atmosphere
Article Precipitation Microphysical Characteristics of Typhoon Mangkhut in Southern China Using 2D Video Disdrometers
Lu Feng 1, Sheng Hu 1, Xiantong Liu 1,*, Hui Xiao 1, Xiao Pan 2, Feng Xia 1, Guanhua Ou 3 and Chu Zhang 4
1 Guangzhou Institute of Tropical and Marine Meteorology, China Meteorological Administration, Guangzhou 510641, China; [email protected] (L.F.); [email protected] (S.H.); [email protected] (H.X.); [email protected] (F.X.) 2 Institute of Atmospheric Environment, China Meteorological Administration, Shenyang 110166, China; [email protected] 3 Xinfeng Meteorological Bureau, China Meteorological Administration, Xinfeng, Guangdong 512028, China; [email protected] 4 Jiangmen Meteorological Bureau, China Meteorological Administration, Jiangmen, Guangdong 529000, China; [email protected] * Correspondence: [email protected]
Received: 3 August 2020; Accepted: 8 September 2020; Published: 11 September 2020
Abstract: The microphysical characteristics of tropical cyclones vary in different rain regions, which affects not only the dynamic and thermodynamic mechanisms of the typhoon system but also the development of tropical cyclones. This study analyzed the raindrop size distribution (DSD) and the gamma DSD parameters associated with Typhoon Mangkhut using three two-dimensional (2D) video disdrometers from the Longmen Field Experiment Base for Cloud Physics, China Meteorological Administration in Guangdong, China during 16–17 September 2018. According to the observed track and radar reflectivity, this process can be divided into three distinct segments: the outer rainband before landfall (S1), the inner core (S2), and the outer rainband after landfall (S3). The outer rainband mainly produces stratiform rains, while the inner core mainly produces convective rains. The temporal and spatial variations in the rain rate, radar reflectivity, and DSD parameters of the different segments were analyzed and compared at three sites. Although the DSD characteristics are distinctly different in the three segments, the DSD characteristics of the same segment were similar at different sites. In the inner core (S2), the precipitation contains smaller drops (around 0.5 mm) and the concentrations are higher within each size bin compared with those of the other segments, resulting in the maximum 1 3 rain rate (11.66 mm h− ), radar reflectivity (34.53 dBZ), liquid water content (0.65 g m− ), and number 1 3 concentration (4.12 mm− m− on a logarithmic scale) occurring in this segment. The Nw–Dm scatter pairs have maritime-like convection, which increases outward from the inner core (S2). The relationship between the shape (µ) and slope (Λ) was also investigated. The microphysical characteristics determined in this study provide useful information for understanding microphysical precipitation processes and for improving the precision of numerical weather prediction models.
Keywords: Typhoon Mangkhut; 2D video disdrometer; raindrop size distribution; microphysics; precipitation
1. Introduction The raindrop size distribution (DSD) is a key parameter for cloud and precipitation microphysical process analysis, which is essential for creating numerical weather prediction models [1,2].
Atmosphere 2020, 11, 975; doi:10.3390/atmos11090975 www.mdpi.com/journal/atmosphere Atmosphere 2020, 11, 975 2 of 18
The variations in the DSD are also important to quantitative precipitation estimation (QPE) and forecasting (QPF) based on polarimetric radar [3,4]. In the past, conventional measurement techniques, including the momentum method, the flour method, filter paper, raindrop camera, and the immersion method, have been used to collect and determine the DSD parameters artificially. However, these methods have many disadvantages, such as measurement error, a heavy workload, and low efficiency [5]. To develop a faster technique, the Joss–Waldvogel (JW) disdrometer, the optical disdrometer, and the acoustic disdrometer were invented [6–10]. Use of the optical disdrometer is widespread now, including the one-dimensional disdrometer (such as the Parsivel) and the two-dimensional (2D) disdrometer (such as the 2D Video Disdrometer, 2DVD). Moreover, Raupach et al. [11] presented a method that improved the accuracy of the DSD measurements recorded using the Parsivel by using a 2DVD as a reference instrument. Compared with the Parsivel, the 2DVD can effectively avoid the particle superposition errors because it performs high-speed scanning in two mutually perpendicular directions and obtains accurate, high-resolution DSD parameters (particle shape, diameter, axial ratio, and size distribution) vertically and horizontally [12,13]. However, the 2DVD is rarely used to obtain the microphysical characteristics of precipitation particles in China because it is quite expensive [14]. Several 2DVDs have been built in the Longmen Field Experiment Base for Cloud Physics, China Meteorological Administration, in recent years, for the in-depth investigation of microphysical precipitation processes. Based on the JW disdrometer, the DSDs of seven tropical cyclones in the United States were found to exhibit high concentrations of both small and midsize drops [15]. Chen et al. [16] focused on the DSD of a typhoon in Fujian Province, China, using a Parsivel. They found that the stratiform rain consisted of rimed ice particles and the melting of graupel in the outer rainband and eye region. Based on the 2DVD and C-band polarimetric radar, Chang et al. [17] investigated the DSDs and drop shape relations (DSR) of typhoon systems during landfall in the western Pacific. They determined that the DSDs collected by the 2DVD were located between the maritime and continental clusters, which were defined by Bringi et al. [18], while exhibiting a maritime convective type over the ocean based on the C-band polarimetric radar. During the passage of Typhoon Matmo over Eastern China, Wang et al. [19] investigated the DSDs of the different stages of the typhoon using an S-band polarimetric radar and a 2DVD. Furthermore, the convective rain was compared by Bringi et al. [18]. Based on the 2DVD and C-band polarimetric radar data, Wen et al. [20] attempted to investigate the DSD and DSR of seven typhoons in China. They found that although the DSDs of the seven typhoons differed, the microphysical characteristics of two of the typhoons were similar. Bao et al. [21] studied the DSDs of the different rainbands of Typhoon Fitow during landfall in Eastern China using a Parsivel. Moreover, they demonstrated that the evolutions of the DSDs with increasing rain rate in the different convective rainbands were completely different. Previous studies have investigated the DSD characteristics of different rain types of different precipitation systems in different rain regions [20–24]. Several scholars have focused on the DSD characteristics of tropical cyclone precipitation systems before and after landfall [25,26]. Heavy rainfall events are common in Southern China, and they frequently cause financial loss and endanger people’s lives and societal security. Although various scholars have investigated the DSDs of typhoon systems, they are still poorly studied in Southern China, and few studies have focused on the different horizontal and spatial distributions of typhoons. In this study, we focus on the DSD characteristics of Typhoon Mangkhut as it made landfall over Southern China using a 2DVD, revealing that it had unique dynamic and microphysical characteristics. Moreover, the different rain regions in numerical weather prediction models may require different microphysical parameterization schemes. Atmosphere 2020, 11, x FOR PEER REVIEW 3 of 18
2. Data and Methods
2.1. Instruments and Dataset In this study, the datasets were collected using the 2DVD from the Longmen Field Experiment Base for Cloud Physics, China Meteorological Administration. The three 2DVDs at the Enping (EP), Fogang (FG), and Xinfeng (XF) sites were used during Typhoon Mangkhut’s passage over Guangdong on September 16–17, 2018 (Figure 1). The 2DVDs performed high-speed scanning with light line arrays in two mutually perpendicular directions (55 kHz). The rectangular sample area was about 10 × 10 cm2, and the sampling interval of the particle sizes was 0.2 mm (from 0.1 to 8.1 mm) in diameter. The details of the 2DVD instrument can be found at www.distrometer.at. First, the 2DVD data were processed into a one-minute resolution dataset, and then, its quality was controlled using Tokay’s method [27]. For every 1 minute, if the rain rate was less than 0.1 mm h–1 or the total number of raindrops was less than 10, the data point was removed to ensure data quality. The processed 2DVD observation data are consistent with that of a rain gauge, which has been assessed by Feng et al. [28]. Moreover, the number concentration of raindrops with diameters Atmosphere 2020, 11, 975 3 of 18 in the range of a unit size interval ( ) is calculated as follows:
( ) 1 2. Data and Methods ( ) = (1) ∙∆ ∙ , ∙∆ 2.1. Instruments and Dataset 2 where is the effective sampling area (about 10 × 10 cm ); ∆ is the sampling time (1 min); , (m s–1) isIn the this fall study, speed the in datasetsthe ith size were bin collected and in the using number the 2DVD of raindrops from the bin Longmen j; ( ) Field is the Experimentnumber of raindropsBase for Cloud in each Physics, bin; and China ∆ Meteorological is the sampling Administration. interval of the particle The three sizes 2DVDs (0.2 mm). at the Enping (EP), FogangIn addition, (FG), and Xinfengan S-band (XF) polarimetric sites were used radar during was Typhoonused to Mangkhut’scollect the passageradar reflectivity over Guangdong at the Guangzhouon 16–17 September site (GZ). 2018 The (Figure S-band1). The polarimetric 2DVDs performed radar high-speedsimultaneously scanning transmits with light and line receives arrays horizontallyin two mutually and perpendicular vertically polarized directions scattered (55 kHz). signals The rectangular with the resolution sample area range was aboutincreasing 10 10 from cm2 , × 1000and theto 250 sampling m. The interval S-band ofpolarimetric the particle radar sizes was 0.2processed mm (from into 0.1 a six-minute to 8.1 mm) resolution in diameter. dataset, The details and itsof thequality 2DVD was instrument controlled can usin beg foundthe method at www.distrometer.at of Liu [13]. .
