Upper Ocean Response to Two Sequential Tropical Cyclones Over the Northwestern Paciﬁc Ocean

remote sensing

Article Upper Ocean Response to Two Sequential Tropical Cyclones over the Northwestern Paciﬁc Ocean

Jue Ning 1, Qing Xu 1,* , Tao Feng 1 , Han Zhang 2 and Tao Wang 3,4

1 College of Oceanography, Hohai University, Nanjing 210098, China; [email protected] (J.N.); [email protected] (T.F.) 2 State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China; [email protected] 3 Key Laboratory of Marine Environment and Ecology, Ocean University of China, Qingdao 266100, China; [email protected] 4 Qingdao National Laboratory for Marine Science and Technology, Qingdao 266100, China * Correspondence: [email protected]; Tel.: +86-025-83787340

Received: 28 August 2019; Accepted: 18 October 2019; Published: 19 October 2019

Abstract: The upper ocean thermodynamic and biological responses to two sequential tropical cyclones (TCs) over the Northwestern Pacific Ocean were investigated using multi-satellite datasets, in situ observations and numerical model outputs. During Kalmaegi and Fung-Wong, three distinct cold patches were observed at sea surface. The locations of these cold patches are highly correlated with relatively shallower depth of the 26 ◦C isotherm and mixed layer depth (MLD) and lower upper ocean heat content. The enhancement of surface chlorophyll a (chl-a) concentration was detected in these three regions as well, mainly due to the TC-induced mixing and upwelling as well as the terrestrial runoff. Moreover, the pre-existing ocean cyclonic eddy (CE) has been found to significantly modulate the magnitude of surface cooling and chl-a increase. With the deepening of the MLD on the right side of TCs, the temperature of the mixed layer decreased and the salinity increased. The sequential TCs had superimposed effects on the upper ocean response. The possible causes of sudden track change in sequential TCs scenario were also explored. Both atmospheric and oceanic conditions play noticeable roles in abrupt northward turning of the subsequent TC Fung-Wong.

Keywords: upper ocean response; sequential tropical cyclones; ocean cyclonic eddy

1. Introduction Tropical cyclones (TCs), which are among the most devastating natural disasters, pose signiﬁcant threat on the lives and property of global coastal regions [1]. During the passage of a TC, the strong wind stress could typically produce intense oceanic entrainment and upwelling [2–4], which leads to physical and biological responses of the upper ocean. Sea surface temperature (SST) decrease, the most striking phenomenon, is usually observed in the range of 1–9 ◦C with stronger cooling to the right side of a TC’s track [5–9]. The sea surface cooling has a negative feedback to a TC by suppressing the TC development in turn [10]. Furthermore, the SST decrease would have an impact on the subsequent TCs if they pass by these cold wakes coincidentally [11]. The distribution of phytoplankton biomass, as is measured by chlorophyll a (chl-a) concentration, is also inﬂuenced by TCs. Previous studies have found that the surface chl-a concentration would be largely increased after TCs, with estimated maximum contribution of 20–30% for the annual new production in the South China Sea (SCS) [12,13]. It is well recognized that the magnitude and spatial distribution of SST decrease and chl-a enhancement mainly depend on the intensity and translation speed of TCs and the background ocean environments, such as the mixed layer depth (MLD) and mesoscale eddies, as well as topography [2,13–16]. Owing to the

Remote Sens. 2019, 11, 2431; doi:10.3390/rs11202431 www.mdpi.com/journal/remotesensing Remote Sens. 2019, 11, 2431 2 of 19 complex pre-TC conditions of different regions, the responses of the upper ocean in these regions are well worth studying in detail. Although the upper ocean response to a single TC has been commonly focused on [6–9,17–20], inadequate attention is paid to how sequential TCs affect the upper ocean from both physical and biological aspects. The mesoscale cyclonic eddy (CE), as one of the main pre-TC ocean features, plays an important role in the upper ocean response to TCs [7,8,21–23]. CEs with negative sea surface height anomaly (SSHA) and cold water in the core region provide a relatively unstable thermodynamic structure that help elevate cold and nutrient-rich water below easily [7,8,21]. Conversely, CEs might be influenced by individual TC in many ways [23,24]. However, the interaction between sequential TCs and CEs still remains unclear. It seems that more intense TCs happen annually under the background of warming climate [25]. Nevertheless, the current level of TC forecast does lay behind the urgent needs of disaster prevention and mitigation [26]. Particularly, when two or more TCs exist simultaneously in the same region, it becomes much more difficult to forecast their tracks [27,28]. Previous studies suggested both atmospheric and oceanic factors could affect the forecast accuracy of the TC by influencing its motion and intensity, such as western North Pacific subtropical high (WNPSH), the environmental flow, SST and upper ocean heat content (UOHC) [29–33]. However, how these factors contribute to the sudden track change in sequential TCs scenario has been seldom systematically investigated. Thus, it is essential to comprehensively understand the possible causes under complex atmospheric and ocean environments. This study aims to explore the thermodynamic and biological responses of the upper ocean to two sequential TCs over the Northwestern Pacific Ocean (NWP) in 2014 and reveal the possible causes leading to the sudden track change of the subsequent TC in this scenario. A brief description of the datasets and methods is presented in Section2. Section3 gives the results and discussion in detail. Finally, the conclusions are made in Section4.

2. Data and Methods

2.1. Data

2.1.1. TC Best Track Data The TC information, including the time (UTC), center location, the maximum sustained wind speed (MSW) and minimum sea surface pressure every 6 hours, is obtained from Joint Typhoon Warning Center (JTWC, http://www.usno.navy.mil/NOOC/nmfc-ph/RSS/jtwc/best_tracks). The best track dataset is suggested to be more dynamically consistent than some other datasets [34]. The tracks and intensities of Kalmaegi and Fung-Wong in September 2014 are shown in Figure1a–c. Based on the time series of center locations, the translation speeds of the two TCs are calculated (Figure1d,e). TC Kalmaegi formed on September 10 in the Tropical Paciﬁc. It went straight northwest, crossed the South China Sea, and ﬁnally made landfall in Hainan Province on September 16. The largest MSW 1 reached 80 kt (i.e., 41 m s− ) as a Category 1 TC. After one week, Tropical Storm Fung-Wong formed in the area where Kalmaegi passed by and then followed the Kalmaegi’s track to the northwest. While until September 20, a sudden turning occurred over the Luzon Strait. Afterward it moved to the north and landed in Zhejiang Province on 1 September 22. It reached its peak MSW at 50 kt (26 m s− ) on September 21. Remote Sens. 2019, 11, x FOR PEER REVIEW 3 of 20 Remote Sens. 2019, 11, 2431 3 of 19

86 Figure 1. The tracks (a), intensities (b,c), and translation speeds (d,e) of Kalmaegi (left panel) and 87 FigureFung-Wong 1. The (righttracks panel).(a), intensities The blue (b and–c), redand dashedtranslation lines speeds indicate (d tracks–e) of Kalmaegi of Kalmaegi (left and panel) Fung-Wong, and 88 Fung-Wongrespectively. (right The panel). symbol The “*” inblue (a) and denotes red thedash centered lines location indicate of two tracks TCs of at 00:00Kalmaegi UTC and on the 89 Fung-Wong,corresponding respectively. date. The The black symbol triangles “*” in with (a) deno symbolstes the from center “B1” location to “B5” of indicate two TCs ﬁve at array00:00 UTC stations. 90 onThe the magenta corresponding pentagrams date. withThe black symbols triangles “A1” andwith“A2” symbols indicate from the “B1” locations to “B5” of indicate the two five Argo array ﬂoats. 91 stations. The magenta pentagrams with symbols “A1” and “A2” indicate the locations of the two 2.1.2. Satellite Observations 92 Argo floats. The daily SST product used in this study is Microwave and Infrared OI SST (MW-IR OISST) 93 2.1.2.from Satellite the Remote Observations Sensing Systems (http://www.remss.com/) with a spatial resolution of 9 km 9 km. ×

Remote Sens. 2019, 11, 2431 4 of 19

It combines the through-cloud capability of the microwave OI SST product [35] with the high spatial resolution of the infrared SST by using Optimum Interpolation method [36]. The daily SSHA dataset, provided by Archiving, Validation and Interpretation of Satellite Data in Oceanography (AVISO) has a spatial resolution of 0.25 0.25 . The altimeter products are ◦ × ◦ produced and distributed by the Copernicus Marine and Environment Monitoring Service (CMEMS, http://marine.Copernicus.eu/). Closed contours of negative SSHA are normally corresponding to mesoscale cyclonic eddies (CEs) with cold water in the core region [8]. Because the daily chl-a concentration dataset includes plenty of data gaps caused by severe cloud contamination, we use the 8-day averaged data to study the biological response of the upper ocean to the sequential TCs. Previous studies pointed out that phytoplankton growth, which attributes to chl-a enhancement under the inﬂuence of a TC, needs a delay of several days ( 5 days) to reach its peak [21]. ∼ The accurate days for chl-a concentration to rise to its maximum remains unclear [22]. The merged 8-day chl-a concentration data, with a spatial resolution of 4 km 4 km, produced and distributed by × the GlobColour Project (http://hermes.acri.fr/) are satisﬁed with the basic research requirements [22]. The GlobColour data were developed, validated, and distributed by ACRI-ST, France. The daily ocean surface winds on a global 0.25◦ grid derived from the Blended Sea Winds dataset are acquired from the National Oceanic and Atmospheric Administration’s (NOAA’s) National Climatic Data Center, via their website (http://http://www.ncdc.noaa.gov/oa/rsad/air-sea/seawinds. html). The gridded wind speeds were created from the blending observations of multiple satellites [37].

