A three-dimensional numerical simulation of supercell hailstorm seeding over Greece using a cloud model

Theodore Karacostas1, Vlado Spiridonov2, Dimitrios Bampzelis1 and Ioannis Pytharoulis1

1Aristotle University of Thessaloniki, Department of Meteorology and Climatology, GR- 541 24, Thessaloniki, Greece. e-mail: karac@geo.auth.gr 2 Republic Hydrometeorological Service, Skupi bb 1000 Skopje

1. Introduction

Based upon the structural and evolutionary properties, convective hailstorms could be classified as single cell, multicell and supercell (Marwitz, 1972a, b). The supercell hailstorm cloud usually consists of one and rarely from more cells. It has horizontal and vertical development more than 30 km and 12km, respectively. Circulation wise, the embryo formation area (EFA), the hail growth region (HGR) and the hail cascade area (HCA) are adjacent within the storm (Karacostas, 1989). Such a circulation supports the regeneration of the ascending airstreams in cloud. Case studies are carried out in order to verify and document the value of the cloud model used in contributing to the understanding of supercell convective storm dynamics and microphysics. The examined supercell hailstorm, which occurred over Greece on the 17 June 2009, is analyzed in this study. Numerical simulation of supercell hailstorm seeding has been performed according to the seeding methodology, seeding hypothesis and seeding rates adopted by the Greek National Hail Suppression Program (NHSP) (Karacostas, 1984 and 1989). The examination of the performance and capability of the model is tested through comparisons between simulated and observed radar reflectivity fields (PPI and RHI) plots, being provided for the selected case study by the TITAN software tool (Thunderstorm Identification, Tracking, Analysis and Nowcasting), (Dixon and Wiener, 1993).

The cloud model formulation is briefly described. The boundary conditions and numerical techniques are then explained, followed up by a brief explanation of the seeding methodology. The analyses continue with the numerical simulation of the supercell hailstorm seeding with the comparative analyses. Finally, the results are followed by discussion and the conclusions are summarized.

2. Model characteristics

Only few basic characteristics of the model are

summarized here. The present version of the model is a three-dimensional, non-hydrostatic, time-dependant, compressible system, which is based on the Klemp and Wilhelmson (1978) dynamics, Lin et. al. (1983) microphysics, and Orville and Kopp (1977) thermodynamics. The bulk microphysical parameterization uses a double-moment scheme for all species. The activation of AgI is parameterized by the three nucleation mechanisms based on Hsie

(1980) and Kopp (1988), which are deposition (including sorption) nucleation, contact freezing nucleation, Brownian collection and inertial impact due to cloud droplets and raindrop. The calculation of agent dispersion is done by using an additional conservation equation. Since, in its initial phase the model dispersion of the agent takes place on a sub-grid scale, the advection and diffusion are represented by individual puffs, which spread in time according to the turbulent diffusion coefficients proposed by Georgopoulos and Seinfeld (1986). The equivalent radar reflectivity factors for hail and rain are computed on the equations given by Smith et. al. (1975) and empirical equation for snow by Sekhon and Srivastava (1970). More detail information about the model, initial and boundary conditions, numerical technique and initialization could be found in Barth et. al. (2007).

Fig. 1 A representative sounding taken at 00 UTC for Thessaloniki, Greece from University of Wyoming on June 17, 2009 2.1. Initial conditions and initialization

Initial impulse for convection is an ellipsoidal

warm bubble with the maximum temperature perturbation in the bubble center (To = 2.8°C). The model domain is 61 km x 61 km x 18 km3. The horizontal resolution of the model is 0.5 km, while the vertical one is 0.2 km. The temporal resolution of the model (time step) is 10 s for the integration of the dynamics, microphysics and chemistry and a smaller one (2 s) for solving the sound waves.

2.2. General characteristics of hailstorm case

The convective cloud observed on 17 June exhibits the general characteristics of the supercell hailstorm. The intensive cloud activity that was observed in the afternoon hours, is registered on the whole territory of northern Greece from 14:47 to 16:03.

Fig. 2. Model simulated vertical transects of the reflectivities along NW-SE, from 15 to 45 min, at 10 min time intervals. a) Unseeded case. b) Seeded case. A seeding agent placement is shown on the first r.h.s. panel from above.

2.2. General characteristics of hailstorm case, occurred in northern Greece on June 17, 2009

The convective cells with heights up to 5-8 km, exhibited the maximum reflectivity values (around 66 dBz). The maximum observed heights of cloud top were around 15 km. The life cycle of the convective cloud was about 70 min. The hailstorm was moving with mean speed of 55 km/h from NW to SE flow. The dominant observed phenomena were intensive showers, hail and strong wind. Hailfall is registered around 30 min from the beginning of the radar observation. 2.3 Seeding approach

The adopted seeding hypothesis is based on the beneficial competition theory, which is specifically described by Karacostas (1989). In this particular case study, the seeding was conducted at the cloud

top and the AgI was introduced within the area bounded by the temperature zones of -10 °C and -8 °C. The preferable areas were chosen to be on the upshear side of the storm and to exhibit strong updrafts and high values of liquid water content and lack of ice. The seeding rate was chosen to be 1 to 2 flares of 20 g every 5 seconds. The time seeding duration was 4 to 5 min, flying back and forth, from SW to NE. The seeding rate, in this particular case study, is ten times larger than the aforementioned. In this case, the aircrafts seeding of this vigorous convective cloud started at its early developing stage, that is, at 15 min, within the main and mostly secondary inflow region, with enhanced updrafts, associated with the new growth zone of the later developed supercell storm, when the reflectivity reaches and exceeds the 35 dBz, between -5° C and -30 °C, at about 6 km height a.s.l.

