A Case Study of Typhoon Mangkhut (2018) Past Over the Northern South China Sea

remote sensing

Technical Note Spatiotemporal Distributions of Ocean Color Elements in Response to Tropical Cyclone: A Case Study of Typhoon Mangkhut (2018) Past over the Northern South China Sea

Junyi Li 1,2, Quanan Zheng 1,3, Min Li 1,2, Qiang Li 1 and Lingling Xie 1,2,*

1 Laboratory of Coastal Ocean Variation and Disaster Prediction, College of Ocean and Meteorology, Guangdong Ocean University, Zhanjiang 524088, China; [email protected] (J.L.); [email protected] (Q.Z.); [email protected] (M.L.); [email protected] (Q.L.) 2 Key Laboratory of Climate, Sources and Environments in Continent Shelf Sea and Deep Ocean, Zhanjiang 524088, China 3 Department of Atmospheric and Oceanic Science, University of Maryland, College Park, MD 20742, USA * Correspondence: [email protected]

Abstract: The ocean color elements refer to total suspended sediment (TSS) and chlorophyll-a (Chl-a), which are important parameters for the marine ecological environment. This study aims to examine the behavior of ocean color elements in response to a tropical cyclone in the case of typhoon Mangkhut (2018), which passed over the northern South China Sea (NSCS) on 16 September 2018, using satellite

multi-sensor observations, Argo ﬂoat proﬁles, and tidal gauge sea level data. The results indicate that typhoon Mangkhut (2018) resulted in TSS and Chl-a concentrations increasing, with the spatial

Citation: Li, J.; Zheng, Q.; Li, M.; and timing behavior different in the offshore, shelf, and basin areas. In the offshore area from the Li, Q.; Xie, L. Spatiotemporal coast to isobath 50 m, the mean TSS concentration, i.e., CTSS, reached 13.9 mg/L on 18 September Distributions of Ocean Color 2018, two days after typhoon landfall, against about 3.5 mg/L before typhoon landfall. In the shelf

Elements in Response to Tropical area with depths from 50 m to 100 m, the mean CTSS reached 2.5 mg/L, against about 0.8 mg/L Cyclone: A Case Study of Typhoon before typhoon landfall. In the basin area with depths of 100 m and beyond, the mean CTSS had Mangkhut (2018) Past over the only a little ﬂuctuation. On the other hand, in the offshore area, the mean Chl-a concentration, i.e., Northern South China Sea. Remote 3 3 CChl-a, was 7.3 mg/m on 21 September, ﬁve days after typhoon landfall, against 2.4 mg/m as the Sens. 2021, 13, 687. https://doi.org/ monthly mean value. Furthermore, TSS concentrations favorable for Chl-a bloom range from 6 to 10.3390/rs13040687 3 3 7 mg/L in this area. In the shelf area, the mean CChl-a increased from 0.2 mg/m to 0.6 mg/m in two days. In the basin area, the C increased from 0.1 mg/m3 to 0.2 mg/m3 during typhoon passage. Academic Editor: Chl-a Malgorzata Stramska Concurrent dynamic condition analysis results indicate that, in the offshore area, typhoon-induced solitary continental waves may play a dominant role in determining the spatial distribution features

Received: 30 December 2020 of the TSS originating from the Pearl River runoff. The Chl-a bloom delayed rather than concurrently Accepted: 6 February 2021 occurred with the terrigenous nutrient peak, which is attributed to the nonlinear relation between

Published: 13 February 2021 CChl-a and CTSS. In the shelf and basin areas, typhoon-enhanced vertical mixing and upwelling may play dominant roles in determining the spatiotemporal behavior of the TSS and the Chl-a. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in Keywords: typhoon Mangkhut (2018); Northern South China Sea; resuspended sediment; Chl- published maps and institutional afﬁl- a bloom iations.

1. Introduction Copyright: © 2021 by the authors. As typhoons pass over the ocean, tremendous wind force strongly impacts the upper Licensee MDPI, Basel, Switzerland. ocean. This process must ﬁrst enhance ocean vertical mixing and upwelling [1–3]. Mean- This article is an open access article while, the typhoon-induced upwelling and dynamic processes of the eddy adjustment are distributed under the terms and able to enhance the preexisting cyclonic eddy [4]. On the continental shelf, strong winds conditions of the Creative Commons and heavy rainfall that accompany the arrival of a typhoon directly affect the hydrody- Attribution (CC BY) license (https:// namic environment. The river runoff caused by heavy rainfall raises transporting fresh creativecommons.org/licenses/by/ water and terrestrial materials into the ocean. The winds cause high waves and increase the 4.0/).

Remote Sens. 2021, 13, 687. https://doi.org/10.3390/rs13040687 https://www.mdpi.com/journal/remotesensing Remote Sens. 2021, 13, 687 2 of 17

near-bottom currents, which resuspends the sediment on the sea floor [5]. The suspended sediment is transported to the outer shelf with the current [6]. The coastal storm surges event due to the passing typhoon generates continental shelf waves and Kelvin waves [7,8]. The wave could be amplified as the storm moves nearly parallel to the shelf, which would be over the dam. The terrestrial material would be transported to the ocean with the seawater. Weber [9] pointed out that the mean alongshore velocity associated with these waves is typically 1 cm/s, and the non-linear mean transport may be important for the transport of biological material. Furthermore, the particulate matter from land, together with sea salt aerosol from breaking waves during whitecap formation, should be injected into the shelf area with the rainfall when wind speed is significant [10–12]. These processes would increase the concentration of the suspended sediment in the ocean. The South China Sea (SCS) is a hallway of Pacific Ocean typhoons and a local typhoon birthplace. There is an average of 6.0 typhoons a year that pass over the SCS, and among them, 1.3 originate locally [13]. Shang et al. [14] investigated a Chl-a bloom induced by typhoons in the SCS, and found that typhoon Lingling (2001) induced a large patch of enhanced Chl-a concentration of 0.37 mg/m3 against the background level of 0.08 mg/m3. Chen et al. [3] investigated the ocean biological and physical responses to typhoon Megi and found that a Chl-a bloom was triggered by strong vertical mixing and upwelling. Pan et al. [2] found that the Chl-a blooms during a typhoon event may be attributed to multiple factors related to the ocean dynamic conditions and cyclone characteristics. Satellite remote sensing observations are a powerful data source for investigating characteristics and mechanisms of ocean color element response to typhoons. In particular, the Soil Moisture Active Passive (SMAP) sensor provides the sea surface salinity (SSS) distribution data, which contain information about the river runoff spreading on the continental shelf. This case study aims to reveal the ocean color element responses to the passage of typhoon Mangkhut (2018) over the NSCS in September 2018, based on satellite multi-sensor observations, Argo float profile data, and tidal gauge sea level data. This paper is organized as follows. The next section gives a brief introduction to the data and methodology, including algorithms for the retrieval of the Chl-a and the total suspended sediment (TSS) concentrations from satellite observations. Section3 analyzes the spatiotemporal distribution feature of the TSS and the Chl-a in the NSCS during the typhoon Mangkhut (2018) passage. Section4 analyzes the behavior of Chl-a blooms in three subareas: the offshore, shelf, and basin areas. Section5 contains a summary.

