1. Introduction
A complex winter precipitation event occurred on 8–9 March 1994 in Oklahoma and neighboring states. Snow accumulations greater than 30 cm (12 in.) were measured within a ∼50-km-wide corridor in northern Oklahoma, within which smaller pockets of accumulations in excess of 35 cm (14 in.) were measured (Fig. 1). The late-season snowfall created hazardous road conditions throughout Oklahoma, resulting in hundreds of traffic accidents and two fatalities [according to Storm Data (NOAA 1994)]. South of the heaviest snowfall, convective cells produced mixed-phase precipitation, strong surface winds, and significant cloud-to-ground lightning: approximately 10 000 cloud-to-ground flashes were recorded by the National Lightning Detection Network [NLDN; see Cummins et al. (1995) and Orville (1994)] on 8 March in Oklahoma.
A unique set of data was collected on the variety of winter precipitation observed on this day using the Cimarron polarimetric radar (CIM), operated by the National Severe Storms Laboratory (NSSL). As discussed recently by Zrnic and Ryzhkov (1999), polarimetric radar signals have a proven advantage over those of unpolarized radars in terms of hydrometeor classification and quantitative precipitation estimation (QPE). Polarimetric radar data have been used successfully in diagnostic studies of convective phenomena such as severe hail storms (e.g., Bringi et al. 1986a,b; Conway and Zrnic 1993), lightning-producing storms (e.g., Carey and Rutledge 1996; Lopez and Aubangac 1997), and mesoscale convective systems (e.g., Zrnic et al. 1993; Ryzhkov and Zrnic 1994), and also have been used to improve QPE (e.g., Ryzhkov and Zrnic 1995). The purpose of our study is to explore the use of these data in the investigation of the precipitation processes within and structure of a few prominent storm-scale features embedded within the much broader area of winter precipitation; generally speaking, our analyses are among the first to provide even a cursory examination of the detailed organization of such features. We also take advantage of the proximity of the precipitation to the dual-Doppler lobes formed by the Twin Lakes, Oklahoma, WSR-88D (KTLX) and the Cimarron radar:dual-Doppler retrieval of 3D wind fields affords a novel evaluation of the kinematics of the small-scale winter precipitation structures.
Conventional data are analyzed on the synoptic scale and mesoscale to provide a context for the storm-scale analysis and to determine the process(es) that led to heavy snow accumulation in a narrow band. Processes considered include frontogenesis forcing and secondary circulations associated with coupled polar and subtropical jet streaks, as explored by McCammon (1996) for the present case and as identified in studies of other significant snowfall events in the U.S. Great Plains (e.g., Hakim and Uccellini 1992; Marwitz and Toth 1993). Slantwise convective motions owing to the release of conditional symmetric instability (CSI) also are often used to explain bands of heavy snowfall (see Schultz and Schumacher 1999).
The paper is organized as follows. We examine in section 2 the synoptic scale and mesoscale, and show that the vertical circulation associated with active frontogenesis aloft is responsible for the mesoscale organization of the heavy snowfall over Oklahoma. Dual-polarization and dual-Doppler radar datasets are described briefly in section 3. These data are discussed first in section 4 to reveal the general structure and evolution of the precipitation on a broad scale and also to show attributes of polarimetric radar measurands within heavy snowfall. We then analyze in a generally qualitative manner the following smaller-scale features, in order of distance southward toward a surface cold front: an elevated convective element, embedded within a broad region of generally stratiform precipitation associated with the heavy snowfall (section 5); a reflectivity band that, at times, is associated with the rain–snow transition zone (section 6); and a long-lived, electrically active, yet nonelevated, convective cell (section 7). As appropriate, and respecting the limitations of the incomplete data, we provide explanations for each of these features and attempt to identify their respective contributions to the overall winter precipitation. Our conclusions are provided in section 8.
2. Synoptic and mesoscale analysis
The upper-tropospheric synoptic pattern over Oklahoma prior to the heavy precipitation event was characterized by a slowly moving closed low over the southwest United States. The center of this low moved from southern California at 0000 UTC 8 March 1994 (8/00; in this section, date and time will be abbreviated as day/hour) to the Arizona–New Mexico border at 8/12 (Fig. 2a). At this time, strong tropospheric deep confluence (formed by a ridge over trough pattern), acting both to support the surface anticyclone centered over Nebraska and to promote lower- and middle-tropospheric frontogenesis over the southern Plains, was centered over the central Plains with southwesterly flow aloft over Oklahoma. This frontogenesis can be seen at 600 hPa, where cool northwesterlies over Nebraska and Kansas are confluent with warmer southwesterlies over Oklahoma and Texas (Fig. 2b). By 9/00, the closed low opened up as it entered the confluence zone. The coupled upper-level jet pattern in this event (Fig. 2a) resembles that of a previous heavy snowband event analyzed by Hakim and Uccellini (1992).
At the surface, a broad 1005-hPa cyclone was situated over western Texas with a 1029-hPa high centered over Nebraska at 8/00 (not shown). A southwest–northeast-oriented front separated warm (20°–25°C) southeasterly flow over eastern Texas from cool (11°–14°C) northeasterly flow over Oklahoma. At this time, light rain in western Oklahoma and thunderstorms in west-central Texas were occurring.
At 8/12, the surface high intensified to 1031 hPa and moved equatorward to northern Kansas (Fig. 2c). Temperatures north of the frontal boundary had decreased by about 10° to 3°C in central Oklahoma. An east–west-oriented area of precipitation had developed 200–400 km north of the surface frontal boundary (Fig. 3a).
By 9/00, surface temperatures in western Oklahoma had fallen below freezing, while temperatures in southeastern Oklahoma remained above freezing (not shown). The broad region of precipitation north of the front was breaking up from the west (Fig. 3b) as the trough aloft moved toward the northeast (not shown). The frontal boundary had moved farther south into southern Texas.
The thermodynamic profile of the atmosphere south and north of the surface front is revealed by the 8/12 soundings at Stephenville, Texas (SEP), and Norman, Oklahoma (OUN), respectively (Fig. 4). South of the front, the SEP sounding had a shallow moist layer capped by a drier layer aloft; the convective available potential energy (CAPE) computed from this sounding was 21 J kg−1 (Fig. 4). Near the region of heaviest precipitation, the OUN sounding was stable below 750 hPa, the approximate height of the frontal surface, suggesting that convective motions must have been based above that height and hence have been “elevated” (Fig. 4). This point is further illustrated by a cross section across the frontal zone from the Eta Model 12-h forecast valid at 8/12 (Fig. 5a). Whereas CAPE calculated from parcels originating at 1000 hPa was substantial south of the front, a modest amount of CAPE calculated from parcels originating between 800 and 500 hPa existed above the frontal zone in the region of heaviest snowfall. The spatial distributions of surface- and 600-hPa-based CAPE supports the collocation of the snowfall and elevated CAPE, exceeding 100 J kg−1 (Fig. 5b).
