d speed profiles of typhoon matmo observed u sing doppler...

Win

3 Resear4 Ass

minsttylaana copothin

K

* Corr

nd Spee

Yuan-We

rcher, Taiwan

sociate profess

5 Researche

The winmeasured usin 2014 withtrong wind ypes of winayer for the nd deviationgradient he

ondition. Bower law tohe evolutionntensity pro

Keywords: b

responding au

ed Profi

-Shiang Tsen-Chang Y

1 Associa

National A2 Resea

National A

n Ocean Resea

sor, Departme

er, Taiwan Po

nd speed aing a groun

h the measurspeed exce

nd profiles aentire obse

n to the logeight close t

Besides, the o fit the lown of the hofile.

Typhoon bboundary la

uthor, E mail:

iles of T

Dop

sai 1* YaYang 3 P

ate researcher

Applied Resear

arch assistant,

Applied Resear

arch Institute,

ent of Atmosph

ower Research

AB

and turbulennd-based Dorement heigeeding 10 mare observeervation heiarithmic proto the surfapresent stu

wer and uppourly mean

boundary layayer, power

ystsai@narlab

Jour

Typhoon

ppler Li

a-Chao YaPo-Hsiung

r, Taiwan Oce

rch Laborator

, Taiwan Ocea

rch. Laborato

National App

heric Science,

h Institute, Ta

BSTRAC

nce intensioppler Lidarght betweenm/s in the d, which aright; 2. signofile above

ace; 4. formudy shows

per layer reswind speed

ayer, turbuler law

bs.org.tw

rnal of Coastal

n Matm

idar

ang 2 Wag Lin 4 J

ean Research

ries, Kaohsiun

an Research I

ories, Kaohsiu

plied Research

, National Tai

aiwan Power C

CT

ty profile or at Hsingda

n 48 and 268atmospheri

re: 1. develnificantly afthe surface

mation of lowthat a two

spectively isd profile as

ence intens

and Ocean Eng

mo Obse

an-Ting Cin-Lin Ch

Institute,

ng, Taiwan.

Institute,

ung, Taiwan

h Laboratorie

iwan Universi

Company, Taip

of typhoon a Harbour, s8 m. Under ic neutral sopment of ffected by Ce layer; 3. inw level jet io-layer mods appropriats well as th

ity, atmosp

gineering, Vol.

erved U

Chang 2 hen 5

es, Kaohsiung,

ity, Taipei, Ta

ipei, Taiwan.

n Matmo wsouth Taiwthe relative

stability, foa logarithmCoriolis forn existence in the rainfadel using tte to describhe turbulen

pheric surfa

17, No. 1

1

Using

, Taiwan

aiwan.

was an

ely our mic rce of

fall he be

nce

ace

海洋工程學刊第十七卷第一期

2

督卜勒光達麥德姆颱風風速剖面觀測

蔡原祥 1* 楊雅兆 2 張宛婷 2 楊文昌 3 林博雄 4 陳景林 5 1國家實驗研究院台灣海洋科技研究中心副研究員

2國家實驗研究院台灣海洋科技研究中心佐理研究員 3國家實驗研究院台灣海洋科技研究中心研究員

4國立台灣大學大氣科學系副教授 5台灣電力公司綜合研究所研究員

摘要

於台灣南部興達港使用督卜勒光達(Doppler Lidar)於 2014 年量測颱風麥

德姆颱風的風速與紊流強度剖面分佈，測量高度介於 48 至 268 m。在風速較

強，大於 10 m/s 的大氣中性穩定條件下，觀測到四種型態風速剖面： 1.所

量測高度區間風速邊界層的發展完全符合對數型態風速剖面；2.明顯受科式

力影響，高度大於表面層 (surface layer) 時，風速偏離對數型態剖風速剖面；

3. 存在一梯度高度(Gradient height)的淺層邊界層； 4.在降雨的條件下，形

成類似於低空噴流型態。本研究顯示，使用指數型態進行最適合化曲線，兩

層模式(two-layer model) 在邊界層上、下層各自有一獨立的冪指數，較能描

述平均風速與紊流強度垂直分佈的演變。

關鍵詞：颱風邊界層、紊流強度、大氣近地表邊界層、指數公式

* 通訊作者 E-mail: [email protected]

Wind Speed Profiles of Typhoon Matmo Observed Using Doppler Lidar

Journal of Coastal and Ocean Engineering, Vol. 17, No. 1 3

1. INTRODUCTION

Atmospheric boundary layer (ABL) near the surface and the turbulent fluctuations generated inside plays significant roles in the field of wind energy. The subject concerns the wind shear and turbulence induced cyclic and fatigue loading on the turbine structure, which can reduce the turbine reliability and expected lifetime as well as the influence of power generation for a contemporarily large size of wind turbine. Also, understanding the ABL improves the accuracy of weather model prediction, for which to know the upstream time history of mean wind speed, gustiness, and direction for several hours or days in advance is crucial for operation of offshore wind farms. This has to be particularly considered for the extreme wind speed in typhoon weather because severe damages on wind turbines are often reported in typhoon prone regions such as in Taiwan and Japan (Ishihara et al., 2005; Chou et al., 2013). To ensure an appropriate protection against the effect of typhoon winds, it is essential to study the detailed formation of typhoon boundary layer (TBL) and turbulence distributed in the range height of turbines to assess the structural dynamics response to the extreme wind.

