Subseasonal and Diurnal Variability in Lightning and Storm Activity Over the Yangtze River Delta, China, During Mei-Yu Season

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Subseasonal and Diurnal Variability in Lightning and Storm Activity over the Yangtze River Delta, China, during Mei-yu Season

a,b,c a,b d,e a,b c JI YANG, KUN ZHAO, XINGCHAO CHEN, ANNING HUANG, YUANYUAN ZHENG, AND a,b,c KANGYUAN SUN a Key Laboratory for Mesoscale Severe Weather/Ministry of Education and School of Atmospheric Science, Nanjing University, Nanjing, China b State Key Laboratory of Severe Weather and Joint Center for Atmospheric Radar Research of the China Meteorological Administration and Nanjing University, Beijing, China c Jiangsu Research Institute of Meteorological Sciences, Nanjing, China d Department of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, Pennsylvania e Center for Advanced Data Assimilation and Predictability Techniques, The Pennsylvania State University, University Park, Pennsylvania

(Manuscript received 20 June 2019, in ﬁnal form 16 March 2020)

ABSTRACT

Using 5 years of operational Doppler radar, cloud-to-ground (CG) lightning observations, and National Centers for Environmental Prediction reanalysis data, this study examined the spatial and temporal characteristics of and correlations between summer storm and lightning activity over the Yangtze River Delta (YRD), with a focus on subseasonal variability and diurnal cycles. The spatiotemporal features of storm top, duration, maximum reflectivity, size, and cell-based vertical integrated liquid water were investigated using the Storm Cell Identification and Tracking algorithm. Our results revealed that there was high storm activity over the YRD, with weak diurnal variations during the mei-yu period. Specifically, storms were strongly associated with mei-yu fronts and exhibited a moderate size, duration, and intensity. On average, afternoon storms exhibited stronger reflectivity and higher storm tops than morning storms, as evidenced by the afternoon peak in CG lightning. The storm intensity strengthened in the post-mei-yu period, due to an increase in atmospheric instability; this was accompanied by a higher frequency of CG lighting. The diurnal cycles of storm frequency and CG lightning in the post-mei-yu period followed a unimodal pattern with an afternoon peak. This is attributable to increased thermodynamic instability in the afternoon, as little diurnal variation was observed for wind shear and moisture. An inverse correlation between lightning occurrence and mean peak current (MPC) for negative CG lightning was evident during the pre-mei-yu and mei-yu periods. The diurnal variation in MPC for negative CG lightning agreed well with that for storm intensity.

1. Introduction weather and climate predictions. For example, the temperature and humidity in the upper troposphere The spatial distribution and diurnal cycles of storms can be affected by the height and intensity of storms and precipitation over East Asia during the monsoon (Folkins 2002). In addition, storm properties can be have been investigated extensively in recent years (Lin used as evaluation benchmarks for numerical models et al. 2011; M. Chen et al. 2014; Chen et al. 2015, 2017, and parameterization schemes (Davis et al. 2003; 2018). However, few studies have focused on the prop- Arakawa 2004; Liang et al. 2004; Starzec et al. 2018). erties of warm-season storms or their diurnal cycles over The mei-yu (baiu in Japan) season over the YRD is the Yangtze River Delta (YRD) in China, which is lo- associated with a northward shift of the East Asian cated in one of three maximum rainfall centers collec- summer monsoon (Sampe and Xie 2010; Luo et al. tively referred to as the Yangtze–Huaihe River basin 2013). During the mei-yu period (mid-June to mid- (YHRB) (Ding and Chan 2005). An understanding July), a zonal rainband with heavy rainfall is frequently of these storms and their properties is important for observed. This rainband, referred to as the mei-yu front, is controlled by frontal structures in the lower tropo- Corresponding author: Kun Zhao, [email protected] sphere and characterized by a sea level pressure trough,

