The Sigüenza tornado: a case study based on convective ingredients concept and conceptual models

Transcription

1 Meteorol. Appl. 4, (1997) The Sigüenza tornado: a case study based on convective ingredients concept and conceptual models F Martín, R Riosalido and L de Esteban, Instituto Nacional de Meteorología (I.N.M.), C/ Paseo de las Moreras s/n, Ciudad Universitaria D.P , Madrid, Spain On 24 May 1993, part of the Iberian Peninsula was affected by convective activity concentrated on the eastern side of a low-level thermal boundary which was orientated north south. A series of storms evolved into a squall line striking at the province of Guadalajara (Central Spain). The southernmost cell of this mesoscale convective system generated a tornado that hit the city of Sigüenza between 1930 and 1940 UTC. This paper has two objectives. The first aim is to investigate the ingredients (buoyancy, wind shear, vertical distribution of moisture content, and synoptic and mesoscale lifting mechanisms) and the atmospheric agents (mid-upper level trough, low level-boundary, convergence zones, etc.) which favour the production of severe storms. The second one is to analyse information provided by operational remote-sensing systems (satellite, radar and lightning) in order to test and evaluate some conceptual models of severe storms in an operational environment. For the first objective, the ingredient-based methodology will be shown to be a valuable operational approach allowing forecasters to focus on the possibility of a severe event using the appropriate diagnostic or prognosis tools. For the second objective, special attention is given to the suitability of conceptual models associated with convective phenomena and the potential value of such models (lightning charge related to wind shear and radar-based multicell conceptual models) for understanding the observed processes. From an operational viewpoint some problems may arise because of the technical characteristics of the equipment, particularly related to radars (e.g. scanning strategy, distance between radar and targets, and radar signal processing and displaying). Possible guidelines for using volumetric radar data (non Doppler) for deep convection monitoring are suggested for rugged and complex topographical regions. 1. Introduction Between 1930 and 1940 UTC on 24 May 1993, many thunderstorms swept through Guadalajara province (Central Spain). A tornado was reported at Sigüenza: see Figure 1 for location map and regional topography. The damaging tornado was documented by Miguel Gayá, a meteorologist from the Spanish Meteorological Service (INM), three days after the event. According to his report, the tornado occurred between 1930 and 1940 UTC (2130 and 2140 local time). Based on the damage to houses, buildings, monuments, trees, etc., maximum wind gusts were estimated to be 170 km h 1. The tornado was therefore classified as weak according to the Fujita Scale (Fujita, 1973); Type F1 has winds of km h 1. The tornado direction was north northeasterly along a relatively straight path. The affected area was no less than 250 m in diameter along a corridor of 2 3 km in width. The rocky landscape surrounding the city hindered the recordings of additional data, although very large hailstones were reported to the northwest of the tornado path. Damage was estimated to be about $4 million (in 1993), and most of the urban area was affected. Fortunately, there was no loss of life. This tornadic event was the first that could be analysed in detail at the INM due to the proximity of the convective cell to the Madrid radar. The purpose of this paper is to document this case and to add to our knowledge of Spanish tornadoes. Generally speaking, Spanish forecasters are more familiar with flash floods and heavy rain events in the autumn over the Western Mediterranean areas and hail situations in warm periods over the central and northeastern zones of the Iberian Peninsula (IP). Little attention has been given to tornadic situations, although a few internal reports exist. With regard to Spanish tornadogenesis, mountain barriers and rugged topography are important obstacles to the development of severe storms with a high degree of organisation. In contrast, the topographic features may favour the development of hail, heavy rain or flash flood events. Only flat terrain or open water, such as in Mediterranean areas, may support storms with a higher degree of organisation which may eventually evolve into 191