In the field of wind engineering, literature surveys showed that previous TBL observations were mainly for the depth close to the surface, that is, in the surface layer (SL) using conventional

masts facilitated with anemometers. The universal logarithmic law and empirical power law were remarked to well model the wind speed profile for the strong wind speed. Besides, the decay of turbulence intensity with respect to height was described using the power law (e.g. Choi, 1978; Ishizaki, 1983; Hui et al., 2009; Song et al., 2016). A comparison of wind features between typhoons and monsoons was carried out by Choi (1978), who showed that the along-wind variance of velocity fluctuations in typhoon winds was an order larger than those in monsoon winds, revealing the extreme gustiness and complicated nature of typhoon generated winds.

In addition to tower observations, dropsonde and remote sensing technique have been employed to observe TBL, which are useful to investigate wind profiles over SL to the upper limit of TBL. Using the GPS dropsonde over the sea, Vickery et al. (2009) demonstrated that the development of entire TBL was the type of low level jet (LLJ) with the strong wind speed between 20 and 80 m/s. The logarithmic profile appropriately predicted the vertical distribution of wind speed below the jet noses. Tse et al. (2013) studied the TBL using both Lidar and Sodar. However, the LLJ type was not clearly observed over the land for the hourly mean wind speed profiles. The reason was attributed to the relative low wind speeds below 20 m/s, which were substantially lower than those studied in Vickery et al. (2009). Tse et al. (2013) concluded that the logarithmic law and


4 海洋工程學刊第十七卷第一期

power law reasonably explained the vertical distribution of wind speeds with the height up to 300 m.

Although characteristics of typhoon wind structure and boundary layer have been studied for decades in aspects of the wind engineering field, it appears that the knowledge gained from observations, particularly, over the height of SL is far from sufficient to fully understand the development of TBL. Also, difficulty is encountered due to the induvial feature of typhoon characterized by the surface roughness, topography, and atmospheric conditions of temperature and pressure gradient. In the present study, typhoon Matmo landfall Taiwan in 2014 was observed using the remote sensing technique of the ground-based Doppler Lidar at Hsingda Harbour, south Taiwan. An attempt was made to study the detailed formation of TBL and vertical variation of turbulent intensity profile, which were analyzed in the hourly mean values and compared with the empirical power law, theoretical logarithmic law and Deaves and Harris model (D-H model, Cook 1997). Among the wind profiles, the D-H model predicts the entire ABL and turbulence intensity profile , which appears to have not been validated for typhoon winds in previous studies.

The problem under consideration and the structure of this paper are as follows. Section 2 discusses the empirical and theoretical wind speed and turbulence intensity profiles. Section 3 introduces the measurement principle and calibration of

the present Lidar used. Section 4 describes the typhoon Matmo, observation site, and data processing. Section 5 presents and discusses the results of the measurements in comparison with the empirical and theoretical profiles and the conclusions are given in Section 6.

2. THEORY

2.1 Power law

In description of the mean wind speed profile, the empirical power law has been widely used in the wind engineering community. The power law is a simple mathematic expression described as follows: ( )( ) = ( ) (1) where denotes the reference wind speed at

the reference height and α denotes the

power exponent, which is the kernel parameter to represent the profile feature. Theoretically,

α is only dependent on the terrain roughness

in the atmospheric neutral stability. It is often quoted for the value of 0.14 in a flat terrain and significantly increases to a value larger than 0.3 in the city centre with tall buildings.

However, site observations experience that α

varies with the range of height and even with the magnitude of the wind speed. The power law is also employed to illustrate the vertical distribution of the turbulence intensity (Choi, 1978; Tamura, 2007) giving the formula as follows: ( )( ) = ( ) (2)



where = / represents the

turbulence intensity; is the standard deviation of the wind velocity in the

along-wind component; represents the reference turbulence intensity at the

reference height; and β represented the

power exponent for the turbulence intensity. Generally, in the atmospheric neutral stratification without the thermal buoyancy effect the turbulence intensity

decrease with respect to height and β is a

negative value.

2.2 Logarithmic law

In the typhoon event with the cooling weather and strong wind speed, the atmospheric stability is that of neutrally stratified flow (Tse et al., 2013). The turbulence generated for the depth immediately over the ground is predominated by the surface friction. In SL, the variation of the shear stress is negligible and assumed to be constant (Panofsky and Dutton, 1984). The universal logarithmic profile well describes this adiabatic layer with the form: U(z) = ∗ ln (3) where ∗ represents the surface friction

velocity and denotes the surface roughness length. Introducing the standard

deviation, , in the along-wind stream

and re-arranging equation (3), the vertical distribution of turbulence intensity is theoretically expressed as follows: TI(z) = k ∗ ln (4)

where / ∗ is the turbulence ratio. In

atmospheric neutral stability, the ratio is usually quoted to be 2.4 (Panofsky and Dutton, 1984). In the present study, the observed turbulence ratio was fed into equation (4) to make a direct comparison with the observed turbulence intensity profile.

2.3 Deaves and Harris model

As interpreted by Cook (1997), Deaves and Harris develops a more complicated D-H model to simulate the formation of entire ABL for the strong wind and neutral stratification in the homogeneous terrain. In contrast to the logarithmic law without an upper boundary condition, the D-H model matches both the upper and surface boundary conditions. A quartic polynomial was added to modify the logarithmic profile expressed as follows: U(z) = ∗ ln + 5.75 −1.88 − 1.33 + 0.25 (5) where denotes the thickness of ABL, calculated using the Rossby-Montgometry formula: z = ∗ (6) where represents the Coriolis

parameter with the value of 5.673×10-5 at

the Lidar measurement site of Hsingda Harbour and C represents the empirical constant equal to 6. The D-H model also



empirically formulates the vertical distribution of turbulence intensity:

TI(z) = . . . ( / ) ( ) . ( ∗ / ) (7) where the scaling parameter = 1 −/ . The D-H model has been widely

used in the wind engineering field to account the wind shear and fatigue loading particularly for tall buildings when the logarithmic law cannot model the wind speed profile over the SL.