2.1.3. In Situ Measurements Temperature and salinity profiles used to investigate the thermal responses are obtained from Argo observations and a cross-shaped observational array in the SCS deployed by the Second Institute of Oceanography, Ministry of Natural Resources of China in 2014. The Argo profiles are provided by the China Argo Real-time Data Center (http://www.argo.org.cn/) and the quality control has been performed [38]. The locations of Argo floats and observational array are shown in Figure1a. There are two Argo floats located in the area influenced by both Kalmaegi and Fung-Wong. The observational array consists of five moored buoys and four subsurface moorings organized into five stations. Considering the validity of the data and the distance between the stations and two TCs, the data at Stations 4 and 5 are analyzed in this study.

2.1.4. Ocean Numerical Model Outputs The daily ocean analysis data with a spatial resolution of 0.08 0.08 are obtained from the global ◦ × ◦ HYbrid Coordinate Ocean Model (HYCOM) + Navy Coupled Ocean Data Assimilation (NCODA) based ocean prediction system (hereafter called HYCOM, https://www.hycom.org/)[39]. As shown in Figure2, HYCOM simulations of SST, SST di ﬀerence (SSTD) during and before Kalmaegi passed by and SSHA are in good agreement with satellite observations. It is clear that the SSHA from HYCOM and AVISO both reveal the same CE region. Therefore, the data can be used for further analysis.

2.1.5. Atmospheric Reanalysis Data The atmospheric ﬁelds are obtained from the National Centers for Environmental Prediction–Department of Energy (NCEP–DOE) AMIP-II reanalysis 2 data, which is from the National Oceanic and Atmospheric Administration (NOAA) Earth System Research Laboratory’s Physical Sciences Division (https://www.esrl.noaa.gov/psd/). The reanalysis data have a spatial resolution of 2.5 2.5 on a global grid and 17 pressure levels from 10 to 1000 hPa [40]. ◦ × ◦ Remote Sens. 2019, 11, 2431 5 of 19

Remote Sens. 2019, 11, x FOR PEER REVIEW 5 of 20

135

136 FigureFigure2. 2. ComparisonsComparisons of of SST, SST, SSTD SSTD and and SSHA SSHA between between satellite satellite observations observations (Top) (Top) and HYCOM and HYCOM data 137 data (Bottom). (a)–(b): SST distributions before Kalmaegi, (c)–(d): SSTD during the passage of (Bottom). (a,b): SST distributions before Kalmaegi, (c,d): SSTD during the passage of Kalmaegi (i.e., 138 Kalmaegi (i.e., SST difference between September 15 and 9), (e)–(f): negative SSHA in the area SST diﬀerence between September 15 and 9), (e,f): negative SSHA in the area denoted by the blue 139 denoted by the blue box in (c) before Kalmaegi. The dash and solid lines denote the tracks of 140 boxKalmaegi in (c) beforeand Fung-Wong, Kalmaegi. respectively. The dash andThe black solid an linesd gray denote parts theof the tracks lines ofrepresent Kalmaegi the andTC has Fung-Wong, 141 respectively.and has not passed The black the region, and gray respectively. parts of theThe lines red dot represent denotes thethe TCcenter has location and has of notKalmaegi passed at the region, 142 respectively.00:00 UTC on The September red dot 15. denotes the center location of Kalmaegi at 00:00 UTC on September 15.

143 2.2.2.1.5. Methods Atmospheric Reanalysis Data 144 InThe this atmospheric study, SST fields on September are obtained 9 from is considered the National to Centers be the pre-TCsfor Environmental condition. Prediction– The SSTD, which 145 denotesDepartment the SST of Energy variation (NCEP–DOE) during and AMIP-II before reanalysis TCs pass 2 by,data, can which be calculated is from thefrom National satellite Oceanic observations 146 orand HYCOM Atmospheric data by Administration subtracting SST(NOAA) during Earth the System TCs and Research that on Laboratory's September Physical 9. Sciences 147 Division (https://www.esrl.noaa.gov/psd/). The reanalysis data have a spatial resolution of 2.5° × 2.5° The MLD, defined as the depth where the temperature decreases 0.5 ◦C compared to that at 148 on a global grid and 17 pressure levels from 10 to 1000 hPa [40]. surface [41], or that was based on density variation according to Equation (1) of Kara et al. (2000) [41], 149 is2.2. calculated Methods from temperature sections of Argo profiles, observational array and HYCOM data. The temporal variations of MLDs are similar when we use temperature or density criterion, although 150 In this study, SST on September 9 is considered to be the pre-TCs condition. The SSTD, which 151 thedenotes absolute the values SST variation of the later during are aand little before smaller. TCs Here, pass theby, resultscan be of calculated MLD calculated from satellite by temperature 152 criterionobservations are adopted. or HYCOM Mixed data by layer subtracting temperature SST during (MLT) the and TC mixeds and that layer on September salinity (MLS) 9. are taken as the 153 averageThe values MLD, indefined the mixed as the layer. depth where the temperature decreases 0.5 °C compared to that at 154 surfaceThe [41], UOHC or that is calculated was based usingon density HYCOM variation output according of ocean to Equation temperature (1) of profilesKara et al. T(z): (2000) 155 [41], is calculated from temperature sections of Argo profiles, observational array and HYCOM data. 156 The temporal variations of MLDs are similarZ 0when we use temperature or density criterion, 157 although the absolute values of theUOHC later are= a little smaller.ρCp(T Here,(z) the26) dz,results of MLD calculated by (1) D26 − 158 temperature criterion are adopted. Mixed layer −temperature (MLT) and mixed layer salinity (MLS) 159 are taken as the average values in the mixed layer.3 where ρ is the seawater density (1024 kg/m ); Cp is the heat capacity (4186 J/kg ◦C). D26 is the depth of 160 The UOHC is calculated using HYCOM output of ocean temperature profiles T(z): the 26 ◦C isotherm, which can characterize the relative warm or cold of the upper ocean. 0 The potential upwelling speedUOHCw due = toρ CTC (T(z) winds - 26)dz is calculated, using the classical Ekman(1) pumping -D26 p velocity (EPV) formula [4]: →τ w = curl( ), (2) ρf where f is the Coriolis parameter. The wind stress →τ can be obtained by the bulk formula [42]:

→τ = ρaCdU10→u10, (3) Remote Sens. 2019, 11, 2431 6 of 19

where ρa is the air density; U10 and →u10 are the wind speed and wind vector 10 meters above sea surface, respectively; Cd is the drag coeﬃcient and is calculated using the formula proposed by Oey et al. (2006) [43], which ﬁts the formula at low-to-moderate wind speeds [44] and the results at high wind speeds [45],

1 Cd 1000 = 1.2 U10 < 11 ms− × 1 = 0.49 + 0.065U10 11 < U10 < 19 ms− (4) = 1.364 + 0.0234U 0.00023158U2 19 < U < 100 ms 1 10 − 10 10 − 3. Results and Discussion

