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An Observation Study of Typhoon Vicente over Complex Terrains

Y.C. HE1, Q.S. Li1, P.W. Chan2 1Department of Architecture and Civil Engineering, City University of , Hong Kong, 2Hong Kong Observatory, Hong Kong, China email: [email protected], [email protected], [email protected]

ABSTRACT: This paper presents an observation study on Typhoon Vicente which has been the strongest typhoon event that attacked Hong Kong since 1999. Synchronized measurements from multiply meteorological stations are analyzed. Vertical mean wind profiles below 5000 m over both marine and rugged exposures are highlighted. The results show that mean wind speed profiles with an open sea exposure are much similar to those observed over oceans which are featured by a jet-like structure with the lower portion following the logarithmic law; while those with rugged upwind terrains are influenced severely by topographic effects. Specifically, waves/vortexes might occur downwind of mountains/hills as embodied by the severe wind shears. Speed-up effects are found evident at the zenith of an isolated island. In addition, intermittent existence of secondary horizontal wind maximum (SHWM) is also observed around 4000 m which was associated with evident convections. Due to the complexity of surrounding topographic features, measurements of surface wind are also found influenced by such topographic effects significantly. To eliminate these effects, a data-driven standardization scheme is proposed for the standardization of the raw surface wind speeds. The effectiveness of this scheme is validated through comparing the standardized results at two stations.

KEY WORDS: Typhoon; Wind Profile; SHWM; Speed-up; Gust; Complex Terrain; Standardization.

1 INTRODUCTION Knowledge of landfall (TC) wind fields is useful for the wind-resistant design of civil structures at TC-prone areas. Although there have been extensive studies conducted on TC wind characteristics during the last decades, due to the low probability of a landfalling TC passing through an equipped site and the frequent damage of measurement devices during strong winds, there are still insufficient observations of TC winds, especially at upper portion of the TC boundary layer (TBL). Meanwhile, most previous observation studies concerned with open flat terrain conditions; measurements of TC wind field over complex terrains have rarely been reported. As is known, hills may result in complex flow phenomena such as development, separation, reattachment and downstream recovery of the turbulent boundary layer. Thus, wind characteristics over rugged terrains usually demonstrate markedly different features from those under flat terrain conditions. Hong Kong (HK) is sited on the southeast coastal line of China and is attacked by TCs every year. The regional topography, as characterized by disorderly distributed mountains/hills/islands, is considerably complicated. The potential danger for populations, aircrafts and civil structures against severe winds makes it of great importance to clarify the TC wind fields under such complex terrain conditions. This paper presents an observation study of a landfall typhoon. Multi-type datasets from a number of scattered meteorological stations are adopted to explore the TC structures within the whole TBL.

2 OBSERVATION NETWORK AND DATASET There are over 40 meteorological stations distributed in HK territory which are equipped with cup or propeller anemometers. Eight of them are selected for this study, i.e., TMS, R2E, SHW, HKO, PKA, YTS, CCH, and WGL, as shown in Figure 1. The location heights of the anemometers at these sites are listed in Table 1. Among these stations, TMS and YTS are located atop the peaks of Tai Mo Shan (955 m above mean sea level, AMSL) and Lantau Island (742 m AMSL), respectively. PKA is sited at the saddle point of two peaks of the Lantau Island. WGL and CCH are located respectively at the zenith of Waglan Island and Cheung Chau Island (Figure 1b). HKO is sited above a built-up terrain. R2E is located around the runway of the Hong Kong International Airport. SHW is sited at the foot of the Lantau Island. Thus, the results measured at these stations are expected to reflect wind characteristics at different boundary layer levels and over various terrain/topographical setups. The anemometer-based measurements at each station consist of 1 min mean wind speed and direction as well as 3 sec peak gust which are updated every minute. In addition, R2E and SHW can offer 1 sec to 1 sec updated records as well. Besides the anemometer devices, CCH and SHW are also equipped with boundary-layer-type Doppler radar profilers. The two profiler systems work in both low and high modes simultaneously. At CCH, the low mode detects the atmosphere in a vertical