3. LIDAR WIND PROFILER

3.1 Measurement of Lidar

Light Detection and Ranging (Lidar) is an advanced remote sensing technology to measure three dimensional wind velocities. The measurement principle is that the emitted laser beam in atmosphere, when encountering to the aerosols, the scattered light returns and detects by the receiver of the system. Because the aerosols move along with the atmospheric airflow relative to the beam direction, the received signal experiences the Doppler

frequency shift. The radial velocity, , in

the line-of-sight (LOS) is calculated from the relation: v = λΔ (8) where represents Doppler frequency

shift and represents the laser wavelength.

The pulsed Lidar employed in the present study is Leosphere Windcube v2

with = 1.543 μm in the near-infrared

range for the eye safety. Adopting Doppler beam swinging technique, the Windcube sequentially sent four beams with a cone-angle of 28o in four directions, north, east, south, and west, respectively and follows a vertical beam directed to zenith. The designation of the independently vertical beam improves the measurement accuracy of vertical velocities, which is in advantage of assessing the momentum flux (Mann et al., 2010). The orthogonal frame of the Windcube v2 is illustrated in Figure 1. The three dimensional velocity of component for u, v, and w velocity can be retrieved from the radial velocities described as follows: u = (9) v = (10) w = Vr (11) where , , , and represented the radial velocity directed to north, south, east, and west, and vertical direction. The wind speed, U, of the along-wind component and wind direction,

θ, are calculated using the following

transformation: U = √u + v (12) = tan v/u (13)

Fig.

Bthe radof horithe paiaspect,constrahomoggenerasea, hterrain

3.2 Li

Tof thepreviouIndustrChanginstrumregion was inm to observ

. 1 Orthogo

Because the dial velocityizontal veloirs of the v, the meaained in ageneity floally occurs ihowever, l

n. (Cariou an

idar calib

o assess the present Lusly conducry Park (2hua Cou

mental site wfacing the

nstalled on tha mast wit

vations were

onal frame di

Lidar direy and the twocities are rvelocities inasurement

assumption ow. The n a flat terralimited fornd Boquet, 2

bration

he measuremLidar, a cacted in Cha24.1072oN, unty, Tawas locatedTaiwan Strhe roof of ath 70 m ine carried ou

Wi

of the Winrection (Ca

ectly measuwo componeretrieved fron LOS. In t

technique of horizoncircumstan

ain or over r a comp2010)

ment accuraalibration wnghua Coas120.3828o

aiwan. Td in the coasrait. The Lida container, n height. T

ut once a we

ind Speed Profi

Journal

ndcube v2 uariou and B

ures ents om this

is ntal nce the lex

acy was stal oE), The stal dar 80

The eek

in 31DeLitheW70siginashexobstrbeHedirupwabeanmaof

iles of Typhoon

of Coastal and

used to inteBoquet, 201

each season, June 23 to

ecember 16dar measure ultrason

WXT520, ins0 m in hegnificant biaappropriate own in the d

xcluded forbservation rong monsoeen surrounence, those rection pa

pstream werake effect.etween 33o and 214 o, andake the com

f the site is r

Matmo Observ

d Ocean Engine

erpret the w10)

n for the peo 30, Septem6 to 22, rements wenic anemotalled on th

eight. It was in wind dinstallation

data of Septthe comparsite is we

oon in the wnded withmeasureme

assing the re filtered o

Only theand 56o, 112d 292 o and

mparison. Deferred to T

ved Using Dopp

eering, Vol. 17,

wind speed

eriods of Mamber 22 to respectively

ere compareometers, Vhe booms at was noted direction dun of the Lidtember, whirison. Beca

ell-known fwinter the mh wind tuents with the wind tout to preve wind dir2 o and 158

338 o were Detailed descTsai et al. (2

pler Lidar

No. 1 7

and

ar 24 to 29, and y. The ed with Vaisala 50 and that a

e to the dar was ich was

ause the for the

mast has urbines. he wind turbines vent the rections o, 191 o used to cription

2015)

督卜勒光

8 海洋

Fig. 2(b

Fig. 3(b

光達麥德姆颱風

洋工程學刊第

2 Comparisb) wind dir

3 Comparisb) wind dir

風風速剖面觀測

第十七卷第一

(a)

(c)

son betweerection (c) w

(a)

(c)

son betweerection (c) w

測

一期

en the Lidawind speed

en the Lidawind speed

(b)

(d)

ar and WXTd standard d

(b)

(d)

ar and WXTd standard d

T520 at 50 deviation (d

T520 at 50 deviation (d

m in heighd) turbulen

m in heighd) turbulen

ht (a) wind nce intensit

ht (a) wind nce intensit

speed ty.

speed ty.