3.1. Thermodynamic Response

3.1.1. Sea Surface Cooling As shown in Figures3a and4a,c,e, the background ocean environments on September 9 provided favorable conditions for TC generation, with high SST, relatively deep D26, MLD and high UOHC. The SST in most part of study area was higher than 30 ◦C. During the passages of both Kalmaegi and Fung-Wong, there was a cool trail along their tracks with rightward bias (Figure3b–f). In particular, three distinct cold patches were detected, which were marked with black, gray and red box and correspondingly labeled as R1, R2, R3 in Figure3, respectively. In region R1, the maximum decrease of SST located to the right side of Kalmaegi’s track was 3.18 ◦C on September 14 (Figure3b). The ocean surface cooled again 5 days later when Fung-Wong passed through the same area (Figure3d), with a temperature decrease of 2.36 ◦C. Overall, during the passages of the sequential TCs, SST dropped by 3.28 ◦C. Kalmaegi and Fung-Wong were both strong 1 1 with MSW ranging between 28.3~36.0 m s− and 15.4~18.0 m s− , respectively. Therefore, the induced strong mixing effects were able to bring colder water from deep to surface. Furthermore, this region was characterized by shallower MLD, D26 and lower UOHC before the arrival of TCs (Figure4), which is beneficial to the cooling of sea surface. Interestingly, as Figure5 shows, whether during the passage of Kalmaegi or Fung-Wong, this cold patch was highly consistent with the location of a pre-existing CE (Figure5). Negative SSHA inside the CE indicates that the MLD was relatively shallower than the background ocean. It means the thermodynamic structure inside the CE was relatively unstable, which makes it possible to uplift the cold water below easily. Therefore, the pre-existing CE is an essential factor contributing to the stronger surface cooling, which has also been noticed in previous studies [7,8]. As can be seen in Figure3c, the maximum SST drop in region R2 reached 3.73 ◦C after Kalmaegi passed. The ocean surface then gradually recovered until September 19 when Fung-Wong affected this region. The surface cooled down again by 1.93 ◦C, but much weaker than the first cooling. The magnitude of temperature decrease in this region after sequential TCs was larger than that in the other two regions. The possible reasons are: (1) Shallower MLD, D26 and lower UOHC were all favorable for the surface cooling. (2) The intensity of Kalmaegi increased continuously to its peak 1 MSW of 41 m s− when passing by Region R2. While during Fung-Wong, its slow translation speed 1 (from 3.1 to 4.8 m s− ) could induce strong upwelling. However, because this region was located to the left of Fung-Wong, the intensity of which was much smaller than Kalmaegi, the weaker mixing effect resulted in a weaker second cooling. For Region R3, the strongest surface cooling caused by Kalmaegi was 2.54 ◦C on September 15. During Fung-Wong on September 20, SST was reduced again by 2.38 ◦C after its recovery from the influence of Kalmaegi. The magnitude of SST decrease induced by the sequential TCs reached up to 2.92 ◦C in this region compared to pre-TC conditions, which was the smallest among the three regions owing to the relatively unfavorable ocean conditions of MLD, D26 and UOHC. Meanwhile, the translation speed of Kalmaegi was the fastest when passing through this region. However, the MSW 1 of Fung-Wong over the same region ranged from 18.0 to 25.7 m s− and the translation speed was Remote Sens. 2019, 11, x FOR PEER REVIEW 7 of 20

200 speed (from 3.1 to 4.8 m s-1) could induce strong upwelling. However, because this region was 201 located to the left of Fung-Wong, the intensity of which was much smaller than Kalmaegi, the 202 weaker mixing effect resulted in a weaker second cooling. 203 For Region R3, the strongest surface cooling caused by Kalmaegi was 2.54 °C on September 15. 204 During Fung-Wong on September 20, SST was reduced again by 2.38 °C after its recovery from the 205 influence of Kalmaegi. The magnitude of SST decrease induced by the sequential TCs reached up to 206 2.92 °C in this region compared to pre-TC conditions, which was the smallest among the three 207 Remote Sens.regions2019 ,owing11, 2431 to the relatively unfavorable ocean conditions of MLD, D26 and UOHC. Meanwhile, 7 of 19 208 the translation speed of Kalmaegi was the fastest when passing through this region. However, the 209 MSW of Fung-Wong over the same region ranged from 18.0 to 25.7 m s-1 and the translation speed 210 was between 3.1 and1 5.7 m s-1, which represented the strongest and slowest stage of Fung-Wong. between 3.1 and 5.7 m s− , which represented the strongest and slowest stage of Fung-Wong. The longer 211 The longer life cycle of Fung-Wong also contributes to the occurrence of the strongest second life cycle of Fung-Wong also contributes to the occurrence of the strongest second cooling. 212 cooling.

213

214 FigureFigure 3. Satellite 3. Satellite observed observed evolution evolution of of SST SST before, before, during during and after and Kalmaegi after Kalmaegi and Fung-Wong. and Fung-Wong. (a): 215 (a): beforebefore Kalmaegi, Kalmaegi, (b ,(cb):)–( duringc): during Kalmaegi Kalmaegi and and before before Fung-Wong, Fung-Wong, ((dd–)–(f):f): after after KalmaegiKalmaegi and during 216 Fung-Wong.during TheFung-Wong. expression The ofexpression TC tracks of TC is thetracks same is the as same Figure as2 Figure. The red2. The and red green and green dots dots denote the 217 center locationsdenote the of center Kalmaegi locations and of Fung-WongKalmaegi andat Fung-Wong 00:00 UTC, at respectively.00:00 UTC, respectively. The black, The gray black, and gray red boxes 218 Remote Sens.and 2019 red, 11boxes, x FOR represent PEER REVIEW typical regions with distinct sea surface cooling. 8 of 20 represent typical regions with distinct sea surface cooling.

219

220 FigureFigure 4. Spatial 4. Spatial distributions distributions of MLD, D26 D26 and and UOHC UOHC from from HYCOM HYCOM output outputbefore the before formation the formationof of 221 Kalmaegi on September 9 (upper panel) and Fung-Wong on September 17 (lower panel). (a)–(b): Kalmaegi on September 9 (upper panel) and Fung-Wong on September 17 (lower panel). (a,b): MLD, 222 MLD, (c)–(d): D26, (e)-(f): UOHC. The expression of TC tracks is the same as Figure 2. The red dot 223 (c,d):denotes D26, ( ethe,f): center UOHC. location The of expression Kalmaegi at of 00:00 TC UTC tracks on isSeptember the same 17. as Figure2. The red dot denotes the center location of Kalmaegi at 00:00 UTC on September 17.

224

225 Figure 5. Distribution of SSTD during the passages of Kalmaegi on September 14 (i.e., SST difference 226 between September 14 and 9) (a) and Fung-Wong on September 19 (i.e., SST difference between 227 September 19 and 9) (b). Overlaid is SSHA (contours, unit: cm) on the corresponding date. Only 228 negative values are plotted, with closed contours indicating the location of the CE. The expression of 229 TC tracks is the same as Figure 2. The red and green dots denote the center locations at 00:00 UTC of 230 Kalmaegi and Fung-Wong, respectively.

231 3.1.2. Subsurface Response 232 In order to explore subsurface thermodynamic changes induced by Kalmaegi and Fung-Wong, 233 temperature and salinity data observed by two Argo floats (A1 and A2 in Figure 1(a)) and two 234 stations (B4 and B5 in Figure 1(a)) of the observational array were analyzed here. Float A1 was close 235 to the center of Kalmaegi while A2 was on the left side of its track. They were both located on the 236 left of Fung-Wong. Neither float A1 nor A2 has moved a long distance from September 11 to 23.

Remote Sens. 2019, 11, x FOR PEER REVIEW 8 of 20

219 220 Figure 4. Spatial distributions of MLD, D26 and UOHC from HYCOM output before the formation of 221 Kalmaegi on September 9 (upper panel) and Fung-Wong on September 17 (lower panel). (a)–(b): 222 MLD, (c)–(d): D26, (e)-(f): UOHC. The expression of TC tracks is the same as Figure 2. The red dot 223 Remote Sens.denotes2019, the11, 2431center location of Kalmaegi at 00:00 UTC on September 17. 8 of 19

224

225 FigureFigure 5. 5.Distribution Distribution of of SSTD SSTD during during thethe passagespassages of Kalmaegi on on September September 14 14 (i.e., (i.e., SST SST difference diﬀerence 226 betweenbetween September September 14 14 and and 9) 9)( a(a)) andand Fung-WongFung-Wong onon September 19 19 (i.e., (i.e., SST SST difference diﬀerence between between 227 SeptemberSeptember 19 19 and and 9) 9) (b ().b). Overlaid Overlaid is is SSHA SSHA (contours,(contours, unit:unit: cm) cm) on on the the corresponding corresponding date. date. Only Only 228 negativenegative values values are are plotted, plotted, with with closed closed contourscontours indicatingindicating the the location location of of the the CE. CE. The The expression expression of of 229 TCTC tracks tracks is theis the same same as as Figure Figure2. 2. The The red red and and green green dotsdots denotedenote the center locations locations at at 00:00 00:00 UTC UTC of of 230 KalmaegiKalmaegi and and Fung-Wong, Fung-Wong, respectively. respectively.