DOI: 10.1175/JCLI-D-19-0453.1 Ó 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses). Unauthenticated | Downloaded 10/01/21 11:32 AM UTC 5014 JOURNAL OF CLIMATE VOLUME 33 horizontal shear, sharp moisture gradients, and rela- from the Chinese operational radar network provide a new tively weak temperature gradients (Ding and Chan opportunity to gain insight into the three-dimensional (3D) 2005; Sampe and Xie 2010). Previous studies have shown structure and evolution of storms during different phases of that the associated convection that becomes organized the monsoon period for characterizing diurnal variations in in the midnight-to-morning hours during the mei-yu storm properties. period is closely related to ascending moisture flow over Lightning activity is an effective indicator of deep convectively generated cold pools (Luo et al. 2014; He convection and climate change, and has been widely et al. 2018). Another possible mechanism driving the investigated over different regions (Hondl and Eilts mei-yu front is the synoptic-scale frontal convergence 1994; Zipser and Lutz 1994; Watson et al. 1995; created by accelerated southerly moisture flows result- Gremillion and Orville 1999; Zipser et al. 2006; Yuan ing from clockwise rotation of low-level winds (Chen and Qie 2008; Mosier et al. 2011; Seroka et al. 2012; et al. 2010; Chen et al. 2017). Xue et al. (2018) used Metzger and Nuss 2013; Qie et al. 2014; Zheng et al. convection-permitting simulations to investigate the key 2016). Laboratory studies show that riming electrifi- mechanism controlling the mei-yu precipitation diurnal cation is the main charge separation mechanism asso- cycle. They found that the convergence forced by low- ciated with thunderstorms, occurring mainly during level ageostrophic winds results in an early morning graupel–ice crystal collisions with supercooled water peak and an evening minimum in precipitation, which (Takahashi 1978; Saunders 1993). Many previous stud- can be explained by the boundary layer inertial oscilla- ies concentrated on the lightning rate, spatial distribution theory (Blackadar 1957). Diurnal variations in the tion, and diurnal cycle (Zajac and Rutledge 2001; Qie precipitation amount, frequency, and intensity have re- et al. 2003; Yuan and Qie 2008; Xia et al. 2015, 2018; ceived more attention in recent years (Chen et al. 2010; Yang et al. 2016). Observational studies have indicated Bao et al. 2011; Xu and Zipser 2011; M. Chen et al. 2012; that the peak current of negative lightning is closely G. Chen et al. 2012; G. Chen et al. 2014; Chen et al. 2017; related to thunderstorm intensity. This putative rela- Xu 2013). During the mei-yu period, frequent nocturnal tionship is associated with the small eddies created by long-duration rainfall events with shallow echo tops strong turbulence within afternoon storms; under these contribute to the early-morning rainfall maximum over conditions, the distances between electrostatic thun- the YRD, whereas deep convection produces a sec- dercloud charges become smaller, resulting in frequent ondary afternoon peak in precipitation (Chen et al. lightning occurrences but with less charge available to 2010; Xu and Zipser 2011). During the post-mei-yu flow into the return stroke, resulting in a smaller peak period, the diurnal cycle of deep convection, precipi- current and flash size (Bruning and MacGorman 2013; tation, and lightning exhibits a single peak (Xu and Chronis et al. 2015a,b). However, there have been rel- Zipser 2011). Luo et al. (2013) compared the summer atively few studies investigating the relationship be- storm properties over southern China and the YHRB tween various storm properties and the peak amount of based on satellite observations. They found that the lightning (Shafer et al. 2000; Carey and Rutledge 2003; contribution of heavy rainfall to total rainfall amount is Zheng et al. 2016). greater in the YHRB than in southern China. They also In this study, the summer storm properties and light- showed that convective intensity strengthens progres- ning activity over the YRD during the pre-mei-yu, mei- sively from the premonsoon period to the monsoon yu, and post-mei-yu periods from 2010 to 2014 were period and further to the postmonsoon period over the investigated. In contrast to previous studies based on YHRB and southern China. Furthermore, in most of satellite imagery, high-resolution ground-based radar the Asian monsoon regions, convection is stronger during and cloud-to-ground (CG) lightning observations were the monsoon break and postmonsoon periods than dur- used here for the first time to reveal the spatiotemporal ing monsoon activity (Kodama et al. 2005; Yuan and Qie structure of storms and lightning activity with fine resolu- 2008; Xu et al. 2009; Xu and Zipser 2011; Luo et al. tion. Relevant atmospheric conditions were also examined 2013). The abovementioned studies focused mainly on using reanalysis data. Based on statistical characterization, the spatial distribution of storms and cloud tops across the environmental conditions influencing storm activity different regions and/or periods based on satellite data and CG lightning over the YRD are discussed with respect such as data from the Tropical Rainfall Measuring to the different monsoon phases. Mission that recorded rainfall from a particular location The rest of the paper is organized as follows. The data twice a day. Temporal resolution limitations and atten- and methodology are introduced in section 2. Section 3 uation (Xu 2013) have limited the ability to investigate describes the large-scale flow and environmental con- the properties of storms, including storm lifetime, ditions during the pre-mei-yu, mei-yu, and post-mei-yu movement, vertical structure, and diurnal cycle. Observations periods. Section 4 presents the spatial distribution of