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range of 213-1656 m at 60 m interval, compared to the range of 459-5371 m at 205 m interval for the high mode. The remote sensing probes from both modes are recorded every 2 minutes, which stand for 10 min bulk average values due to the overlapping average by the data logger. At SHW, the low mode works in a range of 133-1576 m at 60 m interval, while the high mode performs in a range of 371-5283 m at 205 m interval. The detecting records from the two modes also stand for 10 min mean values but are updated every 10 minutes. Detailed information about these devices can be found in He et al., (2013a, b). Severe Typhoon Vicente is one of very few TC events influenced HK that necessitated the issuance of No. 10 Hurricane Signal (sustained wind speed>32.8 m/s) from . As shown in Figure 1, it entered the northern part of the Sea on the morning of 21st July 2012, and intensified continuously in the following two days. The strongest local surface winds (1 min mean and 1 sec mean speeds: 41.2 m/s and 51.0 m/s at CCH) were recorded around 00:00-02:00 on 24th July when the storm center got closest to Hong Kong (about 100 km to the southwest of HKO) with a translational speed of 20 km/h toward NW. The temporal central pressure is estimated around 950 hPa, while in HK, the lowest instantaneous mean-sea- leave pressure of 981.6 hPa was recorded at CCH. Vicente made landfall near the coastal areas of Taishan of mainland China about 130 km west-south west of HK before dawn on 24th July. After that, it weakened rapidly and finally dissipated over the northern part of on 25th July.

Table 1. Location heights of anemometers at 8 meteorological stations in HK (unit: m). Name CCH HKO PKA R2E SHW TMS WGL YTS Above Ground Level (m) 26.7 31.7 15.7 10 10 11.2 26.9 10 Above Mean Sea Level (m) 98.6 74 386.2 15.2 14.7 966.2 82.7 752

Figure 1. Locations of the weather stations (a) and the zoomed view of CCH (b)

(a) (b)

HK

Figure 2. Center track of Typhoon Vicente-(a): during 21st -25th July when the center was within 800 km radius range away from HK; (b) during 23rd-24th July when Vicente got close to HK

3 RESTULTS 3.1 Evolution of vertical profiles Measurements collected from the anemometers and the two modes of Doppler radar profilers at both CCH and SHW are synchronized (mean wind values from the anemometers are calculated following the way involved in the profiler’s logger), to get integrated wind profiles which cover the whole TBL. The non-synchronicity is controlled within 1 minute. The integrated single profiles are then averaged (non-overlapping) over each half-hour to generate 30 min mean wind profiles. The evolutions of vertical profiles of mean horizontal wind speed (U) and direction (θ) as well as the mean vertical speed (W) are shown in

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Figure 4 in a format of filled color contour. Corresponding time histories of air pressure measured at CCH (for profiles at CCH) and HKA (for profiles at SHW; HKA is located close to R2E) are also depicted (red dotted lines) at the upper portion of each figure, to indicate the variations of storm-relative position during the passage of Vicente. For SHW, the measurements during 22:00-24:00 on 23rd are missed, which results in a 2 hours’ gap in the contour picture. Noting that W values detected by Doppler radar profilers in rainy weather mostly (when W<0) account for the falling precipitations rather than wind flows. Thus, negative values of W may roughly indicate the intensity of dropping precipitations.

