Characteristics of Wind Structure and Nowcasting of Gust Associated with Subtropical Squall Lines Over Hong Kong and Shenzhen, China

atmosphere

Case Report Characteristics of Wind Structure and Nowcasting of Gust Associated with Subtropical Squall Lines over Hong Kong and Shenzhen, China

Junyi He 1, P.W. Chan 2,*, Qiusheng Li 1, Lei Li 3, Chao Lu 3, Li Zhang 3 and Honglong Yang 3 1 Department of Architecture and Civil Engineering, City University of Hong Kong, Hong Kong, China; [email protected] (J.H.); [email protected] (Q.L.) 2 Hong Kong Observatory, Hong Kong, China 3 Shenzhen National Climate Observatory, Meteorological Bureau of Shenzhen Municipality, Shenzhen 518040, China; [email protected] (L.L.); [email protected] (C.L.); [email protected] (L.Z.); [email protected] (H.Y.) * Correspondence: [email protected]

Received: 13 December 2019; Accepted: 5 March 2020; Published: 9 March 2020

Abstract: A number of squall line passages over the Pearl River Delta (PRD) are documented for the first time based on the wind data collected by a 356 m-high meteorological tower with high temporal resolution (10 Hz). The mean wind and turbulence characteristics are studied based on a sample of six cases. The mean wind profile is consistent with the international standard for wind engineering, but the turbulence intensity profile has quite significant deviations. Moreover, the energy spectrum of the fluctuating wind is found to be consistent with the 5/3 law, as expected in the inertial subrange. − For the purpose of wind gust nowcasting, the performance of a nowcasting algorithm based on upper air wind and thermodynamic profiles is examined using the limited dataset. The results highlight that the mean wind gust estimates are sufficient to nowcast the surface wind gust as measured by the anemometers, but for an extreme squall line case, the maximum wind gust estimates would be useful. The information in this paper is believed to be useful for wind engineering applications and weather nowcasting for wind gusts associated with subtropical squall lines, and, to the best of the authors’ knowledge, this is the first study of its kind for the PRD region.

Keywords: meteorological tower; turbulence; gust nowcasting

1. Introduction Subtropical squall lines commonly aﬀect southern China in the summer time. They are also known as “Shi Hu Feng” by local people (https://www.hko.gov.hk/education/edu01met/wxphe/ele_squalle.htm) and can bring damaging wind to natural vegetation and man-made objects/structures, such as the collapsing of trees or the falling of empty containers at container terminals. Despite the commonality of this phenomenon, systematic studies of subtropical squall lines are rather limited, especially for wind engineering applications. An example of this limited research is a numerical simulation that was performed to further understand the squall line over southern China [1]. Additionally, observational wind studies have not been extended to wind applications either. Surface observations are common, but are mostly focused on the high wind gust following the passage of the squall line. Furthermore, the structure of the squall line is not well understood for wind engineering applications. In particular, the vertical structure above the ground is predominantly observed by remote sensing instruments, such as the Doppler weather radar wind proﬁler and acoustic radar. Though available at high temporal resolution, one major limitation of these remote sensing instruments is that they only provide the mean wind speed over a period of time, at least in the order of 1 min. ≥

Atmosphere 2020, 11, 270; doi:10.3390/atmos11030270 www.mdpi.com/journal/atmosphere Atmosphere 2020, 11, 270 2 of 16