Fig. 4o

Ficorreladirectiturbuleobservanemorespectshowninstrumspeed Also, gstandarthe turthe agrpresen

4. TYI

4.1 D

Twas dPhilipptravelli

4 Track of tof the Beau

igure 2 anation of the on, standence intevations of ometers at tively. Ver

n in the corrmental mea

and directgood consird deviationrbulence intreement sho

nt Lidar mea

YPHOOINSTRU

escription

The typhoondeveloped 2pine, in theing in north

typhoon Mutfort wind

nd 3 demhourly meadard devensity b

Lidar an50 and 70 ry good agrelation bet

asurements ion at the stency was n of the witensity. Theowed the acasurement.

ON MATUMENT

n of typho

n Matmo (M280 km eae Pacific Ohwest to no

Wi

Matmo; the d force scale

repre

monstrated tan wind speviation, aetween tnd ultrason

m in heiggreement wtween the twfor the wiboth heighgiven for t

ind speed ae indicationccuracy of t

TMO ANSITE

oon Matm

MAT, 20141ast of Chuucean in 20orth-northw

ind Speed Profi

Journal

circle of dae7; the timesenting 6 h

the eed, and the nic

ght, was two ind hts. the and n of the

ND

mo

10) uk, 14,

west

dirradscgrtypeathiCeincthema(TToIslAMChtheontheHatypap23theou

iles of Typhoon

of Coastal and

ash line repe interval bhours.

rection towdius, repreale 7, was adually inflphoon arriv

ast coast onis period, entre Weathcreased to te minimumade landfa

Taipei timeownship, Tland and enM 04:20 hanghua Coe observati

n July 23, Ae track ofarbour. Thphoon centr

pproximately3, AM 03:00e typhoon

uter vortex.

Matmo Observ

d Ocean Engine

presenting tbetween tw

wards Taiwesented the

approximafluenced theved the wa

n July 22, Paccording her Bureauthe maximu

m pressure oll on Julye, UTC+8aitung Countering the

in Shenounty. The on site of

AM 11:00. Ff MAT relhe shortest re to the oby 130 km 0. This indicwind was

ved Using Dopp

eering, Vol. 17,

the storm rwo open dot

wan. The e Beautfortately 200 ke Island whaters offshoPM 01:00.

to the repu, the windum of 38 mof 960 hPay 23, AM 8), in Chunty, crossie Taiwan Sngang Tow

storm radiHsingda H

Figure 4 illulated to H

distance bservation s

observed ocation show

measured

pler Lidar

No. 1 9

radius ts

storm t wind km and hen the ore the During

port of d speed m/s and a. MAT

00:10 hangbin ing the

Strait at wnship, ius left

Harbour ustrated Hsingda

of the site was on July

wed that at the

督卜勒光

10 海洋

F

4.2 Ind

InconducTaiwanthe ingeneraand approxsmall low-risapartmheight.small condenand scentre north. Alien, Mountfrom nland ohighesheight

Tbuildin


洋工程學刊第

Fig. 5 GeogrHarbou

nstrumentdata proc

n situ obscted at Hn. Figure 2 nstrumentalally flat, sur

fish farximately 1.5town locatse houses a

ments with . The outevillages an

nsed residensouthwest,

of Tainan 12 km towlocated in t

tain, which north to soutof the Taiwt mountainover 2000 m

he Lidar ng roof (22


第十七卷第一

raphic enviur and the

tal site ancessing

servation oHsingda Ha

displays thel site. Thrrounded byrms. Tow5 km is Taites in the wand scattereapproximat

er area disnd towns fontial areas a

respectivelwas 15 km

wards the easthe foothill longitudinath and occuwan Island

n is 60 km m.

was insta2.8757oN, 1

測

一期

ironment suinstallation

nd wind

of MAT warbour, soue geographyhe terrain y parks, farmwards wiwan Strait.west with ed middle-rtely 10 mstributes w

for which tare in the noly. The c

m away in tst is the towof the Cent

ally distribuupies two-thd. The loca

east with

alled on 120.2133oE)

urroundingn place of t

was uth

y of is

ms, west . A the rise

in with two orth city the wn, tral

utes hird ally the

the ) 8

m as we88anneairmosyflumaspcolowtwet resremal.stanem/TBsu

po

g the instruthe Lidar. ©

in height fshown in

ere observed8, 108, 128, nd 268 m inear the surfarflow inhereotion inducstem and

uctuations. ajor peaks, ectral ga

orrespondingwest level o

wo peaks (Val., 1996

sults were amove the m. (2013) conability undeeutral when /s. This criBL study tourface flow.

The leaower law wa

umental sit©2015 Goo

from the groFigure 5. T

d at twelve 148, 168, 1n height. Face, the priently compced by a

micro-scaThe spectrbetween w

ap at thg to 0.1-5 hof wind enerVon der Hov

). The preaveraged formicroscale flncluded thaer the typhthe wind s

itiera is useo ensure the

ast square as employed

te of Hsingdogle Inc.

ound near tThe wind plevels with

188, 208, 22For a typicaimary atmo

prises a largsynoptic w

ale of turum exhibi

which the sohe time

hour containrgy to separven, 1956;

resent obser 1 hour intefluctuations.at the atmohoon weathspeed exceeed for the e neutral st

curve usind to fit the ty

da

the port profiles 48, 68,

28, 248, al wind ospheric ge-scale weather urbulent its two o-called

scale ning the rate the Powell

ervation erval to . Tse et spheric

her was eded 10 present

tratified

ng the yphoon



wind profiles. The results showed that a single power exponent usually cannot well describe the shape of the full observation range. A simple two-layer model was developed to fit the power law in the upper and lower layer, respectively. To compare with the logarithmic law and D-H models, the surface parameters of the friction

velocity ∗ and roughness was calculated using the profile fitting method. Previous studies have confirmed that the logarithmic layer developed for a depth approximate to 100 m in the neutral stratification (Panofsky and Dutton, 1984). Hence, the wind speed measured at the three lowest levels at 40, 50, and 60 m were employed to fit the logarithmic

profile to determine the ∗ and . The

period between July 23, AM 01:00 and July 24, AM 00:00 showed the significant wind speed of MAT with the U48, where the subscribe denoted the observation height, close to or greater than 10 m/s were examined.