Figure 1. Variations of 30 min mean wind profiles in form of filled color contour (dotted lines stand for variations of air pressure)

The results from the two sites demonstrate a similar pattern in both amplitude and phase. Spatially, the TBL is found to occupy the lowest 1000-1500 m depth of the atmosphere. Beyond the TBL, the measurements reflect a relatively smooth wind field with respect to altitude; while within the TBL, wind shears become significant. In particular, the W profile above CCH is capped with a layer featured by abruptly weakened precipitations (small amplitude of negative W). The results above SHW also reveal the existence of such a layer, but the location appears to be slightly higher. The heights of this layer here are consistent with the melting level (~5 km) of the conceptual model of rainbands’ structure presented in Hence and Houze (2012). This melting layer separates the ranband vertically into two portions: the upper and the lower. The lower portion is featured by convective or stratiform rainfall precipitations. The upper portion in the inner region of the rainband is characteristic of ice particles imported from the eyewall which seed the clouds below and further produce rainfall in the low-level portion. From the viewpoint of time, governed by the typhoon’s dynamics/thermodynamics, mean wind profiles at the study sites evolved consistently with the variation of storm-relative position. As the typhoon approached, mean wind strengthened continuously with the rainfalls getting intermittently larger and longer. During 22:00/23rd-02:00/24th when Vicente got closest to the study sites, wind strength reached to its maximum level (Umax=45 m/s recorded at the 1235 m gate above CCH), and the wind direction varied rapidly from E to SE. Meanwhile, this period was associated with continuous heavy rains. After that, the wind started to weaken and the rainfalls decreased intermittently as the typhoon moved away. Despite the above similarities, a scrutiny of Figure 4 shows that there are noticeable differences between the results at these two sites. First, the TBL flows above SHW are apparently more turbulent than those above CCH, which reflects the more severe topographic effects around SHW. Second, the intermittent horizontal wind minima centered 3000 m above CCH are absent in the results at SHW. By contrast, the intermittent horizontal wind minima located around 1600 m above SHW after 12:00/24th are less evident above CCH. These features are speculated caused by a combination of vertical wind shear and the convective cells that tend to be influenced by underlying terrain/topographic setups and the storm-relative positions. 3.2 Wind profiles at selected stages To further explore the characteristics of typhoon wind field, we select a number of typical stages out of the whole studied period, according to wind strength, upwind topographic setups and also the steady-state conditions of the typhoon. For CCH, the considered segments include: 08:00-14:00/23rd, 22:00/23rd-01:00/24th and 01:00-03:00/24th. For SHW, the considered stages are: 08:00-14:00/23rd, 14:00-17:00/24th and 18:00-19:0024th. Figure 5 depicts the ensemble-mean wind profiles at each of the above

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stages. The Mean Boundary Layer (MBL) speed and direction, defined respectively as the scalar/vector average of all gate records below 1000 m, are computed and shown in each picture. Also presented are the TBL depth (h) and the ratio of mean speed at the anemometer height (Ua) to the gradient speed (Uh, estimated as the maximum value of measurements from the low- mode of profiler).  Stage 22:00/23-01:00/24 at CCH This stage contains the strongest winds and corresponded to an open sea exposure. Based on the radar echoes captured at 01:00/24, the temporal eye-radius of Vicente is estimated to be 35 km. The radial distance of CCH away from the storm center is 100 km (N) at 22:00/23, and 80 km (NE) at 01:00/24. Thus, at this stage, CCH is located in the downshear-right (DR) quadrant of the inner rainband region according to the classification in Hence and Houze (2012). From Figure 5, the wind speed profile is characterized by a low-level jet (LLJ) centered 1200 m. Speeds decrease both below and above this height, with the one at the lower portion basically following the logarithmic law. The LLJ observed here agrees with the one reported in Barnes et al (1983) where the low-level wind maximum (LLWM) occurred around 1500 m. The jet-like structure in rainband is similar in shape to that observed in the eyewall (e.g., Powell et al., 2003; Giammanco et al., 2013). But they differ from each other in generating mechanisms distinctly. While the LLJ in eyewall is attributed to the weakening of the horizontal pressure gradient with height in the warm core of a TC (Powell et al., 2003), the one in rainband is speculated caused by the convective motions of the overturning updraft and/or the inner-edge downdraft (IED) in the principal rainband (Didlake and Houze, 2009). By fitting the gate records between 200-1000 m (record from the anemometer is excluded as it is opined to be influenced by non-ignorable topographic effects), the roughness length scale is estimated as 3 mm, which is comparable to those observed over oceans (e.g., Powell et al., 2003; Vickery et al., 2009). For the wind direction profile, mean wind veers with height above 200 m, from 94° at the 213 m gate to 104°, 110° and 125° at the heights around 500 m, 1000 m and 5000 m, respectively. These veering angles are consistent with the counterparts over open terrain (e.g., Yeo and Simiu, 2010). But non-consistence exists at the anemometer height (102°). Usually, atmosphere in the surface layer (ASL) is regarded as well mixed with unchanged mean wind direction along height. Observations here seem to reveal the existence of backing wind in the ASL. This discrepancy may be related to the different detecting principles of adopted instruments in this study (e.g., an anemometer may overestimate the real values in strong winds due to inertia effects), and/or the topographic effects cause by the Cheung Chau Island.