Thus, the high frequency or variability of the wind is not captured, which limits our understanding of the impact of squall lines on man-made structures/buildings, such as the vertical variability of gust factor and turbulence intensity, which are important for wind engineering applications. The availability of the 356 m-high wind tower in Shenzhen, China, provides the much-needed and valuable high temporal resolution wind data at heights above the ground. Sonic anemometers are installed at four levels and they provide three-dimensional wind data at 10 Hz. By using the data captured by this tower, the parameters required for wind engineering applications can be calculated for the first time for weather phenomena over the Pearl River Delta (PRD) region. This paper documents the wind observations in subtropical squall lines or six cases over Shenzhen and Hong Kong, China in the summer of 2019. Though the number of cases is not large, this is the first time that observations of subtropical squall lines in this region with high temporal resolution have been supplied by a meteorological tower. In other studies, e.g., in Singapore, gusty winds associated with thunderstorm outflows have been examined in larger numbers, e.g., 50 cases in the research of Choi [2]. In the present study, we focus more specially on subtropical squall lines, which do not occur as frequently as ordinary thunderstorm outflows, and thus the number of samples is much more limited. As more cases will be accumulated over the years, the statistical analysis of a larger sample will be reported in a future paper for the PRD region. Apart from presentation of the vertical wind profile, the statistical property of the upper air winds (winds above the ground) in the subtropical squall is presented in this paper following the method of Solari et al. [3] and Burlando et al. [4]. Winds of up to about 360 m above ground are considered. Previously, such analysis was only possible for ground-based measurements from sonic anemometers at high frequencies. With the Shenzhen wind tower, it is possible to analyze the wind at upper levels (up to about 360 m above ground level). Thus, the applicability of an inertial subrange of wind turbulence can now be examined at heights above the ground. Another feature of this paper is a review of the application of the gust nowcasting method, as discussed in Chan and Hon [5]. A very limited sample is presented in that paper using the gust nowcasting algorithm based on a wind profiler and microwave radiometer, providing the upper-air wind and the thermodynamic profile of the atmosphere, respectively. The upper-air wind comes from the wind profiler measurements of up to 9 km above ground. The thermodynamic profiles come from the microwave radiometer, and they include the temperature and humidity profiles measured by the radiometer up to 10 km above ground. For the sake of simplicity, only the final wind gust estimates are shown, without showing the individual upper-air wind profile and upper-air thermodynamic profile. The performance of this nowcasting algorithm is reviewed using the limited samples of squall lines available in this paper.

2. Equipment The Shenzhen Meteorological Gradient Tower (SZMGT) is located in Shenzhen, Guangdong Province, which is one of the most rapidly developing cities in China [6]. A photograph of the tower and the locations of the anemometer installation are shown in Figure1. Mean wind is measured at 13 height levels, including 10, 20, 40, 50, 80, 100, 150, 160, 200, 250, 300, 320, and 350 m. The measurement instrument is the Wind Set WA-25 (Vaisala, Vantaa, Finland), consisting of a Vaisala Anemometer WAA252 and a Vaisala Wind Vane WAV252 (Vaisala, Vantaa, Finland). The measurement ranges of wind speed and direction are 0.4~75 m/s and 0~360, respectively. The accuracies of wind speed and direction measurement are 0.17 m/s and 3, respectively. This set of equipment records 2 min mean ± ± wind speed and direction every 10 s. Turbulent wind is measured at 4 height levels, including 10, 40, 160, and 320 m. The measurement instrument is a Vaisala WINDCUP Ultrasonic Wind Sensor WMT703 (Vaisala, Vantaa, Finland). The measurement ranges of wind speed and direction are 0~75 m/s and 0~360, respectively. The accuracies of wind speed and direction measurement are 0.1 m/s and 2, ± ± respectively. This set of equipment provides high-resolution wind measurements sampled at 10 Hz, that is, wind speed and direction every 0.1 s. Atmosphere 2020, 11, 270 3 of 16

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(a) (b)

(c)

Figure 1. (a) Bird view of Shenzhen Meteorological Gradient Tower (SZMGT), (b) locations of Figure 1. (a) Bird view of Shenzhen Meteorological Gradient Tower (SZMGT), (b) locations of anemometer installation, and (c) the geographical location of SZMGT (red triangle) in Google Map. anemometer installation, and (c) the geographical location of SZMGT (red triangle) in Google Map. Before application to wind turbulence analysis, data pre-processing is required to detect any Before application to wind turbulence analysis, data pre-processing is required to detect any anomalies and remove invalid data points. Firstly, wind speed time series were divided into non- anomaliesoverlapping and remove samples, invalid each with data a length points. of 30 s. Firstly, Then, abnormal wind speed data points time serieswere determined were divided by the into non-overlappingso-called multiple samples, truncation each with variance a length method, of 30 following s. Then, the abnormal same procedures data points as Lin were et al. determined [7]: by the so-called multiple truncation variance method, following the same procedures as Lin et al. [7]:

dU(t) = U(t + 2) U(t) (1) − Atmosphere 2020, 11, 270 4 of 16

1 Pn 2 dU = n 2 i=−1 dU(t) (2) − 2 1 Pn 2 2 dU = n 2 i=−1 dU(t) (3) − 2 τ = dU2 dU (4) − ∆ = c τ0.5 (5) · where U(t) is the wind speed at t-th time point, and c = 4 in Equation (5). If the absolute difference between the value of a point and the mean value of the sample is greater than ∆, the point will be identified as an unreasonable point, which will be removed. For instance, for a squall line with gust wind speed of about 35 m/s (case 6 in the present study), a typical value of ∆ is around 20 m/s, i.e., data larger than 55 m/s or lower than 15 m/s will be considered unreasonable. Such data only amount to a small portion of the whole (less than 5% of the whole). In the case that the continuous missing or abnormal data points are fewer than or equal to 3, a linear interpolation will be applied to make up the data; otherwise, they will be discarded. In the latter part of this paper, the wind gust nowcasting algorithm based on measurements by ground-based remote-sensing meteorological instruments, namely, a radar wind profiler and a microwave radiometer, is considered. The wind profiler is a boundary layer-type instrument that operates at a central frequency of 1299 MHz. It operates by Doppler swinging of three beams—one vertical and two oblique beams—at an angle of 15 degrees around the vertical. The three components of the wind are obtained from about 300 m up to about 9000 m above ground, with a spatial resolution of around 200 m. Mean wind profiles are available every 10 min. For the microwave radiometer, it operates at 14 channels to measure the brightness temperatures of oxygen and water vapor at the air. Temperature and dew point profiles are obtained every 10 min, up to a height of around 10 km above ground.

3. Cases under Consideration The six cases under consideration occur on four days in the summer of PRD in 2019. The time periods are given below (all times in local times, HKT = UTC + 8 h): (1) 21:00~21:40, 11 April 2019 (2) 21:40~22:30, 11 April 2019 (3) 12:00~12:40, 19 April 2019 (4) 12:40~13:30, 19 April 2019 (5) 13:05~13:45, 20 April 2019 (6) 17:20~18:00, 10 June 2019 There are two cases for 11 April 2019 and 19 April 2019. For each day, the two cases refer to two recorded events in a single squall line. The above does not mean to be a comprehensive summary of the occurrence of subtropical squall lines in the PRD region in summer of 2019. They just represent the samples in which the squall line passed through the Shenzhen meteorological tower so that a high wind gust was observed at that location, and therefore the structure of the squall line could be analyzed. The high wind gust occurred at about the middle of each time period, as given above, and data around 20 min before and after the high wind gust were included in the statistical study of the wind associated with the squall lines. As a summary of the meteorological situation during the squall line occurrence, the surface weather chart at 00 UTC on the above-mentioned days and a typical weather radar imagery of each event are given in Figure2. Synoptically, the PRD region was a ﬀected by either a southwest monsoon or a surface trough of low pressure. Squall lines could be found near the Shenzhen tower, as given in the radar imagery. Surface weather observations are not shown in order to save space, but low-level wind convergence was noticeable around the squall line. Sometimes, low-level wind jet was observed at the rear of the squall line itself. Atmosphere 2019, 10, x FOR PEER REVIEW 5 of 16 Atmosphere 2020, 11, 270 5 of 16 wind convergence was noticeable around the squall line. Sometimes, low-level wind jet was observed at the rear of the squall line itself. (a) (b)

(g) (h)

Figure 2. The upper four panels (a–d) are the surface isobaric charts at 00 UTC of the squall line days, and the lower four panels (e–h) are the weather radar imagery when the squall line passed through Shenzhen, China. Atmosphere 2019, 10, x FOR PEER REVIEW 6 of 16

Figure 2. The upper four panels (a–d) are the surface isobaric charts at 00 UTC of the squall line days, Atmosphereand2020 the ,lower11, 270 four panels (e–h) are the weather radar imagery when the squall line passed through6 of 16 Shenzhen, China. 4. Mean Wind Structure 4. Mean Wind Structure The mean vertical wind profiles for the 6 cases are given in Figure3, which can be seen to The mean vertical wind profiles for the 6 cases are given in Figure 3, which can be seen to be be consistent with the power law, with an alpha of 0.21. The profiles also follow the standards consistent with the power law, with an alpha of 0.21. The profiles also follow the standards GB50009- GB50009-2012 [8] and AIJ-RLB-2004 [9], which are the Chinese Code and the Japanese Code for 2012 [8] and AIJ-RLB-2004 [9], which are the Chinese Code and the Japanese Code for the design of the design of building structures, respectively. These codes formulate wind loadings and dynamic building structures, respectively. These codes formulate wind loadings and dynamic responses of responses of structures based on the profiles of mean wind speed, gust factors, turbulence intensity, etc. structures based on the profiles of mean wind speed, gust factors, turbulence intensity, etc. It is It is noteworthy that the wind and turbulence profiles stipulated in these codes are generally based on noteworthy that the wind and turbulence profiles stipulated in these codes are generally based on observations during synoptic strong winds, while thunderstorm outflows (specifically for squall lines) observations during synoptic strong winds, while thunderstorm outflows (specifically for squall lines) have not yet been considered. For wind profiles, the empirical power law profile is used: have not yet been considered. For wind profiles, the empirical power law profile is used: α 𝑈𝑧U(z) 𝑧 z = z (6) U(zre= f ) re f (6) 𝑈𝑧 𝑧