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FIG. 1. (a) Location of Nanjing radar is represented by black triangle. Blue dots show the locations of the lightning detection system sensors. The Yangtze River Delta (YRD) defined in the study is marked by green circle. Red lines indicate the urban areas. Orography is given by grayscale. (b) Case example identified by SCIT at 1.58 elevation angle at 1756 LST 20 Aug 2014. The black triangles indicate storm positions in temporal series, and the circles represent current storm positions. storms, as well as lightning and storm properties. components in an elevation scan. In this study, this step Section 5 compares the diurnal cycle of storm proper- was repeated over a reflectivity threshold of 30–60 dBZ ties and lightning. A brief summary and conclusions are in 5-dBZ increments, to improve storm cell identifica- given in section 6. tion performance. Additionally, 2D storm components with an area of less than 10 km2 were discarded. The 2. Data and methodology vertical association of 2D storm components in all elevation scans was created to form 3D storm cells. Finally, a. Radar data the identified storm cells were tracked in space using a The radar data used in this study were collected by the discrete time interval (every 6 min in this study), if the China Next Generation Weather Radar in Nanjing distance between the centroid of storm cells and the (NJRD) during the warm season (1 May to 31 August) first-guess location determined by the storm cell’s pre- from 2010 through 2014. The wavelength of the NJRD vious motion vector or default motion vector was less 2 system is 10 cm (S band), with a 18 beam width. The than the threshold value (30 m s 1 times the time inter- radar scan mode was volume coverage pattern 21; scans val between two contiguous volume scans). The storm were acquired at ;6-min intervals. properties—including the storm top, maximum storm NJRD is located near the Yangtze River (YR) at an reflectivity, cell-based vertical integrated liquid (VIL), altitude of 187 m (Fig. 1a).Theterrainofthestudy storm duration, storm size, and moving speed—were area (green circle in Fig. 1a) is lower than 300 m. determined. The storm top was defined as the height of Therefore, there is no obvious blocking or ground the storm center of the highest storm component with a clutter in the NJRD data; however, anomalous prop- reflectivity threshold of 40 dBZ. agation tends to contaminate radar reflectivity. Based To keep only the convective storm cells, two supple- on the horizontal and vertical reflectivity structures of mental selections were applied, based on the maximum nonprecipitation echoes, automatic quality control storm reflectivity and the cell-based VIL. Previous was implemented, following the procedure described studies indicate that a reflectivity threshold greater than by Zhang et al. (2004). 40 dBZ is a reasonable criterion for separating convective and stratiform rain (Reap and MacGorman 1989; b. Retrieval of storm properties Livingston et al. 1996; Lin et al. 2011; M. Chen et al. Storm properties were retrieved via the Storm Cell 2012). In this study, if the maximum storm reflectivity Identification and Tracking (SCIT) algorithm (Johnson of a given storm cell during its lifetime was less than et al. 1998), which is a 3D centroid-based storm cell al- 40 dBZ, the storm cell was discarded. Considering that gorithm. The SCIT algorithm first identifies the contig- the reflectivity of the bright band of the stratiform can be 2 uous range gates and azimuths with radar reflectivity larger than 40 dBZ, a VIL threshold of 6.5 kg m 2 was above a specified threshold as two-dimensional (2D) then used to remove the storm cell with the brightest

Unauthenticated | Downloaded 10/01/21 11:32 AM UTC 5016 JOURNAL OF CLIMATE VOLUME 33 band, as proposed by Zhang and Qi (2010). Figure 1b (https://ngdc.noaa.gov/eog/dmsp/downloadV4composites. shows an example of a SCIT algorithm application. html#AVSLCFC) developed by the Earth Observation Although SCIT has been successfully used to inves- Group, National Oceanic and Atmospheric Administration/ tigate long-term storm activity over various regions National Geophysical Data Center (Peterson 2003; (MacKeen et al. 1999; Mohee and Miller 2010; Mosier Lindén et al. 2015) was used to identify rural and urban et al. 2011; Lin et al. 2011; Seroka et al. 2012) and has a areas; data are in the form of composite images, each proven storm cell detection accuracy exceeding 90%, with 30-arc-s resolution that provides an average annual the algorithm still has some limitations. For example, brightness level ranging from 0 to 63 (the larger number the algorithm does not account for storm cell merging corresponds to a higher brightness level). This product is and splitting. Further, the algorithm has a poor cell de- widely used to identify urban areas in different cities tection rate due to the cone of silence near the radar site (e.g., Small et al. 2005, 2011). In this study, the gridded and low vertical resolution at greater distances from the Stable Lights product was applied to identify urban radar site. To reduce the poor cell detection rate, only areas, using a brightness level .40 (2013), as shown storm cells located within 20–150 km from the radar site in Fig. 1a. were used in this study. e. Determination of the mei-yu period The storm location was used to reveal the storm distribution with a horizontal resolution of approximately The spatial and temporal characteristics of and cor- 10 km. The largest values of reflectivity, top, VIL, size, relation between summer storm activity and lightning and average speed over the storm’s lifetime were used to over the YRD were investigated, with a focus on sub- resolve the subseasonal variation in and diurnal cycle of seasonal variability and diurnal cycles. The warm season storms over the YRD. (1 May to 31 August) from 2010 to 2014 was divided into three distinct synoptic regimes, as follows: 1) the pre- c. CG lightning data mei-yu period, characterized as dry and stable with CG lightning was detected by China Lightning mainly westerly wind flow; 2) the mei-yu period, char- Detection Network sensors located within the study acterized as an unstable and very moist period with area, as shown in Fig. 1a. The mean detection radius large-scale weather systems (mei-yu fronts) associated of a sensor is approximately 300 km, and the location with horizontal wind shear and sharp gradients in rela- error is approximately 300 m. The lightning flash de- tive humidity in the lower troposphere (Sampe and Xie tection efficiency is approximately 90% (Xia et al. 2010); and 3) the post-mei-yu period, characterized as a 2015). The lightning statistics calculated in this study very unstable and moist regime without large-scale were based on a single lightning flash, which may weather system involvement. The pre-mei-yu period consist of a series of separate return strokes (commonly is defined as the period from 1 May until the onset of referred to as a multiplicity). Data quality control was mei-yu events. The post-mei-yu period is from the end of performed in accordance with methods described by the mei-yu events until 31 August. The definition of the Cummins and Murphy (2009). Positive CG lightning mei-yu period over the study region was based on the with an intensity ,15 kA was removed, to prevent its operational forecast from the China Meteorological mischaracterization as cloud lightning. The stroke-to- Administration (Table 1). The mei-yu period varied flash grouping algorithm (Cummins and Murphy 2009) from one year to the next over the study period from was adopted to collect associated strokes into a single 2010 through 2014, with the longest and shortest mei-yu flash within a clustering radius of 10 km, centered by periods of 37 and 15 days recorded in 2011 and 2013, thefirststrokewithatimeintervaloflessthan0.5s. respectively. d. Additional data 3. Environmental conditions Global gridded analysis data from the National Centers for Environmental Prediction Final Operational Model Figure 2 presents the average subseasonal transitions Global Tropospheric Analyses dataset (FNL; https:// in wind, pressure, and relative humidity at 500 and rda.ucar.edu/datasets/ds083.2/) were used to investigate 850 hPa based on 5 years of FNL data. During the pre- large-scale conditions over the study area. The horizontal mei-yu period, strong westerlies at 500 hPa dominated resolution of the reanalysis data is 0.58, and data were over East China (Fig. 2a). Moist air mainly prevailed acquired at 0000, 0600, 1200, and 1800 UTC [0800, 1400, over southern China and the South China Sea (Fig. 2d). 2000, and 0200 local standard time (LST), respectively]. Figure 3 presents the environmental characteristics The version 4 Defense Meteorological Satellite Program- averaged over the study area (green circle in Fig. 1a) Operational Line Scanner gridded Stable Lights product with respect to the three periods considered (pre-mei-yu,