Figure 5. Mean speed profiles at three stages above CCH and SHW (mean speed/direction values are respectively computed via scalar/vector average method; error-bar stands for ±std; MBL indicates the mean value of all gates below 1000 m; ‘Uh’ represents the maximum speed estimated via a 5th order polynomial fitting based on the measurements from the low-mode of profiler, with ‘h’ the corresponding height; ‘Ua’ means the mean speed at the anemometer height).

 Stage 01:00-03:00/24 at CCH This stage also corresponds to an open sea exposure (MBL speed: 137°). From Figure 5, the speed profile is featured by a negative increase of mean speed along height at the lower portion (33.2 m/s at 26.7 m and 32.1 m/s at 213 m), owing to the speed-up effect caused by the island (Figure 1b). Compared with the profile at Stage 22:00/23-01:00/24, it’s clear that the

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surface winds at this stage are more severely influenced by the speed-up effect, although the mean directions (at 26.7 m) differ mutually with only 30°. The large gradient of this directionally varied speed-up effect found here is consistent with the correction-factor results (0.710 for 102°, 0.627 for 132°) presented in He et al. (2014) which are used to convert the raw surface wind speeds into their potential values (i.e., speed at 10 m height over open flat terrain z0=0.03 m). These observations suggest that densely classified azimuthal sections should be considered for the issues relevant to such irregular topographic features.  Stage 08:00-14:00/23 at CCH/SHW The MBL direction is found around 60° for both sites, and the mean direction values at the anemometer height and the 1500 m gate are 27°/80° at CCH and 39°/72° at SHW, respectively. The upwind topographic features are considerably complicated at this stage (Figure 1a). For CCH, the main topographies include Tai Mo Shan (955 m AMSL, peak-to-peak distance, or PPD for short, is 25 km), Tai Lo Shan (583 m, to the NNE of HKO, PPD is 25 km), the western part of Hong Kong Island (554 m, PPD is 15 km) and the northeastern part of Cheung Chau Island (Figure 1b). For SHW, the main topographic features include Tai Mo Shan and the northeastern hills of Lantau Island. The speed profiles at both sites are featured by a significant shear between a typical range of 300-1500 m. Mean wind speeds above this range tend to level off first and then decrease moderately with height. The maximum values of 23.9 m/s 22.3 m/s occur around 1700 m and 2300 m above CCH and SHW, respectively. The a bit weaker and higher maximum wind above SHW can be reasonably explained by its slightly outer storm-relative position, compared to that of CCH (Figures 1-2).

Figure 6. Evolution of 10 min mean speed and direction at different gates of the Doppler radar profiler and anemometer at CCH