Figure 3. Ensemble mean wind profile of all 6 events. N is the number of individual profile members. Figure 3. Ensemble mean wind profile of all 6 events. N is the number of individual profile members. Individual measurements (green dots), mean (black squares) and standard deviation (horizontal bars) Individual measurements (green dots), mean (black squares) and standard deviation (horizontal bars) are shown for each height bin. Power law fitting and empirical profiles are also shown. are shown for each height bin. Power law fitting and empirical profiles are also shown. For urban terrain with few tall buildings, the Japanese Code (AIJ-RLB-2004) stipulate α = 0.2, whileFor for theurban Chinese terrain Code with (GB50009-2012), few tall buildings,α = 0.22. the NoJapanese low-level Code jet was(AIJ-RLB-2004) observed in thestipulate mean profile,α = 0.2, whichwhile isfor not the consistent Chinese withCode the (GB50009-2012), study of Choi [2α]. = This 0.22. may No below-level due to thejet limitedwas observed number in of the cases. mean profile,The which individual is not cases consistent are shown with inthe Figure study4 .of Low-level Choi [2]. This jets deviating may be due from to thethe powerlimited law number could of becases. observed in some of the cases, notably between 100 and 200 m above ground in case 3 (Figure4c). Low-levelThe individual jet has been cases reported are shown in previous in Figure studies 4. Lo ofw-level thunderstorm jets deviating outflow from [2, 10the,11 power]. At the law height could ofbe the observed jet, the in mean some wind of the can cases, be a notably few times between greater 100 than and the 200 mean m above winds ground above in and case below 3 (Figure the 4c). jet. ForLow-level instance, jet in has one been of the reported cases considered in previous in thisstudies paper of thunderstorm (Figure4c), the outflow jet has a mean[2,10,11]. wind At of the around height 15of mthe/s, whereasjet, the mean the mean wind wind can be above a few and times below greater the jet than is in the ordermean ofwinds 10 m /aboves. However, and below they dothe not jet. occurFor instance, in all of in the one cases. of the In cases particular, considered case in 5 isthis a verypaper typical (Figure subtropical 4c), the jet has squall a mean line wind (typical of around in the sense15 m/s, of thewhereas appearance the mean in thewind radar above imagery, and below based the on thejet is experience in the order of theof 10 weather m/s. However, forecasters they over do southernnot occur China) in all of with the ancases. extended In particular, band of case thunderstorm, 5 is a very typical as shown subtropical in the weather squall line radar (typical image, in but the the mean wind profile follows the power law very well (Figure4e), without any low-level jet, e.g., rear Atmosphere 2019, 10, x FOR PEER REVIEW 7 of 16

Atmospheresense of 2020the ,appearance11, 270 in the radar imagery, based on the experience of the weather forecasters7 ofover 16 southern China) with an extended band of thunderstorm, as shown in the weather radar image, but the mean wind profile follows the power law very well (Figure 4e), without any low-level jet, e.g., inﬂowrear inflow jet in ajet conceptual in a conceptual model model of the squallof the squall line [1 ].line The [12]. occurrence The occurrence of low-level of low-level jet for squall jet for lines squall in thelines PRD in the region PRD would region need would to be need further to be studied further with studied both awith much both larger a much data larger sample data and sample numerical and simulationnumerical insimulation order to understandin order to understand why it is not why so common. it is not so common.