2. Data and Methodology 2.1. Study Area The SCS is the largest semi-enclosed marginal sea of the northwest Paciﬁc Ocean. The area of the continental shelf and island occupies 48% of the total area [15]. In the NSCS, the width of the continental shelf, with depths shallower than 200 m extending from the coast, is about 200 km. The depth contour is generally parallel to the coastline. The Pearl River contributes the biggest runoff for this shelf. The study area occupies an area with boundary lines on two sides about 200 km to the typhoon track. According to the geological features of the shelf and traditional Chl-a distribution, the study area is divided into three subareas: the offshore, shelf, and basin areas, as shown in Figure1. The depths of the offshore area are shallower than 50 m. The shelf area is located on the continental shelf shallower than 100 m. The basin area extends from an isobath of 100 m to the SCS deep basin, with depths near 3000 m. The average distance from the shelf and basin area to the coastline are 70 km and 140 km, respectively.

2.2. Typhoon Mangkhut (2018) Super typhoon Mangkhut (2018) formed in the central Paciﬁc Ocean as a tropical depression at 11:00 UTC on 7 September 2018. It rapidly strengthened into a typhoon, and moved westward to the SCS, as shown in Figure1. The size of typhoon Mangkhut Remote Sens. 2020, 12, x FOR PEER REVIEW 3 of 18 Remote Sens. 2021, 13, 687 3 of 17 Super typhoon Mangkhut (2018) formed in the central Pacific Ocean as a tropical depression at 11:00 UTC on 7 September 2018. It rapidly strengthened into a typhoon, and moved westward to the SCS, as shown in Figure 1. The size of typhoon Mangkhut (2018) was(2018) larger was than larger 1000 than km, 1000 and km, it sustained and it sustained wind speeds wind above speeds 65 above m/s for 65 a m/s maximum for a maximum of 2 min.of 2 The min. minimum The minimum central centralpressure pressure was less wasthan less910 hPa. than It 910 landed hPa. on It the landed south on coast the of south Chinacoast ofwith China a wind with speed a wind higher speed than higher 48 m/s thanby 9:00 48 UTC m/s on by 16 9:00 September UTC on 162018. September Typhoon 2018. MangkhutTyphoon Mangkhut(2018), the (2018),strongest the typhoon strongest that typhoon landed that on China landed in on 2018, China brought in 2018, heavy brought rainfallheavy of rainfall 389 mm of and 389 a mm high and storm a highsurge storm water surgelevel of water 2 m. The level storm of 2 surge m. The superposed storm surge onsuperposed the high waves, on the pushed high waves, by a strong pushed wind by athat strong caused wind enormous that caused damage enormous to the damageprop- to ertiesthe properties along the alongcoast of the China. coast of China.

FigureFigure 1. 1. MODISMODIS visible visible band band image image of oftyphoon typhoon Mangkhut Mangkhut (2018) (2018) at 3:10 at 3:10 UTC UTC on on16 September 16 September 2018. 2018.Green Green curve curve with with blue blue dots dots (every (every 3 h) 3 representsh) represents the the typhoon typhoon track. track. Red Red lines lines represent represent concurrent concurrentsatellite altimeter satellite altimeter tracks. Pink tracks. polygons Pink polygons represent represent the study the areastudy consisting area consisting of three of three subareas: the subareas:offshore, the shelf, offshore, and basin shelf, areas.and basin Black areas. triangles Black triangles along the along coastline the coastline represent represent tidal gauge tidal stations gaugeZhapo, stations Hongkong, Zhapo, andHongkong, Shenzhen. and Shenzhen. The red triangle The red represents triangle represents the landfall the landfall point of point the of typhoon the typhoon center in Taishan, Guangdong, China. Black curves show trajectories of the Argo center in Taishan, Guangdong, China. Black curves show trajectories of the Argo ﬂoats, and black floats, and black triangles A, B, C, and D represent the float locations on 9, 13, 17, and 21 Septem- bertriangles 2018, respectively. A, B, C, and Numerals D represent on thethe ﬂoatisobaths locations are in onm. 9, 13, 17, and 21 September 2018, respectively. Numerals on the isobaths are in m. The track of typhoon Mangkhut (2018) was obtained from the Tropical Cyclone Data CenterThe of the track China of typhoon Meteorological Mangkhut Administ (2018)ration was obtained(CMA) (http://tcdata.typhoon.org.cn) from the Tropical Cyclone Data [16].Center The of data the of China typhoon Meteorological center location Administrations, minimum pressure, (CMA) ( http://tcdata.typhoon.org.and two-minute mean maximumcn)[16]. The sustained data of wind typhoon near centerthe tropical locations, cyclone minimum center were pressure, gathered and every two-minute 6 h and 3 mean hmaximum after it entered sustained the SCS. wind near the tropical cyclone center were gathered every 6 h and 3 h after it entered the SCS. 2.3. Satellite Multi-Sensor Data 2.3. Satellite Multi-Sensor Data The Chl-a concentration data from 1 to 30 September 2018 are downloaded from http://oceandata.sci.gsfc.nasa.gov/.The Chl-a concentration data The from dataset 1 to is 30 a level September two product, 2018 arewith downloaded a spatial reso- from lutionhttp://oceandata.sci.gsfc.nasa.gov/ of 1 km derived from an empirical. The algorithm dataset and is athe level ocean two color product, index with(OCI) a for spatial Terraresolution and Aqua of 1 kmMODIS derived sensors from [17]. an empiricalThe data from algorithm the two and platforms the ocean are color merged index for (OCI) improvingfor Terra and the Aquacoverage MODIS of the sensors Chl-a data [17 ].[18] The. In data this fromstudy, the the two average platforms Chl-a areconcentra- merged for tionimproving is calculated the coverage by the following of the Chl-a algorithm data [18 [19]:]. In this study, the average Chl-a concentration is calculated by the following algorithm [19]: 𝐶 +𝐶 𝐶 = (1) 2 Cchl−aTerra + Cchl−aAqua C − = (1) chl a 2 C C where chl-aTerra and chl-aAqua are the Chl-a concentration data derived from the Terra and Aqua observations, respectively. The monthly mean chlorophyll-a concentration from 2002 Remote Sens. 2021, 13, 687 4 of 17