5. RESULTS AND DISCUSSION

The evolution of the hourly mean wind speed and direction in the process of MAT is demonstrated in Figure 6. The wind speed started to significantly increase on midday of July 22 when the storm radius touched the land, half day before the typhoon landfall. The maximum wind speed recorded was 24 m/s at the height of 268 m on July 23 AM 06:00 after MAT crossed the Central Mountain and arrived in the western coast while the distance

between the typhoon centre and observation site was shortest. The wind speed subsequently decreased when MAT progressively moved away and the wind pattern finally returned to the originally weather system. A considerable falling of the wind speed is observed on July 23, AM 11:00, which is the heavy rainfall caused phenomenon. Because of the naturally cyclonic typhoon wind, the wind direction reversed counterclockwise from the north-northwest on July 22, PM 23:00 to south-southeast on July 24, PM 14:00.

5.1 Wind speed profile

The vertical distribution of the mean wind speed profile is demonstrated in Figure 7 with the power law curving fitting. As expected for a conventional boundary layer, the wind speed profile generally shows that the wind speed monotonically increases with respect to height. However, it is noted that in the initial stage with relative weak wind speed between Figure 7(b) and 7(e), the wind speed appears not to increase and keep uniform in the upper layer between 148 and 188 m. This is in agreement with Amano et al. (1999), who observes a gradient height in the TBL near the surface. A particular case is g in Figure 7(k) with a reversed wind speed over 168 m in height, forming the profile of low level jet (LLJ) type. In contrast to the time series shown Figure 6 a significant falling and reduction of discrepancy of the wind speed between upper and lower layer is observed. It appeared that a local eddy occurs with a strong down burst flow.

督卜勒光

12 海洋

Fig. 6

Figfitting


洋工程學刊第

Evolution

g. 7 Observg; ; for


第十七卷第一

of the hori

ved hourly r the entire

low

測

一期

izontal wininv

mean wind12 levels o

wer layer;

nd speed (upvasion of M

d speed proof observati

; for th

pper) and dMAT.

ofiles on Juion betweenhe upper la

direction (l

ly 23 with tn 48 to 268 ayer.

lower) duri

the power l8 m; ; f

ing the

law for the



Table 1 Parameters of wind profiles for wind speed and turbulence intensity

Time Type U48

(m/s) Dir48

(deg) σU48 (m/s)

u*o

(m/s)zo (m)

α β

α12 αL αU zα (m) β12 βL βU zβ (m)

01:00 2 9.19 302 1.61 0.76 0.39 0.20 - - 248 -0.26 -0.13 -0.60 12802:00 3 8.95 280 1.60 0.87 0.79 0.18 0.21 0.07 128 -0.33 -0.30 -0.64 16803:00 3 10.95 268 1.78 1.08 0.84 0.17 0.21 0.03 128 -0.43 -0.29 -0.53 88 04:00 3 12.11 278 2.42 1.15 0.72 0.15 0.20 0.004 128 -0.36 -0.18 -0.64 10805:00 3 11.63 275 2.21 1.14 0.80 0.18 0.22 0.11 148 -0.20 -0.15 -0.30 14806:00 2 15.43 261 3.05 1.39 0.56 0.25 0.23 0.24 128 -0.29 -0.16 -0.43 10807:00 1 14.68 251 2.58 1.46 0.87 0.23 0.24 0.16 148 -0.39 -0.13 -0.62 88 08:00 2 16.84 223 2.09 1.25 0.22 0.18 0.19 0.15 148 -0.42 -0.14 -0.66 88 09:00 2 16.05 213 2.29 0.85 0.025 0.15 0.14 0.15 128 -0.35 -0.15 -0.82 12810:00 2 13.99 208 2.69 0.83 0.058 0.19 0.15 0.26 108 -0.27 -0.22 -0.45 10811:00 4 11.03 230 4.47 0.29 10-5 0.004 0.08 -0.40 148 -0.036 0.17 -1.07 14812:00 1 13.18 214 2.72 0.99 0.24 0.18 0.19 0.16 148 -0.43 -0.16 -0.91 10813:00 2 13.99 212 2.01 0.78 0.036 0.16 0.14 0.21 128 -0.14 -0.059 -0.51 14814:00 2 14.18 201 2.41 0.94 0.12 0.19 0.17 0.23 128 -0.29 -0.22 -0.47 12815:00 1 14.19 189 2.18 1.32 0.65 0.2 0.21 0.11 188 -0.49 -0.33 -0.95 12816:00 1 13.12 188 1.96 1.24 0.70 0.21 0.22 0.16 188 -0.35 -0.22 -0.50 88 17:00 1 14.05 190 2.37 1.34 0.72 0.21 0.21 0.15 188 -0.44 -0.32 -0.77 12818:00 1 13.80 189 2.14 1.37 0.86 0.21 0.22 0.13 168 -0.44 -0.35 -0.75 12819:00 1 13.78 187 2.08 1.28 0.65 0.19 0.20 0.14 148 -0.35 -0.26 -0.64 12820:00 1 13.19 181 2.15 1.18 0.55 0.19 0.21 0.14 148 -0.28 -0.19 -0.55 12821:00 3 12.66 181 2.05 1.24 0.82 0.19 0.21 0.14 128 -0.37 -0.33 -0.41 12822:00 1 11.86 181 1.82 1.17 0.83 0.21 0.22 0.18 148 -0.30 -0.23 -0.66 14823:00 3 11.17 185 1.87 1.16 1.01 0.22 0.23 0.10 168 -0.43 -0.24 -0.79 10800:00 3 9.70 186 1.74 1.07 1.26 0.20 0.23 0.12 128 -0.29 -0.25 -0.43 128