231 3.1.2.3.1.2. Subsurface Subsurface Response Response 232 InIn order order to to explore explore subsurface subsurface thermodynamic thermodynamic changes induced induced by by Kalmaegi Kalmaegi and and Fung-Wong, Fung-Wong, 233 temperaturetemperature and and salinity salinity data data observed observed by by two two Argo Argo floats floats (A1 (A1 and and A2 inA2 Figure in Figure1a) and 1(a)) two and stations two 234 (B4stations and B5 (B4 in Figure and B51a) in ofFigure the observational 1(a)) of the observat array wereional analyzed array were here. analyzed Float A1here. was Float close A1 to was the close center 235 of Kalmaegito the center while of Kalmaegi A2 was on while the left A2side wasof on its the track. left side They of were its track. both locatedThey were on theboth left located of Fung-Wong. on the 236 Neitherleft of floatFung-Wong. A1 nor Neither A2 has float moved A1 anor long A2 distancehas moved from a long September distance 11 from to 23.September The variations 11 to 23. of temperature and salinity profiles from two Argo floats are shown in Figure6, from which the trends in MLD, MLT and MLS were calculated and listed in Table1. One can see from Table1, the MLD measured by float A1 remained basically unchanged during the transit of Kalmaegi, probably because A1 was near the TC center. After Fung-Wong, the mixed layer deepened and the MLD increased to 47.5 m on September 23. The MLT dropped by 0.96 ◦C during Kalmaegi and the cooling was strengthened with a further temperature decrease of 0.40 ◦C after Fung-Wong. Although the MLS increased by ~0.15 as Kalmaegi passed by, it is notable that from September 15 to 19, it was reduced by 0.22 due to the influence of Fung-Wong which was on the right of float A1.

Table 1. The locations of Argo ﬂoats and variations of MLD, MLT and MLS.

Float Location (◦) Date MLD (m) MLT (◦C) MLS (119.28 E, 17.90 N) Sep. 11 42.5 29.41 33.14 (119.41 E, 17.97 N) Sep. 15 42.5 28.45 33.29 A1 (119.44 E, 17.93 N) Sep. 19 37.5 28.65 33.07 (119.69 E, 18.09 N) Sep. 23 47.5 28.25 33.11 (116.72 E, 16.86 N) Sep. 11 35.5 29.26 33.34 (116.84 E, 16.99 N) Sep. 15 36.5 28.84 33.18 A2 (116.93 E, 16.92 N) Sep. 19 45.5 28.68 33.14 (116.95 E, 16.87 N) Sep. 23 40.5 28.34 32.97

For Float A2, the MLD gradually increased from September 11 to 19 as a result of the inﬂuence of two TCs. Since A2 was located on the left side of the TCs, the magnitude of mixed layer deepening was a little smaller than that of A1 with only a few meters. Meanwhile, during this period both MLT and MLS dropped continuously. The decreases in MLT from September 11 to 15, and from 15 to 19 were 0.42 ◦C and 0.16 ◦C, respectively. The declines in MLS were 0.16 and 0.04, respectively. What leads to Remote Sens. 2019, 11, x FOR PEER REVIEW 9 of 20

237 The variations of temperature and salinity profiles from two Argo floats are shown in Figure 6, 238 from which the trends in MLD, MLT and MLS were calculated and listed in Table 1. 239 One can see from Table 1, the MLD measured by float A1 remained basically unchanged 240 during the transit of Kalmaegi, probably because A1 was near the TC center. After Fung-Wong, the 241 mixed layer deepened and the MLD increased to 47.5 m on September 23. The MLT dropped by 242 0.96 °C during Kalmaegi and the cooling was strengthened with a further temperature decrease of 243 0.40 °C after Fung-Wong. Although the MLS increased by ~0.15 as Kalmaegi passed by, it is notable 244 that from September 15 to 19, it was reduced by 0.22 due to the influence of Fung-Wong which was 245 on the right of float A1.

246 Table 1. The locations of Argo floats and variations of MLD, MLT and MLS.

Float Location (°) Date MLD (m) MLT (°C) MLS (119.28 E, 17.90 N) Sep. 11 42.5 29.41 33.14 (119.41 E, 17.97 N) Sep. 15 42.5 28.45 33.29 A1 (119.44 E, 17.93 N) Sep. 19 37.5 28.65 33.07 Remote Sens. 2019(119.69, 11, 2431 E, 18.09 N) Sep. 23 47.5 28.25 33.119 of 19 (116.72 E, 16.86 N) Sep. 11 35.5 29.26 33.34 (116.84 E, 16.99 N) Sep. 15 36.5 28.84 33.18 A2 the diﬀerence(116.93 in mixed E, layer16.92 cooling N) or salinitySep. 19 reduction? 45.5This may be related 28.68 to the relatively 33.14 weaker intensity of Fung-Wong(116.95 E, 16.87 and theN) longer Sep. distance 23 between its 40.5 track and the ﬂoat28.34 location. 32.97

247 248 FigureFigure 6.6.Temperature Temperature and and salinity salinity profiles profiles observed observed by Argoby Argo floats floats A1 (Top, A1 (Top, (a,b)) and(a)–( A2b)) (Bottom,and A2 249 ((Bottom,c,d)). Curves (c)–(d with)). Curves different with colours different represent colours observations represent observations on different on dates. different dates. Figure7a,b and Figure8a–c show the changes of temperature and salinity in the upper ocean as 250 For Float A2, the MLD gradually increased from September 11 to 19 as a result of the influence well as that of the mixed layer before and after the sequential TCs at Station B4, which was located to 251 of two TCs. Since A2 was located on the left side of the TCs, the magnitude of mixed layer the right of Kalmaegi but left of Fung-Wong. It can be seen that the increase in MLD and decrease in 252 deepening was a little smaller than that of A1 with only a few meters. Meanwhile, during this MLT influenced by Kalmaegi were much larger than that induced by Fung-Wong, whereas the MLS 253 period both MLT and MLS dropped continuously. The decreases in MLT from September 11 to 15, increased during Kalmaegi but then decreased during Fung-Wong. The differences in the variations of 254 and from 15 to 19 were 0.42 °C and 0.16 °C, respectively. The declines in MLS were 0.16 and 0.04, MLD, MLT and MLS caused by Kalmaegi and Fung-Wong were mainly due to the large difference in 255 respectively. What leads to the difference in mixed layer cooling or salinity1 reduction? This may be the MSW of the two TCs. The MSW of Kalmaegi ranged from 33 to 36 m s− when it passed over this 1 region, while that of Fung-Wong was only 18 to 21 m s− . In addition, the turning of wind stress to the right side of TC’s track may resonate with the near-inertial oscillations generated by a TC, which resulted in stronger vertical mixing [3,19]. Figure7a,b shows that, the subsurface temperature at depth of ~50 to 100 m increased obviously, while the salinity above the depth of ~50 m increased first and then decreased after the two TCs. Compared with Figure3c, the observations at Stations B4 and B5 reproduced the process of SST change measured from satellite, captured the two cooling events and the difference in cooling intensity as well. Station B5 was located to the left side of both TCs’ tracks. As can be seen from Figure7c,d and Figure8d–f, compared with Station B4, the trends of MLD and MLT were similar but with weaker amplitudes, especially during the passage of Kalmaegi. There was no distinct change in MLS, probably because the salinity variation is constrained by many factors, such as precipitation and evaporation. It is worth mentioning that there was an obvious signal around September 16 that all isotherms within 200 m of the upper layer sank sharply (Figure7c,d). This is possibly caused by the resonation between Kalmaegi-generated near-inertial oscillation and the internal wave, which could produce more energy and lead to stronger vertical mixing. Remote Sens. 2019, 11, x FOR PEER REVIEW 10 of 20

