Mediterranean Storms
(Proceedings of the 5rd EGS Plinius Conference held at Ajaccio, Corsica, France, October 2003)
 2003 by Editrice
RELATING CLOUD MICROPHYSICAL PROPERTIES AND LIGHTNING:
MODEL ANALYSIS OF AN EXTREME HAILSTORM.
R. Solomon, C. Medaglia, C. Adamo, S. Dietrich, A. Mugnai
(1) Istituto di Scienze dell'Atmosfera e del Clima (ISAC-CNR Roma), Via Fosso del
Cavaliere 100, 00133 Roma, Italy; robert@robert.ifa.rm.cnr.it
ABSTRACT
The University of Washington, 1.5-dim thunderstorm model (UWTM) is used to model
microphysical cloud properties and related electrical activities of convective cells
associated with the 3-5 August 2002 storm over the Po Valley (Northern Italy). Thee
MM5 mesoscale model, which has been used to analyze the development of this severe
storm, is used to initialize the UWTM at various locals to obtain a large collection of
lightning, precipitation and microphysical profiles for this event. The performance of the
models have been evaluated by comparing the results from lightning flash rate (from
ground based lightning sensors) and cloud reflectivity (from a C band ground based
radar). This study is important, due to the relationships between microphysical
parameters (e.g., ice and liquid water content, hydrometeor size and distributions
obtained from the UWTM output) to better represent the vertical microphysical structure
of lightning producing clouds within mesoscale models or nowcasting when lightning
observations are available.
1
INTRODUCTION
We present study of the case has been called “the Po Valley case” which had one of the
highest occurrences of hail damage together in 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 the 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.
We use a combination of modeling techniques to evaluate cloud conditions in these sever
thunderstorms relating modeled lightning characteristics to clouds microphysical
properties. In section 2 we briefly describe the models, sections 3and 4 outline the
methodology and results with conclusion presented in section 5.
2
NUMERICAL MODELS: MM5 AND TENEBROUS
There is a strong link between in cloud dynamic and microphysical properties and
lighting. Using this link between electrification and the occurrence of lightning, we
present a preliminary study where we utilize a simple 1.5 dimensional numerical model
with explicit microphysics, cloud electrification and a lightning parametrization coupled
with the MM5 mesoscale model.
2.1
MM5
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. In this model are used for the evolution of the basic equations a finite different
scheme and a time-split explicit method. Two domains are implemented to obtain higher
resolution over the Radar area (Fossalon di Grado – Gorizia (Italy)) without increasing
the computational model time too much. The mother grid point domain 27x32, with a 30
Km resolution, covering Alps area, North and Central Italy.
The inner 25x25 grid point domain (covers the Radar sounding area), with a 10 Km
resolution, interacts with the mother domain by a two way nesting strategy. In the
vertical direction there are twenty- three sigma levels. All the simulations are 60-hours
long, starting from the 00 UTC of 3 August 2002 and ending at 12 UTC of 5 August
2002. MM5 is initialised with data from the ECMWF Toga Archive and for boundary
conditions. Although in MM5 Several different physical schemes are available for
parametrization of PBL, radiative transfer, surface transfer, microphysics and cumulus
convection, for our MM5 run In the table below, we choose a set of fixed
parametrization:
2.2
The Thunderstorm Model: UWTM
We use the University of Washington, 1.5-dim thunderstorm model (UWTM), to
simulate the convective elements of the Po Valley case and to infer microphysical cloud
properties. The model consist of 3 cylindrical regions and includes dynamics,
entrainment, explicit microphysics, electrification and a lightning parameterization.
(Baker and Solomon, 1998, 2002).
UWTM is initialised 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 initialise the
calculations in the various components that make up the model. Whenever possible we
use observations of local conditions to set these parameters. For example, information on
storm duration, cloud radius, cloud base pressure and cloud condensation nucleus
concentration may be available from observations.
