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Article Ocean Response to Successive Typhoons Sarika and Haima (2016) Based on Data Acquired via Multiple Satellites and Moored Array

Han Zhang 1,2 , Xiaohui Liu 1,2,*, Renhao Wu 2,3, Fu Liu 1,4, Linghui Yu 5, Xiaodong Shang 5, Yongfeng Qi 5, Yuan Wang 1, Xunshu Song 1, Xiaohui Xie 1, Chenghao Yang 1, Di Tian 1 and Wenyan Zhang 6 1 State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China; [email protected] (H.Z.); [email protected] (F.L.); [email protected] (Y.W.); [email protected] (X.S.); [email protected] (X.X.); [email protected] (C.Y.); [email protected] (D.T.) 2 Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China; [email protected] 3 Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, and School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China 4 Key Laboratory of Mesoscale Severe Weather/MOE and School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China 5 State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China; [email protected] (L.Y.); [email protected] (X.S.); [email protected] (Y.Q.) 6 Institute of Coastal Research, Helmholtz-Zentrum Geesthacht, 21502 Geesthacht, Germany; [email protected] * Correspondence: [email protected]

Received: 25 August 2019; Accepted: 9 October 2019; Published: 11 October 2019

Abstract: Tropical cyclones (TCs) are natural disasters for coastal regions. TCs with maximum wind speeds higher than 32.7 m/s in the north-western Paciﬁc are referred to as typhoons. Typhoons Sarika and Haima successively passed our moored observation array in the northern South China Sea in 2016. Based on the satellite data, the winds (clouds and rainfall) biased to the right (left) sides of the typhoon tracks. Sarika and Haima cooled the sea surface ~4 and ~2 ◦C and increased the salinity ~1.2 and ~0.6 psu, respectively. The maximum sea surface cooling occurred nearly one day after the two typhoons. Station 2 (S2) was on left side of Sarika’s track and right side of Haima’s track, which is studied because its data was complete. Strong near-inertial currents from the ocean surface toward the bottom were generated at S2, with a maximum mixed-layer speed of ~80 cm/s. The current spectrum also shows weak signal at twice the inertial frequency (2f ). Sarika deepened the mixed layer, cooled the sea surface, but warmed the subsurface by ~1 ◦C. Haima subsequently pushed the subsurface warming anomaly into deeper ocean, causing a temperature increase of ~1.8 ◦C therein. Sarika and Haima successively increased the heat content anomaly upper than 160 m at S2 to ~50 and ~100 m◦C, respectively. Model simulation of the two typhoons shows that mixing and horizontal advection caused surface ocean cooling, mixing and downwelling caused subsurface warming, while downwelling warmed the deeper ocean. It indicates that Sarika and Haima sequentially modulated warm water into deeper ocean and inﬂuenced internal ocean heat budget. Upper ocean salinity response was similar to temperature, except that rainfall refreshed sea surface and caused a successive salinity decrease of ~0.03 and ~0.1 psu during the two typhoons, changing the positive subsurface salinity anomaly to negative

Keywords: ocean response; tropical cyclone; typhoon; temperature anomaly; salinity anomaly; wind speed; sea surface; mixed layer; South China Sea

Remote Sens. 2019, 11, 2360; doi:10.3390/rs11202360 www.mdpi.com/journal/remotesensing Remote Sens. 2019, 11, 2360 2 of 23

1. Introduction Tropical cyclones (TCs) are intense natural hazards that pose a significant threat to coastal and inland areas. In the regions around the Northwest Pacific, TCs with maximum wind speeds greater than 32.7 m/s are usually referred to as typhoons. The response of ocean to a tropical cyclone is dramatic and not only impacts the local ocean environment [1–4], global ocean heat transport [5–7], and kinetic energy budget [8–10], but also changes the development of the tropical cyclone itself through TC–ocean feedbacks [11–14]. The response is indeed a hot topic in the study of the atmosphere and oceans. The strong wind stress of a tropical cyclone induces a significant near-inertial horizontal current [15– 19]. The near-inertial current normally decays within 5–20 inertial periods and propagates both horizontally and vertically in the ocean [20,21]. The near-inertial current is accompanied by alternative upwelling and downwelling (near-inertial pumping) [22], which is asymmetric with a rapid transition from a maximum in the downwelling phase to a maximum in the upwelling phase, followed by a gradual transition to the next downwelling maximum [23,24]. The horizontal and vertical propagation of the near-inertial current results in wave dispersion and propagation of kinetic energy [10,16,25,26], which can also generate super-inertial internal waves such as double-inertial frequency (2f ) waves [27,28] that contribute to the energy cascade toward dissipation. In the Northern (or Southern) Hemispheres, the upper ocean current responses to a tropical cyclone are respectively biased to the left and right sides of the TC track, owing to the better wind-current resonance on the right (or left) sides [29,30]. The TC-induced near-inertial current enhances the velocity shear in the mixed layer [31], deepens the mixed layer, cools sea surface, and warms subsurface [6,7]. The sea surface temperature (SST) cooling was usually by 1–6 ◦C[2,4,31–35], and by more than 10 ◦C in some extreme cases [36,37].Owing to the rightward (or leftward) bias of the current response, the temperature response is also usually biased to the right side (or left side) of the TC track in the Northern (or Southern) Hemisphere [15,22]. Besides mixing, the vertical advection (upwelling and downwelling) and horizontal advection can also modulate the oceanic temperature structure. In general, the subsurface warm anomaly can be strengthened or weakened by upwelling or downwelling [15,22,38], and the effect of horizontal advection depends on the current speed and horizontal temperature gradient [22]. The vertical advection mainly influences the subsurface and deeper ocean, as Argo data reveal that upwelling contributes an average of 15% of the cooling in the near-surface layer (10–30 m), 84% in the subsurface layer (30–250 m), and 94% in the deep layer (250–600 m) during the period of 0.5–2.5 days after the passage of a typhoon [39]. The ocean temperature response to TCs contributes not only to the local ocean environment, but also to the global meridional heat transport [6,7]. Studies show that TCs are responsible for 1.87 PW (11.05 W/m2) of the annual global heat transfer from the ocean to atmosphere [40]. The response of ocean salinity to a TC is similar to the temperature response [41,42], except for the sea surface salinity decrease by precipitation [42]. In general, most observations have revealed positive and negative sea surface salinity anomalies on the right and left sides of TC tracks in the Northern Hemisphere [41,43–45]. Although the oceanic response to a tropical cyclone was widely studied in the past decades, there are still many aspects that are waiting for further study. For example, the ocean response to sequential tropical cyclones was seldom studied before. Some previous observation shows that the second TC usually cools the ocean surface cold wake of a preceding TC [46,47] and tends to be weakened as it travels over the cold wake of the first TC [47,48], but further study was in a shortage because of the limited amount of in situ observation. In 2016, our moored observation array in the northern South China Sea captured two successively passing TCs, Sarika and Haima, over a period of four days. Combined with remote sensing data, the observations provided a good opportunity to study oceanic response to successive TCs. We will show how Sarika and Haima influenced the local ocean current, temperature, and salinity, and particularly decomposed the inner ocean mechanisms that modulated Remote Sens. 2019, 11, 2360 3 of 23 the upper ocean temperature using a three dimensional model, then summarize with a sketch how the temperature profiles were changed successively by the two TCs. Hopefully the result of this paper will help us to better understand the TC–ocean interaction, especially the upper ocean thermal response to sequential tropical cyclones.