Figure 1. The geographic locations of the instruments in Guangdong used in this study. The three 2D Figure 1. The geographic locations of the instruments in Guangdong used in this study. The three Video Disdrometer (2DVDs) were located at the Enping (EP), Fogang (FG), and Xinfeng (XF) sites. 2D Video Disdrometer (2DVDs) were located at the Enping (EP), Fogang (FG), and Xinfeng (XF) sites. The S-band polarimetric radar was located at the Guangzhou (GZ) site. The S-band polarimetric radar was located at the Guangzhou (GZ) site.
2.2. 2DVDFirst, Data the 2DVD Processing data were processed into a one-minute resolution dataset, and then, its quality wasThe controlled gamma using distribution Tokay’s of method the DSDs [27 ].is Forexpressed every 1 as minute, if the rain rate was less than 0.1 mm 1 h− or the total number of raindrops was less than 10, the data point was removed to ensure data quality. The processed 2DVD observation ( data) = are consistentexp( Λ with) that of a rain gauge, which has been(2) –1 –3 –1 whereassessed by (mm Feng m et al.) is[ the28]. intercept; Moreover, the is the number shape; concentration and Λ (mm of) is raindrops the slope. with The diameterscurve decreases in the whenrange of a> unit0, and size intervalit increasesN(D iwhen) is calculated < 0. as When follows: = 0, it degenerates into an exponential
41 n(i) X X 1 N(Di) = (1) A ∆t Vi j ∆Di i=1 j=1 · · , · where A is the effective sampling area (about 10 10 cm2); ∆t is the sampling time (1 min); V (m s 1) × i,j − is the fall speed in the ith size bin and in the number of raindrops bin j; n(i) is the number of raindrops in each bin; and ∆Di is the sampling interval of the particle sizes (0.2 mm). In addition, an S-band polarimetric radar was used to collect the radar reflectivity at the Guangzhou site (GZ). The S-band polarimetric radar simultaneously transmits and receives horizontally and vertically polarized scattered signals with the resolution range increasing from 1000 to 250 m. The S-band polarimetric radar was processed into a six-minute resolution dataset, and its quality was controlled using the method of Liu [13].
2.2. 2DVD Data Processing The gamma distribution of the DSDs is expressed as
N(D) = N Dµ exp( ΛD) (2) 0 − Atmosphere 2020, 11, 975 4 of 18
1 3 1 where N0 (mm− m− ) is the intercept; µ is the shape; and Λ (mm− ) is the slope. The curve decreases when µ > 0, and it increases when µ < 0. When µ = 0, it degenerates into an exponential distribution. 1 3 The exponential distribution with N0 = 8000 mm− m− is known as the Marshall–Palmer DSD [29]. 6 3 When N(Di) is calculated using Equation (1), the radar reflectivity factor Z (mm m− ), the rain 1 3 rate R (mm h− ), the liquid water content LWC (g m− ), and the total raindrop number concentration 3 Nt (m− ) can be calculated using the following equations:
XL 6 ( ) Z = Di N Di ∆Di (3) i=1
XL 6π 3 R = D ViN(Di)∆Di (4) 104 i i=1 L π X LWC = D3N(D )∆D (5) 6000 i i i i=1 XL Nt = N(Di)∆Di (6) i=1 where L is the total number of bins (L = 41); Di (mm) is the equivalent spherical raindrop diameter 1 in the ith size bin; ∆Di (mm) is the corresponding diameter interval; and Vi (m s− ) is the fall speed 1 3 in velocity bin i. N(Di) (mm− m− ) is the number concentration of raindrops with diameters in the range of D 0.5∆D to D + 0.5∆D (per unit size interval). i − i i i The nth-order moment of the DSD is defined as
Z Dmax n Mn = N(D)D dD0. (7) 0
The mass-weighted mean diameter Dm (mm) is defined as the ratio of the fourth to the third moment of the size distribution as shown in (8):
M4 Dm = . (8) M3
1 3 The generalized intercept parameter Nw (mm− m− ) is given by ! (4.0)4 103W N = (9) w 4 πρω Dm
3 3 3 where ρω (g cm− ) is the density of water (1 g cm− ), and W (g m− ) is the rainwater content.
