DECEMBER 2015 K U M J I A N A N D D E I E R L I N G 1469

Analysis of over Northern Colorado

MATTHEW R. KUMJIAN Department of , The Pennsylvania State University, University Park, Pennsylvania

WIEBKE DEIERLING Research Applications Laboratory, National Center for Atmospheric Research,* Boulder, Colorado

(Manuscript received 13 January 2015, in final form 12 August 2015)

ABSTRACT

Lightning flashes during snowstorms occur infrequently compared to warm- convection. The rarity of such thundersnow events poses an additional hazard because the is unexpected. Because electrification in thundersnow storms leads to relatively few lightning discharges, studying thundersnow events may offer insights into mechanisms for charging and possible thresholds required for lightning dis- charges. Observations of four northern Colorado thundersnow events that occurred during the 2012/13 are presented. Four thundersnow events in one season strongly disagrees with previous climatologies that used surface reports, implying thundersnow may be more common than previously thought. Total lightning information from the Colorado Lightning Mapping Array and data from conterminous United States light- ning detection networks are examined to investigate the snowstorms’ electrical properties and to compare them to typical warm-season . Data from polarimetric WSR-88Ds near Denver, Colorado, and Cheyenne, Wyoming, are used to reveal the storms’ microphysical structure and determine operationally relevant signatures related to electrification. Most lightning occurred within convective cells containing and pristine . However, one flash occurred in a stratiform snowband, apparently triggered by a tower. Depolarization streaks were observed in the radar data prior to the flash, indicating electric fields strong enough to orient pristine . Direct comparisons of similar lightning- and nonlightning- producing convective cells reveal that though both cells likely produced graupel, the lightning-producing cell had larger values of specific differential phase KDP and polarimetric radar–derived ice mass. Compared to warm-season thunderstorms, the analyzed thundersnow storms had similar electrical properties but lower flash rates and smaller vertical depths, suggesting they are weaker, ordinary thunderstorms lacking any warm (.08C) cloud depth.

1. Introduction incidents have occurred at ski resorts, which host a variety of outdoor activities (e.g., Berger 1998; Zook 2014). Thundersnow events are rare phenomena that are said Electrified winter can pose an aviation hazard, as to occur when -bearing storms produce lightning highly electrified areas have a high probability of causing and thunder. Because lightning in winter storms is less aircraft- or helicopter-triggered lightning (e.g., Mäkelä common and may seem counterintuitive, such events may et al. 2013; Wilkinson et al. 2013). Additionally, other take forecasters and the public by surprise and may pose winter hazards such as heavy snow have been an unexpected hazard. Though people tend to spend associated with thundersnow events (Crowe et al. 2006). less time outdoors in winter months, lightning-related Thus, better understanding these unique storms could serve to mitigate potential risks. * The National Center for Atmospheric Research is sponsored Schultz and Vavrek (2009) provide a good review of by the National Science Foundation. historical observations of thundersnow events, which are limited because of their rarity. In the United States, early climatological studies of thundersnow events used Corresponding author address: Dr. Matthew R. Kumjian, Dept. of Meteorology, The Pennsylvania State University, 513 Walker surface reports. For example, Curran and Pearson Bldg., University Park, PA 16802. (1971) investigated 76 thundersnow cases in the United E-mail: [email protected] States and found that only 1.3% of cool-season