2. Data and Method

2.1. Remote Sensing Data Acquired via Multiple Satellites The 1 hourly cloud-top brightness temperature data with 0.05 0.05 horizontal resolution used ◦ × ◦ in this study was acquired by the Himawari-8 satellite that downloaded from the website of Kochi University. The 6 hourly surface wind data with 0.25 0.25 horizontal resolution was acquired using ◦ × ◦ the cross-calibrated multi-platform (CCMP) version 2.0 ocean vector wind analysis system [49]. The 3 hourly rainfall data with 0.25 0.25 horizontal resolution was obtained through the CPC MORPHing ◦ × ◦ technique (CMORPH) [50] by the National Oceanic and Atmospheric Administration. The data of the daily sea surface height anomalies and geostrophic velocity anomalies with 0.25 0.25 horizontal ◦ × ◦ resolution were obtained from the Ssalto/Duacs altimeter products that were produced and distributed by the Copernicus Marine and Environment Monitoring Service (CMEMS). The daily sea surface temperature data with 0.088 0.088 horizontal resolution consisted of optimally interpolated (OI) ◦ × ◦ microwave sea surface temperature (SST) data [51]. The eight-day running average Level 3 sea surface salinity data with 0.25 0.25 horizontal resolution was obtained using RSS soil moisture active ◦ × ◦ passive (SMAP) sea surface salinity analysis [52]. See Table1 for the sources (websites) of the data.

Table 1. Sources of Data *.

Data Website Cloud-top brightness temperature http://weather.is.kochi-u.ac.jp/sat/GAME/2016/Oct/IR1 Surface wind http://www.remss.com/measurements/ccmp https://www.cpc.ncep.noaa.gov/products/janowiak/ Rainfall cmorph_description.html Sea surface height anomaly, geostrophic velocity http://marine.copernicus.eu Sea surface temperature http://data.remss.com/SST/daily/mw_ir/v05.0/netcdf/2016 http://data.remss.com/smap/SSS/V04.0/FINAL/L3/8day_ Sea surface salinity running/2016 JTWC best track data http://www.usno.navy.mil/JTWC http://www.jma.go.jp/jma/jma-eng/jma-center/rsmc-hp- JMA best track data pub-eg/besttrack.html CMA best track data http://tcdata.typhoon.gov.cn * JTWC, JMA and CMA correspond to the Joint Typhoon Warning Center of the UST, the Japan Meteorological Agency, and the China Meteorological Administration.

2.2. Buoy and Mooring Stations In 2016, we set up three observation stations to monitor the tropical cyclones that passed by. Stations 1 and 2 (S1 and S2) contained buoys and moorings (B1 and M1; B2 and M2), while Station 3 (S3) contained only a buoy (B3). Tropical cyclone Sarika travelled through the observation array between October 16 and 18, and tropical cyclone Haima followed on the right side of the observation array between October 20 and 21. Unfortunately, Buoy 3 (B3) and Buoy 1 (B1) were damaged on August 5 and September 16, respectively. Hence, only Mooring 1 (M1), Buoy 2 (B2), and Mooring 2 (M2) were operational during the TCs. We mainly analyze the ocean response at Station 2 (B2 and M2, Tables2 and3) in the main body of this paper because its data was complete, and present the observation from M1 in AppendixA as a supplement. Remote Sens. 2019, 11, 2360 4 of 23

Table 2. Observation instruments and measured elements at Buoy 2 *.

Measured Instruments Designed Depth (m) Resolution (s) Elements Gill-MetPak Meteorology 4 m above from sea surface 1 (3600) JFE-A7CT T, S 12 22 52 68.5 90.5 111 131 142 162 182 202 242 282 322 362 402 442 482 300 \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ ONT7000 T 17 27.5 44 49.5 63 74 85 96 106 147 157 302 342 382 422 462 502 1 \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ SBE-56 T 33 38.5 57.5 79.5 101 116 121 126 121 126 137 152 172 192 222 262 1 \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ location: 133 m, uplooking; ﬁrst bin: 24.74 m; last bin: 136.74 m; bin RDI 75K-ADCP U, V 300 size: 16 m location: 1385 m, uplooking; ﬁrst bin: 15.69 m; last bin: 255.69; bin size: RDI 300K-ADCP U, V 600 8 m * Red font indicates that the instrument was lost during the observation, while blue font indicates no data or some error in data. The meteorological station (Gill-MetPak) observations occurred every second, with outputs every 3600 s for air temperature, pressure, wind, and dew temperature 4 m above the sea surface. T, S, P, U, and V respectively denote temperature, salinity, pressure, eastward current speed, and northward current speed.

Table 3. Observation instruments and measured elements at Mooring 2 *.

Measured Instrument Design Installation Depth (m) Resolution (s) Element SBE-37 T, S, P 300/315/330/345/360/375/400/450/500/L160/L140/L120/L100/L80/L60/L40 120 SBE-39 T, P 600/700/800 120 Seaguard U, V 600/700/800/L80 600 Location: 500 m, uplooking; ﬁrst bin: 24.45 m; last bin: 600.45 m; bin RDI 75K-ADCP U, V 600 size: 16 m Location: L80 m, downlooking; ﬁrst bin: 6.15 m; last bin: 110.15 m; bin RDI 75K-ADCP U, V 600 size: 4 m * L indicates above ocean bottom; for example, L140 means 140 m above the ocean bottom. T, S, P, U, and V denote temperature, salinity, pressure, eastward current speed, and northward current speed, respectively.

Buoy 2 was deployed at 114◦54.42’ E and 19◦27.328’ N at 09:30 Beijing Time (01:30 UTC) on 31 July and recovered at 20:40 Beijing Time (12:40 UTC) on 26 October. Mooring 2 was deployed at 114◦54.324’ E and 19◦28.976’ N at 12:15 Beijing Time (04:15 UTC) on 31 July and recovered at 08:30 Beijing Time (01:30 UTC) on 25 October. Note that observation in Station 2 (Tables2 and3) includes meteorology data from 4 m above the sea surface, as well as ocean temperature, salinity, and current from ocean surface to bottom. The meteorology data includes wind, air pressure, humidity, and temperature.