3. Overview of the Typhoon Typhoon Mangkhut formed over the western north Pacific Ocean on 14 September 2018 and made landfall in Guangdong Province at 16:00 BST on 16 September 2018. Its maximum wind speed 1 was 45 m s− , and its minimum central pressure was 955 hPa. It moved northwest at 25–30 km 1 h− . The typhoon caused heavy rainfall in western Guangdong, eastern Guangdong, and the Pearl River Delta. The typhoon weakened and dissipated on 17 September 2018. During its passage over Guangdong, Typhoon Mangkhut passed through the disdrometer site. The National Centers for Environmental Prediction’s (NCEP) reanalysis data with a 0.25 0.25 ◦ × ◦ spatial resolution at 08:00 BST on 16 September (Figure2a,b), and the convective available energy (CAPE) for the three 2DVDs from the nearest sounding data at Yangjiang station and Heyuan station (Figure2c,d) were used to analyze the precipitation system. The western Pacific subtropical high is Atmosphere 2020, 11, 975 5 of 18
located in southern Japan (25◦ N–35◦ N) (Figure2a). The airflow transported moisture and energy to Typhoon Mangkhut (Figure2b). The main airflow came from the southeasterly jet from the Bay of Bengal, which is located near the equatorial convergence zone (5–15◦ N). The southeasterly jet 1 continuously transported more moisture with a wind velocity greater than 7.5 m s− and a moisture 1 1 1 flux divergence greater than 12 g cm− hPa− s− . The large moisture flux divergence in the typhoon’s 1 1 1 centerAtmosphere was 2020 greater, 11, x FOR than PEER 60 REVIEW g cm− hPa− s− . In the outer rainband, before landfall (Figure5 of 218c,d), the water vapor content was high in the lower layer and low at 850–700 hPa. The CAPE values at two 1 –1 stationsThe CAPE were values greater at thantwo stations 930 J kg were− . The greater wind than direction 930 J kg transitioned. The wind fromdirection northly transitioned near the from ground layernorthly to easterly near the in theground low layer layer, to transporting easterly in the the low warm, layer, moist transp airorting in the the atmospheric warm, moist boundary air in the layer. Theatmospheric dry, cold airflow boundary in thelayer. mid-high The dry, level,cold airflow the warm, in the moistmid-high airflow level, in the the warm, low level,moist airflow and the in high CAPEthe low values level, were and beneficial the high CAPE to thermal values development were beneficial [30 to– thermal32]. development [30–32].
(a) (b)
(c) (d)
FigureFigure 2. National2. National Centers Centers for for Environmental Environmental Prediction reanalysis reanalysis data data with with a 0.25° a 0.25 × ◦0.25°0.25 spatial◦ spatial 5 ×1 resolutionresolution collected collectedat at 08:0008:00 BST BST on on September September 16, 16,2018. 2018. (a) Vorticity (a) Vorticity field (10 field–5s–1) (10at 500− shPa,− ) atand 500 (b) hPa, –1 –1 1–1 1 1 andwind (b) windfield and field moisture and moisture flux divergence flux divergence (g cm (ghPa cm −s )hPa at 850− s hPa.− ) at T–lnp 850 hPa.curves T–lnp for 06:00 curves BST for on 06:00 BST16 on September 16 September 2018 at 2018 (c) Yangjiang at (c) Yangjiang station stationand (d) Heyuan and (d) Heyuanstation. station.
FigureFigure3 shows 3 shows the observedthe observed track track of Typhoon of Typhoon Mangkhut Mangkhut and theand radarthe radar reflectivity reflectivity of the of constant the altitudeconstant plan altitude position plan indicator position (CAPPI) indicator at (CAPPI) an elevation at an elevation angle of 0.5angle◦ at of the 0.5° GZ at sitethe basedGZ site on based the S-bandon polarimetricthe S-band radarpolarimetric with a radar 200 km with range. a 200 Accordingkm range. According to the observed to the observed track and track the radarand the reflectivity, radar thisreflectivity, process can this be process divided can into be threedivided distinct into th segments:ree distinct thesegments: outer rainbandthe outer beforerainband landfall before (S1), thelandfall inner core (S1), (S2), the inner and thecore outer (S2), and rainband the outer after rainba landfallnd after (S3). landfall To make (S3). itTo more make clear, it more the clear, movement the directionmovement and direction the direction and the perpendicular direction perpendicular to the movement to the movement are shown are in shown Figure in3 b–e.Figure It 3b–e. should It be notedshould that be during noted thethatpassage during the of Typhoonpassage of Mangkhut, Typhoon Mangkhut, the time seriesthe time of theseries disdrometer of the disdrometer data at the data at the FG and XF sites reveal two different segments (S1 and S3) associated with these geographic positions. The standard to distinguish between S1 and S3 is whether the perpendicular (solid red arrow) passed the site or not. The specific time periods of the three segments at the three sites are presented in Table 1.
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Table 1. Duration of the three segments observed by the three 2DVDs.
Period Site Segment Distance (km) Beginning Ending S1 09:00 BST, 16 Sep 2018 16:29 BST, 16 Sep 2018 223 EP S2 16:30 BST, 16 Sep 2018 18:59 BST, 16 Sep 2018 58 S3 19:00 BST, 16 Sep 2018 10:00 BST, 17 Sep 2018 260 Atmosphere 2020, 11, 975 S1 09:00 BST, 16 Sep 2018 16:59 BST, 16 Sep 2018 301 6 of 18 FG S3 17:00 BST, 16 Sep 2018 10:00 BST, 17 Sep 2018 402 S1 09:00 BST, 16 Sep 2018 14:59 BST, 16 Sep 2018 328 XF S3 15:00 BST, 16 Sep 2018 10:00 BST, 17 Sep 2018 451 FG and XF sites reveal two different segments (S1 and S3) associated with these geographic positions. Note: The terms S1, S2, and S3 represent the outer rainband before landfall, the inner core, and the The standard to distinguish between S1 and S3 is whether the perpendicular (solid red arrow) passed outer rainband after landfall, respectively. The distance is that between the tropical cyclone’s center the site or not. The specific time periods of the three segments at the three sites are presented in Table1. and each disdrometer site (S1, S2, and S3).
(a)
Atmosphere 2020, 11, x FOR PEER REVIEW 7 of 18 (b) (c)
(d) (e)
FigureFigure 3. (a) 3. Observed (a) Observed track track of Typhoon of Typhoon Mangkhut, Mangkhut, (b–e ()b radar–e) radar reflectivity reflectivity factor factor Z (dBZ) Z (dBZ) at 15:00at 15:00 BST, 16:00BST, 17:0016:00 BST, and17:00 19:00 BST, BST,and respectively.19:00 BST, respec Thetively. solid blackThe solid arrow black is the arrow movement is the movement direction of Typhoondirection Mangkhut. of Typhoon The Mangkhut. solid red arrow The solid is the red direction arrow is perpendicularthe direction perpendicular to the solid to black the solid arrow. black The two linesarrow. intersect The two in lines the typhoon’sintersect in eye.the typhoon’s eye.
The temporal variability of the instantaneous wind speed and the hourly rain rate at the EP, FG, and XF sites obtained from the National Ground Observation Station of China are shown in Figure 4. The maximum instantaneous wind speed (23.3 m s–1) and the hourly rain rate (47.6 mm h–1) occurred at the EP site during S2. Compared to S1, S3 had a lower instantaneous wind speed and a higher hourly rain rate.
Figure 4. The temporal variabilities of the instantaneous wind speed and hourly rain rate obtained from the National Ground Observation Station of China at the (a) EP, (b) FG, and (c) XF sites.
In general, coastal Southern China was affected by a positive vorticity at 500 hPa, a low pressure at 850 hPa, and a high moisture content in the lower layer, which improved the development of the tropical cyclone. In addition, the wind was strong, and the rain rate was heavy during S2. Atmosphere 2020, 11, x FOR PEER REVIEW 7 of 18
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Table 1. Duration of the three segments observed by the three 2DVDs.