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TABLE 1. Pre-mei-yu, mei-yu, and post-mei-yu days of each year to lower instability during the mei-yu period, the storms in 2010–15 over YRD. Numbers of days during each period are in were not as intense, and the frequency of CG lightning parentheses. was lower (Fig. 3a). The monthly normalized number of Year Pre-mei-yu Mei-yu Post-mei-yu storms (Fig. 4a) was slightly less in the post-mei-yu pe- 2010 1 May–17 Jun (48) 18 Jun–18 Jul (31) 19 Jul–31 Aug (44) riod than in the mei-yu period; however, CG lightning 2011 1 May–14 Jun (45) 15 Jun–21 Jul (37) 22 Jul–31 Aug (41) occurrence in the post-mei-yu period was nearly dou- 2012 1 May–26 Jun (57) 27 Jun–18 Jul (22) 19 Jul–31 Aug (44) ble that of the mei-yu period (Fig. 4b). Notably, the 2013 1 May–23 Jun (54) 24 Jun–8 Jul (15) 9 Jul–31 Aug (54) MUCAPE increased from the mei-yu period to the post- 2014 1 May–25 Jun (56) 26 Jun–18 Jul (23) 19 Jul–31 Aug (44) mei-yu period, especially in the afternoon, when strong storm formation and lightning production are favored. mei-yu, and post-mei-yu). The pre-mei-yu period ex- The increased wind shear also facilitates storm organi- hibited the smallest and lowest amount of most unstable zation, especially multicellular storms and broad up- convective available potential energy (MUCAPE), the drafts (Palucki et al. 2011; Fuchs et al. 2015), leading to lowest level of neutral buoyancy (LNB), the least total the production of more lightning. The monthly nor- precipitable water (TPW), and the weakest vertical wind malized CG lightning occurrence (Fig. 4b)increased shear (200–850 hPa) over the YRD, among the three from the pre-mei-yu period to the mei-yu period and periods (Fig. 3). further to the post-mei-yu period. Most CG lightning During the mei-yu period, the westerlies weakened was negative (Fig. 4b) during the warm season. The and shifted northward at 500 hPa (Fig. 2b). The ridge of percentages of positive CG lightning events (the ratio the west Paciﬁc subtropical high was located at 238N. of positive CG lightning to total CG lightning) during With the enhancement in low-level southwesterly winds, the pre-mei-yu, mei-yu, and post-mei-yu periods were warm moist air was transported to the YRD (Fig. 2e). 17%, 7%, and 4%, respectively (Fig. 4b). The excep- The MUCAPE (Fig. 3a), LNB height (Fig. 3b), TPW tionally moist air during the mei-yu and post-mei-yu (Fig. 3c), and vertical wind shear (Fig. 3d) increased periods provided favorable conditions for negative CG dramatically from the pre-mei-yu period to the mei-yu lightning formation (Carey and Buffalo 2007; Fuchs period. During the post-mei-yu period, the westerlies et al. 2015). moved farther northward, and the ridge of the west Figures 5 and 6 present the spatial distributions of Paciﬁc subtropical high was located at 298N(Fig. 2c). monthly normalized storms and CG lightning (the Warm and moist air from the South China Sea extended number of storms and CG lightning events over indi- to the YRD (Fig. 2c) during the post-mei-yu period. vidual grids during each period was normalized with TPW (Fig. 3c) over the YRD decreased slightly from the respect to 30 days), respectively. The warm-season mei-yu period to the post-mei-yu period. The regional storm and CG lightning maximum regions were lo- mean MUCAPE (Fig. 3a) over the study area (Fig. 1a) cated upstream and downstream, respectively, of the 2 increased from 328 J kg 1 during the mei-yu period Nanjing radar site (gray triangle in Fig. 5) over the urban 2 to 1115 J kg 1 during the post-mei-yu period. In addi- areas along the YR (Figs. 5a and 6a). During the pre- tion, the MUCAPE (Fig. 3a) at 1400 LST exceeded mei-yu period, the storm frequency relative to the other 2 1700 J kg 1. At the same time, the LNB height (Fig. 3b) two periods was much lower (Fig. 5b). During the mei- and wind shear (Fig. 3d) reached peak values during yu period, there was a clear storm maximum region the post-mei-yu period. Thus, atmospheric conditions (Fig. 5c) with a southwest-to-northeast long axis of over during the post-mei-yu period were more favorable for 150 km near the YR, which is associated with storms organized deep convection than those of the previous embedded in the mei-yu rainband. The storms within (pre-mei-yu and mei-yu) periods. the mei-yu rainband only produced several CG lightning events (Fig. 6c). During the post-mei-yu period, the spatial distribution of storms was rather homogeneous. 4. Spatial distributions and storm properties However, two local maximum regions were located near Figure 4 presents the monthly normalized (over Hongze Lake and in an area downstream of the Nanjing 30 days) number of storms and CG lightning during each radar site along the YR; the latter corresponds to the period over the study area (green circle in Fig. 1a). The maximum region of CG lightning shown in Fig. 6d. TPW mei-yu period had the highest frequency of storms and wind shear values were comparable during the mei- among the three periods (Fig. 4a) but not the highest yu and post-mei-yu periods. One notable difference frequency of CG lightning (Fig. 4b). The higher fre- was observed for the MUCAPE, which increased from 2 2 quency of storms is attributable to continuous convec- 328 J kg 1 during the mei-yu period to 1115 J kg 1 dur- tive initiation driven by the mei-yu front; however, due ing the post-mei-yu period. Similarly, the MUCAPE at