2.3. Typhoons Sarika and Haima The best-track datasets of tropical cyclones were obtained from the Joint Typhoon Warning Center (JTWC), the Japan Meteorological Agency (JMA), and the China Meteorological Administration (CMA) [53] (Table1). The TC tracks from the three sources were observed to be quite consistent (Figure1). Sarika was formed in the northwest of the Paciﬁc Ocean (129.7 ◦ E, 12.5◦ N) at 18:00 UTC on October 12, moved northwestward, and grew from a tropical depression into a typhoon. It travelled through the Philippines, with its maximum wind speed reaching 42 m/s, and then weakened after entering the South China Sea, where its maximum wind speed fell to 38 m/s. When it travelled through our observation array, its translational speed was ~6.53 m/s. Stations 1 and 2 were respectively biased by ~15.77 and ~254.49 km to the right side of Sarika’s track. Beyond the observation array, Sarika quickly weakened and dissipated after making landfall on the Hainan Island and the adorning mainland. Remote Sens. 2019, 11, x FOR PEER REVIEW 4 of 23 meteorology data from 4 m above the sea surface, as well as ocean temperature, salinity, and current

Remotefrom Sens.ocean2019 surface, 11, 2360 to bottom. The meteorology data includes wind, air pressure, humidity,5 ofand 23 temperature.

Figure 1. TracksTracks of Typhoons Sarika and Haima obtain obtaineded from the Joint Typhoon Warning Center (JTWC) data (orange), Japan Meteorological Agency (JMA) data (brown), and ChinaChina MeteorologicalMeteorological Administration (CMA) data (black), showing their positions every 6 h (dots). The text boxes point to the UTC 00:00 of the the positions positions everyday, everyday, show the dates, sustained maximum wind speed, and central pressure obtained from the CMACMA data.data. The red numbersnumbers indicate the positions of the observation stations. The background shade indicates the topography.

Haima was alsoTable formed 2. Observation in the northwest instruments of the and Pacific measured Ocean elements (144.4 at◦ BuoyE, 7.2 2*.◦ N) at 12:00 UTC on October 14. It moved northwestward, growing from a tropical depression into a super typhoon, and Instrument Measured Resoluti travelled through the Philippines with its maximumDesigned wind speeddepth reaching(m) 68 m/s. It weakened after enterings the Southelements China Sea, where the maximum wind speed fell to 42 m/s, and travelledon through (s) Gill- our observationMeteorology array with a translation speed4 ofm ~7.18above m from/s. Stations sea surface 1 and 2 were respectively 1 (3600) biased by ~535.57MetPak and ~208.44 km to the right side of Haima’s track (Table4). Beyond the observations array, 12\22\52\68.5\90.5\111\131\142\162\182\202\242\282\322\362 HaimaJFE-A7CT quickly weakenedT, S and dissipated after making landfall on the mainland. 300 \402\442\482 17\27.5\44\49.5\63\74\85\96\106\147\157\302\342\382\422\46 ONT7000 T 1 Table 4. Details of Typhoons Sarika and Haima2 when\502 closest to Stations 1 and 2 *. 33\38.5\57.5\79.5\101\116\121\126\121\126\137\152\172\192\ SBE-56 T Sarika-S1 Sarika-S2 Haima-S1 Haima-S21 222\262 RDI 75K- Longitude (◦E)location: 133 112.168 m, uplooking; 114.907 first bin: 24.74 112.168 m; last bin: 114.907 LatitudeU, (VN) 18.036 19.469 18.036 19.469300 ADCP ◦ 136.74 m; bin size: 16 m Ocean Depth (m) ~2400 ~1450 ~2400 ~1450 RDI 300K- location: 1385 m, uplooking; first bin: 15.69 m; last bin: Distance to tropicalU, cyclone V track (km) 15.77 254.49 -535.57 -208.44600 ADCP Closest time 10/17, 13:00255.69; 10 bin/17, size: 00:00 8 m 10/20, 18:00 10/20, 18:00 * Red* font Depth indicates refers the that ocean the depth instrument at the observation was lost during station. the Positive observation, (negative) while values blue of the font distance indicates to tropical no data or some cycloneerror in track data. refers The to meteorological the right (left) side station of the (Gill-MetPak) track. observations occurred every second, with outputs every 3600 s for air temperature, pressure, wind, and dew temperature 4 m above the sea surface. T, S, P, U, and V respectivelyAs shown denote in Table temperature,5, the nondimensional salinity, pressure, translation eastward current speed speed, ( S) is and the northward ratio of the current local speed. inertial period to the translation speed of the TC [44,54]. The values of S for Sarika and Haima were close to 1, indicating that the oceanic responses to the two TCs were significantly biased to the right. The Rossby number of the mixedTable layer 3. Observation current (Q instruments) is the ratio and of themeasured horizontal elements advection at Mooring of the 2*. momentum to the Coriolis force [54]. The Q values for Sarika and Haima indicated insignificant nonlocal effects of the horizontal advections during the forced stages of the typhoons. Remote Sens. 2019, 11, 2360 6 of 23 Remote Sens. 2019, 11, x FOR PEER REVIEW 6 of 23

Table 5. Parameters of Typhoons Sarika and HaimaSarika *. Haima

Maximum wind speed (𝑉, m/s) 38.00 42.00 Sarika Haima Translational speed (𝑈, m/s) 6.53 7.18 Maximum wind speed (Vmax, m/s) 38.00 42.00 Radius of fastest wind (𝑟, km) 120.0 (37.04) 150.0 (46.3) Translational speed (U, m/s) 6.53 7.18 Mixed layer depth (ℎ, m) 45 50 Radius of fastest wind (rm, km) 120.0 (37.04) 150.0 (46.3) NondimensionalMixed layer translational depth (h , m) speed, (𝑆= ) 451.161 (3.760) 1.021 50 (3.308) mix Nondimensional translational speed, (S = U ) 1.161 (3.760) 1.021 (3.308) Rossby number of mixed layer current, (Qrm f = ) 0.253 0.257 τmax Rossby number of mixed layer current, (Q = ρ ) 0.253 0.257 * The values were calculated using the China MeteorologhmixUf ical Administration (CMA) best-track data when the two typhoons* The values were were close calculated to our usingobservation the China array. Meteorological Values in Administration brackets were (CMA) obtain best-tracked from data the when Joint the Typhoon two typhoons were close to our observation array. Values in brackets were obtained from the Joint Typhoon Warning Warning Center (JTWC) data set. 𝑟 without bracket is calculated from observations using the method of [15], Center (JTWC) data set. rm without bracket is calculated from observations using the method of [15], which is used which isfor used the wind for the ﬁeld wind of the field model of simulation.the modelh simulation.mix is estimated ℎ using is theestimated depth that using was the 0.5 ◦depthC cooler that than was ocean 0.5 °C cooler thansurface ocean with surface the temperature with the proﬁle temperature at S2 that profile was one at inertial S2 that period was one on average inertial after period the twoon average tropical cyclones. after thef two was calculated using the average latitude of S1, S2, and S3 (18.753 N). tropical cyclones. 𝑓 was calculated using the average latitude of ◦S1, S2, and S3 (18.753° N).

