SIMULATING CONVECTION AND LIGHTNING OCCURRENCE: MICROPHYSICAL ANALYSIS OF AN EXTREME HAIL-STORM

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1 SIMULATING CONVECTION AND LIGHTNING OCCURRENCE: MICROPHYSICAL ANALYSIS OF AN EXTREME HAIL-STORM C. Adamo, C.M. Medaglia, S. Dietrich, A. Mugnai ISAC CNR, Via Fosso del Cavaliere 100, Roma, Italy ABSTRACT We use the 1.5 D Thunderstorm Model Tenebrous, developed at University of Washington, to simulate the convective part of the 3-4 August 2002 event and the associated electrical activity to infer microphysical cloud properties, together with the mesoscale model MM5 to represent the development of the system. Microphysics of strongly convective clouds are, for several reasons, the most difficult to reproduce in simulations and to observe directly. In such a context, lightning flash rate (from ground based lightning sensors), cloud reflectivity (from C Band ground radar) represent means to probe the modeling results. We present the key study of the 3-4 August 2002 event on the Po Valley. This is one of the areas of high occurrence of hail damage together with southern France, Switzerland, southern Germany, Austria, Hungary and the Caucasus region. Due to its particular geographical situation, surrounded on three sides by high mountains, the Po Valley is an area with high humidity and rather light winds at lower atmospheric levels, which provides favorable conditions for the formation of line storms and Mesoscale Convective Systems (MCS). According to the static stability criteria, the lower troposphere in the Po Valley is, on average, markedly unstable during summertime afternoon and evening hours. However, dynamical forcing, induced by synoptic or mesoscale disturbances, plays an even more important role than purely thermodynamic causes in the triggering and maintenance of thunderstorm activity in northern Italy. The night-time hailstorm of Sunday, 4 August 2002, is a good example of a synoptic disturbance combined with the polar jet stream triggering the formation of deep convective storms in northern Italy. 1. INTRODUCTION It has been established in laboratory experiments that, at the current time, charge separation via the noninductive charge transfer is the dominant means of charge separation (see section 2). This mechanism is an extremely strong function of conditions within the charging zone (such as the distribution of large and small ice, liquid water and dynamic aspects such as updraft velocity). We would like to understand, that given the strong relationship between charging (lightning occurrence) and microphysics. For this issue, we discuss about the use of an explicit microphysics thunderstorm model (EMTM) in conjunction with a mesoscale model (MM5) to obtain a large collection of lightning, precipitation and microphysical profiles. As the mesoscale model does not explicitly treat microphysical quantities, the 1.5 Dim model can better determine the relationships between microphysical parameters (e.g., ice and liquid water content, hydrometeor size and distributions obtained from the its output) and represent the vertical microphysical structure of lightning producing clouds within mesoscale models or nowcasting when lightning observations are available.