2 F Martín, R Riosalido and L de Esteban scale to mesoscale including the microscale, rather than as an isolated event in space or time. When an operational forecaster is faced with the possibility of convective development, the first step involves an assessment of what kinds of convective events are likely and what atmospheric conditions are suitable for supporting them. Different approaches are applied to convective event forecasting (e.g. decision trees, rules of thumb, MOS, etc.). However, as noted by Doswell et al. (1995, hereafter referred to as D95), one effective and scientific approach uses the concept of basic ingredients:... the ingredients for any significant atmospheric event are a set of the known physical processes by which this phenomenon is produced and the pertinent parameters that control it, so the forecaster can focus his/her attention in investigating and anticipating the possibility of the development of such event. In D95 it is illustrated how this methodology might be applied in practice for flash flood events and it is shown that this approach might be applied to a broader spectrum of forecast situations. A similar approach was applied to the case study of the Sigüenza tornado. Our task focused on the meteorological agents (upper-level trough, boundaries, convergence zone, etc.) that produce and bring together the ingredients for severe thunderstorm development. Basically, both methodologies, based on ingredients (physical processes) or atmospheric agents (synoptic and mesoscale disturbances), are quite similar if we are able to understand what atmospheric processes are taking place and why they are happening. But, as noted in D95, the advantages of using the first approach are evident:... an ingredients-based methodology is certainly a logical choice for the application of scientific understanding to the forecasting task.... By focusing on ingredients, forecasters can reduce the range of their choice... and flash flood [in that paper] can be diagnosed and anticipated.... Figure 1. Location map and main places mentioned in the text: Sigüenza (S), Madrid (M) and radar site (R). (a) The Iberian Peninsula. (b) Madrid radar coverage, geographic boundaries and topography of the area. Elevations in metres. tornadic cells. Recently, this mentality has changed and internal reports (in Spanish) about preliminary climatological tornado studies have appeared (Gayá, 1992). Training courses have also been developed about severe thunderstorms which resemble those occurring over the Great Plains of the USA; American concepts and examples have been used in this training. However, there have been problems with this training because, for example, the Spanish topographical features are complex so making detailed surface analyses and observations is difficult; the density of surface reports is low for convective phenomena and no tornadic case studies existed using the operational and observational tools at INM. The development of a particular type of convective phenomenon is the result of a series of processes that occur in the atmosphere like a cascade, from synoptic 192 Once the convective phenomena have appeared then a different approach must be applied to detect and evaluate the existence of life-threatening storms. Now, maximum attention must be given to the extent and degree of organisation in order to determine what surface results are likely (heavy rain, hail, damaging winds, tornadoes, etc.). The convective conceptual models are very useful for this task; these are mainly radar-based conceptual models. Two such models will be used in this paper. It should be noted that in this study use was not made of advanced and/or derived output from a Numerical Weather Prediction (NWP) operational model, such as the storm-relative environmental helicity (Brooks et al., 1993) and the energy-helicity index (Davies, 1993). These topics may be the subject of another study. In this paper, analysis will be made of some conventional derived parameters related to convective development (e.g. instability indices, warm thermal advection and convergence zones), but use of the quantitative

3 The Sigüenza tornado: a case study threshold approach has been avoided. In this context, there may be a tendency to use thresholds as a way of forecasting atmospheric events rather than leading to a logical understanding of the atmospheric factors producing and controlling them. In particular, overseas thresholds for severe convective phenomena must be used with caution, and such thresholds must initially be tested. Therefore, a qualitative approach was adopted for some convective parameters and a logical methodology for convective forecasting was applied. The following study examines how modern ideas can be applied to this severe event in an operational context. In Section 2 we consider the basic theory and concepts related to severe convection, before the squall line development, so the synoptic and mesoscale setting will be discussed. Section 3 describes some relevant factors which confirm the previous ideas. In Section 4, once the deep convective cells form, the volumetric radar data is used to investigate the degree of organisation using radar-based conceptual models. The electrical life-cycle of the convective system is described in Section 5. The last section discusses the results and offers some conclusions. 2. Ingredients for severe weather producing storms: synoptic and mesoscale setting According to the US definition, see for instance Doswell (1985, from now D85) pp , a severe convective storm is one which produces one or more of the following phenomena: hail ( 1.9 cm in diameter), damaging winds ( 50 kn) and tornadoes. At the INM there is not an official definition of a severe but intense thunderstorm. In the Spanish case, the definition is quite similar to that used in the USA, but different thresholds are used: hail ( 1 mm in diameter), damaging winds ( 60 km h 1 or 33 kn) and tornadoes or waterspouts. Anyway, severe convective events are associated with large hail or damaging winds or tornadoes; severe thunderstorms are always linked to deep and organised convection. Figure 2. Analyses for 1200 UTC on 24 May 1993 from the INM-LAM. (a) 300 hpa contour heights (gpm, solid lines) and temperature (ºC, dashed lines). (b) As (a) but for 1000 and 850 hpa. (c) Static stability parameter σ at 700 hpa (in 10 7 m 4 s 2 kg 2 ; only zero and negative values are represented by heavy solid lines; the dotted area shows the instability close to the Iberian Peninsula) and 850 hpa thermal advection (positive values in thin lines, negatives in dashed lines, ºC/12 h 1 ). (d) 850 hpa θ w (ºC, heavy solid lines) and divergence (in 10 5 s 1 ; positive values in thin dashed lines and negative ones in thin solid lines). C indicates maximum of convergence and D the same but for divergence. + indicates a relative maximum of warm thermal advection over the Iberian Peninsula. 193

