Factors Affecting Chlorophyll a Concentration in the Central Beibu Gulf, South China Sea

Vol. 474: 67–88, 2013 MARINE ECOLOGY PROGRESS SERIES Published January 31 doi: 10.3354/meps10075 Mar Ecol Prog Ser

Factors affecting chlorophyll a concentration in the central Beibu Gulf, South China Sea

Andrea Bauer, Joanna J. Waniek*

Leibniz Institute for Baltic Sea Research Warnemünde, Department of Marine Chemistry, 18119 Rostock, Germany

ABSTRACT: Since in situ data are sparse, we used a 1D coupled physical−biological model to investigate the complex connection between atmospheric forcing, associated physical water column structure, and primary production within the entire seasonal cycle in the central Beibu Gulf from 2000 to 2010. The results were corroborated by remotely measured sea surface temperature (SST) and surface chlorophyll concentrations in combination with in situ measurements (temperature and chlorophyll) carried out during 2 German−Chinese cruises (September/October 2009 and December 2011). Over the 11 yr period, 87% of the observed variance in daily SST was captured by the model. The model indicates that the central Beibu Gulf is generally unaffected by water masses from the South China Sea and the Beibu Gulf coastal regions. Thus, most of the primary production is locally generated. A strong stratification and a deep chlorophyll maximum develop during summer, vanishing in autumn when the stratification breaks down due to the change from the weak southwest to the stronger northeast monsoon. Deep mixing brings a higher nutrient supply to the surface waters, leading to a phytoplankton bloom which lasts on average about 6 mo. Along with the semi-annual wind system change, temporally short, strong wind events affect primary productivity in the region. Typhoon crossings can enhance primary production by up to 275% relative to the summer background chlorophyll concentration at the surface according to our modeling results. These events play an important role in primary production and the corresponding biogeochemical cycling in this oligotrophic region during the summer and the autumn low-productive periods.

KEY WORDS: Phytoplankton bloom · Model · Shelf sea · Typhoon · Tidal forcing · Remote sensing · Gulf of Tonkin

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INTRODUCTION The growth of phytoplankton depends on the availability of nutrients, incident solar irradiance, and Primary production and the associated energy grazing pressure and varies regionally through dif- transfer into higher trophic levels due to grazing ferent oceanic conditions (Yoder et al. 1993). Com- (Ross 2004), as well as nutrient recycling through bio- pared to land-based primary producers, phyto - mass sinking and decomposition play a major role in plankton are subject to the strong variability of the biogeochemical cycling of oceanic regions (Chen the turbulent marine environment. This means that et al. 2003). For this, phytoplankton is fundamentally their occurrence, regional distributions, and seasonal important for the functioning of marine ecosystems cycles are determined by physical processes (Ward & (e.g. Waniek & Holliday 2006) and crucial for oceanic Waniek 2007) such as currents, vertical mixing, par- carbon fixation, which in turn has an impact on the ticularly through tides generating a near-bottom atmospheric carbon dioxide content (Chen et al. turbulence and wind-stress creating additional tur- 2003). bulence near the sea surface (Tett et al. 1986), and

*Email: [email protected] © Inter-Research 2013 · www.int-res.com 68 Mar Ecol Prog Ser 474: 67–88, 2013

stratification. As a result, phytoplankton always have chlorophyll maximum (DCM), which in most studies to cope with rapid vertical attenuation of light represents a real maximum in phytoplankton bio- (Sharples 1999) and the limitation of nutrient supply mass (Sharples et al. 2001), is commonly observed from the deeper waters in stratified regimes. within the thermocline. The establishment of the Tides, wind, solar radiation, and their interactions DCM is caused by unsteady pulses of mixing pro- affect motion and mixing of the water column cesses which may bring nutrients into the ther - (Dickey 1988) and lead to the characteristic seasonal mocline (Klein & Coste 1984, Sharples & Tett 1994), cycles in the mixed layer thickness (Williams & Fol- such as periodical tidally-driven turbulence, surface lows 2003). From autumn to spring (in the northern break ing waves, wind events, and internal wave hemisphere), low surface heating and a steady influ- instabilities (Lauria et al. 1999). These pulses lead to ence of wind and tides lead to erosion of the seasonal an oscillation of the thermocline supporting a nutri- thermocline and hence to a deep mixing. Depending ent flux into the surface layer. Due to episodic weak- on the water depth, this mixing can even reach the ening of the thermocline and consequent nutrient bottom, which is common in shallow shelf regions. input to the surface waters, the variability in the The deep mixing leads to a high nutrient supply in surface wind stress, especially during storm events the euphotic zone, which could immediately trigger a such as typhoons, also contributes to the formation of phytoplankton bloom. This has been identified as the the subsurface chlorophyll maximum (Klein & Coste determinant of the primary production in, for in - 1984, Sharples & Tett 1994) and is important espe- stance, the western part of the Mediterranean Sea cially in the subtropical/tropical regions. (Klein & Coste 1984). It is the availability of light To understand the temporal and spatial variability which makes the difference in the timing of the of primary production in marine environments, the phytoplankton bloom between regions in high versus connection between primary production and sea- in low latitudes. Seasonal cycles in subtropical waters sonal variability of the vertical water column stability show highest surface chlorophyll concentrations dur- (Sharples 1999, Ross 2006) needs to be investigated. ing winter, e.g. in the South China Sea (e.g. Liu et al. The timing, strength, and duration of the phyto- 2002), and lowest in summer, in contrast to polar/sub- plankton bloom is known to play a fundamental role polar and temperate waters (Howard & Yoder 1997), for growth and survival of organisms of higher which are dominated by a spring bloom (Yoder et al. trophic levels and hence the functioning of biological 1993), e.g. the Northeast Atlantic (Waniek 2003). Fur- communities (e.g. Ridderinkhof 1992, Waniek & Hol- thermore, depending on the depth of the oceanic liday 2006, Sharples 2008). For the northeast Atlan- region, phytoplankton may be vertically transported tic, meteorological factors (solar heating, wind mix- below the euphotic depth, due to the deep mixing ing) have been shown to be responsible for timing and tidally-driven turbulence, and can no longer and strength of the spring bloom (Waniek 2003). conduct photosynthesis (Lauria et al. 1999, e.g. North To investigate the complex connection between Atlantic, cf. Ward & Waniek 2007). If the influence of atmospheric forcing, associated physical water col- solar irradiance overcomes the capacity for tidal mix- umn structure, and primary production, continuous ing in deep regions or regions with low tidal currents, and extensive sampling within the respective study the vertically homogeneous water column can no area is necessary. In most regions this is impossible, longer be maintained and thermally stratifies in although we can use numerical models as tools to spring and summer (Sharples 2008). Algal cells and explain intermittently observed distributions. nutrients are then trapped in the surface layer and The first aim of this study was therefore to examine may induce a spring phytoplankton bloom. the timing of stratification and phytoplankton growth As an important physical barrier, the seasonal ther- in the Beibu Gulf throughout an annual cycle using a mocline separates the wind-mixed surface layer from simple 1D model. Due to a lack of empirical in situ tidally-mixed deeper waters (Ross & Sharples 2007) data, little is known about the oceanic and biological and inhibits the transfer of properties, such as nutri- processes, including spatial and seasonal variation of ents, algal cells, and oxygen (e.g. Klein & Coste 1984, phytoplankton concentration, in this region (Tang et Sharples et al. 2001). Many regions show oligo - al. 2003), which plays an important role in biogeo- trophic conditions during the period of vertical strati- chemical cycling in the northwestern region of the fication (Varela et al. 1992) due to the fast con - South China Sea (Song 2010). The modeling results sumption of nutrients in the surface layer and the were compared to satellite as well as in situ measure- thermocline, which prevents nutrient replenishment ments and literature values from all seasons in differ- from the bottom layer. In those regions, a deep ent years. Since the Beibu Gulf is affected by tidal Bauer & Waniek: Chl a concentration in central Beibu Gulf 69

currents with velocities up to 0.6 m s−1 (Manh & Arafura Shelves Province (Longhurst 1998). The re - Yanagi 1997) and occasional typhoon crossings, 2 gion is characterized by a large riverine discharge in other questions arise: (1) What effect does the the north and northwest, a broad opening in the south spring−neap tidal cycle have on primary production connecting the gulf with the South China Sea, and in the Beibu Gulf, especially within the thermocline the Qiongzhou Strait, a narrow opening to the South in relation to the deep chlorophyll maximum, and (2) China coastal area in the northeast. A year-round to what extent do strong wind events (>10 m s−1) westward mean water transport through the Qiong - affect phytoplankton growth? Both forces can con- zhou Strait forces a gulf-wide cyclonic circulation tribute to the enhancement of nutrient flux from pattern in all seasons (Shi et al. 2002, Wu et al. 2008). the deeper into the surface water layers, which in In this study, we concentrated on the central Beibu turn can cause the development of a phytoplankton Gulf (Fig. 1), a region which may only be affected by bloom (Williams & Follows 2003). The final question external water masses to a small degree in compari- is: Which factors are important in generating inter- son to other regions within the gulf (Bauer et al. annual variability in the timing of stratification and 2013). Therefore, most of the primary production the phytoplankton bloom? should be locally generated, with a small amount being transported through Qiongzhou Strait or from the South China Sea during strong wind events. MATERIALS AND METHODS The central Beibu Gulf is an area with a depth between 54 and 78 m and a summer stratification Study area with a strong thermocline between 20 and 50 m depth (Huang et al. 2008, Bauer et al. 2013). Surface The Beibu Gulf, also known as the Gulf of Tonkin, chlorophyll a (chl a) concentrations are low in sum- is a hydrodynamically variable region influenced by mer (<0.5 mg m−3) and show a seasonal peak in win- the Asian monsoon system, tidal currents, and occa- ter due to the strong northeast monsoonal winds sional typhoon activity. It is a marginal sea of the (Hu et al. 2003, Tang et al. 2003). Typically for South China Sea located within the broad Sunda- oligotrophic regions, only low surface nitrate (up to 0.5 µM) and phosphate (at detection 22 limit) concentrations were found in the China central Beibu Gulf with an N:P ratio >16 21.5 0 indicating phosphate limitation (Bauer 25 et al. 2013). Due to the strong stra - 21 Vietnam 0 25 Leizhou tification in summer, nutrient supply 25 Peninsula from the deeper nutrient-rich water is 20.5 25 limited, and enhanced chlorophyll con- 0 50 50 5025 25 25 Qiongzhou Strait5075 centrations are located in the vicinity of 20 25 25 0 0 50 the thermocline, where sufficient nutri-

