A NUMERICAL STUDY OF THE EFFECTS OF AEROSOL ON ELECTRIFICATION AND LIGHTNING DISCHARGES IN THUNDERSTORMS

Transcription

1 CHINESE JOURNAL OF GEOPHYSICS Vol.60, No.5, 2017, pp: DOI: /cjg A NUMERICAL STUDY OF THE EFFECTS OF AEROSOL ON ELECTRIFICATION AND LIGHTNING DISCHARGES IN THUNDERSTORMS TAN Yong-Bo, MA Xiao, XIANG Chun-Yan, XIA Yan-Ling, ZHANG Xin Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Joint International Research Laboratory of Climate and Environment Change (ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing , China Abstract Based on existing three-dimensional (3-D) thunderstorm electrification and discharge model, this work coupled with a classical parameterization scheme of aerosol activation is used to simulate a case of tropical convection in Changchun. The study shows that the change of aerosol concentration has an important influence on the microphysics, electrification and discharge processes of thunderstorm clouds. The results show that: (1) As the aerosol concentration increases in the polluted thunderclouds, the increase of the number of cloud droplets and the updraft cause the increase of the number of ice crystal and graupel, but the decrease of the scale; (2) Compared to the clean thunderclouds, the non-induced electrification process is weak, while the induction electrification process is strong, and the duration of electrification become longer in polluted thunderclouds; (3) The first charge time of the polluted thunderclouds delays, but the total lightning frequency increases and duration is longer. Meanwhile, the frequency of the cloud-to-ground flash in the polluted thunderclouds increases, and the increase of the positive cloud-to-ground flash is more obvious. Key words Aerosol; Charging rate; Charge structure; Discharge characteristics; Numerical simulation 1 INTRODUCTION In recent years, more evidences have indicated that aerosols influence lightning activity. Because of such factors as traffic, industry, commerce, etc., lightning activity in urban areas is significantly higher than in rural areas (Westcott, 1995; Orville et al., 2000; Steiger and Orville, 2003). Forest fires release vast amount of dust particles in favor of the occurrence of positive cloud-to-ground (CG) flashes (Lyons et al., 1998); and Kar et al. (2009) found that PM10 and SO 2 concentrations were negatively correlated with positive CG flash activity. Recent studies have also shown that, with the occurrence of volcanic eruptions, lightning activity is significantly greater than the summer average in the western Pacific Ocean region east of the Philippines (Yuan et al., 2011). It can be shown that the lightning activity and aerosol content have close relationship. Then the aerosol is how to affect the thunderstorm s cloud electrical process on earth. Due to limitations of current observation methods, to know more about the influence of aerosols on the various characteristics of a thunderstorm s cloud electrical process, its corresponding patterns need to be studied. The electrical-electronic coupling digital simulation of strong storms is becoming one of the most important research methods used in cloud precipitation physics and atmospheric science. By comparing the thunderstorm process over the ocean, Mitzeva et al. (2006) found that when aerosol concentration is higher, cloud droplet number increases, windspeed is enhanced, ice particles increase in number, precipitation decreases, negative charge density increases, and the electrification process is more intense. Mansell and Ziegler (2013) and Tan et al. (2015) used the two-dimensional cloud model to investigate the response of the internal electrical process to aerosol concentration. In addition, Zhao et al. (2015) used the WRF model to analyze the electrification process in the background of clean clouds and polluted clouds. It was found that, as aerosol concentration increases, both ybtan@ustc.edu

2 432 Chinese J. Geophys. Vol.60, No.5 cloud water content and the concentration of ice particles increase, leading to a stronger electrification process. All these studies reveal the relationship between aerosols, the electrification process and the charge structure, but do not analyze the influence of aerosols on lightning discharge behavior. However, only the considered model work of the discharge process has not also established the integrated discharge parameterization program. They obtain lightning discharge frequency only by inferring or using a simple empirical formula. For example, Shi et al. (2015) used a formula related to the lightning incidence and the mass flow of ice particles to calculate the frequency of lightning in marine thunderstorms and terrestrial thunderstorms, thus