4 F Martín, R Riosalido and L de Esteban This is not the right place for a detailed discussion about the ingredients necessary to produce severe convection. The interested reader is referred to D85 for comprehensive analyses of severe thunderstorms and their ingredients. The ingredients are listed below: Moderate or high instability: buoyancy. Vertical wind shear: minimum values depending on the buoyancy. A dry lower mid-troposphere: there must be sufficient moisture content at low levels. Some processes must exist to lift the parcels to their level of free convection (LFC): these mechanisms may be found in the synoptic and/or mesoscale environment. The synoptic background was characterised by a persistent blocking system and quasi-stationary depression, both of them close to the IP. For several days, the eastern regions were dominated by a strong low-level anticyclone throughout much of the western Mediterranean basin. A strong north south-oriented ridge was over the same region at middle levels, with a quasistationary low over northwestern Spain controlling the westerly moving cloud systems. This large-scale background is typical of spring summertime situations, which favour the convective developments associated with the diurnal cycle on the eastern regions of the IP. Now concentrate attention on the 24 May over the IP. As the result of the persistent blocking pattern, several important disturbances appeared during daytime up to 1200 UTC (see Figures 2 and 3): a north southoriented thermal boundary formed at low levels (850 and 1000 hpa), persistent warm thermal advection existed at the eastern portion of this boundary and the solar heating was very effective in the region mentioned above. The last two factors contributed to the production of an elongated tongue-shaped area of low potential stability covering the entire right side of the thermal discontinuity where the environmental lapse rate was conditionally unstable. The large-scale mid-upper tropospheric dynamic forcing, according to NWP model output (such as Q-vector divergence, not shown) had a slight positive bearing on convective developments. Simultaneously, significant vertical wind shear existed: southerly or southeasterly winds of kn at low levels were increasing to kn and veering to south southwesterly at mid-upper levels in almost all of the eastern areas. But southwesterly winds at all levels affected the western regions of the low-level boundary. These perturbations can be observed in the objective analysis (Díaz-Pabón, 1989) for 1200 UTC, 24 May, produced by the Spanish limited area model (LAM) (see Figure 2(a), (b)). Figure 2(c) depicts the tongue of convective instability at 700 hpa and the warm thermal advection at 850 hpa over the study region, and Figure 194 Figure 3. (a) Surface analysis at 1200 UTC on 24 May 1993: sea level pressure (PSL, hpa) and winds (in kn, long barb = 10 kn, short barb = 5 kn). Thunder areas are indicated by a specific symbol. (b) Composite chart for the same time. L and l indicate low pressure areas, H and h indicate high ones. 2(d) shows θ w at 850 hpa and convergence zones at the same level. Surface analyses at 1200 UTC on 24 May (see Figure 3(a)) show the pressure systems, surface winds and areas where the first thunderstorms developed. Figure 3(b) is a composite chart showing the main elements required for convective generation. Under these conditions the most susceptible area for convective developments were located east of the surface thermal boundary; the visible midday satellite images showed the development of the first convective cells. In a broad sense, some ingredients existed and NWP output provided some approximate indication of their existence but others were missing or they were not apparent (e.g. lifting mechanisms). According to D95, it is necessary that all ingredients must be in the correct place at the right time for the development of severe convection. The role of the forecaster/nowcaster is to evaluate the possibility that coincidence may exist using any data available. 3. Remote sensing data analysis prior to the tornado Some elements and atmospheric agents controlling the type of convection may be identified using operational

5 The Sigüenza tornado: a case study Figure 4. METEOSAT satellite images at 1200 UTC for (a) enhanced WV, (b) IR, and (c) VIS channels. (d) Sketch showing the main features from the METEOSAT channels. tools, such as NWP fields or standard surface reports. Others must be inferred using remote sensing data, conceptual models and basic convective theories relating to severe storms. Some ingredients are missing, mainly due to the spatial and temporal resolution of current operational sensors and tools. But, in any case, the main objective of the forecaster is always the same: to get a four-dimensional picture of the atmosphere and the local phenomena which are going to take place. If our mental model does not fit the observations then we must modify that model to fit the current observations. Similar processes were used here and a description of how such tools can be used, together with suitable conceptual models, are given below Basic pre-convective factors One of the most important tasks in convection forecasting is to discriminate between an ordinary day and one for which hazardous weather may occur. If the nowcaster/forecaster perceives evidence that all ingredients are in place, then he/she may diagnose and anticipate the severe events. Remote sensing data are a very valuable tool for this purpose. We are going to analyse why the atmospheric situation 24 May led to a nontypical convective event. METEOSAT satellite imagery showed an upper-level trough crossing the IP during the daytime (see Figure 4(a), (b) for water vapour (WV) and infrared (IR) images, at 1200 UTC). Its typical structure is easy to identify on the WV channel by the dark (warm dry) area behind moisture zone at mid-upper levels. This disturbance was not well shown in the corresponding LAM output (see Figure 2(a)). The development of storms might be expected ahead of the moving mid-upper-level trough if instability existed over appropriate regions, but there was no evidence of convection initiation. In contrast, and this was surprising, early storm activity occurred at the eastern areas of the low-level boundary and behind the trough (see Figure 4(b), 4(c)). These storms were characterised by an abnormal presence of more positive electrical discharges than negative ones (see Figure 5(a)). Positive lightning was associated with convective cells in the mature phase of development. These storm cells were overrun by the dark (dry) area of the midupper-level trough at that time. Consideration should be given to the fact that the rearside of a mid-upperlevel trough is normally a dry area defined by relatively low potential temperatures at mid-upper levels. In addition, the slightly negative or zero synoptic mid- 195