50 75 25 ent concentrations and light are avail- 25 19.5 50 50 able. This deep chlorophyll maximum 50 75 lies typically in around 30 to 50 m depth Hainan Island 100 Latitude (°N) 19 50 25 with a maximum chl a concentration of 100 75 50 25 50 25 about 0.6 to 1 mg m−3 (Huang et al. 75 18.5 25 100 25 75 2008, Wu 2008, Bauer et al. 2013). 75 25 75 25 75 50 50 100100 75 25 75 75 75 25 50 5 75 1 75 18 7 00 75 50 75 75 100 75 50 00 0 1 1 7 00 100 5 10 100 100 South In situ data for model validation 75 00 1 75 75 China Sea 17.5 75 50 50 75

75 10 7 75 1 100 5 00 25 7 0 100 Observational data were collected 0 5 752 25 50 50 17 10 50 5 100 during the German−Chinese FENDOU 105.5 106 106.5 107 107.5 108 108.5 109 109.5 110 110.5 111 5 cruise in September/October 2009 Longitude (°E) and the SONNE 219 cruise in Decem- Fig. 1. Study area in the eastern Beibu Gulf. Filled circles indicate sampling ber 2011. Using an IOW (Institut für stations of the FENDOU 5 cruise in September/October 2009 and the central Beibu Gulf (dashed red line). Blue stars indicate the sampling stations of the Ostseeforschung War ne münde) mini SONNE cruise in December 2011 PUMP CTD system (Strady et al. 2008), 70 Mar Ecol Prog Ser 474: 67–88, 2013

depth profiles of hydrographical parameters (temperature (°C), and daily mean solar irradiance (W m−2), ature, conductivity, oxygen) were recor ded at 8 sta- are used by the physical module to calculate heat tions within the central Beibu Gulf during the fluxes across the air−sea boundary and wind-driven FENDOU 5 cruise. For hydrographic profiling and momentum flux transmitted into the water column by water sampling, a Sea bird CTD was used during the using a quadratic stress boundary condition at the sea SONNE 219 cruise. Water samples were taken at dif- surface (Sharples 1999). The daily mean vertical pro- ferent depths during the upcast for chlorophyll and files of the photosynthetically active radiation (PAR, −2 nutrient analysis (NO2, NO3, PO4, SiO4). The samples W m ) are calculated by the model, determining the were low vacuum filtered through 0.7 µm Whatman surface PAR as a fraction of the incident solar radia- GF/F glass fiber filters, which were pre-combusted tion (Table 1). PAR is then distributed through the for preparing water samples for nutrient analysis, water column by using a vertical absorption coeffi- and frozen at around −20°C. Extracted chlorophyll cient (Table 1; Sharples 1999). As the attenuation co- samples (IOC-SCOR 1994) were analyzed fluoro - efficient for PAR changes seasonally within each re- metrically (Turner 10-AU) without correction for gion, it was calculated after Kirk (2011) by using the phaeo pigments. We used an autoanalyzer (Evolution mean Secchi depth of 9.2 m determined from all, only III, Aliance Instruments) to process nutrient samples sparsely available, Secchi depths measured from the

(detection limits: NO2: 0.02 µM; NO3: 0.05 µM; PO4: FENDOU 5 and SONNE cruises. 0.02 µM; SiO4: 0.1 µM) following standard methods The biological component of the model is a simple (Hansen & Koroleff 1999). cell quota, threshold-limitation scheme after Tett et al. Furthermore, in situ CTD data (temperature) and (1986), simulating vertical profiles of phytoplankton surface chlorophyll concentrations from August 2009, biomass (in mg chl m−3) and dissolved inorganic nitro- August 2010, and September 2011 provided by the gen (DIN, in mmol m−3). This module has the same South China Sea Branch of the State Oceanic Admin- vertical (1 m) and temporal (daily) resolution as the istration (SOA) and from the World Ocean Circula- physical component. Phytoplankton growth depends tion Experiment (WOCE) Upper Ocean Thermal on the availability of light, driven by the mean PAR (WOCE UOT 2006, available at http://doi.pangaea. within a model grid depth element (Sharples 1999), de/10.1594/PANGAEA.361180?format=html) from and DIN. Both potentially limiting resources lead to Jan uary 1992 were used for model validation. respiration if there is insufficient growth due to the light environment or nutrient limitation (Sharp les et al. 2006). A fixed grazing rate that re cycles nutrients Simple 1D coupled physical−biological model acts on phytoplankton biomass throughout the year, and in addition, remineralized nitrogen diffuses from To investigate the link between the physical envi- the seabed. To simulate the behavior of zooplankton ronment, especially stratification and mixing of the feeding when it is energetically favorable, the as- water column, and phytoplankton growth in the sumed linear grazing (Table 1; grazing exponent) is central Beibu Gulf, a simple 1D coupled physical− only allowed to take place if the biomass is greater biological model established by Sharples (1999) was than a threshold value (Sharples & Tett 1994). This used. This model is limited to depths less than 200 m threshold value is set to 0.16 mg chl m−3, i.e. the and can be applied to regions from estuaries to the lowest remotely measured surface chlorophyll con- shelf edge (Sharples 1999). The physical module of centration for the central Beibu Gulf in 2009. Phyto- the model simulates daily mean vertical profiles of plankton biomass and DIN are vertically mixed by temperature (°C), u-component of currents (zonal, turbulence calculated by the physical module. Initial- ms−1), and turbulent mixing (m2 s−1) with 1 m depth ization parameters used for both modules (physical resolution. An oscillating sea surface slope, with 2 and biological) are summarized in Table 1. tidal constituents, drives the tidal currents. Only the The maximum depth of the central Beibu Gulf aver-

M2 and S2 tidal constituents are used because these ages 63 m; this depth was chosen as well as the mean are mainly responsible for the spring−neap tidal cycle latitude of 19°N. Current data were only ob tained (Sharples 2008). This allows investigation into the ef- during the spring tide, leading to a calculated mean −1 fect of varying kinetic energy levels in the bottom M2 amplitude of 0.6 m s . For the neap tide, a lower- layer caused by the strongest and weakest tidal cur- ing of this amplitude is expected, which would lead to rents for a semimonthly time period. Meteoro logical a lower mean M2 amplitude. Therefore, for all model data, daily mean wind u- and v-components (zonal runs, the M2 amplitude was set to the mean value of and meridional, m s−1), daily mean dewpoint temper- 0.15 m s−1, containing several tidal cycles, estimated Bauer & Waniek: Chl a concentration in central Beibu Gulf 71

Table 1. Initialization parameters for the model runs used in the physical and biological module of the model. Chl: chlorophyll; PAR: photosynthetically active radiation; DIN: dissolved inorganic nitrogen; SST: sea surface temperature

