A subsurface chlorophyll a bloom induced by typhoon in the South China Sea

H.J. Ye a,b, Y. Sui c, D.L. Tang a,b,⁎, Y.D. Afanasyev c

a Research Center for Remote Sensing and Marine Ecology & Environment, State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of

Sciences, Guangzhou, Chinab Graduate University of the Chinese Academy of Sciences, Beijing, Chinac Department of Physics & Physical Oceanography, Memorial University, Newfoundland, Canada

a b s t r a c ta r t i c l e i n f o

Article history:

Received 8 February 2013

Received in revised form 18 April 2013

Accepted 22 April 2013

Available online xxxx

Keywords:

Subsurface

Chlorophyll a bloom

Typhoon

South China Sea

Previous studies showed that typhoons often induce chlorophyll a (Chl-a) blooms in the surface waters. This

paper shows that Chl-a blooms can occur not only on the surface but also in the interior just above the ther-

mocline after the passage of a typhoon. We used satellite and cruise survey data to analyze physical and

biological characteristics in the South China Sea after the passage of the typhoon Nuri in August 2008. This

paper shows that a subsurface (20 to 100 m depth) Chl-a bloom (1.31 ± 0.47 mg m−3) occurred and lasted

for three weeks, stronger and longer than the surface Chl-a bloom (0.48 ± 0.23 mg m−3). The maximum

value of Chl-a of 2.10 mg m−3 was detected at 50 m depth. This value was approximately 4–5 times higher

than the background value of 0.48 mg m−3 measured at non blooming areas at the same time and about 7.5

times higher than the mean Chl-a value of 0.28 ± 0.13 mg m−3 measured over the period of five years. The

mixed layer depth and the thickness of the Chl-a bloom increased after the typhoon. Our analysis clearly

shows that a subsurface upwelling caused by the passage of the typhoon, transported nutrients to the eupho-

tic zone and supported the Chl-a bloom. These observations provide some insight on the effect of typhoons

on marine ecosystems, especially as related to the Integrated Primary Production.

© 2013 Elsevier B.V. All rights reserved.

1. Introduction

Recently, subsurface chlorophyll has received a lot of attention in

modeling studies as well as in primary production studies because

of its significant contribution to ecology (Fennel and Boss, 2003; Lu

et al., 2010; Perry et al., 2008; Sarma and Aswanikumar, 1991). As a

result of physical processes occurring on different time scales (Price,

1981; Tang et al., 2004a,b; Wang et al., 2010), nutrients are pumped

from the deep waters of the ocean to the surface and subsurface where

they initiate a sequence of biological processes. In the open ocean, the

subsurface chlorophyll maximum depth remains relatively stable. In the

nearshore waters, the subsurface chlorophyll maximum shoals and

weakens when the surface layer is affected by river discharges (Lu et al.,

2010). In the northern part of the South China Sea (SCS), the depth

where the maximum value of chlorophyll a (Chl-a) concentration is ob-

served is lowest (20–30 m) in the winter, intermediate in May and is

the deepest (50–90 m) in other months (Chen et al., 2006).

Recent studies showed that typhoons, hurricanes or tropical cy-

clones can cause significant increase of Chl-a concentration in surface

waters. A tropical cyclone “Kai-Tak” triggered a 30 fold increase in the

surface Chl-a concentration in the SCS in 2000 (Lin, 2003). Other

examples where the increase of Chl-a concentration was observed

offshore include typhoons “Damrey” in 2005 (Zheng and Tang, 2007)

and Nuri in 2008 (Zhao et al., 2009). In 2007, typhoon “Hagibis” caused

a notable effect on Chl-a concentrationswith the forcing timemuch lon-

ger than the geostrophic adjustment time in themiddle of the SCS (Sun

et al., 2010). Tropical cyclone “Linfa” in 2009 triggered an eddy-like

Chl-a bloom (Walker et al., 2005). Typhoon “Morakot” changed the

diatom abundance and species composition due to strong winds and

caused nutrient entrainment from upwelling and nutrient-enriched

floodwaters (Chung et al., 2012). In the above studies the surface

Chl-a blooms were detected using satellite data for surface Chl-a.