2.1.2.4. Typhoons Typhoons Sarika Sarika and and Haima Haima TheThe numerical numerical model model used in thisthis study study was was a three-dimensionala three-dimensional version version of the of Price–Weller–Pinkelthe Price–Weller– Pinkelmodel model (3DPWP) (3DPWP) [54,55 [54,55],], which which has has been been used used successfully successfully in in previousprevious studies to to simulate simulate and and understandunderstand the the physical physical processes processes involved involved in inthe the oceanic oceanic response response to toa TC a TC [15–17, [15–17 22,,22 56–58].,56–58]. The The modelmodel domain domain used used here here spans spans 1200 1200 km km in in the the across-track across-track direction direction and and 5600 5600 km km in in the the along-track along-track direction,direction, with with a ahorizontal horizontal resolution resolution of of 8 8km km and and a avertical vertical resolution resolution of of 10 10 m m with with the the ocean ocean depth depth ofof 1450 1450 m. m. The The time time resolution resolution is is120 120 s. s.The The mode modell starts starts from from rest, rest, and and the the initial initial temperature temperature and and salinitysalinity were were set set to to be be horizontally homogeneoushomogeneous using using the the average average proﬁles profiles from from Station Station 2 during 2 during UTC UTC00:00 00:00 on 14on October14 October to UTCto UTC 00:00 00:00 on on 16 16 October October for for Sarika Sarika and and during during UTC UTC 00:00 00:00 on on 18 18 October October to toUTC UTC 00:00 00:00 on on 20 20 October October for for Haima Haima (see (see Figure Figure2). The 2). CoriolisThe Coriolis parameter parameter for the for model the model was 4.861 was 3 1 × 4.861×1010− s−-3, s which-1, which corresponds corresponds to to the the latitude latitude of of Station Station 2 (19.4692 (19.469°N)◦N) and and an an inertial inertial period period of of 35.91 35.91 hr. hr.The The parameters parameters of of wind wind ﬁeld field for for Sarika Sarika and and Haima Haima in in model model were were thethe samesame asas thethe valuesvalues inin TableTable3 , 3,see see [[15]15] forfor moremore detailsdetails of of the the model model setup. setup.

FigureFigure 2. Initial 2. Initial temperature, temperature, salinity, salinity, and and density density profile proﬁless for for Sarika Sarika (red) (red) and and Haima Haima (blue) (blue) in in3DPWP 3DPWP modelmodel simulation. simulation. Profiles Proﬁles for for Sarika Sarika (Haima) (Haima) are are av averagederaged over over UTC UTC 00:00 00:00 on on 14 14 (16) (16) October October to toUTC UTC 00:0000:00 on on 16 16 (20) (20) October October of of the the observation observation at at Station Station 2. 2. 3DPWP: 3DPWP: three-dimensional three-dimensional version version of ofthe the Price–Weller–PinkelPrice–Weller–Pinkel model model.

3. Results

3.1. Results of Remote Sensing Using Multiple Satellite

3.1.1. Cloud and Rainfall

Remote Sens. 2019, 11, 2360 7 of 23

3. Results

3.1. Results of Remote Sensing Using Multiple Satellite

Remote3.1.1. Sens. Cloud 2019 and, 11, Rainfallx FOR PEER REVIEW 7 of 23 The cloud-top brightness temperatures shown in Figure3a–h reveal that the structures of Sarika and HaimaThe cloud-top were relatively brightness circular temperatures before they shown passed in Figures through 3a–3h the Philippines. reveal that the Note structures that lower of Sarikacloud-top and brightness Haima were temperature relatively represents circular higherbefore cloud-topthey passed height through and more the Philippines. convection. TheNote clouds that lowerfrom the cloud-top two typhoons brightness on the temperature right side ofrepresents the tracks higher weakened cloud-top after enteringheight and the more South convection. China Sea, Theresulting clouds in from a leftward the two asymmetry typhoons on of thethe brightnessright side of temperatures the tracks weakened (Figure3 b,f);after this entering may bethe due South to Chinathe local Sea, land–sea resulting distribution. in a leftward The asymmetry clouds gradually of the brightness dissipated temperatures after making (Figures landfall on3b and the Chinese3f); this maymainland. be due Station to the 1local was land–sea in the path distribution. of the eye The of Sarika clouds (Figure gradually3c), while dissipated Station after 2 was making on right landfall part onof thethe spiralChinese cloud mainland. band of Station Sarika. 1 Fourwas in days the later,path of the the left eye part of ofSarika the spiral (Figure cloud 3c), bandwhile ofStation Haima 2 wasinﬂuenced on right both part Stations of the 1spiral and 2.clou Thed rainfallband of (Figure Sarika.3 i–p)Four mainly days later, occurred the left near part the of eyewall, the spiral while cloud the bandspiral of cloud Haima band influenced showed someboth Stations weak precipitation. 1 and 2. The Both rainfall Stations (Figures 1 and 3i–3p) 2 experienced mainly occurred rainfall fromnear theboth eyewall, Sarika and while Haima. the spiral cloud band showed some weak precipitation. Both Stations 1 and 2 experienced rainfall from both Sarika and Haima.

Figure 3. ((a–ha–h)) Cloud-top Cloud-top brightness brightness temperatures temperatures obtained by the Himawari-8 satellite at 12:00 UTC between October 15 and 22, and (ii–p–p) correspondingcorresponding rainfall data obtained by the CPC MORPHingMORPHing technique (CMORPH)(CMORPH) data. data. The The white white hollowed hollowed dots dots indicate indicate the the buoy buoy and and mooring mooring stations; stations; the black the blacklines indicatelines indicate the tropical the tropical cyclone cy tracks;clone andtracks; the and black the dots black indicate dots indi the centerscate the of centers the tropical of the cyclones. tropical cyclones. 3.1.2. Wind and Sea Surface Heights 3.1.1.A Wind background and Sea Surface northeast Heights wind prevailed before the two typhoons (Figure4a). During Sarika and Haima,A background the wind northeast distribution wind was prevailed in accordance before the with two the typhoons cloud and (Figure precipitation 4a). During (Figure Sarika4a–h). and Haima,However, the contrary wind distribution to the cloud was and in precipitation, accordance the with wind the wascloud stronger and precipitation on the right side(Figures of the 4a–4h). tracks However,of Sarika and contrary Haima to when the cloud they travelled and precipitation, through our the observation wind was array stronger (Figure on 4theb,f). right The seaside surface of the tracksheights of exhibited Sarika and negative Haima and when positive they anomalies travelled atthrough Stations our 1and observation 2 (see Figure array4i–p). (Figures The geophysical 4b and 4f). The sea surface heights exhibited negative and positive anomalies at Stations 1 and 2 (see Figures 4i– 4p). The geophysical current anomaly indicated that Station 2 was on the boundary of a cyclonic (cold) eddy, which moved only a little during the two typhoons.