Parameter (unit) Value Source

Physical module Depth (m) 63 Maximum eddy viscosity and diffusivity (m2 s−1) 0.1 Sharples (1999) Bottom quadratic drag coefficient 3.0 × 10−3 Sharples (1999) Latitude (°N) 19 Background viscosity and diffusivity (m2 s−1) 1.0 × 10−5 Sharples (1999) −1 Amplitude of M2 tidal current (m s ) 0.15 Zu et al. (2008), Manh & Yanagi (1997) S2 tidal amplitude (as fraction of M2) 0.98 Present study Light attenuation coefficient (m−1) 0.1 Kirk (2011) Heat shading coefficient (m2 [mg chl]−1) 0.012 Sharples (1999) Initial homogeneous temperature (°C) 24.41 Satellite SST Fraction of solar radiation that is PAR 0.45 Sharples (1999) Attenuation coefficient for PAR (m−1) 0.15 Present study Pigment absorption cross section (m2 [mg chl]−1) 0.012 Sharples (1999) Maximum near bed DIN concentration (mmol m−3) 2.12 Present study Benthic nutrient input rate (s−1) 2.3 × 10−7 Sharples (1999) Biological module Subsistence quota (mmol N [mg chl]−1) 0.2 Sharples (1999) Maximum quantum yield (mg C [mg chl]−1 d−1 [W m−2]−1) 4.1 Sharples (1999) Cell chl:carbon ratio (mg chl [mg C]−1) 0.02 Sharples (1999) Maximum cell quota (mmol N [mg chl]−1) 1.0 Sharples (1999) Recycled proportion of grazed nutrients 0.5 e.g. Tett (1981), Sharples (1999), Ross & Sharples (2008) Maximum specific growth rate (d−1) 1.2 Sharples (1999) Maximum nutrient uptake rate (mmol DIN [mg chl]−1 d−1) 2.0 Sharples (1999) Nutrient concentration for half maximum uptake (mmol DIN m−3) 0.5 e.g. Waniek (2003), Sharples et al. (2006), Waniek & Holliday (2006) Grazing threshold limit (mg chl m−3) 0.16 Present study Respiration rate (mg C [mg chl]−1 d−1) 3.5 Sharples (1999) Grazing rate (fraction standing stock d−1) 0.12 e.g. Sharples & Tett (1994), Sharples (1999), Sharples et al. (2006) Grazing exponent 1.0 Sharples (1999) Limiting nitrate concentration (mmol DIN m−3) 0.32 Present study from Manh & Yanagi (1997) as well as Zu et al. (2008) The initial homogeneous temperature was taken for the central Beibu Gulf. Published tidal ellipse po- from remotely measured sea surface temperature larizations for the Beibu Gulf are conflicting (e.g. (SST; see subsection ‘Meteorological and compara- Manh & Yanagi 1997, Zu et al. 2008). For this reason, tive satellite data’) on 31 December from the previous the tidal cycles recorded during the FENDOU 5 year, taking into account that the central Beibu Gulf cruise at different depths were used to define the is well-mixed in winter (Table 2). The maximum near tidal ellipse polarization as a degenerated one. The bed DIN concentration was estimated from the zon- mean S2 tidal amplitude (0.98) which is expressed as ally averaged bottom nitrate concentrations mea- a fraction of M2, was calculated from the predictions sured during the FENDOU 5 cruise. The parameters provided by harmonic analysis for the current records in the initial phytoplankton file describe a simple,

(Emery & Thomson 2001). Changing the mean S2 neutrally buoyant phytoplankton species (Sharples tidal amplitude did not show any signifi cant effect in 1999). Within the model, only DIN was used as a the model output. As a result of the S2 tidal amplitude nutrient, but based on our measurements, the Beibu activation from 0 to 1, a cooling of about 0.2% in the Gulf seems to be phosphate limited (Bauer et al. upper 49 m of the water column and a warming of 2013). In general, phytoplankton assimilates phos- about 0.9% in the bottom waters was produced. phate whenever available and accumulates it within 72 Mar Ecol Prog Ser 474: 67–88, 2013

the cells, allowing ongoing grow- ing during poor living conditions (M. Nausch pers. comm.). To include non-modeled phosphate, the phosphate detection limit of 0.02 µM was used to calculate the Bloom corresponding nitrate concentra- ); and start and termi-

sfc tion using the Redfield ratio. The calculated limiting nitrate concentration of 0.32 mmol DIN m−3 is ); modeled surface and bottom equivalent to the 0.3 mmol DIN m−3 dew

T external concentration at which n the previous year and ending in the phy toplankton is generally capable

Stratification to actively take up DIN (Reynolds 2006). sfc ) Start End End Start Length (d) –3

Meteorological and comparative

Annual chl satellite data ) (mg m Modelled variables –3 sfc The model was forced with Chl daily surface u- and v-components of wind, dewpoint temperature, calculated after Wanielista et al. (1997) using air temperature and bot T (°C) (mg m relative humidity, and downward longwave radiation flux all taken from the National Center for Envi-

) and annual integrated surface biomass concentration (Annual chl ronmental Prediction (NCEP) ob - sfc

sfc tained at www.esrl.noaa.gov for T (°C) 11 yr (2000 to 2010; Fig. 2, see also Fig. S1 in the supplement at www. int-res.com/articles/suppl/ m474 p067_supp.pdf). As the spatial given year (except for the modelled mean year) resolution of the NCEP reanalysis dew

T data set is 2.5° × 2.5° (Kalnay et al. 1996), the Beibu Gulf area has been cubically interpolated to a resolution of 0.1° × 0.1°. The inter- ) (°C)

–2 polated meteorological data were averaged for the entire area in the central Beibu Gulf to force the model (18.3−19.6°N, 107.2−108.2°E; Forcing parameters

) m (W Fig. 1). –1

), modeled surface chlorophyll concentration (chl Comparative satellite data for

bot daily SST were taken from www. T (3.7 to 9.9) (353 to 435) (12.0 to 24.8) (22.5 to 35) (22.5 to 25.2) (0.16 to 2.3) (0.2 to 16.4) (312 to 446) (6.3 to 26.3)(1.1 to 38.9) (20.1 to 32.3) (20.1 to 23.4) (334 to 440)(0.4 to 13.4) (0.16 to 2.5) (4.2 to 26.5) (314 to 445)(0.5 to 13.7) (20.9 to 31.5) (7.4 to 27.2) (20.9 to 25.4) (315 to 448)(0.2 to 16.9) (0.16 to 2.7) (20.4 to 32.4) (6.8 to 28.4) (20.5 to 24.1) (319 to 445)(0.6 to 15.4) (0.16 to 2.3) (20.4 to 33.5) (4.2 to 27.0) (20.5 to 23.7) (324 to 442)(0.3 to 18.1) (0.16 to 2.4) (19.5 to 31.8) (4.7 to 26.2) (301 to 439) (19.5 to 23.9(0.2 to 16.7) (6.0 to 27.3) (0.16 to 2.4) (20.8 to 32) (297 to 440) (20.8 to 23.9)(0.1 to 17.5) (20.2 to 31.5) (4.9 to 26.9) (0.16 to 2.3) (20.2 to 24.4) (305 to 449)(0.7 to 15.5) (0.16 to 2.3) (17.8 to 32.5) (8.0 to 27.3) (17.8 to 21.9) (339 to 442) (0.16 to 2.3) (20.8 to 32.6) (6.6 to 27.6) (20.8 to 24.2) (0.16 to 2.4) (21.8 to 32.1) (21.8 to 25.0) (0.16 to 2.5) (0.03 to 16.5) (328 to 446) (9.7 to 26.0) (21.3 to 33.2) (21.3 to 24.3) (0.16 to 2.4) remss.com (Tropical Rainfall Mea- and suring Mission Microwave Imager, sfc resolution 0.25° × 0.25°) and used (°C) (m s temp. DLRF Wind for the comparison with the pre- dicted SST. To compare the modeled primary production, monthly 2002 23.3 6.5 ± 3.0 401 ± 26 19.7 ± 4.0 26.4 ± 3.2 22.4 ± 1.3 0.9 ± 326 35 265 97 260 184 2000 22.292001 23.85 6.3 ± 3.12003 6.4 ± 2.8 400 ± 28 24.262004 403 ± 27 19.8 ± 4.3 23.762005 6.4 ± 2.4 20.1 ± 3.8 24.222006 26.3 ± 3.7 6.0 ± 2.4 400 ± 29 23.382007 26.9 ± 3.6 6.8 ± 2.7 21.2 ± 0.8 395 ± 29 19.7 ± 4.1 24.292008 6.5 ± 2.6 22.5 ± 0.8 0.8 ± 0.7 400 ± 28 19.8 ± 4.2 23.812009 26.6 ± 3.6 6.9 ± 2.8 0.8 ± 400 ± 28 19.9 ± 4.7 273 24.412010 27.0 ± 3.7 7.0 ± 2.8 21.8 ± 0.9 397 ± 30 20.0 ± 4.4 295 24.48 26.2 ± 3.6 6.3 ± 2.8 21.7 ± 0.9 64 395 ± 32 0.6 ± Mean 20.0 ± 4.2 23.82 26.8 ± 3.6 6.9 ± 2.9 21.0 ± 1.2 319 398 ± 31.0 73 0.6 ± 0.7 19.8 ± 4.7 217 26.2 ± 3.6 22.0 ± 0.9 6.5 ± 1.3 318 20.0 ± 4.0 403 ± 27 0.7 ± 0.6 120 228 21.5 ± 1.0 25.8 ± 4.2 285 18 0.7 ± 399 ± 26 20.5 ± 4.0 127 236 0.7 ± 26.7 ± 3.7 19.3 ± 1.1 329 278 44 19.9 ± 3.6 – 262 22.0 ± 0.9 0.7 ± 26.7 ± 3.2 260 207 343 18 99 28.6 ± 4.0 23.1 ± 0.9 0.7 ± 240 324 64 106 275 31 23.6 ± 0.8 0.9 ± 0.8 336 295 251 204 102 315 52 0.6 ± 0.7 196 317 256 120 342 123 31 234 172 266 274 103 52 321 229 222 38 273 305 119 330 194 267 119 273 211 88 217 285 169 Year Initial Table 2. Relevant forcing Table parameters and calculated values for the years 2000 to 2010 modelled mean year: initial temperature; mean ± SD (range) values of meteorological solar irradiation forcing: as downward wind velocity, longwave radiation flux (DLRF), and dewpoint temperature ( temperature ( T nation of stratification and phytoplankton bloom (day the year). Bloom length relates to the phytoplankton bloom beginning i SeaWiFS (2000−2010) and MODIS Bauer & Waniek: Chl a concentration in central Beibu Gulf 73

10 )

–1 a

Wind (m s −10 0 30 60 90 120 150 180 210 240 270 300 330 360

25 b 20 (°C)

dew 15 T

10 0 30 60 90 120 150 180 210 240 270 300 330 360

) 450

–2 c Fig. 2. Mean meteorological forcing for the years 2000− 400 2010 (11 yr): (a) wind velocity, (b) dewpoint temper- DLRF (W m ature (Tdew), (c) solar irradiance as downward long - 350 0 30 60 90 120 150 180 210 240 270 300 330 360 wave radiation flux (DLRF) Day of year