Typhoons also affect particulate organic carbon flux in subsurface

waters (Chen et al., 2009; Hung et al., 2010), suspended matter

concentration, re-suspension and terrestrial runoff, entrainment of

riverine-mixing, Integrated Primary Production (IPP), (Chen et al.,

2009; Gautam et al., 2005; Hung et al., 2010; Kundu et al., 2001;

Shiah et al., 2000) and fish abundance (Yu et al., 2013). However,

Shiah et al. (2000)mentioned that the spatial and temporal variation

patterns of Chl-a were quite heterogeneous, and that a detailed in-

formation on Chl-a variations in the subsurface was lacking. There

clearly remains a certain lack of information on subsurface phytoplank-

ton, on the occurrence of blooms in subsurfacewaters and on themech-

anisms of blooming. In August 2008, the typhoon Nuri passed over the

northern part of SCS and provided us with an opportunity to study bio-

logical and physical changes in the subsurfacewaters. Several days after

the passage of Nuri, a research cruise was conducted to obtain in situ

Journal of Marine Systems xxx (2013) xxx–xxx

⁎ Corresponding author at: Research Center for Remote Sensing and Marine Ecology

& Environment, State Key Laboratory of Tropical Oceanography, South China Sea Insti-

tute of Oceanology, Chinese Academy of Sciences, Guangzhou, China.

E-mail address: Lingzistdl@126.com (D.L. Tang).

MARSYS-02361; No of Pages 8

0924-7963/$ – see front matter © 2013 Elsevier B.V. All rights reserved.

http://dx.doi.org/10.1016/j.jmarsys.2013.04.010

Contents lists available at SciVerse ScienceDirect

Journal of Marine Systems

j ourna l homepage: www.e lsev ie r .com/ locate / jmarsys

Please cite this article as: Ye, H.J., et al., A subsurface chlorophyll a bloom induced by typhoon in the South China Sea, J. Mar. Syst. (2013), http://dx.doi.org/10.1016/j.jmarsys.2013.04.010

data in this region. The results documented a subsurface Chl-a bloom

that lasted for a long time even after the surface Chl-a bloom has

disappeared.

2. Data and methods

2.1. Study area

The northwest Pacific is the region with the most numerous and

violent typhoons in the world (Fumin et al., 2002), and the SCS is

the largest semi-enclosed marginal sea in the northwest Pacific with

an area of about 3.5 × 106 km2 (Fig. 1). On average more than 10 ty-

phoons pass through this region annually, and the typhoon tracks are

mostly in the westward direction over the northern SCS (Elsner and

Liu, 2003; Wu et al., 2005; Zheng and Tang, 2007). Compared with

other ocean ecosystems, the summer SCS is notable for its shallow

Mixed Layer Depth (MLD) which is typically less than 50 m (Chen

et al., 2006; Karl and Lukas, 1996). During the summer season, the

northern SCS shows generally stratified and oligotrophic conditions

(Chen et al., 2003).

2.2. In situ data

In situ data of Chl-a, temperature and salinity were measured at

14 stations (Fig. 1) during a Research Cruise of the South China Sea

Institute of Oceanology, Chinese Academy of Science from 18 August

to the 6 September 2008 after typhoon Nuri (Table 1). 1–2 L water

samples from five depths (0, 25, 50, 75, 100 m) were collected at

each station in order to measure the Chl-a concentrations. Sea

water was filtered through a GF/F filter (Whatman, 25 mm) and

the filter paper was wrapped in aluminum foil and stored at temper-

ature−20 °C pending analysis. Chl-a concentration was determined

by fluorescence with a Turner Design 10 fluorometer following the

equations given by Parsons et al. (1984). Temperature and salinity

data were obtained by a Conductivity–Temperature–Depth probe.

The MLD was determined based on a 0.125 unit potential density

criterion (Levitus, 1982). In order to obtain information about mean

MLD in previous years we used CTD data obtained in cruises conducted

in 2004, 2005, 2006, and 2007 (Table 2). Vertical profiles of Chl-a,

temperature and salinity were obtained along the Transect North (TN)

(Stations 2–9) and the Transect South (TS) (Stations 10–13) (Fig. 1).

Relevant published information on Chl-a concentration in the SCS was

used in this study and is summarized in Table 3.

2.3. Typhoon track

The typhoon Nuri track, based on the best track data issued by the

Joint Typhoon Warning Center (JTWC), was obtained from the Unisys

Weather Web (http://weather.unisys.com/hurricane/w_pacific/

index.html). The information such as typhoon center locations, central

pressure and Maximum Sustained Wind (MSW) was gathered every

17

19

21

23 S

E

PRE

Hainan Island

14

13

1

2

12 11

84 6

AUG/21/00AUG/20/00

9

10

AUG/22/00

ChinaN

Luzon Island

Tai Wan

15

109 112 115 118 121 124° E

753

B

AB Pacific

Ocean

South China SeaIndian

Ocean

TN

TS

90

80

70

60

50

40

30

20

100

MSW

(Knots)

Central

Press

(hPa)