DOI: 10.1175/WAF-D-15-0007.1

Ó 2015 American Meteorological Society 1470 WEATHER AND FORECASTING VOLUME 30 thunderstorms (i.e., those occurring between October that the mean environment of their thundersnow cases and May) produced snow, and that only 0.07% of was supportive of elevated convection, with a stable snowfall observations were associated with lightning or boundary layer topped by a near-neutral thermal profile. thunder. Further, Market et al. (2002) analyzed 3-hourly Market et al. (2006) found similar results for thunder- to construct a climatology of thundersnow snow events in the central United States, with the most- events. They reported only three incidences of thun- unstable level roughly 30–50 hPa above the top of the dersnow in northern Colorado over a 30-yr period from low-level temperature inversion. Rauber et al. (2014) 1961 to 1990, and an average annual occurrence of only found that lightning in midwestern winter 6.3 events across the conterminous United States tended to occur in regions of convective instability in (CONUS). Their climatology was not meant to be ex- the comma-head region, associated with dry upper- haustive and, instead, probably better characterizes the tropospheric air overrunning moister air from the Gulf broader synoptic distribution of thundersnow events, as of Mexico. They suggest that conditional symmetric in- the use of surface reports for thundersnow detection is stability (CSI) likely did not play a role in driving the limited by the spatial coverage and resolution of surface convection. In contrast to typical convective observing stations, population density, etc. storms, thundersnow storms are found to have lower These studies were performed before data from na- convective available potential energy (CAPE) (e.g., tionwide lightning detection networks were readily Market et al. 2006; Mäkelä et al. 2013) and, conse- available. These networks provide high-resolution spa- quently, weaker updrafts and much lower vertical tiotemporal information on lightning events across the cloud extent. CONUS (e.g., Orville 1991; Cummins et al. 1998; Orville In addition to an environment supporting convection, and Huffines 2001; Holle 2014). More recent studies cold (,08C) air throughout the -bearing have made use of such lightning detection network data layer is required to produce snow at the surface. The to investigate various aspects of thundersnow events composite sounding in Market et al. (2006) was cold (e.g., Pettegrew 2008; Market and Becker 2009; Rauber enough throughout the lower to support et al. 2014). For example, Pettegrew (2008) analyzed snow. The surface temperature in thundersnow events Vaisala’s National Lightning Detection Network often is found to be very near 08C (e.g., Schultz 1999; (NLDN) data from 14 central United States thunder- Hunter et al. 2001; Stuart 2001). Market et al. (2002) snow cases between October 2006 and April 2007, and found the mean surface temperature in their thunder- found that only 1.4% of flashes during these events were snow cases to be about 218C. Model soundings from the associated with winter precipitation. long-lived thundersnow event studied by Market et al. Such CONUS networks mostly detect cloud-to- (2007) were consistent with these previous findings, ground (CG) lightning, which only makes up a frac- as well. tion of all lightning discharges (Cummins et al. 1998; electrification leading to lightning is Boccippio et al. 2000). In recent years, however, the typically associated with storms exhibiting a strong up- detection efficiency of total lightning from these net- draft and a robust mixed-phase region (Williams and works has been improving (e.g., Rudlosky and Fuelberg Lhermitte 1983; Dye et al. 1988; Zipser and Lutz 1994; 2010). Additionally, the growing availability of regional Wiens et al. 2005; Deierling et al. 2008). Moreover, total lightning detection systems has enhanced our de- collisions between hydrometeors such as graupel and ice tection capabilities. Such systems include the Lightning crystals in the presence of supercooled liquid water Mapping Array (LMA), developed by the New Mexico (SLW) is the basis for significant charging to take place Institute of Mining and Technology (NMIMT), which via the noninductive charging mechanism that is thought detects both CG and in-cloud (IC) flashes with high to play a dominant role in lightning production detection efficiency and accuracy (Rison et al. 1999; (Takahashi 1978; Saunders 1993; Saunders and Peck Krehbiel et al. 2000; Thomas et al. 2004; Lang et al. 2004) 1998; MacGorman and Rust 1998; Takahashi and within a 100–200-km range. Thus, with these systems it is Miyawaki 2002). However, in the absence of appreciable possible to document events that previously may have SLW, noninductive charging may also occur (e.g., Dye gone undetected. and Willett 2007; Kuhlman et al. 2009), albeit at lesser Previous studies have also explored the necessary at- charging rates. Furthermore, other charging mecha- mospheric ingredients for thundersnow storms. Schultz nisms including inductive charging may also contribute and Vavrek (2009) point out that the same conditions to cloud electrification (e.g., MacGorman and Rust needed for warm-season thunderstorms must be present 1998). As thundersnow cases documented in previous in thundersnow events: moisture, lift, and an unstable studies are associated with lower CAPE, yielding lower temperature profile. Curran and Pearson (1971) showed updraft strength and vertical cloud extent, one expects DECEMBER 2015 K U M J I A N A N D D E I E R L I N G 1471 that the availability of SLW, charging, and thus resultant 2012/13 season was anomalous, it does hint at the possi- flash rates should also be lower compared to their warm- bility that thundersnow events are more common than season convective storm counterparts. For reference, previously documented [i.e., only 6.3 events on average flash rates in warm-season convective storms may range annually in the CONUS; Market et al. (2002)], as obser- from several flashes per minute to hundreds of flashes vations from regional lightning detection networks such as per minute in high-end severe cases (e.g., Williams et al. the LMA detect CG and IC (i.e., total) lightning more 2005; Deierling et al. 2008; Fuchs et al. 2015). In contrast, comprehensivelythandotheCONUSnetworksusedin total lightning flash rates in a variety of thundersnow the previous studies mentioned above. storms have yet to be quantified. This study aims to answer the following questions: Several authors have also investigated the precipi- (i) How often are these storms detected by CONUS tation structure of thundersnow events using radar. versus LMA networks? Pettegrew et al. (2009) used data from a single- (ii) What types of dual-polarization radar signatures in polarization WSR-88D to investigate a thundersnow these Colorado thundersnow storms may be rele- event over eastern Iowa and north-central Illinois. The vant to operational forecasters? echo top of the storm in their case study never ex- (iii) What are the electrical properties of these storms, ceeded ;3.7 km AGL, and its maximum values of re- and how do they compare to ordinary warm-season flectivity factor at horizontal polarization Z never H convective storms? surpassed 40–45 dBZ. These maximum ZH values were confined to the lowest levels, consistent with particles If the LMA data reveal events that are missed by the growing by aggregation and/or riming as they descend. CONUS networks, this implies that previous climatol- Market and Becker (2009) analyzed the spatial re- ogies constructed using only surface reports or CONUS lationship between lightning and low-level ZH in network data may underestimate the frequency of oc- thundersnow events, using data from the NLDN and currence of thundersnow. Any dual-polarization radar preupgraded WSR-88D network. They found that signatures, if found more widely in thundersnow events the lightning flashes tended to be identified down- around the country, could provide increased situational stream of the largest ZH. awareness about a particular storm’s propensity to pro- However, ZH alone provides only limited insights into duce an otherwise unexpected lightning flash and atten- microphysical structures and processes. In contrast, the dant winter weather hazards such as heavy snow. Also, use of radar polarimetry provides more information such observations can provide information about the bulk about the bulk microphysical structure of thundersnow microphysical structure of lightning-producing convec- storms. A series of studies of an electrified storm over tive snowstorms. In addition, studying low-flash-rate the Sea of Japan made use of C-band dual-polarization thundersnow events could be scientifically advanta- radar data (Fukao et al. 1991; Maekawa et al. 1992, geous, as such events are marginal in nature and could be 1993). These authors noted the collocation of radar- used to better define thresholds necessary for lightning inferred graupel and ice crystals at the 2108C level flashes to occur. Finally, analysis of the microphysical and preceding lightning flashes. They also found that the electrical structure of these storms and the environments lightning-producing cell exhibited ZH . 40 dBZ,whereas in which they form can provide operational guidance for other nearby cells did not. The lightning production situations conducive to thundersnow. seemed to be tied to an increase in the inferred graupel The next section provides an overview of the in- content. However, these authors did not have available strumentation and data used to analyze thundersnow the full complement of polarimetric variables and derived events in this study. Section 3 presents an overview of the products routinely obtained from today’s operational cases, and an analysis of the LMA and CONUS lightning WSR-88D network. data, followed by the detailed polarimetric radar data Comprehensive information about the finescale elec- analysis in section 4. The paper finishes with a discussion trical and microphysical structure of thundersnow is not and summary of the main conclusions in section 5. available to date. In this paper, we report on four events that occurred in northern Colorado over a 5.5-month 2. Instrumentation and data period during the 2012/13 cold season. For the first time, a. Dual-polarization WSR-88Ds the electrical and microphysical thundersnow events are analyzed using lightning data from both the LMA and The National Weather Service WSR-88D network CONUS networks, and using dual-polarization WSR-88D recently has undergone an upgrade to have dual- data. During these four events, a total of 16 individual polarization capabilities. In addition to the conven- storms produced lightning. Though unclear whether the tional moments of ZH, Doppler velocity Vr, and Doppler 1472 WEATHER AND FORECASTING VOLUME 30