(July 2002 to 2010) surface chlorophyll concentrations cycle of physical factors, e.g. vertical temperature from http://gdata1.sci.gsfc.nasa.gov were used and distribution, mixed layer depth (MLD, depth where a averaged between July 2002 and 2010 because of difference of 0.5°C between SST and temperature at gaps in both data sets. The satellite data were aver- the depth is reached), euphotic depth (1% of the sur- aged for the entire central Beibu Gulf region as well. face PAR), and biological properties, e.g. chlorophyll distribution representing primary production. The mean modeled temperature distribution for 2000 to RESULTS 2010 for the entire water column down to the mean depth of 63 m for the central Beibu Gulf shows sur- All model simulations for the years 2000 to 2010 face heating in summer with an associated stratifica- started at the same initial conditions for the physical tion and a winter deep mixing (Fig. 3a). The stratifi- and biological module (Table 1). The only differences cation establishes on average in spring around Day were in the meteorological forcing and in the initial 38 and exists until the end of November (Day 330; homogeneous temperature which was taken from Fig. 3a,b). The beginning of stratification is defined satellite SST for the previous year on 31 December as the first day in spring when surface and bottom (Table 2). A comparison of a 3 yr run using meteoro- temperatures are no longer equal, whereas the end logical data from 2009 shows a similar vertical tem- of stratification is defined as the first day in autumn perature distribution for each year, indicating stabil- when both temperatures are equal again (Fig. 3b). ity of the numerical scheme. Despite that, an initial During summer, the MLD persists on average at leg of 1 yr was introduced to allow a better adapta- about 18 m depth and shows a deepening during tion of the biological components. winter (January and December) due to strong vertical mixing (Fig. 3a). To validate the model predictions, simulated mean Mean annual cycle daily SST was compared to satellite-derived SST, which was averaged over the 11 yr period (2000− In order to investigate the effect of the meteorolog- 2010) and in situ data (Fig. 3b). The model correctly ical forcing, a mean annual cycle was modeled using simulated the annual cycle of temperature rising dur- the mean meteorological forcing calculated as the ing spring and summer and its decreasing in autumn average over the years 2000 to 2010 (Figs. 2 & 3). The and winter due to reduced solar irradiance (Fig. 3b). analysis of the model results focuses on the annual Modeled and satellite-derived SST agree well during 74 Mar Ecol Prog Ser 474: 67–88, 2013

l 20 30 40 Depth (m) 50 60 30 60 90 120 150 180 210 240 270 300 330 360 Day of year

24 26 28 30 32 34 Temperature (°C) b 36 WOCE UOT (2006) 1992 34 Liu et al. (1998) 1994 Lü et al. (2008) 1960 32 SOA 2009/2010/2011 FENDOU 2009/ SONNE 2011 30 28 26 Temperature (°C) 24 22

30 60 90 120 150 180 210 240 270 300 330 360 Day of year c

10 20 30 40 Depth (m) 50 60 30 60 90 120 150 180 210 240 270 300 330 360 Day of year

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 Chlorophyll (mg m–3) d 2 Liu et al. (1998) 1994 ) SOA 2009 –3 FENDOU 2009/ SONNE 2011 1.5

0.5 Chlorophyll (mg m

0 1 2 3 4 5 6 7 8 9 10 11 12 Month of year Bauer & Waniek: Chl a concentration in central Beibu Gulf 75

Fig. 3. Simulated mean annual cycle using mean meteorological forcing for the years 2000−2010 (11 yr) in the central Beibu Gulf. (a) Temperature distribution over the entire water column. White dashed line indicates the calculated mi x ed layer depth (MLD). (b) Simulated daily mean sea surface temperature (SST) (red line) in comparison to remotely measured SST (black line) averaged over the 11 yr and in situ observations (black symbols). Blue line represents the modeled daily mean bottom temperature and the respective observations (black symbols). (c) Chlorophyll distribution over the entire water column. White dashed line indicates the calculated MLD; white dotted line indicates the euphotic depth (1% of surface photosynthetically active radiation, PAR). (d) Simulated monthly mean sea surface chlo rophyll concentrations (green line) in comparison to satellite-derived monthly mean (±SD) surface chlorophyll concentrations (black line) winter but deviate from each other during summer. up to 5.5°C. The strong winds in this period de - The model overestimated the SST by up to 5.3°C in creased SST on average (±SD) by 2.4 ± 1°C. Ob - late summer. In winter, the modeled SST was slightly served winter surface and bottom temperature data lower than the remotely measured SST by up to from the SONNE cruise and the WOCE UOT 2006 at 1.1°C. Higher temperatures during summer, espe- stations within the central Beibu Gulf corroborate the cially in late summer, may result from the functional model results (Fig. 3b). Also the bottom temperature principle of the 1D model, as it is always the same data from the FENDOU 5 cruise as well as published water body that is heated. Lateral transport as well as bottom temperatures of Liu et al. (1998) and Lü et al. a cloud cover factor are not taken into account by the (2008) agree well with the model results (Fig. 3b). model. In the mean run, wind peaks, which are nor- In summer and autumn, the in situ SST values cor- mally responsible for a surface temperature cooling roborate the satellite data but not the SST of the by mixing processes, were smoothed due to averag- mean year. The modeled SSTs were remarkably con- ing, which resulted in higher surface temperatures as sistent with the remotely measured SSTs over the well. As a result, the higher dewpoint temperature 11 yr period studied. The model captured 87% of and solar radiation in summer led to an increasing the ob served variance in daily surface temperatures SST. Using mean solar irradiance, mean dewpoint (Fig. 4). In winter, the modeled SSTs were slightly temperature, but realistic wind from 2009 reduced too low, in summer, they were slightly too high. the temperature difference between modeled and The modeled chlorophyll distribution shows an remotely measured SST in the period of highest vari- annual cycle with a pro ductive season during winter - ation, caused by highest typhoon activity, in late time due to the deep mixing and the formation of a summer and autumn between Days 207 and 287 by DCM during summer be cause of the strong stratification and the nutrient depletion in 34 the surface water layer (Fig. 3c). The DCM establishes in March when 32 the MLD reaches 20 m depth and the stratification begins to develop 30 (Fig. 3c). During summer, the DCM is located at around 26 m depth, some- 28 what shallower than the euphotic depth (31 m). Due to the strong ver- 26 tical mixing during January and December, the phyto plankton bloom 24 signal is transported down to the bottom below the euphotic depth which is Modeled SST (°C) 22 permanently located in around 25 to 31 m depth (Fig. 3c). During summer, 20 the monthly mean surface chlorophyll concentrations of about 0.1 to 0.2 mg 18 m−3 are captured very well by the R2 = 0.87 model compared to the satellite- 16 16 18 20 22 24 26 28 30 32 34 derived concentrations averaged for Satellite SST (°C) the 11 yr period and in situ measurements (Fig. 3d). The decrease of Fig. 4. Correlation between model and satellite data of all daily sea surface temperatures (SST) for the years 2000–2010. Grey line indicates the regres- surface chlorophyll concentration in sion line with a slope of 1 spring (February and March) and the 76 Mar Ecol Prog Ser 474: 67–88, 2013

increase in autumn and winter (October to De - the annual mean deviation of SST reached only cember) are also well modeled but with differences −0.08°C. The highest temperature of 32.6°C was of up to 0.8 mg m−3. In January and February as well modeled in September on Day 242 in comparison to as Nov ember and December, modeled chlorophyll the remotely measured maximum temperature of concentrations were higher than those measured by 31.7°C on the same day. The lowest temperature of satellites. On the other hand, slightly lower concen- 20.8°C was modeled during winter on Day 28 (Janu- trations were modeled for March and April as well as ary), while 21.3°C was measured on Day 29. Around July to September. The standard deviations repre- Day 265 (September), a sudden temperature de - sent the interannual variability of satellite month ly crease of about 4.6°C took place within 10 d, induced surface chlorophyll concentrations (Fig. 3d). From by a typhoon which passed the study area. After that, January to March and from November to December, the water column was well mixed down to 44 m highest standard deviations were calculated for the depth for around 7 d (Days 271−277; Fig. 5a). The remotely measured chlorophyll concentrations, indi- water column then stratified again for a short period cating that highest interannual variability occurs of around 2 wk (Days 276−291) and transitioned during winter. slowly to winter conditions. The bottom temperature Vertical depth profiles of temperature, chlorophyll, showed a persistent warming from Day 26 (January) and DIN from different cruises during summer/ at 20.9°C to Day 321 (November) at 24.2°C (Fig. 5b). autumn corroborate the model results averaged over From the end of November, the bottom water tem- the summer stratification period with regard to the perature decreased again due to the winter mixing of depth of the thermocline, the depth of the DCM, and the entire water column and reduced solar radiation the DIN distribution (see Figs. S2 & S3 in the supple- as well as decreased dewpoint temperature during ment). this time of the year. The observed surface and bottom temperature data from the FENDOU 5 (2009) cruise and received from SOA at the stations within Annual cycle 2009 the central Beibu Gulf corroborate the model results (Fig. 5b). In 2009, a weak stratification established at the After the MLD reached its shallowest depth beginning of February (Day 31) and continued devel- (around 3 m) and the stratification was fully devel- oping to a fully stratified water column in spring until oped in April, the DCM became established (Fig. 5c). autumn (around Days 102 to 274; Fig. 5a). Corres - The summerly DCM was located at around 27 m pondingly, the MLD reached the bottom during the depth, again shallower than the euphotic depth winter season and became shallower in February (30 m). The phytoplankton bloom in January with when weak stratification occurred (Fig. 5a). During 1.9 mg chl m−3 and the low concentrations of about spring and summer, the MLD persisted on average at 0.1 to 0.2 mg chl m−3 during summer were modeled about 20 m depth, followed by the seasonal deepen- quite well (Fig. 5d). In general, the surface chloro- ing starting at the end of September due to strong phyll decrease in spring (February and March) and wind events and culminating in a fully mixed water increase in autumn and winter (October to Decem- column during winter. ber) were well captured with differences of up to Modeled and satellite-derived SSTs were consis- 0.9 mg m−3. During winter, the model results showed tent from Day 35 (February) to Day 144 (May; higher concentrations than remotely measured Fig. 5b). From that day on, the modeled SST showed (Fig. 5d). The standard deviations (indicated by the slightly higher values until Day 293 (October) and green and black bars in Fig. 5d) indicate the tempo- lower values than those remotely measured from ral (and for the satellite data also spatial) variability October to December (Days 294−365). Nevertheless, of monthly mean surface chlorophyll concentrations