944

952

960

968

976

984

992

1000

1008

Typhoon Nuri

25°N

Fig. 1. (A) Location of the South China Sea. (B) Study area (Box S) and the track of typhoon Nuri. The typhoon center positions for every 6 h are indicated by the colored circles. The

circle color and size represent the central pressure [hPa] and the maximum sustained wind speeds [MSW, knots, 1 knot = 0.514 m s−1], respectively. Box E is typhoon effect area

(1.46 × 105 km2; clockwise from the top, 116°W–22.5 °N, 119.5 °W–20.5 °N, 118.5 °W–18.5 °N and 115 °W–20.5 °N); TN: Transect North (Stations 2–9); TS: Transect South

(Stations 10–13); PRE: Pearl River Estuary; the black triangle: Dongsha Island. All times are in Coordinated Universal Time (UTC). (For interpretation of the references to

color in this figure legend, the reader is referred to the web version of this article.)

Table 1

Information on in situ measurements at different stations in the SCS during 2008.

Station Station locations Date/time

1 114.00 °E, 21.00 °N 0248 Sep 6

2 114.50 °E, 20.50 °N 2041 Sep 5

3 115.00 °E, 20.50 °N 2045 Sep 5

4 115.50 °E, 20.50 °N 1623 Sep 5

5 116.00 °E, 20.50 °N 1255 Sep 5

6 116.50 °E, 20.50 °N 0830 Sep 5

7 117.00 °E, 20.50 °N 0615 Sep 5

8 117.50 °E, 20.50 °N 0215 Sep 5

9 120.00 °E, 20.50 °N 2033Aug 18

10 120.00 °E, 20.00 °N 0033Aug 19

11 117.00 °E, 20.00 °N 1519 Sep 4

12 116.00 °E, 20.00 °N 1326 Sep 3

13 115.00 °E, 20.00 °N 0541 Sep 3

14 116.00 °E, 19.00 °N 0305 Sep 2

2 H.J. Ye et al. / Journal of Marine Systems xxx (2013) xxx–xxx

Please cite this article as: Ye, H.J., et al., A subsurface chlorophyll a bloom induced by typhoon in the South China Sea, J. Mar. Syst. (2013), http://dx.doi.org/10.1016/j.jmarsys.2013.04.010

6 h. The translation speed of the typhoonwas estimated using the posi-

tions of its center recorded every 6 h. TheMSWand the central pressure

of the typhoon are shown in Fig. 1.

2.4. Satellite data

The daily, merged 8 day Chl-a concentration and sea surface tem-

perature (SST) data Level 3, with a spatial resolution of 4 km, from the

ocean color sensor Moderate Resolution Imaging Spectroradiometer

(MODIS) were obtained from the Distributed Active Archive Center

(DAAC) of the US National Aeronautics and Space Administration

(NASA) (http://oceancolor.gsfc.nasa.gov/cgi/l3). Sea level anomaly

(SLA) data gathered from the TOPEX/Poseidon and JASON altime-

ters (http://www.aviso.oceanobs.com/) was used to analyze surface

circulations.

The microwave scatterometer SeaWinds (QuikScat) data (http://

www.remss.com) was used to obtain wind vectors at the sea surface

for the periods before, during and after typhoon Nuri. The wind field

data allows us to estimate wind stress τ→

on the ocean surface using

the conventional formula:

τ→

¼ ρaCDjU→

10jU→

10; ð1Þ

where ρa is the density of air and U→

10 is wind vector, and the drag co-

efficient CD (Jarosz et al., 2007), is expressed as:

CD ¼ 2:229þ 0:2983 U10−0:00468 U210

� �

� 10−3

: ð2Þ

In order to estimate the rate of exchange between the deep layers

and the top layer we calculated the Ekman pumping velocity WE as

follows:

WE ¼ curl τ→

=ρf� �

; ð3Þ

where ρ is the density of seawater and f is the Coriolis parameter.

Thermocline displacement Δη due to a typhoon can be estimated

using the formula given by

Δη ¼τ→

= ρf Utð Þ; ð4Þ

(Price et al., 1994) where Ut is the translation speed of the typhoon.

Alternatively, the thermocline displacement can be estimated from

the SLA data. Assuming purely baroclinic response such that the ther-

mocline displacement compensates for the surface displacement and

is of opposite sign, we have a simple relation

Δηg0¼ −gΔh ð5Þ

(Shay et al., 2000) where g′ = gΔρ/ρ is the reduced gravity, Δρ is the

density difference between the upper and lower layers and Δh is the

SLA. The thermocline displacement is then

Δη ¼ −Δhρ=Δρ: ð6Þ

3. Results

3.1. Surface Chl-a bloom during typhoon Nuri in the SCS

Nuri (2008) was a Category 2 (based on Saffir-Simpson scale) ty-

phoon that impacted a wide area from Luzon Strait to Pearl River

Estuary. It was developed as a tropical depression in the northern

Pacific, and strengthened to a typhoon status on the 18 August 2008.