2 2. THUNDERSTORM MODEL FOR THE CLOUD ELECTRIFICATION Thunderstorm electrification has a microphysical origin since the dominate source of in-cloud charge is the result of colliding ice particles. Rimed ice particles rise and grow within convective updrafts. These rimed particles collide with smaller ice particles rising in the updraft and, typically, the larger graupel particles charge negatively while the ice-crystals positively. However, the sign and charge is actually a strong function of the liquid water content, particle size and temperature. The region in which the charge transfer takes place is delineated by approximately the -5ºC and -25ºC isotherms and is referred to as the charging zone. Larger particles remain suspended in the updraft and fall out when their terminal velocity exceeds the updraft while the lighter ice particles are lofted to the upper regions of the cloud. The charge is then separated, as a result of differing fall velocities of the charged ice particles, and an electric field is established within the cloud. If the in-cloud electric field is greater than a threshold (approx kv/m) lightning is initiated. Modelling results illustrate the relationship between lightning and cloud microphysical properties. Relationships between lightning and microphysical parameters as the maximum updraft velocity at the charging zone boundary and as the peak liquid water flux into the charging zone are shown in Solomon and Baker (1998) and, with the ice crystal concentration in the charging zone, in Schroeder (2000) illustrating a strong dependence between lightning and ice content, updraft velocity and liquid water which can be useful in the retrieval of cloud profiles from remote sensing sources. To understand the physical mechanisms operating to produce this storm we used the EMTM Cloud Resolving Numerical Study (M.B. Baker and R. Solomon, 1997, 2000). EMTM models the electrical parameters electrical microphysics within the convective area of a cloud. The model consist of 3 cylindrical regions and includes dynamics, entrainment, explicit microphysics, electrification and a lightning parameterization. The explicit microphysics is required in order to include a charge transfer mechanism that is dependent on particle size (Saunders et al, 1991). EMTM is initialized with an environmental sounding which includes temperature and dew-point temperature as functions of pressure. There are a number of additional input parameters that are based on local environmental conditions and are used to initialize the calculations in the various components that make up EMTM. 3. METHODOLOGY We have the possibility to initialized EMTM with the modeled soundings taken from the output of MM5 (using the inner grid, resolution 10 km). The rational behind this comes the necessity to initialize the EMTM model with the environment sounding that is representative of the environment when the storm occur. The only actual soundings are available at two stations (Udine and San Pietro Capofiume) which have a limited temporal resolution (12 hours) and may be located many kilometers from the location of interest. Using the ensemble of MM5 soundings we initialize EMTM to model the convective cells recognized from the mesoscale models and we also could follow the movements of the cells. In this scenario, we had the chance to analyzed the temporal and spatial changing of the convective cells and looking the microphysical development of the thunderstorm. All the simulations for the convective cells give us an ensemble of microphysical profiles with the lightning occurrences for different kind of simulated cell. Combining all the simulations, we have an ensemble of cloud property profiles for many types of convective situation that occurrence during this event: deep and shallow convection and those clouds that did and did not produce lightning. MM5 setting The Fifth-Generation NCAR/Penn State Mesoscale Model is the latest (waiting for WRF) in a series that developed from a mesoscale model used by Anthes at Penn State in the early '70's. For the presented case, MM5 runs are initialised with the data of ECMWF Toga Archive as a first-guess. Two domains are implemented to obtain higher resolution over the Friuli area without increasing too much computational model time. The mother 54x64 grid point domain, with 30 Km resolution, cover Alps area, North and Central Italy. The inner 25x25 grid point, centered on Fossalon di Grado, Friuli, covers the Radar sounding area with 10 km resolution. The inner grid interacts with the mother domain by a two way nesting strategy

3 4. MODELED MICROPHYSICS RESULTS This section is dedicated to the modelled microphysics results obtained from the use of EMTM in conjunction with the MM5 mesoscale model wherein the EMTM is initialized with values obtained from MM5 at various locales to obtain a large collection of lightning, precipitation and microphysical profiles. We have done a deep study using EMTM over the Po Valley case (4-5 August 2002). In particular, we focus our study over the Friuli area to validate our results with the radar and ground based lightning network. In fact, output from the EMTM has been validated with radar and lighting data to insure the modeled storms are consistent with the actual storms (fig.1). Note that the model produces intra-cloud and cloud to ground, instead lightning data measured from ground base network and are only cloud to ground. The model lightning compare very well with observations, in both cases showed in Figure 1, as well when we don t have a large amount of lightning as when we have a considerable amount of lightning. Figure 1. Actual Lightning flash rate from data (dashed) and model (solid) for two different examples. For both panels, x-axis represents the Flash-rate (lightning/min) and y-axis the time (sec). The convective cell that we reproduce is the one on 4 August 2002, from to 21 UTC (left) and from to UTC (right) on the North East of Italy. Vertical profiles of all microphysical quantities are extracted every 100 seconds and associated with the corresponding flash rate at that time for a total of 1000 vertical profiles throughout the life time of each of the 20 simulated clouds. All of these modeled results are combined and categorized by the lightning flash rate, F [#/min]: 1<F<6, 6<F<12, 12<F<18, 18<F<24 and 24<F<30. Figure 2 gives the modeled reflectivity profiles for each of these regimes. There is a marked distinction between each of these profiles with in that the higher the flash rate the greater (through out the vertical) the reflectivity.

