Two phytoplankton blooms near Luzon Strait generatedby lingering Typhoon Parma

Hui Zhao,1 Guoqi Han,2 Shuwen Zhang,1 and Dongxiao Wang3

Received 30 October 2012; revised 9 February 2013; accepted 15 February 2013; published 3 April 2013.

[1] Two phytoplankton blooms near Luzon Strait triggered by Typhoon Parma in 2009were investigated using remote sensing data and in situ observations. Parma was slowmoving (a translation speed of ~2m s�1) and relatively weak (a maximum sustained windof ~30m s�1) during its lingering path northwest of Luzon Island. After it reached a point(120.5�E, 20.3�N) west of Luzon Strait, Parma turned sharply back toward the northernPhilippines along approximately the same course. Such long (~7 days) lingering typhoonsare rather rare in the South China Sea (SCS). Before Parma, low Chl-a concentrations(<0.2mgm�3) were observed in the northeastern SCS. After its passage, a strong offshorephytoplankton increase (Chl-a> 0.6mgm�3) appeared west of the central Luzon Strait; anearshore phytoplankton increase was also observed north of Luzon Island, together withhigh CDOM (color dissolved organic matter). During and after the typhoon, sea-surfacecooling (~3�C), stronger wind (>20m s�1), and heavy rainfall (>100mmday�1) wereseen in the above regions. The offshore bloom occurred where Parma’s translation speedwas the slowest (~1m s�1). It may be caused primarily by the Ekman pumping whichbrought nutrients upward to the euphotic zone and also by the entrainment mixing. Thenearshore bloom may be triggered by the heavy typhoon-induced rainfall, which suppliednutrients for the coast region north of Luzon Island. The rapid increase of CDOM in thenearshore region implied that terrestrial input may be the source of nutrients.

Citation: Zhao, H., G. Han, S. Zhang, and D. Wang (2013), Two phytoplankton blooms near Luzon Strait generated bylingering Typhoon Parma, J. Geophys. Res. Biogeosci., 118, 412–421, doi:10.1002/jgrg.20041.

1. Introduction

[2] Typhoons can cause extremely strong winds, whichcan have dramatic effects on the upper oceans. They canhave disastrous consequences during their passage overhabitats of lands or farmlands. Due to limit of nutrientsand influence of light, a maximum concentration appears ata subsurface layer which may vary from below the surfaceto near or below the bottom of the euphotic zone [Steeleand Yentsch, 1960]. Therefore, typhoons may also play animportant role in phytoplankton blooms and increasedprimary productivity in oligotrophic ocean waters [e.g., Linet al., 2003; Babin et al., 2004; Walker et al., 2005; Zhengand Tang, 2007]. They can cause entrainment, strongvertical mixing, and upwelling as well as near-surfacewater’s cooling on the right-hand side of the storm track in

the Northern Hemisphere [Hazelworth, 1968; Dickey andSimpson, 1983; Stramma et al., 1986; Sanford et al., 1987;Price, 1998; Emanuel, 1999].[3] Typhoons or tropical cyclones occur frequently in the

South China Sea (SCS), more than seven times annuallyon average [Lin et al., 2003; Zheng and Tang, 2007; Zhaoet al., 2008; http://en.wikipedia.org/]. They can triggeruptake of nutrients from subsurface layer and phytoplanktonblooms near their paths through oceanic eddies, mixing, andupwelling [Chang et al., 1996, 2008; Chen et al., 2003; Linet al., 2003; Zheng and Tang, 2007; Zhao et al., 2008]. Cy-clones and typhoons have important effects on chlorophyll-a(Chl-a) and phytoplankton blooms, with estimated maximumcontribution of 20–30% for the annual new production in theSCS [Lin et al., 2003]. Zhao et al. [2008] indicated that differ-ent kinds of typhoons, with different translation speeds andintensities, exert diverse impacts on intensity and area ofphytoplankton blooms. The typhoon-induced increase of thePearl River discharge [Zhao et al., 2009] can trigger an exten-sive phytoplankton bloom under the influence of favorablecurrents. Zheng and Tang [2007] investigated the impacts ofa category 2 typhoon on two phytoplankton blooms in thenorthwest SCS, one nearshore and the other offshore. Theoffshore bloom was associated with the strongest maximumsustained wind of ~41m s�1, while the inshore bloomoccurred over the shallow continental shelf (depth <80m),without any great river.

1Guangdong Key Lab. of Climate, Resource and Environment inContinental Shelf Sea and Deep Sea, College of Ocean and Meteorology,Guangdong Ocean University, Zhanjiang, China.