The typhoon migrated towards the northwest, as its center passed

through the DongSha Island on the 21 August 2008 and then moved

northwest towards PRE (Fig. 1). Before the typhoon, on the 9–16 August

2008 the wind in the northern SCS was weak (~7 m s−1) (Fig. 2Aa).

During the passage of Nuri the winds were strong, in excess of

30 m s−1 (Fig. 2Ab). After the typhoon, the wind speed returned to a

low value of approximately 5 m s−1 (Fig. 2Ac). According to the

JTWC, the maximum sustained winds reached 51 m s−1 on the 20

August in the Luzon Strait. In the study area, the average wind

speed was 35 m s−1 from 1800 UTC on the 20 August to 0000 UTC

on the 22 August. In the same period the translation speed of the ty-

phoon was Ut = 4.2 m s−1. Although Nuri was a weak, fast moving

typhoon, a heavy rain brought by Nuri led to a significant direct eco-

nomic impact of about ¥400 million (http://finance.sina.com.cn/

roll/20080827/09172394980.shtml).

In the period of 12–19 August before Nuri's passage, the map of

SST shows that the study area was dominated by warm water with

SST exceeding 29 °C (Fig. 2Ba). The SST map obtained during the

passage of Nuri demonstrates that a significant cooling occurred

along the track of the typhoon with ΔSST = −2.0 °C, approximately

(Table 4). The lateral extent of the low SST patch was approximately

100 km. The low temperature patch persisted for about two weeks

after the passage of Nuri (Fig. 2Bc). It is interesting to note a clear

rightward bias of in ΔSST distribution. The low SST patch was located

mainly to the right of the typhoon track such that its centerline was

shifted by approximately 50 km from the track. The rightward bias

was observed previously by many authors (Fedorov et al., 1979;

Sanford et al., 1987) and was discussed by Price (1981), Greatbatch

(1983) and Price et al. (1994). The bias occurs because of the effective

coupling between the wind stress of the moving typhoon and the

upper ocean inertial current. The current turns to the right and so does

the wind stress on the right hand side of the track. This causes a positive

feedback on the current. As a result the currents are stronger to the right

of the track. Surface horizontal divergence and hence the pumping of

cold water to the surface in this area become stronger as well.

The sea surface Chl-a concentrations were significantly enhanced

after Nuri's passage. Pre-typhoon Chl-a concentration was in the range

from 0.09 to 0.10 mg m−3 (Fig. 2Ca). The concentration increased up

Table 2

The mixed layer depth (MLD) in our study area at different sampling years.

(Aug–Sep) Year Number of observations MLD (m)

2004 10 30.5 ± 7.58

2005 6 36.0 ± 7.59

2006 7 41.4 ± 17.54

2007 4 33.5 ± 3.11

2008 10 63.0 ± 9.49

Values were presented as mean ± standard deviation.

Table 3

The number of Chl-a data in our study area and data sources.

Date Number of

observations

Data was obtained

within 15 days after

typhoon passed

Sources

12 Jun–7 Jul, 1998 2 No Ning et al. (2005)

Sep, 1998 1 No Chen et al. (2006)

14–18 Sep, 1998 3 No Liu et al. (2002)

18–20 Sep, 2004 6 No Present study

6–7 Sep, 2005 2 No He et al. (2009)

14 Aug, 2007 1 No Liu et al. (2009)

2–6 Sep, 2008 5 Yes (12–16 days) Present study

16–17 Sep, 2010 4 No Present study

3H.J. Ye et al. / Journal of Marine Systems xxx (2013) xxx–xxx

Please cite this article as: Ye, H.J., et al., A subsurface chlorophyll a bloom induced by typhoon in the South China Sea, J. Mar. Syst. (2013), http://dx.doi.org/10.1016/j.jmarsys.2013.04.010

to 0.24 mg m−3 two days later and up to 0.50 mg m−3 four days later.

However, only one week after the passage of the typhoon the Chl-a

concentration on the surface returned to its pre-typhoon value of

0.11 mg m−3 (Fig. 2Cc). Further note that the patch of enhanced

Chl-a concentration approximately coincided with the low SST patch

(compare Fig. 2Bb and Cb). This suggests that the enhanced Chl-a

concentration was due to the introduction of nutrients from the deeper

waters accompany with cool SST.

The comparison of the SLA images before and immediately after

the typhoon (Fig. 2Da andDb) shows a depression of the surface centered

at the latitude of approximately 20.5 °N. Associated with this depression,

the cyclonic cold eddy persisted for almost three weeks (Fig. 2Dc).