2 spectrum width sw, the polarimetric radars provide the squares x minimization technique (e.g., Hiscox differential reflectivity ZDR; differential propagation et al. 1984). phase FDP, from which the specific differential phase KDP r c. CONUS networks is computed; and the copolar correlation coefficient ( hv or CC). Descriptions of these polarimetric variables and Lightning captured by lightning detection networks their informative content can be found in Doviak and covering the CONUS are used herein as well. These Zrnic (1993), Zrnic and Ryzhkov (1999), Straka et al. include Earth Networks Total Lightning Network (2000), Bringi and Chandrasekar (2001), Ryzhkov et al. (ENTLN), the United States Precision Lightning (2005),andKumjian (2013a–c), among others. Network (USPLN) owned by Weather Services In- Data from the WSR-88D polarimetric stations near ternational (WSI), and Vaisala’s NLDN. Generally Denver, Colorado (KFTG), and Cheyenne, Wyoming these networks detect a high percentage of CG lightning (KCYS), are used in this study. In addition to the po- and a lower percentage of IC lightning, as they mostly larimetric variables, the output of the operational hy- operate in the low-frequency (LF) band. Specifically, the drometeor classification algorithm (HCA) is used. The NLDN consists of a combination of time-of-arrival current HCA combines the informative contents of sensors and wideband magnetic direction finder (MDF) each polarimetric radar variable and determines the sensors, collectively referred to as the Improved Accuracy type of scatterer dominating the returned signals in through Combined Technology (IMPACT) sensors. They each radar sampling volume (Park et al. 2009). Cur- detect the electromagnetic radiation with frequencies rently, 1 of 10 possible classes is assigned: light-to- around 10 kHz emitted from long transient current events moderate , heavy rain, big drops, rain mixed with such as CG lightning return strokes. The NLDN also , graupel, wet snow, dry snow aggregates, ice crys- detects a lower percentage of IC lightning. The two- tals, biological scatterers, and ground clutter and/or dimensional, horizontal lightning locations (x, y co- anomalous propagation. ordinates) are retrieved using a generalization of the least squares x2 minimization technique discussed by Hiscox b. Colorado Lightning Mapping Array et al. (1984). NLDN measurements used herein include Three-dimensional total lighting data collected by the information about the location and time, polarity, signal Colorado Lightning Mapping Array (COLMA) were strength, multiplicity (number of return strokes in a flash), used in this study to document the total flash rate from and type (e.g., return stroke or IC event) of the measured the thundersnow events as well as to deduce the location lightning. Detailed descriptions of the NLDN can be found and polarity of charge layers within storm cells. During in Cummins et al. (1998), Cummins and Murphy (2009), the period of study, the COLMA consisted of 15 stations and on the Vaisala website (http://www.vaisala.com/en/ within a 100-km radius equipped with global positioning products/thunderstormandlightningdetectionsystems/ system (GPS) sensors at the locations xi, yi, and zi, where Pages/NLDN.aspx). The ENTLN (http://earthnetworks. the subscript integer i indicates the station number. The com/OurNetworks/LightningNetwork.aspx) uses broad- sensors record the time of arrival ti of received VHF band sensors operating in the LF and high-frequency sources emitted from lightning at around 60–66 MHz (HF) bands between 1 kHz and 12 MHz (Liu and (Thomas et al. 2004). Lightning emits broadband radi- Heckman 2011). Similar to the NLDN, the ENTLN also ation; breakdown processes of IC and CG lightning detects and locates CG and IC lightning events based discharges such as negative leaders and streamers radi- on the time of arrival of their waveforms. The HF mea- ate strongly at VHF, making it possible to map IC and surements provide improved detection efficiency for IC CG lightning in great detail at this frequency band. As lightning. The USPLN (http://www.uspln.com/uspln. such, the LMA provides comprehensive measurements html) is also a time-of-arrival system using broadband of IC and CG lightning. In principle, if four or more sensors with a bandwidth from 1.5 to 450 kHz. Similarly, stations detect a source, the three-dimensional position the USPLN detects CG lightning and some IC x, y, and z, and time t of this source can be determined lightning events. using the system of equations defined by Thomas et al. All of these networks measure parts of lightning (2004): flashes (such as return strokes of CG flashes, etc.), which we will call lightning events. Each of the networks 2 5 2 2 1 2 2 1 2 2 1/2 classifies an event as a CG or IC part of a lightning flash, c(t ti) [(x xi) (y yi) (z zi) ] , and possibly what events belong to the flash. CONUS where c is the speed of light. Six or more stations are lightning data used in this study include the date, time, required to allow a VHF source to be counted as a de- polarity, signal strength, and type of a lightning event. tection. The source locations are retrieved using a least Flash information was also available from the NLDN DECEMBER 2015 K U M J I A N A N D D E I E R L I N G 1473

FIG. 1. Synoptic overview of each thundersnow case. The 500-hPa heights (dkm; gray curves) are overlaid by selected surface features including the 08C isotherm (dashed green curves), location of surface low pressure centers, and surface fronts. Analyses are adopted from the National Centers for Environmental Prediction/ Hydrometeorological Prediction Center (NCEP/HPC). Upper-air (surface) analyses are valid at (a) 0000 (0300) UTC 25 Oct 2012, (b) 0000 (0000) UTC 11 Nov 2012, (c) 0000 UTC 29 Jan (2100 UTC 28 Jan) 2013, and (d) 1200 (0700) UTC 9 Apr 2013. and ENTLN. We determined flashes from USPLN- for the Colorado Front Range and Palmer Divide (e.g., measured lightning events by applying the criteria de- Rasmussen et al. 1995; Kumjian et al. 2014; Schrom et al. scribed in Cummins et al. (1998). Note that the detection 2015), overlaid by larger-scale southwesterly flow aloft. efficiency, classification of IC and CG events, and flash The proximity of the upper-level trough would support determination can vary between the networks depend- large-scale ascent across the region, whereas topo- ing on factors such as network station density and the graphically forced ascent was likely for some events, as way detected lightning signals are processed. discussed below. Figure 2 shows the nearest soundings from each of the 3. The thundersnow events four cases. The lowest levels in the first three cases (Figs. 2a–c) exhibited temperatures .08C; however, a. Environment and overview of the cases strong cold advection associated with the frontal passage The synoptic conditions for each thundersnow case soon decreased temperatures throughout the atmo- reveal similarities (Fig. 1). On 11 November 2012, sphere to below 08C. For example, at 0000 UTC 28 January 2013, and 9 April 2013, a large-scale, posi- 25 October 2012, the surface temperature near Denver tively tilted 500-hPa trough was located to the west of was about 108C(Fig. 2a), whereas near Cheyenne it Colorado, over the Rocky Mountains. On 25 October was already below 218C (not shown). By 0200 UTC, 2012, the trough axis had just passed through Colorado Denver was reporting snow and a surface temperature and was lifting out. A ridge was located over the eastern of 0.58C (not shown). The soundings are quite consis- United States in all four cases. In each case, a surface low tent with those associated with thundersnow cases was located to the south or east of the COLMA domain, presented in previous studies (e.g., Curran and Pearson and a cold frontal passage had just occurred, providing 1971; Market et al. 2006, 2007), with a low-level in- surface temperatures very near 08C. The surface fea- version or stable layer overtopped with nearly pseu- tures provided northerly or northeasterly upslope flow doadiabatic lapse rates and small dewpoint depressions. 1474 WEATHER AND FORECASTING VOLUME 30

FIG. 2. Radiosonde measurements of temperature (blue curves) and dewpoint temperature (dashed orange curves) observed at (a) 0000 UTC 25 Oct 2012, (b) 0000 UTC 11 Nov 2012, (c) 0000 UTC 29 Jan 2013, and (d) 0820 UTC 9 Apr 2013. The data in (a)–(c) are from the operational soundings taken from DNR, whereas (d) shows a sounding taken from the Marshall Field Site near Boulder during the Front Range Orographic Storms experiment (; Kumjian et al. 2014).