256 related to the relatively weaker intensity of Fung-Wong and the longer distance between its track 257 and the float location. 258 Figures 7(a)–(b) and 8(a)–(c) show the changes of temperature and salinity in the upper ocean 259 as well as that of the mixed layer before and after the sequential TCs at Station B4, which was 260 located to the right of Kalmaegi but left of Fung-Wong. It can be seen that the increase in MLD and 261 decrease in MLT influenced by Kalmaegi were much larger than that induced by Fung-Wong, 262 whereas the MLS increased during Kalmaegi but then decreased during Fung-Wong. The 263 differences in the variations of MLD, MLT and MLS caused by Kalmaegi and Fung-Wong were 264 mainly due to the large difference in the MSW of the two TCs. The MSW of Kalmaegi ranged from 265 33 to 36 m s-1 when it passed over this region, while that of Fung-Wong was only 18 to 21 m s-1. In 266 addition, the turning of wind stress to the right side of TC’s track may resonate with the 267 near-inertial oscillations generated by a TC, which resulted in stronger vertical mixing [3,19]. Figure 268 7(a)–(b) shows that, the subsurface temperature at depth of ~50 to 100 m increased obviously, while 269 the salinity above the depth of ~50 m increased first and then decreased after the two TCs. 270 Compared with Figure 3(c), the observations at Stations B4 and B5 reproduced the process of SST 271 change measured from satellite, captured the two cooling events and the difference in cooling 272 intensity as well. 273 Station B5 was located to the left side of both TCs’ tracks. As can be seen from Figure 7(c)–(d) 274 and 8(d)–(f), compared with Station B4, the trends of MLD and MLT were similar but with weaker 275 amplitudes, especially during the passage of Kalmaegi. There was no distinct change in MLS, 276 probably because the salinity variation is constrained by many factors, such as precipitation and 277 evaporation. It is worth mentioning that there was an obvious signal around September 16 that all 278 isotherms within 200 m of the upper layer sank sharply (Figure 7(c)–(d)). This is possibly caused by 279 the resonation between Kalmaegi-generated near-inertial oscillation and the internal wave, which 280 could produce more energy and lead to stronger vertical mixing. 281 Consequently, the MLD deepened and MLT dropped after Kalmaegi or Fung-Wong, owing to 282 the entrainment and upwelling induced by the TC. Meanwhile, the MLS increased on the right side 283 Remoteof their Sens. tracks2019 ,but11, 2431decreased on the left side. The difference is mainly due to the asymmetry of 10 of 19 284 precipitation (the figure is not shown) brought by the TC [46].

285

286 FigureFigure 7. 7. VariationsVariations of oftemperature temperature (Top, (Top, (a) and (a,c ))(c)) and and salinity salinity (Bottom,(Bottom, ( b), dand)) vertical (d)) vertical proﬁles at Stations 287 B4profiles (Left) at andStations B5 (Right).B4 (Left) and The B5 dashed (Right). and The solid dashed vertical and solid straight vertical lines straight denote lines thedenote time the when Kalmaegi 288 Remotetime whenSens. 2019 Kalmaegi, 11, x FOR and PEER Fung-Wong REVIEW passed by, respectively. 11 of 20 and Fung-Wong passed by, respectively.

289 Figure 8. Variations of MLD (Top, (a,d)), MLT (Middle, (b,e)), and MLS (Bottom, (c,f)) at Stations B4 290 (Left)Figure and 8. B5 Variations (Right). of The MLD dashed (Top, ( anda) and solid (d)), vertical MLT (Middle, straight (b) linesand (e denote)), and MLS the (Bottom, time when (c) and Kalmaegi and 291 (f)) at Stations B4 (Left) and B5 (Right). The dashed and solid vertical straight lines denote the time Fung-Wong passed by, respectively. 292 when Kalmaegi and Fung-Wong passed by, respectively.

293 3.2.Consequently, Biological Response the MLD deepened and MLT dropped after Kalmaegi or Fung-Wong, owing to the entrainment and upwelling induced by the TC. Meanwhile, the MLS increased on the right side of their 294 Figure 9 depicts the temporal evolution of surface chl-a concentration before, during and after 295tracks the but passages decreased of Kalmaegi on the and left Fung-Wong. side. The diBeforeﬀerence TCs, isthe mainly chl-a concentration due to the asymmetryin the SCS and of CE precipitation 296(the region ﬁgure (region is not shown)R1 in Figure brought 9) was bya little the higher TC [46 than]. that in other areas of the WNP but fell within 297 the predominant value of ≤ 0.1 mg m-3 in typical summer in SCS [12]. Not surprisingly, three 2983.2. Biologicaltypical regions Response with obvious surface cooling are also noted with pronounced growth of chl-a after 299 sequential TCs. As mentioned in Section 3.1.1, the translation speed and intensity of the TCs were Figure9 depicts the temporal evolution of surface chl-a concentration before, during and after 300 both conducive to chl-a rise when they passed over these three regions. However, the extent of 301the passagesenhancement of varied Kalmaegi from andregion Fung-Wong. to region due to Before the specific TCs, mechanisms the chl-a concentration involved. in the SCS and CE

302

303 Figure 9. Satellite observed evolution of surface chl-a concentration (mg m-3) before (a), during (b) 304 and after (c) sequential TCs. The expression of TC tracks is the same as Figure 2. The black, gray and

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289

290 Figure 8. Variations of MLD (Top, (a) and (d)), MLT (Middle, (b) and (e)), and MLS (Bottom, (c) and 291 (f)) at Stations B4 (Left) and B5 (Right). The dashed and solid vertical straight lines denote the time 292 when Kalmaegi and Fung-Wong passed by, respectively. Remote Sens. 2019, 11, 2431 11 of 19 293 3.2. Biological Response

294 regionFigure (region 9 depicts R1 in the Figure temporal9) was evolution a little of highersurface thanchl-a concentration that in other before, areas during of the and WNP after but fell within 295 the passages of Kalmaegi and Fung-Wong. Before TCs, the chl-a concentration in the SCS and CE the predominant value of 0.1 mg m 3 in typical summer in SCS [12]. Not surprisingly, three typical 296 region (region R1 in Figure 9)≤ was a little higher− than that in other areas of the WNP but fell within 297 regionsthe predominant with obvious value surfaceof ≤ 0.1 cooling mg m-3are in typical also noted summer with in pronouncedSCS [12]. Not growth surprisingly, of chl-a three after sequential 298 TCs.typical As regions mentioned with obvious in Section surface 3.1.1 cooling, the translation are also noted speed with and pronounced intensity growth of the of TCs chl-a were after both conducive 299 tosequential chl-a rise TCs. when As mentioned they passed in Section over these 3.1.1, threethe translation regions. speed However, and intensity the extent of the of TCs enhancement were varied 300 fromboth regionconducive to regionto chl-a duerise towhen the they speciﬁc passed mechanisms over these three involved. regions. However, the extent of 301 enhancement varied from region to region due to the specific mechanisms involved.

302 3 303 FigureFigure 9. 9. SatelliteSatellite observed observed evolution evolution of surface of surface chl-a concentration chl-a concentration (mg m-3) before (mg ( ma),− during) before (b) (a), during (b) 304 andand after (c ()c sequential) sequential TCs. TCs. The ex Thepression expression of TC tracks of TC is tracksthe same is as the Figure same 2. asThe Figure black,2 gray. The and black, gray and red boxes represent three typical regions with obvious chl-a increase and surface cooling as well as shown in Figure3.

3 Inside the CE (region R1), the maximum increase (0.21 mg m− ) in chl-a concentration occurred near the center of the eddy. Owing to the special thermodynamic structure of the CE, the subsurface water with rich nutrients inside the eddy would be more likely to be brought to the euphotic zone by TC-enhanced vertical mixing. Therefore, the pre-existing CE could not only modulate the thermodynamic response of the upper ocean, but also cause changes in biological processes. As for the near-shore area (region R2), the average surface chl-a concentration increased from 0.38 3 to 0.53 mg m− . At certain locations (e.g., 118.4◦E, 20◦N) of the coastal area, the chl-a concentration 3 reached as high as 20 mg m− . Except for the influence of translation speed and intensity of TCs, two other mechanisms may be responsible for this. (1) The depth of water in areas tens of kilometers offshore is usually only tens of meters [47], which make it easier to bring the nutrient from the lower layer to the surface. (2) The heavy rainfall caused by TCs can trigger the enrichment of terrigenous nutrients in near-shore waters. 3 The peak value of chl-a rise in Luzon Strait (region R3) reached up to 0.58 mg m− . The chl-a 3 concentration even increased from 2.01 to 5.16 mg m− at the land-sea junction, demonstrating a prominent enhancement. It is noteworthy that the intensity of Fung-Wong had been continuously strengthened as it passed through this region during September 19 to 20. In addition to the mixing effect induced by sequential TCs, it can be observed from Figure 10 that both Kalmaegi and Fung-Wong caused strong upwelling with maximum EPV larger than 1.5 104 m s 1, which is able to transport × − subsurface nutrients upward to the euphotic zone as well. Compared with the period from September 14 to 21, the response of chl-a during September 22 to 29 was more remarkable, probably related to the lag response of chl-a and the superposition effect of sequential TCs [11,21,48].