3.2. Variations of hydrographic conditions

The changes of physical hydrography in the upper ocean were ex-

amined using temperature and salinity measured at 14 stations in the

period of 12 to 16 days after the typhoon (Fig. 3). The results showed

that the highest temperature and the lowest salinity occurred at sea

surface as one might expect. A peak in isolines of temperature and sa-

linity centered at Station 7 indicates a region of upwelling. Compared

with surrounding stations, this region is associated with a sharp drop

of temperature by 3–4 °C and increase in salinity by approximately

0.2 psu between 60 m and 120 m depth. A region of equally strong

downwelling was observed at Station 5. We will discuss the physical

mechanism of this phenomenon in Section 4. The greatest tempera-

ture and salinity change occurred at the 60 m depth. The sharp drop

of temperature and sharp rise of salinity indicated that the typhoon

has induced a subsurface upwelling. The upwelling lifted deeper

water from approximately 140 m to 20 m depth and was sustained

for at least 16 days before returning to the normal climatology level.

The MLD in this region is typically about 35 m at this time of year

as data from previous years indicates (Table 2). Station 2, located at

the extreme left of the typhoon track where the influence of typhoon

Chl-a

a. 12-19 Aug b. 20-27 Aug

18

20

22

c. 27 Aug 10

1

0.1

0.01

SS

T

a. 12-19 Aug c. 28 Aug-4 Sepb. 20-27 Aug30.5

24.5

26.5

28.5

SS

T (

oC

)

18

20

22

a. 14-20 Aug b. 28 Aug-3 Sep c. 4-10 Sep

SL

A (

cm

)

30

10

20

0

-10

SLA

18

20

22

c. 24-30 Auga. 10-16 Aug b. 21 Aug30

0

10

20W

ind S

peed

18

20

22

Before typhoon During typhoon After typhoon

A

B

C

D

-

-

116114 118 120 116114 118 120 116114 118 120

Win

d S

pe

ed

(m

s-1

)C

hl-

a (

m m

g-3

)

25°N

25°N

25°N

25°N

122°E

Fig. 2. Optical and biological responses of the ocean to the passage of typhoon Nuri. (A) QuikScat wind-vector fields, (B) sea surface temperature, (C) MODIS-derived ocean color

products for Chl-a concentration, (D) sea level anomaly from AVISO. Rectangles in panels Bb, Cb, Db and Dc indicate the study area. Red crosses show the track of typhoon Nuri in

panel Bb. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Table 4

Comparisons of environmental variables between surface and subsurface and the potential mechanism induced by Nuri.

Variables Nuri induced Chl-a (mg m–3) Climatology Chl-a (mg m–3) Tem change (°C)

Maximum Mean Lasted time Bloom size (105 km2) Maximum Mean Maximum Mean

Surface 1.10a 0.48 ± 0.23a 1 week 0.60a,b (Chl-a ≥ 0.50 mg m−3) 0.20c 0.10 ± 0.07c 3.40a 1.70a

subsurface 2.10c 1.31 ± 0.47c ~3 weeks 1.00b,c (Chl-a ≥ 1.00 mg m−3) 1.00c 0.28 ± 0.13c 3.50c 2.00c

Mechanism Short-lasting vertical mixing and long-lasting subsurface upwelling

a Remote sensing data.b Bloom size calculated from Figs. 2Cb and 4c.c In situ data.

4 H.J. Ye et al. / Journal of Marine Systems xxx (2013) xxx–xxx

Please cite this article as: Ye, H.J., et al., A subsurface chlorophyll a bloom induced by typhoon in the South China Sea, J. Mar. Syst. (2013), http://dx.doi.org/10.1016/j.jmarsys.2013.04.010

was minimal, shows a similar value of approximately 40 m. However

in the area affected by the mixing induced by the typhoon, the mean

MLD increased significantly to approximately 70 m.

3.3. Subsurface Chl-a bloom after the typhoon Nuri

The Chl-a concentration at the sea surface returned to the normal

climatology level after about two weeks after the Nuri's passage

(Fig. 4A and B). However, high subsurface Chl-a concentrations

with average value of 1.31 ± 0.47 mg m−3 at 50 m depth were ob-

served in the vicinity of the Nuri's track (Fig. 4C, D, E and Table 4).

