCS cases at the 99.9% confidence level and even the Finland and the inability of the midlevel lapse rate to iMCSs from the niMCSs at the 95% level. The bulk wind distinguish between the different event types, the ab- shear from the surface to 6 km (not shown) is able to solute values of Due identified in this study demonstrate discriminate the iMCS class from the sub-MCS class at the importance of studying local MCS environments. the 99% confidence level, which is not the case between Cohen et al. (2007) studied quasi-linear MCSs with the other classes. The median value in the SIG class 2 varying extents of wind damage east of the Rocky is 10 m s 1, which is almost equal to the typical values Mountains in the United States. They found that CAPE for nonsupercell thunderstorms in the United States and maximum vertical equivalent potential temperature (Thompson et al. 2003). According to Evans and Doswell difference had skill to discriminate weak events from (2001), typical 0–6-km wind shear values in derecho cases 2 significant events. Cohen et al. (2007) also observed that are between 12 and 20 m s 1 but during nonderecho MCS 2 the midlevel lapse rate performed quite well in dis- situations they range from 5 to 13 m s 1. tinguishing between different event types, which was not The mean wind speeds for three different layers were the case in our study. calculated: 0–6 km, 850–200 hPa, and lifting condensa- The average LCL seems to fluctuate from class to class tion level–equilibrium level (LFC–EL). The layer-mean (Fig. 12e). The lowest median LCL value is found in the wind parameters show particularly good ability in sep- niMCS class while the highest value is the sub-MCS class. arating the iMCS from the sub-MCS class as well as the The latter reflects relatively dry low-level air, which is SIG from the NONSIG class. The layer-mean wind typical for the westerly-to-northerly flows (Fig. 11). The distributions are statistically different at the 99.9% level. LCLs in the SIG class are slightly lower than those in the For example, the mean wind for the cloud-bearing layer 2 NONSIG class, which suggests that dry boundary layer (LFC–EL) has a median value of 13 m s 1 in the SIG air and evaporative cooling of air at low levels are not class (Fig. 13b), whereas the corresponding value in the 2 major contributors to severe wind events in Finland. The NONSIG class is only 9 m s 1. LCL distribution of sub-MCSs is statistically significantly Many recent MCS studies in the central and eastern different from that of both iMCSs and niMCSs. United States have shown that the deep-layer-mean The 500- and 700-hPa relative humidity in the SIG winds distinguish between different MCS populations. class does not differ statistically significantly from the The mean wind and bulk wind shear layers up to 10 km NONSIG class (Figs. 12f,g). Therefore, the midlevel discriminate mature MCSs from decaying MCSs relative humidity values do not support the hypothesis (Coniglio et al. 2007) and weak MCSs from severe that dry air is more conducive for the production of se- wind–producing MCSs (Cohen et al. 2007)overthe vere convective winds (e.g., Atkins and Wakimoto United States. Moreover, Coniglio et al. (2006) showed 1991). However, the relative humidity at 700 hPa, and in their model simulations that the intensification especially at 500 hPa, discriminates between MCSs and of wind shear over a very deep layer led to deeper sub-MCSs with high statistical confidence. updrafts.