Period Site Segment Distance (km) Beginning Ending S1 09:00 BST, 16 Sep 2018 16:29 BST, 16 Sep 2018 223 EP S2 16:30 BST, 16 Sep 2018 18:59 BST, 16 Sep 2018 58
S3 19:00 BST, 16 Sep 2018 10:00 BST, 17 Sep 2018 260 S1 09:00 BST, 16 Sep 2018 16:59 BST, 16 Sep 2018 301 FG (d) (e) S3 17:00 BST, 16 Sep 2018 10:00 BST, 17 Sep 2018 402 S1 09:00 BST, 16 Sep 2018 14:59 BST, 16 Sep 2018 328 XF Figure 3. (aS3) Observed 15:00track BST,of Typhoon 16 Sep 2018 Mangkhut, ( 10:00b–e) radar BST, 17 reflectivity Sep 2018 factor Z (dBZ) 451 at 15:00 BST,Note: 16:00 The terms BST, S1, 17:00 S2, and BST, S3 representand 19:00 the outerBST, rainbandrespectively. before The landfall, solid the black inner core,arrow and is the the outer movement rainband directionafter landfall, of Typhoon respectively. Mangkhut. The distance The is thatsolid between red arrow the tropical is the direction cyclone’s centerperpendicular and each disdrometerto the solid site black (S1, arrow.S2, and S3).The two lines intersect in the typhoon’s eye.
The temporal variability of the the instantaneous instantaneous wind wind speed speed and and the the hourly hourly rain rain rate rate at at the the EP, EP, FG, FG, and XF sites obtained obtained from from the the National National Ground Ground Observation Observation Station Station of of China China are are shown shown in in Figure Figure 44.. –11 –11 The maximum instantaneous windwind speedspeed (23.3(23.3 mm ss− ) and the hourly rainrain raterate (47.6(47.6 mmmm hh− )) occurred occurred at the EP site during S2. Compared Compared to to S1, S1, S3 S3 had a lower instantaneous wind speed and a higher hourly rain rate.
Figure 4. The temporal variabilities of the instantaneous wind speed and hourly rain rate obtained from the National Ground Observation Station ofof ChinaChina atat thethe ((a)) EP,EP, ((bb)) FG,FG, andand ((cc)) XFXF sites.sites.
In general,general, coastalcoastal Southern Southern China China was was aff ectedaffected by aby positive a positive vorticity vorticity at 500 hPa,at 500 a lowhPa, pressure a low pressureat 850 hPa, at and 850 a highhPa, moistureand a high content moisture in the lowercontent layer, in whichthe lower improved layer, thewhich development improved of the developmenttropical cyclone. of the In addition,tropical cyclone. the wind In was addition, strong, the and wind the rainwas ratestrong, was and heavy the during rain rate S2. was heavy duringIn S2. the following sections, the characteristics of the DSDs during the three segments are analyzed to determine the microphysical process of Typhoon Mangkhut. The DSDs at the three sites are also compared to reveal any spatial variations. Atmosphere 2020, 11, x FOR PEER REVIEW 8 of 18
In the following sections, the characteristics of the DSDs during the three segments are analyzed to determine the microphysical process of Typhoon Mangkhut. The DSDs at the three sites are also compared to reveal any spatial variations.
Atmosphere4. DSDs 2020Characteristics, 11, 975 Derived from the 2DVD Measurements at the Three Stations 8 of 18
4.1. Temporal Evolution and Variations in the Raindrop Size Distribution (DSDs) 4. DSDs Characteristics Derived from the 2DVD Measurements at the Three Stations Figure 5 shows the time series of the DSDs observed by the three 2DVDs. The average DSD 4.1.parameters Temporal for Evolution each segment and Variations are presented in the Raindrop in Table Size2. When Distribution we focused (DSDs) on the EP site (Figure 5a–c), we found that the evolution trends of the rain rate, radar reflectivity, and number concentration wereFigure consistent.5 shows The the radar time reflectivity series of theand DSDsnumber observed concentration by the increase three 2DVDs. with increasing The average rain DSD rate. parametersCompared with for each the segmentother segments, are presented S1 exhibited in Table the2. Whenminimum we focused radar reflectivity on the EP siteof 29.10 (Figure dBZ5a–c), and wemass-weighted found that themean evolution diameter trends of 1.30 of mm, the rainand rate,a relatively radar reflectivity,low rain rate and (5.28 number mm h concentration–1) and liquid werewater consistent. content (0.28 The radarg m–3) reflectivity on average. and The number main concentration characteristics increase of S1 withwere increasingthe relatively rain rate.low Comparedconcentrations with of the small other and segments, midsize drops S1 exhibited (<3 mm) the and minimum the narrowest radar reflectivityraindrop spectra of 29.10 (maximum dBZ and 1 mass-weighteddiameter of about mean 3 mm). diameter The ofraindrops 1.30 mm, with and diameters a relatively of low < 1 rain mm, rate 1–3 (5.28 mm, mm and h −> 3) andmm liquidare defined water 3 contentas small, (0.28 midsize, g m− and) on large average. drops The by main Tokay characteristics et al. [27] and of Janapati S1 were et the al. relatively [25]. We lowused concentrations the same size ofclassification small and midsize criteria dropsin this ( Figure 5. Cont. Atmosphere 2020, 11, 975 9 of 18 Atmosphere 2020, 11, x FOR PEER REVIEW 9 of 18 1–1 –33 FigureFigure 5.5. TemporalTemporal evolution evolution of of the the number number concentration concentration ND ND (mm (mm− m m− ,, shownshown byby lgND),lgND), rainrain raterate 1 –1 RR (mm(mm h −h),), radar radar reflectivity reflectivity factor factor Z (dBZ), Z (dBZ mass-weighted), mass-weighted mean diameter mean Ddiameterm (mm), andDm normalized(mm), and 1 3 –1 –3 numbernormalized concentration number concentration Nw (mm− m −N,w shown(mm bym the, shown lgNw )by at the (lgNa–c)w) EP, at (thed–f )(a FG,–c) andEP, ((gd––if)) XFFG, sites. and (g–i) XF sites. Table 2. Microphysical characteristics of the raindrop size distributions of the three segments of TyphoonTable 2. MangkhutMicrophysical at the characteristics three sites. The of 1stthe/2nd raindrop/3rd values size distributions are the means, of medians, the three and segments standard of deviationsTyphoon Mangkhut for specific at periods, the three respectively. sites. The 1st/2nd/3rd values are the means, medians, and standard deviations for specific periods,R respectively. Z D lgN LWC Site Segment m w 1 (dBZ) (mm) (mm 1 m 3) 3 (mmR h− ) Z Dm lgNw− − LWC(g m − ) Site Segment S1 5.28(mm/3.57 h–1/)4.83 29.10(dBZ)/37.31 /7.97 1.30(mm)/1.30 /0.24(mm 3.66–1/ 3.77m–3)/ 0.41 0.28(g m/0.23–3) /0.24 EP S2S1 11.66 5.28/3.57/4.83/9.12/11.02 29.10/37.31/7.97 34.53/43.97/8.84 1.30/1.30/0.241.33/1.48/0.44 3.66/3.77/0.41 4.12/4.12/0.38 0.28/0.23/0.24 0.65/0.59/0.55 EP S3S2 11.66/9.12/11.02 5.05/2.84/8.44 34.53/43.97/8.84 30.88/38.90/6.98 1.33/1.48/0.441.52/1.51/0.31 4.12/4.12/0.38 3.34/3.38/0.36 0.65/0.59/0.55 0.26/0.16/0.42 S3 5.05/2.84/8.44 30.88/38.90/6.98 1.52/1.51/0.31 3.34/3.38/0.36 0.26/0.16/0.42 S1S1 2.06/1.50/2.112.06/1.50/2.11 25.40/33.01/6.89 25.40/33.01/6.89 1.24/1.21/0.271.24/1.21/0.27 3.46/3.46/0.30 3.46/3.46/0.30 0.12/0.10/0.11 0.12/0.10/0.11 FG FG S3S3 6.36/4.24/11.986.36/4.24/11.98 29.99/38.70/8.34 29.99/38.70/8.34 1.28/1.29/0.291.28/1.29/0.29 3.82/3.91/0.35 3.82/3.91/0.35 0.35/0.25/0.57 0.35/0.25/0.57 S1S1 2.42/1.97/1.852.42/1.97/1.85 27.34/35.23/5.37 27.34/35.23/5.37 1.29/1.29/0.191.29/1.29/0.19 3.50/3.47/0.32 3.50/3.47/0.32 0.14/0.11/0.11 0.14/0.11/0.11 XF XF S3S3 3.45/1.94/4.683.45/1.94/4.68 26.26/33.74/7.66 26.26/33.74/7.66 1.21/1.20/0.291.21/1.20/0.29 3.68/3.72/0.38 3.68/3.72/0.38 0.19/0.13/0.23 0.19/0.13/0.23 Note: The terms R, Z, Dm, lgNw, and LWC are the rain rate, radar reflectivity, mass-weighted mean Note: The terms R, Z, Dm, lgNw, and LWC are the rain rate, radar reflectivity, mass-weighted mean diameter, diameter,normalized normalized number concentration, number concentration, and liquid water and content, liquid respectively. water content, respectively. 