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FIG. 2. Composite environment ﬁelds at (left) 500 and (right) 850 hPa for the (a),(d) pre-mei-yu, (b),(e) mei-yu, and (c),(f) post-mei-yu periods over 2010–14. The scale of the wind vector is marked in the solid box. The radar site is indicated by the blue triangle. The magenta line indicates the Yangtze River. Contours indicate the mean pressure (at left) and color-ﬁlled contours represents the relative humidity (at right).

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FIG. 3. The subseasonal variations of the storm environment characteristics over the study region (green circle in Fig. 1) during the pre-mei-yu, mei-yu, and post-mei-yu periods: (a) most unstable CAPE (MUCAPE), (b) LNB, (c) total precipitable water, and (d) wind shear between 200 and 850 hPa. Squares represent the mean values, and whiskers indicate 25% and 75% quartiles, respectively.

2 1400 LST increased from 465 to 1729 J kg 1 between mixed-phase region for electriﬁcation (Williams and the two periods. Previous studies have shown that Stanﬁll 2002; Williams et al. 2005). The thermodynamic thermodynamic instability is closely related to convec- instability factor appears to play more of a role than tive updrafts, which could lift supercooled water to the wind shear or TPW with respect to the differences in

FIG. 4. Variations in the monthly-normalized (a) numbers of storms and (b) CG lightning regionally summed over the study area (green circle in Fig. 1) during the pre-mei-yu, mei-yu, and post-mei-yu periods (number per month).

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FIG. 5. The spatial distribution of monthly storms, showing the (a) total, (b) pre-mei-yu, (c) mei-yu, and (d) post- mei-yu periods; the gray triangle indicates the radar location. A black line represents the Hongze Lake and a magenta line indicates the Yangtze River. lighting frequency between the mei-yu and post-mei-yu Riming ice hydrometers are crucial for thunderstorm periods over the YRD. electrification (Takahashi 1978; Saunders 1993; Carey The cumulative distribution frequencies of the storm and Rutledge 1996, 2000; MacGorman et al. 2008; properties are presented in Fig. 7. A Student’s two- Xu 2013; Kumjian and Deierling 2015; Takahashi sample t test (Student 1908) revealed that the differ- et al. 2017), with VIL providing a partial contribution. ences in storm properties among the three periods were Although VIL includes warm rain processes at low statistically significant (p , 0.05). Storm reflectivity levels that are not necessarily related to storm electrifi- during the post-mei-yu period differed within 40– cation, it can be a useful proxy for storm intensity and 55 dBZ from those in the pre-mei-yu and mei-yu pe- mixed-phase precipitation (ice) processes necessary for riods; these differences may be related to graupel and lightning production. Approximately 80% of the storms 2 small hail (Straka et al. 2000; Park et al. 2009). For the had a VIL of less than 15 kg m 2 during the pre-mei-yu post-mei-yu period, this suggests that there was a strong and mei-yu periods, whereas the percentage during the riming process favoring lightning (Zipser and Lutz 1994; post-mei-yu period was approximately 60% (Fig. 7d). Carey and Rutledge 1996, 2000; Zipser et al. 2006; Strong convective updrafts bring hydrometers to high Deierling and Petersen 2008). The VIL was also quan- levels to form high storm tops (Matthee et al. 2014); tified, in an attempt to resolve its relationship to light- therefore, a higher storm top during the mei-yu and ning, as previous studies had indicated that the two were post-mei-yu periods suggests the presence of stronger well correlated (Watson et al. 1995; Shafer et al. 2000). updrafts.