Fig. 5. Simulated annual cycle for 2009 in the central Beibu Gulf. (a) Temperature distribution over the en tire water column. White dashed line indicates the calculated mixed layer depth (MLD). (b) Simulated daily mean sea surface temperature (SST; red line) in comparison to remotely measured SST (black line) and observations (black symbols). Blue line represents the modeled daily mean bottom temperature and the respective observations (black symbols). (c) Chlorophyll distribution over the entire water column. White dashed line indicates the calculated MLD; white dotted line indicates the euphotic depth (1% of surface photosynthetically active radiation, PAR). (d) Simulated monthly mean (±SD) sea surface chlorophyll concentrations (green line) in comparison to satellite-derived monthly mean surface chlorophyll concentrations (black line). Black circles indicate observations during the FENDOU 5 cruise; black diamonds are observations provided by the State Oceanic Administration in 2009. Error bars represent both the spatial and temporal variability of the data sets Bauer & Waniek: Chl a concentration in central Beibu Gulf 77

10 20 30 40

Depth (m) 50 60 30 60 90 120 150 180 210 240 270 300 330 360 Day of year (2009)

22 24 26 28 30 32 Temperature (°C) b 32

Temperature (°C) 22

30 60 90 120 150 180 210 240 270 300 330 360 Day of year (2009) c

10 20 30 40

Depth (m) 50 60 30 60 90 120 150 180 210 240 270 300 330 360 Day of year (2009)

0 0.5 1 1.5 2 Chlorophyll (mg m–3) d 4 )

–3 3

1 Chlorophyll (mg m 0

1 2 3 4 5 6 7 8 9 10 11 12 Month of year (2009) 78 Mar Ecol Prog Ser 474: 67–88, 2013

a 20 ) –1 15

5 Wind velocity (m s

0 250 255 260 265 270 275 280 285 290 Day of year (2009) b

10 20 30 40 Depth (m) 50 60 250 255 260 265 270 275 280 285 290 Day of year (2009)

23 24 25 26 27 28 29 30 31 32 Temperature (°C) c

10 0.32

20 0.32 30 0.32 0.32 40

Depth (m) 50 60 250 255 260 265 270 275 280 285 290 Day of year (2009)

0 0.5 1 1.5 2 DIN (mmol m–3) d Fig. 6. September/October (Days 250−290) of 2009 showing the effect of a typhoon 10 pas sing throughout the region

20 0.32 based on (a) abso lute wind ve- 0.32 locity, (b) vertical temperature 30 0.32 0.32 distribution, (c) vertical distri- 40 bution of dissolved inorganic

Depth (m) nitro gen (DIN), and (d) ver- 50 tical chlorophyll distribution. 60 White da shed line is the 250 255 260 265 270 275 280 285 290 mixed layer depth (MLD) (b− Day of year (2009) d); white dotted lines indicate the limiting nitrate concen - tration of 0.32 mmol m−3 (c,d); 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 white solid line in (d) is the Chlorophyll (mg m–3) euphotic depth Bauer & Waniek: Chl a concentration in central Beibu Gulf 79

a b c

0.4

10 0.35 10

0.3 20 20 )

–3 Fig. 7. Simulated 50 d sec- 0.25 tion of daily mean vertical chlorophyll distribution and 30 0.4 0.4 30 0.4 dissolved inorganic nitro- 0.6 0.6 0.6 0.8 0.2 gen (DIN) isolines for model Depth (m) 0.8 Depth (m) 0.8 1 1 runs (a) without and (b) 1.2 1.2 1 1.4 with tidal forcing in the 40 1.4 0.15 40 1.2 1.6 1.6 year 2009. Black dashed 1.8 1.8 Chlorophyll (mg m line is the mixed layer 1.4 2 2 depth (MLD); dash-dotted 0.1 1.6 line is the euphotic depth. 50 50 1.8 (c) Chlorophyll profiles on 1 d for a model run without 0.05 2 tidal forcing (black solid 60 60 line; Day 220), for a neap 0 tide (red solid line; Day 200 210 220 230 240 250 200 210 220 230 240 250 0 0.25 0.5 220), and for a spring tide Day of year (2009) Chlorophyll (mg m–3) (red dashed line; Day 212)

(Table S1 in the supplement). Highest variability around 0.16 to 1 mg m−3 on Day 278 at the surface. occurred during winter and spring (between January The nutrient concentration reached its maximum and April as well as November and December). The (0.35 mmol m−3) on the same day (272) on which the measurements and the overlapping standard devia- wind reached its maximum velocity, whereas maxi- tions point to a good agreement between the mod- mum chlorophyll concentration within the upper eled and the remotely measured monthly mean sur- 20 m depth was reached 5 d (Days 277−278) later. face chlorophyll concentrations.

Effects of tides Effects of strong wind events Fig. 7 shows the effect of tidal forcing on the DCM The wind forcing at the surface is demonstrated in within a 50 d period from July to September 2009. Fig. 6a for a time period of 40 d, including the passing The resulting DCM from a model run with tides of Typhoon Ketsana (25 to 30 September 2009, Days (Fig. 7b) is more developed than the DCM of a model

268−273) with maximum wind speeds of up to 17.5 m run without tides (M2 and S2 tidal amplitudes set to 0, s−1 in the central Beibu Gulf around Day 272. Stratifi- Fig. 7a). Maximum chlorophyll concentrations for the cation was very strong during summer prior to the model run without tidal forcing reach 0.31 mg m−3 at typhoon crossing, and the MLD only reached down around 26.5 m depth in comparison to 0.42 mg m−3 to 20 m depth (Fig. 6b). During the typhoon (Day for the model run with tides at similar depth. This is 272), the temperature of the surface layer decreased an increase of around 36%. Besides the higher con- rapidly from around 32 to 27°C, the thermocline centrations, the tidally forced DCM is also slightly deepened and destabilized, and the MLD reached broader with a thickness (determined as the part of 44 m (Fig. 6b). As a consequence, between Days 271 the chlorophyll depth profiles showing higher values and 274, the nutrient concentration in the surface than surface background chlorophyll concentration waters exceeded 0.32 mmol DIN m−3, the defined of 0.16 mg m−3, Fig. 7c) of around 12 m compared limiting nitrate concentration or nutricline (Fig. 6c). to 9 m for the run without tides (Fig. 7c), which is This in turn led to enhanced primary production in an increase of around 33%. Due to the maximum the surface layer above the euphotic depth, which tidal forcing during spring tide, the modeled DCM was visible with a lag of about 2 d (Fig. 6d). The (Fig. 8c) is slightly shifted towards the surface by chlorophyll concentration increased from values of around 1 m at the upper boundary of the DCM. Fur- 80 Mar Ecol Prog Ser 474: 67–88, 2013

20 Temperature (°C) b 10 20 30 40 50 Depth (m) 60

18 20 22 24 26 28 30 32 Temperature (°C) c

10 20 Fig. 8. Interannual com- 30 parison of the years 2000 to 2010. (a) Simulated 40 daily mean surface (red MLD (m) 50 line) and bottom tempera- 60 ture (blue line), and remotely measured SST d (black line). Cros ses indicate measurements during 10 the FEN DOU 5 cruise and 20 cruises conducted by the 30 40 State Oceanic Administra- tion (August 2009 and

Depth (m) 50 60 2010). (b) Daily mean temperature distribution over the entire water column. 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 (c) Calcula ted daily mixed DIN (mmol m–3) layer depth (MLD, m). (d) e Daily mean dissolved inorganic nitrogen (DIN) dis- 10 tribution over the entire 20 water column. White line 30 indicates the de fined limit- 40 ing nitrate concentration 50 −3 Depth (m) 60 of 0.32 mmol m . (e) Daily 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 mean chlorophyll distribution. White lines em- phasize the deep chloro- 0 0.5 1 1.5 2 2.5 phyll maximum Chlorophyll (mg m–3) thermore, during spring, the rate of turbulent dissi- isolines towards the surface. The 2.0 mmol m−3 iso- pation at the base of the thermocline increases and line is located on average at about 56 m depth in the leads to an eroding of the stratification and hence to model run without tides but at about 45 m during a nutrient fluxes into the water layer above the thermo- spring tide. As the tides in the central Beibu Gulf cline (e.g. Sharples et al. 2001). The differences in are weak, this effect deflates relatively fast towards thickness and strength of the DCM are a result of the surface, which causes only 1 m difference in the higher nutrient supply within the euphotic zone position of the 0.4 mmol DIN m−3 isoline. Despite this (Fig. 7a,b) and utilization of DIN by the phytoplank- weak elevation of the nutrient-richer water layers ton due to the optimal living conditions within this into the thermocline, primary production within the layer. The tidally induced turbulence pushes the DIN DCM is enhanced by one-third. Bauer & Waniek: Chl a concentration in central Beibu Gulf 81