to 2016, with a spatial resolution of 5 km, is also used to calculate the mean state of the chlorophyll-a in the SCS. The remote sensing reflectance (Rrs) at 443, 488, 555, and 645 nm with a spatial resolution of 1 km was obtained from the NASA Ocean Biology Processing Group, which could be used to calculate the TSS concentration. The sea surface temperature (SST) data from 1 to 26 September 2018 are downloaded from https://podaac-opendap.jpl.nasa.gov/. The dataset is a level two product from Advanced Microwave Scanning Radiometer-2 (AMSR-2) on board the Global Change Observation Mission-W1 (GCOM-W1). The temporal resolutions of AMSR-2 at a frequency of 6.9 GHz are once every two days, and the spatial resolution is 25 km [20]. Since the microwave has a certain penetration performance through cloud cover, the data have advantages for ocean observation, particularly during typhoon passage. The sea surface wind data containing measurements of the wind direction and wind speed at 10 m above the sea surface are obtained from http://oceandata.sci.gsfc.nasa. gov/. The data are derived from level two processing of scatterometer data with a spatial resolution of 25 km, measured by the Advanced Scatterometer (ASCAT) instrument on EUMETSAT Metop-A satellite. The level two SSS observations of the SCS in September 2018 derived from the soil moisture active passive (SMAP) mission are downloaded from http://oceandata.sci.gsfc. nasa.gov/[ 21]. The SMAP dataset is a gridded product with a temporal resolution of eight days and a horizontal resolution of 40 km. The along-track significant wave height (SWH) is produced and distributed by the Copernicus Marine Environment Monitoring Service (CMEMS), using altimeter along- track data of Sentinel 3a and Saral-AltiKa, with repeat ground tracks every 4 d and 35 d, respectively [22]. The temporal resolution is 1 s, and the spatial resolution is about 7 km in the study area. The eight-point moving average is applied to the data to filter out ocean processes with a length scale less than 50 km. Sentinel 3a passed over the study area twice at 2:29 UTC on 16 September and at 13:59 UTC on 19 September 2018, respectively. Saral-AltiKa passed over once at 10:39 UTC on 17 September. The Argo float profile data were obtained by the Argo float (ID 2901481) that was deployed at 16.67◦N, 116.22◦E on 28 April 2016. The float is designed to measure the temperature and salinity profiles from about 5 m to 1200 m every four days. The float drifted to the northwest of the Philippines on 13 September 2018 before the typhoon arrived. Another profile was obtained on 17 September, one day after the typhoon passed by.

2.4. TSS Retrivial Previous studies have developed various algorithms for estimating the water quality, as shown in Table1[ 23–26]. One can see that the TSS concentration can be calculated with retrieval algorithms using Rrs (443), Rrs (488), Rrs (555), and Rrs (645) data. These algorithms are applied to the data of Rrs (645) distribution on 20 September 2018, as shown in Figure2.

Table 1. TSS concentration (CTSS) retrieval models.

Order Algorithm Model

1 CTSS = −1.91 + 1140.25 × Rrs645 Miller 2 CTSS = 0.6455 + 1455.7 × Rrs645 Miller (adjusted) 3 lgCTSS = 0.6311 + 22.2158 × (Rrs555 + Rrs645) − 0.5239 × (Rrs488/Rrs555) Zhang 4 lgCTSS = 2.4618 + 0.9905 × lg(Rrs555 + Rrs645) − 1.2073 × lg(Rrs488/Rrs555) Tassan −3.9322 5 CTSS = 3.2602 × (Rrs443/Rrs555) Pan

Figure3 shows the average TSS concentration for the offshore, shelf, and ocean area using five retrieval models on 20 September 2018. One can see that the average TSS concentrations in the shelf area derived from five algorithms are similar (green curve). In the offshore area, the average TSS concentration (red curve) is about 3~7 mg/L from the Remote Sens. 2020, 12, x FOR PEER REVIEW 5 of 18 Remote Sens. 2021, 13, 687 5 of 17 mg/l. Moreover, it is obviously unreasonable that model 1 gives negative values of TSS concentration for the small values of Rrs (645). Thus, we used model 2 to calculate the TSS concentration in the study case [24]. first four models, and 24 mg/L from the fifth algorithm. Thus, the results from the first four algorithms should have more statistical weight. In the ocean area, the algorithms Table 1. TSS concentration (CTSS) retrieval models. could be divided into three categories according to the average TSS concentrations: (1) a highOrderconcentration model, i.e., theAlgorithm first two models, (2) a moderate concentrationModel model, 1 𝐶 = −1.91 + 1140.25 × 𝑅𝑟𝑠645 Miller i.e., the third and fourth models, and (3) a low concentration model, i.e., the last model. Li Miller (ad- 2 𝐶 = 0.6455 + 1455.7 × 𝑅𝑟𝑠645 et al. [12] found that the suspended sediment concentration in the deepjusted) sea basin of the SCS increaseslg𝐶 = from 0.6311 0.48 + 22.2158 to 1.4 × mg/L𝑅𝑟𝑠555 during + a𝑅𝑟𝑠645 typhoon − 0.5239 ×passage.𝑅𝑟𝑠488/ Moreover, the observed 3 Zhang TSS concentration from our cruise𝑅𝑟𝑠555 investigation in August 2020 in the north of the SCS is lg𝐶 = 2.4618 + 0.9905 × lg𝑅𝑟𝑠555 + 𝑅𝑟𝑠645 − 1.2073 ~0.84 mg/L. Moreover, it is obviously unreasonable that model 1 gives negativeTassan values of × lg𝑅𝑟𝑠488/𝑅𝑟𝑠555 TSS concentration for the small values of Rrs (645).. Thus, we used model 2 to calculate the 5 𝐶 = 3.2602 × 𝑅𝑟𝑠443/𝑅𝑟𝑠555 Pan TSS concentration in the study case [24].

FigureFigure 2. 2. RrsRrs (645)(645) (sr−1 (sr) derived−1) derived from MODIS from imag MODISes on images 20 September on 20 2018. September Pink polygons 2018. repre- Pink polygons Remote Sens. 2020, 12, x FOR PEER REVIEWrepresentsent the study the area study consisting area consisting of three suba of threereas: subareas:the offshore, the shelf, offshore, and basin shelf, areas. and basin areas. 6 of 18

Figure 3. Average TSS concentration using ﬁve retrieval models for offshore, shelf, and ocean areas Figureon 20 3. September Average TSS 2018. concentration using five retrieval models for offshore, shelf, and ocean areas on 20 September 2018.

2.5. Tidal Gauge Data The de-tided sea level data measured at tidal gauge stations Shenzhen, Hong Kong, and Zhapo from 1 to 25 September 2018 were used to calculate the sea level anomaly (SLA) with respect to a 25-day mean sea level. The temporal resolution is 1 h.