Remote Sens. 2019, 11, 2360 8 of 23

current anomaly indicated that Station 2 was on the boundary of a cyclonic (cold) eddy, which moved Remoteonly aSens. little 2019 during, 11, x FOR the PEER two typhoons.REVIEW 8 of 23

FigureFigure 4. ((a–ha–h)) Wind Wind data data obtained obtained by by CCMP CCMP at at 12:00 12:00 UTC UTC between between October October 15 15 and and 22 22 and and ( (i–pi–p)) CMEMSCMEMS seasea surfacesurface height height (color) (color) and and geostrophic geostrop currenthic current (vector) (vector) anomalies. anomalies. CCMP: cross-calibratedCCMP: cross- calibratedmulti-platform. multi-platform. CMEMS: CopernicusCMEMS: Copernicus Marine and Marine Environment and Environmen Monitoringt Monitoring Service. Service 3.1.3. Sea Surface Temperature and Salinity 3.1.1. Sea Surface Temperature and Salinity. Both Sarika and Haima caused sea surface cooling (Figures5a–h and6a–h), with the cooling Both Sarika and Haima caused sea surface cooling (Figures 5a–5h and 6a–6h), with the cooling strongest one day after the two typhoons. The cooling was biased a little to the right side of the typhoon strongest one day after the two typhoons. The cooling was biased a little to the right side of the tracks and gradually recovered after the cold wake. Station 1 was just at the core of the cold wake of typhoon tracks and gradually recovered after the cold wake. Station 1 was just at the core of the cold Sarika, while Station 2 was on the boundary of the cold wake. Conversely, Station 1 was away from wake of Sarika, while Station 2 was on the boundary of the cold wake. Conversely, Station 1 was the cold wake of Haima, while Station 2 was once again on the boundary of the typhoon’s cold wake. away from the cold wake of Haima, while Station 2 was once again on the boundary of the typhoon’s Similar to the sea surface temperature anomalies, the sea surface salinity was also increased by Sarika cold wake. Similar to the sea surface temperature anomalies, the sea surface salinity was also and Haima, with the anomalies in this case seeming to be biased to the left and right side of the tracks increased by Sarika and Haima, with the anomalies in this case seeming to be biased to the left and of the two typhoons, respectively (see Figures5i–p and6i–p). The heavy rainfall of Haima might have right side of the tracks of the two typhoons, respectively (see Figures 5i–5p, 6i–6p). The heavy rainfall refreshed the left side of its track a little. It should be noted that the maximum surface temperature of Haima might have refreshed the left side of its track a little. It should be noted that the maximum cooling (~4 ◦C) and salinity increase (~1.2 psu) caused by Sarika were greater than those caused by surface temperature cooling (~4 °C) and salinity increase (~1.2 psu) caused by Sarika were greater Haima (~2 ◦C and ~0.6 psu, respectively), possibly because the water was already mixed by Sarika, than those caused by Haima (~2 °C and ~0.6 psu, respectively), possibly because the water was and hence the cooling cannot be as much during Haima. However, it may also due to the diﬀerent already mixed by Sarika, and hence the cooling cannot be as much during Haima. However, it may local initial stratiﬁcations. also due to the different local initial stratifications.

RemoteRemote Sens. Sens.2019 2019, 11, ,11 2360, x FOR PEER REVIEW 9 of9 23 of 23 Remote Sens. 2019, 11, x FOR PEER REVIEW 9 of 23

Figure 5. (a–h) Microwave optimally interpolated (OI) sea surface temperature, and (i–p) soil Figure 5. (a–h) Microwave optimally interpolated (OI) sea surface temperature, and (i–p) soil moisture moistureFigure 5. active (a–h) passiveMicrowave (SMAP) optimally sea surface interpolated salinity at (O12:00I) sea UTC surface between temperature, October 15 andand 22.(i–p ) soil activemoisture passive active (SMAP) passive sea (SMAP) surface sea salinity surface at sa 12:00linity UTC at 12:00 between UTC Octoberbetween 15October and 22. 15 and 22.

Figure 6. (a–h) Sea surface temperature and (i–p) sea surface salinity anomalies at 12:00 UTC between Figure 6. (a–h) Sea surface temperature and (i–p) sea surface salinity anomalies at 12:00 UTC between October 15 and 22. The anomalies are relative to the conditions at 12:00 UTC on October 14. OctoberFigure 6. 15 (a–h and) Sea 22. surfaceThe anomalies temperature are relative and (i–p to) thesea conditionssurface salinity at 12:00 anomalies UTC on at October 12:00 UTC 14. between October 15 and 22. The anomalies are relative to the conditions at 12:00 UTC on October 14.

Remote Sens. 2019, 11, x FOR PEER REVIEW 10 of 23

3.1. Buoy and Mooring Observation Results at Station 2

3.1.1. Air–Sea Interface Figure 7 shows a background wind from the north-east with a velocity of ~10 m/s at Station 2 before Sarika, which is consistent with the satellite observations in Figure 3. The background air pressure and humidity were ~1010 hPa and ~83%, respectively. The wind, air pressure, and air humidity approached ~20 m/s, ~1000 hPa, and ~90% when Sarika was close to Station 2 and ~20 m/s, ~996 hPa, and ~90% when Haima was close (Figures 7a, 7c and 7e). The wind rotated clockwise under Sarika and anticlockwise under Haima, in accordance with the fact that Station 2 was on the right and left sides of the tracks of Sarika and Haima, respectively (Figure 7b). Note that wind speed observed by Station 2 was consistent with the data from satellite (Figure 7a), but wind direction was more irregular than satellite data (Figure 7b).