Interannual variability the nutricline (Fig. 8d, white line). In all years, the limiting nitrate concentration of about 0.32 mmol m−3 As is typical for the Beibu Gulf region, the absolute (which is equivalent to a phosphate concentration of wind shows lower velocities during summer when 0.02 mmol m−3 necessary for phytoplankton growth) the southwest monsoon is predominant and highest lies on average at 29 m depth during summer, with velocities in winter during the northeast monsoon in higher values below and a nutrient-depleted surface the time period between 2000 and 2010 (Fig. S1a). water body (Fig. 8d). In autumn and winter, when the Wind peaks during late summer and autumn (August mixed layer deepens, nutrient inputs from the bottom to November) indicate strong wind events, such as water layer into the surface layer enhance nutrient tropical storms or typhoons. The downward long- concentrations within the euphotic zone (Fig. 8d). In wave radiation flux (DLRF, W m−2) displays the typi- some years (e.g. 2001, 2004, and 2010), this nutrient cal annual cycle with high insolation in summer input is not visible because it is directly ingested by (Fig. S1b). In winter, the irradiance is lower but, typ- phytoplankton in the model. In autumn 2002, a ical for the region, still high with values between 300 strong wind event on Day 265 (Fig. S1) terminated and 400 W m−2. the stratification by September, which led to a strong Maximum and minimum wind forcing in each nutrient input into the surface layer and hence an year are mirrored by the temperature distribution early phytoplankton bloom (Fig. 8d,e). In all years, a (Fig. 8a,b) and the MLD (Fig. 8c). Longer periods of phytoplankton bloom developed between autumn low wind speeds, e.g. in summer 2001 (Days 224− and winter and persisted until spring (Fig. 8e). At 239), 2004 (Days 218−239), 2007 (Days 227− 233), and the turn of the years 2000/2001, 2002/2003, 2005/ 2009 (Days 233−243) lead to an increase of tempera- 2006, and 2007/2008, the phytoplankton bloom is ture in the surface water layer and a shallowing of well developed. By contrast, the bloom is less pro- the MLD, in 2004 for instance from 27 to 3 m in depth nounced be tween 2001/2002, 2004/2005, 2006/2007, and in 2007 from 30 to 2 m. On the other hand, strong and 2008/ 2009 (Fig. 8e). Due to the maximum MLD wind events in late summer and autumn, e.g. in 2000 (63 m) during winter the signal of the bloom reaches (Day 288), 2001 (Day 222), 2002 (Day 265), 2007 (Day the bottom in every year. The stratification vanishes 276), 2009 (Day 272), and 2010 (Day 277), cause a in autumn between Days 265 and 343, but the al - cooling of the surface water between 0.6 and 6.7°C, ready established phytoplankton bloom starts be - depending on the strength of maximum wind tween Days 256 and 295 (Table 2). Strong wind (Table 3), and a deepening of the MLD, for instance events as well as the change from the weaker south- from around 6 to 50 m in 2000, from 19 to 63 m in west to the stronger northeast monsoon lead to a 2002, and from 20 to 44 m in 2009. weakening of the thermocline in autumn, to episodi- The start of sustained stratification and vertical cal nutrient supply into the surface waters and hence mixing is indicated by the surface and bottom tem- a phytoplankton bloom establishing already before perature trends when SST and bottom temperature the stratification breaks down completely. On aver- begin to diverge in spring and converge again in age, a bloom persists for about 204 d, or more than autumn, respectively (Fig. 8a). Periods of mixing 6 mo. The spring stratification starts between Days 17 and/or weak stratification occur between the middle and 72, whereas the phytoplankton bloom ends be - of September and the middle of March of the follow- tween Days 97 and 127 (Table 2). The shortest bloom ing year. The beginning of the main period of stratifi- occurred between 2004 and 2005 (172 d, Table 2). cation is defined as the first day after the last day of Between 2005 and 2006, the bloom lasted for the entire vertical mixing, the end as the first day of total longest time (229 d, Table 2). Within this 11 yr period, vertical mixing in 1 yr (Fig. 8a, Table 2). In the Beibu the well-developed bloom between 2002 and 2003 Gulf, the winter period is the main productive season shows the highest chlorophyll concentrations at (Hu et al. 2003, Tang et al. 2003). The termination of 2.7 mg m−3 (Table 2). The highest annual integrated the thermal stratification in autumn/winter is the surface biomass concentration of 326 mg m−3 was most important factor for the timing of nutrient sup- calculated for 2002, the lowest at 218 mg m−3 for 2003 ply from the bottom waters (Fig. 8d) and hence the (Table 2). initiation and timing of the phytoplankton bloom. On The modeled monthly mean surface chlorophyll average, the termination of stratification takes place concentrations in almost all years are higher compared in November with a strong nutrient input into the to the remotely measured concentrations (Fig. 5). On surface layer in most of the years directly after the average, the modeled bloom has a 0.6 mg m−3 higher stratification breakdown indicated by shallowing of chlorophyll concentration than remotely measured 82 Mar Ecol Prog Ser 474: 67–88, 2013 - ) (DoY) (%) −3 O’Hara & Falvey (2006), f ) which affected primary pro rediction; DoY: day of the year rediction; DoY: −1 ification and data are from the Joint 10 m s ag between wind peak and lowest SST Atangan & Preble (2005), e chlorophyll concentration found in the central Beibu Gulf −3 Furze & Preble (2003), d Angove & Falvey (2010) j ) (DoY) (°C) (lag) (DoY) (DoY) m (mg −1 Furze & Engel (2002), c ) (gusts) s (m −1 Cooper & Falvey (2009), i (m s Grandau & Engel (2001), b Cooper & Falvey (2008), h type intensity NCEP wind speed decrease of PP of PP production increase TS 19WTY 23W 20−23 AugTS 28W 05−10 SepTS 13W 06−13 Oct 23.2 (28.3) 08−11 AugTY 27W 48.9 (59.2)TS 20W 06−12 NovTS 24W 20.6 (25.7) 20.6 (25.7) 15−20 AugTY 25W 15.5 (235) 23−27 Sep 15.9 (254) 12−19 Nov 59.2 (72.0)TS 08W 16.4 (288) 28.3 (36.0)TS 16W 2.2 (1) 12.5 (222) 28−31 Jul 28.3 (36.0)TY 17W 4.4 (1) 38.6 (46.3) 14−18 SepTD 17W 16.5 (318) 5.0 (5) 20−27 SepTY 18W 1.0 (1) 14.2 (230) 21−25 Sep 235 23.2 (28.3) 38.9 (265) 25 Sep−02 Oct 25.7 (33.4) 4.1 (6) 254 11.7 (314) 46.3 (56.6)TY 16W 15.4 (20.6) 1.4 (2) 285 64.3 (77.2)TS 20W 222 bloom Within 6.7 (4) 29 Sep−03 Oct 11.6 (212)TS 22W 2.1 (3) 16.2 (261) 26−30 SepTY 17W 17.2 (270) 12−15 Oct 15.4 (274) 246 Bloom initiated 230 bloom Within 12.9 (268) 36.0 23−29 Sep 0.6 (2) 282 260 1.6 (1)TD 14W 2.0 (2) 1.2 (2) 227 28.3 2.3 (2) 04−06 Oct 0.3 (237) 18.0 bloom Within 213 bloom Within Bloom initiated 0.6 (259) 46.3 18.1 (276) 256 241 0.2 (224) 266 87.5 15.3 (274) 15.4 2.5 (1) 275 Bloom initiated 16.7 (288) 17.5 (272) 0.3 (233) 214 25 Bloom initiated 4.2 (1) 2.7 (1) 274 4.9 (2) 15.5 (277) 87.5 bloom Within 0.2 (213) 273 Bloom initiated 3.9 (3) 267 25 Bloom initiated 273 Bloom initiated Bloom initiated c h f c d a f h j a b i e e g a e b O’Hara & Falvey (2007), McPherson & Zettlemoyer (2000), 2000 Kaemi Year Name Cyclone Period Estimated max. Daily mean SST Start increase End increase Maximum Production a g 20002000 Wukong 2001 No name 2001 Usagi 2001 No name2002 Lingling WE2002 Vongfong 2003 Mekkhala 2004 Nepartak 2005 No name2005 Washi WE2005 Vicente 2006 Damrey 2006 No name 2007 Xangsane 2007 No name2007 No name WE2008 Lekima WE2008 Mekkhala 2009 No name 2010 Ketsana 2010 No name2010 No name WE No name WE 11.2 (254) 2.1 (2) 11.7 (276) 253 2.2 (4) 11.2 (218) 276 10.7 (267) 264 1.2 (1) 1.7 (1) 0.2 (256) 10.7 (198) 287 218 10.6 (236) 266 1.1 (2) 25 1.1 (2) 0.2 (279) 234 198 273 236 25 0.3 (225) 0.2 (268) 205 247 87.5 25 0.2 (201) 0.2 (238) 25 25 Table 3. Wind events classified into tropical 3. Wind stormTable (TS), typhoon (TY), tropical depression (TD), and strong wind events (WE, > during summer. For wind events initiating the phytoplankton bloom, end of increased PP is not detectable. Cyclone class during summer. see footnotes for detailed sources). NCEP: National Center for Environmental P Warning Center (www.usno.navy.mil/JTWC/; Typhoon duction (PP) in the central Beibu Gulf (2000 to 2010) with corresponding sea surface temperature (SST) decrease including the l in parentheses. The production increase expressed as a percentage is related to the background 0.16 mg m Bauer & Waniek: Chl a concentration in central Beibu Gulf 83