In each of the soundings, layers of potential instability preferred location for lightning activity south of the (i.e., where the vertical gradient of equivalent potential LMA network, seemingly anchored to the terrain fea- temperature Due/Dz is negative) are found above the ture known as the Palmer Divide. The northerly or low-level stable region, also consistent with Market northeasterly upslope low-level flow in each case would et al. (2006). Typically, these layers were associated favor enhanced uplift at the Palmer Divide. This topo- with temperatures between 2138 and 2308C. Using graphically forced ascent could provide a focused lifting high-resolution soundings (cf. Fig. 2d), Kumjian et al. mechanism required to release the potential instability. (2014) found potential instability layers that were not In the absence of other lifting mechanisms, the Palmer observed by the nearby coarser operational soundings; Divide then could serve as a focus for convective initi- thus, it is plausible that the magnitude or depth of the ation and subsequent lightning activity. The presence of potential instability in these cases is underestimated by broader large-scale ascent associated with upper-level the operational soundings. troughs in each case could also have helped provide the The analysis domain is shown in Fig. 3. Locations of all lift necessary to release the potential instability. LMA sources from each case are overlaid, as are the Other features of note in Fig. 3 include linear tracks locations of the COLMA stations, the WSR-88Ds near of static discharges seen by the LMA that are produced KFTG and KCYS, and the National Weather Service by aircraft departing from or arriving at Denver Inter- Denver sounding site (DNR). One immediately sees a national Airport (i.e., LMA source locations increased or DECEMBER 2015 K U M J I A N A N D D E I E R L I N G 1475

produced 10 flashes over a period of about 30 min. In contrast, cells 2 and 4 only produced one flash, and cell 6 only produced two flashes. Six additional cells pro- duced lightning flashes over the next 5 h (not shown in Fig. 4), with most of these not producing more than four flashes in their lifetime. One short-lived cell (cell 9) was more active, producing 15 flashes within 15 min. An- other (cell 8) produced 19 flashes over about 90 min. The 11 November case (Fig. 4b) had the most electrically active storm of the dataset, with 28 flashes observed over about 1 h. Two cells produced flashes on 28 January (Fig. 4c), and one produced five flashes in about 10 min on FIG. 3. Map of the terrain (m MSL; shaded according to scale) in 9 April 2013 (Fig. 4d). the study domain. Locations of the operational sounding site Flash characteristics from each case are summarized (DNR; square green marker) and WSR-88Ds (KFTG and KCYS; red triangle markers) are shown. Colorado LMA stations are in Table 1. The total number of flashes was determined shown by circle black markers. Pink dots represent LMA sources by accumulating lightning data from all networks and for 25 Oct 2012, cyan dots represent source points for 11 Nov 2012, matching them in space (within 1–2 km) and time blue dots represent source points for 28 Jan 2013, and goldenrod (within 1 ms, the temporal resolution of CONUS net- dots represent source points for 9 Apr 2013. work data). IC and CG events were determined based on the available data, including CONUS network decreased in altitude at rates typical of commercial air- classifications (e.g., Cummins et al. 1998)andinter- craft ascent and descent rates). The LMA observes VHF pretation of 3D LMA data (e.g., Thomas et al. 2003). sources from sparks caused by planes that get charged The maximum flash rate (based on total flashes) in any (through collisional charging of the aircraft’s fuselage 10-min period is also provided. Four cases produced with ice particles) when flying through ice clouds (e.g., more CG flashes than IC flashes, though one of these Thomas et al. 2004). For the subsequent analyses, these cases (cell 1, 25 October 2012) was at the edge of the points were removed based on their linear spatial pattern LMA detection range,1 and thus not all flashes may and temporal continuity. Thus, in the event of a real flash have been detected. Another flash (cell 2, 25 October in the spatial and temporal proximity of an aircraft 2012) likely was tower initiated, as discussed further in track, a small number of real source points may be re- section 4b. Otherwise, the majority of the cases pro- moved and/or a small number of aircraft sources may be duced more IC than CG lightning. Interestingly, for retained, but this was not found to be an important issue most cases the three CONUS networks exhibited var- for these cases. iability in the number, type, and polarity of flashes detected, owing to differences in their design and per- b. Lightning analysis and charge structures formance, especially for cells with high IC-to-CG ra- LMA sources and CONUS data were used to de- tios. Note that there are ambiguities in deciding if termine the number of IC and CG lightning events for flashes were IC or CG events based on the LMA data, each case. To filter out noise, LMA VHF sources were particularly for flashes that initiate and progress very kept only if they were detected by a minimum of seven close to the ground and thus are limited by the line-of- LMA stations, had altitudes ,15 km, and had x2 , 2:0. sight restrictions of the LMA detections. Therefore, we Flashes were determined manually from VHF sources caution that these flash-type classifications contain following Deierling et al. (2008), using visualization uncertainty. software from NMIMT with the aid of their inbuilt flash Flash rates were determined from a 10-min moving algorithm (Thomas et al. 2003). The LMA data were window throughout each cell’s lifetime. The maximum also overlaid on composite ZH imagery from the KCYS flash rate in any 10-min window throughout a cell’s and KFTG radars. Localized enhancements of ZH as- lifetime is shown in Table 1. Most cells had maximum 2 sociated with lightning flashes (hereafter cells) were flash rates ,1.0 min 1; the maximum flash rate for all subjectively identified and tracked through their dis- events was from the 11 November 2012 cell, but was only cernible lifetimes. Time series of the flash counts determined by the LMA and CONUS networks for each case are shown in 1 The farther distance from the LMA network also explains why Fig. 4. In the first 80 min on 25 October, six different cells cells 1 and 8 on 25 Oct 2012 had strokes detected by the CONUS produced flashes (Fig. 4a), including one (cell 1) that networks but not the LMA. 1476 WEATHER AND FORECASTING VOLUME 30

FIG. 4. Time series of flash counts for each case: (a) 25 Oct 2012, (b) 11 Nov 2012, (c) 28 Jan 2013, and (d) 9 Apr 2013. The same horizontal and vertical axis ranges are used to facilitate comparison. Multiple cells during one event are shown in different color lines.

2 1.3 min 1. Compared to flash rates in warm-season shown in Fig. 5. The heights of the charge regions varied thunderstorms (e.g., Williams et al. 2005; Deierling by case, occurring anywhere between 2 and 10 km AGL. et al. 2008), flash rates in these thundersnow cases were Manual flash-by-flash analysis allows us to infer charge much lower, exemplifying the more marginal nature of regions based on the propagation of LMA-detected these storms. Fuchs et al. (2015) determined that 0-dBZ VHF sources (e.g., Wiens et al. 2005). These analyses echo-top heights in Colorado summertime thunder- suggested that, in many of the cases, negative charge was storms varied between 12 and 18 km, whereas the located at lower altitudes and positive charge at higher thundersnow storm echo-top heights varied between 8 altitudes in these storms. This positive-over-negative and 12 km for most cases (and did not exceed 14 km). charge structure could be achieved if the faster-falling This suggests less vigorous upward motion than warm- riming particles (e.g., graupel or rimed aggregates) season convection in this region. In addition, observed gained negative charge in these storms at temperatures temperature profiles suggest no warm-cloud (.08C) ,08C and intermediate values of SLW (e.g., Saunders depth associated with these storms. These environ- and Peck 1998; Takahashi and Miyawaki 2002). Similar mental factors are consistent with the observed lower processes contribute to cloud electrification in warm- flash rates (e.g., Williams et al. 2005; Fuchs et al. 2015). season thunderstorms; however, warm-season storms The charge structure of these cells was also examined. often appear to be dynamically more vigorous than As such, the vertical distribution of LMA sources is these thundersnow events (i.e., greater updraft velocities DECEMBER 2015 K U M J I A N A N D D E I E R L I N G 1477

TABLE 1. Summary of thundersnow storms and their flash characteristics. The date of each event is in the left column, followed by the cell number for each date, the total number of flashes, the numbers of IC and CG flashes, the number of those flashes detected by the LMA, the range (from min to max) of the number of flashes detected by the any of the three CONUS networks, and the max flash rate (flashes per minute) within a 10-min window.