RemoteThe Sens. initial2019, 11 surface, 2360 air and sea surface temperatures were ~28.5 and ~29.5 °C at stations 1 and10 of 232, respectively (Figure 7d); Sarika reduced the former by ~1 °C to the minimum value of 28.4 °C around UTC 00:00 on 18 October, one day after the typhoon. Haima also cooled the sea surface temperature slightly.3.2. Buoy The and sea Mooring surface Observation temperature Results in Figure at Station 7d 2is the temperature observed by the sensor at the shallowest depth of 22 m. It is interesting that the surface air temperature increased slightly, to ~29 3.2.1. Air–Sea Interface °C, during the forced stage of Sarika and then fell to a minimum value of ~26.3 °C after one day. The sea surfaceFigure 7temperature shows a background was slightly wind higher from than the th north-easte surface air with temperature, a velocity although of ~10 m the/s at opposite Station was2 before sometimes Sarika, true which (Figure is consistent 7d), resulting with the in a satellite reversal observations of the ocean in surface Figure sensible3. The background heat flux. Note air pressurethat the sea and surface humidity temperature were ~1010 from hPa satellite and ~83%, data respectively. (OI SST) was The lower wind, than air pressure, the sea andsurface air temperaturehumidity approached observed ~20by mStation/s, ~1000 2 but hPa, more and consistent ~90% when with Sarika surface was closeair temperature to Station 2 and(Figure ~20 7d), m/s, ~996indicating hPa,and that ~90% OI SST when may Haima reflect was the closeair temperature (Figure7a,c,e). rather The than wind the rotated ocean clockwisetemperature under in the Sarika air– seaand surface. anticlockwise Another under air temperature Haima, in accordance minimum with of ~26.5 the fact °C thatoccurred Station when 2 was Haima on the was right closest and left to Stationsides of 2. the The tracks surface of Sarika heat flux and (Figure Haima, 7f) respectively revealed that (Figure the shortwave7b). Note thatradiation wind and speed latent observed heat flux by controlledStation 2 was the consistent air–sea interface with the heat data flux from during satellite Sarika (Figure and7 Haimaa), but wind(Figure direction 7f). The was ocean more gained irregular heat fromthan satellitethe shortwave data (Figure radiation7b). and lost heat to the air through the latent heat flux.

Figure 7. Time series of the ( a) sustained surface wind wind speed, speed, ( (bb)) wind wind direction, direction, ( (cc)) air air pressure, pressure, ( (dd,, red) surface air temperature, ( d, blue) sea surface temperature, temperature, ( (e)) air air humidity, humidity, surface fluxes ﬂuxes of the (f, blue) sensible heat, (f, red) latentlatent heat, (f, black)black) shortshort wavewave radiation, and (f, orange) long wave radiation at Station 2 during Sarika and Haima. Regarding Regarding the wind directions, N, W, S, and E indicate indicate the approach directions of the winds, namely, north, west, south, and east, respectively. The vertical black dashed lines represent the times when Sarika andand Haima were closest to Station 2. Black dots in (a,),b ,(db)), were and the(d) remotewere the sensingsatelliate remote sensingsatelliate data of cross-calibrated data of cross-calibrated multi-platform multi-platform (CCMP) wind (CCMP) and windMicrowave and Microwave optimally interpolatedoptimally interpolat sea surfaceed sea temperature surface temperature (OI SST). (OI SST).

The initial surface air and sea surface temperatures were ~28.5 and ~29.5 ◦C at stations 1 and 2, respectively (Figure7d); Sarika reduced the former by ~1 ◦C to the minimum value of 28.4 ◦C around UTC 00:00 on 18 October, one day after the typhoon. Haima also cooled the sea surface temperature slightly. The sea surface temperature in Figure7d is the temperature observed by the sensor at the shallowest depth of 22 m. It is interesting that the surface air temperature increased slightly, to ~29 ◦C, during the forced stage of Sarika and then fell to a minimum value of ~26.3 ◦C after one day. The sea surface temperature was slightly higher than the surface air temperature, although the opposite was sometimes true (Figure7d), resulting in a reversal of the ocean surface sensible heat flux. Note that the sea surface temperature from satellite data (OI SST) was lower than the sea surface temperature observed by Station 2 but more consistent with surface air temperature (Figure7d), indicating that OI SST may reflect the air temperature rather than the ocean temperature in the air–sea surface. Another air temperature minimum of ~26.5 ◦C occurred when Haima was closest to Station 2. The surface heat flux (Figure7f) revealed that the shortwave radiation and latent heat flux controlled the air–sea Remote Sens. 2019, 11, 2360 11 of 23 interface heat flux during Sarika and Haima (Figure7f). The ocean gained heat from the shortwave radiation and lost heat to the air through the latent heat flux. Remote Sens. 2019, 11, x FOR PEER REVIEW 11 of 23 3.2.2. Ocean Current 3.1.1. Ocean Current Before the two typhoons, the background upper and bottom ocean currents were north-eastward and south-westwardBefore the two respectivelytyphoons, the at Stationbackground 2 (Figure upper8a–d). and Then bottom near-inertial ocean currents oscillations were occurred north- aftereastward Sarika and and south-westward Haima, with the maximumrespectively current at Station speed reaching2 (Figures ~80 cm8a–8d)./s in theThen mixed near-inertial layer. The phaseoscillations of the occurred near-inertial after current Sarika inand the Haima, vertical with direction the maximum tilted with current time duringspeed reaching the relaxation ~80 cm/s stage in ofthe the mixed two layer. typhoons. The phase That is,of the the near-inertial current phase current deeper in inthe the vertical ocean direction delayed tilted the one with at atime shallower during level,the relaxation with the stage delay of increasing the two typhoons. with time. That This is, was the due current to the phase dispersion deeper of in the the near-inertial ocean delayed waves, the theone processat a shallower of which level, has beenwith previouslythe delay increasing explained with [25,26 time.,59]. This The resultswas due of to the the spectral dispersion analysis of the in Figurenear-inertial8e–h reveals waves, significant the process near-inertial, of which has diurnal, been previously and semidiurnal explained frequency [25,26,59]. signals The of results the current of the fromspectral the analysis ocean surface in Figure to the 8e–8h bottom. reveals There significant was no significant near-inertial, blue diurnal, shift occurred and semidiurnal at Station 2,frequency which is consistentsignals of withthe current the fact thatfrom Station the ocean 2 was surface so far fromto the both bottom. Sarika There (254.49 was km) no and significant Haima (–208.44 blue shift km) thatoccurred the near-inertial at Station 2, current which might is consistent have been with dispersed the fact before that Station it reached 2 was Station so far 2, leaving from both mainly Sarika the inertial(254.49 frequency.km) and Haima It should (–208.44 be noted km) thatthat therethe near-ine was alsortial a weak current super-inertial might have wave been signaldispersed with before twice theit reached inertial Station frequency 2, leaving (2f ). The mainly super-inertial the inertial wave frequency. signal has It been should previously be noted reported that there to be was the also cause a ofweak the super-inertial nonlinear effect wave in the signal current with response twice the [27 inertial,28]. frequency (2f). The super-inertial wave signal has been previously reported to be the cause of the nonlinear effect in the current response [27,28].