In order to assess the forcing for the vertical motion responsible for heavy snow formation, adiabatic Lagrangian frontogenesis (Petterssen 1936) is calculated from the Eta Model initialized at 8/00. Frontogenesis at 600 hPa was north of the east–west-oriented zone of heaviest snowfall (Figs. 1 and 5), suggesting that precipitation formation processes were driven by upward vertical motion in the warm air above the northward-sloping frontal surface rather than at the surface frontal position farther south. This hypothesis is confirmed by computing the cross- and alongfront circulations using the methodology of Keyser et al. (1992) and Loughe et al. (1995). This methodology partitions the three-dimensional vertical circulation into two two-dimensional components, allowing an objective assessment of the extent to which a three-dimensional circulation is oriented in a preferred direction. An additional utility of this methodology is that the cross-front circulation corresponds to the frontal-scale circulation and the alongfront circulation corresponds to the synoptic-scale vertical motion (Keyser et al. 1992). At 8/12, the cross-front circulation shows the largest ascent above the frontal zone in a region of conditional instability (Fig. 6a), whereas the alongfront circulation shows much weaker ascent (Fig. 6b) due to the larger-scale flow. Thus, the mesoscale environment for the snowfall was characterized by ascent due to frontal forcing in a region of elevated conditional instability and CAPE.
3. Radar dataset description and analysis methodology
Our focus in sections 4–7 is on dual-polarization and dual-Doppler radar data and how these data relate to National Weather Service (NWS) surface reports, NLDN data, and to the larger-scale atmospheric structure. Pertinent information about the radar data and analysis methodology thus is provided in this section. The Cimarron 10-cm wavelength radar system is described in Zahrai and Zrnic (1993).
Polarimetric radar measurands1 and their meteorological applications have been reviewed recently by Zrnic and Ryzhkov (1999). The measurands used in this study are differential reflectivity (ZDR), specific differential phase (KDP), and correlation coefficient (ρHV); radar reflectivity factor (at horizontal polarization; ZH) is also used. As discussed in detail by Doviak and Zrnic (1993, 239–271), ZDR is proportional to the ratio of transmitted and received power at horizontal polarization to that at vertical polarization. Briefly, it is a function of hydrometeor shape, density, and orientation. Differential reflectivity varies from 0 to 4 dB for rain, depending on the median drop size that determines the average oblateness of rain drops. It is relatively small (few tenths of a dB) for snow aggregates due to their low density and almost random orientation and can increase substantially (up to 4 or 5 dB) for pristine ice crystals because of their higher density and horizontally preferred orientations (for certain ice crystal habits). Specific differential phase represents the radial gradient of the phase lag between radar signals at horizontal and vertical polarization. It is a function of shape, density, orientation, and additionally concentration. In rain, KDP values vary widely, as do ZDR values. The KDP is quite small (0.1°–0.2° km−1 at the 10-cm radar wavelength) for aggregates but is substantially larger for horizontally oriented ice crystals. Finally, ρHV is the correlation coefficient between horizontally and vertically polarized radar returns, and is a measure of the diversity of hydrometeor sizes, shapes, orientations, and densities. With the CIM radar, ρHV can be as low as 0.6 in a region of mixed-phase precipitation; ρHV of unity is expected in precipitation with a uniform distribution of hydrometeor size, shape, etc.
The procedure described by Ryzhkov and Zrnic (1998) is used here to compute KDP. Interpolation of KDP and the other variables to a uniformly spaced Cartesian grid is performed using a single-pass, Barnes (1964) objective analysis scheme. A dimensional smoothing parameter value (see Koch et al. 1983) of 1.03 km2 is used for “fine-grid” analyses, in which horizontal and vertical gridpoint spacings are 1 and 0.5 km, respectively; a value of 2.17 km2 is used for“coarse-grid” analyses, in which horizontal and vertical gridpoint spacings are 2 and 1 km, respectively. The reader should consult Trapp and Doswell (2000) for a justification of and philosophy behind the use of this analysis scheme and parameter values.
During the interpolation step, we adjust for precipitation echo movement during a volumetric radar scan.2 Cartesian velocity components (u, υ) are then synthesized from CIM and KTLX radial velocities that are interpolated to the coarse grid; the synthesis methodology follows that of Brandes (1977) and others. Vertical velocity (w) is determined via integration of the anelastic continuity equation, using an explicit technique discussed by T. Gal-Chen (1983, unpublished manuscript), Sperow (1995), and Sperow et al. (1995). The integration is taken from the echo top (where w is assumed to be zero) downward. Divergence errors that accumulate during integration are adjusted according to the technique of Nelson and Brown (1982), who additionally discuss problems related to boundary condition uncertainties.
Dual-Doppler analyses prior to 1945 UTC (hereafter, all times are for 8 March 1994 unless otherwise indicated) are not possible due to the unavailability of KTLX data in Archive Level II format. Also, polarimetric data are not available until 1545 UTC, prior to which CIM was not operating. One data limitation is the rather coarse time resolution of the CIM volume scans, owing to the 13 minutes required to complete the radar-tilt sequence used on this day. Such time resolution, coupled with the movement of the phenomenon of interest into and out of the dual-Doppler lobes, precludes calculations of reliable parcel trajectories, for example.
4. Overview of structure and evolution revealed by radar
A sense of the general evolution of the precipitation event is provided by the series of CIM plan position indicators (PPIs), at 0.5° elevation in Fig. 7. These PPIs during the period 1800–2300 UTC additionally show the context of the smaller-scale precipitation features discussed below. For example, each of the figure panels depicts a broad, generally continuous 15–25-dBZ echo north of the radar (Figs. 7a–f). In a location between this broad echo and the relatively intense cells/clusters of cells that are found south of the radar (see section 7) is a pronounced, ∼25-km-wide, 30–35-dBZ reflectivity band (Figs. 7b,c) (see section 6). Evident in Figs. 7d–f are narrow (widths of a few kilometers) 30–35-dBZ reflectivity bands that are embedded within or found just south of the broad echo (see section 5). All these featured radar echoes have locations several hundred kilometers poleward of the surface cold front (see Fig. 2). As is demonstrated in the subsequent sections, the precipitation structure and evolution agrees in general with, for example, Martner et al.’s (1993) schematic representation of a winter storm observed during the Lake Ontario Winter Storms project, save for the type of front and the detail afforded to these authors by mobile radiosonde observations and other “advanced” remote sensors.