The maximum Chl-a value of 2.10 mg m−3 (Fig. 4C, D and Table 4)

was observed at 50 m depth (Station 8). The maximum Chl-a value

at the stations away from the typhoon track (Stations 1, 2, 13 and 14)

was less than 0.60 mg m−3. Vertically, the Chl-a values decreased

sharply in both upward and downward directions away from the

A Tem0

40

80

120

160

200

Depth

(m

)

92 3 4 5 6 7 8

Station

33.5

33.4

33.3

33.2

33.9

33.8

33.7

33.6

34.3

34.2

34.1

34.0

34.7

34.6

34.5

34.4

27

28

29

30

23

24

25

26

19

20

21

22

15

16

17

18

Psu

N

14 16 18 20 22 24 26 28 30

Station 8 (2008)

33.6 33.6 34.2 34.5 34.8

Tem Sal

C

Temperature(OC)

Salinity (Psu)

B Sal

Station

92 3 4 5 6 7 8

depth

(m

)

0

40

80

120

160

200

D Sampling stations along TN

113 115 117 119 121E

18

20

22

8TN 92

OC

Fig. 3. Vertical distribution of temperature (A) and salinity (B) in the upper 200 m at the TN Transect North, with contour intervals of 1 °C and 0.10 Psu, respectively. Temperature

(black) and salinity (red) profiles after Nuri's passage (C). The circles on the top of (A) and (B) indicate Nuri's track. The black rectangles show the area where decrease in temper-

ature or increase in salinity is observed. (D) Sampling locations along the transect TN. (For interpretation of the references to color in this figure legend, the reader is referred to the

web version of this article.)

Chl-a (mg m-3)

0.4 0.8 1.2 1.6 2.00.0

17

19

21

23°N

A MODIS chl-a (Sep 2-6)

1112

E Chl-a inTransect TS

2

D Chl-a in Transect TN

0

20

40

60

80

100

depth

(m

)

4 6 8Station Station13111 117 119°E

17

19

21

113 115

C Chl-a at 50 m depth (Sep 2-6)

TN

TS

17

19

21

B Chl-a on surface (Sep 2-6)

TN

TS

23°N

23°N

TNTS

Fig. 4. The Chl-a contours at the surface (A, B) and at 50 m (C) depth after Nuri's passage. The vertical distribution of Chl-a at the transect TN (Stations 2, 4, 6 and 8) (D) and the

transect TS (Stations 11–13) (E) after Nuri's passage. The black circles on top of (D) and (E) indicate the locations of typhoon Nuri. The black triangle indicates the Dongsha Island.

5H.J. Ye et al. / Journal of Marine Systems xxx (2013) xxx–xxx

Please cite this article as: Ye, H.J., et al., A subsurface chlorophyll a bloom induced by typhoon in the South China Sea, J. Mar. Syst. (2013), http://dx.doi.org/10.1016/j.jmarsys.2013.04.010

subsurface chlorophyll maximum layer at 50 m (Fig. 4D and E). The en-

hanced subsurface Chl-a concentration was observed 12–16 days after

Nuri's passage though its duration may have been longer.

Fig. 5A shows typical climatological profiles of Chl-a concentration

in the open sea. The profiles were calculated using the data given by Liu

et al. (2002), Ning et al. (2005), Chen et al. (2006), He et al. (2009), Liu

et al. (2009), and Lu et al. (2010) and from the present study. The

concentration is typically low at the surface and increases slowly with

depth until it reaches maximum somewhere between 50 and 75 m

depth. The concentration then decreases towards the bottom of the

euphotic layer (Fig. 5A and B only show data for depth b 100 m).

The maximum value of Chl-a concentration after the typhoon Nuri

is enhanced to approximately 7.5 times the climatological value

(0.28 ± 0.13 mg m−3) (Table 4).

4. Discussion

4.1. Typhoon induced high-salinity and low-temperature patch

It is useful to estimate the main physical parameters of the flow

generated by the typhoon in order to understand the observed pat-

terns of temperature and salinity. A linear solution describing the re-

sponse of the ocean to a moving storm was given by Geisler (1970).

Nonlinear behavior of the flowwas further investigated using numer-

ical models by Chang and Anthes (1978), Price (1981), Greatbatch

(1983), and Price et al. (1994). In particular, Geisler (1970) showed

that the baroclinic response of a two-layer ocean is more important

than the barotropic one and includes an inertia-gravity wave wake in

the tail of the storm. A wake pattern of a storm translating at 5 m s−1

over an ocean with MLD of 50 m was given in Fig. 1 in Greatbatch

(1983). The pattern consists of alternating regions of horizontal diver-

gence and convergence. These regions correspond to upwelling and

downwelling respectively. This effect was called “inertial pumping”

(Price et al., 1994).