Total IC (CG) LMA CONUS Max flash rate in 2 Date Cell No. flashes flashes detections detections 10-min window (min 1) 25 Oct 2012 1 10 3 (7) 6 4–10 0.4 25 Oct 2012 2 1 0 (1) 1 0 0.1 25 Oct 2012 3 4 3 (1) 4 0–4 0.5 25 Oct 2012 4 1 1 (0) 1 0 0.1 25 Oct 2012 5 9 5 (4) 9 1–5 0.6 25 Oct 2012 6 2 2 (0) 2 0–1 0.2 25 Oct 2012 7 1 1 (0) 1 1 0.1 25 Oct 2012 8 19 14 (5) 18 2–12 0.5 25 Oct 2012 9 15 12 (3) 15 2–8 1.2 25 Oct 2012 10 3 2 (1) 3 1–2 0.3 25 Oct 2012 11 4 4 (0) 4 2–3 0.4 25 Oct 2012 12 1 1 (0) 1 0–1 0.1 11 Nov 2012 1 28 17 (11) 28 3–8 1.3 28 Jan 2013 1 1 1 (0) 1 0 0.1 28 Jan 2013 2 3 1 (2) 3 1–2 0.2 9 Apr 2013 1 5 2 (3) 5 0–4 0.5

leading to higher echo-top heights). We caution that the flash is detected by the LMA (VHF sources indicated by flashes did not always reveal such a simple charge the black markers in Fig. 6d). A strikingly similar evo- structure, and longer-lived events exhibited evolving lution is observed for the 28 January case (Fig. 7). structures throughout their lifetimes. Thus, it is difficult Again, the echo is dominated by dry snow aggregates to make any broad generalizations about the charge initially (Fig. 7a). By the 2131:03 UTC scan (Fig. 7b), a structure of thundersnow storms without a much larger few contiguous pixels of graupel are identified. This dataset. region expands considerably in the next two scans (Figs. 7c,d). The first LMA sources occurred shortly 4. Radar analysis after 2142 UTC (Fig. 7d). Such a rapid appearance and expansion of graupel a. Evolution of HCA fields identifications in both cases is suggestive of convective The upgraded WSR-88D network employs a hydro- activity and considerable ongoing riming within a region meteor classification algorithm (Park et al. 2009) that of snow aggregates and ice crystals, which are precursors categorizes each radar pixel as 1 of 10 possible classes. In to electrification. In most of the cases, the operational this section, we show illustrative examples of the HCA HCA output classified regions of graupel prior to the evolution for two cases: 11 November and 28 January (a first LMA-indicated flash. Most often this change in similar evolution was observed for cells on 25 October classification from snow aggregates to graupel is related and for 9 April; for brevity these are not shown). to the increase in ZH values over those expected for dry Figure 6 provides the evolution of the HCA output at snow aggregates; in other words, more weight is assigned

2.48 elevation using volume scans from 2350 UTC to the graupel category as ZH increases to over 35– 10 November through 0007 UTC 11 November 2012, 40 dBZ. collected by the KFTG WSR-88D. Initially, mainly dry From an operational perspective, it appears that a snow aggregates are classified in the echo to the sudden appearance or expansion in the areas classified southwest of the radar (Fig. 6a, centered at about as graupel should warrant more attention, as conditions x 5235 km, y 5225 km, where the origin of the co- are favorable for the development of electrification and ordinate system is the KFTG radar). By 2356 UTC, a possible lightning initiation, as well as potentially heavy small area of graupel is identified (Fig. 6b,markedby snowfall. Crowe et al. (2006) explore correlations be- the arrow). This HCA-indicated graupel region ex- tween heavy snowfall and thundersnow occurrences pands in areal extent in the next two volume scans, more using METAR. They report that, if a storm is capable than doubling the number of graupel-identified pixels of producing thundersnow, then there is an enhanced (Figs. 6c,d). By the end of the 0007 UTC volume scan, a likelihood of that system producing heavy snow 1478 WEATHER AND FORECASTING VOLUME 30

FIG. 5. LMA source frequency binned by altitude (m MSL) for each case: (a) 25 Oct 2012, (b) 11 Nov 2012, (c) 28 Jan 2013, and (d) 9 Apr 2013. LMA sources are thresholded by altitude and x2 , 2. Aircraft tracks have been subjectively identified and removed. accumulations. The areal expansion of graupel de- 11 November case is investigated in more detail in sec- scribed above for two of the thundersnow events tion 4c below. It is likely that ongoing riming and implies a larger region of enhanced ZH values, which charging was occurring in these cells. However, the generally suggest larger surface precipitation rates. charging apparently was not sufficient to induce a Further, riming adds mass to hydrometeors and in- lightning discharge. creases their fall speeds, also increasing the ice mass flux In addition to such null cases (i.e., HCA-identified to the surface. Given that the lightning-producing cells graupel but no lightning), there was one flash on 25 Octo- tended to have larger ZH (and subsequently larger pre- ber 2012 that occurred in the absence of HCA-identified cipitation rates) than the other cells that did not produce graupel. In fact, the flash occurred in a snowband that did lightning, the association between enhanced pre- not exhibit the typical convective appearance of the other cipitation rates and thundersnow supports the findings lightning-producing cells. However, as discussed in detail in of Crowe et al. (2006). the next subsection, this case did exhibit a polarimetric However, the appearance of HCA-identified graupel signature that could have provided forecasters with in- itself is not a necessary or sufficient condition for light- formation about electrification in the cloud. ning in the thundersnow cases presented herein. For b. 25 October 2012 depolarization streak example, in at least two of the cases (25 October and 11 November) there were other cells in which graupel Here, we present data from the 25 October 2012 case, was identified that did not produce lightning. The in which a snowband produced a flash (the northernmost DECEMBER 2015 K U M J I A N A N D D E I E R L I N G 1479

FIG. 6. Output of the operational HCA at (a) 2350 UTC 10 Nov, (b) 2356 UTC 10 Nov, (c) 0002 UTC 11 Nov, and (d) 0007 UTC 11 Nov 2012. Data are collected at the 2.48-elevation scan. LMA sources that occurred within the volume scan time are indicated as small black triangle markers. The arrow indicates the eruption of HCA-indicated graupel.

 flash in Fig. 3) in the absence of any obvious convective negative ZDR (e.g., Scott et al. 2001; Ryzhkov and Zrnic structure in the radar data. Despite not having a clear 2007; Hubbert et al. 2010; Kumjian 2013c). Such a de- convective structure apparent in the radar data or large polarization streak is evident in the 0.928-elevation scan