2Northwest Atlantic Fisheries Centre, Fisheries and Oceans Canada,St. John’s, NL, Canada.

3State Key Laboratory of Tropical Oceanography, South China SeaInstitute of Oceanology, Chinese Academy of Sciences, Guangzhou, China.

Corresponding author: Hui Zhao, College of Ocean and Meteorology,GuangdongOcean University, Zhanjiang 524088, China. (chaohui@scsio.ac.cn)

©2013. American Geophysical Union. All Rights Reserved.2169-8953/13/10.1002/jgrg.20041

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JOURNAL OF GEOPHYSICAL RESEARCH: BIOGEOSCIENCES, VOL. 118, 412–421, doi:10.1002/jgrg.20041, 2013

[4] Luzon Strait, the most important channel for theexchange of the SCS deep water with the water of the opennorthwestern Pacific Ocean, is about 350 km in width with asill depth of about 1900m. Previous investigations indicatedthat seasonal phytoplankton blooms and upwelling prevailednorthwest of Luzon in winter [Chen et al., 2006; Gong et al.,1992; Shaw et al., 1996; Peñaflor et al., 2007; Lee Chenet al., 2007; Liu et al., 2007]. However, in the other seasons,the region is generally controlled by oligotrophic water withabundant light [Liu et al., 2002; Zhao and Tang, 2007].Therefore, typhoons may play an important role in the in-crease of phytoplankton and primary productivity in theregion.[5] Parma at its strongest was a category 4 typhoon based on

the Saffir-Simpson typhoon/hurricane scale (http://weather.unisys.com/hurricane/w_pacific/). It originated in the westernPacific (Figure 1) and traversed westward into the SCS. Parmabecame slow moving and relatively weak (not greater thancategory 1), while lingering near the northern Luzon Islandfor about 7 days in an area of 3� by 3� (Figures 1 and 2), wherethe offshore water depth is over 2000m. Such long lingeringtyphoons are rather infrequent near Luzon Island in the SCS,and their influences on phytoplankton blooms have seldom

been evaluated. Parma over its long lingering time may exertlarge influence on terrestrial nutrients runoff, mixing entrain-ment, and upwelling, and therefore phytoplankton in thisregion. In the present paper, we investigate two phytoplanktonblooms (one offshore and the other nearshore) north of LuzonIsland and the impacts of typhoon’s translation speed andintensity during Parma, using satellite observations and in situdata. Dynamic mechanisms of the phytoplankton blooms arediscussed based on meteorological and oceanographic data.In particular, the relative roles of the Ekman pumping versusthe mixing entrainment are evaluated based on concurrentin situ temperature, salinity, and nutrient profiles in thedeep SCS.

2. Data and Methods

2.1. Satellite Products and Hurricane Data

[6] The Aqua MODIS-derived Chl-a product with 9 kmresolution was obtained from the Distributed Active ArchiveCenter (DAAC) of the National Aeronautics and SpaceAdministration (NASA; ftp://oceans.gsfc.nasa.gov/Merged/).Considering the influence of clouds during typhoon onsatellite ocean color, we chose 8 day Level 3 ocean color datain the present study, which was calculated using the OC4algorithm [O’Reilly et al., 1998]. The Aqua MODIS-derived(MODISA) color dissolved organic matter (CDOM) index isproduced based on the algorithm of Morel and Gentili[2009], available at http://oceandata.sci.gsfc.nasa.gov/. The

Figure 1. (a) The study area (15�N–22�N, 118�E–125�E)and the track of typhoon Parma. (b) Track and intensity ofTyphoon Parma (2009) in the study area. Shown in Figure 1aare (1) fast moving, intensifying wind speed; (2) fastmoving, decreasing wind speed; and (3) slow moving,moderate wind speed. The three yellow asterisks in Figure 1bare the stations with CTD observations. LS: Luzon strait; LI:Luzon island.

Figure 2. Change in maximum sustained wind speed(MSW) and translation speed of the typhoon. (a) MSW andsea-level pressure (SLP) of Typhoon Parma (box in Figure 2a,the stage influencing the study area). (b) Translation speed ofthe typhoon. In the red box of the lower panel, the meantranslation speed is 1.6m s�1, and the MSW is 28–31m s�1

with a mean MSW of 29m s�1. In the blue box of thelower panel (i.e., 4–5 October), the mean translation speedis 1.2m s�1 for the radius range of 60 km. The gray box ofthe lower panel, the center of the typhoon, is located onLuzon Island.