The regions of upwelling and downwelling shown in our Fig. 3

correspond to those given by the theoretical solution. Note that the

transect TN (Stations 2–9) is not perpendicular to the typhoon track

but rather at an angle of about 30°. Thus, we are able to observe the

alternating patches of upwelling/downwelling along the typhoon

track. Eqs. (1) and (3) give the estimate for the mean wind stress

τ→

= 3.5 N m−2. Eq. (4) then allows us to calculate the thermocline dis-

placement to beΔη = 21 mwhich is in reasonable agreementwith the

observed displacement shown in Fig. 3. We can also estimate the ther-

mocline displacement using the altimetry data. Fig. 2Db shows that a

surface depression of approximately Δh = −5 cm occurred after the

passage of Nuri. Eq. (6) then gives Δη = 20.5 m. Here we take the

value of the density difference between the upper and lower layers to

be Δρ = 2.5 kg m−3. This value was calculated from the temperature

and salinity data measured at Station 2 where these characteristics

were almost undisturbed by the typhoon and corresponded well to

the climatology data (Table 2). The thermocline displacement calculat-

ed using SLA is in surprisingly good agreement with that calculated

using the wind stress and with the observed displacement.

An important control parameter for the flow induced by a moving

storm is the ratio of the translation speed of the storm to the velocity of

the baroclinic gravity waves, c = (g′H)1/2, where H is the depth of the

upper (mixed) layer (before the typhoon). Taking Δρ = 2.5 kg m−3

and H = 35 m, we obtain c = 0.9 m s−1. Thus the ratio Ut/c which is

15

17

19

21

23

25°N

109 112 115 118 121 124°E

15

17

19

21

23

25°N

D

CA

B

Fig. 5. Chl-a concentration. (A) The averaged Chl-a concentration in the study area in 2008 after the typhoon Nuri (red dots). Chl-a climatology (squares) averaged over 1998, 2004,

2005, 2007, 2008 and 2010; Chl-a climatology (triangles) where 2008 data is excluded. (B) The averaged Chl-a concentration (red dots) in typhoon affected area compared with the

data from outside the Nuri's track. In (C), red dots show sample sites and blue symbols show sample sites except for 2008. In (D), red dots and black squares show sample sites

within and without the study area, respectively. In (C) and (D), the green circles show Nuri's track. (For interpretation of the references to color in this figure legend, the reader

is referred to the web version of this article.)

6 H.J. Ye et al. / Journal of Marine Systems xxx (2013) xxx–xxx

Please cite this article as: Ye, H.J., et al., A subsurface chlorophyll a bloom induced by typhoon in the South China Sea, J. Mar. Syst. (2013), http://dx.doi.org/10.1016/j.jmarsys.2013.04.010

in fact the Mach number is quite high in our case, Ut/c = 4.7. This indi-

cates that typhoon Nuri is a fast-moving storm. Coincidently, most of

the control parameters in our case are very close to those chosen by

Chang and Anthes (1978) and Greatbatch (1983) in their numerical

simulations. Thus, Fig. 1 in Greatbatch (1983) gives a good picture of

the flow for the present case. In particular, it shows that maximum verti-

cal velocity is approximately 3 × 10−3 m s−1. According to Greatbatch

(1983) the along-track wavelength of the trailing wave pattern can be

estimated using the inertial wavelength λ = 2π Ut/f = 530 km. We did

not observe another maximum/minimum further down the track of the

typhoon because of the vicinity of the coast.

In order to get some understanding of the vertical exchange in the

SCS, we calculated the Ekman pumping velocityWE using Eq. (3). The

wind stress curl was calculated using the QuikScat wind data before

and after the typhoon (Fig. 2Aa and Ac). The typical values of velocity

were quite low,WE = 0.5 × 10−4 m s−1which is not surprising for the

region with oligothrophic upper layer. The estimate of WE for typhoon

winds (Fig. 2Ab) gave an order of magnitude higher value of WE =

5 × 10−4 m s−1 near the center of the typhoon. This enhanced vertical

velocity which occurred during the passage of the typhoon can result in

significant displacement of isolines of temperature and salinity (Sun et

al., 2010).

The effects of pumping (the Ekman pumping during the typhoon

and the inertial pumping in the wake of the typhoon) together with

an intense turbulent mixing of the upper layer by the typhoon result

in the occurrence of the low-temperature and high-salinity patch that

we observed. Our measurements showed that the patch lasted for the

period of about threeweeks (Figs. 2B and 3). The duration of the patch is

consistentwith the previous observations in the SCS by Zheng and Tang

(2007) and Zhao et al. (2009).