In this severe-shear-featured range, mean speeds drop drastically from the maxima to 14 m/s and 7.8 m/s at 300 m above CCH and SHW, respectively. Figure 6 shows the time histories of 10 min (overlapping average) mean speed and direction from the anemometer and another five gates (213, 333, 514, and 995 m gates from low mode, and 1892 m gate from high mode) of the profiler at CCH. The consistent fluctuations of the speed samplings at 213, 333 and 514 m gates reveal the existence of vortexes/waves, which is further supported by the noticeable variations of the direction samplings around 11:02 and/or 11:50 at the above three gates. But these features become less evident in the records at the 995 and 1892 m gates and the anemometer height. Thus, the waves/vortexes are speculated less likely to extend to the surface level or beyond 1000 m. These findings are consistent with those reported in Chan (2012) in which vortex/wave shedding from the Lantau Island was observed through both in-situ measurement and numerical simulation. It is interesting that mean speed values in the middle parts of this severe-shear featured layer abide by the logarithmical law well. Through fitting, the corresponding roughness length scales are determined as 45 m and 180 m at CCH and SHW, respectively. These values are speculated to be dependent on the geometric dimensions of upwind topographies, the coverage and the distance downwind from them (Bitsuamlak, et al., 2004; Cao et al, 2012). Below this shear range, mean speed values vary slightly with height. At SHW, owing to the remarkable sheltering effect, considerably low speed of 3.8 m/s is observed at the anemometer height, compared to 10.4 m/s at CCH where speed-up effect tends to play a role.  Stage 14:00-17:00/24 at SHW This stage (MBL direction: 145°) corresponds to a hilly upwind terrain dominated by the hill (440 m AMSL at the crest) at the northeastern part of Lantau Island (Figure 1a). From Figure 5, mean speed profile in the range of 100-400 m also exhibits a significant shear (from 18.2 m/s at 433 m to 6.5 m/s at 133 m; roughness length scale is 75 m) which is similar to but located much lower than that at Stage 08:00-14:00/24. It is speculated that the phenomena of flow separation and vortex shedding occurred on the leeward of the hill. Slightly above this range, mean speed is found to accelerate noticeably (18.2 m/s at 433 m, compared to 16.1 m/s at 914 m), mostly due to the speed-up effect. Around the heights between 1500-2000 m, the mean wind profiles depict another wind shear, which will be further discussed in the following part.  Stage 18:00-19:00/24 at SHW Mean speed profile above SHW is featured by an additional severe-shear-layer between 1200 m and 2200 m, besides the one in the range of 100-500 m (Figure 5). A secondary horizontal wind maximum (SHWM) of 17.5 m/s is recorded at 2213 m, compared to the low-level maximum of 20.3 m/s at 734 m. The local weakest mean wind of 5.5 m/s is measured at 1456 m. To examine how this secondary severe-shear-layer evolves along time, Figure 7 depicts the hourly-to-hourly updated vertical profiles of non-overlapping mean horizontal wind speed (U) at both CCH and SHW during the period of 17:00-22:00 on 24th

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July. The results at CCH show that a much higher SHWM occurs around 3500-4500 m, which is followed by the minimum wind centered 3000 m. The observed SHWM above CCH is similar to those reported in Donaher et al (2013) (3500-5000 m) and Hence and Houze (2008) (centered 4000 m) which are regarded as a kinematic consequence of the vertical wind shear and the updraft (Hence and Houze, 2008; Didlake and Houze, 2009). Compared to the case at CCH, results above SHW vary markedly among different segmental periods. The SHWM phenomenon tends to appear around 2200 m during 17:00-18:00, and gets evident during the following hour. After that, it uplifts greatly to 3000 m and then become less sharp during 20:00-22:00. The distinct discrepancy of vertical wind structures above SHW from those above CCH is possibly attributed to the topographic effects that may influence the convective activity significantly. Collectively, the SHWM phenomenon above both sites is accompanied with noticeable fluctuations of U below the minimum winds, which reflects the vertical transportation of momentum through convection.

Figure 7. Hourly-to-hourly updated mean speed profiles above CCH and SHW during 17:00-22:00 on 24th July

3.3 Surface winds at various stations Time histories of 10 min mean records of surface wind at different stations during the passage of Vicente are depicted in Figure 8. YTS (752 m) records the maximum speed of 52 m/s, which is markedly larger than the one of 40 m/s at TMS (966.2 m). This discrepancy may be explained by the differences of storm-relative locations as well as the topographical effects at these sites. Around PKA, the wind structure is dominated by the canyon effect. The prevailing wind directions are constrained around 150° and 340° which are parallel to the canyon’s orientation. Results at R2E and SHW reflect the variation of sheltering effect with respect to downwind distance from the hill crest, i.e., wind strength decreases sharply with the decrease of downwind distance. HKO sites at built-up terrain which is further surround by Tai Lo Shan (583 m) to the NNE of HKO (Figure 1a). The maximum speed recorded there is only 16 m/s, which is similar to that at SHW.