2.6. Ekman Pumping The concurrently strong winds produce an Ekman transport in the ocean surface layer, which leads to an Ekman pumping. The velocity of upwelling is calculated by the following equations [27]: 𝑊𝑒 = ∇×𝜏, (2) where We is the velocity of Ekman pumping and ρ, f, and τ are the seawater density, Cor- iolis parameter, and wind stress, respectively. The wind stress curl is:

∇×𝜏= − 𝜏 cos 𝜑, (3)

where R is the earth radius, φ and λ are the geographic latitude and longitude, respectively, and τx and τy are the zonal and meridional wind stress, respectively. In order to calculate the wind stress curl, a finite difference scheme is applied [3]:

, , , , ∇×𝜏, = − , (4) ,

The wind stress curl is [28]:

𝜏=𝜌𝐶𝑈|𝑈|, (5)

where ρa, CD, and U are the air density, drag coefficient, and 10 m wind, respectively.

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2.6. Ekman Pumping The concurrently strong winds produce an Ekman transport in the ocean surface layer, which leads to an Ekman pumping. The velocity of upwelling is calculated by the following equations [27]: 1 We = (∇ × τ), (2) ρ f where We is the velocity of Ekman pumping and ρ, f, and τ are the seawater density, Coriolis parameter, and wind stress, respectively. The wind stress curl is: 1 ∂τy ∂ ∇ × τ = − (τ cos ϕ) , (3) R cos ϕ ∂λ ∂ϕ x

where R is the earth radius, ϕ and λ are the geographic latitude and longitude, respectively, and τx and τy are the zonal and meridional wind stress, respectively. In order to calculate the wind stress curl, a ﬁnite difference scheme is applied [3]:

− ! 1 τy i+1,j τy i−1,j (τx cos ϕ)i,j+1 − (τx cos ϕ)i,j−1 ∇ × τi,j = − , (4) R cos ϕi,j 2∆λ 2∆ϕ

The wind stress curl is [28]: τ = ρaCDU|U|, (5)

where ρa, CD, and U are the air density, drag coefﬁcient, and 10 m wind, respectively.

3. Spatial Distribution Analysis The TSS and Chl-a time series images during the typhoon Mangkhut (2018) passage are shown in Figure4. From Figure4a, one can see that on 15 September 2018, one day before typhoon landfall, the high TSS values in the offshore area were concentrated in the Pearl River Estuary. The mean value was about 3.5 mg/L with the maximum of 15.0 mg/L. This means that the rushing river water is the primary source of suspended sediment. The TSS concentration in the shelf area was 0.9 mg/L, much lower than that in the estuary. The TSS data in the basin area were missing due to the heavy clouds. Figure4b shows the distribution of TSS on 18 September 2018, two days after typhoon landfall. A high-concentration TSS plume was distributed from the Pearl River Estuary to the offshore water with depths of about 70 m. The maximum TSS concentration of about 40.0 mg/L was distributed near the Hong Kong coast, located inside the Pearl River Estuary. The mean TSS concentration in the offshore area was higher than 13.9 mg/L, against 3.5 mg/L on 15 September before typhoon landfall. Meanwhile, the distribution extent of high TSS concentration was remarkably expanded to the southwest of the Pearl River Estuary. In the shelf area, the mean TSS concentration increased by three times, reaching 2.5 mg/L. Furthermore, one can see a high TSS plume with a concentration higher than 15 mg/L, ﬁve times higher than that before typhoon landfall. In the basin area, however, the mean TSS concentration increased only a little. The TSS was deposited slowly after typhoon landfall, as shown in Figure4c,d. In the offshore area, the mean TSS concentration decreased slowly from 6.7 mg/L on 20 September (Figure4c) to 6.3 mg/L on 21 September (Figure4d). In the shelf and basin areas, it remained at 0.8 and 0.9 mg/L on 20 and 21 September, respectively. Figure4e shows the distribution image of Chl-a on 15 September. One can see that, in the offshore area, the Chl-a concentration of about 15 mg/m3 was distributed in the Remote Sens. 2021, 13, 687 7 of 17

estuary and along the coast. In the shelf area, it decreased to about 0.5 mg/m3. In the basin Remote Sens. 2020, 12, x FOR PEER REVIEW 8 of 18 area, it further decreased to less than 0.3 mg/m3.

FigureFigure 4. 4. TimeTime series series images images of of ( (aa––dd)) TSS TSS concentration concentration and and ( (ee––hh)) Chl-a Chl-a concentration concentration in in the the NSCS NSCS onon 15, 15, 18, 18, 20, 20, and and 21 21 September September 2018. 2018. Three Three polygons polygons from from the the coast coast to to the the deep deep basin basin are are defined deﬁned asas the the offshore, offshore, shelf, shelf, and and basin basin areas, areas, respecti respectively.vely. Color Color codes codes for for TSS TSS concentration concentration and and Chl-a Chl-a concentration (logarithmic scale) are in mg/l and mg/m3, respectively. Numerals on isobaths are in concentration (logarithmic scale) are in mg/L and mg/m3, respectively. Numerals on isobaths are m. in m.

TheFigure time4f series shows of the TSS Chl-a concentrations concentration are distributionshown as red on curves 18 September. in Figure One5. From can Fig- see urethat, 5a, in one the offshorecan see that, area, in the the mean offshore Chl-a area concentration, the mean TSS was concentration 3 mg/m3, against (red 15curve) mg/m re-3 mainedon 15 September. lower than On 6 mg/l the other before hand, 15 September in the shelf and area, peaked the Chl-a up to concentration 13.9 mg/l on was18 Septem- double ber, then reduced quickly to 2.9 mg/l on 23 September. In the shelf area, it remained lower than 1 mg/l before 15 September, peaked up to 2.5 mg/l on 18 September, and decreased to 1.0 mg/l on 22 September, as shown in Figure 5b. The high standard deviations (SDVs) of TSS values in the offshore and shelf areas were greater than 10 and 1 mg/l from 18 to 22 September, indicating that the TSS concentration fluctuated considerably. In the basin