4 Figure 2. Vertical profiles of reflectivity (dbz) (left panel) and standard deviation (right panel) (dbz) versus altitude (m) for various lightning flash rates, F #/min: 1<F<6 (leftmost solid line), 6<F<12 (rightmost solid line), 12<F18 (dashed line), 18<F<24 (dotted line) and 24<F<30 (dot-dashed line). These results are also in good agreement with our previous study (Adamo et al., 2001). In these observational studies, lightning flash rate (obtained from the Lightning Imaging Sensor) and the vertical profiles of reflectivity (from the Precipitation Radar) show strong relationships between the lightning intensity and differences in the vertical makeup of lightning producing storms. In addiction we define a non dimensional index to analyze these simulations: where CAPE I = 2 v CAPE Zct Zcb g ( Tv,ad Tv,env ) dz T v, ad (EQ 1) (EQ 2) where T v,env and T v,ad are the virtual temperatures in the environment computed from soundings along the reversible moist adiabatic through cloudbase at Z cb. Environments with low level of CAPE had relatively few cloud-to-ground lightning flashes. High CAPE environments produced much more CG lightning. I is the ratio of CAPE (convectively available potential energy) and the applied forcing, so it is gives an idea of the sensitivity of the output on the sensitivity between the environment energy and the applied energy. Using the values shown in Table 1, we have plotted, I as a function of the flash rate. In the Figure 3, we observe this plot; one can see that lightning flash rate is maximized for 1 x 10 3 < I < 2 x 10 3.for all the simulations of the Po Valley case. In this range the lightning occurrence tends to be maximum and if we force the model with higher value of v the lightning occurrence decreases. We explain the physical reason for that taking into account the times of permanence of the water droplets and of the graupel in the charging zone.

5 date 4 August (real) 4 August (MM5) 4 August (MM5) 5 August (MM5) 3 August (MM5) Cloud base press mb CAPE (J/kg) CAPE C.Z. (J/kg) Cloud base Temp ( C) Table 1. Cloud base pressure, CAPE, CAPE in Charging Zone and Cloud Base Temperature, for each sounding used to initialized the EMTM. Figure 3. Index I as a function of modeled lightning flash. For different soundings used. In the table 1 there are the CAPE CZ (charging zone), that are the values of the CAPE for that portion of the cloud. The charging zone is the zone in which the charge is separated, it is limited from range temperatures: 5 C and 30 C. We can note from the soundings showed before that in our regions the charging zone has a vertical extent of about 4 km, going from 4 km of height to 8 km. The ratio between the CAPE in the cloud (between the cloud base and the top) and the portion of CAPE only in the charging zone is, for these clouds in the Mediterranean, about 2 (Figure 3). This is a value that could be typical of the tropical clouds that however exhibit much more water content, and so much more lightning. In order to obtain microphysics relationship on this region, we analyzed modeled Liquid Water Flux as a function of the maximum updraft in the simulation, for the ensemble of runs on Po Valley. In Figure 4 diamonds represent no producing lightning storms, the asterisks the producing lightning storms. In this case the wpeak is referred to the maximum value of the vertical velocity during all the temporal range of the simulation, and the liquid water flux has been computed as the flux between 4000 m and 8000 m (the estimated charging zone range). We observe a linear relation between Liquid Water Flux (in the charging zone) and maximum updraft value; it s because this storm have the same nature. For those runs in which we use strongest kinetic force, we obtained strongest updraft s values, some of them are bigger than 30 m/s. Note that these runs don t always produce very much lightning, because the updraft is too strong and doesn t allow particles to stay within in the charging zone for a long period of time. This in turn reduces the amount of the particles interest in the charge separation mechanism resulting in a net reduction in separated charge.

6 From the Figure 4 we can observe that there are three different zone: the first one, delimited by the maximum updraft is higher than 16 m/s and the liquid water flux in the charging zone is more 13 g/m 2 s in which we always have found lightning producing storms, the other with LWF between 7 and 13 g/m 2 s and W peak is between 9 and 16 m/s in which there can be conductions to have lightning or not, and the third region in which we never observe lightning with low LWF (less than 7 g/m 2 s) and low updraft (less than 8 m/s). Figure 4. Modeled Liquid Water Flux as a function of the maximum updraft in the simulation, for the ensemble of runs on Po Valley. The diamonds represent no producing lightning storms, the asterisks the producing lightning storms Available Supercooled Water Figure 5. Charge Transfer: Laboratory Results from Saunders et al, 1991: The region with the symbols + is the region in which the charge transferred to hail is positive, in the region with. the hail is charged positively.