6 F Martín, R Riosalido and L de Esteban Figure 5. Lightning map and conceptual models. (a) Lightning map detected from 0000 to 1200 UTC on 24 May 1993: positive (+) and negative (.). (b) Possible relationship between wind shear and location of negative and positive main charge centres. CG = Cloud-to-ground. Adapted from Takeuti et al. (1978). upper-level dynamic forcing of the short trough was not intense enough to inhibit convection, probably due to the moderate/strong atmospheric instability and the existence of some kind of mesoscale lifting. To the contrary, no convective activity developed ahead of the trough where mid-upper dynamic forcing exists. These circumstances must not be overlooked because some ingredients were acting at that time. (a) Convective instability 196 Figure 6. Soundings on a skew T-log p diagram for 1200 UTC on 24 May 1993 for (a) Madrid and (b) Zaragoza. The vertical temperature and dewpoint profiles are in heavy solid and dashed lines, respectively. Thin lines show the surface lifted parcel from LFC and LCL. Numbers next to the plotted winds are actual wind speed observations in kn. Some instability indices are given at the bottom of the diagram. The dry-tongue at mid-upper levels overran areas in which diurnal heating and low-level warm advection were significant (see Figure 2(c)). These events produced an increase in convective instability (Carr & Millard, 1985) due to differential advection processes: areas of high potential temperature at low levels overrun by areas with lower potential temperature. The result would be an increase in the lapse rate. Note that the stability parameter showed in Figure 2(c) is the static stability parameter σ (see Holton 1979, pp. 131 and 137 for its influence on quasi-geostrophic forms of the omega and height tendency equations). This physical parameter is very useful as a diagnostic tool for cyclogenesis (e.g. see Smith & Tsou, 1988; Tsou & Smith, 1987) but it may be used as a convective forecasting tool as well. In both cases, large and subsynotic forcing mechanisms for vertical motion are more effective in a less stable environment (smaller σ). (b) Significant vertical wind shear The substantial presence of positive lightning can be explained by the conceptual model shown in Figure 5(b), in which the wind shear effect tends to separate the main centres of negative and positive charge. Vertical wind shear was later confirmed by the sounding data from Zaragoza (see Figure 6 (b)). There were southeasterly or southerly winds at the surface, veering to southwesterly in the mid troposphere. In this condition there might be sufficient environmental shear present in combination with some minimum value of buoyancy, as pointed out Weisman & Klemp (1986), for the production of severe storms.

7 (c) Lifting processes It is well-known that synoptic-scale vertical motions typically do not provide the lifting necessary to initiate convection, see Doswell (1987) and D95. Often the required lift is associated with mesoscale processes and they are very difficult to evaluate and forecast operationally using standard observational data. In this case there was evidence of mesoscale ascent because the first convective cells developed ahead of the low-level cloud band when the solar heating was very effective. It was likely that a new shallow converge zones appeared at the right edge of the cloud area, associated with the surface boundary due to differential heating process between cloud-covered and clear sky areas. Observational evidence is provided by the METEOSAT VIS image (see Figure 4(c)). During the warm season and daytime, large temperature gradients develop over land close to the low-level cloud edge. In addition, a shallow circulation is established perpendicular to the cloud edge with ascending flow over the cloudless area and warm sector. This mesoscale lifting process might release the convective instability and produce thunderstorms (Purdom, 1982; Kurz, 1984). It is worth noting, from a synoptic viewpoint, that it is very common to observe that over Spanish latitudes persistent or intense low-level warm thermal advection is occasionally an atmospheric factor more important than mid-tropospheric differential vorticity advection in generating ascents that trigger and organises the convection. Spanish forecasters tend to pay attention not only to 500 or 300 hpa vorticity configurations but also to the strong and/or persistent low-level warm thermal advection. In turn, this mechanism produces a significant increase of conditional instability, as noted by Maddox (1982). These synoptic processes were going on during this day. As mentioned above, additional problems emerge when operational forecasters try to evaluate the mesoscale lifting needed for convective initiation. This task is not easy using routine data from mountainous regions like the IP where the density of surface observations is insufficient. In our case the mesoscale lifting processes had to be strong enough to generate convective activity over a region behind the short mid-upper-level trough, and so eliminate its slight negative dynamic forcing. Occasionally, adverse convective phenomena develop over the IP and surrounding areas within a mid-upperlevel ridge or even behind a weak upper-level trough. In these cases the role of low-level warm thermal (and moist) advection, diurnal heating, terrain-induced front or boundary, etc., are crucial for convection initiation. (d) Moisture distribution The existence of a low-tropospheric moist layer and generally dryer air aloft give a favourable environment for the potential development of severe storms. In this situation, the mid-upper dry zone was sustained by the dry-tongue associated with the mid-upper-level trough. The Madrid sounding at 1200 UTC (see Figure 6(a)) confirms the presence of the dry layer at midupper levels, as opposed to the Zaragoza sounding (see Figure 6(b)) that shows the arrival of the moisture associated with the short trough. At low levels, there are important differences in the humidity content across the boundary. Whereas Madrid showed a low-level moist layer (left side of the boundary), the Zaragoza sounding had an onion-shaped profile (Miller, 1972) at the same level. A complete onion-like shaped sounding appeared over the Sigüenza area (right side of the boundary) when it was overrun by the dry tongue at mid-upper levels. This kind of T T d vertical profile is very useful for the identification of an environment that can produce severe storms, if other positive ingredients exist at the same time. All of the above-mentioned elements favoured the development of potentially severe storms rather than storms associated with high values of precipitation efficiency (i.e. the ratio of total precipitation reaching the surface to the total input of water vapour to the storm). For more details of this topic, see D85, pp Analysis of Madrid radar data The Sigüenza tornado: a case study The Madrid radar is located in the south of the province. A short description of this C band radar can be found in the COST-75 Reports (Aguado et al., 1995). The radar gets volumetric polar data every 10 minutes in Normal mode. This is used to produce a Cartesian volume by means of a four-point interpolation technique. Ground-echoes are eliminated by a ground-echo mask technique. Its spatial resolution is about 2 2 km 2 in Normal mode. When convection begins to show significant development and organisation, remote sensing data are crucial for understanding what is happening. In particular, the use of radar data provides the possibility of analysing three-dimensional structures, which is extremely important for detecting potentially severe cells (Lemon, 1980; D85) Detection and evaluation of the first echoes aloft At INM it is recommended that images of Zmaxhor/Zmax-ver (ZMAX) are used. This consists of the horizontal and vertical projections of reflectivity maxima in the horizontal (Zmax-hor), and north south and west east planes (Zmax-ver). The process is as follows: From the Cartesian volumetric data and for any point (x, y) the system finds the maximum of reflectivity along the vertical coordinate (z). 197