ZH values (.35 dBZ) that could be indicative of graupel of ZDR from KCYS at 0035 UTC (Fig. 9b), about 3– (Fig. 8a), nor any areas of graupel identified in the HCA 4 min prior to the flash (Fig. 9c). Note that it is exceed- output (Fig. 8b), the 25 October snowband case did ingly unlikely for the negative ZDR streaks to be caused exhibit a polarimetric radar signature indicative of by differential attenuation in this case, as (i) the pre- electrification, beginning at least one volume scan pre- cipitation was entirely snow at this time; (ii) the WSR- ceding the CG flash. Strong electric fields in clouds can 88D operates at S band, at which specific differential alter the orientation of small ice crystals (e.g., Caylor attenuation for snow is negligibly small owing to the very and Chandrasekar 1996; Ryzhkov and Zrnic 2007). The small relative permittivity of ice particles; and (iii) max- cloud was sufficiently strongly electrified that these low- imum ZH values are rather low, indicating a lack of very inertia ice crystals were oriented at angles off the prin- large sizes or concentrations of particles necessary to cipal polarization plane axes (i.e., not 08 or 908). Radars produce attenuation at S band. The streak also moves in that operate in a mode of simultaneous transmission and time (cf. Fig. 9), indicating that it is not caused by some reception of horizontally H and vertically V polarized sort of partial beam blockage by a ground-based target. waves (such as the WSR-88Ds) produce an artifact when Figure 10 provides an average of radial traces of ZH, the beam propagates through canted ice crystals. The ZDR,andFDP through the depolarization streak at canted media lead to depolarization of the signal, re- 0039 UTC. [Note that FDP is not currently displayed in the sulting in radially oriented streaks of positive or National Weather Service Advanced Weather Interactive 1480 WEATHER AND FORECASTING VOLUME 30

FIG.7.AsinFig. 6, but for HCA at (a) 2124, (b) 2131, (c) 2135, and (d) 2140 UTC 28 Jan 2013.

Processing System (AWIPS) software but is available in (not shown). The decrease in FDP suggests the presence of archived level-II data.] Between range bins 100 and 175, nonspherical particles with their maximum dimensions both ZH and FDP increase, whereas ZDR is relatively low projected more in the vertical plane than the horizontal but positive. This suggests particles are getting larger with plane. Such an alignment is possible for conical graupel or increasing range, presumably larger aggregates and/or small ice crystals aligned in an electric field. However, the small graupel with intrinsically low ZDR.IncreasingFDP fact that ZDR begins to decrease monotonically with range indicates more pristine, nonspherical particles are present here suggests depolarization, which favors oriented ice as well because fluffy snow aggregates or graupel largely crystals that are not perfectly vertically (or horizontally) are invisible to FDP. Thus, the combination of each po- oriented. The increase in FDP farther downrange (range larimetric variable provides information about a mixture bins .250) suggests crystals with a more horizontal ori- of particles being present simultaneously in the cloud. In- entation (e.g., Ryzhkov and Zrnic 2007). Interestingly, the teractions among these different hydrometeors is one of depolarization streaks persisted for another ;15 min after the possible mechanisms thought to play a role in charging the flash (cf. Figs. 9d–f), indicating that the cloud was still (e.g., Pruppacher and Klett 1997; MacGorman and Rust electrified, albeit insufficiently for a lightning discharge. 1998; Rakov and Uman 2003). Recent work (e.g., Dye This example demonstrates that depolarization streaks in et al. 2007; Dye and Willett 2007; Kuhlman et al. 2009; ZDR can be useful indicators of electrification, though they Tsenova et al. 2014) has also suggested that charging can do not necessarily indicate that a lightning strike is im- occur in the absence of graupel or supercooled cloud minent. Note that many of the other cases of lightning- droplets through ice–ice interactions, and could plausibly producing thundersnow storms in our study were isolated explain the electrification in this case. cells, so there was a general lack of downrange echoes in

Notably, FDP values decrease from range bins 175 to which to observe any depolarization streaks. 250 along the depolarization streak, whereas adjacent The vertical structure of the storms can also be in- azimuths featured monotonic increases in FDP with range formative. A vertical cross section along the azimuth DECEMBER 2015 K U M J I A N A N D D E I E R L I N G 1481

the LMA at this range, it is plausible that this flash was triggered by a man-made object. This would explain the isolated nature of this flash, as well as the seeming lack of a convective appearance in the radar data. Man-made objects such as towers can serve to locally enhance the electric field, possibly to a level sufficient to cause a discharge. In fact, Rakov and Uman (2003) suggest that the large horizontal extent of low-level charge regions common in winter storms favor lightning triggered by such towers. Similar observations of flashes in the absence of notable convective structures were made by Bech et al. (2013) in a thundersnow case over Catalonia, Spain. Those authors hypothesized the importance of tall telecommunication towers in leading to CG lightning flashes. Tower-initiated flashes have also been observed in northern Alabama winter cases (C. Schultz 2014, personal communication) and over tall buildings in Chicago, Illinois (Warner et al. 2014). Thus, tall towers may be sufficient to produce a dis- charge in otherwise submarginal conditions for thundersnow. c. 10–11 November 2012: A tale of two cells During 10–11 November 2012, there were numer-

ous isolated convective cells that produced ZH values .35 dBZ, suggestive of graupel. However, only one of these cells produced lightning flashes. FIG. 8. The 0.58 PPI scan from KCYS at 0039 UTC, showing To investigate any possible microphysical differ- (a) ZH and (b) HCA output for the stratiform flash case. LMA ences between the cell that produced lightning and sources are indicated by triangle markers, as in the previous figures. those that did not, we compare the polarimetric ra- Note modified color scale for ZH: max values only barely exceed 30 dBZ. dar variables ZH, ZDR,andKDP within two con- trasting cells: the lightning-producing cell between 0002 and 0106 UTC 11 November, and a cell between nearest to the flash (Fig. 11) shows enhanced vertical 2112 and 2211 UTC 10 November 2012. In both cases, structure in ZH centered at a range of about 90 km, co- the operational HCA output indicated graupel, sug- incident with the location of the flash. Though ZH values gesting ongoing riming within the cells. Additionally, in this area remain ,30 dBZ throughout, its vertically large (up to 5-mm diameter) conical graupel was ob- extensive structure is suggestive of enhanced vertical served in the earlier cell near Boulder, Colorado motion. This is supported by weak midlevel conver- (Fig. 13). Both cells existed in similar environments gence that is present in the Doppler velocity field (the same region and within ;4 h of one another),

(not shown). produced ZH . 40 dBZ and graupel, lasted for ex- Figure 12 reveals the three-dimensional structure of tended periods (.1h),andremainedwithinsimilar the 0039 UTC CG flash and its evolution. The LMA ranges of the radar. However, only the later cell pro- sources indicate the flash initiated below 2 km MSL duced lightning flashes. For these reasons, these two (within a few hundred meters above ground level) and cells offer a good opportunity to look for subtle dif- progressed southward. The second part of the flash is ferences in their microphysical characteristics. We will accompanied by an upward-moving leader to the north hereafter refer to the lightning-producing cell as the again, which also initiates very close to the ground. The active cell, and the cell that lacked lightning as the initial low-level sources (gray markers, near the ground) inactive cell. are within 1–2 km of several wind turbines and a com- To facilitate a comparison, data from sampling munications tower as observed on Google satellite im- volumes subjectively identified as being associated agery. Given the uncertainty in VHF source positions by with each cell are selected. The data from the PPI 1482 WEATHER AND FORECASTING VOLUME 30

FIG. 9. Consecutive fields of ZDR from the 0.928 PPI scan at (a) 0031, (b) 0035, (c) 0039, (d) 0043, (e) 0048, and (f) 0052 UTC 25 Oct 2012. The red arrow points to the location of the observed depolarization streaks. The pink markers show LMA sources from the flash that occurred at 0039:01 UTC.