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5. Discussion and summary Laing and Fritsch 2000; Parker and Johnson 2000) have shown that upstream upper-level troughs are a com- The occurrence of mesoscale convective systems in monly observed feature in conjunction with MCSs of Finland and nearby regions over an 8-yr period was varying extents and intensities. These troughs modify studied. In addition to the radar data–based MCS sta- the large-scale environment to be more conducive to tistics, the MCS environment was investigated with the organized deep moist convection by, for example, af- aid of proximity soundings. Three subsets of events were fecting moisture transport and the deep-layer wind studied; intense mesoscale convective systems (iMCSs), shear. Upstream upper-level troughs have been ob- nonintense mesoscale convective systems (niMCSs), served in Finland during various MCS situations (e.g., and smaller clusters of thunderstorms (sub-MCS). Punkka et al. 2006; Järvi et al. 2007; Rauhala and Moreover, soundings from days with significant (SIG) Punkka 2008; Törmä et al. 2013). They were also ob- and negligible (NONSIG) amounts of wind damage served in this study in composite reanalysis maps in the were examined separately. Box-and-whiskers plots were MCS cases (Fig. 11). During the sub-MCS events, the compiled from the proximity sounding data for each upper-level composite field was dominated by a ridge of class of events. Composite maps based on NCEP–NCAR high pressure. However, the reliability of these com- reanalysis data were created in order to determine the posite maps is questionable as a result of the smoothing accuracy of the perception commonly held by Finnish effect of the compositing method on the resulting fields. weather forecasters of synoptic situations that favor the In this study, the majority of the MCSs moved toward development of MCSs in Finland. the northeast yet a small fraction of the systems traveled toward the west. Throughout most of Europe, the pre- a. MCS features vailing direction for MCS motion is east or northeast (Schiesser et al. 1995; Hagen et al. 1999; Morel and The manual investigation of the radar reflectivity com- Senesi 2002; García-Herrera et al. 2005; Rigo and Llasat posite imagery revealed the following MCS properties: 2007; Davini et al. 2011; Goudenhoofdt and Delobbe d MCSs were most common in July and August, and 2012). According to Lewis and Gray (2010), some MCSs iMCSs were very rare in winter. Of the systems, one- in the United Kingdom move toward the north or third became intense (maximum reflectivity exceeding northwest. These MCSs with a northward component to 50 dBZ for at least two consecutive hours). their motion occur when a synoptic pattern called d The average MCS duration was 10.8 h but short-lived a European easterly plume is present. During this syn- systems were most common. optic pattern, a strong high pressure area is located over d The iMCS events showed a strong diurnal cycle, Scandinavia and a plume of warm air streams westward having a preference to initiate in the afternoon and toward the United Kingdom. Kolios and Feidas (2010) dissipate in the evening. showed that in southeastern Europe the average MCS d Afternoon systems reached their maximum intensity motion direction is toward the north. A vast majority of quicker than MCSs during other times of day and they the MCSs in the continental United States move toward were more likely to reach the iMCS status than other the east or southeast (Maddox 1980; Bentley and Sparks systems. 2003) and systems having a motion component toward d The majority of the MCSs moved toward the sector the west are rare. between the northwest and east. Some MCSs pos- Differences within the synoptic framework (e.g., lo- sessed a motion component toward the west. cation and orientation of upper-level troughs) are also d The most typical convective line orientations were reflected in the orientation of linear MCSs. In this study southwest–northeast, south–north, and southeast– southwest–northeast, south–north, and southeast– northwest. northwest orientations were most common, which partially deviates from the typical line orientation observed in the continental United States. According to Geerts b. Large-scale weather patterns (1998), Parker and Johnson (2000), and Schumacher and The evolution of the synoptic-scale (and mesoscale) Johnson (2005), southwest–northeast and west–east line weather patterns a couple of days, or even hours, before orientations are most frequent in the continental United the onset of deep moist convection critically affects the States. intensity, areal extent, and convective mode of an event. From time to time, a meridionally elongated upper- Several studies in Europe (e.g., Hernández et al. 1998; level trough and low pressure area are located west or Lewis and Gray 2010) and in the continental United southwest of Finland enabling southerly or southeast- States (Maddox 1983; Hilgendorf and Johnson 1998; erly flow from the Baltic countries and Russia into