Fig. 3. RHI echoes recorded by TITAN system on 04.08.2007 from 15 to 45 min at 10 min time intervals. The first echoe is observed at 15:03 local time, while the last echo is observed at 15:33 local time 3. Results 3.1 The numerical simulation of hailstorm seeding

Numerical simulation of hailstorm seeding has been performed following the operational hailstorm seeding operational method applying in the Greek NHSP. A three-dimensional numerical simulation has shown a typical supercell hailstorm with intensive growth. The maximum simulated vertical velocity is 27.6 m/s, the cloud top reaches 16.8 km and the total accumulated rainfall at the ground is 55.7 kg/m2. The maximum simulated radar reflectivity of 70 dBz is slightly lower than the observed radar reflectivity (66 dBz). The max calculated mixing ratio of cloud water, cloud ice, hail, rain and snow is: 7.4, 7.2m 17.5, 9.7 and 5.2 g/kg,

respectively. As it is illustrated in Fig. 2b (top panel), seeding material is correctly introduced at the cloud side, in the main inflow area, in radar reflectivity zone greater than 35 dBz between -8 °C and -10 °C.

Fig. 4. PPI echoes recorded by TITAN software system on 04.08.2007 from 15 to 45 min at 10 min time intervals. The first echoe is observed at 15:03 the local time, while the last echo is observed at 15:33 local time The silver iodide aircraft seeding trajectory is well seen in the horizontal cross section plot shown in Fig. 5 (also r.h.s. top panel). Seeding material in convective cloud is realized in 15 min of the simulation time. The positive or negative effects of the hailstorm seeding could be identified by comparing the radar reflectivities (horizontal and vertical transects) in a different time intervals, between the unseeded and seeded cases. A slight difference is noted on the radar reflectivity patterns a few minutes after the seeding, as it is shown in a vertical cross section of the radar reflectivity fields at 10, 20 and 30 min after the initial seeding. The change of the reflectivity structure is also evident at the horizontal cross section of the reflectivity echoes (see Fig. 5a, b). Seeded case, exhibits a slight increase of the reflectivity 10 min after the initial seeding (as it was expected) and rapidly decrease of it at 25 min after the seeding. The RHI plots shown on Fig. 3, and PPI plots at the same time intervals provided from TITAN, show a relatively similar reflectivity patterns. The difference becomes more evident in the cloud mature stage, when intensive rainfall occurs. By comparing vertical and horizontal transects of reflectivity fields at 25, 35 and 45min (Fig. 2 and 5), a distinct picture of the positive effects of hailstorm seeding is obtained. Radar reflectivity in seeded case is substantially decreased 30 min after the initial seeding. A more realistic view of the hailstorm occurred in northern Greece on June 17,

2009 is visualized through a three-dimensional numerical simulation of the cloud.

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Fig. 5. Model simulated horizontal cross sections of the reflectivity’s at height=7 km a.s.l. from 15 to 45 min. at 10 min time intervals. a) Unseeded case. b) Seeded case. A seeding agent placement is shown on the first r.h.s. panel from above. Fig. 7a, b shows 3-D depictions of the cloud life cycle viewed from the southeast (SE) with hydrometeors (cloud water, cloud ice, hail, rain and snow), expressed through mixing ratios, together with seeding material, which is released by aircraft seeding (see Fig. 7b). The plot size dimensions of AgI have been increased for visualization purposes. It is well seen how seeding material is released in the appropriate place in the inflow region (see blue fields), within the hailstone growing area, during the growing phase. The cloud grows quite rapidly and the upper portion extends towards SE ten min after the seeding. The internal structure and the horizontal extension of the apparent anvil, categorize this cloud as a typical supecell hailstorm. The panels at 25 min show that some of the AgI has been used up and some has been transported to southeast. Most of the seeding material has been activated within the 25 min. It is obvious that seeding has contributed in modification of the cloud environment, which is more visible 20 and 30 min after the initial seeding was performed. Seeded case shows rainwater field increase and slight hailfall decrease in 25 min. The difference between the internal structures of both

cases becomes more evident in 35 and 45 min of the simulation time. AgI seeding has modified the in-cloud volume and caused enhanced rainfall at the ground.

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An attempt has been made to simulate a supercell hailstorm seeding occurred on June 17, 2009 in northern Greece using a 3-D cloud model. Seeding experiment is performed according to the seeding hypothesis adopted by the Greek NHSP. Taking into consideration the very fast growing of the hailstones within the supercell storm, it is pointed out the significant importance of delivering the AgI at the right time and place, according to the standard seeing criteria. Even this is a single analyzed case study, the greatest efficiency is achieved if sufficient amount of ice nuclei is introduced in the hailstone growing area during the phase of their formation, when the hailstones are small and the number of large cloud droplets is greater than the number of hailstones.

Simulation of aircraft seeding at the frontal part of the supercell hailstorm, in radar reflectivity zones greater than 35 dBz between the -8 °C and -10 °C isotherms results in cloud modification, change of the internal

structure, hailfall decrease and total rainfall increase by 12.5 % with respect to the unseeded case. In spite the fact that this is only a single case study of a supercell hailstorm seeding, the obtained results are quite optimistic, in respect to the obvious potential for modification of cloud environment by applying appropriate cloud seeding with optimal placement, time and seeding amount.

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