3.3. Influence of Sequential TCs on the CE As mentioned in Sections 3.1 and 3.2, the pre-existing CE has a significant impact on both the thermodynamic and biological responses of the upper ocean to TCs. Conversely, TCs could also influence the structure and intensity of the eddy. In this study, it is of interest that the CE region interacted with two TCs successively. Before Kalmaegi, the SST inside the CE was about 29.5 ◦C, not obviously lower than that of background waters (Figure 11a). On September 13 and 14 when Kalmaegi passed over the eddy, there was a significant decrease of 3.18 ◦C in SST (Figure 11b). During this period, 1 1 the MSW ranged from 28.3 to 36.0 m s− . The translation speed was higher than 6.0 m s− , which is Remote Sens. 2019, 11, x FOR PEER REVIEW 12 of 20

305 red boxes represent three typical regions with obvious chl-a increase and surface cooling as well as 306 shown in Figure 3.

307 Inside the CE (region R1), the maximum increase (0.21 mg m-3) in chl-a concentration occurred 308 near the center of the eddy. Owing to the special thermodynamic structure of the CE, the subsurface 309 water with rich nutrients inside the eddy would be more likely to be brought to the euphotic zone 310 by TC-enhanced vertical mixing. Therefore, the pre-existing CE could not only modulate the 311 thermodynamic response of the upper ocean, but also cause changes in biological processes. 312 As for the near-shore area (region R2), the average surface chl-a concentration increased from 313 0.38 to 0.53 mg m-3. At certain locations (e.g., 118.4°E, 20°N) of the coastal area, the chl-a 314 concentration reached as high as 20 mg m-3. Except for the influence of translation speed and 315 intensity of TCs, two other mechanisms may be responsible for this. (1) The depth of water in areas 316 tens of kilometers offshore is usually only tens of meters [47], which make it easier to bring the 317 nutrient from the lower layer to the surface. (2) The heavy rainfall caused by TCs can trigger the 318 enrichment of terrigenous nutrients in near-shore waters. -3 319 RemoteThe Sens. peak2019, 11 value, 2431 of chl-a rise in Luzon Strait (region R3) reached up to 0.58 mg m . The chl-a12 of 19 320 concentration even increased from 2.01 to 5.16 mg m-3 at the land-sea junction, demonstrating a 321 prominent enhancement. It is noteworthy that the intensity of Fung-Wong had been continuously 322 deﬁnedstrengthened as a “fast-moving” as it passed through TC [3]. this The region conditions during were September favorable 19 forto 20. the In formation addition ofto strongthe mixing vertical 323 mixing,effect induced especially by tosequential the right TCs, side it of can the be TC’s observed track. Afterfrom that,Figure the 10 water that both temperature Kalmaegi gradually and 324 recoveredFung-Wong but caused the process strong wasupwelling then disturbed with maximum when EPV Fung-Wong larger than passed 1.5×10 by.4 m On s–1 September, which is able 19 to when 325 Fung-Wongtransport subsurface left this area, nutrients a distinctly upward extreme to the coldeuphotic patch zone was as observed well. Compared again in with the CE the region period with 326 from September 14 to 21, the response of chl-a during September 22 to 29 was more remarkable, a much stronger cooling of up to 3.28 ◦C compared to that on September 9 (Figure 11c). By September 327 30,probably more than related 10 days, to the this lag cold response patch was of stillchl-a evident and the (Figure superposition 11d). effect of sequential TCs 328 [11,21,48].

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329343 formation of strong vertical mixing, especially to the right side of the TC’s track. After that, the 344 water temperature gradually recovered but1 the process was then disturbed when Fung-Wong 1 Figure 10. The wind ﬁeld (arrows; m s−−1 ) at 10 m above sea surface and estimated EPV (colours; m−1 s− ) 330345 Figure 10. The wind field (arrows; m s ) at 10 m above sea surface and estimated EPV (colours; m s ) passedon Septemberby. On September 15 (a), 1919 andwhen 20 Fung-Wong (b). The expression left this area, of TC a tracksdistinctly is the extreme same ascold Figure patch2. was The red and 331346 observedon September again in the 15 (CEa), region19 and with20 (b a). muchThe expression stronger cooling of TC tracks of up isto the3.28 same °C compared as Figure to2. thatThe onred and green dots denote the center locations of Kalmaegi and Fung-Wong at 00:00 UTC, respectively. The red 332347 Septembergreen dots9 (Figure denote 11(c)). the center By September locations 30, of Kalmaemore thangi and 10 days,Fung-Wong this cold at 00:00patch UTC,was stillrespectively. evident The box represents region R3 depicted in Figure9. 333348 (Figurered 11(d)). box represents region R3 depicted in Figure 9.

334 3.3. Influence of Sequential TCs on the CE 335 As mentioned in Sections 3.1 and 3.2, the pre-existing CE has a significant impact on both the 336 thermodynamic and biological responses of the upper ocean to TCs. Conversely, TCs could also 337 influence the structure and intensity of the eddy. In this study, it is of interest that the CE region 338 interacted with two TCs successively. Before Kalmaegi, the SST inside the CE was about 29.5 °C, not 339 obviously lower than that of background waters (Figure 11(a)). On September 13 and 14 when 340 Kalmaegi passed over the eddy, there was a significant decrease of 3.18 °C in SST (Figure 11(b)). 341 During this period, the MSW ranged from 28.3 to 36.0 m s−1. The translation speed was higher than 342 6.0 m s−1, which is defined as a “fast-moving” TC [3]. The conditions were favorable for the

349 350 FigureFigure 11. EvolutionEvolution of ofsatellite satellite observed observed SST (Top, SST (Top,(a)–(d ())a –andd)) negative and negative SSHA (Bottom, SSHA (Bottom, (e)–(h)) in (e –h)) in the CE 351 regionthe CE before,region before, during during and after and sequentialafter sequential TCs. TC Thes. The expression expression of of TC TC tracks tracks isis thethe samesame as as Figure2. The 352 redFigure and 2. green The red dots and denote green dots the centerdenote locationsthe center locations of Kalmaegi of Kalmaegi and Fung-Wong and Fung-Wong at 00:00 at 00:00 UTC, respectively. 353 UTC, respectively. Figure 12 shows the variation of upper layer temperature at the eddy center. It can be seen that, 354 Figure 12 shows the variation of upper layer temperature at the eddy center. It can be seen that, the 29 C isotherm, which was initially at a depth of ~50 m, rose rapidly to the surface on September 355 the 29◦ °C isotherm, which was initially at a depth of ~50 m, rose rapidly to the surface on September 356 1414 and and outcroppedoutcropped after after that that until until September September 26. From 26. September From September 14 to 15, all 14isotherms to 15, allexhibited isotherms a exhibited 357 adownward trend. trend. For Forexample, example, the 27 the °C 27isotherm◦C isotherm deepened deepened from the depth from of the ~60 depth m to ~80 of ~60m. m to ~80 m. 358 TheseThese isotherms isotherms then rose rose slowly slowly until until the the foll followingowing TC TCFung-Wong Fung-Wong interacted interacted with the with eddy. the eddy. Under 359 theUnder inﬂuence the influence of the of sequential the sequential TCs, TCs, the the isotherms isotherms tended tended to to descenddescend as as a a whole, whole, which which means the 360 verticalmeans the mixing vertical eﬀ mixingect plays effect a dominantplays a dominant role in role the in surfacethe surface cooling cooling of of the the CECE region.