Figure 4. Wind proﬁles of each individual event, total = 6. N refers to number of samples. Figure 4. Wind profiles of each individual event, total = 6. N refers to number of samples. 5. Turbulence Intensity and Gust 5. TurbulenceTurbulence Intensity intensity and represents Gust the ratio between the ﬂuctuating component and the mean componentTurbulence of wind intensity speed andrepresents is determined the ratio as follows:between the fluctuating component and the mean component of wind speed and is determined as follows: I = σ (7) U

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Atmosphere 2020, 11, 270 𝜎 8 of 16 𝐼= (7) 𝑈 wherewhereU(t)¯ Ū(t)is is the the mean mean wind wind speed speed and andσ is σ theis the standard standard deviation deviation of the of windthe wind speed. speed. Considering Considering the non-stationarythe non-stationary feature feature of thunderstorm of thunderstorm wind wind records, records, a non-overlapping a non-overlapping moving moving window window of 30 s of was 30 adopteds was adopted for calculating for calculating the turbulence the turbulence intensity. intensity. AnotherAnother quantityquantity ofof interestinterest isis thethe gustgust factor.factor. ItIt isis defineddefined asasthe theratio ratiobetween between 1-s1-sgust gustwind wind speedspeed and and the the maximum maximum value value of of 30 30 s s mean mean wind wind speed, speed, as as recommended recommended by by Solari Solari et et al. al. [ 3[3]:]: 𝑢 G = uˆ (8) 𝐺= umax (8) 𝑢 wherewhereû ûis is the the 1-s 1-s gust gust wind wind speed speed and andu¯ maxūmaxis is the the maximum maximum value value of of 30 30 s s mean mean wind wind speed. speed. This This definitiondefinition is is in in accordance accordance with with the the traditional traditional definition definition of gustof gust factors factors for for thunderstorm thunderstorm outflows outflows by Choiby Choi [12], [13], Holmes Holmes et al. et [ 13al.], [14], and and Lombardo Lombardo et al. et [ 10al.]. [10]. TheThe empirical empirical profile profile for for turbulence turbulence intensity intensity is is given given by: by: 𝑧 d 𝐼=𝑐I = c z (9)(9) 10 10 InIn thethe JapaneseJapanese CodeCode (AIJ-RLB-2004),(AIJ-RLB-2004), cc= = 0.250.25 andand dd= = 0.25;0.25; whereas,whereas, inin thethe ChineseChinese CodeCode (GB50009-2012),(GB50009-2012),c c= =0.23 0.23 and andd d= =0.22. 0.22. The The vertical vertical distribution distribution of of turbulence turbulence intensity intensity for for all all six six cases cases is givenis given in Figure in Figure5. It can5. It be can seen be that seen the that distribution the distribution does not quitedoes follownot quite the follow international the international standards ofstandards GB50009-2012 of GB50009-2012 and AIJ-RLB-2004. and AIJ-RLB-2004. The turbulence The tu intensityrbulence profileintensity of profile subtropical of subtropical squall lines squall in thelines PRD in regionthe PRD appears region to appears be quite to unique be quite and unique may have and implications may have regardingimplications the regarding specification the ofspecification wind standard of wind for wind standard engineering for wind applications, engineering but applications, this needs but to be this established needs to usingbe established a much largerusing sample.a much Thelarger occurrence sample. ofThe a new occurrence shape of of the a turbulentnew shape intensity of the turbulent profile not intensity consistent profile with thenot existingconsistent international with the existing standard international would have standard great implications would have for great the implications applicability for of suchthe applicability a standard forof such the southern a standard China for the area. southern This is China an important area. This issue is an within important the wind issue engineering within the wind community, engineering e.g., thecommunity, establishment e.g., ofthe a establ windishment code for of southern a wind China.code for southern China.

Figure 5. Ensemble mean turbulence intensity profile of all 6 events. Figure 5. Ensemble mean turbulence intensity profile of all 6 events. The individual turbulence intensity profiles are shown in Figure6. In general, they do not follow the internationalThe individual standards turbulence very intensity well. Figure profiles7 shows are show the verticaln in Figure profile 6. In of general, the gust they factor. do not A fitting follow the international standards very well. Figure 7 shows the vertical profile of the gust factor. A fitting

Atmosphere 2020, 11, 270 9 of 16 Atmosphere 2019, 10, x FOR PEER REVIEW 9 of 16 curvecurve based based on on the the power power law law could could be generated, be generated, and it followsand it quitefollows well quite the internationalwell the international standards GB50009-2012standards GB50009-2012 and AIJ-RLB-2004. and AIJ-RLB-2004.

Figure 6. Turbulence intensity proﬁles of each individual event, total = 6. N refers to the number of samplesFigure 6. in Turbulence each panel. intensity profiles of each individual event, total = 6. N refers to the number of samples in each panel.