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that on September 15. Meanwhile, in the basin area, the Chl-a also bloomed, with a peaked concentration of 1.4 mg/m3. From Figure4g,h, one can see that, in the offshore area, the Chl-a bloom delayed to 20 and 21 September. The maximum Chl-a concentration reached as high as 40 mg/m3 on 21 September, against 15 mg/m3 before typhoon landfall. Remote Sens. 2020, 12, x FOR PEER REVIEW The time series of TSS concentrations are shown as red curves in Figure59. of From 18 Figure5a , one can see that, in the offshore area, the mean TSS concentration (red curve) area, the mean TSS concentration only had a little fluctuation, especially during the ty- remained lower than 6 mg/L before 15 September and peaked up to 13.9 mg/L on 18 phoon passage, as shown in Figure 5c. September, then reduced quickly to 2.9 mg/L on 23 September. In the shelf area, it The time series of mean Chl-a concentrations are shown as blue curves in Figure 5. remained lower than 1 mg/L before 15 September, peaked up to 2.5 mg/L on 18 September, From Figure 5a, one can see that, in the offshore area, the mean Chl-a concentration was and decreased to 1.0 mg/L on 22 September, as shown in Figure5b. The high standard 3 3 lowerdeviations than 5 mg/m (SDVs) before of TSS 15 September. values in the It sharply offshore increased and shelf from areas 3.2 weremg/m greater on 18 thanSep- 10 3 3 temberand to 1 mg/L7.3 mg/m from on 18 21 to September, 22 September, then indicating sharply decreased that the TSS to 2.5 concentration mg/m within ﬂuctuated two days.considerably. Figure 5b shows In the that, basin in the area, shelf the area, mean the TSS mean concentration Chl-a concentration only had aincreased little ﬂuctuation, from 3 3 0.2 especiallymg/m before during typhoon the typhoon landfall passage, to 0.6 mg/m as shown after in typhoon Figure5 c.landfall. Figure 5c shows 3 that, in theThe basin time seriesarea, the of mean mean Chl-a Chl-a concentrations concentration areincreased shown asfrom blue 0.1 curves mg/m in to Figure 0.2 5. 3 mg/mFrom during Figure typhoon5a, one passage. can see that, in the offshore area, the mean Chl-a concentration was lowerThe above than 5time mg/m series3 before analysis 15 September.indicates that It sharplythe Chl-a increased blooms fromin the 3.2 offshore mg/m 3andon 18 shelfSeptember areas lagged to 7.3 by mg/mfour to3 fiveon 21 days September, behind the then TSS sharply peak. As decreased shown in to Figure 2.5 mg/m 5a,b,3 withinthe TSStwo concentration days. Figure peaked5b shows on 18 that, September, in the shelf two area, days the after mean typhoon Chl-a landfall. concentration On the increased other hand,from the 0.2 Chl-a mg/m concentration3 before typhoon in the landfalloffshore to area 0.6 mg/mpeaked3 afteron 20 typhoon September, landfall. and, Figurein the 5c shelfshows area, that,peaked in theon basin21 September, area, the meani.e., th Chl-ae Chl-a concentration blooms had increaseddelayed for from four 0.1 and mg/m five3 to days,0.2 respectively. mg/m3 during typhoon passage.

Figure 5. Time series of TSS and Chl-a concentrations for (a) the offshore, (b) shelf, and (c) basin Figureareas 5. Time in September series of 2018.TSS and Red Chl-a and blueconcentrations curves with for dots a) the and offshore, plus signs b) representshelf, and thec) basin mean ar- and the eas inSDV September of TSS and 2018. Chl-a Red concentrations, and blue curves respectively. with dots and Black plus vertical signs represent lines represent the mean passing and the times of SDVtyphoon of TSS and Mangkhut Chl-a concentrations, (2018). respectively. Black vertical lines represent passing times of typhoon Mangkhut (2018).

4. Chl-a Bloom Timing Analysis As shown in Figure 5, the Chl-a blooms in three subareas were not concurrently occurring. In this section, the mechanisms to cause Chl-a bloom timing are analyzed using multi-sensor data.

4.1. Offshore Area

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The above time series analysis indicates that the Chl-a blooms in the offshore and shelf areas lagged by four to ﬁve days behind the TSS peak. As shown in Figure5a,b, the TSS concentration peaked on 18 September, two days after typhoon landfall. On the other hand, the Chl-a concentration in the offshore area peaked on 20 September, and, in the shelf area, peaked on 21 September, i.e., the Chl-a blooms had delayed for four and ﬁve days, respectively.

4. Chl-a Bloom Timing Analysis As shown in Figure5, the Chl-a blooms in three subareas were not concurrently occurring. In this section, the mechanisms to cause Chl-a bloom timing are analyzed using multi-sensor data. Remote Sens. 2020, 12, x FOR PEER REVIEW 10 of 18 4.1. Offshore Area FigureFigure 66a–da–d showsshows thethe timetime series series images images of of the the SSS SSS distribution distribution in in the the NSCS NSCS from from 10 10to to 21 21 September September 2018. 2018. From From Figure Figure6 a,6a, one one can can see see that that on on 1010 September,September, beforebefore typhoon arrival,arrival, a alow low salinity salinity water water plume plume with with an anSSS SSS lower lower than than 30 and 30 and a length a length of about of about 150 km150 was km distributed was distributed in the in west the of west the ofPearl the Ri Pearlver Mouth. River Mouth. Figure 6b Figure shows6b that shows on that17 Sep- on tember,17 September, after typhoon after typhoon landfall, landfall, the low the SSS low water SSS water plume plume disappeared, disappeared, and instead, and instead, the majorthe major study study area was area occupied was occupied by high by SSS high wa SSSter, with water, a salinity with a salinityof 34–35. of On 34–35. 18 Septem- On 18 ber,September, the SSS recovered the SSS recovered to the level to theof that level be offore that typhoon before landfall, typhoon as landfall, shown in as Figure shown 6c. in FigureFigure 6d6c. shows Figure that6d showson 21 September, that on 21 five September, days after ﬁve typhoon days after landfall, typhoon the low landfall, SSS water the plumelow SSS reappeared water plume in the reappeared offshore area. in the It offshore expanded area. to Itabout expanded 300 km to and about spread 300 km south- and westwardspread southwestward along the coast, along which the resulted coast, which in heavy resulted rainfall in of heavy 389 mm, rainfall with of the 389 maximum mm, with hourlythe maximum rainfall intensity hourly rainfall reaching intensity 74 mm reaching along the 74 coast mm alongof Guangdong the coast ofduring Guangdong the ty- phoonduring Mangkhut the typhoon (2018) Mangkhut passage (2018) [29]. passageThe river [29 discharges]. The river of dischargesfresh water of and fresh terrigenous water and nutrientsterrigenous should nutrients be favorable should be to favorablephytoplank to phytoplanktonton blooms [30]. blooms In addition, [30]. In the addition, typhoon- the inducedtyphoon-induced local vertical local verticalmixing mixingand upwelling and upwelling could could provide provide extra extra vertical vertical nutrient nutrient transporttransport to to further further enhance enhance the the ocean ocean primary primary prod productivityuctivity [31]. [31].

FigureFigure 6. 6. SeaSea surface surface salinity salinity (SSS) (SSS) distri distributionbution images inin thethe NSCSNSCS onon (a) 10, (bb)) 17, 17, c ()c )18, 18, and and d ()d 21) 21 SeptemberSeptember 2018. 2018. Color Color codes codes are are in in practical practical salinity salinity units units (PSU). (PSU). Numerals Numerals on on isobaths isobaths are are in in m. m.