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8 day product of CDOM index was used as a proxy to evaluatethe influence from terrestrial materials and phytoplanktonincrease. Furthermore, the CDOM images were processed intomean images to discuss variations of CDOM during, before,and after Parma. In order to analyze the role of mixing,entrainment, and wind-induced upwelling on the offshorephytoplankton increase, MODISA-derived euphotic depthwas also used in the present study (http://oceandata.sci.gsfc.nasa.gov/).[7] The absolute geostrophic velocity was obtained from

the Colorado Center for Astrodynamics Research (CCAR)of the University of Colorado (http://las.aviso.oceanobs.com/). The data set was generated from model mean andaltimeter measurements at the CCAR [Le Traon andMorrow, 2000].[8] Daily rainfall rate and fusion of daily sea-surface

temperature (SST) (TMI_AMSRE) (www.ssmi.com) werederived from the Tropical Rain Measuring Mission (TRMM)Microwave Imager (TMI) and the Advanced MicrowaveScanning Radiometer-EOS (AMSR-E) with a resolution of0.25� by 0.25�. Due to the cloud-penetrating capacity ofboth TMI and AMSR-E, the two measurements togethercan overcome influence of cloudy conditions [Wentz et al.,2000]. Therefore, TMI_AMSRE and TRMM data canprovide continuous SST/rainfall observations with bettercoverage before, during, and after a typhoon or hurricane.[9] The surface wind data are based on the microwave

scatterometer SeaWinds on QuikSCAT satellite thatmeasured surface wind over the oceans [Liu et al., 2000].The daily QuikSCAT data including ascending and descend-ing passes downloaded from the NASA (http://poet.jpl.nasa.gov) were used to study Typhoon Parma. The typhoon dataused in this study were downloaded from the UnisysWeather website (http://weather.unisys.com/hurricane/w_pacific/), which is based on the best hurricane-track data fromthe Joint Typhoon Warning Center in the USA. The datainclude the maximum sustained wind (MSW) velocity, andthe longitude and latitude of the hurricane center every 6 h.The translation speed (i.e., speed of movement) of a hurricanewas thus estimated based on the 6 h position of its center in ouranalysis. The MSW speeds were labeled for the period of Ty-phoon Parma (Figure 1).

2.2. Methodology

2.2.1. Ekman Pumping Velocity (EPV) and Sea SurfaceWind Vector (SSWV)[10] To present the spatial-temporal variation of wind

speed and wind-induced upwelling before and duringParma, daily sea surface wind vectors (SSWVs) were firstprocessed into daily product averaged for the two ascendingand descending passes, and Ekman Pumping Velocity(EPV) was estimated based on daily wind data [Stewart,2002; Zhao and Tang, 2007]. Then, the daily product wasaveraged for 15–30 September and 4–5 October 2009.The time series of wind speed and EPV were obtained byaveraging daily data over boxes (Figure 3), respectively.2.2.2. Chl-a Concentrations and CDOM[11] Chl-a concentration and CDOM were first averaged

over the two periods: the pre-Parma period (15–30 September2009) and the post-Parma period (8 days after typhoonParma’s passage, i.e., 08–15 October 2009). The post-Parmaperiod was so chosen since phytoplankton blooms generally

appeared several days after a storm [Shi and Wang, 2007]and decayed gradually to the nominal prestorm level afterseveral weeks, as well as there were generally relatively sparsevalid observations of Chl-a due to cloudy weather conditionsduring Parma [Lin et al., 2003; Zheng and Tang, 2007; Zhaoet al., 2008]. Their 8 day time series were produced based onthe box average (boxes shown in Figure 3).2.2.3. Rainfall, SST, and Geostrophic Current[12] Similar to the means of QuikSCAT wind speed, the

images of rainfall, SST, and geostrophic current (GC)were plotted to show changes of these conditions duringthe pre-Parma, Parma, and post-Parma periods. The productsfor the pre-Parma were estimated based on the average for15–30 September 2009 (16–30 September 2009 for theGC). In view of their different response time scales totyphoons and data availability, here the rainfall rate wasaveraged for 02–09 October, SST averaged for 04–12 October,and GC averaged for 7–14 October for the Parma andpost-Parma periods. These variables were further aver-aged over the boxes or point in Figure 5 to obtain theirtime series.2.2.4. Time Series of Satellite and In Situ Data[13] To investigate further the relationship between Chl-a