Radar reflectivity displayed in the CIM PPIs in Fig. 7 and also ZH time integrated over various intervals fail to reveal unambiguously the location of the largest accumulations of snow that were recorded in northern Oklahoma (see Fig. 1). Indeed, with the caveat that the distance from CIM to one of the snow-accumulation maxima in northern Oklahoma is ∼100 km (hence the center of the radar beam at 0.5° elevation is ∼0.87 km), we can find no patterns in the data, such as distinct, persistent echoes, that discriminate the 25- to 35-cm snow accumulations from those of a few centimeters. Fields (not shown) of CIM radar-estimated snow water equivalent S (and also snow depth), calculated as in Super and Holroyd (1996) via the relation Ze = αSβ, where Ze is equivalent radar reflectivity, likewise fail to reveal the largest measured accumulations.3 Thus, our observations prompt us to make the perhaps obvious statement that an elongated maximum of snow accumulation does not necessarily result from a band of persistent, enhanced radar reflectivity factor and vice versa. The observations additionally bring to light some of the difficulties in snowfall QPE using radar reflectivity data alone; such difficulties are due in part to the lack of a well-established relation between snow-crystal shape and size (Ryzhkov and Zrnic 1998).
A more physical diagnosis of the snowfall is provided by the polarimetric measurands. Consider the radar data and snowfall at a specific NWS surface observation site in northern Oklahoma: at Enid, Oklahoma (END; range = 96.9 km, azimuth = −5.7° with respect to CIM), 30 cm of snow accumulated during the 18-h period beginning 1200 UTC. NWS surface observations of snow depth, snow intensity, and accumulation rates exceeding 2.5 cm (1 in.) h−1 allow us to compare in more detail the time tendencies in the snowfall at a single site to the polarimetric measurands.
A time–height presentation of ZH in the vicinity of END is constructed from area-averaged, then temporally smoothed4 vertical profiles from each radar volume scan during the period 1700–2359 UTC; snow was reported at each observation time during this period (Fig. 8a). The END precipitation echo is at all times relatively shallow, with an average echo top of ∼6 km. The echo is characterized by ZH that generally decreases with height above the ground, a manifestation of the decrease with height of snow crystal size. Such a vertical gradient in ZH is enhanced during a few brief periods when ZH exceeds 20 dBZ in the lowest few kilometers above the ground (Fig. 8a).
We caution against the temptation here to relate ZH values to NWS reports of snowfall intensity, because of the dependence of the NWS’s horizontal visibility based snowfall intensity observations on snow-crystal size, density, and concentration (Rasmussen et al. 1999). Consider as an alternative the physical consistency between the more reliably measured 5 cm (2 in.) h−1 accumulation rates and the low-level ZH maxima and midlevel ZDR and KDP maxima that precede them (Figs. 8b,c). At ∼1800 UTC, the vertical increases in ZDR and KDP represent the increase with height of nonaggregated crystals (with horizontally preferred orientations): a period of enhanced snowfall at the ground is consistent with the prior generation of relatively larger and more abundant ice crystals aloft. Indeed, relatively larger values of ZH and smaller values of ZDR and KDP are found at low levels after 1800 UTC. These respective values reveal large aggregates that apparently tend to tumble and/or wobble while they fall, motions that give the aggregates an effective sphericity from the perspective of the radar (Ryzhkov and Zrnic 1998).
5. Elevated convective element
NWS surface observations at Wiley Post Airport, Oklahoma (PWA; see Fig. 11), during the period 2100–2200 UTC include “thunder-snow,” an accumulation of 5 cm of snow, and surface temperatures of 0° to −1°C. According to the NLDN data, no cloud-to-ground lightning strikes were recorded during this period in the vicinity of PWA, implying that the audible thunder (as implied by the thunder-snow observation) likely was associated with in-cloud lightning. The analyses that we now consider suggest a relationship near PWA between the thunder and heavy snow, an elevated convective element, and a reflectivity band (see Figs. 7 and 9) embedded within the broad-area precipitation echo.
Constructed using (fine)gridded data from the 2103–2115 UTC CIM volume scan, a vertical cross section taken parallel to a reflectivity band and in the vicinity of PWA (see Fig. 9 for cross-section location) reveals a channel of enhanced ZH that tilts strongly with height (Fig. 10). The presumed convective element has a “base” at approximately 2 km, below which the reflectivity is horizontally uniform. Figure 10 depicts convection that “upwells” from or is embedded within stratiform-type precipitation. Note that the manifestation of this and other convective cells as reflectivity bands on a PPI or constant-altitude PPI (CAPPI) (Figs. 7 and 9) is a result of the strong vertical wind shear within the lowest several kilometers above the ground (see Fig. 4). Thus, the bands are precipitation streaks from elevated convection (J. Marwitz 1999, personal communication).
We address the elevated nature of the convection by recalling the frontal analysis presented in section 2. The height of the cold frontal surface in central Oklahoma is ∼2 km at midday. Diagnosed at this height and north of this region are large positive values of the frontogenesis function. We conclude in section 2 that a vertical circulation associated with such active frontogenesis at 600 hPa can explain the mesoscale area of precipitation in the northern half of Oklahoma. On a smaller scale, it appears as if the frontal circulation also aids the development of the elevated convection near PWA, allowing parcels above ∼2 km to release their conditional instability (see Figs. 4 and 5). Thus, invoking CSI to explain the tilted cell does not appear to be necessary.
Our dataset provides an example of the class of thunderstorms examined by Colman (1990a,b) and Moore et al. (1998): those that form above frontal surfaces in environments of zero or small ground-based CAPE. Hence, what we term an elevated thunderstorm is in this case a highly tilted, relatively low-topped cell with a narrow (1 to 2 km wide) reflectivity core (Fig. 10); the relatively larger-scale focus of the Colman and Moore et al. studies did not allow for such a storm-scale characterization. Analysis of polarimetric radar measurands now can be used to examine the microphysical structure this elevated thunderstorm, and the role the cell may have had in the heavy snowfall at PWA.
From the relatively high KDP shown in Fig. 10, nonspherical pristine ice crystals with horizontally preferred orientations are inferred (e.g., Ryzhkov and Zrnic 1998) near the “summit” of the convective cell. The highest concentration of these ice crystals is indicated by the KDP maximum at 6-km altitude. This altitude corresponds to temperatures of −15° to −20°C (see Fig. 4), which is within the temperature range that planar-type ice crystals grow (Pruppacher and Klett 1980, 32–35). Aggregation at altitudes generally below 2 km is evident from the increase with decreasing height of ZH; this signature in Fig. 10 (and also the corresponding ZDR field; not shown) arises from the decrease in bulk density and increase in equivalent diameter of aggregates, as compared to nonaggregated crystals (e.g., Vivekanandan et al. 1994). A melting-layer bright band (see section 6) is not readily apparent in the vertical section, as it had been in data collected near PWA at times several hours previous; we presume that by this time the melting layer has been removed (by evaporative cooling) and that the aggregates fall to the ground without appreciable melting and refreezing (see Fig. 4).