demonstrating that aerosols can make the electrical activity between the sea and land generate differences. Shi et al. (2015) used this empirical formula to analyze the response of lightning incidence to aerosol concentration. In addition, Wang et al. (2011) used the WRF model to compare the differences in the dynamics, microphysics, and electrical processes of contaminated thunderstorms and clean thunderstorms. Wang et al. (2011) used the lightning potential index to describe the electrical process, and the lightning potential index is related to the ice particle content, liquid water content, and rising wind speed. Therefore, in order to overall understand the aerosol how to affect the characteristics of the discharge in the thunderstorm cloud, it is necessary to carry out the three-dimensional thunderstorm cloud and discharge simulation test. In this paper, based on the existing three-dimensional thunderstorm electrification and discharge model, the aerosol activation process is added to establish a thunderstorm electrification and discharge model of the coupled aerosol module. Setting the clean and polluted aerosol as a background, respectively, tests were carried out by numerical simulation. The influence of aerosol on the microphysical development, the electrification process, and the discharge process of the thunderstorm cloud is analyzed. And further to analyze the relationship of the lightning frequency, the ratio of CG flashes and the ratio of positive and negative cloud-to-ground flashes, then make the corresponding microphysical explanation. 2 SIMULATION METHODS In this paper, the three-dimensional thunderstorm electrification and discharge model developed through the cumulus model by the Chinese Academy of Meteorological Sciences (CAMS) was used to explore the internal physical mechanism of aerosols affecting the thunderstorm electrical process (Hu and He, 1987; Wang et al., 1991; Yu et al., 2001). The calculated domain size of the model is 76 km 76 km 20 km with a resolution of 500 m 500 m 500 m, which includes detailed cloud microphysics and considers five hydrometeor categories: cloud droplet, rain, ice crystal, graupel, and hail; the particles are all assumed to have a gamma function distribution of diameter. The electrification scheme mainly considers the processes of non-inductive and inductive charge separation. Inductive charging parameterization is based on Ziegler et al. s (1991) research. When ice particles (e.g., graupel and hail) descend in the gravitational field, they collide with cloud droplets and then bounce off, allowing the cloud droplets to move upward with the positive charge, while the ice particles with the negative charge move downward. The non-inductive electrification mechanism mainly takes into consideration the collision between the graupel and ice crystals. The scheme of charge transfer capacity after a single collision between the graupel and ice particles is modified from Gardiner s (detailed in Tan et al., 2015) scheme, which is related to the size of the ice crystals and the graupel, the relative collision rate, and the coefficient of the inversion temperature. The discharge parameterization scheme is based on Tan et al. s (2006, 2014) study, which takes into consideration such problems as the initiation, the spread, and the calculation of induced charges in the channel, etc. There are two initial breakdown threshold conditions in the model, the first uses the runway electron threshold changing with the altitude. Second, when the field at any point in the model exceeds the conventional air breakdown threshold (160 kv m 1 ), the grid node is also seen as a possible lightning breakdown point (refer to Tan et al., 2006, 2014). The lightning channel is extended step by step, that is, the positive and negative channels only extend one subsequent channel point each time (Mansell et al., 2002). We assume the lightning channel is a good conductor with resistance in the model, and the potential at a channel grid point is derived from the