Figure 8. Time histories of 10 min mean records of surface wind at different stations. (a) (b)

Figure 9. Gust factor (GF) at different sites: (a) GF time histories; (b) GF values VS mean wind speed)

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The gust factors (GFs) of 3 sec wind peaks over 10 min mean speeds at these sites are compared in Figure 9a. As expected, wind flows at WGL, TMS, CCH and R2E are relatively smoother, while those at HKO and SHW become much more turbulent. The comparatively large GF values at YTS (752 m) before 00:00/24, which are comparable to those at HKO and SHW, reveal that the local wind turbulence structures are influenced significantly by the upwind mountains (i.e., Tai Mo Shan/Tai Lo Shan). But such interference effects become much weakened at CCH (GF is around 1.5 before 00:00/24). At PKA, GF gets its maximum value of 3.5 (which is also the maximum among all stations) around 18:00/23 when the upwind flows were forced to be parallel to the canyon’s orientation. Note that GF values may also vary among different stages during the storm’s passage, and demonstrate a dependence on storm-relative position (Giammanco et al., 2013). They may be occasionally affected by the local convective activities as well (Vickery and Skerlj, 2005). But, basically, such influences are less significant compared to the topographic effects in this study. Variations of GF with respect to 10 min mean wind speed at various stations (Figure 9b), collectively demonstrate a consistent 3-stage tendency. Under weak wind conditions, GFs decrease with speed. Results at HKO show that the thermal effect tends to play a more evident role. As the wind further strengthens, GFs start to increase (e.g., at WGL and R2E), due to the enhanced air- sea interactions (i.e., roughness scale over sea water increases with wind speed). When the speed exceeds about 30 m/s, GFs become to level off, or even decrease slightly with the speed (i.e., at TMS and YTS). 3.4 Standardization of surface wind speeds As discussed above, the measurement records of surface wind may be severely influenced by the topographical effects, which would further bring in errors for the weather forecasting and the determination of design speed for civil structures under complex terrain conditions. A conventional method of correcting such raw data is to conduct wind tunnel tests based on topographical models. However, in case of large area of rugged terrains, small scale topographical models have to be adopted due to the limited size of conventional wind tunnels, which may lead to non-ignorable testing errors (Bowen, 2003). In addition, the wind tunnel testing method may suffer from bad portability, i.e., correction results at one site may be hardly used for the same purpose at another nearby site. One may also resort to numerical simulations, e.g., using computational fluid dynamics (CFD) techniques. But the numerical methods may be of high computational cost. Meanwhile, the validity and accuracy of the CFD results under complex terrain conditions has not been well recognized (Cochran and Derickson, 2011). Recently, the authors have proposed a data-driven standardization method based on field measurements from both profiler system and surface anemometer (He et al., 2014). As there is no need to carry out extra wind tunnel tests or CFD simulations, this method has the merit of low cost. Meanwhile, the speed records of surface wind at adjacent sites which are not equipped with remote sensing systems can also be corrected. Thus, this method is considerably efficient. The basic idea of this method lies in that the gradient speed, regarded as the LLWM detected by the profiler system, keeps unchanged before and after the standardization. Detailed introduction of this method is skipped here. One can refer to He et al. (2014) for further information.