To address the heavy snowfall at PWA, we consider the polarimetric-radar observations in terms of the conceptual model of nimbostratus summarized by Houze (1993, 196–220). In this model, embedded convective cells act as “generators” and “seeders” of ice crystals that are “fed” by the underlying cloud. The “feeder–seeder” mechanism has been used previously to explain cold and warm frontal precipitation bands. We theorize that this mechanism played a role during the period of heavy snowfall at PWA5 and can explain the related narrow reflectivity band seen in Fig. 9 (see also Fig. 7):the polarimetric data provide clear evidence that the convective cell is associated with ice-crystal generation aloft (Fig. 10). The crystals then gravitationally settle out of the cell, and grow subsequently as snow via vapor deposition, aggregation, and perhaps some riming of supercooled liquid water, ultimately enhancing snowfall at the ground. Similar, yet independent, evidence is furnished by data from an airborne 95-GHz polarimetric radar, collected 10–15 km north to northwest of PWA, at approximately 2021 UTC (Galloway et al. 1997). These radar scans additionally show nonspherical ice particles at an altitude of ∼5 km and also their sedimentation represented as “fall streaks.” Although we have no proof, owing to diminished spatial resolution at large distances from the radar, we speculate that the feeder–seeder mechanism also acted to enhance snowfall in northern Oklahoma.
6. Reflectivity band and the rain–snow transition
At approximately 1900 UTC, an east–west-oriented, quasi-linear echo or reflectivity band appeared in low-elevation angle PPIs, ∼50 km south of CIM (Fig. 7b). By 2130 UTC this reflectivity band became less coherent 20–30 km north of CIM; its nominal width and length were 25 and 100 km, respectively. Band evolution and movement are depicted in coarse-grid CAPPIs generated from CIM volume scans beginning 1900, 1924, and 2001 UTC (Fig. 11).
Distinct signatures in other polarimetric measurands accompany this reflectivity band: a minimum in ρHV [maximum in ZDR (and in KDP; not shown)] is found generally within or north (south) of the pronounced maximum in ZH composing the band (Fig. 12). Band-normal vertical cross sections through the ZH maximum near OUN also indicate that extrema of these polarimetric measurands weaken and broaden as the band moves north of OUN, into the near-freezing air (Figs. 11 and 12). The observed variations in the band structure likely are due in part to the change in the radar sampling as the band nears the radar, and in part to microphysical and dynamical effects as explained below.
Ryzhkov and Zrnic (1998) associated these signatures with the rain–snow transition zone, as corroborated by precipitation-type observations near OUN during the period 1900–2000 UTC. Drawing on transition-zone conceptual models described by Stewart and King (1990) and Stewart (1992), Ryzhkov and Zrnic explained that (i) the peak ZDR (and KDP) prior to the transition from rain to snow is due to the presence of large, oblate raindrops; (ii) the pronounced dip in ρHV essentially within the transition zone owes to a large spread in the distribution of hydrometeor types and sizes (Doviak and Zrnic 1993, 264–266); and (iii) the peak in ZH just after the transition responds to the aggregates of effectively large diameter found in this region. The reflectivity band in Figs. 11 and 12 can be interpreted as a horizontal segment of a “vertical bright band” (VBB). In essence, the VBB is a manifestation of the mixed-phase precipitation generated within the rain–snow transition zone (Stewart and King 1990, their Fig. 15). As demonstrated by Ryzhkov and Zrnic, horizontal profiles of polarimetric data through this vertical bright band are analogous to typical vertical profiles through horizontal bright bands (see Zrnic et al. 1993).
The idealized, 2D, numerical modeling results of Szeto et al. (1988a,b) provide some insight into the dynamics of this rain–snow transition zone. Szeto et al. (1988a,b) found that the melting of frozen precipitation prescribed above the 0°C level produces solenoidal vertical circulations. In absence of a base-state temperature gradient, the solenoidal circulations are intimately linked to an expanding cold pool driven by melting effects. With time, the circulation cells become broader and shallower. Such circulation character and also evolution changes with the addition to the model base state of vertical shear of the mean wind. For example, because “upstream” movement of the cold pool is now slowed or even reversed, the upstream circulation cell becomes downstream-shifted and hence may develop an updraft over the precipitation. A base-state horizontal temperature gradient results in a comparatively larger, thermally indirect circulation that is frontogenetical at low levels.
The effects of melting precipitation and also of vertical wind shear may partially explain the evolution and structure of the VBB. For example, the broadening of the band is consistent with the lateral spreading of a low-altitude cold pool. Wind shear likely played a role in the band’s movement and additionally in its broadening: strong southwesterly winds above the frontal surface steered the VBB in a northeasterly direction; northeasterly winds below the frontal surface helped broaden the VBB through advection. Melting became less effective as the VBB moved into deeper, colder air. This may explain why the transition zone became less pronounced with time.
It is important to note here that the rain–snow transition existed prior to the formation of this reflectivity band and also after its demise. For example, the transition zone progressed southward from its central Oklahoma position at midday to a position south of the Texas–Oklahoma border by 0600 UTC 9 March. Several questions thus are brought to mind: In an apparent paradox shown in Fig. 11, though perhaps resolved by the Szeto et al. results, why did the VBB form and subsequently move northward, in a direction toward colder air at the surface and also toward the area of snow? Such behavior apparently is counter to that of VBBs studied by Stewart and King (1990) and also to that of the narrow reflectivity band analyzed by Heffernan and Marwitz (1996). Why was the VBB present during such a relatively short time? Did its presence mark a period during which the rain–snow transition was the most dramatic (and did its absence mark a period when the transition was unobservable or unresolvable by radar)? Answers to these and related questions likely await a numerical modeling effort and thus are outside the scope of the current paper.
7. Intense, nonelevated convective cell
Maxima of cloud-to-ground lightning flashes on 8 March occur at 1400 and 2000 UTC. During the latter time, NLDN data reveal a high spatial density of predominantly negative cloud-to-ground strikes associated with a single convective cell (hereafter termed the “Norman” cell because of its proximity to Norman, Oklahoma; Figs. 7c and 11c). This storm’s (i) lightning characteristics; (ii) location a few hundred kilometers north of the surface cold front in near-freezing surface air; (iii) contribution to the overall winter precipitation through its production of rain, snow, and ice pellets (the frozen precipitation accumulated at the ground only in relatively minor amounts); and (iv) proximity to both CIM and KTLX at this time render it a rather unique entity (in the literature and perhaps even in nature) and thus a good candidate for study. The reader is referred to Holle and Watson (1996) for a discussion of other winter storms in which lightning was observed.