3 Tan Y B et al.: A Numerical Study of the Effects of Aerosol on Electrification and Lightning Discharges 433 certain internal electric field (E int =500 V m 1 ). In addition, the discharge process will directly neutralize the existing charges in the lightning channels and the charges near the channels, resulting in the reduction of net charge near the lightning channels, which changes the distribution of the original charges. To directly reflect the effect of the reduction of net charge density without calculating the inductive charges in the lightning channels, the charge density of the channel and near the channels is reduced directly according to a certain proportion. The formula is as follows: δq k = β σ k δρ eχ, (1) Σ i σ i where δq k is the charge density of hydrometeor particle k after the discharge; δρ eχ is the charge density of the lightning channel and its nearby grid point before the discharge; σ k is the surface area of hydrometeor particle k; Σ i σ i is the total surface area of all the hydrometeor particles; and β is the reduction ratio of the charge density of hydrometeor particle k. In this paper, it is proposed that the charge density of the various hydrometeor particles of the channel and adjacent grid points be reduced to 30% of the value before the discharge. This model provides a reasonable simulation ability for the cloud microphysical, electrification, and the discharge process. On this basis, this paper introduces a maturer aerosol activation parameterization scheme into the existing three-dimensional thunderstorm cloud electrification and discharge model, establishing a new thunderstorm cloud model coupled with the aerosol, with cloud droplet concentrations changing from a constant to a more reasonable forecast. The following describes the aerosol initial field and activation scheme. 2.1 Initial Conditions Aerosol concentration decreases with increasing height due to the effects of the Brownian motion and gravitational settling, assuming that the concentration of aerosol in the horizontal direction is the same. Therefore, the concentration can be expressed as (Yin et al., 2000): where, z s (the scale height) is set to 2 km in this study, N is the concentration of aerosol on the ground (initial conditions of aerosol), which varies with geographical position, season, and atmospheric conditions. The assumption in this study is that the aerosol concentration at the same height is uniformly distributed when the aerosol is initialized in each grid point. Therefore, the aerosol concentration distribution for the whole space can be calculated given the aerosol concentration on the ground. We set two aerosol background fields (Wang et al., 2011) (Fig. 1), polluted (case P) and clean thunderclouds (case C), respectively, to investigate the effects of aerosol on the microphysical process and electrification of thunderstorms. 2.2 Aerosol Activation N a (z) = N(z = 0) exp( z/z s ), (2) Fig. 1 Vertical distribution of the aerosol concentration The red line represents polluted thunderclouds, the green line represents clean thunderclouds. It is unreasonable that the number concentration of cloud droplet is constant in the original electrification model, and the cloud droplet can be activated by aerosol particles. Therefore, this paper puts a classical activation parameterization scheme of aerosol into the three-dimensional thunderstorm model. The cloud droplet activation is calculated according to the empirical formula as follows: N ccn = C o S K, (3) where, N ccn is the number of activated CCN (Cloud Condensation Nuclei) and S is the supersaturation of the cloud, K is a constant and depends on the chemical composition and physical properties of the aerosol. This

4 434 Chinese J. Geophys. Vol.60, No.5 paper, like Wang (2005), refers to K as 0.7. For simplicity, C o is the concentration of CCN activated numbers when supersaturation is 1% and is used to indicate the initial concentration of aerosol (Li et al., 2008) in each numerical experiment. On this basis, this paper adds a diagnostic process to ensure that our model can be consistent with common sense better. { } 1 new N c = max [Nc Nc old ], 0, (4) t where, the number concentration of activated cloud droplets within a new time step ( t) is calculated as Nc new, Nc old is the number concentration of cloud droplet at the former time step, a new cloud droplet forms when Nc new > Nc old, and the activation rate is N c. 2.3 Experiment Case and Initial Disturbance Conditions A sounding profile is used for the simulation of thunderstorm clouds, in Changchun, China, at 20:00, June 10, The vertical temperature, dew point and wind profiles (Fig. 2) reveal a weak thermal instability at 400 hpa to 600 hpa in the atmosphere, which is suitable for simulating a thunderstorm. To initiate the cloud, A humid and warm bubble of horizontal radius 4 km and vertical radius 1 km is set in the middle of the simulation domain, with a temperature perturbation of 2.5 K and a relative humidity perturbation of 80% applied for one-time step at t = 0 at a height of 1 km. The length and width of the disturbed zone is 20 km and the thickness is 4 km. All simulations were carried out in 90 minute, and the time step is 4 s. Fig. 2 Environmental stratification curve (a) and vertical wind profile (b) (a) The black solid line represents the dew point, the green solid line represents the temperature; (b) The blue solid line represents the wind speed of the u direction, the red solid line represents the wind speed of the v direction. 