Subscribe 12, L, and U in the power exponent, α and β, denoting the entire, upper, and

lower layer fitting. zα and zβ representing the characteristic height for the wind speed

and turbulence intensity profile to separate the two layers.

The power law indicated that, a single

power exponent α12 fitted for the entire

height of the Lidar observation matched the observation only given in Figure 7(a), 7(h), 7(i), 7(l), and 7(v). Tse et al. (2013) remarked that a power law modeled the TBL up to 300 m in height. However, the observed wind profiles intrinsically demonstrated two layers. This is displayed in Figure 7 with the individual power exponent in the lower and upper layer,

characterized by the height of zα to

distinguish the two layers. Table 1 displays the basic parameters to represent the mean wind profile and the character height

manually determined for the wind speed and turbulence intensity profile. The velocity gradients in the lower layer, significantly influenced by surface friction, are usually greater than those in the upper layer. The opposite results are given in Figure 7(j), 7(m), and 7(n) with a relative weak surface friction velocity.

Typhoon observations to the height of

70 m from Choi (1978) showed that α was

between 0.19 and 0.26, which was slightly larger than the present observation between 0.15 and 0.25 for the entire layer and between 0.14 and 0.23 for the lower layer. The power exponents in the both

督卜勒光

14 海洋

studiesquotedindicathigher

Fiprofile

of /logaritsurfacelengths

Fig


洋工程學刊第

s are generad value of 0ted that thwind shear

igure 8 deme using the ∗ to com

thmic and De friction vs are listed

g. 8 Wind s/ ∗ to co


第十七卷第一

ally larger th0.14 on a flahe typhoonr.

monstrated thdimensionl

mpare with t

D-H model.velocities a

d in Table 1

speed profiompare wit

Log

測

一期

han the usuaat terrain. Tn generated

he wind speless parame

the theoreti

The obtainand roughn1. It has be

les on Julyth the theo

garithmic p

ally This d a

eed eter

ical

ned ness een

suaptyp

an(6tabgrexin Du

y 23 presentretical loga

profile;

uggested tpproximatesphoon wind

nd 400 m6 ) using th

ble 1. Theater than

xperienced nthe neutral

utton, 1984)

ted using tharithmic an

; D-H pro

that the to 10% o

d the SL dep

m calculate

he friction

he results a genera

not more thal stratificati).

he dimensiond D-H proofile.

depth oof ABL. Fpth is betwe

ed from 0velocity li

are signifral SL than 100 m inion (Panofs

onless scaleofile.

of SL For the een 200 0.1 ∗ /isted in

ficantly ickness

n height sky and

e of ;

(a)

Comparisoween the LL

1 profile at

Detailed inspthere are ned as fole strong wi

the va

ximation to agreed with nstrated in en 8(o) and ntum flux gn mechanimaintain a

uppresses thrcumstanceted using/(6f ). Typ

e shear as shen 8(h) and

momentuopment of th

of approximriolis force pper layer,

than the

on of (a) diLJ type prot PM 17:00

pection of Ffour typesllows. Typind shear ne

alue of

10, the entithe logarithFigure 8(

8(t), and 8(generated bsm transpolong constae Coriolis f, the depth

g the fo

pe 2, with a

hown in Figd 8(j), 8(m),um flux he logarithmmately 100 shows its scausing thlogarithmic

Wi

irectional dofile (Type 0; ; Type

Figure 8 shos of profipe 1, withear the surfaU /u∗ire observatihmic profile(g), 8(l) a(v). The stroby the surfaorts upwarant shear layforce effect.

of SL can formation

a relative we

gure 8(a), 8, and 8(n),

limits mic layer to

m. The effsignificancee wind spe

c profile. T

ind Speed Profi

Journal of

(b)

difference p4) with Typ2 profile a

03:00.

ows iles

h a face

in

ion e as and ong face rds, yer . In be of

eak

(f), the the the

fect e in eed The

D-disTytheof as 8(ucoob14he8(esuproSe

bounwiintdis

dif

are

iles of Typhoon

of Coastal and O

profile and pe 1, Type t PM 14:00

-H model vestribution oype 3, with e wind spee

f the logarithshown be

u), 8(w), onsistent wibserved up t48 m in heeight is notee). Type 4

urface frictiofile is ob

eptembers 2

As menoundary laynder the rapind speed.teresting pstributions

fference, Δθe examined

Matmo Observ

Ocean Engineer

(b) vertica2, and Typ

0 ; ; Type

ery well preof the horizthe relative ed turns to hmic profiletween Figuand 8(x).