The Norman cell forms at approximately 1900 UTC, ∼120 km south-southwest of CIM and hence south of the surface freezing line/significantly north of the surface cold front. Subsequent mean storm motion is 24 m s−1 from 240°. Aligned nearly along this motion vector are several other cells at various stages in their respective life cycles. Some develop low-altitude reflectivity cores of ZH > 50 dBZ, as does the Norman cell. However, none apparently endure as long and as far north of the front as does this cell: it is still visible at 2104 UTC during its decay stage, in a region where surface temperatures are <0°C. Interestingly, remnants of other cells can be related to the shallow reflectivity bands discussed in section 5.
Cell structure depicted by vertical cross sections derived from the 1949 and 2001 UTC CIM volume scans includes a pronounced tilt with height of a ZH column (Fig. 13). Such a northeasterly tilt appears early in the Norman cell’s life cycle, as it does in neighboring cells. Dual-Doppler wind fields (on the coarse grid) in these vertical cross sections suggest an association between the tilted ZH column and a deep updraft. The convective draft appears to stem from the lowest kilometer above ground, despite the cell’s position in post–cold frontal air.
Bearing in mind the midday frontal position and thermodynamic environment in central Oklahoma, the foregoing analyses raise compelling questions about the origin of parcels that populate this apparent “boundary layer rooted” updraft and also about its forcing. Data limitations (see section 3) do not allow us to state with certainty the extent that parcels within the potentially cool boundary layer affect the deep convection. Using inferences of the dynamical processes represented in the retrieved flow fields, however, we can address the existence of the updraft at low altitudes.
Let us consider CAPPIs at analysis times beginning at 1949 and 2001 UTC, respectively. At 1949 UTC, the z = 5.5 km deviation (from the horizontal mean6) wind field indicates a mesocyclonic couplet that straddles the reflectivity maximum and updraft (Fig. 14a). By 2001, a broad, cyclonic mesocyclone is collocated with the reflectivity maximum at z = 5.5 km. On the right flank of the reflectivity maximum, one can now find an updraft maximum that correlates spatially to a localized area of enhanced vertical vorticity (Fig. 14b).
Figures 13 and 14 are consistent with the model of supercell evolution due to Rotunno and Klemp (1985):(i) updrafts growing in a sheared environment develop counterrotating mesocyclonic vortices at midlevels, owing to the vertical tilting of environmental horizontal vorticity; (ii) the midlevel vortices result in vertical pressure gradients (VPGs) on the right and left flanks of the original updraft; (iii) so-called lifting VPGs force upward vertical accelerations on the updraft flanks and therefore within the mesocyclones; and (iv) resulting vertical motion stretches and thereby increases vertical vorticity within the mesocyclones. These individual processes are coupled in a feedback loop that can be used to explain supercell propagation (e.g., Weisman and Rotunno 2000).
The aforementioned supercell dynamics plays two possible roles in the Norman cell. First, it helps drive a low-altitude updraft in the cool, stable, postfrontal air;outflow dynamics may also contribute to the low-altitude updraft forcing (see Fig. 13). Second, it enhances the inflow into the storm of the potentially buoyant air that resides above the frontal surface (Fig. 4b), therefore contributing to updraft sustenance. As with the elevated cells discussed in section 4, the frontal circulation then likely helps air parcels above the front release their conditional instability. Partial support for our hypothesis comes from an analysis (not shown) of a comparatively shorter-lived cell that developed and moved just downwind with respect to the Norman cell: at the time of its most intense reflectivity core, it possessed neither mesocyclonic circulations nor deep updrafts that originated below the frontal surface, and also did not produce observable cloud-to-ground lightning. Why this cell (and others) failed to generate a mesocyclone remains a question for future study.
In addition to these inferences of the storm dynamics, deductions about the microphysical structure of the Norman cell also are possible. Using polarimetric values tabulated in Doviak and Zrnic (1993, p. 271), we deduce from Fig. 13 that precipitation in the form of graupel inhabits the tilted ZH column at altitudes above 3 km, where ZH ≥ 35 dBZ and KDP and ZDR are both small; precipitation in the form of snow probably resides outside the 35-dBZ reflectivity core. The graupel falls and partially melts into small drops within the layer of warmer air at 2 km, as implied in Fig. 13 where KDP ∼ 0° km−1, ZDR > 0.5 dB, and ZH ∼25 dBZ in the vertical layer generally beneath the updraft. Some of the drops then refreeze and fall to the ground as ice pellets, as supported by simple calculations (e.g., Pruppacher and Klett 1980, p. 552); others reach the ground as rain (see Fig. 13b). Likely, the snow also undergoes some partial melting but then refreezes before reaching the ground. These deductions are corroborated by later observations of thundershowers of ice pellets, snow, and rain, associated with the Norman cell that by ∼2030 UTC had moved to Tinker Air Force Base, Oklahoma (TIK).
Last, we comment briefly on the cloud-to-ground lightning associated with the Norman cell, keeping in mind the preceding discussions on the storm dynamics and microphysics. As evident in Figs. 11 and 13, the observed lightning strikes are located well downstream of the low-altitude reflectivity core but generally are collocated with higher reflectivity aloft within the tilted ZH column. Such higher reflectivity aloft has been attributed to graupel. As summarized by Williams (1998), graupel particles and ice crystals in a mixed-phase environment are necessary for the so-called noninductive mechanism of charge separation. The mixed-phase region corresponds roughly to a temperature region of −10° to −25°C, coinciding in this case to a vertical layer spanning ∼4.5 to 6.5 km (Fig. 4). Williams (1998) additionally notes that the “total lightning flash rate is strongly dependent on the vertical development of precipitation within the mixed phase region.” We find that at 2001 UTC, when the flash rate is at a maximum, the higher reflectivity core aloft inhabits much of the mixed-phase region and is the most vertically extensive (see Fig. 14). Clearly, our data of a wintertime thunderstorm in postfrontal air are consistent with current electrification theory and observations of severe and nonsevere storms.
8. Conclusions
The multiscale structure and evolution of a late-season Oklahoma winter precipitation event was analyzed;during this event more than 35 cm of snow accumulated at the ground in a narrow corridor in northern Oklahoma. Conventional surface and upper-air observations and also dual-polarization and dual-Doppler radar data were used. The radar-based analyses of winter precipitation features on the storm scale are among the first to provide even a cursory examination of the detailed organization of such features. The synoptic-scale and mesoscale analyses rendered a context for the storm-scale analysis and additionally afforded a means to determine the larger-scale forcing that led to the heavy snow accumulation.