3 SIMULATION RESULTS AND ANALYSIS 3.1 Microphysics Figure 3 shows the maximum cloud water content and the maximum rising wind speed over time in case C (clean thunderclouds) and case P (polluted thunderclouds). The figure shows that within 20 minute of the development of the thunderstorm cloud, compared to the clean thunderstorm, the number of the cloud droplets by the aerosol activation increase in the polluted thunderstorm cloud, and the more latent heat of condensation was released during the condensing process of the cloud droplet, so the rising wind speed of the polluted thunderstorm cloud is stronger than the clean thunderstorm cloud. The maximum rising wind speed in the clean thunderstorm was 31.4 m s 1, while the maximum rising wind speed in the polluted thunderstorm was 35.1 m s 1. The cloud water content continuously rose in the strong updraft. The cloud droplets in the polluted thunderstorms resulted in a significant increase in the cloud-water mixing ratio: the maximum cloud

5 Tan Y B et al.: A Numerical Study of the Effects of Aerosol on Electrification and Lightning Discharges 435 water content (Q c ) in the clean thunderstorm was 5.7 g kg 1, while the maximum cloud water content (Q c ) in the polluted thunderstorm was 11.6 g kg 1. With the development of thunderstorms, the cloud water was continuously consumed, and with the formation of precipitation particles, the updraft was gradually blocked. After 40 minute, the updraft, which was more than 3 m s 1, began to disappear. The number concentration of cloud droplets (maximum is 532 cm 3 ) of the polluted thunderclouds is greater than that of the clean thunderclouds (maximum is 88 cm 3 ). In the same water vapor content, cloud droplets contend for water vapor condensation growth, with the increase of cloud droplet concentration, cloud droplet scale decreases, while the small droplets are difficult to form raindrops by automatic conversion, so the cloud droplets stay longer in the polluted thunderstorm and the raindrops are suppressed (see Figs. 3a, 3b and 4a, 4b). Conversely, the cloud droplet scale in the clean cloud is relatively large, the raindrops begin to appear in about 10 minute, because of the automatic conversion process of the cloud droplets, and the content is obviously higher than that of the polluted thunderstorm (see Fig. 4a). In addition, the stronger updraft in the polluted thunderclouds will bring more water vapor and cloud water into the cold layer, which increases the supersaturation relative to the ice and conducive to the growth process of the ice crystallization, condensation, and coagulation (with the cloud droplet). The content of ice crystal in polluted thunderclouds is larger than that in the clean thunderclouds (see Figs. 4c, 4d). At the same time, as cloud water consumption in the polluted thunderclouds is slow (shown in Fig. 3b), the cloud droplets continue to interact with the ice crystals, resulting in an ice content of clean thunderclouds significantly increasing after 30 minute (see Figs. 4c, 4d). Moreover, the mixing ratio and the number concentration of ice crystals in the polluted thunderclouds are increasing, while the increase in the number concentration of ice crystals is more significant (see Figs. 4c, 4d), so the scale of ice crystals is reduced. The automatic conversion of ice crystals is the starting item of the graupel, and the process of the growth of the graupel is mainly related to the freezing process of the rain and the ice, the collision of the cloud droplets, and the collision process of the raindrops. As the content of raindrops in the polluted thunderclouds is relatively small, the growth of the graupel is limited. From Figs. 4e and 4f, the maximum value of graupel is at about 20 minute, and with the development of time, the content of hail is gradually reduced and begins to fall through melting and rapidly changes. The maximum mixing ratio of polluted thunderclouds is 9.6 g kg 1 with a maximum concentration of kg 1, whereas the maximum mixing ratio of clean thunderclouds is 10.0 g kg 1 with a maximum concentration of kg 1, which would explain why the scale of the clean thunderclouds is greater than that of polluted thunderclouds. Fig. 3 Spatial and temporal distribution of the peak updrafts (w) and maximum water content (Q c) in two cases (Numerical represents the maximum vertical section on each floor, below the same) (a) C: the clean thunderclouds; (b) P: the polluted thunderclouds. Peak updraft velocity contour respectively represents: 3, 5, 10, 15, 20, and 30 m s 1.