21 21 sweeps in which the cell is observable are used. At 28 km in 0.258 km increments for KDP.Thefre- each volume scan time, the data are binned as follows: quency distribution is normalized by the maximum from 0 to 50 dBZ in 2-dB increments for ZH,from21 frequency at each time such that the peak for each to 5 dB in 0.5-dB increments for ZDR,andfrom218 to time is equal to one. DECEMBER 2015 K U M J I A N A N D D E I E R L I N G 1483

in the active cell compared to the inactive cell. These observations all point to better particle growth conditions within the active cell, which may include more favorable vertical velocities, higher liquid water contents, more ice mass, or some combination of these factors.

The distributions of ZDR in both cells reveal a peak at about 0 dB throughout the 1-h time period chosen for analysis. Note that the base-10 logarithm of the frequency distribution is plotted in Fig. 14 in order to bring out subtle changes in the distributions’ tails. Subtle increases in the

frequency of high-ZDR volumes are observed between 0010–0030 and 0040–0050 UTC in the active cell. How- ever, in general, the inactive cell produces relatively more

high-ZDR volumes. This may be a result of the higher-ZH values in the active cell: more reflective graupel with in-

trinsically lower ZDR could dominate the backscatter, weighting ZDR more heavily than in the inactive cell.

FIG. 10. Traces of azimuthally averaged profiles of ZH (blue), The distributions of KDP, however, are not weighted ZDR (red), and FDP (black) through the depolarization streaks at by reflectivity, only responding to the anisotropic scat- 0039 UTC 25 Oct 2012. Note that ZH is divided by 10 for display terers within the sampling volume. In winter storms, this purposes. means the KDP will provide a measure of the mass content of more pristine crystals (e.g., Ryzhkov et al. The results are shown in Fig. 14. The active cell is 1998; Kennedy and Rutledge 2011; Andric et al. 2013; shown in Fig. 14 (left), with asterisks above indicative of Schrom et al. 2015). The normalized KDP distribution in minutes in which lightning occurred. Note the jump in the active cell has an enhanced tail at the second volume relative frequency of the larger ZH points (.30 dBZ)at scan, just prior to the onset of the first flashes. This is the second volume scan. This increase in ZH occurs prior followed by a weaker enhancement that persists for the to the first flashes in this case. Compared to the inactive second half of the analysis period. In contrast, the in- cell, the active cell has very similar peaks in the nor- active cell features very few higher-KDP volumes, par- malized frequency distribution. However, the active cell ticularly after the first few volume scans. (In fact, has a much broader tail, with larger relative contribu- throughout most of the analysis period, there are no 21 tions from ZH . 40 dBZ. (Indeed, the maximum ZH in volumes with KDP . 0.58 km .) This strongly suggests the active cell exceeded 50 dBZ.) This may suggest the that the inactive cell contained less pristine ice mass presence of more, larger, and/or higher-density graupel than did the active cell. In other words, there were fewer

FIG. 11. Reconstructed RHI scan of ZH (dBZ; shaded according to scale) from constant- elevation angle PPI scans in the volume beginning at 0035 UTC 25 Oct 2012 from KCYS. The azimuth is 1088, corresponding to the location CG flash detected at 0039 UTC. The flash was located at a range of ;89 km from the radar. Note the vertically extensive region of enhanced ZH at this range. 1484 WEATHER AND FORECASTING VOLUME 30

FIG. 12. Multipanel view of LMA sources associated with the 0039 UTC 25 Oct 2012 stratiform flash: (a) time (s; past 0000 UTC) vs height (m MSL), (b) lon (8) vs height (m MSL), (c) lon (8) vs lat (8) underlaid with a map, and (d) height (m MSL) vs lat (8). The color of the markers indicates the time of the source, binned into every 0.1 s starting at 2340:40 UTC, as indicated in the legend above (d). and/or smaller pristine ice crystals in the inactive cell inactive cell. Taken together, this indicates that the compared to the active cell. active cell had larger, more numerous, and/or higher- In summary, the active cell had a broader distribution density graupel as well as a larger mass content of pris- of ZH values, including more high-ZH (.40 dBZ) vol- tine ice crystals than the inactive cell. This suggests that umes than did the inactive cell. Additionally, there were there may be observable microphysical differences be- more high-KDP volumes in the active cell than the tween cells that produce lightning and those that do not DECEMBER 2015 K U M J I A N A N D D E I E R L I N G 1485

are found during a period of heightened lightning ac- tivity. The increased ice mass is consistent with the

larger KDP values observed in this case. We performed a similar comparison between the two cells using the level-III product called the enhanced echo-top height (not shown). There were no significant differences between the two cells, highlighting their similarity in storm depth. This also could mean that the vertical resolution of the WSR-88D volume scan is in- sufficient to observe such subtle differences. These analyses offer promising clues of subtle differ- ences between otherwise similar convective cells. However, a much larger dataset is required to determine the robustness of these radar-observed differences. Compositing or averaging over a large number of storms FIG. 13. Conical graupel particle observed near Boulder at may help reveal reliable bulk microphysical differences 2201 UTC 10 Nov 2012. The largest graupel particles observed at this time approached 5 mm in diameter at their base. between convective snowstorms that produce lightning and those that do not. in similar environments. Obviously, more cases are 5. Discussion and conclusions needed to determine the reliability of these subtle sig- The four thundersnow events presented in this study nals, as this analysis only considers two cells. Addition- display common features in their synoptic-scale setting, ally, the inactive cell was somewhat farther from KFTG thermodynamic environment, radar presentation, and than the active cell throughout the analysis period, so electrical properties. Each case featured a large-scale the sampling volumes were somewhat larger. environment conducive for ascent, with low-level me- Because the mixture of graupel and pristine ice is a soscale features that provided upslope flow. In particu- key ingredient for electrification, the combined use of lar, the Palmer Divide was found to be a preferred Z and K offers some promise in quantifying this H DP location for electrically active snowstorms in Colorado. mixture. Use of C- or X-band polarimetric radars will be In each case, the surface temperature was just under 08C. especially helpful, as K is inversely proportional to DP With regard to the questions asked in the in- radar wavelength for hydrometeors like pristine ice troduction, we come to the following conclusions: crystals that are in the Rayleigh scattering regime. Thus, subtle differences in KDP will be more easily distin- (i) In general, lightning from the four thundersnow guishable with higher-frequency radars. days was detected by both the CONUS and LMA In addition to the polarimetric radar variables, other networks. Of the six cells without CG flashes, the investigators have explored the use of radar-derived CONUS network detected IC flashes in four of products for the detection of storms capable of pro- them. The two cases that were not detected by the ducing lightning. Figure 15 shows two of these products: CONUS network were only weakly electrically volume averaged height-integrated radar reflectivity active, producing only one in-cloud flash. The (VAHIRR; Krider et al. 2006) and a proxy for ice mass LMA detected flashes in all 16 cells, though indi- (e.g., Carey and Rutledge 2000; Mosier et al. 2011). vidual flashes were missed when the cells were at These are products derived from gridded radar volume the edge of the network’s detectability. The rela- scans that have been used in previous lightning fore- tively prolific number of thundersnow storms in the casting studies. One should not ascribe too much im- 2012/13 snow season in northern Colorado strongly portance to individual values, but rather the relative suggests that thundersnow is more common than differences in the two cases are what is important. previously reported in published climatologies that VAHIRR values in the active cell are larger than those used different datasets (i.e., no combination of of the inactive cell, which do not exceed ;25 dBZ km. LMA and CONUS networks). LMA networks The most striking contrast is found in ice mass, however. allow for the detection of marginal events with a Whereas the ice mass in the inactive cell does not exceed single or a few IC flashes that generally do not get 2 2 about 3.5 g m 3, values .4gm 3 are consistently found detected as efficiently by CONUS networks. Fu- in the active cell throughout the period in which it is ture research should investigate other LMA net- 2 producing lightning. In fact, values in excess of 8 g m 3 works in different parts of the world to verify if, in 1486 WEATHER AND FORECASTING VOLUME 30