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Figure 7. Gust factor profile of all 6 events. Figure 7. Gust factor profile of all 6 events. 6. Statistical Analysis of the Wind 6. Statistical Analysis of the Wind The statistical analysis follows the method as described in Solari et al. [3] and Burlando et al. [4]. GaussianThe distributionstatistical analysis of the follows wind and the method5/3 law ofas thedescribed spectral in intensitySolari et al. were [3] expectedand Burlando based et on al. the [4]. − previousGaussian studies distribution of thunderstorm of the wind outflows.and −5/3 law Similar of the analysis spectral was intensity conducted were forexpected the dataset based of on this the studyprevious to see studies if the presentof thunderstorm data also outflows. follow such Similar laws. analysis If such laws was wereconducted indeed for fulfilled, the dataset this wouldof this givestudy greater to see confidence if the present to the data quality also offollow the data such and laws. confirm If such that laws the were physical indeed laws fulfilled, are consistent this would with thegive squall greater line confidence outflow cases to the considered quality inof thisthe paper.data and A summaryconfirm that of the the analysis physical method laws are is given consistent here. Thewith decomposition the squall line of outflow wind is cases given considered by: in this paper. A summary of the analysis method is given here. The decomposition of wind is given by: U(t) = U(t) + U (t) (10) 𝑈𝑡 =𝑈𝑡 +𝑈𝑡0 (10) wherewhereU(t) ¯Ū(t)is is the the slowly-varying slowly-varying mean mean wind wind velocity velocity extracted extracted here here by by a a running-mean running-mean filter filter with with a a movingmoving average average period period T T= = 3030 s.s. U’(t)Ū¯ ’(t) isis thethe residualresidual turbulentturbulent fluctuationfluctuation expressedexpressed as:as:

𝑈 𝑡 =𝜎𝑡𝑈𝑡 (11) U0(t) = σ(t)Ur(t) (11) where σ is the slowly-varying standard deviation of Ū’(t), calculated over a sliding window T = 30 s, ¯ whereand Urσ (t)is theis the slowly-varying reduced turbulence standard fluctuation. deviation This of U’(t) latter, calculated quantity is over usually a sliding modeled window as a stationary T = 30 s, andGaussian Ur (t) israndom the reduced process turbulence with zero fluctuation. mean and This unit latter standard quantity deviation. is usually The modeled probability as a stationary density Gaussianfunction of random a standard process Gaussian with zerodistribution mean and is given unit by: standard deviation. The probability density function of a standard Gaussian distribution is given by: 1 𝑓𝑥 = 𝑒 (12) √2𝜋 1 1 x2 f (x) = e− 2 (12) √2π In addition, to overcome the problem of spectrum leakage caused by direct use of the fast Fourier transformIn addition, (FFT), to the overcome power spectral the problem density of spectrum (PSD) of leakagereduced caused turbulence by direct fluctuation use of the was fast calculated Fourier transformby the Welch (FFT), method the power [15]. spectral density (PSD) of reduced turbulence fluctuation was calculated by the WelchFor completeness, method [14]. the time series of wind at different averaging stages are shown. The raw time seriesFor and completeness, 30 s average the are time shown series in ofFigure wind 8a–d. at di ffTheerent reduced averaging turbulence stages are fluctuations shown. The are raw given time in seriesFigure and 8e–h. 30 sThe average resulting are shownGaussian in Figurefits are8 showna–d. The in Figure reduced 9a–d. turbulence It can be fluctuations seen that, in are general, given inthe FigureGaussian8e–h. fits The the resultingwork very Gaussian well. The fits corresponding are shown in power Figure spectra9a–d. Itare can shown be seen in Figure that,in 9e–h. general, At the various heights, the inertial subrange (−5/3 law) works wells up to about 1 Hz. At higher frequencies, there are deviations from this law, and the power at high frequencies appears to be on the higher side,

Atmosphere 2020, 11, 270 11 of 16 the Gaussian ﬁts the work very well. The corresponding power spectra are shown in Figure9e–h. At the various heights, the inertial subrange ( 5/3 law) works wells up to about 1 Hz. At higher Atmosphere 2019, 10, x FOR PEER REVIEW − 11 of 16 frequencies, there are deviations from this law, and the power at high frequencies appears to be on the higherparticularly side, particularly for cases 4 for and cases 6. More 4 and cases 6. Morewould cases need wouldto be accumulated need to be accumulatedto see if this is toa common see if this is a commonfeature. feature.