4.2.4.2. DSDDSD ParametersParameters ScatterplotsScatterplots ofof thethe shapeshape parameterparameter (µ(μ),), mass-weighted mass-weighted mean mean diameter diameter (D (Dmm),), slopeslope parameterparameter ((ΛΛ),), andand totaltotal concentration concentration (N (Nt)t) versusversus the the rain rain rate rate (R) (R) for for the the three three segments segments are are shown shown in in Figure Figure6. Segments6. Segments S1, S1, S2, S2, and and S3 S3 are are shown shown as as red red dots, dots, green green dots, dots, and and blue blue dots, dots, respectively. respectively. TheThe rangerange decreasesdecreases withwith increasingincreasing rainrain rate,rate, andand itit becomesbecomes moremore stablestable atat higherhigher rainrain ratesrates atat thethe EPEP sitesite (Figure(Figure6 a).6a). The The values values of of µμand andΛ Λdecrease, decrease, whilewhile DDmm andand NNtt increaseincrease withwith thethe increasingincreasing rainrain rate.rate. –11 TheThe didifferencesfferences between between the the three three segments segments are are significant. significant. When When R R<< 10 10 mm mm h h− ,, thethe rangesranges ofofµ μ,D, Dmm,, Λ, and Nt are greater during S1 and S3. This indicates that the microphysical process is complicated during S1 and S3. When R > 25 mm h–1, during S2 and S3, the values of μ and Λ remain nearly Atmosphere 2020, 11, 975 10 of 18 Atmosphere 2020, 11, x FOR PEER REVIEW 10 of 18 Λ, and Nt are greater during S1 and S3. This indicates that the microphysical process is complicated 1 during S1 and S3. When R > 25 mm h− , during S2 and S3, the values of µ and Λ remain nearly constant, and the values of Dm converge, while the values of Nt increase with the increasing rain rate. constant, and the values of D converge, while the values of N increase with the increasing rain In addition, when R > 25 mm h–1m, there were no raindrops measuredt by the 2DVD during S1. For rate. In addition, when R > 25 mm h 1, there were no raindrops measured by the 2DVD during S1. high rain rates, the raindrop size distributions− evolve into an equilibrium distribution under the For high rain rates, the raindrop size distributions evolve into an equilibrium distribution under the action of coalescence and breakup [33]. Under these equilibrium conditions, the value of Dm remains action of coalescence and breakup [33]. Under these equilibrium conditions, the value of D remains nearly constant, and the increase in the raindrop concentration is mainly due to the increasem in the nearly constant, and the increase in the raindrop concentration is mainly due to the increase in the rain rate [18]. When we focused on the probability density function (PDF), we found that the rain rate [18]. When we focused on the probability density function (PDF), we found that the majority majority of the raindrop sizes (Dm) were 1–2 mm in three segments. The distributions of the four of the raindrop sizes (D ) were 1–2 mm in three segments. The distributions of the four parameters parameters have the samem characteristics for the FG and XF sites (Figure 6b,c). The difference is that have the same characteristics for the FG and XF sites (Figure–1 6b,c). The di fference is that there were there were no raindrops at the XF site when R > 601 mm h . This is probably because of the different no raindrops at the XF site when R > 60 mm h− . This is probably because of the different location. location. The characteristics of Dm and Nt in our study show that the heavy precipitation in the The characteristics of D and N in our study show that the heavy precipitation in the typhoon was typhoon was mainly composedm of hight concentrations of small and midsize drops (<2 mm), which is mainly composed of high concentrations of small and midsize drops (<2 mm), which is consistent consistent with the results of Chang et al. [17], Wen et al. [20], and Janapati et al. [25]. with the results of Chang et al. [17], Wen et al. [20], and Janapati et al. [25]. 1 3 1 FigureFigure 6. 6.ScatterplotsScatterplots of ofμ, µD,Dm m(mm),(mm), Λ Λ(mm(mm–1),− and), and lgN lgNt (mt (m–3) −versus) versus R (mm R (mm h–1 h) −for) forthe the three three segmentssegments at the at the (a) (EP,a) EP, (b) ( bFG,) FG, and and (c) ( cXF) XF sites. sites. The The probability probability density density functions functions (PDF) (PDF) of the of the four four raindropraindrop size size distribution distribution (DSD) (DSD) parameters parameters at at th thee EP, EP, FG, and XFXF sitessites areare given given in in each each panel panel as as well. well.Segments Segments S1, S1, S2, S2, and and S3 S3 are are shown shown as redas red dots, dots, green green dots, dots, and and blue blue dots, dots, respectively. respectively. To make it clearer, Figure7 shows the relative contribution of each size class to the total raindrop To make it clearer, Figure 7 shows the relative contribution of each size class to the total concentration (Nt) and R. The relative contributions of Nt and R at the EP site show that the small raindrop concentration (Nt) and R. The relative contributions of Nt and R at the EP site show that the drops (<1 mm) dominate Nt (>90%) and the midsize drops (1–2 mm) dominate R (>45%) in all three small drops (<1 mm) dominate Nt (>90%) and the midsize drops (1–2 mm) dominate R (>45%) in all segments. When we focused on the small drops (<1 mm), we found that the relative contributions three segments. When we focused on the small drops (<1 mm), we found that the relative of Nt and R initially increased and then decreased from S1 to S3. More significantly, the drops that contributions of Nt and R initially increased and then decreased from S1 to S3. More significantly, were 1–3 mm in diameter contributed to the rain rate in S2. The large drops (>4 mm) contributed less the drops that were 1–3 mm in diameter contributed to the rain rate in S2. The large drops (>4 mm) than 3% during S2 and S3, and their contribution was negligible during S1. Except for the larger size contributed less than 3% during S2 and S3, and their contribution was negligible during S1. Except for the larger size drops (4 mm), the relative contributions of Nt and R at the three sites exhibit similar behaviors. This is consistent with the conclusion drawn from Figure 6 that the small and midsize drops dominated the typhoon’s precipitation. Atmosphere 2020, 11, x FOR PEER REVIEW 11 of 18 Atmosphere 2020, 11, 975 11 of 18 Overall, the characteristics of the DSD parameters were different in the three segments because of the different dynamic and thermodynamic mechanisms of rain formation in the different rain dropsregions (4 [34–37]. mm), the As relative a result contributions of the different of N locationt and Rs, at the the characteristics three sites exhibit of the similar DSD behaviors.parameters This in the is consistentsame segment with were the conclusion not completely drawn the from same Figure for 6the that EP, the FG, small and and XF sites. midsize In dropsthe following dominated section, the typhoon’sthe characteristics precipitation. of the DSDs during the three segments are investigated. t Figure 7.7. Relative contribution of each size classclass to thethe totaltotal raindropraindrop concentrationconcentration NNt (red)(red) andand rainrain raterate RR (blue)(blue) forfor thethe entireentire datasetdataset atat thethe ((aa)) EP,EP, ( (bb)) FG, FG, and and ( c(c)) XF XF sites. sites. 