8 F Martín, R Riosalido and L de Esteban Figure 7. Zmax-hor/Zmax-ver for the Madrid radar at 1820 UTC on 24 May Sigüenza (S), Madrid (M) and radar site (R). BSL means Broken Squall Line. Figure 9. Zmax-hor (dbz) and radar vertical cross-section (dbz) image of the potentially severe thunderstorm at 1900 UTC on 24 May The cross-section is along the plane of mid-level wind direction. Z (dbz) scale as in Figure 7. S represents the town of Sigüenza and the white dotted line is the cross-section plane from the radar site (outside the figure) and the convective cell which affected the city. 198

9 The Sigüenza tornado: a case study Figure 8. METEOSAT enhanced IR images over the Sigüenza area at (a) 1800, (b) 1830, (c) 1900 and (d) 2000 UTC on 24 May (e) For 1930 UTC, showing the V shaped feature and brightness temperature contours (solid lines in K/10 every 10 degrees). The coloured enhancement from 32 ºC (orange) up to 68º (black), changes every 4 degrees according to the coloured scale in panel (a). S = Sigüenza. 199

10 F Martín, R Riosalido and L de Esteban This maximum value of reflectivity is projected onto the horizontal plane (X, Y) giving the Zmax-hor image. The same processes are performed for the (Y, Z) and (X, Z) planes, generating Zmax-ver images. These images are displayed on the screen, so as to permit a quick view of reflectivity maxima and their heights. The main advantage of this regional surveillance product is that it provides a simple two-dimensional image for monitoring a three-dimensional volume of data. The Madrid radar initially detected potentially severe storms but they were isolated and poorly structured vertical cells, all of which were located to the east of radar coverage. Between 1740 and 1750 UTC, both the ZMAX and echotop images showed the incipient echoes in three north northeasterly to south southwesterly parallel lines close to the radar. The central line developed rapidly, absorbing the line to the right whereas the left line dissipated. Intense convective echoes aloft started to develop along that line at 1820 UTC (see Figure 7) showing extremely high average reflectivity values (50 dbz above 5 km heights) and echotops around km. The first indications of severe activity appeared at middle and upper levels as a consequence of strong updrafts, which are typical of deep convection Convection organisation in a mesoscale convective system: a broken squall line From 1830 to 1900 UTC, convective events occurred in an explosive manner. The following was observed. METEOSAT IR images showed rapidly and continued growth of the colder cloud top areas (see Figure 8(a) to (e)). The convective cells evolved to become a Mesoscale Convective System (MCS), according to the MCS definition related to IR satellite observations: a cloud system that occurs in connection with an ensemble of thunderstorms and produce a contiguous precipitation area on the order of 100 km or more at least one direction (see e.g., Houze, 1993, MCS chapter). The V shape feature became apparent as its size increased, as shown in Figure 8(e). Severe weather and V features appear to be strongly correlated because both are associated with strong updrafts and wind shear (Heymsfield & Blackmer, 1988). Radar observations showed four or five convective cells along the linear structure. All of them maintained their own identity for at least about three hours, showing a degree of internal organisation. As seen by radar, the MCS has a large linear structure similar to a broken squall line, according to the radar-based definition from Schiesser et al. (1995): two or more cell complexes are arranged in a line almost perpendicular to the apparent direction of movement of the whole 200 line. The 40-dBZ radar echo contours of individual cell complex are separated, and the size of an individual cell complex is similar to that an isolated one. At that time the crucial point was, therefore, to detect the degree of organisation and whether severe structures existed (multicells, supercells, etc.) according to their associated radar conceptual models. At 1840 UTC, the system had reached a greater size than that associated with a simple storm. According to radar observations, it measured approximately km from west to east, km from north northeast to south southwest and echotops of around 13 km were sensed. The amount of associated positive lightning even exceeding that of negative lightning at times, although in absolute terms the quantity of lightning was very low (see Figure 12 which appears later). If convection shows some degree of organisation in an MCS, then it is necessary to suspect that hazardous events may occur. The next steps will be to analyse the internal organisation of the cells Internal organisation in severe storms within the MCS Monitoring convective evolution, in larger and more complex systems, might be relevant for forecasting severe weather. In these conditions, radar data are crucial in identifying the three-dimensional structure of cells. They may, therefore, enable us to determine certain elements or features indicating severity. The highest reflectivity values (>50 dbz) of all cells were observed at mid-tropospheric levels as a result of intense updrafts (the main component of severe convection is strong ascending airflow). Updrafts also affected MCS echotops which were higher than the surrounding cells. Although ZMAX is quite a comprehensive surveillance image at certain times and under certain conditions, specific vertical cross-sections are required to identify more highly structured features. The location and direction of the cross-sections must be based on the air motion at low levels (inflow direction) and airflow at mid-upper levels. On this occasion the last one was quite similar to the storm motion direction. Figure 9 shows a cross-section according to the mid-upperlevel wind direction. In this figure, the high and intense reflectivity cores behave as authentic obstacles to radar signals, so that shadowed areas are generated behind them according to the radial from the radar equipment (C band in our case and, therefore, susceptible to attenuation processes within deep convective phenomena due to high rainfall rates and hail). The details can be observed in the Zmax-hor plus vertical cross-section image of the tornadic convective cell, taken at 1900 UTC (see Figure 9). In this figure, another shadow may be observed associated with the