4 ) –3

Surface chlorophyll (mg m 0

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Year Fig. 9. Interannual variability of the modeled (green line) and remotely measured (black line) monthly mean surface chlorophyll concentrations for the time period 2000 to 2010. Grey bars indicate the spatial availability of satellite chlorophyll data for the central Beibu Gulf, and the crosses show measurements during the FENDOU 5 cruise and a cruise conducted by the State Oceanic Administration (August 2009) and a shift of up to 2 mo between both signals can be of water, because lateral transports of water masses seen, for example between 2002 and 2003 (Fig. 9). are not taken into account by the model. Another While the satellite observed blooms start in No - reason is the missing cloud cover correction within vember/December and continue until April/May, the the model. The surface dewpoint temperature (mini- modeled blooms start between September and De- mum of 4.2°C in winter and maximum of 28.4°C in cember and continue until January to March (Fig. 9). summer; Table 2) and the high solar irradiance (typi- In all years, a DCM was detected more or less cally ranging between 297 and 449 W m−2, Table 2) developed between 19 m (e.g. in 2001) and 33 m result in a strong stratification during summer with (e.g. in 2004; Fig. 8e, emphasized by the white line SSTs of up to 33.5°C. which indicates the 0.2 mg chl m−3 isoline). In some Wind and its effects on water column stability seem years, short-lived blooms prior to the main phyto- to play the most important role for phytoplankton plankton bloom were modeled. These blooms are growth in the central Beibu Gulf. The assumption associated with strong wind events in late summer was tested using the model with only 1 changed and autumn (Fig. S1) for example in 2000 and 2005 meteorological forcing parameter (dewpoint temper- to 2010 (Fig. 8e). ature, solar irradiance, and wind velocities) for 2009 in each run. The minimum and maximum values of the respective forcing parameter were used to act DISCUSSION throughout the year. The differences in the resulting annual mean of surface chlorophyll concentrations Considering that the model works simply with ver- between the model runs forced with the minimum tical exchange and does not include advective flows, and maximum value of every meteorological input its success in capturing 87% of the observed variance are 4% for solar irradiance (min. = 305 W m−2, max. = in daily surface temperatures indicates that surface 449 W m−2), 63% for the surface dewpoint tempera- water masses from the South China Sea or the Beibu ture (min. = 8.0°C, max. = 27.3°C), and 90% for wind −1 −1 Gulf coastal regions do not strongly affect the central velocities (umin. = −0.0017 m s , vmin. = −0.041 m s , −1 −1 Beibu Gulf. This agrees with the general cyclonic cir- umax. = −11.99 m s , vmax. = −14.95 m s ). This sup- culation pattern in the Beibu Gulf (Wu et al. 2008). ports our conclusion that wind is the most important Therefore, the local meteorological forcing seems to parameter for phytoplankton growth in the central be the most important factor for the formation of the Beibu Gulf. This is already known from the Arabian vertical water column temperature distribution. The Sea, which is also a monsoon-influenced region (e.g. approximately 14% over- and underestimation for Bauer et al. 1991). Based on observations, Bauer et al. summer and winter temperatures, respectively, can (1991) identified wind forcing as the primary factor be explained by the structure of the 1D model itself, influencing the MLD and hence pigment biomass in as it always warms up and cools down the same body the monsoon season. 84 Mar Ecol Prog Ser 474: 67–88, 2013

As the light regime is relatively constant through- rather than by tidally-driven turbulence as discussed out the year, phytoplankton growth depends mainly later. Depending on the strength and quantity of on the availability of nutrients, which in turn is these events, the DCM is more or less strongly devel- affected by the water column structure and physical oped within the different years. The DCM can disap- forces acting upon it. Due to the strong water column pear for periods when the time between the entrain- stratification (see Figs. S2a & S3a), most pronounced ment events is longer than the utilization time scale between February and November, the central Beibu of DIN (Sharples & Tett 1994); this clearly happened Gulf is nutrient depleted in the upper water layer in autumn 2004 and summer 2010 (Fig. 8d). during this period (Figs. S2c & S3c). As a result, only Due to the strong northeast monsoon beginning in minimum phytoplankton growth takes place in the autumn, the stratification breaks down between surface waters, and a DCM develops at around 20 to October and December and allows the development 30 m depth where the nutricline and euphotic zone of a phytoplankton bloom. The onset of the phyto- overlap (see Fig. 6d). The depth of the DCM seems to plankton bloom around Day 273 ± 22 (Table 2), some depend on the depth of the nutricline rather than on 47 d before the disappearance of stratification on Day the euphotic depth (Fig. 6d), which was described by 320 ± 55, leads to the assumption that stratification is Cullen & Eppley (1981) for the Southern California already weakened in autumn due to tides, storms, Bight. They found the depth of the DCM at about and the change of the wind system to the stronger 20 to 50 m correlating more with the depth of the northeast monsoon, before it finally disappears. The nutricline (15−45 m, 15−6% of the surface irradiance stronger wind-driven turbulence induced at the sur- available) than with the euphotic depth (33−66 m). face deepens the MLD (Bauer et al. 1991) and leads For the mean modeled year, the calculated PAR at to nutrient input into the surface water layer through the mean depth of the DCM (26 m) is about 4% of the the thermocline. In turn, this allows a phytoplankton surface PAR. The link between the nutricline and the bloom to start before stratification breaks down. Dif- DCM results in a gradual deepening of the nutricline ferences in the strength and quantity of nutrient and the DCM within the thermocline, which was inputs lead to different timing and development of shown for the western English Channel by Sharples the phytoplankton bloom (cf. Waniek 2003). Ongoing et al. (2001). strong winds and the further decrease in solar irradi- The mean modeled DCM is located somewhat ance then enable a mixing down to the seabed and shallower than the depth range for the DCM in the full development of the bloom. The spring stratifica- central Beibu Gulf of about 30 to 50 m reported by tion starts on average around Day 44 ± 19, whereas Huang et al. (2008), Wu (2008), and Bauer et al. (in the phytoplankton bloom ends around Day 112 ± 15 press). Our own measurements and literature values (Table 2). It takes about 69 d until stratification is (Liu et al. 1998) indicate a relatively high variability fully developed and nutrients within the surface in the depth of the DCM as well as in its strength. water layer are depleted. About 2 mo after stratifica- The mean modeled DCM shows maximum chloro- tion occurs, phytoplankton growth is terminated, in - phyll con centrations of around 0.5 mg m−3 (Fig. 3c), dicating a very slow onset of full stratification, prob - whereas the maximum chlorophyll concentrations ably with periodic nutrient inputs in the surface layer within the DCM vary between 0.2 and 1.1 mg m−3 due to tidal forcing, a low nutrient uptake rate, slow (Fig. 8e) for the different years, and particularly for remineralization, or a grazing pressure acting on the different periods within the years, which agrees well phytoplankton. According to Chung et al. (2012), with the range of 0.6 to 1 mg m−3 reported by Wu phytoplankton blooms are terminated due to herbi- (2008) and Bauer et al. (in press). If enough nutrients vore grazing rather than nutrient depletion or sedi- and light are available to compensate for loss pro- mentation. A model test with deactivated grazing cesses through photosynthesis, a net phytoplankton showed that a strong phytoplankton bloom would bloom occurs when cells are trapped near the surface persist over the entire year. Despite nutrient deple- (Sverdrup 1953, Ward & Waniek 2007). Despite the tion during summer, zooplankton grazing seems to strong stratification during summer, the existence of be the most important factor for termination of the a DCM implies that a complete decoupling of the sur- phytoplankton bloom in the central Beibu Gulf. The face and bottom waters does not occur (Sharples & variability in the beginning and ending of stratifica- Tett 1994). The continuous presence of the DCM tion and phytoplankton bloom indicates that the tim- throughout the summer is caused by the variability in ing of the bloom is less variable than the timing of surface wind stress driving occasional events intro- stratification (e.g. Sharples et al. 2006). This also sup- ducing DIN into the system (Sharples & Tett 1994), ports the conclusion that wind forcing is the most Bauer & Waniek: Chl a concentration in central Beibu Gulf 85