ith the logto the heigh

eight. Particed in Figure4, with a sion velocitybserved in 3, AM 11:0

tioned abovyer (Type 4pid falling

To furthephenomeno

of the

θ=θ48-θz, an

and compa

ved Using Dopp

ring, Vol. 17, N

al velocity ppe 3 profilee 3 profile

edicted the vzontal wind weak windthe left-han

e in the uppeure 8(b) an. The degarithmic laht between cularly, a ge between 8significantlyty, the LL

n Figure 800.

ve, the LL4 profile) of the hor

er investigaon, the v

wind dire

nd vertical v

ared with th

pler Lidar

No. 1 15

profile e ; ; at AM

vertical speed.

d speed, nd side er layer

nd 8(e), pth in ayer is 128 to

gradient 8(c) and y small LJ type

(k) on

LJ type formed rizontal ate this vertical ectional

velocity

he other



three types of profiles in Figure 8(q) at PM 17:00 for Type 1, Figure 8(n) at PM 14:00 for Type 2, and Figure 8(c) at AM 03:00 for Type 3 as shown in Figure 9.

The LLJ type profile demonstrated considerable variation of 25o for the vertical discrepancy of wind direction between 48 to 268 m in height. Besides, the vertical velocity significantly moved downwards with the maximum of -1.34 m/s at 128 m in height. In contrast, for the other three types the directional differences were 6.2o, 3.57o, and 1.65o and the vertical velocities were 0.27, 0.4, and 0.11 m/s at 48 m in height for the Type 1, Type 2, and Type 3, which are significantly less than the LLJ type profile. Aitken et al. (2012) studied the rainfall effect on the Windcube Lidar measurement. They remarked that the observed horizontal wind speeds were not affected by rainfall. However, the Lidar observed terminal velocities of raindrops rather than the truly vertical velocity of the airflow. Hence, the significantly downward flow shown in Figure 9(b) represents the heavy rainfall condition. It is likely that the interaction of the atmospheric turbulence and droplets generated local vortex, producing a complex flow with considerable variation of the wind direction as explained in Figure 9(a).

5.2 Turbulence intensity profile

Turbulence intensity profiles were depicted in Figure 10. The turbulence intensity decreased with the increase of the height, generally varying between 15% and

20% at the height of 48 m. The logarithmic law, D-H formula, power law, the two-layer model using power law are employed to fit the observed profile of turbulence intensity as given in Figure 10. The turbulence intensity discrepancy calculated from both the logarithmic and D-H model are insignificant, however, usually greater than the observation. Reasonable agreement between the D-H and observed profiles is shown in Figure 10(j), 10(m), and 10(n), for which the wind speed profile also agrees with the D-H predictions. The power law for the entire observation height does not well fit the mean profile. In analogous to the boundary layer of wind speed, there also exists two layers with the different power exponent in the upper and lower layer. The power

exponent considerably varied with β12

between -0.14 and -0.43, βL between -0.13

and -0.35, and βU between -0.41 and -1.07

in the typhoon process of MAT. The turbulence decay rate in the upper layer is significantly larger than the lower layer.

The characteristic height zβ is between 88

to 148 m in height. Apart from the heavy rainfall condition, there appears in lack of direct relation between the wind speed and turbulence intensity profile. Nevertheless, the current data demonstrates that for Type 1 profile of the entirely logarithmic layer the decay of the turbulence intensity with respect to height is faster than other two types of profiles. In the typhoon turbulence study of Choi (1979), the power exponent

showed β=-0.31. The long-term mean

values in the present study give β12=-0.34,

βL=-0.21, and βU=-0.56 through averaging

the hoexpone

Figco

Foconditifluctua168 mdeviatimeasurobservavailab268 m.

ourly valuesent in th

. 10 Lidar ompared wexponent, a

or the partiion of Figuations incre

m with a sigion as showrement un

ved considebility from . Hence, the

s in Table he lower

observationwith logaritand two-lay

icular case ure 10(k),

eases with gnificantly lwn in Tablender the herable redu50% at 48

e raindrops c

Wi

1. The powlayer w

n of hourlyhmic law, Dyer model;

in the rainfthe turbulheight bel

large standae 1. The Lidheavy rainfuction of d

m to 15%causes a low

ind Speed Profi

Journal of

wer with

coest

y mean turbD-H model; line styles

fall lent low ard dar fall

data % at wer

fremeinf

usfordis

iles of Typhoon

of Coastal and O

omparable tablishes a s

bulence intl, power laware explain

equency easurementfluence requ

6. C

The typing the Drmation ostribution

Matmo Observ

Ocean Engineer

height tosignificant s

tensity profw with the ned in Figu

response. accuracy o

uired further

CONCLU

hoon MatmDoppler Lid

f the TBof turbu

ved Using Dopp

ring, Vol. 17, N

o Choi smaller valu

files on Julsignle pow

ure 8 and 9

Whetherof turbulenr study.

USIONS

mo was obdar to stuBL and vulence in

pler Lidar

No. 1 17

(1978) ue.

y 23 wer 9.

r the nce was

S

bserved dy the vertical

ntensity.



Generally, the power law with a single power exponent cannot well model the growth of the wind speed with respect to height between 48 and 268 m. The simple two layers distinguished in the upper and lower layer with the different power exponent appropriately fits the wind profile. This two layer phenomenon is also observed in the profile of turbulence intensity with a more rapid decay rate in the upper layer. However, the present data appears not to observe a clear relation between the wind speed and turbulence intensity profile. In discussion the TBL using the dimensionless wind speed U/u*o, four types of the profiles are observed in the typhoon process of MAT. Type 1 shows the consistent with logarithmic profile for the entire observation layer under a relative strong wind shear. Type 2 reveals the significant effect of Coriolis force over SL and well modeled using the D-H profile under a weak surface friction velocity. Type 3 forms a gradient height under a relatively weak wind speed. Type 4 is a LLJ type profile occurred in the rainfall condition.