A broad region of generally stratiform snowfall coincided with mesoscale ascent provided through frontogenesis forcing aloft and persisted in the northern half of Oklahoma during our 6-h period of study. Within this stratiform region, periods of heavier snow—at times accompanied by in-cloud lightning—were associated with embedded elevated convective elements that served as generator cells as part of the feeder–seeder mechanism; this mechanism also may have aided the production of the relatively large amount of snow that accumulated in a narrow band. More intense convective cells formed south of the stratiform precipitation, yet still poleward of the surface cold front, in air with little or no surface-based CAPE. These northeastward-moving cells produced rain, and also some snow and ice pellets; the frozen precipitation accumulated at the ground only in relatively minor amounts, however. One cell was a prolific lightning producer and particularly long-lived, owing to its rotational dynamics. A transition zone existed between the areas of stratiform snowfall and convective rainfall. Mixed-phase precipitation fell within this transition zone. The coupled effects of melting precipitation and of vertical wind shear were invoked to help explain the evolution and structure of the rain–snow transition.
Acknowledgments
Drs. John Cortinas, Bob Maddox, Tom Matejka, and Terry Schuur (NSSL and/or CIMMS) provided comments on a draft of the manuscript. Irv Watson (NWSFO Tallahassee) helped with the inceptive analysis effort. Dr. Dusan Zrnic (NSSL) provided the initial motivation to pursue this study. Oklahoma Mesonetwork data were provided courtesy of the Oklahoma Mesonet Project, a cooperative venture between Oklahoma State University and the University of Oklahoma. Much of this work was performed while the first author was a visiting scientist with the Mesoscale and Microscale Meteorology Division of the National Center for Atmospheric Research.
REFERENCES
Barnes, S. L., 1964: A technique for maximum detail in numerical map analysis. J. Appl. Meteor.,3, 396–409.
Brandes, E. A., 1977: Flow in a severe thunderstorm observed by dual Doppler radar. Mon. Wea. Rev.,105, 113–120.
Bringi, V. N., R. M. Rasmussen, and J. Vivekanandan, 1986a: Multiparameter radar measurements in Colorado convective storms. Part I: Graupel melting studies. J. Atmos. Sci.,43, 2545–2563.
——, J. Vivekanandan, and J. D. Tuttle, 1986b: Multiparameter radar measurements in Colorado convective storms. Part II: Hail detection studies. J. Atmos. Sci.,43, 2564–2577.
Carey, L. D., and S. A. Rutledge, 1996: A multiparameter radar case study of the microphysical and kinematic evolution of a lightning producing storm. J. Meteor. Atmos. Phys.,59, 33–64.
Colman, B. R., 1990a: Thunderstorms above frontal surfaces in environments without positive CAPE. Part I: A climatology. Mon. Wea. Rev.,118, 1103–1121.
——, 1990b: Thunderstorms above frontal surfaces in environments without positive CAPE. Part II: Organization and instability mechanisms. Mon. Wea. Rev.,118, 1123–1144.
Conway, J. W., and D. S. Zrnic, 1993: A study of embryo production and hail growth using dual-Doppler and multiparameter radars. Mon. Wea. Rev.,121, 2511–2528.
Cummins, K. L., E. A. Bardo, W. L. Hiscox, R. B. Pyle, and A. E. Pifer, 1995: NLDN’95: A combined TOA/MDF technology upgrade of the U.S. National Lightning Detection Network. Proc. Int. Conf. on Lightning and Static Electricity, Williamsburg, VA, U.S. Navy, U.S. Navy Rep. NAWCADPAX-95-306-PRO, 72-1–72-15.
Damiana, T. A., and J. Marwitz, 1995: Development of a gravity wave event during an Oklahoma blizzard. Preprints, 27th Conf. on Radar Meteorology, Vail, CO, Amer. Meteor. Soc., 314–316.
Doviak, R. J., and D. S. Zrnic, 1993: Doppler Radar and Weather Observations. Academic Press, 562 pp.
Galloway, J., A. Pazmany, J. Mead, R. E. McIntosh, D. Leon, J. French, R. Kelly, and G. Vali, 1997: Detection of ice hydrometeor alignment using an airborne W-band polarimetric radar. J. Atmos. Oceanic Technol.,14, 3–12.
Hakim, G. J., and L. W. Uccellini, 1992: Diagnosed coupled jet-streak circulations for a northern Plains snow band from the operational Nested-Grid Model. Wea. Forecasting,7, 26–48.
Heffernan, E., and J. Marwitz, 1996: The Front Range blizzard of 1990. Part II: Melting effects in a convective band. Mon. Wea. Rev.,124, 2469–2482.
Holle, R. L., and A. I. Watson, 1996: Lightning during two central U. S. winter precipitation events. Wea. Forecasting,11, 599–614.
Houze, R. A., Jr., 1993: Cloud Dynamics. Academic Press, 573 pp.
Keyser, D., B. D. Schmidt, and D. G. Daffy, 1992: Quasigeostrophic diagnosis of three-dimensional ageostrophic circulations in an idealized baroclinic disturbance. Mon. Wea. Rev.,120, 698–730.
Koch, S. E., M. DesJardins, and P. J. Kocin, 1983: An interactive Barnes objective map analysis scheme for use with satellite and conventional data. J. Climate Appl. Meteor.,22, 1487–1503.
Lopez, R. E., and J.-P. Aubagnac, 1997: The lightning activity of a hailstorm as a function of changes in its microphysical characteristics inferred from polarimetric radar observations. J. Geophys. Res.,102, 16 799–16 813.
Loughe, A. F., C.-C. Lai, and D. Keyser, 1995: A technique for diagnosing three-dimensional ageostrophic circulations in baroclinic disturbances on limited-area domains. Mon. Wea. Rev.,123, 1476–1504.
Martner, B. E., J. B. Snider, R. J. Zamora, G. P. Byrd, T. A. Niziol, and P. I. Joe, 1993: A remote-sensing view of a freezing-rain storm. Mon. Wea. Rev.,121, 2562–2577.
Marwitz, J. D., and J. Toth, 1993: A case study of heavy snowfall in Oklahoma. Mon. Wea. Rev.,121, 648–660.
McCammon, R. C., 1996: Dry air interactions with a late season heavy snow event over Oklahoma. NOAA Tech. Memo. NWS CR-112, 11 pp.
Moore, J. T., A. C. Czarnetzki, and P. S. Market, 1998: Heavy precipitation associated with elevated thunderstorms formed in a convectively unstable layer aloft. Meteor. Appl.,5, 373–384.
Nelson, S. P., and R. A. Brown, 1982: Multiple Doppler radar derived vertical velocities in thunderstorms. Part I—Error analysis and solution techniques. NOAA Tech Memo ERL NSSL 94, 10 pp.