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Finland (e.g., Punkka et al. 2006; Järvi et al. 2007; same pressure levels (not shown), differences between Rauhala and Punkka 2008; Törmä et al. 2013). During the MCS classes are minor over the southern part of the these situations, the southerly flow brings moisture-rich study area. However, in the northern part the niMCS air to Finland. This weather pattern is occasionally as- cases have the highest relative humidity values. Again, sociated with a cold front approaching from the south- the sub-MCS cases are notably drier than the MCS cases west or even south. The front and vertical wind profile over the whole study area. As previously noted, the re- together might lead to the formation of a linear MCS liability of the composite maps is rather limited but that, by North American standards, has a rare line ori- similar moisture features are also visible in the proxi- entation and motion direction. The line orientation (e.g., mity soundings. The sub-MCS cases occur in consider- southeast–northwest) originates from the orientation of ably drier environments than do the MCS cases. the frontal boundary and the peculiar direction that the Despite the fact that no definitive conclusions can be MCSs travel in (such as toward the northwest or west) is drawn based on this brief analysis, the results suggest due to southerly to easterly steering flow. that moisture above cloud base could be important for The above-mentioned weather pattern also affects the the upscale growth and intensity of deep moist convec- midlevel lapse rates. However, the proximity soundings tion in Finland and nearby regions. Analogously with showed that midlevel lapse rate is a poor discriminator the findings of James and Markowski (2010), dry mid- between the event classes. The lapse-rate values found level air appears to favor sub-MCS-scale weak convec- 2 in this study are between 6 and 6.5 K km 1 and therefore tion as opposed to MCS-scale convection in our study. are very low compared to the typical values for MCSs in Our results did not show any evidence that would the central United States (Jirak and Cotton 2007; Cohen indicate that dry low- or midlevel environments are et al. 2007; Coniglio et al. 2007). more prone to produce severe wind events than moist environments. According to Kuchera and Parker (2006), c. Role of moisture the midlevel relative humidity only differed slightly The role of low-level moisture was clearly observed in between the environments of severe convective wind– this study in the iMCS class. According to the proximity producing thunderstorms and ordinary thunderstorms. sounding analysis, the low-level mixing ratio discrimi- Moreover, our results could not verify the validity of nated between the iMCS and niMCS classes and between the 20-K equivalent potential temperature rule (Atkins the iMCS and sub-MCS classes, as did the CAPE values. and Wakimoto 1991), which is widely used for the pre- In addition, the LCL height was lowest in the iMCS cases diction of downbursts in the United States. The median and notably higher in the sub-MCS class. The above- value for the SIG class was only slightly over 10 K. In- mentioned results suggest that low-level moisture has an stead of moisture-dependent variables, deep-layer- effect on the type of deep moist convection. mean winds (0–6 km, 850–200 hPa, and LFC–EL) were Unlike low-level moisture, the role of dry air above able to distinguish between the SIG and NONSIG the cloud base has received limited attention in previous classes at a very high level of confidence. studies. James and Markowski (2010) recently performed a numerical study on the effect of dry air on deep d. Implications for forecasting moist convection. One of their main findings was that Based on the results and discussion in the earlier dry air above the cloud base did not reinforce the sections, the following remarks about the dynamic and downdrafts and cold pool if CAPE was low. Moreover, thermodynamic environment of Finnish MCSs can be the updraft mass flux was observed to decrease when dry made: air was present. In Finland, CAPE values are typically modest and therefore high humidity above cloud base d The sub-MCS-scale deep moist convection takes place might be beneficial for the development and sustenance in notably drier low- and midlevel environments than of deep moist convection. MCSs. The intense MCSs occur in the most humid The 850-, 700-, and 500-hPa pressure levels are mainly low-level environments. Whenever modest CAPE is located above the convective cloud base in Finland. An available, weather forecasters should pay special examination of composite specific humidity maps for attention to areas with high moisture values in the these levels (700 hPa shown in Fig. 11) reveals that the low- to midtroposphere. most substantial differences are situated in the southern d The presence of dry low- and midlevel air does not half of the study domain. In this area the iMCS cases seem to increase the likelihood of severe convective have the highest moisture values, followed by the wind events in areas with modest CAPE values. niMCS cases. The sub-MCS cases are notably drier than d Midlevel lapse rates are very similar in MCSs and sub- the MCS classes. In the relative humidity plots for the MCSs. The lapse rate fails to discriminate between the

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