Finally, the detailed information of the TBL and turbulence intensity concluded in this study can widespread be used to account the wind shear loading of typhoons on tall structures. Particularly, for wind turbines the ICE standard (ICE 61400-3 2005) prescribes to use either the power law or logarithmic profile as wind shear model may not be completely appropriate for typhoon winds.

ACKNOWLEDGEMENTS

The authors wish to express their acknowledgement to Ministry of Science and Technology (MOST) to support and founding this research.

REFERENCES

Aitken, M. L., Rhodes, M. E., and Lundquist, J. K. (2012) “Performance of a wind-profiling lidar in the region of wind turbine rotor disks,” J. Atmo. Oceanic Tech., Vol. 29, pp. 347-354.

Amano, T., Fukushima, H., Ohkuma, T., Kawaguchi, A., and Goto, S. (1999) “The observation of typhoon winds in Okinawa by Doppler sodar,” J Wind. Eng. Ind. Aerodyn., Vol. 83, pp. 11-20.

Cariou J. P., and Boquet M. (2010) Leosphere

Pulsed Lidar Principles: Contribution to UpWind WP6 on Remote Sensing devices, pp. 1-32.

Choi, E. C. C. (1978) “Characteristics of typhoons over the south China Sea,” J. Wind Eng. Ind. Aerodyn., Vol. 3, pp. 353-365.

Chou, J. S., Chiu, C. K., Huang, I. K., and Chi, K. N. (2013) “Failure analysis of wind turbine blade under critical wind loads,” Eng. Failure Analysis, Vol. 27, pp.99-118.

Cook, N. J. (1997) “The Deaves and Harris ABL model applied to heterogeneous terrain,” J. Wind Eng. Ind. Aerodyn., Vol. 66, pp. 197-214.

Hui, M. C. H., Larsen, A., Xiang, H. F. (2009) “Wind turbulence characteristics study at the Stonecutters Bridge site: Part I-Mean wind and turbulence intensities,” J Wind. Eng. Ind. Aerodyn., Vol. 97, pp. 22-36.



IEC 61400-3 (2005) Ed. 3, Wind turbines- part 1:

Design requirements, International IEC 61400-1 Electrotechnical Commission (IEC), Geneve, Switzerland.

Ishihara, T., Yamaguchi, A., Takahara, K., Mekaru, T., and Matsuura, S. (2005) “An Analysis of Damaged Wind Turbines by Typhoon Maemi in 2003,” The Sixth

Asia-Pacific Conference on Wind Engineering, pp. 1413-1428, Seoul, South Korea.

Ishizaki, H. (1983) “Wind profiles, turbulence intensities and gust factors for design in typhoon-prone regions,” J. Wind Eng. Ind. Aerodyn., Vol. 13, pp. 55-66.

Mann J., Pena, A., Bingol, F., Wagner, R., and Courtney, M. S. (2010) “Lidar scanning of momentum flux in and above the atmospheric surface layer,” J. Atmo. Oceanic Tech., Vol. 27, pp. 959-976.

Panofsky, H. A. and Dutton, J. A. (1984)

Atmospheric turbulence: models and methods for engineering applications, John Wiley & Sons, New York.

Powell, M. D., Houston, S. H., and Reinhold, T. A. (1996) “Hurricane Andrew’s landfall in south Florida, Part I: measurements for documentation of surface wind fields,” Wea. Forecasting, Vol. 11, pp. 304-328

Song, L., Chen, W., Wang, B., Zhi, S., and Liu, A. (2016) “Characteristics of wind profiles in the

landfalling typhoon boundary layer,” J. Wind Eng. Ind. Aerodyn., Vol. 149, pp. 77-88.

Tamura, Y., Iwatani, Y., Hibi, K., Suda, K., Nakamura, O., Maruyama, T., and Ishibashi, R. (2007) “Profiles of mean wind speeds and vertical turbulence intensities measured at seashore and two inland sites using Doppler sodars,” J. Wind Eng. Ind. Aerodyn., Vol. 95, pp. 411-427.

Tsai, Y. S., Lin, P. H., Yang, Y. C., Chen, J. L. (2015) “Lidar observation of surface wind profiles in Changhua Coastal Industrial Park,”

Proceedings of Central Weather Bureau 2015 Conference on Weather Analysis and Forecasting, Taipei, Taiwan.

Tse, K. T., Li, S. W., Chan, P. W., Mok, H. Y., and Weerasuriya, A. U. (2013) “Wind profile observations in tropical cyclone events using wind-profilers and doppler SODARs,” J. Wind Eng. Ind. Aerodyn., Vol. 115, pp. 93-103.

Vickery, P. J., Wadhera, D., Powell, M. D., and Chen, Y. (2009) “A hurricane boundary layer and wind field model for use in engineering applications,” J. Applied Meteo. Climat., Vol. 48, pp. 381-405.

Von der Hoven (1956) “Power spectrum of horizontal wind speed in the frequency range from 0.0007 to 900 cycles per hour,” J. Meteorol., Vol. 14, pp. 160–164



Manuscript Received: Apr. 25, 2017Revision Received: May. 24, 2017

and Accepted: May. 24, 2017

d speed profiles of typhoon matmo observed u sing doppler...

Documents