concentration and oceanic conditions (including river/terres-trial discharge and slow-translation speed of the typhoon),we chose two boxes (119�E–120.5�E, 19.8�N–20.9�N) and(120�E–122.3�E, 18.3�N–19.3�N) in Figure 4b for the timeseries, where the variations of Chl-a and CDOM were morenotable. The time series of Chl-a, CDOM, EPV, wind speed,rainfall rate, SST, and GC were averaged over thecorresponding boxes (Figures 3–5) during 25 August to24 October 2009, where the changes were more evident.Using World Ocean Atlas data 2009 (WOA 09) (http://www.nodc.noaa.gov/OC5/WOA09/), we produced a clima-tological vertical profile of nitrate for September by averag-ing over the offshore box (Figure 3c) to indicate the typicalvertical distribution of nutrients. Three in situ profiles oftemperature and salinity (depicted by three pentacles inFigure 1) were used to indicate changes in the upper layerin the offshore typhoon-induced region (available at: http://www.nodc.noaa.gov). From salinity and temperature,

Figure 3. Surface wind vector (m s�1) and Ekman pumpingvelocity (EPV) (color shaded in 10�4m s�1): (a) beforetyphoon and (b) during typhoon. Red Box: a sampling regionof EPV (119�E–120�E, 19.5�N–20.5�N); and black box: asampling region of wind speed (119�E–121�E, 19�N–21�N).

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potential density (sigma-theta) is calculated to estimate themixed layer depth (MLD) using Levitus’ method [Levitus,1982]: starting at 10m, search down the water column untilthe potential density has increased by 0.125 kgm�3.

3. Results

3.1. Wind and EPV During Typhoon Parma

[14] Parma was a category 4 typhoon (Figure 1), whichoriginated from a tropical depression in the northwest Pacific(147.50�E, 9.90�N) at 00:00UTC on 27 September 2009,strengthened to a typhoon at 00:00UTC on 30 Septemberwith the strongest wind speed near (130.90�E, 11.90�N)at 00:00UTC on 01 October, and weakened to a category1 typhoon (MSW: 41m s�1) when it intruded into thenortheastern SCS through Luzon Strait at 06:00 UTC on03 October. Parma maintained generally at the level of atropical storm or a tropical depression during its intrusioninto the SCS. It gradually weakened to become a tropicalstorm after it lingered near (119.8�E, 19.9�N); it thenretraced to Luzon Island. Its mean MSW was 30m s�1

(at a level of strong tropical storm), with a slow mean trans-lation speed of 1.6 m s�1 (Figure 2) and the slowest transla-tion speed of 0.7 m s�1 (the MSW was only 28m s�1)during its lingering time northwest of Luzon Island. Finally,Parma traversed the northern SCS from the coastline ofcentral western Philippines to the Gulf of Tonkin with amean MSW of ~20m s�1 and a mean translation speed of~3.1m s�1.[15] The wind vector image (Figure 3a) averaged for 15–30

September as the pretyphoon background state shows that the

wind was generally weak (<8m s�1) and northeasterly in thestudy area and was even weaker (<3m s�1) south of the studyarea. Here, we chose an image of the wind vector averaged for4–5 October (Figure 3b) to represent the wind during thetyphoon. During Parma’s intrusion into the northern LuzonIsland, the relatively strong wind (>12m s�1; Figure 3b)prevailed over the entire study area. The intensity of windspeed (Figures 1a and 3a) was stronger (>15m s�1) alongParma’s track and northwest of the study area, where therewas a mean MSW of 34m s�1 with a fast translation speedof 3.1m s�1. There was a weakening tendency of MSW from39m s�1 at (121.20�E, 18.20�N) at 12:00UTC on 3 October to29m s�1 at (119.80�E, 19.90�N) at 12:00UTC on 4 October.However, there was a weaker stable MSW of about 28m s�1

with a slower mean translation speed of 1.6m s�1 when itretraced from the location of (119.8�E, 19.90�N) from12:00UTC on 4 October to 18:00UTC on 5 October.[16] Themeanwind speed during Parma (Figure 3b) was only

threefold higher than that before Parma in the study area. How-ever, upwelling indicated by the EPV in the region increased sig-nificantly, with the EPV value up to 1–4� 10�4ms�1 nearParma’s path (the region with yellow/red colors in Figure 3b),which is about 2 orders of magnitude higher than the peakvalue in the background EPV (<0.08� 10�4m s�1;Figure 3b). The region of high EPV (>2� 10�4m s�1)induced by Parma (Figure 3b) was located near (119.4�E,19.8�N), where Parma lingered at its slowest speed.