Figure 8. Time histories of (a–d) measured and slowly varying mean wind speed, and (e–h) reduced turbulenceFigure 8. ﬂuctuation, Time histories at heightof (a–d levels) measured of 10, and 40, slowly 160 and varying 320 m mean during wind 6 events.speed, and (e–h) reduced turbulence fluctuation, at height levels of 10, 40, 160 and 320 m during 6 events.

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Figure 9. (a–d) Histograms of reduced turbulence fluctuation compared with Gaussian distribution, and (Figuree–h) power 9. (a–d spectral) Histograms densities of reduced compared turbulence with fluctuation5/3 law, compared at height levelswith Gaussian of 10, 40, distribution, 160 and 320 m − duringand 6 ( events.e–h) power spectral densities compared with −5/3 law, at height levels of 10, 40, 160 and 320 m during 6 events. 7. Wind Gust Nowcasting 7. Wind Gust Nowcasting For the six squall line cases, the 1 min (3 s mean) wind gusts, as measured by the anemometers in Hong Kong, were examined. The locations of the surface anemometers are given in Figure 10a, together with the locations of the microwave radiometers, namely, KP in the urban area and S1E at the airport. The boundary layer-type wind profiler is operated at locations near KP and S1E, respectively, Atmosphere 2019, 10, x FOR PEER REVIEW 13 of 16 Atmosphere 2020, 11, 270 13 of 16 For the six squall line cases, the 1 min (3 s mean) wind gusts, as measured by the anemometers in Hong Kong, were examined. The locations of the surface anemometers are given in Figure 10a, in the derivation of the wind gust estimate. There are two estimates for each site, namely, the mean together with the locations of the microwave radiometers, namely, KP in the urban area and S1E at windthe gust airport. estimate The and boundary the maximum layer-type wind wind gust profile estimate.r is operated The details at locations could benear found KP and in Chan S1E, and Hon [respectively,5]. The wind in the gust derivation estimates of the serve wind as gust nowcasts estimate. of There the strength are two estimates of the wind for each gust, site, because namely, they showthe the mean potential wind gust values estimate that theand windthe maximum gust could wind reach gust inestimate. order The to alert details the could weather be found forecasters in aboutChan the possibleand Hon strength [5]. The ofwind the gust wind estimates gust. They serve can as servenowcasts the purposeof the strength of nowcasting, of the wind though gust, they are observation-based.because they show the potential values that the wind gust could reach in order to alert the weather Figureforecasters 10a about also shows the possible the surface strength anemometer of the wind readings gust. They (10 can min serve mean the wind) purpose during of nowcasting, the passage of the squallthough line they through are observation-based. Hong Kong on 20 April 2019, in which wind gust up to 35–40 m/s was registered at some anemometerFigure 10a also stations. shows the This surface is a rather anemometer extreme readings squall line(10 min case, mean and wind) the gust during measured the passage is among of the squall line through Hong Kong on 20 April 2019, in which wind gust up to 35–40 m/s was the top three of the gust climatology of the station, without considering tropical cyclone and strong registered at some anemometer stations. This is a rather extreme squall line case, and the gust monsoonmeasured cases. is Foramong the the other top cases,three of the the wind gust climatology gusts are relatively of the station, smaller, without with considering a range of tropical 15–20 m/s, and theycyclone may and be strong considered monsoon to be cases. more For “ordinary” the other cases, squall the line wind cases. gusts The are ordinary relatively is smaller, in the sense with a of the gust factor,range of namely, 15–20 m/s, the and gust they over may the be mean considered wind to is inbe themore order “ordinary” of a few squall times line (e.g., cases. 3 The to 5 ordinary times).For a largeris gust in the factor, sense theof the squall gust linefactor, appears namely, to the be gust more over special. the mean wind is in the order of a few times The(e.g.,wind 3 to 5 gusttimes). estimate For a larger is plotted gust factor, with the the squall measured line appears wind to gusts be more at thespecial. various stations in the form of aThe time wind series gust in estimate Figure 10 isb–e plotted for thewith various the meas casesured studiedwind gusts in thisat the paper. various It couldstations be in seen the that, for ordinaryform of a squall time series line, in the Figures mean 10b–e wind for gust the isvarious already cases su ffistudiedcient in for this nowcasting paper. It could the gustbe seen magnitude. that, However,for ordinary for more squall extreme line, the cases mean like wind the gust one is already for 20 April sufficient 2019, for the nowcasting maximum the gust wind magnitude. gust estimate However, for more extreme cases like the one for 20 April 2019, the maximum wind gust estimate appears to catch the high wind gust at about 20 min before the peak of the wind gust, though the appears to catch the high wind gust at about 20 min before the peak of the wind gust, though the magnitudemagnitude is still is still smaller smaller by by a fewa few m m/s./s. Nonetheless, Nonetheless, the the maximum maximum wind wind gust gust estimate estimate is considered is considered to beto useful be useful in nowcasting in nowcasting the the occurrence occurrence of of gusty gusty windswinds from from squall squall lines. lines.