NOAA, 1994: Storm Data. Vol. 36, No. 3, 78 pp.
Orville, R. E., 1994: Cloud-to-ground lightning flash characteristics in the contiguous United States: 1989–1991. J. Geophys. Res.,99, 10 833–10 841.
Petterssen, S., 1936: Contribution to the theory of frontogenesis. Geofys. Publ.,11 (6), 1–27.
Pruppacher, H. R., and J. D. Klett, 1980: Microphysics of Clouds and Precipitation. D. Reidel, 714 pp.
Rasmussen, R. M., J. Vivekanandan, and J. Cole, 1999: The estimation of snowfall rate using visibility. J. Appl. Meteor.,38, 1542–1563.
Rotunno, R., and J. B. Klemp, 1985: On the rotation and propagation of simulated supercell thunderstorms. J. Atmos. Sci.,42, 271–292.
Ryzhkov, A. V., and D. S. Zrnic, 1994: Precipitation observed in Oklahoma mesoscale convective systems with a polarimetric radar. J. Appl. Meteor.,33, 455–464.
——, and ——, 1995: Comparison of dual-polarization radar estimators of rain. J. Atmos. Oceanic Technol.,12, 249–256.
——, and ——, 1998: Discrimination between rain and snow with a polarimetric radar. J. Appl. Meteor.,37, 1228–1240.
Schultz, D. M., and P. N. Schumacher, 1999: The use and misuse of conditional symmetric instability. Mon. Wea. Rev.,127, 2709–2732.
Smith, P. L., and A. B. Super, 1999: Snowfall algorithms for radar estimation of precipitation. Preprints, 29th Conf. on Radar Meteorology, Montreal, PQ, Canada, Amer. Meteor. Soc., 790–793.
Sperow, K. S., 1995: Airborne Doppler analysis of the 18 February 1993 TOGA COARE squall line using a new analysis method: The two-step, second order Lax-Wendroff scheme. M.S. thesis, University of Oklahoma, 89 pp. [Available from School of Meteorology, University of Oklahoma, 100 E. Boyd, Norman, OK 73019.].
——, H. B. Bluestein, and T. Gal-Chen, 1995: Testing a Doppler analysis method: The two-step, second order Lax-Wendroff scheme. Preprints, 27th Conf. on Radar Meteorology, Vail, CO, Amer. Meteor. Soc., 296–298.
Stewart, R. E., 1992: Precipitation types in the transition region of winter storms. Bull. Amer. Meteor. Soc.,73, 287–296.
——, and P. King, 1990: Precipitation type transition regions in winter storms over southern Ontario. J. Geophys. Res.,95, 22 355–22 368.
Super, A. B., and E. W. Holroyd, 1996: Snow accumulation algorithm for the WSR-88D Radar, Version 1. Bureau of Reclamation Report R-96-04, Denver, CO, 133 pp. [Available from Bureau of Reclamation, P.O. Box 25007, Denver, CO 80225-0007.].
Szeto, K. K., C. A. Lin, and R. E. Stewart, 1988a: Mesoscale circulations forced by melting snow. Part I: Basic simulations and dynamics. J. Atmos. Sci.,45, 1629–1641.
——, R. E. Stewart, and C. A. Lin, 1988b: Mesoscale circulations forced by melting snow. Part II: Application to meteorological features. J. Atmos. Sci.,45, 1642–1650.
Trapp, R. J., and C. A. Doswell III, 2000: Radar data objective analysis. J. Atmos. Oceanic Technol.,17, 105–120.
Vivekanandan, J., V. N. Bringi, M. Hagan, and P. Meischner, 1994: Polarimetric radar studies of atmospheric ice particles. IEEE Trans. Geosci. Remote Sens.,32, 1–10.
Weisman, M. L., and R. Rotunno, 2000: The use of vertical wind shear versus helicity in interpreting supercell dynamics. J. Atmos. Sci.,57, 1452–1472.
Williams, E., 1998: The electrification of severe storms. Preprints, 19th Conf. on Severe Local Storms, Minneapolis, MN, Amer. Meteor. Soc., 630.
Zahrai, A., and D. S. Zrnic, 1993: The 10-cm wavelength polarimetric weather radar at NOAA’s National Severe Storms Laboratory. J. Atmos. Oceanic Technol.,10, 649–662.
Zrnic, D. S., and A. V. Ryzhkov, 1999: Polarimetry for weather surveillance radars. Bull. Amer. Meteor. Soc.,80, 389–406.
——, N. Balakrishnan, C. Ziegler, V. Bringi, K. Aydin, and T. Matejka, 1993: Polarimetric signatures in the stratiform region of a mesoscale convective system. J. Appl. Meteor.,32, 678–693.