3.2. Chl-a and CDOM

[17] Satellite-derived Chl-a (Figure 4b, left) averaged for15–30 September 2009 was generally low (<0.1mgm�3)

Figure 4. Left panels: images before Typhoon Parma; middle and right panels: images afterTyphoon Parma. (a) Color dissolved organic material (CDOM) (no units) and (b) Chlorophyll-a (Chl-a)(mgm�3). The offshore box (119�E–120.5�E, 19.8�N–20.9�N) and the nearshore box (120�E–122.3�E,18.3�N–19.3�N) in the lower panels are sampling regions of Chl-a and CDOM.

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before Parma’s presence in the study area. Relatively highChl-a (>0.3mgm�3) was confined to the coastal zone(within about 20 km from the coastline). However, therewere some drastic changes in Chl-a 1week after Parma’spassage. There were two significant bloom regions: one off-shore northwest of Luzon Island and the other nearshorenorth of Luzon Island. The offshore Chl-a (Figure 4b, mid-dle) increased quickly from 0.08 to 0.73mgm�3 in thenorthwestern study area (averaged over an offshore area of19,189 km2 in Figure 4b, middle) with a peak value of about1.5mgm�3. In the coastal region, the Chl-a increased from0.2 to 1.3mgm�3 (averaged over the coastal box of about2.68� 104 km2 in Figure 4b, middle), with a peak of 5.6mgm�3. Then, the Chl-a (Figure 4b, right) decreased to thelevel of ~0.2mgm�3 2weeks after Parma in the offshorebloom area; however, the nearshore bloom decreased

relatively slowly with a Chl-a level over 0.3mgm�3 basedon an average for 16–23 October. CDOM (Figure 4a, left)before Parma’s intrusion was relatively low in the studyarea. CDOM (Figure 4a, middle) displayed obvious increasein most of the study area during 8–15 October after Parma’sintrusion, especially in the coastal region. Two weeks afterthe intrusion, the CDOM (Figure 4a, right) displayed anincreasing tendency in the two bloom regions.

3.3. Rainfall and SST

[18] Before Parma’s passage, the mean rainfall was gener-ally low (<15mmd�1) in most of the study area, with a littlehigher rainfall (15–30mmd�1) in the southernmost studyarea (Figure 5a, left). During the period of Parma’s intrusioninto the study area (Figure 5a, right), the rainfall averaged for02–09 October around the typhoon’s path increased to 3–10

Figure 5. Left panels: before Typhoon Parma; right panels: during/after Typhoon Parma. (a) TRMM rain-fall (mm d�1); (b) GHRSST L4 RSSMW IR OI SST (�C); (c) absolute geostrophic current (GC; m s�1). Theblack boxes in Figures 5a and 5b delineate sampling regions of TRMM rainfall (120�E–122�E, 16�N–19�N)and SST (118.5�E–120.5�E, 18.5�N–21�N), respectively; the asterisk in Figure 5c is the sampling point ofthe GC (121.6�E, 8.8�N).

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Figure 6. Time series of ocean conditions for the chosen regions and location. (a) SST (�C); (b) rainfall(mm day�1); (c) the V-component of the geostrophic current (m s�1); (d) wind speed (m s�1); and(E) Ekman pumping velocity (10�4 m s�1).

Figure 7. Time series of 8 day-mean Chl-a and CDOM. (a, c) Averaged for the offshore box in Figure 4b(middle); and (b, d) averaged for the nearshore box in Figure 4b (middle). Note: the data shaded by theblue bars is unreliable in Figures 7b and 7d due to their sparse distribution.

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times (>45mm d�1; Figure 5a, right) of the pre-Parma rain-fall (Figure 5a, left). There was heavier rainfall (>60mmd�1)over Luzon Island, being the heaviest (>135mm d�1) inthe northwestern Luzon Island, roughly centered at(120.5�E, 16.5�N; Figure 5a, right). The SST averaged over15–30 September (Figure 5b, left) indicated that high temper-ature (>29�C) prevailed in the region before Parma. The SSTdecrease was evident after Parma’s intrusion. There was a lowSST patch (<26.5�C) near Parma’s path (Figure 5b, right)northwest of Luzon Island, roughly a decrease of 2–3�C.