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Figure6c shows a low salinity water plume, with the SSS lower than 30 and a length of about 150 km, distributed in the west of the Pearl River Mouth on 18 September. On the other hand, Figure4b shows high concentration TSS water of a mean concentration higher than 15 mg/L distributed in the same area. A combination of above two observations reveals that the low salinity and high TSS water plume was originating from the Pearl River runoff, which contains rich terrigenous nutrients. However, the Chl-a bloom did not happen concurrently with high concentration nutrient inputs, instead, it was delayed, reaching a maximum of 40.0 mg/m3 on 21 September, about ﬁve days after typhoon landfall. Pan et al. [32] also found a similar Chl-a bloom delay phenomenon by numerical modeling. To explain the mechanisms for the Chl-a bloom delay phenomenon, we propose the following scenario. In the view of ocean primary productivity, as chlorophyll carriers, Remote Sens. 2020, 12, x FOR PEER REVIEWphytoplankton blooms rely on two key conditions: nutrient concentration increase11 of 18 and underwater sunlight radiance intensiﬁcation. During typhoon landfall, heavy rainfall causescauses the rivers the rivers to discharge to discharge a sharply a sharply increa increasedsed quantity quantity of sediments of sediments into the into offshore the offshore water.water. The Theeffects effects of terrigenous of terrigenous sediments sediments on the on marine the marine ecologic ecologic environment environment are two- are two- fold:fold: 1) raising (1) raising the nutrient the nutrient supply supply level, level,and 2) and increasing (2) increasing the turbidity the turbidity of seawater. of seawater. Point Point one oneis favorable is favorable for phytoplankton for phytoplankton blooms, blooms, while while point pointtwo restrains two restrains the phytoplankton the phytoplankton bloombloom by the by attenuation the attenuation of sunlight of sunlight radiance radiance in seawater. in seawater. In addition, In addition, heavy heavycloudiness cloudiness and andheavy heavy rain rainattenuate attenuate the sunlight the sunlight incident incident on the on sea the surface. sea surface. Thus, the Thus, phytoplankton the phytoplankton bloombloom must must delay delay for a forcouple a couple of days of daysuntil untilthe TSS the redeposits TSS redeposits to a favorable to a favorable level. level. Figure 7 shows a curve of the Chl-a concentration vs. TSS concentration in the off- Figure7 shows a curve of the Chl-a concentration vs. TSS concentration in the offshore shore subarea from 18 to 23 September 2018, after typhoon landfall on the coast near the subarea from 18 to 23 September 2018, after typhoon landfall on the coast near the Pearl Pearl River Estuary on 16 September. One can see that the TSS concentrations favorable River Estuary on 16 September. One can see that the TSS concentrations favorable for Chl-a for Chl-a bloom range from 6 to 7 mg/l in the study case. bloom range from 6 to 7 mg/L in the study case.

FigureFigure 7. Chl-a 7. Chl-a concentration concentration vs. TSS vs. concentration TSS concentration in the in offshore the offshore area from area from18 to 1823 toSeptember 23 September 2018, 2018,after after typhoon typhoon Mangkhut Mangkhut (2018)(2018) landfalllandfall on thethe coast near near the the Pearl Pearl River River Estuary Estuary on on 16 16 Sep- September. tember. Figure8 shows the time series of SLA derived from tidal gauge data measured at coastalFigure stations8 shows in the September time series 2018. of AtSLA station derived Shenzhen, from tidal the gauge SLA reached data measured 2.5 m at 4:00 at UTC, coastal5 h stations before typhoon in September landfall 2018. on At 16 Septemberstation Shenzhen, (no data the after SLA that). reached At station2.5 m at Hong 4:00 Kong, UTC,the 5 SLAh before showed typhoon a maximum landfall on surge 16 September of 1.91 m at (no 7:00 data UTC, after 2 hthat). before At typhoonstation Hong landfall on Kong,16 the September. SLA showed Station a maximum Zhapo, which surge is of located 1.91 m inat the7:00 south UTC, of2 h the before typhoon typhoon track, land- showed a fall onsurge 16 September. of 1.17 m at Station 9:00 UTC, Zhapo, just thewhich time is forlocated typhoon in the landfall. south of The the time typhoon lags of track, the SLA at showedthe threea surge stations of 1.17 imply m at 9:00 that UTC, there just was th ae typhoon-forcedtime for typhoon solitarylandfall. continental The time lags shelf of wave the SLApropagating at the three southwestward stations imply along that the there coastline was a [typhoon-forced33]. The waves solitary carrying continental low salinity and shelfhigh wave TSS propagating concentration southwestward water discharged along from the coastline the Pearl [33]. River The spread waves southwestward carrying low along salinitythe coast.and high TSS concentration water discharged from the Pearl River spread southwestward along the coast.

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FigureFigure 8. 8.SLA SLA time time series series at at tidal tidal gauge gauge stations stations Shenzhen Shenzhen (red (red curve), curve), Hong Hong Kong Kong (blue (blue curve), curve), and and Zhapo Zhapo (black (black curve) curve) in Septemberin September 2018. 2018.