11 The Sigüenza tornado: a case study northernmost cell on the Zmax-hor image. Features related to severe cells may be identified by detecting potential elements according to available conceptual models (Chisholm & Renick, 1972; Lemon 1980; D85) such as overhang, weak echo region (WER), intense reflectivity gradients at low levels, presence or absence of a mesocyclone, etc. Another vertical cross-section has been taken for the same cell at 1900 UTC, but in this case using the inflow direction (see Figure 10, which represents the radar image from the lowest elevation angle). Some previously mentioned elements can be observed: overhang area, high echotops, high values of reflectivity, and vertical tilting of maximum reflectivity values at different levels. Unfortunately, some other structures are too small in relation to the resolution of the Spanish operational radar to be easily detected. This is accentuated by the specific nature of radar data, scanning strategy, signal processing and displaying, interpolation of polar volumetric data into a Cartesian reference system, distance and size of the structure to be detected in relation to radar, absorption processes, etc. This is the case with the possible bounded weak echo area, vertical and horizontal hook-like shapes, etc. The above considerations lead to the need to adapt radar cell conceptual models to remote-sensing data systems used in specific operational tasks. As an example, we can analyse a multicellular (or possibly supercellular) structure and consider how it is shown by the Madrid radar. It may be observed that certain similarities exist between the ideal model, on the left side of Figure 10(b) and the structure displayed by the Spanish system, on the right. Extremely intense and high reflectivity measurements, high echotops, and the presence of certain features relating to the overhang area are shown. On the other hand, other features are difficult to see, such as an existing bounded weak echo area, vertical hook-like shaped structures, etc. If we align the points associated with the reflectivity maximum, or echotop, of the new cell aloft and the maximum of reflectivity at low levels associated with the old cell, we should obtain the cell tilting. As suggested by Lemon (1977, 1980), this represents a change from non-severe storms, for which the echotop and maxima of reflectivity, at different levels, are quasivertical, as well as there being a low-level reflectivity gradient formed by the strong southeasterly inflow winds. The southwesterly mid-upper-level winds acted to separate the updraft and donwdraft, and in turn to produce some kind of internal organisation (D85). This apparent organisation associated with preferential development of the new cells lasted more than one hour and it was observed for the most active cells of the MCS. Referring again to Figure 9, it should be pointed out that the Spanish radars scan from top to bottom, which means that signals coming from upper levels might have been taken two or three minutes before those from the lowest levels. If these structures moved in a north northeasterly or northeasterly direction, this would mean that the lower area must have moved in that direction after data were recorded at mid to upper levels. The real tilting had to be greater than that shown by radar at the given nominal time. A detailed study of the cells comprising the MCS enables us to conclude that they had common characteristics: all of them were at least multicellular and potentially severe, which is quite significant in itself. For operational implications, it is important to note that these specific radar structures, as described above, such as tilting, WER, etc., were neither permanent features nor readily observed. But for all cells the radar showed strong and deep radar structures with a preferred location for the generation of new storms on the right flank of the MCS, suggesting some kind of internal organisation Severe cell dissipation and collapse stage Referring to Figures 9, 10 and 11, we can observe how the system evolved until 1930 UTC, just prior to the Sigüenza tornado. It is during the dissipation phase or when certain multicellular structures collapse that the most severe weather conditions, and in particular tornadoes, may occur on the ground (D85). This is exactly what happened. At approximately 1930 UTC one of the most active cells, located at the southernmost portion of MCS and close to Sigüenza, apparently lost its organisation. ZMAX images, as well as cross-sections, showed how significant elements evolved: vertical organisation disappeared, and upper and high reflectivity values dropped toward the ground. Those events occurred minutes before the tornado touchdown appeared. Currently it is not easy to safely predict this phase at the INM. If supercell structures existed, Doppler radar data should have provided the mesocyclonic features and how it was descending from mid levels to the ground. But even using Doppler information, the distance between the radar site and tornado (more than 110 km) was not likely to be suitable for detecting and monitoring it. In any case we may hypothesise what might be occurring around 1930 UTC. The internal and external equilibrium among updrafts, downdrafts and gust fronts which existed with the storm s environment disappeared due to some of these factors: the updrafts were too strong to be shifted by the environmental shear, weakening low-level inflow, etc. If the storm cell had a supercell organisation, the probability of a tornado was now at its greatest. According to Lemon (1980) and D85, the final stage of supecell (echotop collapse) might be reached in that time: there are no indications of 201