3.4. Absolute Geostrophic Current

[19] There were a relatively strong cyclonic current(Figure 5c, left) west of Luzon Island and a strong northwardcurrent (i.e., the Kuroshio) north of Luzon Island based on theabsolute geostrophic current averaged for 16–30 Septemberbefore Parma’s intrusion. A weak southward current(<0.1 m s�1) was also observed north of Luzon Island to20�N. After the typhoon’s passage, the northward currentwas intensified north of Luzon Island where the CagayanRiver discharges. After Parma, the cyclonic current(Figure 5c, right) in the northwestern study area(118�E–121�E, 19�N–22�N) became much stronger too.

3.5. Time Series of Ocean Conditions

[20] The SST decrease was significant, with a maximumreduction of 3.2–3.7�C 3days after the typhoon’s passage on8 October (Figure 6a). Then, the SST increased slowly.There was low rainfall (<10mmd�1) during 15 September�01October (Figure 6b) (except on 25 September when anotherfast-moving typhoon passed by). However, intensive storm-induced rainfall accumulation of 662mm for 02–08 Octoberoccurred over the northern Luzon Island during Parma’sintrusion. The rainfall was evidently higher than that duringthe nontyphoon period. The time series of meridional compo-nent (Figure 6c) of the geostrophic current indicated that thenorthward current was strong (> 0.3m s�1) during Parma; thenthe current speed reduced, and it reversed direction immediatelyafter Parma’s passage.[21] The wind speed (<8m s�1) was generally weak with

obvious diurnal variation during the pre- and post-Parmaperiods (Figure 6d). The wind speed was relatively higher(>12m s�1) during the typhoon’s lingering over the studyarea. Thus, the mean wind speed during this period was only~1.5 times of that before Parma. However, the EPV(Figure 6e) was low during the periods without Parma anddramatically high during Parma, with an estimated cumulative

Figure 8. Vertical profiles of (a) the climatological nitrates in September, (b) temperature (�C), (c) salinity(psu), and (d) density (st).

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vertical displacement of ~47.5m based on the area-averagedEPV and Parma’s lingering time (3 to 5 October).[22] Before Parma’s passage, there were generally low

concentrations of CDOM (Figure 7; on average, ~1.4 forthe offshore region and ~2.3 for the nearshore region) andChl-a (on average, <0.08mgm�3 for the offshore regionand <0.4mgm�3 for the nearshore region). The peak valueof Chl-a (on average, 0.73mgm�3 for the offshore regionand 1.3mgm�3 for the nearshore region) appeared in thefirst week (08–15 October 2009) after Parma’s passage.[23] Peaks of CDOM (on average, 4.3 and 6.5 for the

offshore and nearshore regions, respectively) occurred over16–23 October, 2weeks after Parma, with a 1week lag tothe peaks of Chl-a blooms. The CDOM in the offshore bloomregion was low (<2) during the period from 29 September to15 October and only increased significantly to its peak in thesecond week after Parma’s passage. In contrast, the CDOMin the nearshore bloom region increased immediately to thelevel over 4.5 after Parma’s intrusion (i.e., on 8–15 October),double the pre-Parma CDOM. Due to limited data availability,we did not analyze the mean values of Chl-a and CDOMaveraged for 30 September to 7 October.

3.6. In Situ Observation

[24] The hydrographic profiles are available from theNational Oceanographic Data Center (NODC) of the NationalOceanic and Atmospheric Administration. The Conductivity-Temperature-Depth (CTD) data were downloaded fromhttp://www.aoml.noaa.gov. We used only the CTD data ofthree stations at (119.8�E, 21.09�N), (119.6�E, 21.03�N),and (119.11�E, 21�N) near the offshore bloom region on24 September, 04 October, and 14 October, respectively. Inthis region, the climatological nitrate in September (Figure 8a)increases with depth below 50m. The temperature and salinityprofiles (Figures 8b–8d) show clear changes before, during,and after Parma. The MLD was ~20m with high SST over29�C on 24 September before Parma. The MLD deepened toabout 56m on 4 October with an SST of below 29�C. AfterParma on October 14, although the MLD decreased obviouslyto 16m, the isotherms of 20–27�C, the isohalines of 33.5–34 psu, and the isopycnals of 22–24 kgm�3 shoaled by about50m compared with those before/during Parma, roughly con-sistent with the cumulative upwelling distance suggested bythe EPV. This consistency suggests that the Ekman pumpingassociated with the Parma’s wind stress curls is the primarycause for the isotherm, isohaline, and isopycnal shoaling, nu-trient upwelling, and therefore phytoplankton bloom.