7 For the second region there could be many factors that determinate the occurrence of lightning. To better understand this we can refer to the Saunders parametrization (Figure 5). In this region, the charge transfer may be taking place under conditions where some particles charge negatively but near by, spatially in the vertical, other particles can positively (see regions remarked with dashed circles shown in Figure 5). It depends from the size of the particles and from the temperature. For the storms in the region with lighting in Figure 4, the charge separation conditions corresponds with the white area in Figure 5, in which typically graupel is charged negatively and ice crystal positively. Another considerations is that the rate at which liquid water is depleted within the charging zone. As the amount of liquid water approaches zero, charge separation essentially approaches zero also. Figure 6 also shows that the total ice concentration within the clouds increases with increasing flash rate. Not a completely unexpected outcome as the amount of charge generated is a strong function of the ice content. Figure 6. Integrated columnar ice content (# cm -3 m) versus flash rate (#/min). Dotted line is the standard deviation. Figure 7. Flash Rate (#/min) and Precipitation Rate (mm/hr)

8 Figure 7 shows the flash rate (#/min) as a function of the precipitation rate (mm/hr). The modeled rain rate and the modeled flash rate are taken at the same instant. It becomes quite apparent that it is difficult to find a universal relationship between instantaneous lightning flash rate and rain rate. The peak lightning flash rate and peak rain rate show variability from storm to storm. This study shows that the presence of vary many lightning can not be taken as a presence of high precipitation, so, the use of lightning flash rate as a surrogate for precipitation rate on a storm-by-storm basis requires care. Rather, as Figure 6 suggests, total lightning number is better correlated to the amount of ice crystal concentration in the column. 5. CONCLUSIONS Microphysics of strongly convective clouds are, for several reasons, the most difficult to reproduce in simulations and to observe directly. As this modeling study and the observational studies mentioned previously have shown, lightning can provide useful information about the microphysical characteristics of thunderstorms especially in lieu of other direct observations from radar and/or remote sensing. This is especially true of storms in the Mediterranean area where lightning producing storms which are a small fraction of all precipitating storms are responsible for the majority of rainfall as we found in previous work (Adamo et al., 2003). The EMTM is a very good tool for the study of electrified cloud with its use of an explicit microphysical parameterization. Future work will include more automatic implementation/coupling of the MM5 model with the microphysical parameterization of the EMTM. At some point in the not so distance future, with increased computing power and multi-processor machines/clusters, mesoscale models such as MM5 should be able to overcome the limitations of bulk parameterizations and to make use of more explicit schemes utilized by the EMTM. In the recent years ground base lightning networks are developing everywhere in the world, using different kinds of sensors covering most of the world. Because of the continuous monitoring of lightning from these ground based networks, we can follow the fronts of the storms, and in addition, we can understand the nature of the storm and the microphysics related with lightning occurrence, by just knowing the flash rate. NASA decided to place Lightning Mapper Sensor on the next geostationary satellites (to be launch around 2010) as Hugh Christian proposed (Christian, 1998, Christian et al., 1989). This instrument has been projected by the the NASA space born lightning detection program at the Marshall Space Flight Center (MSFC) in Huntsville, AL, the same team who projected the LIS. It is planned to launch this sensor on board of the new GOES-R satellites, for geostationary detection of lightning over the American continent. The goal of the Lightning Mapper program is to place a sensor, capable of continuously mapping lightning discharges during both the day and night, with a spatial resolution of 10 km, in geostationary orbit. In a geostationary orbit, the Lightning Mapper Sensor will be capable of detecting and locating both cloud-to-ground and intracloud discharges with high spatial resolution and detection efficiency, i.e., detect and locate lightning with a storm-scale resolution over large areas of the Earth's surface. Because the relationship between lightning and other physical parameters, that we show in this work, and because many other reasons (severe storm detection and warning lightning, flash floods, tornadoes, hailstorms, and downbursts ; convective rainfall estimation; storm tracking; aviation hazards, improvement of long-term forecasting by quantifying lightning activity for the time of day, season, location, and storm type.),the advantages of this continuous lightning coverage is evident. The question is: why should Europe be left behind? The European Space Agency is thinking about a similar project (GOMAS; Geostationary Observatory for MW Atmospheric Sounding), but the development of the lightning sensor doesn t seem likely. However, we strongly fell that it will be extremely useful. It has to be remarked that the advantage of the satellite perspective is enormous because there is the capability of registering intra-cloud (IC) strokes. In such a context the satellite perspective has the advantage to provide more information. But on the other hand, also, the inclusion of ground based lightning detection (only CG) is important too because it can provide a constant coverage of electrical/microphysical evolution. The ground based lightning network, in turn, are used, to help to create a database of microphysical properties via numerical modeling to be used for a multi-sensor retrieval algorithm. For future works, if these information will be considered together, it has to remember that the flash rates considered are different. For this issue,