Total snowfall (in in.) in Oklahoma for period 7–9 Mar 1994
Citation: Monthly Weather Review 129, 3; 10.1175/1520-0493(2001)129<0486:MSAEOA>2.0.CO;2
(a) 300-hPa total horizontal wind speed (m s−1, shaded according to scale), height (solid lines every 12 dam), and horizontal wind (pennant, full barb, and half barb denote 25, 5, 2.5 m s−1, respectively) from initial analysis of the Eta Model on 1200 UTC 8 Mar 1994.“J”s represent wind maxima. (b) 1200 UTC 8 Mar 1994 600-hPa level: notation standard (temperature and dewpoint in °C; geopotential height in m, leading “3” or “4” dropped), geopotential height (solid lines every 6 dam), and isotherms (dashed lines every 3°C). (c) 1200 UTC 8 Mar 1994 surface map: notation standard (temperature and dewpoint in °C), isobars (thin solid lines every 4 hPa), and frontal surface (thick solid line)
Citation: Monthly Weather Review 129, 3; 10.1175/1520-0493(2001)129<0486:MSAEOA>2.0.CO;2
Radar summary charts for (a) 1135 UTC 8 Mar 1994 and (b) 0035 UTC 9 Mar 1994
Citation: Monthly Weather Review 129, 3; 10.1175/1520-0493(2001)129<0486:MSAEOA>2.0.CO;2
Skew T–logp diagram for Stephenville, TX (SEP; gray lines), and Norman, OK (OUN; black lines), at 1200 UTC 8 Mar 1994. CAPE is convective available potential energy (J kg−1), and LIFT is lifted index (°C). Wind barbs: pennant, barb, and half-barb represent 25, 5, and 2.5 m s−1, respectively
Citation: Monthly Weather Review 129, 3; 10.1175/1520-0493(2001)129<0486:MSAEOA>2.0.CO;2
12-h forecast from 0000 UTC 8 Mar 1994 Eta Model: (a) cross section from North Platte, NB (LBF), to Brownsville, TX (BRO) (see Fig. 5b for cross section location). Potential temperature (thin solid lines every 3 K), convective available potential energy (J kg−1, shaded according to legend at bottom of figure), frontogenesis [thick solid lines every 6 K (100 km)−1 (3 h)−1], and 80% relative humidity contour (dotted lines). CAPE at a given level is computed by lifting a parcel at that level. Asterisk in the cross section represents the location of the largest snowfall at the surface within the plane of the section (see Fig. 1). (b) Frontogenesis at 1000 hPa [dotted lines every 1.0 K (100 km)−1 (3 h)−1] and 600 hPa [dashed lines every 0.5 K (100 km)−1 (3 h)−1]; convective available potential energy calculated from parcels lifted from 1000 hPa (J kg−1; shaded according to scale at bottom of figure); convective available potential energy calculated from parcels lifted from 600 hPa (overprinted shading and contoured in thick solid lines 1, 50, and 100 J kg−1)
Citation: Monthly Weather Review 129, 3; 10.1175/1520-0493(2001)129<0486:MSAEOA>2.0.CO;2
Cross section from North Platte, NB (LBF), to Brownsville, TX (BRO) (see Fig. 5b), from the 12-h forecast from 0000 UTC 8 Mar 1994 Eta Model. (a) Saturated equivalent potential temperature (thick solid lines every 4 K), streamfunction for divergent circulation in the plane of the cross section (thin dashed line every 3 × 104 Pa m s−1), and omega in the plane of the cross section (0.01 Pa s−1, contoured and shaded every 0.15 Pa s−1). Divergent circulation in plane of cross section (vectors; horizontal magnitude scaled by reference vector in lower right of panel; vertical magnitude scaled by reference vector divided by 100). (b) Potential temperature (thick solid lines every 4 K), streamfunction for divergent circulation normal to the cross section (thin dashed line every 3 × 104 Pa m s−1), and omega normal to the cross section (0.01 Pa s−1, contoured and shaded every 0.15 Pa s−1). Divergent circulation normal to the cross section (vectors; horizontal magnitude scaled by reference vector in lower right of panel; vertical magnitude scaled by reference vector divided by 100)
Citation: Monthly Weather Review 129, 3; 10.1175/1520-0493(2001)129<0486:MSAEOA>2.0.CO;2
Cimarron radar PPIs of radar reflectivity factor (dBZ) at 0.5° elevation. Range rings are indicated at 10-km intervals. In (b), VBB indicates a vertical bright band, which is discussed in section 6. See sections 7 and 5 for a description of the features labelled “cell” and “bands” in (c) and (d), respectively. (a) 1758, (b) 1900, (c) 2002, (d) 2104, (e) 2206, and (f) 2256 UTC
Citation: Monthly Weather Review 129, 3; 10.1175/1520-0493(2001)129<0486:MSAEOA>2.0.CO;2
Time–height plots of (a) ZH (dBZ), (b) ZDR (dB), and (c) KDP (deg km−1), for the period 1700–2359 UTC, near Enid, OK. Surface observations of heavy, moderate, and light snowfall are indicated by “S+,” “S,” and “S-,” respectively. Integers plotted above the snowfall observations represent snow accumulations of 1 in. h−1 or more during the preceding hour
Citation: Monthly Weather Review 129, 3; 10.1175/1520-0493(2001)129<0486:MSAEOA>2.0.CO;2
Horizontal cross section of ZH (dBZ) at 2 km, from the CIM volume scan beginning 2103 UTC. Black line denotes location of vertical cross section in Fig. 10
Citation: Monthly Weather Review 129, 3; 10.1175/1520-0493(2001)129<0486:MSAEOA>2.0.CO;2
Vertical cross section of ZH (dBZ) and KDP (deg km−1) from the CIM volume scan beginning 2103 UTC. KDP is contoured at 0.2° and 0.3° km−1
Citation: Monthly Weather Review 129, 3; 10.1175/1520-0493(2001)129<0486:MSAEOA>2.0.CO;2
Surface isotherms based on Oklahoma Mesonet data, cloud-to-ground lightning strike locations, and horizontal cross sections of ZH (dBZ) at 0.5 km. Isotherm contour interval is 0.5°C. Positive cloud-to-ground strikes are indicated by a “+.” White lines show locations of cross sections in Fig. 12. (a) 1900, (b) 1924, and (c) 2001 UTC
Citation: Monthly Weather Review 129, 3; 10.1175/1520-0493(2001)129<0486:MSAEOA>2.0.CO;2
Vertical cross section of ZH (dBZ), ZDR (dB), and ρHV. ZH is gray shaded at 5 dBZ increments. ZDR is contoured (black lines) at 0.5, 0.75, 1.25, and 1.5 dB, and ρHV (white lines), at 0.8 and 0.85. For clarity of presentation, contours are shown only for altitudes less than 5 km. (a) 1900, (b) 1924, and (c) 2001 UTC
Citation: Monthly Weather Review 129, 3; 10.1175/1520-0493(2001)129<0486:MSAEOA>2.0.CO;2
Vertical cross sections of ZH (dBZ), deviation wind vectors, and the 1 and 5 m s−1 contours of vertical velocity; of ZDR (dB); and of KDP (° km−1). The 30-dBZ ZH contour overlays the ZDR and KDP plots. Cross section locations are indicated in Fig. 14. (a–c) 1949 and (d–f) 2001 UTC
Citation: Monthly Weather Review 129, 3; 10.1175/1520-0493(2001)129<0486:MSAEOA>2.0.CO;2
Horizontal cross sections, at 5.5 km, of ZH (dBZ), deviation wind vectors, and the 1 and 5 m s−1 contours of vertical velocity. (a) 1949 and (b) 2001 UTC
Citation: Monthly Weather Review 129, 3; 10.1175/1520-0493(2001)129<0486:MSAEOA>2.0.CO;2
A measurand is a particular quantity or property subject to measurement, which herein is not measurable directly but rather depends on other measurable quantities through a functional relationship.
A motion vector of 24 m s−1 from 240° is our best estimate of nominal “storm” motion based on the movement of various reflectivity features in CIM plan position indicators.
We were constrained to use published values of α and β; as with those determined empirically by Super and Holroyd (1996), these are given only for “dry” snow (“wet” snow fell in Oklahoma during the 8 March 1994 event). Smith and Super (1999) note moreover that winter precipitation with brightband conditions (as on 8 March 1994;see section 6) may not be appropriate for the Z–S algorithm of Super and Holroyd and others.
Using a Barnes weight function with a smoothing parameter value of 1.037 × 106 s2.
Damiana and Marwitz (1995) also suggested that the feeder–seeder process influenced gravity waves observed near CIM on this day.
Horizontal mean is defined as