4. Discussion

[25] We observed two Chl-a blooms near Luzon Straitafter the passage of Typhoon Parma: (1) an offshore Chl-aincrease northwest of Luzon Island (the upper box inFigure 4b, middle) and (2) a nearshore Chl-a bloom nearthe Cagayan River north of Luzon Island.

4.1. Offshore Phytoplankton Bloom

[26] The increase of the offshore Chl-a occurred afterParma’s passage, instead of an immediate response as thetyphoon passed by, different from the quick drop in SST(Figures 5b (right) and 6a). The CDOM maxima laggingthe Chl-a maxima by ~8 days was mainly produced by

phytoplankton decomposition [Sathyendranath, 2000; Zhanget al., 2009]. Hu et al. [2006] found that CDOM maximalagged pigment maxima by 2–4weeks in the central NorthAtlantic Ocean through investigating a connection betweenchlorophyll and CDOM. The difference in the lag time be-tween our study andHu et al.’s [2006] may result from higherphytoplankton turnover in tropical oceans as well as differentphytoplankton structures [Behrenfeld and Falkowski, 1997].The lag phenomena (Figure 7d) implied also that the offshoreChl-a increase was not induced directly by entrainmentmixing from a preexisting subsurface chlorophyll maximum.It was unlikely that the Chl-a increase was induced by hori-zontal transportation from the coastal water, since a lowerChl-a patch was observed between the coastal and offshoreblooms. Thus, the offshore Chl-a increase was probably aphytoplankton bloom due to phytoplankton growth sustainedby new nutrients brought into the euphotic zone from below,primarily through upwelling and supplemented by mixingentrainment.[27] Why did the offshore bloom appear northwest of

Luzon Island, where the maximum wind speed was about30m s�1 only? Typhoons were much stronger in previousstudies on the responses of phytoplankton blooms totyphoons in the SCS [Lin et al., 2003; Zhao et al., 2008;Zheng and Tang, 2007]. However, according to the resultsof Zhao et al. [2008], the translation speed of a typhoon isalso a key factor that affects phytoplankton bloom. Parmawas a slow-translation storm in the study region; therefore,the cumulative effect of entrainment and upwelling couldbe significant. A recent study has shown that the typhoonsize is also an important parameter to determine the ocean’sresponse to a typhoon [Lin, 2012]. Parma has generally agale force wind radius over 130 km in the region, accordingto data issued by the Japan Meteorological Agency (JMA)(http://agora.ex.nii.ac.jp). Consequently, the influence ofParma on the bloom in the region could last 2.5 days, in viewof its mean slow-translation speed of 1.6m s�1 and itsroundabout route during the period. The accumulateddisplacement of typhoon-induced upwelling (based on theEPV integration from 3 to 5 October) was about 47.5m inthe offshore bloom region. According to the geostrophicadjustment theory [Gill, 1982], the potential wind-inducedupwelling velocity and mixing are only fully developed aftera time longer than the geostrophic adjustment time (i.e., theinertial period). The forcing time (~60 h) in the present studywas much longer than the geostrophic adjustment time(T= 35 h for the latitude of 20�N where the center of thebloom was). Moreover, the preexisting cold-core eddy/coldwater may strengthen the upper ocean dynamics and nutrientresponses with significant increase of nutrient concentrationafter the typhoon passage [Lin et al., 2009; Liu et al., 2009].Thus, the upwelling/mixing processes can be wellestablished in the offshore region. According to the climato-logical vertical profile of WOA 09 (Figure 8a), nitrate inSeptember is nearly constant above 50m and increases withdepth below 50m. In other words, the additional upwardtransport of nutrients into the surface layer could only occurwhen the depth of mixing was deeper than 50m. Upwelledwater with rich nutrients from below 50m depth duringParma as indicated by shoaling isohalines, isotherms, andisopycnals (Figures 8b–8d) can be critical to the offshorebloom. Therefore, we hypothesize that the wind-induced

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upwelling (Ekman pumping) transported deeper waterwith rich nutrients into the upper layer, and then thenutrients reached surface layer through the wind-inducedentrainment mixing, triggering the surface phytoplanktonbloom in the region.