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FIG.6.AsinFig. 5, but for the lightning distribution.

Wind shear (Fig. 3d), which is also larger during the during the post-mei-yu period, with the decrease closely 2 2 mei-yu (;19 m s 1) and post-mei-yu (;21 m s 1) pe- related to the subseasonal variability in westerly steering 2 riods than during the pre-mei-yu period (;9ms 1), wind speeds (Fig. 2). along with the CAPE, was at a level favorable for the Luo et al. (2013) reported that the storms during the development of organized deep storms with intense mei-yu and post-mei-yu periods are strongly controlled lightning activity (Rotunno et al. 1988). In addition, by large-scale weather systems and local instability storms during the mei-yu and post-mei-yu periods oc- due to solar heating, respectively. This conclusion is curred over longer durations (Fig. 7b) and larger areas conﬁrmed by our results, which indicated that storm (Fig. 7f) on average, compared with those of the pre- properties and lightning activity are mainly controlled mei-yu period. These results indicate that longer lasting by environmental conditions, especially thermodynamic and broader convective updrafts can be expected during conditions. the mei-yu and post-mei-yu periods, which may also contribute to stronger lightning activity during these two periods (Williams et al. 1991; Zipser 2003; Palucki et al. 5. Diurnal cycles 2011). An unstable and moist environment (Fig. 3c) also a. Storm frequency and properties favors strong and long-lasting storms during the mei-yu and post-mei-yu periods (Cetrone and Houze 2006; May The diurnal evolution of convection is a fundamental and Ballinger 2007; Peter et al. 2015). The mean storm mode underlying regional climatic variation. Figure 8 motion speed (Fig. 7e) decreased from the pre-mei-yu presents the diurnal variation in regional storm number period to the mei-yu period and further decreased summed over the study area. Figure 9 presents the

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(a) CDF, Max Ref. (b) CDF, Dura. 1 1

0.8 0.8

0.6 0.6

0.4 0.4

All Cumulative Frequency Cumulative Frequency 0.2 Pre-Meiyu 0.2 Meiyu Post-Meiyu 0 0 40 45 50 55 60 65 70 0 30 60 90 120 150 180 210 240 270 Max Reflectivity (dBZ) Duration (min)

0.8 0.8

0.6 0.6

0.4 0.4 Cumulative Frequency Cumulative Frequency 0.2 0.2

0 0 2 4 6 8 10 12 14 0 6 12 18 24 30 36 42 48 Storm TOP (km) VIL (kg/m2)

(e) CDF, Speed (f) CDF, Size 1 1

0.8 0.8

0.6 0.6

0.4 0.4 Cumulative Frequency Cumulative Frequency 0.2 0.2

0 0 10 20 30 40 50 60 70 80 90 100 50 100 150 200 250 300 350 400 450 500 Speed (km/h) Size (km2)

FIG. 7. The cumulative distribution frequencies (CDFs) of storm properties over the study area (green circle in Fig. 1) during the pre-mei-yu, mei-yu, and post-mei-yu periods: (a) maximum reﬂectivity, (b) duration, (c) top, (d) VIL, (e) speed, and (f) size. diurnal variations in storm properties, which were nor- et al. (2018) showed that the morning peak is mainly malized to their maximum values for comparison. associated with convergence forcing produced by low- Figure 10 shows the diurnal variation in CG lightning level ageostrophic winds. The afternoon peak is related occurrence. During the mei-yu period, diurnal storm to solar heating (Luo et al. 2013). With regard to storm number (Fig. 8) varied bimodally, with two comparable properties, two maximum regions were observed in peaks at 1300 and 0500 LST. In a numerical study, Xue Figs. 9b, 9e, 9h, and 9k. The predominant one occurred