6 436 Chinese J. Geophys. Vol.60, No.5 Fig. 4 Spatial and temporal distribution of the largest mixing ratio (Q) and the concentration of largest numbers of hydrometeors (H) of the two cases (a), (b) Rain; (c), (d) Ice crystal; (e), (f) Graupel. C: the clean thunderclouds; P: the polluted thunderclouds. 3.2 Electrification A charge generation in thunderstorms is mainly caused by induction and non-induced electrification. The inductive electrification mechanism is mainly the result of the collision between graupel, hail and cloud droplets, ice crystals. The non-inductive electrification mechanism is mainly caused by the collisions of the graupel and ice crystals, and the hail particles and ice crystals. The concentration of aerosol can affect the microphysical processes in thunderstorms according to the preceding discussion, and how is the effect of different background on the electrification process? Fig. 5 shows the evolution of the maximum non-inductive electrification rate in the two aerosol backgrounds. The non-inductive electrification rate is mainly used for actions between ice crystals and graupel, and the change trend with time is similar in the two cases. The process of electrification starts at about 15 minute, and reaches the maximum value at 25 minute. The non-inductive electrification rate is weak in the dissipation period. In addition, the non-inductive electrification separation process occurs mainly in the low temperature region ( C), while in the higher temperature region, the non-inductive electrification rate is weak, and a polarity reversal phenomenon occurs. Therefore, ice crystals obtain a positive polarity transfer charge, conversely, graupel obtain a negative polarity transfer charge. The non-inductive electrification rate is closely related to the micro-physical characteristics of ice crystals and graupel. Comparing Figs. 5a and 5b, the non-inductive electrification rate (maximum pc m 3 s 1 ) in the clean thunderclouds is greater than that of the polluted thunderclouds (maximum value is pc m 3 s 1 ) during minute. Nonetheless, the non-inductive electrification rate in the polluted thunderclouds is significantly greater than that in the clean thunderclouds between 30 minute and 60 minute. There are two

7 Tan Y B et al.: A Numerical Study of the Effects of Aerosol on Electrification and Lightning Discharges 437 main reasons as follows. (1) In the early stage of thunderstorms development (before 30 minute), although the ice crystal content and the number of graupel in the clean thunderclouds are relatively small, the scale of the ice crystals and the graupel are larger than that of the polluted thunderclouds, so these large particles lead to a stronger non-inductive electrification rate. (2) During the development period (30 60 minute), the content of cloud water and the content of ice crystals in the polluted thunderclouds are favorable to the continuous development of the non-inductive electrification rate. Under the action of the ambient electric field, the cloud droplets and the graupel produce the induced collision electrification process. Fig. 6 shows the inductive electrification rate in the two cases. The positive inductive electrification rate indicates that the graupel carries the positive polarity transfer charge through the induced electrification action, and the opposite cloud droplet obtains the negative polarity transfer charge. It can be seen from Fig. 6 that the positive and negative inductive electrification rates are mainly distributed in the 2 8 km height range, so the inductive electrification rate has a significant effect on the middle and bottom charge stacks of the thunderstorms. This is similar to the simulation results (Tan et al., 2007, 2015). In addition, comparing Figs. 6a with 6b, the inductive electrification rate of the polluted thunderclouds was significantly Fig. 5 The largest non-inductive electrification rate for every minute in the two cases Purple dotted line represents the isotherm (0 C, 13.8 C, and 40 C). (a) The clean thunderclouds; (b) The polluted thunderclouds. Fig. 6 The largest inductive electrification rate (Q gc) for every minute in the two cases (a) The clean thunderclouds; (b) The polluted thunderclouds. The red line is positive inductive electrification rate, the blue line is negative inductive electrification rate; Contours are respectively: ±50, ±20, ±10, ±5, ±1 pc m 3 s 1.

8 438 Chinese J. Geophys. Vol.60, No.5 higher than that in the clean thunderclouds, primarily because the polluted thunderclouds have more cloud droplets and graupel particles. Similar to the distribution of non-inductive electrification rate, the inductive electrification rate is significantly higher than that of the clean thunderclouds in the middle development stage of thunderstorms. 3.3 Lightning Discharges Aerosols have a significant influence on thunderstorm cloud microphysical processes and electrical processes, and the characteristics of lightning discharges are closely related to the charge structure in thunderstorm. (Mansell et al., 2005). Therefore, aerosols are bound to affect the thunderstorm discharge process. Fig. 7 shows the varying curve of the discharge process over time under different thunderstorm cloud background conditions. It can be found from Figs. 7a and 7b that: (1) The first flash occurring in both types of thunderstorms is intra-cloud lightning (IC). The CG occurred later than the IC, and the frequency of the IC was higher than the CG, which is similar to the observation results (Mackerras, 1985; Baral and Mackerras, 1992). (2) The first flash of the clean thunderstorm occurs in 15th minutes, and most flashes occur in 15th minutes to 40th minutes. However, in the polluted thunderstorm, lightning activities are relatively delayed, the first flash occurs in 20th minutes, and most flashes occur in 20th minutes to 70th minutes. Compared with the clean thunderstorm, the aerosol concentration of the polluted thunderstorm was high, the residence time of cloud water was long, the life cycle of cloud is extended and the charging process is relatively slow. Fig. 7 Estimated flash rate related to aerosol concentration in the two cases (a) The clean thunderclouds; (b) The polluted thunderclouds.