important factor driving primary production in the al. 1999, Shiah et al. 2000, Lin et al. 2003, Babin et al. central Beibu Gulf. 2004, Zheng & Tang 2007, Chung et al. 2012, Lin The differences between both developments of 2012). Wind velocities (Fig. S1) show that typically modeled and remotely measured monthly mean sur- more than 1 strong wind event influenced the central face chlorophyll concentration could be caused by Beibu Gulf region during almost every year from lateral transport, which is not included in the model 2000 to 2010 in late summer and autumn. In the 11 yr (Fig. 9). Through currents and tide-induced lateral period, 11 events were detected which initiated a transport, nutrients for phytoplankton growth, or small bloom prior to the highly developed bloom, phytoplankton itself, as well as grazers may be trans- statistically 1 event yr−1 (Table 3). On average, the ported to/from the central Beibu Gulf from/to other estimated temporary increase in primary production regions. This would have an effect on the surface induced by these strong wind events accounts for chlorophyll concentration within the central Beibu 65% with an average duration of 11 ± 7 d. This result Gulf. The standard deviations for the satellite data corresponds well to the 11 d bloom duration after the (Fig. 9) display the spatial variability of the remotely crossing of Hurricane Katrina in the Gulf of Mexico measured surface chlorophyll concentrations. Be - in August 2005 (Shi & Wang 2007). About 1 to 7 d tween 0 and 121 pixels mo−1 were recorded by lagged between the wind-stress peak and the mode- SeaWiFS within the central Beibu Gulf (Table S1). led chlorophyll peak at the surface (Table 3), which is During winter, satellite data for the central Beibu comparable to the 3 to 4 d lag postulated by Walker Gulf are sparse, probably due to a higher cloud cover et al. (2005) for Hurricane Ivan, the 4 d lag described caused by activity of tropical storms. The differences by Shi & Wang (2007) for Hurricane Katrina, both in between the surface chlorophyll concentrations and the Gulf of Mexico, and the 3 to 6 d lag described by the beginning of the phytoplankton bloom can there- Zheng & Tang (2007) for Typhoon Damrey in the fore be attributed to the lack of available satellite South China Sea. The modeled lag between the low- data. The small standard deviations in the output est SST and the chlorophyll peak of up to 6 d agrees data indicate that the model successfully simulated well with the 4 d lag described by Zheng & Tang the surface chlorophyll concentrations for the region. (2007). The low variability in meteorological forcing is mir- However, to what extent a typhoon will affect an rored in the model results (Table 2). Surface and bot- oceanic region depends on the wind intensity, the tom water temperatures as well as surface chloro- transit time, and the ocean’s precondition, which phyll concentrations do not show great differences means how deep or shallow the nutrient-rich water between years, and variations are the result of strong body lies (Lin 2012). If any condition is unfavorable, wind events. In correspondence with the strong wind the ocean’s response will be weakened (Lin 2012). events, the SST declines due to entrainment of For example, the modeled Typhoon Washi enhanced colder, subsurface water masses into surface waters the surface chlorophyll concentration in the central (Price 1981) by 0.6 to 6.7°C (Table 3), depending on Beibu Gulf to up to 0.2 mg m−3 at a maximum wind wind strength, comparable to measured SST res pon - speed of 11.6 m s−1 but enhanced the maximum sur- ses between −2.5 and −9°C (Chang et al. 1996, Lin et face chlorophyll concentration by up to 0.9 mg m−3 al. 2003, Walker et al. 2005, Shi & Wang 2007, Zheng (around 3.8 times before the typhoon) in the SCS at & Tang 2007). The lag between the wind peak and wind speeds of around 18 m s−1 (Chen & Tang 2011). the lowest SST is about 1 to 6 d (cf. Shi & Wang 2007), The greatest effect on the chlorophyll increase was depending as well on the wind intensity and the seen from the passage of Typhoon Wukong through duration of strong wind influence or the transit time the region in 2000 (Table 3). This storm initiated a of the respective typhoon. Despite the pronounced bloom lasting 28 d with a maximum surface chloro- summer stratification, strong wind events such as phyll concentration of 0.6 mg m−3, an increase of tropical storms lead to a deepening of the MLD (Price 275% compared to the summer background surface 1981, Jiang et al. 2009) and hence to a higher nutri- chlorophyll concentration of 0.16 mg m−3. Along with ent supply in the surface water layer resulting in a these temporary bloom events, tropical storms can short-lived enhancement of the primary productivity also initiate a phytoplankton proliferation, for exam- or a phytoplankton bloom (e.g. Zheng & Tang 2007). ple in 2000, 2002, and 2005 to 2010, resulting in a These results are supported by several studies based bloom as early as mid-September such as those in on satellite data or in situ measurements describing 2002 or 2005. The effect of strong wind events on sur- such blooms for different typhoon- or hurricane- face chlorophyll concentration during the fully devel- influenced regions (e.g. Chang et al. 1996, Fogel et oped bloom is difficult to estimate. 86 Mar Ecol Prog Ser 474: 67–88, 2013

Contrary to our expectations, the effect of tides on ing down to the seabed in winter. The physical struc- primary production within the central Beibu Gulf is ture of the water column is reflected in the seasonal only moderate. This may be a result of the relatively cycle of primary production. A phytoplankton bloom great depth (63 m), the distance from shore, the asso- develops when the wind system changes in autumn ciated small tidal forcing in this region, and the lat- into the stronger northeast monsoon, the solar irradi- eral transport initiated by tides, which is not included ance decreases, deep mixing occurs, and nutrients in the model, or a combination of these factors. The from bottom waters are supplied to the surface strong stratification can reduce the already weak waters and therefore are available for phytoplank- tidal forcing, which therefore only has a minor effect ton. During summer, due to the strong stratification, on mixing in the surface water column during sum- the surface waters are nutrient depleted and there- mer. In spite of the weak tides (0.15 m s−1 for ampli- fore only low phytoplankton growth is possible. At a tude of M2 tidal currents) in this region, the tidally depth of around 20 to 30 m, where euphotic depth generated turbulence increases the strength of the and nutricline co-exist, a DCM developed in all mod- DCM by up to 36% and its thickness by up to 33%. eled years. According to the results of Sharples et al. (2006), a The model successfully simulated the observed tidal current amplitude of 0.4 m s−1 can offset the stratification, SST, and bottom temperature as well as influence of heating in stratifying the water column. the chlorophyll distribution. Differences in the SST The result of this would be a weakly stratified water and the monthly mean surface chlorophyll concen- column and a breakdown of stratification that oc curs trations are a consequence of the absent horizontal earlier in the year. Ultimately, due to the intense advection and the missing cloud cover in the model nutrient input from the deep water to the surface and are also attributable to the lack of satellite data. layer, it would strongly enhance the primary produc- A water depth of 63 m, the distance from shore, and tion within the surface water layer throughout the associated weak tidal forcing explain the weak tidal year. The rising bathymetry from south to north in influence in the central Beibu Gulf. However, tides the region means the shallow northern or coastal lead to an enhanced nutrient supply within the regions may be considerably more affected by tidal euphotic zone and hence to a considerable increase currents than the relatively deep central part of the in strength and thickness of the DCM. gulf. In a system which is strongly influenced by Although the interannual variability is generally tides, a constant competition between tidal turbu- low, the timing of the stratification breakdown and lence in the bottom layer and wind-driven turbu- the establishment of a phytoplankton bloom are vari- lence in the surface layer determine the position of able within a timeframe of about 2.5 mo and around the thermocline and its associated DCM (Sharples 1 mo in autumn/winter. Besides these features, 1999). During spring tides, when the maximum strong wind events play an important role in the currents occur, the tidal turbulence pushes the primary production within the central Beibu Gulf. thermocline towards the sea surface, while during Single events strongly enhance primary production neap tides, with only weak currents, the wind-driven during the usually low productive summer season turbulence pushes the thermocline deeper in the and are able to initiate a prior phytoplankton bloom. water column (e.g. Sharples 1999). These forces In summary, the monsoon winds and the occasionally cause periodic pulses of nutrients to the euphotic strong wind events are the most important forces dri- zone and hence higher chlorophyll concentrations ving primary production in the central Beibu Gulf. within the DCM. In the central Beibu Gulf, the influ- Our study helps to compensate for the lack of ence of the spring−neap tidal cycle on the elevation remotely measured and in situ data for the central of the DIN isolines is only visible to a depth of 40 m Beibu Gulf and hence contributes to a more compre- (Fig. 7b). Hence the expected periodic pulses of hensive understanding of processes influencing pri- higher chlorophyll concentrations within the DCM mary production in that region. do not occur.

Acknowledgements. We thank the masters, crews, and participants of the FENDOU 5 and SONNE cruises. The CONCLUSIONS Guangzhou Marine Geological Survey (GMGS) is grate- fully acknowledged for planning and conducting the As is typical for subtropical/tropical shelf seas, the FENDOU 5 cruise and for the good cooperation. Thanks to all colleagues involved in the sample measurements, central Beibu Gulf shows an annual cycle with a in particular B. Fründt and R. Prien from the Leibniz strong stratification during summer and a deep mix- Institute for Baltic Sea Research Warnemünde, Germany, Bauer & Waniek: Chl a concentration in central Beibu Gulf 87

as well as D. P. Connelly from the National Oceanography in physical oceanography, 2nd revised edn. Elsevier Centre, Southampton, UK, for their support and helpful Science, Amsterdam comments on earlier versions of this manuscript. We also Fogel ML, Aguilar C, Cuhel R, Hollander DJ, Willey JD, thank NCEP, SeaWiFS, MODIS, Remote Sensing Systems, Paerl HW (1999) Biological and isotopic changes in South China Sea Branch of the State Oceanic Administra- coastal waters induced by Hurricane Gordon. Limnol tion (PR China), and WOCE for providing their data, and Oceanogr 44:1359−1369 3 anonymous reviewers for their perceptive comments. Furze P, Engel G (2002) 2002 annual tropical cyclone report. 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Editorial responsibility: Graham Savidge, Submitted: April 4, 2012; Accepted: September 25, 2012 Portaferry, UK Proofs received from author(s): January 13, 2013