12 F Martín, R Riosalido and L de Esteban Figure 10. Squall line and severe storm details at 1900 UTC on 24 May (a) Plan Position Indicator, PPI (dbz) and radar vertical profiles (dbz) close to the severe storm. 1 and 2 represent the vertical profiles of the old cell and the new cell aloft, respectively. (b) Vertical section of an ordinary multicell storm normal to the plane of the storm motion. The image on the left is for the ideal case (from Chisholm & Renick, 1972) and that on the right is as seen through INM radar. T marks the tornado location. Overhang (O), Weak Echo Region (WER) and strong gradient of reflectivity (G). Z (dbz) scale as in Figure 7. Figure 11. Squall Line PPI and dissipation stage of the severe storm at 1930 UTC on 24 May 1993 for (a) PPI (dbz) and (b) the vertical section normal to the plane of the storm motion (as in Figure 10(b)). Z (dbz) scale as in Figure

13 The Sigüenza tornado: a case study Figure 12. Electric life cycle of the broken squall line from the Spanish Cloud-to-ground detection network in terms of the flash rate per five minutes. strong updrafts, decrease of reflectivity gradients, lowering of the echotop begins and transfers to over the echo core, etc. As a result the tornado affected Sigüenza. Some indications from the radar data confirm the previous ideas (Figure 11). Another explanation might be possible using the Wakimoto & Wilson (1989) conceptual model of nonsupecell tornadoes. Following their ideas, the collapsing cell produced a gust front outflow that triggered one or more new cells close to Sigüenza. After 1930 UTC explosive cellular growth might have occurred and the tornado might have developed below an explosively growing cell. Some indications supporting such a sequence are: The lightning rate increased after 1930 UTC (as will described in the section 5). Negative lightning is especially large, indicating that the shear effect is less important, possibly because the updrafts were too strong to be shifted by the environmental shear. Hail was reported to the northwest of the tornado (hail reports are not available in real time at the INM). But there was not evidence that these new radar cells originated from the dissipating cell, as expected from this conceptual model. Notice that the distance between the radar site and Sigüenza is more than 110 km and these radar-based features could be difficult to sense. The tornadic cell disappeared after 1950 UTC. The colder cloud top areas of the MCS decreased after 1930 UTC but the warmer ones spread out for a short period of time. Later on, just one convective core (>40 dbz) was observed at 2020 UTC, and it was embedded in a larger precipitation zone of the old MCS. As mentioned above, the amount of positive lightning was abnormally high compared with the quite limited amount of negative lightning, just prior to the tornado touchdown. Moments before the tornado appeared lightning activity decreased drastically and later resumed with negative overwhelming positive lightning just before 1930 UTC, as shown in Figure 12. Nevertheless, it is necessary to explain why there was so little electrical activity sensed by the Spanish lightning detection network. 5. Squall line electrical life cycle Other data that forecasters should consider when analysing convective phenomena is information provided by the lightning detection network. Unfortunately, conceptual models associated with the electrical life cycles of thunderstorms are not as reliable as those associated with radar data. With the INM lightning detection network, just a portion of the discharges information is available: Cloud-to-ground lightning (CG) but not cloud-to-cloud lightning (CC). With respect to severe storms, conclusions are based on partial and specific results of tests carried out in other countries. These can be summarised as follows: Vertical wind shear favours the appearance of relatively larger amount of positive rather than negative lightning even in absolute terms. This applies not only during the dissipation phase but also, and more importantly, during the phase in which the first lightning related to convective cloud development appears. This anomaly could suggest the existence of shearing that may promote severe weather conditions in the event that other components also inter- 203