5. GammaOverall, and the DSD characteristics Parameters of of the the DSD Three parameters Segments were different in the three segments because of the different dynamic and thermodynamic mechanisms of rain formation in the different rain regions5.1. Distributions [34–37]. Asof D am result and N ofw the different locations, the characteristics of the DSD parameters in the same segment were not completely the same for the EP, FG, and XF sites. In the following section, Previous studies have shown that because of the different microphysical processes during rain the characteristics of the DSDs during the three segments are investigated. formation, the DSDs of different rain types vary [38–41]. The variations in the Nw–Dm values reflect 5.the Gamma different and microphysical DSD Parameters formation of the mechanisms Three Segments [18]. The percentage occurrence of the various rain types, which were classified using Bao’s method [21], is given in Figure 8. Figure 8 shows that 5.1.during Distributions S1 (S3), the of D stratiformm and Nw rain contributed more than 70% (50%), while the convective rain contributed more than 60% during S2. Lin et al. [26] also reported that the typhoon precipitation in Previous studies have shown that because of the different microphysical processes during rain the eye wall region was mainly produced by convective rain. In addition, the distributions of the formation, the DSDs of different rain types vary [38–41]. The variations in the Nw–Dm values reflect mass-weighted mean diameter Dm and the generalized number concentration Nw in the three the different microphysical formation mechanisms [18]. The percentage occurrence of the various rain segments are shown in Figure 9. The maritime-like (continental-like) cluster has Dm values of 1.5– types, which were classified using Bao’s method [21], is given in Figure8. Figure8 shows that during 1.75 mm (2–2.75 mm) and lgNw values of 4–4.5 (3–3.5 mm–1 m–3) (the two gray rectangles in Figure S1 (S3), the stratiform rain contributed more than 70% (50%), while the convective rain contributed 9) for the convective rain, as defined by Bringi et al [18]. more than 60% during S2. Lin et al. [26] also reported that the typhoon precipitation in the eye wall The mean Dm steadily increases, and the mean of the logarithmic Nw (lgNw) increases initially region was mainly produced by convective rain. In addition, the distributions of the mass-weighted and then decreases from S1 to S3 (Figure 9a). The variance of Dm increases initially and then mean diameter Dm and the generalized number concentration Nw in the three segments are shown in Atmosphere 2020, 11, 975 12 of 18 Figure9. The maritime-like (continental-like) cluster has D m values of 1.5–1.75 mm (2–2.75 mm) and 1 3 lgNw values of 4–4.5 (3–3.5 mm− m− ) (the two gray rectangles in Figure9) for the convective rain, as defined by Bringi et al [18]. The mean Dm steadily increases, and the mean of the logarithmic Nw (lgNw) increases initially and then decreases from S1 to S3 (Figure9a). The variance of D m increases initially and then decreases, and lgNw steadily increases. When we focused on S1 (Figure9b), we found that the lgN w–Dm pairs mainly occur to the left of the stratiform line defined by Bringi et al. [18] due to the strong stratiform rain over the three sites (Figure8). During S2, it was mainly composed of convective rain. The lgN w–Dm pairs show an inhomogeneous distribution with few pairs falling in the maritime-like cluster, while 1 3 some of the pairs have Dm values of 0–1.25 mm and lgNw values of 4.5–5.0 mm− m− . During S3, we found that the lgNw–Dm pairs were evenly distributed around the stratiform line due to the contribution of stratiform raindrops. Interestingly, few lgNw–Dm pairs fall in the maritime-like cluster, and fewer lgNw–Dm pairs fall in the continental-like cluster. This also indicates that the number of lgNw–Dm pairs that fall in the maritime-like cluster increases from S2 to S3 because of the abundant moisture brought from the South China Sea by the typhoon. The mean Dm and lgNw values of tropical cyclones in different parts of China are presented in Table3. The grade of the tropical cyclone reported by the Japan Meteorological Agency (JMA) (http://www.jma.go.jp/jma/index.html) is also presented in Table3. Typhoon Mangkhut (typhoon) has a smaller raindrop diameter than and the same generalized number concentration as Typhoon Matmo (extra-tropical cyclone), which is the strongest tropical cyclone in Table3. When we focused on the same grade of tropical cyclone (typhoon), we found that our Dm is slightly larger than that of Typhoon Morakot in Fujian, while our Dm (lgNw) is larger (smaller) than that of Typhoon Hato, which made landfall in Guangdong. However, if we compare our Dm and lgNw values with those of Typhoon Nida and Typhoon Pakhar (severe tropical storm), which made landfall in Guangdong, our lgNw is smaller and our Dm is in between those of the other two. The sufficient water vapor brought by the typhoon from the ocean may influence the values of the DSD parameters (such as lgNw and Dm). Moreover, the strong winds shown in Figure4 may have suppressed the collision–coalescence and breakup of the raindrops. Table3. Mean Dm and lgNw values and µ–Λ relationship of various tropical cyclones in different regions. Region Grade Name Author Dm lgNw µ–Λ Relationship Eastern Extra-tropical µ = 0.021Λ2 + Matmo Wang et al. 2016 1.41 4.67 − China Cyclone 1.075Λ 2.979 − Typhoon + Taiwan, Two Tropical Λ = 0.0136µ2 + Tropical Chang et al. 2009 2 3.8 China Cyclones 0.6984µ + 1.5131 Storm Fujian, Λ = 0.0253µ2 + 0.633µ Typhoon Morakot Chen et al. 2012 1.30 – China + 1.524 Severe Guangdong, Tropical Nida Wen et al. 2018 1.4 4.5 – China Storm Guangdong, Typhoon Hato Wen et al. 2018 1.2 4.8 – China Severe Guangdong, Tropical Pakhar Wen et al. 2018 1.3 4.7 – China Storm Severe Eastern + Seven Tropical µ = 0.019Λ2 + 1.09Λ southern Tropical Wen et al. 2018 – – − Storm + 3.119 China Cyclones Typhoon − Guangdong, Λ = 0.0241µ2 + 0.867µ Rainstorm – Liu et al. 2019 1.66 3.91 China + 2.453 Guangdong, µ = 0.0306Λ2 + Typhoon Mangkhut This study 1.33 4.12 − China 1.3513Λ 3.145 − Atmosphere 2020, 11, 975 13 of 18 Atmosphere 2020, 11, x FOR PEER REVIEW 13 of 18 Atmosphere 2020, 11, x FOR PEER REVIEW 13 of 18 Figure 8. The percentage occurrence of the different rain types in the three segments. FigureFigure 8. 8. TheThe percentage percentage occurrence occurrence of of the the differe differentnt rain rain types types in in the the three three segments. FigureFigure 9.9.