9 Tan Y B et al.: A Numerical Study of the Effects of Aerosol on Electrification and Lightning Discharges 439 Hence, it is not difficult to understand the delay of lightning activity. (3) The flash frequency of the polluted thunderstorm cloud was 1203, higher than the 596 in the clean thunderstorm cloud. The total CG lightning frequency of the two thunderstorm types was 5 and 32 respectively. The number of CG lightning in polluted thunderstorm is also larger than that in clean thunderstorm. It should be noted that no positive CG is produced in the clean thunderstorm, while there are 18 positive CG in the polluted thunderstorm. With the increase of aerosol concentration, lightning frequency increases, and it encourages the occurrence of positive CG. This is similar to previous results based on observations (Tan et al., 2016). According to the above analyses, in the polluted aerosol background, the frequency of positive CG in thunderstorm clouds evidently increased. As shown in Fig. 7b, the positive CG occurred mainly in the fading period of the thunderstorm clouds (50 70 minute), which is consistent with previous observations (Rust et al., 1981). During the stage of dissipation, the charge structure of the thunderstorm cloud is dipole structure, that is, the lower part of the main positive charge region contains a main negative charge region (Fig. 8). Fig. 8 shows the charge structure profile of the two cases in 59th minutes. In Fig. 8b, the star represents the position of positive CG. In the two cases, the charge structure is a dipole type, and the polluted case had a positive CG Fig. 8 The charge distribution in the two cases at 59 minute (a) C: y=65.5 km; (b) P: y=65.5 km. The asterisk represents the initial point. in 59th minutes. The clean case had no flash in 59th minutes. The main positive charge was mostly distributed in the height of 4 km to 8 km; the main negative charge was mostly distributed in the height of 4 km to 8 km (Fig. 8); and the charge density is biggish in the case P (see Fig. 8b), which can produce a strong electric field that triggers lightning. In the background of the dipole charge structure, it is propitious to positive CG. Fig. 9 shows the spatial distribution of the positive CG channel in a polluted thunderstorm in 59th minutes. The positive CG usually begins at the junction of the positive and negative charge region, the height was about 6 km, the positive leader was transmitted in the lower part of the negative charge pile, while the negative leader extended in a positive charge pile. Takeuti et al. s (1978) and Brook et al. s (1982) analyses showed that space charge structure is a dipole type when positive Fig. 9 The lightning leader distribution of the polluted thunderclouds at 59 minute The blue line represents the negative leader, the red line represents the positive leader.

10 440 Chinese J. Geophys. Vol.60, No.5 CG occurs, the main positive charge region is larger than the main negative charge region, thus the main negative charge region cannot hinder the positive CG leader from propagating into the ground. Similar conclusions have also been reported by Coleman et al. (2003). Therefore, our simulation is reasonable. 4 CONCLUSIONS A classic aerosol activation parameterization scheme was put into the 3-D thunderstorm electrification and discharge model to investigate the effects of aerosol on the electrification process. Using the improved cloud model, combined with a thunderstorm case in Changchun, two simulated tests were conducted. The two cases were clean thunderstorm and polluted thunderstorm, respectively. The effects of aerosol on microphysical and electrification processes of thunderstorms were compared and analyzed, and the effects of aerosol on lightning discharge characteristics are discussed. Some main conclusions of the above research in this paper are as follows: (1) Aerosols have a great effect on the microphysical process of thunderstorm clouds. Under the background of different concentrations of aerosol, the microphysical processes of thunderstorms are obviously different. Compared with the clean thunderclouds, the number of cloud droplets in the polluted thunderclouds increases, more latent heat is released, and