4.2.4.2. Shelf Shelf Area Area FigureFigure9 shows9 shows time time series series images images of of SST SST and and sea sea surface surface wind, wind, as as well well as as latitudinal latitudinal distributionsdistributions of of the the along-track along-track SWH SWH in in the the NSCS NSCS after after typhoon typhoon Mangkhut Mangkhut (2018) (2018) passage passage onon 16, 16, 17, 17, and and 18 18 September September 2018. 2018. One One can can see see a a remarkable remarkable SST SST cooling cooling event event (about (about 3 3 to to 55◦ C)°C) along along the the typhoon typhoon track. track. In In the the shelf shelf area, area, the the wind wind speed speed was was over over 30 30 m/s m/s during during typhoontyphoon passage, passage, and and decreased decreased to to lower lower than than 10 10 m/s m/s after after typhoon typhoon landfall. landfall. However, However, thethe highly highly variable variable wind wind directions directions were were not not favorable favorable for for the the seaward seaward Ekman Ekman transport. transport. Meanwhile,Meanwhile, the the sea sea state state was was coming coming down down from from the SWH,the SWH, from greaterfrom greater than 11 than m to 11 about m to 2about m. 2 m. FigureFigure 10 10d–fd–f showsshows the Ekman Ekman pumping pumping velocity velocity on on 15, 15, 16, 16,and and 18 September 18 September 2018, 2018,respectively. respectively. One can One see can that see the that upwelling the upwelling on 15 September on 15 September was weak was (about weak 0.3 (about × 10-6 0.3m/s)× 10on− 6them/s continental) on the continental shelf of the shelf NSCS. of theOn NSCS.16 September, On 16 September, when typhoon when Mangkhut typhoon Mangkhut(2018) reached (2018) the reached shelf area, the shelfthe upwelling area, theupwelling was apparently was apparently stronger. The stronger. velocity The of ve- the locityupwelling of the was upwelling as high was as 8 as × high10-6 m/s, as 8 which× 10− 6increasedm/s, which about increased twenty about times, twenty similar times, to the similarresults tofrom the mooring results from observation mooring analysis observation for typhoon analysis Washi for typhoon (2005) [34]. Washi Three (2005) days [ after34]. Threetyphoon days passage, after typhoon the Ekman passage, pumping the velocity Ekman pumpingreturned to velocity the same returned level as 15 to September the same levelin the as shelf 15 September area. We incan the also shelf see area. that Wethe canvelocity also seewas that negative the velocity (i.e., downwelling) was negative in (i.e., the downwelling)left side of the in typhoon the left sidetrack, of which the typhoon should track,be the which reason should that SST be thedropped reason in that the SSTright droppedside of the in thetyphoon right track, side of and the was typhoon much track, larger and than was that much in the larger left side than [35]. that in the left side [35Figure]. 5b shows that the concentration of Chl-a increased three times from 0.2 mg/m3 3 on 15Figure September,5b shows before that the typhoon concentration landfall, of to Chl-a 0.6 mg/m increased3 on three18 September, times from only 0.2 mg/mtwo days 3 onafter 15 September,typhoon landfall, before and typhoon sustained landfall, a level to 0.6higher mg/m thanon 1.0 18 mg/m September,3 for four only days. two Thus, days it 3 afteris reasonable typhoon landfall,to attribute and this sustained immediate a level Chl- highera bloom than to 1.0 the mg/m direct forresponse four days. of the Thus, shelf itarea is reasonable to typhoon to passage. attribute The this vertical immediate mixing Chl-a enhanced bloom toby the the direct sea surface response waves, of the with shelf the areaSWH to as typhoon high as passage. 11 m and The upwelling vertical induced mixing enhanced by typhoon by pumping, the sea surface brought waves, the phyto- with theplankton SWH asin highthe subsurface as 11 m and layer upwelling up to the induced surface bylayer typhoon within pumping,a short time, brought and main- the phytoplanktontained the Chl-a in bloom the subsurface for four days layer [36]. up The to the direct surface injection layer of within TSS transported a short time, by and the maintainedstrong winds, the Chl-atogether bloom with for sea four spray days aero [36].sols The into direct the injection atmosphere of TSS through transported breaking by the strong winds, together with sea spray aerosols into the atmosphere through breaking waves during whitecap formation, should be accounted for such a significant resus- waves during whitecap formation, should be accounted for such a signiﬁcant resuspension pension of sea floor sediment [10,11]. Concurrently, the TSS concentration increased by of sea ﬂoor sediment [10,11]. Concurrently, the TSS concentration increased by 3.3 times, 3.3 times, from 0.8 mg/l to 2.5 mg/l, as shown in Figure 5b, and high SSS water with a from 0.8 mg/L to 2.5 mg/L, as shown in Figure5b, and high SSS water with a salinity of salinity of 34–35 occupied the major study area, as shown in Figure 6b, providing addi- 34–35 occupied the major study area, as shown in Figure6b, providing additional evidence tional evidence for the above interpretation. for the above interpretation.

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FigureFigure 9. 9.(a– (ca))–( Timec) Time series imagesseries images of SST (color of SST codes) (color and codes) sea surface and wind sea (arrows)surface inwind the NSCS(arrows) on 16, in 17, the and 18 SeptemberNSCS on 2018. 16, Red17, and lines 18 represent September satellite 2018. altimeter Red tracks lines in repr (a) Sentinelesent satellite 3a, passed altimeter over at 2:29 tracks UTC on in 16 a) September, Sentinel (b3a,) Saral-AltiKa, passed over passed at 2:29 over atUTC 10:39 on UTC 16 on September, 17 September, b) and Saral-AltiKa, (c) Sentinel 3a, passed passed overover at at 13:59 10:39 UTC UTC on 19 on September. 17 Sep- Colortember, codes and of SST c) areSentinel in degrees 3a, Celsius. passed Numerals over at on13:59 isobaths UTC are on in m.19 (September.d–f) Latitudinal Color distributions codes of theSST along-track are in SWH. degrees Celsius. Numerals on isobaths are in m. (d)–(f) Latitudinal distributions of the along-track SWH.

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Figure 10. (a–c) Sea surface wind (arrows) in the NSCS on 15, 16, and 18 September 2018. (d–f) Ekman pumping velocity on 15, 16, and 18 September 2018. The unit of velocity is m/s. The green curve with blue dots (every 3 h) represents the Figuretyphoon 10. track. (a Numerals)–(c) Sea onsurface isobaths wind are in (arrows) m. in the NSCS on 15, 16, and 18 September 2018. (d)–(f) Ekman pumping velocity on 15, 16, and 18 September 2018. The unit of velocity is m/s. The green curve with blue dots (every4.3. Basin 3 h) Area represents the typhoon track. Numerals on isobaths are in m. In the basin area, the Chl-a concentration was 0.1 mg/m3 on 15 September, before 4.3. Basin Area typhoon Mangkhut (2018) passage, and increased to 0.2 mg/m3 after typhoon passage, against the 0.1 mg/m3 monthly mean Chl-a concentration in September from 2002 to 3 In the basin area,2016. the Therefore, Chl-a theconcentration passage of typhoon was Mangkhut0.1 mg/m (2018) on induced15 September, an increase before in the Chl-a typhoon Mangkhut concentration(2018) passage, in the and basin increased area that was to twice 0.2 themg/m monthly3 after mean typhoon value. passage, against the 0.1 mg/m3 monthlyFigure 11 mean shows Chl-a the temperature concentration and salinity in September profiles measured from 2002 by the to Argo 2016. float in Therefore, the passagethe of west typhoon of Luzon Mangkhut Strait on 9, 13, (2018) 17, and induced 21 September an increase 2018. The in four the vertical Chl-a distribution con- profiles of the water temperature and salinity were measured within 21 km. One can see centration in the basinthat area the temperaturethat was twice (salinity) the at monthly a pressure mean less than value. 40 dbar (~depth < 40 m) was almost Figure 11 showshomogeneous the temperature at 28.8 ◦ Cand (33.1) salinity on 9 and profiles 13 September. measured At the deeperby the layer, Argo the float temperature in the west of Luzon Straitdecreased on 9, with 13, the17, depth.and 21 After September the typhoon 2018. passed The 20 kmfour away vertical from point distribution A at 12:00 UTC profiles of the water temperature and salinity were measured within 21 km. One can see that the temperature (salinity) at a pressure less than 40 dbar (~ depth < 40 m) was almost homogeneous at 28.8 °C (33.1) on 9 and 13 September. At the deeper layer, the temperature decreased with the depth. After the typhoon passed 20 km away from point A at 12:00 UTC on 15 September, the temperature dropped from 28.8 °C to 26.9 °C on 17 September, and the salinity increased from 33.1 to 33.8. On 21 September, the temperature increased to 27.4 °C. During the period of typhoon passage, the depth of the mixed layer was deepened from the original 40 m to 80 m.