Figure 8. Eastward and northward current (a–d) at Station 2, and their spectra between October 13 and Figure 8. Eastward and northward current (a–d) at Station 2, and their spectra between October 13 24 (e–h). The vertical black dashed lines indicate the inertial, diurnal, and semidiurnal frequencies. and 24 (e-h). The vertical black dashed lines indicate the inertial, diurnal, and semidiurnal The vertical violet dashed lines indicate twice the inertial frequency. frequencies. The vertical violet dashed lines indicate twice the inertial frequency. 3.2.3. Ocean Temperature 3.1.1. Ocean Temperature Oceanic temperature can be advected by current, so we can ﬁnd diurnal variation and weak semidiurnalOceanic variation temperature during can observation be advected (Figures by current,9a and so 10 wea), ascan well find as diurnal the near-inertial variation variationsand weak occurredsemidiurnal by thevariation TCs. during observation (Figures 9a and 10a), as well as the near-inertial variations occurred by the TCs. At Station 2 (with the operation of Buoy 2 and Mooring 2, Figures 9–10), there was a “cold– warm–cold” vertical temperature anomaly structure in the upper ocean after the two typhoons. The depth of the mixed layer increased rapidly from ~30 m to ~50 m within 3 hr on October 16, eventually reaching its maximum value of ~54 m several hours before the time Sarika was closest to Station 2. Sarika cooled the upper ocean by ~1 °C from the surface up to a depth of ~40 m. In addition, it warmed the ocean subsurface by ~1 °C between depths of ~40 and 70 m, with a weak warming anomaly further extending to a depth of ~100 m. Sea surface temperature started to decrease when mixed layer depth deepened, and sea surface temperature reached its minimum near the end of upwelling branch. After removing the inertial period signal, a net warming anomaly was apparently caused by downwelling when Sarika was closet to Buoy 2 in the upper ocean (Figure 9e). The upwelling branch was effective when Haima was close to Station 2 (October 20–21), and the mixed layer depth was thus shallow at ~35–60 m, with the 15 °C isotherm lifted from ~250 m to ~150 m. Another downwelling seemed to occur ~1 day after when Haima was closest to Buoy 2, and it further caused an ~2 °C warming

Remote Sens. 2019, 11, x FOR PEER REVIEW 12 of 23 Remote Sens. 2019, 11, x FOR PEER REVIEW 12 of 23 anomaly in the ocean subsurface, with the main warming anomaly reaching a depth of ~90 m, and a anomalyweak in warming the ocean anomaly subsurface, further with extending the main towarming a depth anomaly of ~150 reachingm (Figure a 9a).depth The of upper~90 m, ocean and a heat weakcontent warming increased anomaly sequentially further extending to ~50 m°C to aand dept ~1h00 of m°C ~150 after m (Figure Sarika 9a).and TheHaima. upper Mooring ocean 2heat (Figure content10) increasedshowed that sequentially the warming to ~50 anomaly m°C and caused ~100 m°Cby the after downwelling Sarika and Haima.reached Mooring ~500 m, 2while (Figure Haima 10) showeddownward that pushed the warming it into ~600anomaly m. caused by the downwelling reached ~500 m, while Haima downward pushed it into ~600 m. Remote Sens. 2019, 11, 2360 12 of 23

Figure 9. Temperature (a), temperature anomaly (d) and their net values (b,e) during Sarika and Figure 9. Temperature (a), temperature anomaly (d) and their net values (b,e) during Sarika and Haima FigureHaima 9. Temperature at Buoy 2. (Averagea), temperature temperature anomaly (c) and(d) andtemperature their net anomalyvalues (b,e (f) duringprofiles Sarikabefore andthe two at Buoy 2. Average temperature (c) and temperature anomaly (f) proﬁles before the two typhoons Haimatyphoons at Buoy (black; 2. Average averaged temperature between 14 (c )and and 16 temperature October), after anomaly Sarika (blue;(f) profiles averaged before over the one two inertial (black; averaged between 14 and 16 October), after Sarika (blue; averaged over one inertial period after typhoonsperiod (black; after averaged18 October), between and after 14 and Haima 16 October) (red; aver, afteraged Sarika over (blue;one inertial averaged period over after one 22inertial October). 18 October), and after Haima (red; averaged over one inertial period after 22 October). The black solid periodThe after black 18 October),solid lines and in (aftera,b,d,e Haima) indicate (red; theaver mixedaged over layer one depth, inertial which period is the after depth 22 October). at which the lines in (a,b,d,e) indicate the mixed layer depth, which is the depth at which the temperature is 0.5 ◦C The blacktemperature solid lines is 0.5 in °C (a,b,d,e lower )than indicate the surface the mixed layer layer temperature. depth, which The black is the dashed depth lines at which indicate the the 15 lower than the surface layer temperature. The black dashed lines indicate the 15 ◦C isotherm. (g,h) temperature°C isotherm. is 0.5 °C(g, lowerh) Accumulated than the surface surface layer heat temperature. flux (black Thelines), black heat dashed anomaly lines from indicate 0 to the160 15m (red Accumulated surface heat ﬂux (black lines), heat anomaly from 0 to 160 m (red lines), and their sum °C isotherm.lines), and (g, their h) Accumulated sum (blue lines) surface at Buoy heat 2. flux The (black vertical lines), brown heat dash anomalyed lines from represent 0 to 160 the mtimes (red when (blue lines) at Buoy 2. The vertical brown dashed lines represent the times when Sarika and Haima lines),Sarika and their and sumHaima (blue were lines) closest at Buoy to Station 2. The 2. vertical The te mperaturebrown dash observeded lines representby the sensor the times near thewhen surface were closest to Station 2. The temperature observed by the sensor near the surface (at a depth of 22 m) Sarika(at and a depth Haima of were22 m) closest was used to Station for the 2. heat The content temperature calculations observed for byshallower the sensor depths. near the surface was used for the heat content calculations for shallower depths. (at a depth of 22 m) was used for the heat content calculations for shallower depths.