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361 Figure 12. 362 Figure 12.HYCOM HYCOM output output of temperatureof temperature proﬁle profile at theat the center center of theof the CE CE on on September September 9. The9. The dash dash and solid lines denote the time when Kalmaegi and Fung-Wong passed by the eddy, respectively. 363 and solid lines denote the time when Kalmaegi and Fung-Wong passed by the eddy, respectively. The intensity of a CE can be depicted by negative values of SSHA [49]. As shown in Figure 11, 364 The intensity of a CE can be depicted by negative values of SSHA [49]. As shown in Figure 11, the SSHA at eddy center dropped by ~10 cm after the passage of Kalmaegi. Subsequently, Fung-Wong 365 the SSHA at eddy center dropped by ~10 cm after the passage of Kalmaegi. Subsequently, passed by and the SSHA dropped to the lowest value (~15 cm) by September 20. The northwestern 366 Fung-Wong passed by and the SSHA dropped to the lowest value (~15 cm) by September 20. The part of the pre-existing CE was visibly strengthened by Fung-Wong and moved westward slightly. 367 northwestern part of the pre-existing CE was visibly strengthened by Fung-Wong and moved It is noted that the CE was intensiﬁed by both TCs although with varying degrees of impact, mainly 368 westward slightly. It is noted that the CE was intensified by both TCs although with varying because the MSW of Kalmaegi was twice that of Fung-Wong during this period. 369 degrees of impact, mainly because the MSW of Kalmaegi was twice that of Fung-Wong during this 370 3.4.period. Possible Causes of Sudden Track Change in Sequential TCs Scenario

371 3.4.In Possible additional Causes to theof Sudden significant Track modulationChange in Sequential on the ocean TCs Scenario environment, sequential TCs usually result in an unusual track, as indicated by various studies [50–52]. As shown in Figure1a, Fung-Wong 372 shifted westwardIn additional to the to Luzonthe significant Strait following modulation the prior on the TC ocean Kalmaegi environment, before September sequential 20. TCs However, usually 373 Fung-Wongresult in suddenlyan unusual turned track, northward as indicated passing by the va easternrious studies coast of [50–52]. the Taiwan As Island.shown Isin the Figure sudden 1(a), 374 changeFung-Wong of Fung-Wong’s shifted trackwestward related to thethe prior Luzon TC Kalmaegi?Strait following This study the triesprior to answerTC Kalmaegi this question before 375 bySeptember analyzing both20. However, atmospheric Fung-Wong and oceanic suddenly environments. turned Firstnorthward of all, tracks passing of TCsthe areeastern mostly coast driven of the 376 byTaiwan large-scale Island. steering Is the flow sudden in the change middle of troposphere. Fung-Wong’s However, track related the TC-related to the prior circulation TC Kalmaegi? obscures This 377 thestudy identification tries to answer of the steeringthis question flow by as theanalyzin TCs areg both always atmospheric embedded and in oceanic complex environments. environmental First 378 circulations.of all, tracks A TC-removalof TCs are method,mostly driven which by was larg developede-scale steering by Kurihara flow etin al.the (1993, middle 1995) troposphere. [53,54], 379 canHowever, objectively the identify TC-related an asymmetric circulation TC obscures component the id toentification extract a smooth of the large-scalesteering flow environmental as the TCs are 380 fieldalways [55,56 ].embedded Using this in TC-removal complex method,environmental the background circulations. wind A field, TC-removal which represents method, the which steering was 381 developed by Kurihara et al. (1993, 1995) [53,54], can objectively identify an asymmetric TC flow in the middle troposphere, is extracted to trace the TC’s movement. 382 component to extract a smooth large-scale environmental field [55,56]. Using this TC-removal Variations of environment geopotential height and wind in the middle troposphere from September 383 method, the background wind field, which represents the steering flow in the middle troposphere, 18 to 21 are shown in Figure 13. On September 18, the western North Pacific subtropical high (WNPSH) 384 is extracted to trace the TC’s movement. was significantly strengthened with the 5880 gpm contour penetrating southward to approximately 385 Variations of environment geopotential height and wind in the middle troposphere from 10◦N and dominated the entire tropical Northwestern Pacific (Figure 13a). Easterly prevailed to the 386 September 18 to 21 are shown in Figure 13. On September 18, the western North Pacific subtropical south of the WNPSH and steered the TC Fung-Wong to the west. West of Fung-Wong, a significant ridge 387 high (WNPSH) was significantly strengthened with the 5880 gpm contour penetrating southward and a trough appeared over the SCS and the Philippine Island (Figure 13a). Such ridge and trough were 388 to approximately 10°N and dominated the entire tropical Northwestern Pacific (Figure 13(a)). related to the Rossby energy dispersion radiating from the prior TC Kalmaegi which had dissipated 389 Easterly prevailed to the south of the WNPSH and steered the TC Fung-Wong to the west. West of over the Indochina Peninsula [57,58]. Affected by the energy dispersion, the 5880 gpm contour to the 390 Fung-Wong, a significant ridge and a trough appeared over the SCS and the Philippine Island south of the WNPSH wriggled sharply which resulted in a breakdown of the WNPSH. Thus, the trade 391 (Figure 13(a)). Such ridge and trough were related to the Rossby energy dispersion radiating from 392 the prior TC Kalmaegi which had dissipated over the Indochina Peninsula [57,58]. Affected by the 393 energy dispersion, the 5880 gpm contour to the south of the WNPSH wriggled sharply which

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394 resulted in a breakdown of the WNPSH. Thus, the trade easterly turned to northward since 395 September 19 (Figure 13(b)–(d)). Meanwhile, Fung-Wong turned northward following the 396 transition of the environment steering flow. 397 Figures 13(e) and (f) illustrate the variation of environmental flow steering the TC. The zonal 398 steering flow changed from easterly to westerly during the period from September 18 to 20 (Figure. 399 13(e)), preventing Fong-Wong from moving further westward. In particular, from September 19 to 400 20, weak steering flow corresponded with the slow translation speed (less than 4 m s-1) of 401 Fung-Wong. The northward steering flow suddenly strengthened during September 20, resulting in 402 Remotepoleward Sens. 2019acceleration, 11, 2431 of Fung-Wong (Figure 13(f)). The zonal steering flow was about twice14 of as 19 403 strong as the meridional flow before September 19 but the meridional steering flow dominated after 404 Septembereasterly turned 20. Thus, to northward the sudden since northward September turning 19 (Figure of 13Fung-Wongb–d). Meanwhile, is attributed Fung-Wong to the turnedabrupt 405 changenorthward of the following environmental the transition flow in of association the environment with the steering Rossby ﬂow. energy dispersion of the prior TC 406 Kalmaegi.

407 1 408 Figure 13. 500500 hPa hPa geopotential geopotential height height (colour; (colour; gp gpm)m) and and wind wind field field (black (black arrows; arrows; m m s− s1)− averaged) averaged at at 500–700 hPa. Spatial distributions of 500 hPa geopotential height and wind field averaged at 409 500-700 hPa. Spatial distributions of 500 hPa geopotential height and wind field averaged at 500-700 500–700 hPa before (a,b), during (c) and after (d) the change of Fung-Wong’s track. The cyan line 410 hPa before (a)–(b), during (c) and after (d) the change of Fung-Wong’s track. The cyan line indicates indicates the value of the geopotential height of 5880 gpm at 500 hPa. The expression of TC tracks is 411 the value of the geopotential height of 5880 gpm at 500 hPa. The expression of TC tracks is the same the same as Figure2. The green dot denotes the center location at 00:00 UTC of Fung-Wong. ( e,f) are 412 as Figure 2. The green dot denotes the center location at 00:00 UTC of Fung-Wong. (e) and (f) are temporal variations of zonal and meridional wind speed averaged at 500–700 hPa in a 5 5 region 413 temporal variations of zonal and meridional wind speed averaged at 500-700 hPa in a 5°◦ × 5°◦ region centered at Fung-Wong’s center location, respectively. Positive values of U and V denote the eastward 414 centered at Fung-Wong’s center location, respectively. Positive values of U and V denote the and northward winds, respectively. 415 eastward and northward winds, respectively. Figure 13e,f illustrate the variation of environmental flow steering the TC. The zonal steering flow 416 This pattern aroused the conceptual model of Carr et al. (1977) [59]. However, the critical changed from easterly to westerly during the period from September 18 to 20 (Figure 13e), preventing 417 differences exist between this event and Carr’s model. According to Carr’s model, the WNPSH was Fong-Wong from moving further westward. In particular, from September 19 to 20, weak steering 418 located to the north of the subsequent TC. Combined with the Rossby1 wave dispersion-induced flow corresponded with the slow translation speed (less than 4 m s− ) of Fung-Wong. The northward 419 anticyclone to the east and equatorward of the prior TC, it will impose an equatorward steering flow suddenly strengthened during September 20, resulting in poleward acceleration of Fung-Wong (Figure 13f). The zonal steering flow was about twice as strong as the meridional flow before September 19 but the meridional steering flow dominated after September 20. Thus, the sudden northward turning of Fung-Wong is attributed to the abrupt change of the environmental flow in association with the Rossby energy dispersion of the prior TC Kalmaegi. This pattern aroused the conceptual model of Carr et al. (1977) [59]. However, the critical differences exist between this event and Carr’s model. According to Carr’s model, the WNPSH was located to the north of the subsequent TC. Combined with the Rossby wave dispersion-induced anticyclone to the east and equatorward of the prior TC, it will impose an equatorward environmental Remote Sens. 2019, 11, x FOR PEER REVIEW 16 of 20 Remote Sens. 2019, 11, 2431 15 of 19 420 environmental flow steering the following TC southwest. In this case, the trade easterly to the south 421 of the WNPSH penetrated further equatorward. Modulated by the Rossby wave, the northward 422 flowsteering steering flow theformed following and steered TC southwest. the subsequent In this case, TC thepoleward. trade easterly The differences to the south in ofthe the location WNPSH of 423 penetratedthe WNPSH further are the equatorward. key for the Modulated opposite moving by the Rossby direction wave, of the northwardsubsequent steering TC between flow formed Carr’s 424 andmodel steered and this the subsequentevent. TC poleward. The differences in the location of the WNPSH are the key for 425 the oppositeIn addition moving to the direction favorable of theatmo subsequentspheric conditions, TC between oceanic Carr’s factors model are and also this likely event. to affect the 426 northwardIn addition turning to the of favorable Fung-Won atmosphericg. Figure conditions, 14 displays oceanic the factors distributions are also likelyof some to aff ectocean the 427 northwardenvironmental turning variables of Fung-Wong. on Septembe Figurer 19, 14 i.e., displays before the Fung-Wong distributions turned of some to the ocean north. environmental It is found 428 variablesthat SST in on the September SCS dropped 19, i.e., obviously before Fung-Wong after Kalmae turnedgi. It was to the only north. ~28.4 It°C is and found lower that than SST SST in the in 429 SCSLuzon dropped Strait obviouslyand the coastal after Kalmaegi. region of It Taiwan was only Island. ~28.4 ◦Simultaneously,C and lower than lower SST inUOHC, Luzon Straitshallower and 430 theMLD coastal and D26 region were of Taiwanalso observed Island. in Simultaneously, the SCS. It is believed lower UOHC, that the shallower maintenance MLD of and a mature D26 were TC 431 alsorequires observed heat energy in the SCS.supplement It is believed pumping that from the maintenancethe warm ocean. of a A maturepparently, TC requiresthe ocean heat conditions energy 432 supplementin the SCS were pumping not favorable from the warmfor the ocean. maintenanc Apparently,e of a TC. the oceanThus, conditionswe speculate in thethat SCS Fung-Wong were not 433 favorabletended to formove the to maintenance areas with ofwarmer a TC. Thus, ocean we condit speculateions other that Fung-Wongthan shifting tended further to westward move to areas into 434 withthe colder warmer SCS. ocean conditions other than shifting further westward into the colder SCS.