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strong, organized afternoon storms also produced more lightning (Fig. 10d) than did those of prior periods. Moisture and wind shear values were comparable between 0200 and 1400, whereas the MUCAPE differed 2 2 greatly (;500 J kg 1 at 0200 LST and ;1600 J kg 1 at 1400 LST). This instability potentially plays an important role in controlling storm properties and lightning in the afternoon during the post-mei-yu period. In the early morning (0300–0800 LST), fast mei-yu storms (Fig. 9n) potentially signify more strongly forced storms (Xue et al. 2018) or cold pool–forced mesoscale convective systems (MCSs) (Luo et al. 2014) that occur in the overnight hours with growing diurnally driven, isolated deep convection. This phenomenon is further FIG. 8. The diurnal variations of storm numbers during the pre- strengthened by the longer lifetime (Fig. 9e) and larger mei-yu, mei-yu, and post-mei-yu periods regionally summed over the study area (green circle in Fig. 1). maximum reflectivity (Fig. 9b) of these storms during the mei-yu period. By contrast, post-mei-yu storms are almost exclusively due to diurnally driven convection in during the midday and afternoon hours (1000–1600 the afternoon (Fig. 8). Figure 10 shows a clear afternoon LST), and the secondary one appeared mostly during peak in CG lightning correlated with the afternoon peak predawn and the early morning hours (0300–0800 LST). of thermally driven convection in both the mei-yu and When the normalized frequency was larger than 0.2, the post-mei-yu periods. However, the diurnal peaks in the predominant maximum regions of duration (Fig. 9e), number of storms in the mei-yu period were nearly the storm top (Fig. 9h), VIL (Fig. 9k), and size (Fig. 9q) same in the afternoon and early morning hours (Fig. 8). roughly approximated the secondary ones. When the These results indicate that thermally forced storms may normalized frequency was smaller than 0.2, the maxi- be more electrically active (or more efficient at gener- mum reflectivity (Fig. 9b), duration (Fig. 9e), and storm ating lightning) than nocturnal MCS-type systems in this top (Fig. 9h) increased markedly at around 1600 LST. region. The results are consistent with those presented The 75% quartile of MUCAPE (Fig. 3a) at 1400 LST in Fig. 9, which shows that afternoon thermally forced 2 was indicative of moderate instability (;1500 J kg 1) storms have deeper storm tops than nocturnal organized 2 and moderate wind shear (;16 m s 1)(Fig. 3d). Thus, storms during the mei-yu period. under the influence of a large-scale mei-yu front, the b. Lightning diurnal variations in mei-yu storm number and properties were relatively weak. However, during the mei-yu The peak current of CG lightning is closely related to period, a small proportion of the storms in the afternoon thunderstorm intensity. The diurnal cycle of the mean remained strong and tended to be more organized, re- peak current (MPC) for negative CG lightning is shown sulting in an afternoon peak in CG lightning occurrence in Fig. 10. The variability in MPC (Fig. 10) decreased (1400–1600 LST), as shown in Fig. 10c. from the pre-mei-yu (35–53 kA) to the mei-yu (33.4– Storm activity during the post-mei-yu period exhibi- 39.6 kA) and post-mei-yu (32.6–34 kA) periods; this is ted a pronounced diurnal cycle with a peak in the early coincident with increases in storm reflectivity, top, VIL, afternoon (1400 LST) with a larger amplitude than those duration, and size (Fig. 7) driven by atmospheric insta- of the pre-mei-yu and mei-yu periods (Fig. 8). The bility and wind shear (Fig. 3). Taken together, these normalized frequencies of storm properties, includ- findings suggest that the relatively stronger turbulence ing reflectivity (Fig. 9c), duration (Fig. 9f), storm top within strong storms during the post-mei-yu period may (Fig. 9i), VIL (Fig. 9l), and size (Fig. 9r), peaked in the create shorter distances among electrostatic thunder- afternoon (1200–1800 LST) during the post-mei-yu pe- cloud charges, resulting in frequent lightning with a riod. At 1400, the atmosphere was characterized as small peak current (Bruning and MacGorman 2013; having a moderate to large MUCAPE (Fig. 3a), high Chronis et al. 2015a,b). moisture levels (Fig. 3c), and moderate wind shear During the warm season, the MPC increased from late (Fig. 3d), thus providing a favorable environment evening to early morning, reaching a maximum at 0600 for strong and broad convective updrafts (Williams LST, and then decreased from 0700 to 1300 LST, et al. 1991; Williams and Stanfill 2002; Zipser 2003; reaching a minimum at 1300 LST (Fig. 10a). The inverse Kirkpatrick et al. 2011; Palucki et al. 2011). These correlations between the MPC and lightning numbers

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FIG. 9. The diurnal variations of storm properties during the (left) pre-mei-yu, (middle) mei-yu, and (right) post-mei-yu periods over the study area (green circle in Fig. 1): (a)–(c) maximum reﬂectivity, (d)–(f) duration, (g)–(i) top, (j)–(l) VIL, (m)–(o) speed, and (p)–(r) size. are consistent with similar measurements acquired over system characterized by weak instability, moderate wind the continental United States. However, the range of shear, and moist air. From 1000 to 1800 LST, the MPC variation in the MPC revealed by the current study is (Fig. 10c) decreased to less than 38 kA, reaching a obviously much larger than that for the United States, minimum value around 33.4 kA at 1900 LST, which is except for the oceanic subregion described by Chronis close to the minimum storm number at 2000 LST shown et al. (2015a). in Fig. 8. This may be due to lightning from a relatively The morning mei-yu storms with their frequent oc- few slow-moving evening storms with strong reﬂectivity currences and moderate intensity produced some light- and high tops (Fig. 9). ning, but with a high MPC (Fig. 10c). The morning MPC The MPC (Fig. 10d) during the post-mei-yu period (0400–0900 LST) was relatively uniform with a large exhibited three peaks and seemed to have no relation- mean value, which is consistent with the morning peak ship with respect to lightning occurrence; it should observed for moderate mei-yu storms (Figs. 8 and 9); be noted that the MPC varied within a small range these storms are controlled by a sustained weather (32.6–34 kA).