14 F Martín, R Riosalido and L de Esteban vene (MacGorman et al., 1989; Ziegler & MacGorman, 1994). CC discharges are more frequent than CG ones, particularly in severe weather conditions (MacGorman et al., 1989; Richard, 1992). There have even been cases of no detection of CG lightning in convective development of severe storms with a high rate of CC. The lack of CG lightning activity in extremely intense convective cells may therefore suggest that a substantial part of electrical activity generated by such systems is redistributed throughout the same cloud or clouds that make up the system through CC discharges. Severe weather conditions are normally accompanied and/or preceded by a substantial decrease in lightning activity, which is normally low in any case. The theoretical explanations based on such events suggest that the extremely strong updrafts that exist in this type of system may lift a large volume of precipitation up to middle levels; this produces rapid and continuous charge electrification/generation processes, taking place high above the ground. The centre of negative charge is then located close to that of positive charge, whilst both are vertically separated, as shown in Figure 5(b). The result is that CC discharges are extremely high whereas the CG lightning rate is very low. The existence of a mesocyclone embedded within the system can even further lift up such centres with a subsequent predominance of CC discharge. As an example, Figure 12 depicts the time evolution of the CG lightning rate related to the squall line (not to the cell generating the tornado). This shows that there is more positive than negative CG lightning in the mature phase and a significant minimum just prior to the tornado touchdown. Notice there are some other maxima and minima on the graph, but this kind of information was not relevant for discriminating between a severe and a non-severe event, as pointed out by Reap & MacGorman (1989) and Bracnick & Doswell (1992). Those climatological and case studies indicate that lightning data must be used with caution for severe weather conditions and additional studies are required. For this reason the current CG lightning detection data are not as valuable an observational tool as radar data in severe weather. However, it can be used to complement the radar information and to confirm the existence of electrical activity. 6. Discussion and conclusions In this paper we have studied, from the operational viewpoint, an atmospheric situation over the east of the Iberian Peninsula leading to severe convective storms. For this reason we have not focused on a specific type of data (NWP fields, radar, satellite, etc.) but rather upon the information used by Spanish forecasters in their daily tasks. This tornadic event represents the first 204 documented case study using the range of observational data and tools available at the INM in Two aspects have been emphasised within the paper. The first one is related to the concept of the forecasting based on ingredients (D95). This methodology has been tested for severe storm development using the known basic physical processes by which severe storms are produced: buoyancy, vertical wind shear, dry lower mid tropospheric layer and lifting mechanism for predicting severe storms. A quantitative approach has been adapted. The second one is particularly associated with the use of radar-based conceptual models and their application in real time using an operational radar system for monitoring severe convection. Turning to the first point, we have noted that the synoptic background may be considered as a common feature in this period of the year for the Spanish forecasters. In quite similar patterns, convective developments may frequently appear generating non-severe storms or/and severe events. A major challenge emerges when the forecasters must discriminate between these events and identify potential conditions that may produce lifethreatening situations. We have applied the ingredients-based methodology as a valuable operational approach for predicting severe thunderstorm development. These ingredients must be brought together by atmospheric agents or systems (large-scale and mesoscale disturbances) in the same place and time for the development of severe storm types. As noted by D95, if any of the ingredients are absent, then other types of convective phenomenon may develop. The ingredients for severe conditions are the same but the atmospheric agents supporting them may appear within a broad spectrum of atmospheric disturbances. In this case study, some ingredients may be slightly simulated using the LAM, such as wind shear, moisture distribution and instability areas. On this occasion, low-level warm thermal advection was an important factor for destabilising some portion of the atmosphere over the IP. Subsynoptic elements may be revealed or confirmed by remote-sensing data, radiosonde data and conventional surface reports. In that way WV imagery offered a dry pre-environment at mid level when its dry portion overran the instability areas where the solar heating was very effective. The appropriate vertical moisture distribution and wind shear were supported by the sounding data from Madrid and Zaragoza. The synoptic lifting mechanism was apparently poor, or even negative, behind the moving short-wave trough. Anyhow, convective developments occurred with more positive CG lightning discharges than negative ones. This was a possible indicator that the mesoscale lifting processes had to provide the lifting needed for convective initiation and, probably, the vertical wind shear was intense enough for separating the charge centres at the mature stage of convection.

15 Apparently this was not an ordinary convective day. All ingredients seemed to be in place and the first convective cells developed within a severe potential environment in a specific region of the IP. In the last portion of the paper, we focused on monitoring and detecting some features and patterns associated with severe storms. Remote-sensing data are vital for this purpose. In particular, the vertical structure of radar cells is crucial for evaluating the degree of their organisation: intensity and height of first echoes aloft, echotop heights, etc. The role of the radar-based conceptual model has been emphasised for interpreting the large quantities of data that the forecasters have to face. Some differences emerge between an ideal radar-based multicell conceptual model and the cells as seen through an operational system, such as the Spanish one. This is partly due to the scanning strategy, interpolation method, ground-echo mask processing technique, distance between radar and targets, etc. As has been pointed out previously, some radar-based severe storm characteristics were neither permanent nor readily evident through the life cycle of the convective cell, such as overhang or cell tilting. But the magnitude and intensity of reflectivity at the mid-upper portions of convective thunderstorms were very persistent, patent and crucial for the ready detection and assessment of severe weather potential. These last features are more relevant than the previous one from an operational viewpoint for the Spanish radars and in a complex topographical region. Special mention should be made of the fact that many forecasters are not confronted with this type of atmospheric situation every day of their operational lives; severe storms are uncommon phenomena. Therefore, the ability to put all the pieces of the puzzle together to explain and evaluate what and why is happening in the atmosphere it is quite a difficult operational task. Consequently the INM is putting significant effort into running training courses for operational forecasters about hazardous weather prediction, not only related to heavy rain or flash flood events but also severe phenomena. Ongoing studies of tornado climatology are being conducted in some regional meteorological centres and their results help us realise that tornadic events are much more common in our latitudes than we thought. Acknowledgements Special thanks go to anonymous reviewers of this paper. The authors found their suggestions very helpful and they provided numerous invaluable comments and ideas that enhanced the document considerably. Some figures were obtained through the helpful co-operation of Maria Teresa de las Heras, Alicia Bejarano, Estrella Gutierrez, Fernado Aguado and José L. Camacho. 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