(a) Locations of the automatic weather stations with wind data on 20 April 2019

Figure 10. Cont.

Atmosphere 2020, 11, 270 14 of 16

Atmosphere 2019, 10, x FOR PEER REVIEW 14 of 16

(b) 11 April 2019

(d) 20 April 2019

(e) 10 June 2019.

Figure 10. (a) The locations of the automatic weather stations with wind data (locations with wind Figure 10. (a) The locations of the automatic weather stations with wind data (locations with wind barbs) and the two stations equipped with the microwave radiometer (KP and S1E), together with the barbs) and the two stations equipped with the microwave radiometer (KP and S1E), together with the windswinds over over Hong Hong Kong Kong during during the the passage passage ofof the squall squall line line on on 2020 April April 2019; 2019; (b–e ()b are–e) the are time the series time series of theof windthe wind gust gust at theat the weather weather stations stations andand th thee nowcast nowcast wind wind gusts gusts (including (including maximum maximum and mean) and mean) determineddetermined from from the the wind wind proﬁler profiler and and microwavemicrowave ra radiometerdiometer data. data. The The x axis x axis is time is timein HKT in HKTand y and y axisaxis is the is gustthe gust in min/ s.m/s.

8. Conclusions8. Conclusions SubtropicalSubtropical squall squall lines lines over over the the PRD PRD region were were studied studied for for the the first first time time using using the wind the wind data data collectedcollected by aby 356 a 356 m meteorologicalm meteorological tower tower inin Shenzhen. Both Both the the mean mean wind wind and andthe turbulence the turbulence characteristics of the squall lines were examined. The mean wind profile was found to be consistent with the international standards for wind engineering applications, although a low-level jet, which has been reported by previous studies of ordinary thunderstorm outflows (e.g., Choi [2] and Gunter and Atmosphere 2020, 11, 270 15 of 16

Schroeder [15]), may not be found in individual cases. However, the turbulence intensity profile had quite significant deviations from the international standards, although its characteristics need to be confirmed further with the accumulation of more squall line cases in the PRD region. The fluctuating wind component of the squall line was analyzed based on the power spectrum method. For all of the six cases considered in this paper, this wind component followed the 5/3 law of − inertial subrange up to about 1 Hz, which is similar to ordinary thunderstorm outflows. The power spectrum between 1 and 10 Hz may be suspicious. It is not evident if this is the characteristic of the squall line in this region, or of instrumental issues such as the performance of the sonic anemometers in heavy rain and high wind situations. More systematic studies need to be performed with the accumulation of more squall line cases. As a meteorological application for weather forecasting, a wind gust nowcast algorithm based on ground-based remote-sensing instruments was studied for the six cases of squall lines. For ordinary squall lines, the mean wind gust estimate appeared to be sufficient in nowcasting the strength of the squall. However, for an extreme wind gust case, the maximum wind gust estimate appeared to be useful in nowcasting the possible occurrence of gusts of 35 to 40 m/s. The results may be useful for similar applications of wind gust estimate for squall line passages. One major limitation of this paper is that the number of cases was rather small. The meteorological tower has been operated for a relatively short period of time only, and the accumulation of the number of cases of the passage of subtropical squall lines takes time. Thus, further results need to be reported with the accumulation of more cases.

Author Contributions: Conceptualization, P.W.C., J.H. and Q.L.; methodology, P.W.C. and J.H.; formal analysis, P.W.C. and J.H.; investigation, P.W.C. and J.H.; resources, L.L., C.L., L.Z. and H.Y.; data curation, P.W.C.; writing—original draft preparation, P.W.C. and J.H.; writing—review and editing, P.W.C. and J.H.; supervision, Q.L.; funding acquisition, L.L., C.L., L.Z. and H.Y. All authors have read and agreed to the published version of the manuscript. Funding: This study is supported by National Natural Science Foundation of China (Grant No. 41575005). Data availability. The data in this study are not available for use by others. Conﬂicts of Interest: The authors declare no conﬂict of interest.

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