4.2. Nearshore Chl-a Bloom

[28] The nearshore Chl-a bloom (lower box in Figure 4b,middle) appeared near the northern tip of Luzon Island,where the Cagayan River Estuary, the longest and largestin Luzon Island, lies. The sharply increasing rainfall(Figure 6b) in the northern Luzon Island was observed withthe total rainfall of about 600mm during 02–08 October,and the highest daily rainfall over 200mm occurred on3 October (Figure 6b). The huge precipitation could causea significant increase of river discharge during Parma.Figure 4a (middle) may indicate that the greater volume ofnutrient-rich water from terrestrial runoff with high concentra-tion of CDOM was transported to the region. During Parma,the GC was strong (Figure 7c) and northward, and afterParma, the GC was weak or southward. These changes ofsurface circulation could firstly carry nutrient-rich water intothe nearshore region and then cause high nutrient-rich waterto spread northward, which was favorable to phytoplanktonblooms. Due to the steep topography and favorable currentconditions during Parma (Figure 7c), the transport of runofffrom this watershed into the ocean would have been rapid.Moreover, the weak wind speed, EPV, and weak sea-surfacecooling in the nearshore region (Figure 5b, right) all impliedthat wind-induced upwelling or entrainment mixing wasweak. On the other hand, the runoff had likely been dischargedfrom northern Luzon Island into this nearshore area, wherephytoplankton and CDOM both increased significantly(Figure 4). Although the high level of CDOM may cause anoverestimation of the Chl-a concentration, it suggests favor-able conditions for phytoplankton with an increased load ofnutrient of terrestrial origin.[29] Moreover, the surface current north of Luzon Island

was weak or southward before and after the typhoon, whilea strong northward current during the typhoon was observed(Figure 6c). This northward current could transport thecoastal water and the discharge from the estuary into thenorthern SCS. In comparison to seawater, terrestrial runoffcontains a mass of nutrients [Yin et al., 2004] and CDOM[Milliman and Meade, 1983] orders of magnitude higher,because rivers and coastal waters near coastlines can notonly carry CDOM primarily from soils but also containplankton-derived CDOM produced in rivers and estuaries,as well as anthropogenic compounds from runoff, sewagedischarge, and other effluents [Coble, 2007]. The higherCDOM (Figure 4a, middle) in the bloom region immediatelyafter the typhoon suggests that the discharged water orcoastal water with high CDOM may have intrudednorthward up to 20�N north of Luzon Island. Although datawere not available due to sparse data in the region during30 September to 7 October, the evident CDOM increase(Figure 7) for 8–15 October after the typhoon passagesuggests that the nearshore bloom region was influenced bythe terrestrial discharge. The CDOMmaxima in the nearshoreregion lagged the Chl-a maxima by ~8days, indicating asimilar phytoplankton degradation rate to that in the offshoreregion. Thus, the significant increase in terrestrial discharge

after the typhoon and the strong northward current both playedimportant roles in triggering the bloom in the nearshoreregion. Despite the large amount of rainfall, the river dischargemight not be able to spread as far from the coast without atyphoon-induced current (reflected by the Chl-a pattern;lower boxes in Figures 4b and 5c). Seaward-extendingChl-a filaments carried by typhoon-induced eddies havebeen observed before [Davis and Yan, 2004; Yuan et al.,2004; Walker et al., 2005]. Typhoon-induced rainfall dis-charge, therefore, can influence offshore water more thanthe nontyphoon rainfall discharge which tends to be con-fined to a narrower coastal zone.

5. Conclusion

[30] Two typhoon-induced phytoplankton blooms wereobserved near Luzon Strait where Parma was during theweak-intensity and slow-moving stage: one offshore westof the central Luzon Strait and other nearshore north ofLuzon Island. The CDOM maxima in two bloom areaslagged the Chl-a maxima by ~8 days. The offshore bloomwas likely triggered by wind-induced upwelling of nutrientsand mixing entrainment in view of Parma’s longer lingeringtime, with the former playing a more important role. Thenearshore bloom was likely due to the increased dischargefrom the Cagayan River Estuary supported by typhoon-induced strong precipitation and favorable variation ofcurrent directions during the typhoon.

[31] Acknowledgments. The present research was supported by theNational Natural Science Foundation of China (Grant number: 41006070,41176011, and U0933001) and the Canadian Space Agency GovernmentRelated Initiative Program (GRIP). We thank NASA’s Ocean ColorWorking Group for providing Modis and SeaWiFS data, Remote SensingSystems for TMI-AMSRE sea-surface temperature and QuikSCAT wind-vector data, the Physical Oceanography Distributed Active Archive Center(PO.DAAC) for QuikScat wind stress, GES DAAC for TRMM accumulatedrainfall data, and the Colorado Center for Astrodynamics Research (CCAR)Altimeter Data Research Group for sea-level anomaly data.

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