4.2. Short-term surface Chl-a bloom

Nutrients are vital for growth and propagation of Chl-a in the open

sea. Ocean primary production takes place in the euphotic zone, where

there is enough sunlight for photosynthesis (Hader et al., 1995; Kumar

et al., 2004). However, nutrients are often deficient at the upper layer

but increasewith depth (Levitus and Boyer, 1994). Typhoonswith higher

wind speeds and slow translation speed typically induce longer-lasting

Chl-a blooms in surface water (Zhao et al., 2008). In the present study,

the typhoon with fast translation speed and relatively weak wind speed

induced a short term Chl-a bloom in surface water (Table 4). The

enhanced surface Chl-a concentrations can last for 2−3 weeks (Babin

et al., 2004; Zheng and Tang, 2007), it is a result of upward entrainment

of phytoplankton to the surface from the subsurface Chl-a maximum, or

a result of newproduction of Chl-a because of enhanced nutrient concen-

tration in the upper layer caused by mixing which occurred during the

passage of a typhoon. Although it is difficult to establish with certainty,

it is likely that both of the above processes contributed to the observed

surface Chl-a bloom in our case. Walker et al. (2005) reached a similar

conclusion for the hurricane Ivan in the Gulf of Mexico.

4.3. Long-term subsurface Chl-a bloom

Although the surface Chl-a bloom disappeared (Fig. 4A and B) one

week after the Nuri's passage, the subsurface Chl-a concentration

showed extremely high values (1.31 ± 0.47 mg m−3) (Fig. 4C, D, E and

Table 4) before returning to normal after three weeks. The long-term

subsurface Chl-a bloom resulted from the introduction of nutrients from

the deep water by subsurface upwelling. Description of the nutrient con-

centration might help to explain the subsurface Chl-a bloom, but there

was no supporting data available in the study area at that time.

It is important to discuss the enhancement of the subsurface Chl-a

for the IPP. Whether typhoons, hurricanes and tropical storms have a

significant integrated impact on the IPP in the ocean is still an open

question (Lin, 2003; Sun et al., 2010). The IPP is routinely estimated

from the remotely sensed Chl-a data using one of the mathematical

models. A widely used model was developed by Behrenfeld and

Falkowski (1997). This Vertically Generalized Production Model

(VGPM) is to calculate the primary production in depth-integrated

euphotic zone using surface Chl-a concentration data.

In VGPM model, the climatology (August) Chl-a ratio (subsurface

to surface) is 3 (0.28 mg m−3/0.10 mg m−3), where, the Chl-a ratio

after Nuri is 12 (1.31 mg m−3/0.11 mg m−3) (Fig. 5A and Table 4)

which increase 3 times. If using this model, which is based on surface

Chl-a, to estimate the integrated impact of typhoons, we may under-

estimate the IPP due to missing the contribution of the enhanced sub-

surface Chl-a induced by typhoon. That part which underestimated IPP

can be a big amount in the SCS because there are about 10 typhoons

every year.

5. Conclusions

In this paper we documented the typhoon-induced subsurface

Chl-a bloom that was stronger and lasted for a longer period of time

than the surface Chl-a blooms. The surface Chl-a concentration in-

creased suddenly on the 2nd day after the passage of typhoon Nuri

and lasted for about one week. The subsurface Chl-a bloom lasted for

at least three weeks; Chl-a concentration was approximately 5 times

higher than its normal level. Large increase of the MLD indicated that

Nuri induced significant vertical mixing. The occurrence of low SLA

observed by satellite altimeter aswell asmeasured distributions of tem-

perature and salinity demonstrated that Nuri induced an upwelling.

As a result, the typhoon induced subsurface Chl-a bloom lasted for

a relatively long period of time. We conclude that the impact of a

typhoon on the Integrated Primary Production (IPP) may be greater

than what was estimated before due to the occurrence of strong and

long-lasting subsurface Chl-a blooms. Accurate numerical modeling is

required in order to obtain a more accurate estimate of the impacts of

typhoons on IPP.

Acknowledgment

This study was supported by the following research projects

awarded to DL Tang: (1) National Natural Sciences Foundation of

China (31061160190, 40976091, NSFC-RFBR Project-41211120181

of DL Tang and D. Pozdnyakov); (2) Guangdong Sciences Foundation

(2010B031900041, 8351030101000002); (3) Innovation Group Program

of State Key Laboratory of Tropical Oceanography (LTOZZ1201): and (4)

NSFC41006068, 40976091. YDAfanasyevhas been supported by theNat-

ural Sciences and Engineering Research Council of Canada. The authors

thank the South China Sea Open Cruise, R/V Shiyan 3 (SCSIO, CAS).

The authors are grateful to David Lai of NorthWest Research Associates

for providing valuable comments to the manuscript, to J. D. C. Craig for

thorough proofreading of the manuscript and to all members of the Re-

search Center for Remote Sensing and Marine Ecology & Environment

(RSMEE).

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