9 the ratio between the IC/CG is very important to be known. This number changes with many factor; the average number for our area was about 2 from modeled studies (Adamo 2004) but it can change a lot. In addition, the usefulness of lightning data to better facilitate cloud retrieval methods based on microwave and VIS-IR observations remains very promising. Criteria for characterizing cloud types based on lightning flash rate can be used to augment the identification of precipitation systems via VIS-IR geostationary satellites. Geostationary satellites, which allow rapid measurements of the space-time development of cloud systems and precipitation but are limited in their ability to distinguish precipitation types as they measure the upward directed radiation from the top of cloud systems. Microwave measurements are able to give a much better picture of the microphysical structure with the clouds although such platforms do not provide continuous coverage of precipitation systems, as do geostationary satellites. Algorithms provide a mechanism to use the rather infrequent passive microwave measurements in conjunction with geostationary VIS-IR observations to provide a more reliable determination of precipitation. However, an important consideration neglected by many cloud microphysical retrieval algorithms is the choice between utilizing those based on stratiform or lower rain rate precipitating systems and convective or high rain rate systems (especially for very severe storms) where climatologically based algorithms are optimized for the lower precipitation systems. For this, the inclusion of a lightning based criteria has the potential to better discriminate between stratiform and convective cloud radiation retrievals. 6. ACKNOWLEDGEMENTS The authors wish to thank, M. Bertato and R. Fabbo for assistance with the Fossalon di Grado radar data. Funding has been provided by the Italian National Group for Prevention from Hydro-Geological Disasters (GNDCI), and within the framework of EURAINSAT a shared-cost project (contract EVG ) cofunded by the Research DG of the European Commission within the RTD activities (5 th Framework Program). 7. BIBLIOGRAPHIC REFERENCES Adamo C., 2004 On the use of lightning measurements for the microphysical analysis and characterization of intense precipitation events over the Mediterranean area. University of Ferrara PhD thesis Adamo C., R. Solomon, S. Goodman, D. Cecil, S. Dietrich, A. Mugnai, 2003 :Lighting and Precipitation. Proceedings of 3nd Plinius Conference on Mediterranean Storms, Ajaccio (France). Adamo C., R. Solomon, S. Dietrich, A. Mugnai: Application of LIS data to the multisensor analysis of South Mediterranean severe storm microphysical structure. Proceedings International Lightning Conference Tucson-Arizona October 2002 Christian, H. J. (1998). LMS Mission and Science Requirements. Christian, H. J., R. J. Blakeslee, and S. J. Goodman The detection of lightning from geostationary orbit. J. Geophys. Res. 94, 13,329 13,337. Saunders, C.P.R., Thunderstorm Electrification Experiments and Charging Mechanisms. J.Geophys. Res. 99, Solomon, Robert and Marcia Baker, 1994: Electrification of New Mexico Thunderstorms., Mon Wea Rev, 122, Solomon, R. and M. B. Baker, Lightning Flash Rate and Type in Convective Storms. J. Geophys. Res. 103, Solomon R., C. Adamo, M. Baker 2002: A lightning initiation mechanism: application to a thunderstorm electrification model, C.R. Physique, Saunders, C, W Keith and R Mitzeva, 1991: The Effect of Liquid Water on Thunderstorm Charging. J Geophys Res, 96, 11,007-11,017.