rising wind speed is strengthened. As the concentration of cloud droplets increases, the cloud droplet size decreases, and thus the content of raindrops is weakened. In the polluted thunderclouds, due to rising wind speed, the role of ice crystal growth rate is increased. As the number of ice crystals increases, the ice crystal size in the polluted thunderclouds decreases, and the raindrop content decreases, leading to the increase of the growth rate of the graupel, and the increase in number of the graupel. (2) In the early stage of the development of thunderstorms, the size of ice crystals and graupel in polluted thunderclouds was smaller than that of clean thunderclouds, so the non-induced electrification rate was small. During thunderstorm development, the increase of ice concentration in polluted thunderclouds causes the noninduced electrification rate to be higher than that of clean thunderclouds, with more cloud droplets and graupel appearing, and induction electrification is significantly enhancing. In other words, the duration of electrification in the polluted thunderstorms is longer. (3) Aerosols significantly influence the discharge process of thunderstorm clouds. Compared with the clean thunderclouds, the first discharge is delayed in the polluted thunderclouds, but lasts longer, and there is higher lightning frequency in the polluted thunderclouds. The frequency of lightning flashes noticeably increases in a polluted thunderclouds, and more positive flashes occur during the dispersal period. In this paper, the empirical formula of aerosol activation was added to the three-dimensional thunderstorm electrification and the discharge model. The effect of aerosol as cloud condensation nuclei on the discharge behavior of thunderstorms was investigated. However, the influence of aerosol-related ice nuclei on the internal electrical process was not considered, so the addition of aerosol-related ice nuclei to the research on the impact of the internal electrical process of thunderstorms would merit future study. ACKNOWLEDGMENTS This work was supported by the National Natural Science Foundation of China ( ), the National Key Basic Research Program of China (973 Program) (2014CB441403). The microphysical process of cumulonimbus used in this paper is provided by researcher Hu Z J of the Chinese Academy of Meteorological Sciences. References Baral K N, Mackerras D The cloud flash-to-ground flash ratio and other lightning occurrence characteristics in Kathmandu thunderstorms. Journal of Geophysical Research: Atmospheres, 97(D1): , doi: /91JD Brook M, Nakano M, Krehbiel P, et al The electrical structure of the Hokuriku winter thunderstorm. Journal of Geophysical Research: Atmospheres, 87(C2): , doi: /JC087iC02p01207.

11 Tan Y B et al.: A Numerical Study of the Effects of Aerosol on Electrification and Lightning Discharges 441 Coleman L M, Marshall T C, Stolzenburg M, et al Effects of charge and electrostatic potential on lightning propagation. Journal of Geophysical Research: Atmospheres, 108(D9): Hu Z J, He G F Numerical simulations of cumulonimbus dynamic process I: microphysical model. Acta Meteorologica Sinica (in Chinese), 45(4): Kar S K, Liou Y A, Ha K J Aerosol effects on the enhancement of cloud-to-ground lightning over major urban areas of South Korea. Atmospheric Research, 92(1): 80-87, doi: /j.atmosres Li G H, Wang Y, Zhang R Y Implementation of a two-moment bulk microphysics scheme to the WRF model to investigate aerosol-cloud interaction. Journal of Geophysical Research: Atmospheres, 113(D15): D15211, doi: /2007JD Lyons W A, Uliasz M, Nelson T E Large peak current cloud-to-ground lightning flashes during the summer months in the contiguous United States. Monthly Weather Review, 126(8): , doi: / (1998)126<2217:LPCCTG>2.0.CO;2. Mackerras D Automatic short-range measurement of the cloud flash to ground flash ratio in thunderstorms. Journal of Geophysical Research: Atmospheres, 90(D4): , doi: /JD090iD04p Mansell E R, MacGorman D R, Ziegler C L, et al Simulated three-dimensional branched lightning in a numerical thunderstorm model. Journal of Geophysical Research: Atmospheres, 107(D9): ACL 2-1-ACL 2-12, doi: /2000JD Mansell E R, Macgorman D