FIG. 14. Normalized frequency distributions of (a),(b) ZH; (c),(d) ZDR; and (e),(f) KDP for two graupel-producing cells on 10–11 Nov 2012. (left) The lightning-producing cell (active) from 0002 to 0106 UTC 11 Nov, and (right) a cell that did not produce lightning (inactive) from 2112 to 2211 UTC 10 Nov 2012. Note that the base-10 logarithm of the frequency distribution is shown for ZDR and KDP. The asterisks (left) indicate minutes in which a flash was observed by the LMA.

fact, thundersnow events indeed are more common degree of riming cannot be ruled out, noninductive than previously thought. charging may have still contributed to the pro- (ii) Many of the flash events were associated with duction of a strong enough electric field that

localized high-ZH, low-ZDR regions (i.e., presum- allowed for triggered lightning without the pres- ably convective regions and graupel production). ence (or very low concentrations) of supercooled The sudden appearance and expansion of radar liquid water (e.g., Dye et al. 2007; Dye and Willett gates classified as graupel preceded most of the 2007). As expected, this rarer and more puzzling flashes in these cells. Thus, such a signature in the case was isolated. Presumably, the electric field operational HCA should warrant more attention was stronger in the more vigorous convective for the possibility of lightning production, aviation elements during the same event. Despite being hazards, and heavy snowfall. only weakly electrified, though, the polarimetric In contrast, we documented an isolated flash in radar data did display a depolarization streak regions of presumably snow aggregates. It is clear signature prior to the lightning flash. Thus, the why regions of radar-inferred graupel production presence of depolarization streaks in winter storms would be favorable for electrification and possible should alert forecasters that electric fields are lightning initiation; however, isolated flashes in sufficiently strong to affect the orientation of ice

snowbands are more puzzling. Maximum ZH crystals (though we emphasize that by itself this values did not much exceed 30 dBZ. Though some signature does not guarantee that a lightning flash DECEMBER 2015 K U M J I A N A N D D E I E R L I N G 1487

23 FIG. 15. As in Fig. 14, but for derived quantities of (top) VAHIRR (dBZ km) and (bottom) ice mass (g m ). The ice mass frequency distributions are shown in logarithmic scale.

is imminent). As described above, such strong flashes per minute, the thundersnow events studied 2 electrification can pose aviation hazards, such as herein had much lower flash rates (often ,1 min 1). aircraft- or helicopter-triggered lightning (e.g., This is not surprising given the lower-CAPE envi- Mäkelä et al. 2013; Wilkinson et al. 2013). ronments (and thus weaker maximum updraft Additionally, there were instances of graupel velocities and cloud vertical extent). Flash-by- detected in the operational HCA in cells in which flash analysis based on LMA data suggests negative there was an absence of lightning. It is likely that charge below an upper positive charge region in charging was ongoing, just insufficient in magni- many of the cases. This is very similar to weakly tude for a lightning discharge. A comparison of electrified warm-season thunderstorm structures such an inactive cell with a similar lightning- with intermediate amounts of supercooled liquid producing (active) cell from 11 November 2012 water. Thus, we suggest that thundersnow storms revealed subtle microphysical differences, with the often are simply at the weaker end of the spectrum

inactive cell having lower ZH values and no of ordinary thunderstorms, with an absence of enhanced KDP values compared to the active cell. any .08C temperatures in the lower troposphere. In addition, the active cell had somewhat larger VAHIRR values and significantly larger ice mass Aside from being simply a meteorological curiosity, values than the inactive cell. Enhanced echo tops thundersnow events are scientifically advantageous to showed no discernible differences between the study because of their marginal nature. Electrification two cases. and lightning in deep moist convection are virtually (iii) Compared to typical warm-season convective guaranteed in most midlatitude continental storms, storms that may have from several to hundreds of whereas thundersnow events are much more marginal. 1488 WEATHER AND FORECASTING VOLUME 30

If some electrification threshold exists that may dis- Cummins, K. L., and M. J. Murphy, 2009: An overview of lightning tinguish lightning-producing storms from those that do locating systems: History, techniques and data uses, with an in- not produce lightning, thundersnow storms are cer- depth look at the U.S. NLDN. IEEE Trans. Electromagn. Compat., 51, 499–518, doi:10.1109/TEMC.2009.2023450. tainly closer to that threshold than most deep moist ——, ——, E. A. Bardo, W. L. Hiscox, R. B. Pyle, and A. E. Pifer, convective storms. Electric field measurements inside 1998: A combined TOA/MDF technology upgrade of the U.S. thundersnow clouds may help better define this National Lightning Detection Network. J. Geophys. Res., 103, threshold, if it exists. 9035–9044, doi:10.1029/98JD00153. Curran, J. T., and A. D. Pearson, 1971: Proximity soundings for thunderstorms with snow. Preprints, Seventh Conf. on Severe Acknowledgments. The National Center for Atmo- Local Storms, Kansas City, MO, Amer. Meteor. Soc., 118–119. spheric Research (NCAR) is sponsored by the National Deierling, W., W. A. Petersen, J. Latham, S. Ellis, and H. J. Science Foundation (NSF). Funding for the first author Christian, 2008: The relationship between lightning activity comes from NSF Grant AGS-1143948. Partial support and ice fluxes in thunderstorms. J. Geophys. Res., 113, D15210, for the first author came from the NCAR Advanced doi:10.1029/2007JD009700. Doviak, R. J., and D. S. Zrnic, 1993: Doppler Radar and Weather Study Program. We thank Jim Dye and Matthias Steiner Observations. 2d ed. Academic Press, 562 pp. (NCAR) for valuable discussions on this research, and Dye, J. E., and J. C. Willett, 2007: Observed enhancement of re- Paul Krehbiel and Bill Rison (New Mexico Institute of flectivity and the electric field in long-lived Florida anvils. Mining and Technology) for the Colorado LMA light- Mon. Wea. Rev., 135, 3362–3380, doi:10.1175/MWR3484.1. ning data. 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