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on 15 September, the temperature dropped from 28.8 ◦C to 26.9 ◦C on 17 September, and the salinity increased from 33.1 to 33.8. On 21 September, the temperature increased to 27.4 ◦C. During the period of typhoon passage, the depth of the mixed layer was deepened Remote Sens. 2020, 12, x FOR PEER REVIEWfrom the original 40 m to 80 m. 15 of 18

Figure 11. (a)Temperature and (b) salinity profiles measured by the Argo float in the basin area on 9, Figure 11. (a)Temperature and (b) salinity profiles measured by the Argo float in the basin area on13, 9, 17, 13, and 17, and 21 September 21 September 2018. 2018. Zhao et al. [37] showed that the Chl-a concentration west of the Luzon Strait was Zhao et al. [37] showed that the Chl-a concentration west of the Luzon Strait was low low in all seasons, except winter. Chen et al. [3] attributed the enhancement of the Chl-a in all seasons, except winter. Chen et al. [3] attributed the enhancement of the Chl-a con- concentration to the strong vertical mixing and upwelling during a typhoon process in this centration to the strong vertical mixing and upwelling during a typhoon process in this area. From Figure 11, one can see that, in this case, the mixed layer depth was deepened by area. From Figure 11, one can see that, in this case, the mixed layer depth was deepened 40 m. It is reasonable to attribute the phytoplankton bloom to the nutrient supply brought by 40 m. It is reasonable to attribute the phytoplankton bloom to the nutrient supply up by the vertical mixing and upwelling [36]. On the other hand, the observation results broughtshowed up that by the the maximum vertical mixing Chl-a and concentration upwelling existed[36]. On in the the other subsurface hand, the water observation at depths resultsof 50–70 showed m [38 –that40]. the It ismaximum strong vertical Chl-a mixingconcentration that transports existed in the the phytoplankton subsurface water in theat depthssubsurface of 50–70 layer m up [38–40]. to the surfaceIt is strong layer, vertic andal causes mixing the that Chl-a transports concentration the phytoplankton to increase. in the Likesubsurface the case layer observed up to the in thesurface shelf laye area,r, and the Chl-acauses concentration the Chl-a concentration in the basin to areain- crease.increased immediately after typhoon Mangkhut (2018) passed, then decreased gradually, implyingLike the that case the nutrientobserved supply in the by shelf typhoon-induced area, the Chl-a vertical concentration mixing andin the upwelling basin area was increasedgradually immediately consumed. after Thus, typhoon the observed Mangkhut Chl-a (2018) bloom passed, in the then basin decreased area was gradually, a transient implyingevent in responsethat the nutrient to the passage supply by of typhoontyphoon-induced Mangkhut vertical (2018). mixing and upwelling was gradually consumed. Thus, the observed Chl-a bloom in the basin area was a transient event5. Conclusions in response to the passage of typhoon Mangkhut (2018). This study investigates the behavior of spatiotemporal distributions of ocean color 5.elements, Conclusions including the TSS and the Chl-a, in response to tropical cyclones. The case of typhoon This Mangkhutstudy investigates (2018) passing the behavior over the of NSCS spatiotemporal on 16 September distributions 2018 is examinedof ocean color using elements,satellite multi-sensor including the observations, TSS and the Argo Chl-a, float in profiles,response and to tropical tidal gauge cyclones. sea level The data. case Theof typhoonmajor findings Mangkhut and (2018) results passing are summarized over the NS asCS follows. on 16 September 2018 is examined using satelliteTyphoon multi-sensor Mangkhut observations, (2018) resulted Argo infloat transient profiles, events and tidal of TSS gauge concentration sea level data. peaks The and majorChl-a findings blooms, and with results the spatial are summarized distribution as and follows. timing behavior different in the offshore, shelf, Typhoon and basin Mangkhut areas. In (2018) the offshore resulted area in fromtransient the coastevents to of isobath TSS concentration 50 m, the mean peaks TSS and Chl-a blooms, with the spatial distribution and timing behavior different in the offshore, shelf, and basin areas. In the offshore area from the coast to isobath 50 m, the mean TSS concentration reached 13.9 mg/l on 18 September 2018, two days after typhoon landfall, against about 3.5 mg/l before typhoon landfall. In the shelf area with depths from 50 m to 100 m, the mean TSS concentration reached 2.5 mg/l, against about 1 mg/l before

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concentration reached 13.9 mg/L on 18 September 2018, two days after typhoon landfall, against about 3.5 mg/L before typhoon landfall. In the shelf area with depths from 50 m to 100 m, the mean TSS concentration reached 2.5 mg/L, against about 1 mg/L before typhoon landfall. In the basin area, the mean TSS concentration had only a little fluctuation. On the other hand, in the offshore area, the mean Chl-a concentration reached 7.3 mg/m3 on 21 September, five days after typhoon landfall, against the 2.4 mg/m3 monthly mean value. In the shelf area, the mean Chl-a concentration increased from 0.2 mg/m3 to 0.6 mg/m3 in two days, implying a direct response to vertical mixing and upwelling enhanced by the typhoon. In the basin area, the Chl-a concentration increased from 0.1 mg/m3 to 0.2 mg/m3 during typhoon passage. Concurrent dynamic conditions, including SST, SSS, SLA, SWH, wind fields, water depth, Argo float temperature, and salinity profiles are analyzed for exploration of spatiotemporal distribution features of the TSS and the Chl-a, as well as the timing lags between their peaks and blooms. The results indicate that, in the offshore area, typhoon- induced solitary continental waves may play a dominant role in determining the spatial distribution features of the TSS originating from the heavy loaded Pearl River runoff. The Chl-a bloom was delayed rather than concurrent occurring with the terrigenous nutrient peak, attributed to the nonlinear relation between the Chl-a concentration and the TSS concentration. In the shelf and basin areas, typhoon-induced vertical mixing and upwelling may play dominant roles in determining the spatiotemporal behavior of the TSS and the Chl-a. Furthermore, the direct injection of the particulate matter from land transported by strong wind should be a possible mechanism for the TSS increase in the shelf area.

Author Contributions: All authors have made significant contributions to this research. J.L. and Q.L. analyzed the data; L.X. and M.L. provided important insights and suggestions on this research; J.L. and Q.Z. wrote the paper. All authors have read and agreed to the published version of the manuscript. Funding: Supported by National Natural Science Foundation of China (41706025, 41776034, 41506018), Innovation Team Plan for Universities in Guangdong Province (2019KCXTF021), Matched Grant of Guangdong Ocean University (P15299), Open Fund of the Key Laboratory of Ocean Circulation and Waves, Chinese Academy of Sciences, Program for Scientific Research Start-up Funds of Guangdong Ocean University, Guangdong Province First-Class Discipline Plan (CYL231419012). Data Availability Statement: The typhoon data are obtained from the Tropical Cyclone Data Center of the China Meteorological Administration (CMA) (http://tcdata.typhoon.org.cn). The Chl-a concentration, sea surface wind and sea surface salinity (SSS) data are downloaded from http: //oceandata.sci.gsfc.nasa.gov/. The sea surface temperature (SST) data are downloaded from https://podaac-opendap.jpl.nasa.gov/. Acknowledgments: The authors are grateful to the anonymous reviewers for their valuable suggestions and comments. Conflicts of Interest: The researchers claim no conflict of interest.

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