435 Figure 14. Distributions of SST (a), MLD (b), D26 (c) and UOHC (d) on September 19. The expression of 436 Figure 14. Distributions of SST (a), MLD (b), D26 (c) and UOHC (d) on September 19. The expression TC tracks is the same as Figure2. The green dot denotes the center location at 00:00 UTC of Fung-Wong. 437 of TC tracks is the same as Figure 2. The green dot denotes the center location at 00:00 UTC of 438 4. ConclusionsFung-Wong. The combination of satellite data, numerical model outputs and in situ observations provides 439 4. Conclusions a unique opportunity to study the influence of TCs on the upper ocean. In this paper, multi-platform 440 datasetsThe werecombination used to of investigate satellite data, the thermodynamic numerical model and outputs biological and in responses situ observations of the upper provides ocean a 441 tounique two sequentialopportunity TCs to overstudy the the NWP, influence i.e., Kalmaegiof TCs on andthe upper Fung-Wong ocean. inIn 2014.this paper, The possible multi-platform causes 442 ofdatasets the sudden were used change to investigate of Fung-Wong’s the thermodynami track were alsoc and explored biological considering responses both of the atmospheric upper ocean and to 443 oceanictwo sequential environments. TCs over the NWP, i.e., Kalmaegi and Fung-Wong in 2014. The possible causes of the 444 suddenAfter change two TCs of Fung-Wong’s passed by, the track SST were significantly also explored decreased considering due to the both strong atmospheric oceanic entrainmentand oceanic 445 andenvironments. upwelling. Three distinct cold patches were observed along their tracks. The magnitude and 446 extentAfter of sea two surface TCs passed cooling by, are the not SST only significantly highly related decreased to the intensity due to andthe strong translation oceanic speed entrainment of the TC, 447 butand also upwelling. associated Three with distinct the ocean cold background patches were environments observed(e.g., along MLD, their D26 tracks. and UOHC).The magnitude Double TCsand 448 hadextent superimposed of sea surface eff coolingects on theare uppernot only ocean. highly They related deepened to the the intensity mixing and layer translation and lower speed the MLT of the at 449 theTC, samebut also time. associated The change with of MLDthe ocean or MLT backgr on theound right environments side of the TC’s (e.g., track MLD, was strongerD26 and thanUOHC). that

Remote Sens. 2019, 11, 2431 16 of 19 on the left. The MLS showed a different trend, with a decrease on the left side of the TC but an increase on the right. Meanwhile, it is found that the surface chl-a concentration was enhanced by the TCs. The areas with particularly pronounced chl-a enhancement coincided well with surface cooling regions. The pre-existing CE plays a notable role in modulating both thermodynamic and biological responses of the upper ocean owing to its unique and relatively unstable thermodynamic structure. On the other hand, it was significantly influenced by the TCs. The CE was enhanced with SST drop of 3.28 ◦C and SSHA decline of ~15 cm. The present work indicated that the prior TC can affect the track of the subsequent TC by changing the atmospheric and ocean environments. The mature TC Kalmaegi radiated a Rossby wave energy southeastward which wriggled the environmental flow to the south of WNPSH. Consequently, the steering flow changed from westward to northward, leading to the abrupt northward turning of Fung-Wong. For another aspect, the possible impact of ocean environment on the movement of the TC was also pointed out. With lower UOHC, shallower MLD and D26, the colder SCS could not supply Fung-Wong with enough energy, which can help explain why Fung-Wong did not continue to move westward into the SCS but suddenly turned to the north. Although under different ocean background conditions, the upper ocean responses to TCs may differ, TC-induced strong upwelling and vertical mixing are the main factors that influence upper ocean conditions. Thus the main findings of this study, including sea surface cooling, chlorophyll enhancement, and subsurface warming, could shed light on one of the general behaviors of the upper ocean responses to TCs. Furthermore, the effect of atmospheric and oceanic environmental changes accompanying the prior TC on the characteristics of the following TC is highlighted, which may provide important insights into the forecasting of the TC’s track in sequential TCs scenario. Nevertheless, further studies are needed to improve our understanding of the relationship between the two sequential TCs and their interaction with the ocean by combining the coupled ocean-atmosphere numerical model with current observations.

Author Contributions: Conceptualization, J.N. and Q.X.; methodology, J.N. and Q.X.; software, J.N.; validation, J.N. and Q.X.; formal analysis, J.N.; investigation, J.N., Q.X. and T.F.; data curation, J.N., H.Z. and T.F.; writing—original draft preparation, J.N.; writing—review and editing, Q.X., T.F., H.Z., T.W.; supervision, Q.X., T.F. and T.W. Funding: This research was funded by the National Key Project of Research and Development Plan of China (Grant No. 2016YFC1401905), the Fundamental Research Funds for the Central Universities (Hohai University) (Grant Nos. 2019B18714 and 2018B702X14), the Postgraduate Research & Practice Innovation Program of Jiangsu Province (Grant No. KYCX18_0523), Dayu Scholar Program of Hohai University (for Q. Xu), the National Natural Science Foundation of China (Grant Nos. 41976163 and 41706002), and the National Program on Global Change and Air–Sea Interaction (Grant No. GASI-IPOVAI-04). Acknowledgments: The authors thank the editor and the anonymous reviewers for their constructive comments which help to improve the paper. We acknowledge the Joint Typhoon Warming Center (JTWC) for providing Typhoon information (http://www.usno.navy.mil/NOOC/nmfc-ph/RSS/jtwc/best_tracks), the Remote Sensing Systems for providing the SST data (http://www.remss.com/), the Copernicus Marine and Environment Monitoring Service (CMEMS) database for providing the SSHA dataset (http://marine.Copernicus.eu/), the GlobColour Project for providing the chl data (http://hermes.acri.fr/), the NOAA’s National Climatic Data Center for providing the ocean surface winds (http://www.ncdc.noaa.gov/oa/rsad/air-sea/seawinds.html), the China Argo Real-time Data Center for providing the Argo data (http://www.argo.org.cn/), the Hybrid Coordinate Ocean Model (HYCOM) for providing the ocean analysis data (https://www.hycom.org/), and the NCEP–DOE AMIP-II Reanalysis for providing the atmospheric fields data. Conflicts of Interest: The authors declare no conflict of interest.

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