( a()a The) The mean mean and and variance variance of the of mass-weighted the mass-weighted mean diameter mean Ddiameterm (mm) andDm the(mm) generalized and the 1 3 Figure 9. (a) The mean and variance of the–1 –3mass-weighted mean diameter Dm (mm)b and the numbergeneralized concentration number concentration Nw (mm− mN−w (mm) for the m entire) for the dataset. entire Scatterplot dataset. Scatterplot of Dm and of NDwm and( ) during Nw (b) –1 –3 generalizedS1,during (c) during S1, (numberc) S2, during and concentration ( dS2,) during and (d S3.) Nduring Thew (mm black S3. m The dotted) for black the line dottedentire is the dataset. regressionline is the Scatterplot relationshipregression of Drelationship ofm and Bringi Nw et (b al.of) during S1, (c) during S2, and (d) during S3. The black dotted line is the regression relationship of (2003)Bringi foret stratiformal. (2003) rain. for Thestratiform two gray rain. rectangles The aretwo the gray maritime-like rectangles and are continental-like the maritime-like clusters and of BringiBringicontinental-like etet al.al. (2003). (2003) clusters for ofstratiform Bringi et al.rain. (2003). The two gray rectangles are the maritime-like and continental-like clusters of Bringi et al. (2003). Atmosphere 2020, 11, x FOR PEER REVIEW 14 of 18 5.2. μ–Λ Relationship The three-parameterAtmosphere 2020, 11, 975 (N0, μ, and Λ) gamma distribution is important to understanding14 of 18the DSD characteristics [42,43]. The parameters μ and Λ are the shape and slope of the DSD, respectively. Furthermore,5.2. µ –theΛ Relationship μ–Λ relationship is useful for retrieving the DSD parameters and rain parameters from the remote measurements [41,44]. These μ–Λ relationships are dependent on the geographic The three-parameter (N0, µ, and Λ) gamma distribution is important to understanding the DSD location, characteristicsclimate, and [rain42,43 ].type The [43,45]. parameters Thus,µ and it isΛ arenecessary the shape to and investigate slope of the the DSD, μ–Λ respectively. relationships in each region.Furthermore, To minimize the µ–Λ relationshipthe error, isthe useful sample for retrieving data with the DSD rain parameters rates of and < rain5 mm parameters h–1 and total from the remote measurements [41,44]. These µ–Λ relationships are dependent on the geographic concentrations of Nt <1000 were removed [43]. The μ–Λ relationship (Figure 10) shows that there is a location, climate, and rain type [43,45]. Thus, it is necessary to investigate the µ–Λ relationships good relationship between μ and Λ. The μ–Λ relationship in this study was 1fitted using the in each region. To minimize the error, the sample data with rain rates of < 5 mm h− and total polynomial least squares method. Compared with the other observation results listed in Table 3, our concentrations of Nt <1000 were removed [43]. The µ–Λ relationship (Figure 10) shows that there μ–Λ relationshipis a good is relationship closest to between that developedµ and Λ. The by µLiu–Λ relationshipet al. [13] for in this heavy study rainfall was fitted in usingGuangdong. the In contrast, polynomialthere are considerable least squares method. differences Compared among with the the μ– otherΛ relationships observation results developed listed in by Table scholars3, for different ourpartsµ–Λ ofrelationship China [16,17,19, is closest to20,43]. that developed This indicates by Liu et al.that [13 ]the for heavyμ–Λ rainfallrelationship in Guangdong. depends on In contrast, there are considerable differences among the µ–Λ relationships developed by scholars geographic location, climate, and rain type, which is consistent with the conclusions of previous for different parts of China [16,17,19,20,43]. This indicates that the µ–Λ relationship depends on studies. Ingeographic addition, location, the μ– climate,Λ relationship and rain type, differs which from is consistent that deve withloped the conclusions by Zhang of previouset al. [43], studies. which has been widelyIn addition, used to the calculateµ–Λ relationship the DSD diff parametersers from that developedretrieved byfrom Zhang polarimetric et al. [43], which radar has observations been [42,46,47].widely We also used found to calculate that thethe DSD majority parameters of the retrieved μ–Λ pairs from polarimetricare characterized radar observations by μ< 0 and [42,46 Λ,47< ].2.5 mm– 1 1 during WeS2,also while found they that thewere majority characterized of the µ–Λ pairsby μ are> 0 characterized and Λ ≈2.5–6 by µ< mm0 and–1 Λduring< 2.5 mm S1− duringand S3. This S2, while they were characterized by µ> 0 and Λ 2.5–6 mm 1 during S1 and S3. This indicates that indicates that the microphysical processes during≈ S1 and S3− were complicated, which is similar to the microphysical processes during S1 and S3 were complicated, which is similar to the result obtained the resultin obtained Section 4.2 in. Section 4.2. Figure 10.Figure Scatterplots 10. Scatterplots of the ofμ the–Λ µrelationships–Λ relationships during during ( a)) S1,S1, ( b()b S2,) S2, and and (c) S3.(c) S1,S3. S2, S1, and S2, S3 and are S3 are shown as shownred dots, as red green dots, dots, green dots,and andblue blue dots, dots, respecti respectively.vely. TheThe black black lines lines denote denote the fitting the fitting curves curves of of the filteredthe samples. filtered samples. In addition, In addition, the μ the–Λµ –relationshipsΛ relationships from Chang Chang (2009), (2009), Chen Chen (2012), (2012), Liu (2018), Liu (2018), Wang (2016), Wen (2018), and Zhang (2003) are provided. S1: the outer rainband before landfall, S2: the Wang (2016), Wen (2018), and Zhang (2003) are provided. S1: the outer rainband before landfall, S2: inner core, S3: the outer rainband after landfall. the inner core, S3: the outer rainband after landfall. 5.3. Raindrop Spectra 5.3. Raindrop SpectraThe raindrop spectra of the three segments (Figure 11) show a high concentration of small drops (<0.5 mm). During S2, the number concentration within each size bin is larger than those of the other The raindrop spectra of the three segments (Figure 11) show a high concentration of small drops (<0.5 mm). During S2, the number concentration within each size bin is larger than those of the other segments, especially the small drops (<0.5 mm) and large drops (>4 mm), resulting in a heavy rain rate. The spectrum is wider and has a lager maximum drop diameter (5.3 mm) during S2 and S3. During the passage of the typhoon, the size spectrum changes from narrow to wide, and the evolution of the number concentration initially increases and then decreases. Atmosphere 2020, 11, 975 15 of 18 segments, especially the small drops (<0.5 mm) and large drops (>4 mm), resulting in a heavy rain rate. The spectrum is wider and has a lager maximum drop diameter (5.3 mm) during S2 and S3. During the passage of the typhoon, the size spectrum changes from narrow to wide, and the evolution ofAtmosphere the number 2020, 11 concentration, x FOR PEER REVIEW initially increases and then decreases. 15 of 18 Figure 11. Raindrop spectra of the three segments. 