Dynamics
The dynamic routines calculate the advection of all particles, energy, water vapor and
charge. The equations used are described in detail in Taylor (1987) and were based on
Asai and Kasabara (1967) and Yau (1980).
Microphysics
Ice and water particles are classified by mass into 80 categories for each phase. The
routines accounts for drop formation, vapour growth, collisional growth, evaporation,
melting and glaciation, drop break-up. CCN and ice nuclei are assumed to be spherical
particles of radius 0.25 Mm. Initial ice crystal concentrations are determined by either the
Fletcher (1962) or Meyers et al. (1992) parameterisation. The Fletcher parameterisation is
temperature dependent while Meyers depends on the ice super saturation. Water and ice
particles grow by vapour deposition (Pruppacher and Klett, 1978) and collision and
coalescence. The 'continuous collection' approach is used to calculate the collection of
droplets by larger drops. Additional ice particles can also be produced by secondary ice
production; experiments by Hallet and Mossop (1974) suggest that under certain
conditions ice particles may shatter, ejecting small ice fragments. They found that this
secondary ice production occurs in the temperature range -8° < T < -3°C, peaking at 5°C.
Electrification
Charge separation is assumed to occur via the non-inductive charge transfer mechanism.
Laboratory observations (Takahashi, 1978; Saunders et al., 1991) show that collisions
between ice crystals and graupel particles result in the transfer of small amounts of
charge. The exact amount of charge transferred depends on temperature, liquid water
content and the size of the particles involved in the collision. Specifically, we use the
Saunders et al., 1991parameterisation for charge transfer. See Solomon and Baker, 1998
for more details.
3
METHODOLOGY
We have done a sensibility study using the UWTM over the Po Valley case. In particular
we focus our study over the Friuli area to validate our results with the radar and ground
based lightning network.
We have the possibility to initialized UWTM 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 UWTM 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 UWTM 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,
Output from the UWTM has been validated with radar and lighting data to insure the
modeled storms are consistent with actual.
4
RESULTS AND COMMENTS
Figure 1 illustrates a typical scene from the output of the UWTM. In the example shown
(this snapshot is after the mature phase of the storm) one can discern the region of
precipitation reaching the ground as well as some hail. The electric field at this time has a
peak value of –140 kV/m.
Figure1: Example of output from the UWTM model: The color scale is –30 m/s <
Vertical velocity < 30m/s and –250 kV/m < Electrical Field < 250 kV/m. For the
hydrometers the scale is logarithmic with yellow 10 -5 cm-3 to 103 per cm-3. The vertical
scale in all cases is altitude 0 to 16 km.
We conduct 20 simulations that are initialized with soundings taken from the interior grid
of a simultaneous of MM5. In all, four different locations taken at two different times
are used to model a variety of convective situations: deep convection with heavy rain and
a large amount of lightning and shallow convection with little or no lightning and weak to
moderate rain fall . 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 combine and categorized by the lightning flash rate, F
[#/min]: 1<F<6, 6<F<12, 12<F<18, 18<F24 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..
Figure 2: Vertical profiles of reflectivity (left panel) and standard deviation (right panel)
versus altitude 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).
Figure 3 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 3: Integrated columnar ice content (# cm-3 m) versus flash rate (#/min). Dotted
line is the standard deviation.
These results are also in good agreement with studies done by Adamo et al (2002, 2003).
In these observational studies, lightning flash rate (obtained from the Lightning Imaging
Sensor) and the vertical profiles of reflectivity (from the Precipitation Radar) strong
relationships between the lightning intensity and differences in the vertical makeup of
lightning producing storms.
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 Adamo et al (2003) show that lightning
producing storms (which are a small fraction of all precipitating storms) are responsible
for the majority of rainfall.
The UWTM is an excellent tool for the study of electrified cloud with its use of an
explicit microphysical parameterization. Future work will include further coupling of the
MM5 model with the microphysical parameterization of the UWTM. 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 UWTM.
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 EVG1-2000-00030) co-funded by the
Research DG of the European Commission within the RTD activities (5 th Framework
Program).
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