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FIG. 10. Diurnal variations of lightning numbers (regionally summed) and mean value of peak current (regionally averaged) for the negative CG lightning (red line with asterisk) during the pre-mei-yu, mei-yu, and post-mei-yu periods over the study area (green circle in Fig. 1). c. Diurnal variation in spatial distribution moisture were observed during the post-mei-yu period. The atmospheric instability did not favor storm initia- The storms and lightning mainly occurred during the tion during the nighttime hours (Figs. 12a,b,h), but mei-yu and post-mei-yu periods. Figures 11 and 12 conditions became more favorable during the afternoon present the spatial distributions of the 3-hourly accu- (Figs. 12e,f). There were two local maximum regions of mulated storm frequency during the mei-yu and post- storms in the afternoon—one near Hongze Lake (region mei-yu periods, respectively, and Figs. 13 and 14 show A) and the other in an urban area along the YR, the respective distributions of CG lightning during the same two periods. From 0000 to 0300 LST, mei-yu downstream of the Nanjing radar site (region B). Region storms formed upstream of the Nanjing radar site along A may be related to the lake breeze driven by the the YR. The maximum region of the storm continued to temperature gradient between the lake and the land strengthen and expand from 0300 to 0600 LST. From surface. The lake breeze may converge with southerly 0900 to 1200 LST, the storm center shifted northeast- monsoonal flows to enhance local convective activity ward. The spatial distributions of the 3-hourly accumu- (King 1996; King et al. 2003; Wang et al. 2019). Region B lated lightning occurrence revealed that most lightning is collocated with the local maximum region of CG was not related to this maximum region of storms lighting (Figs. 14e,f) in the afternoon, which may be (Figs. 13a–d). This phenomenon also appeared over related to an effect in which a strong sensible heat flux the following time periods: 1500–1800, 1800–2100, and enhances cloud formation over urban areas (Inoue and 2100–2400 LST. From 1200 to 1500 LST, a small maxi- Kimura 2004). Notably, the prevailing wind direction mum region of lightning (Fig. 13) was located along the influences the location of these events (Haberlie et al. margin of the maximum region of storms. These results 2015). In addition, the circulation caused by an urban indicate that lightning was produced by a minority of heat island can interact with various processes; thus, this strong storms, rather than the frequent moderate storms phenomenon may be another contributing factor for that occurred during the mei-yu period. various precipitation patterns (Tang and Miao 1998; At 0200 and 1400 LST, low and high MUCAPE, re- Chen et al. 2007; Zhang et al. 2011; Dou et al. 2015; Li spectively, as well as moderate wind shear and high et al. 2015).

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FIG. 11. Spatial distributions of the storm occurrence frequency between 0000 and 0300, 0300 and 0600, 0600 and 0900, 0900 and 1200, 1200 and 1500, 1500 and 1800, 1800 and 2100, and 2100 and 2400 LST during the mei-yu period. The white line indicates the Yangtze River; the black line represents Hongze Lake.

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FIG. 12. As in Fig. 11, but for storms during the post-mei-yu period.

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FIG. 13. As in Fig. 11, but for lightning during the mei-yu period.

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FIG. 14. As in Fig. 11, but for lightning during the post-mei-yu period.

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6. Summary and conclusions further to the post-mei-yu period, which corresponds well with patterns associated with storm intensity. S-band weather radar data and CG lightning data from 2010 to 2014 were used to investigate the charac- Storms and CG lightning located around urban areas teristics of convective storms over the YRD in China. during the post-mei-yu period may be related to urban The storm properties, including the storm duration, effects. Future work will include the examination of me- size, top, maximum reflectivity, and VIL, were derived soscale forcing induced by urban effects, the river valley, using the SCIT algorithm. The subseasonal variability and other possible contributing factors related to the storm in storm characteristics and lighting intensity during and lightning maximum regions during the post-mei-yu different phases of the mei-yu season were investi- period, based on convection-permitting simulations. gated. The results indicated that storm and lighting characteristics exhibit strong subseasonal variability Acknowledgments. This work was primarily sup- under different synoptic forcings. The environmental ported by the National Key Research and Development factors influencing storm and lighting activity during Program of China (Grant 2017YFC1501703), the different mei-yu phases were further resolved using National Natural Science Foundation of China (Grants reanalysis data. The main findings of this study are 41475015, 41275031, 41805025, 41322032), and the Open given below. Research Program of the State Key Laboratory of Severe Weather. Xingchao Chen is supported by the 1) During the mei-yu period, storms occurred most Office of Science of DOE Biological and Environmental frequently along the YR, with peak activity occurring Research as part of the Regional and Global Modeling in the early morning and afternoon. The mei-yu and Analysis program. We acknowledge the Jiangsu storms were strongly controlled by the synoptic-scale Meteorological Bureau for collecting and archiving the weather system called the mei-yu front. During this radar data. The data supporting the analysis and con- period, the average environmental conditions were clusions of this paper, including the processed radar characterized by weak instability, moderate wind observations and the synoptic data, can be requested by shear, and high moisture levels, which resulted in the contacting the office at [email protected]. frequent occurrence of long-lived moderate storms. As such, there was relatively weak diurnal variation in mei-yu storm number and storm properties. On REFERENCES average, the afternoon storms were associated with Arakawa, A., 2004: The cumulus parameterization problem: Past, higher reflectivity and higher storm tops than were present, and future. J. Climate, 17, 2493–2525, https://doi.org/ morning storms. 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