Figure 10. Comparison of mean surface wind speeds at CCH and WGL with and without correction

To validate the efficiency of this method, we first focus on the mean wind profile at Stage 22:00/23-01:00/24 from CCH (Figure 5). The mean wind speed and direction measured by the anemometer (26.7 m AGL) is 30.2 m/s and 102°. Using the corresponding directional correction factor (i.e., 0.710) obtained with the data-driven method (He et al., 2014), the raw mean speed record can be corrected into the potential speed value of 21.4 m/s (i.e., wind speed at 10 m height above open flat terrain with z0=0.03 m). On the other hand, we find that the mean speed profile follows the log-law in the middle and upper portions of TBL. Thus, it is reasonable to assume that the corresponding mean speed profile over an open flat terrain (z0=0.03 m) should follow the log-law within the whole TBL. Using the hypothesis of unchanged gradient wind over different terrains, the potential speed can be computed as 22.5 m/s which can be treated as the “true” potential speed value. Thus, the error of the prediction using the data-driven method in this case is 4.9%, which is acceptably good in consideration of a relatively rough classification of azimuth and the non-consideration of speed-dependence of the standardization results in He et al. (2014) due to limited data. We then use the data-driven method to convert all the raw surface wind speed data at CCH and WGL to their potential speed values during this typhoon event. Results are depicted in Figure 10. Two sets of corrected results are presented: the one using the data-driven (DD) method and the one based on wind tunnel tests (WT, only for WGL). As reflected, the raw speed records at CCH (CCH-raw) and WGL (WGL-raw) differ from one another apparently. After the correction, the potential speeds at the two

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sites basically demonstrate a good agreement. It is noted that the LLWM values above a fixed site during a TC may vary noticeably with the storm-relative position (e.g., results at Stage 08:00-14:00/23 in Figure 5, the distance between CCH and SHW is 12 km). Thus, one may not expect that the potential values of surface wind speeds at two neighboring sites should be always the same. This partially explains the relatively large differences between CCH-DD and WGL-DD during the period when the storm got close to HK.

4 CONCLUDING REMARKS Severe typhoon Vicente is one of the seldom TC cases that attached HK with a hurricane or above wind strength. It provides a good opportunity to study the TC wind field under complex terrain conditions. Based on synchronized measurements from multi-type devices, this paper presents an observation study of TC wind field during the passage of this storm. The mean wind profiles, covering a range from the surface height to 5000 m, demonstrate that the mean wind field structures in the TBL (below 1000-1500 m), can be influenced severely by the surrounding topographical features. Speed-up effects and severe wind shears that are most likely caused by mountain waves/vortexes have been observed. Beyond the TBL, while the overall mean TC wind field tends to be less turbulent, phenomenon of SHWM occurs intermittently around 2200-4500 m which is associated with evident transportation of momentum along height. The distinct discrepancy of SHWM’s behaviors above two nearby sites reveals that the SHWM features may be influenced by the underlying terrain/topographic setups significantly. Profiles of the mean vertical speed reflect the existence of a melting level located around 5500-6000 m. For onshore winds with open sea exposures, the vertical profile of mean horizontal speed is featured by a jet-like structure with the LLWM centered 1200 m. Mean speed profile below this height basically follows the log-law with the roughness length scale estimated as 3 mm which is similar to that observed over oceans. Surface wind observations obtained from a number of scattered weather sites are compared, which demonstrate the terrain/topographic effects on wind flows at near ground level. The synchronous in-situ measurements of mean wind speed and gust factor at these sites vary from one to another markedly. It is evident that direct usage of the raw surface wind data may lead to misestimations of the true wind strength. Thus, standardization of raw surface wind records is necessary under such complex terrain conditions. Using the data-driven method proposed by He et al. (2014), mean speed records at two stations are converted to their counterparts under reference conditions. The raw wind speed measurements are found to overestimate the potential values significantly, while the obtained potential values at the two sites show acceptable agreement.

ACKNOWLEDGEMENT The work described in this paper was fully supported by a grant from the Research Grants Council of Hong Kong Special Administrative Region, China (Project No: CityU 118213) and research grants from the National Natural Science Foundation of China (Project No.: 51408520).

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14th International Conference on Wind Engineering – Porto Alegre, Brazil – June 21-26, 2015