R, Ziegler C L, et al Charge structure and lightning sensitivity in a simulated multicell thunderstorm. Journal of Geophysical Research Atmospheres, 110(D12): D12101, doi: /2004JD Mansell E R, Ziegler C L Aerosol effects on simulated storm electrification and precipitation in a two-moment bulk microphysics model. Journal of the Atmospheric Sciences, 70(7): , doi: /JAS-D Mitzeva R, Latham J, Petrova S A comparative modeling study of the early electrical development of maritime and continental thunderstorms. Atmospheric Research, 82(1-2): 26-36, doi: /j.atmosres Orville R E, Huffines G, Nielsen-Gammon J, et al Enhancement of cloud-to-ground lightning over Houston, Texas. Geophysical Research Letters, 28(13): , doi: /2001GL Rust W D, Macgorman D R, Arnold R T Positive cloud-to-ground lightning flashes in severe storms. Geophysical Research Letters, 8(7): , doi: /GL008i007p Shi Z, Tan Y B, Tang H Q, et al A numerical study of aerosol effects on the electrification and flash rate of thunderstorms. Chinese Journal of Atmospheric Sciences (in Chinese). doi: /j.issn Shi Z, Tan Y B, Tang H Q, et al Aerosol effect on the land-ocean contrast in thunderstorm electrification and lightning frequency. Atmospheric Research, : , doi: /j.atmosres Steiger S M, Orville R E Cloud-to-ground lightning enhancement over Southern Louisiana. Geophysical Research Letters, 30(19): 1975, doi: /2003GL Takeuti T, Nakano M, Brook M, et al The anomalous winter thunderstorms of the Hokuriku Coast. Journal of Geophysical Research: Atmospheres, 83(C5): , doi: /JC083iC05p Tan Y B, Peng L, Shi Z, et al Lightning flash density in relation to aerosol over Nanjing (China). Atmospheric Research, : 1-8, doi: /j.atmosres Tan Y B, Shi Z, Chen Z L, et al A numerical study of aerosol effects on electrification of thunderstorms. Journal of Atmospheric and Solar-Terrestrial Physics, doi: /j.jastp Tan Y B, Tao S C, Liang Z W, et al Numerical study on relationship between lightning types and distribution of space charge and electric potential. Journal of Geophysica Research: Atmospheres, 119(2): , doi: /2013JD Tan Y B, Tao S C, Zhu B Y, et al Numerical simulations of the bi-level and branched structure of intracloud lightning flashes. Science in China Series D, 49(6): , doi: /s Tan Y B, Tao S C, Zhu B Y, et al A simulation of the effects of intra-cloud lightning discharges on the charges and electrostatic potential distributions in a thundercloud. Chinese Journal of Geophysics (in Chinese), 50 (4): , doi: /j.issn: Wang C E A modeling study of the response of tropical deep convection to the increase of cloud condensation nuclei concentration: 1. Dynamics and microphysics. Journal of Geophysical Research: Atmospheres, 110(D21): D21211, doi: /2004JD

12 442 Chinese J. Geophys. Vol.60, No.5 Wang Q, Hu Z J Three-dimensional elastic atmospheric numerical model and the simulations of a severe storm case. Acta Meteorologica Sinica (in Chinese), 48(1): Wang Y, Wan Q, Meng W, et al Long-term impacts of aerosols on precipitation and lightning over the Pearl River Delta megacity area in China. Atmospheric Chemistry and Physics, 11(23): , doi: /acp Westcott N E Summertime cloud-to-ground lightning activity around major Midwestern Urban Areas. Journal of Applied Meteorology, 34(7): , doi: / Yin Y, Levin Z, Reisin T G, et al The effects of giant cloud condensation nuclei on the development of precipitation in convective clouds a numerical study. Atmospheric Research, 53(1-3): , doi: /S (99) Yu D W, He G F, Zhou Y, et al Three-dimensional convective cloud seeding model and its field application. Journal of Applied Meteorological Science (in Chinese), 12(S1): Yuan T L, Remer L A, Pickering K E, et al Observational evidence of aerosol enhancement of lightning activity and convective invigoration. Geophysical Research Letters, 34(4): L04701, doi: /2010GL Zhao P G, Yin Y, Xiao H The effects of aerosol on development of thunderstorm electrification: a numerical study. Atmospheric Research, 153: , doi: /j.atmosres Ziegler C L, Macgorman D R, Dye J E, et al A model evaluation of noninductive graupel-ice charging in the early electrification of a mountain thunderstorm. Journal of Geophysical Research Atmospheres, 96(D7): , doi: /91jd01246.