6. Summary In thisthis study,study, thethe microphysicalmicrophysical characteristicscharacteristics of the DSDs during the passage of Typhoon Mangkhut were investigated usingusing the 2DVD data collected from the LongmenLongmen FieldField ExperimentExperiment Base forfor CloudCloud Physics,Physics, ChinaChina MeteorologicalMeteorological Administration.Administration. Based Based on the observed track and radar reflectivity,reflectivity, this this process process can can be be divided divided into into three three distinct distinct segments segments (S1–S3). (S1–S3). Moreover, Moreover, the time the evolutiontime evolution of the of raindrop the raindrop size distribution size distribution reflects reflects the diff erentthe different segments. segments. This study This mainly study focusedmainly onfocused the characteristics on the characteristics of the DSDs of the during DSDs the during three the segments three segments to determine to determine the microphysical the microphysical processes ofprocesses Typhoon of Mangkhut.Typhoon Mangkhut. The DSDs The at theDSDs three at the diff threeerent different sites were sites compared were compared to reveal to any reveal spatial any variations.spatial variations. In addition, In theaddition, microphysical the microphysical characteristics characteristics of Typhoon Mangkhutof Typhoon were Mangkhut compared were with thosecompared of other with tropical those of cyclones other tropical in different cyclones parts in of China.different The parts DSDs of ofChina. Typhoon The DSDs Mangkhut of Typhoon exhibit diMangkhutfferent characteristics exhibit different in the characteristics three segments. in the During three segments. segment S2,During the meansegment of theS2, mass-weightedthe mean of the meanmass-weighted diameter (Dmeanm) wasdiameter 1.33 mm, (Dm) while was 1.33 the variancemm, while of thethe Dvariancem was larger of the (0.44) Dm was than larger in the (0.44) other 1 3 segments,than in the and other the segments, mean of the and generalized the mean numberof the generalized concentration number (lgNw concentration) was 4.12 mm −(lgNm−w), was which 4.12 is themm largest–1 m–3, which value amongis the largest the three value segments. among the three segments. 1. During segment S1 (the outer rainband before landfall), the circulation moved northwestward. 1. During segment S1 (the outer rainband before landfall), the circulation moved northwestward. A strong stratiform precipitation episode mixed with convective precipitation lasting more than A strong stratiform precipitation episode mixed with convective precipitation lasting more than 2 hours occurred over all three sites. The maximum drop size was less than 3 mm, and the 2 h occurred over all three sites. The maximum drop size was less than 3 mm, and the raindrop –1 –3 raindrop concentration was less than1 4 mm3 m (on a logarithmic scale) at all three sites. The concentration was less than 4 mm− m− (on a logarithmic scale) at all three sites. The small and small and midsize drops mainly contributed to the rain rate. The lgNw–Dm pairs mainly midsize drops mainly contributed to the rain rate. The lgNw–Dm pairs mainly occurred to the left occurred to the left of the stratiform line. of the stratiform line. 2. During segment S2 (the inner core), a strong convective precipitation process occurred over site 2. During segment S2 (the inner core), a strong convective precipitation process occurred over site EP. This segment had the largest instantaneous wind speed (23.3 m s−1), rain rate (11.66 mm h−1), EP. This segment had the largest instantaneous wind speed (23.3 m s 1), rain rate (11.66 mm radar reflectivity (34.53 dBZ), liquid water content (0.65 g m−3), and number− concentration (4.12 h 1), radar reflectivity (34.53 dBZ), liquid water content (0.65 g m 3), and number concentration mm− –1 m−3 in logarithmic scale) on average. The small drops (<1 mm)− mainly contributed to the (4.12 mm 1 m 3 in logarithmic scale) on average. The small drops (<1 mm) mainly contributed number concentration,− − while the small and midsize drops (1–3 mm) mainly contributed to the to the number concentration, while the small and midsize drops (1–3 mm) mainly contributed to rain rate. The Nw–Dm scatter pairs indicate maritime-like convection. the rain rate. The N –D scatter pairs indicate maritime-like convection. 3. During segment S3 (thew outerm rainband after landfall), a widespread stratiform precipitation 3. During segment S3 (the outer rainband after landfall), a widespread stratiform precipitation episode mixed with convective precipitation lasted above 10 hours. The DSDs were episode mixed with convective precipitation lasted above 10 h. The DSDs were characterized by a characterized by a high concentration of small drops (<1 mm) and a few larger drops (>5 mm). high concentration of small drops (<1 mm) and a few larger drops (>5 mm). The maximum drop The maximum drop size was greater than 4 mm at all three sites. The Nw–Dm points were mostly distributed around the stratiform rain area, with a few points falling in both the maritime-like and continental-like clusters. This study indicates that the three segments had different DSD characteristics. The outer rainband mainly produced stratiform rains, while the inner core mainly produced convective rains. The small and midsize drops (<3 mm) dominated the typhoon precipitation. The shape (μ) and slope (Λ) exhibit a good polynomial least squares relationship. Atmosphere 2020, 11, 975 16 of 18 size was greater than 4 mm at all three sites. The Nw–Dm points were mostly distributed around the stratiform rain area, with a few points falling in both the maritime-like and continental-like clusters. This study indicates that the three segments had different DSD characteristics. The outer rainband mainly produced stratiform rains, while the inner core mainly produced convective rains. The small and midsize drops (<3 mm) dominated the typhoon precipitation. The shape (µ) and slope (Λ) exhibit a good polynomial least squares relationship. In addition, the mean values of Dm and lgNw were quite different among the tropical cyclones in different parts of China. Compared with the stronger tropical cyclone (Typhoon Matmo) in Eastern 1 3 China, our Dm and lgNw were smaller (1.33 mm and 4.12 mm− m− , respectively). The values of the DSD parameters (such as Dm and lgNw) may be influenced by the sufficient water vapor brought by the tropical cyclone from the ocean and strong winds of the tropical cyclone. The DSDs of Typhoon Mangkhut, which made landfall in Southern China, were quite different from those of tropical cyclones in other parts of China and even within the same region. Therefore, further tropical cyclones making landfall in Southern China are worth investigating in the future. Author Contributions: Conceptualization, S.H. and X.L.; Investigation, L.F. and H.X.; Supervision, X.L., H.X. and X.P.; Formal analysis, X.P., F.X., G.O. and C.Z.; Writing—original draft preparation, L.F.; Writing—review and editing, L.F. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by Science and Technology Planning Project of Guangdong Province, China (2017B020244002), the National Natural Science Foundation of China (41975138, 41705120, 41705011, 41905047), and the Natural Science Foundation of Guangdong Province, China (2019A1515010814, 2018A030313969). Acknowledgments: We thank YUE Qian for translating the manuscript. We also acknowledge LI Jin-hong, WANG Jian-zhuang and LIU Huang for their assistance in the field experiment. This research was jointly supported by Science and Technology Planning Project of Guangdong Province, China (2017B020244002), the National Natural Science Foundation of China (41975138, 41705120, 41705011, 41905047), and the Natural Science Foundation of Guangdong Province, China (2019A1515010814, 2018A030313969). Conflicts of Interest: The authors declare no conflict of interest. References 1. Kirankumar, N.V.P.; Rao, T.N.; Radhakrishna, B.; Rao, D.N. 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