Figure 10. Mooring 2 parameters corresponding to those in Figure9 9.. TheThe heatheat contentcontent anomalyanomaly andand Figurenet 10. heat Mooring content 2 anomalyparameters in (correspondinggg-h–h)) are are between to 210 those m into Figure500 m in 9. the The observation heat content (red anomaly lines). and net heat content anomaly in (g-h) are between 210 m to 500 m in the observation (red lines). At Station 2 (with the operation of Buoy 2 and Mooring 2, Figures9 and 10), there was a “cold–warm–cold” vertical temperature anomaly structure in the upper ocean after the two typhoons. The depth of the mixed layer increased rapidly from ~30 m to ~50 m within 3 hr on October 16, eventually reaching its maximum value of ~54 m several hours before the time Sarika was closest to Station 2. Sarika cooled the upper ocean by ~1 ◦C from the surface up to a depth of ~40 m. In addition, it Remote Sens. 2019, 11, 2360 13 of 23

warmed the ocean subsurface by ~1 ◦C between depths of ~40 and 70 m, with a weak warming anomaly further extending to a depth of ~100 m. Sea surface temperature started to decrease when mixed layer depth deepened, and sea surface temperature reached its minimum near the end of upwelling branch. After removing the inertial period signal, a net warming anomaly was apparently caused by downwelling when Sarika was closet to Buoy 2 in the upper ocean (Figure9e). The upwelling branch was eﬀective when Haima was close to Station 2 (October 20–21), and the mixed layer depth was thus shallow at ~35–60 m, with the 15 ◦C isotherm lifted from ~250 m to ~150 m. Another downwelling seemed to occur ~1 day after when Haima was closest to Buoy 2, and it further caused an ~2 ◦C warming anomaly in the ocean subsurface, with the main warming anomaly reaching a depth of ~90 m, and a weak warming anomaly further extending to a depth of ~150 m (Figure9a). The upper ocean heat content increased sequentially to ~50 m◦C and ~100 m◦C after Sarika and Haima. Mooring 2 (Figure 10) showed that the warming anomaly caused by the downwelling reached ~500 m, while Haima downward pushed it into ~600 m. Remote Sens. 2019, 11, x FOR PEER REVIEW 13 of 23 3.2.4. Ocean Salinity 3.1.1.Figure Ocean 11 Salinity shows the salinity response during Sarika and Haima at Station 2. As the salinity sensorsFigure may have11 shows some deviationsthe salinity and response inaccuracy, during the Sa analysisrika and of salinityHaima at response Station should 2. As the be careful. salinity Becausesensors themay subsurface have some salinity deviations reached and inaccuracy, a maximum the in analysis Station 2,of upwellingsalinity response (downwelling) should be caused careful. salinityBecause increase the subsurface (decrease) salinity upper reached (lower) thana maximum the subsurface in Station maximum. 2, upwelling A weak (downwelling) updrift of salinity caused proﬁlesalinity during increase 16 October (decrease) at Buoy upper 2 (Figure(lower) 11thana–c) the caused subsurface a weak maximum. increase of A ~0.07 weak psu updrift in the of salinity salinity betweenprofile 40during m and 16 80 October m after at Sarika. Buoy However,2 (Figures Sarika’s 11a–11c) rainfall caused reversed a weak the increase surface of salinity ~0.07 psu anomaly in the tosalinity ~–0.03 psu.between Haima’s 40 m rainfall and 80 further m after refreshed Sarika. However, the mixed Sarika’s layer, reducing rainfall thereversed surface the salinity surface anomaly salinity toanomaly ~–0.1 psu; to it~–0. also03 changedpsu. Haima the’s positive rainfall salinityfurther anomalyrefreshed between the mixed depths layer, of reducing 40 and 80 the m intosurface a negative anomaly.

FigureFigure 11. 11.Salinity, Salinity, salinity salinity anomaly,anomaly, andand netnet salinity an anomalyomaly during during Sarika Sarika and and Haima Haima at at Buoy Buoy 2 ( 2a– (ac–)c) and and Mooring Mooring 2 2 ( (dd––ii).). Net Net salinity salinity anomaly anomaly is the oneone inertialinertial periodperiod runningrunning mean mean of of the the salinity salinity anomaly.anomaly. The The salinity salinity anomaly anomaly was was calculated calculated as the as salinity the salinity minus minus the average the average salinity salinity over the over period the UTCperiod 00:00 UTC on 1400:00 October on 14 to October UTC 00:00 to UTC on 16 00:00 October. on 16 Dashed October. lines Dashed represent lines the represent time that the Sarika time and that HaimaSarika were and closestHaima towere the closest stations. to the stations.

3.2.5.3.1.1. Mechanisms Mechanisms of of Upper upper Temperature temperature Responseresponse at Station 2 InIn order order to to further further analyze analyze the the mechanisms mechanisms of of upper upper ocean ocean temperature temperature response response to to the the two two TCs, TCs, wewe used used a a three three dimensional dimensional model model (3DPWP) (3DPWP) to to reproduce reproduce the the ocean ocean response response during during Sarika Sarika and and Haima separately (Figure 12). Consistent with the observation in Figure 8, Sarika and Haima both caused sea surface cooling and subsurface warming anomaly at Station 2 (Figures 12c–d and 12k–l). The surface cooling was mainly caused by mixing and partly by the horizontal advection during the forced stage (Figures 12e–12f and 12m–12n). Note that the maximum sea surface cooling was nearly one day after Sarika (Figures 12c and 7c), when the combination cooling effects of mixing and horizontal advection were strongest, nearly the half period of the first near-inertial oscillation. The sea surface cooling during Haima (Figures 12k and 7c) seems influenced by the oscillation of surface cooling caused by Sarika (Figure 12c) because the surface cooling caused by Haima (Figure 12k) was weak. The vertical advection induced periodic warming (Figures 12g and 11o) and net warming (Figures 12h and 12p) in subsurface and deeper ocean. The subsurface warming during Sarika was caused by the combination effect of mixing and downwelling, while the subsurface warming during Haima was mainly caused by downwelling. In a word, Sarika and Haima both induce net surface cooling and net subsurface/deeper ocean warming. Surface cooling was due to the effects of mixing and horizontal advection, while subsurface warming was induced by the combination effects of mixing and downwelling (Sarika) or mainly downwelling (Haima). Downwelling also further warmed the deeper ocean. Remote Sens. 2019, 11, 2360 14 of 23

Haima separately (Figure 12). Consistent with the observation in Figure8, Sarika and Haima both caused sea surface cooling and subsurface warming anomaly at Station 2 (Figure 12c,d,k,l). The surface cooling was mainly caused by mixing and partly by the horizontal advection during the forced stage (Figure 12e,f,m,n). Note that the maximum sea surface cooling was nearly one day after Sarika (Figures 7c and 12c), when the combination cooling effects of mixing and horizontal advection were strongest, nearly the half period of the first near-inertial oscillation. The sea surface cooling during Haima (Figures7c and 12k) seems influenced by the oscillation of surface cooling caused by Sarika (Figure 12c) because the surface cooling caused by Haima (Figure 12k) was weak. The vertical advection induced periodic warming (Figures 11o and 12g) and net warming (Figure 12h,p) in subsurface and deeper ocean.Remote Sens. The 2019 subsurface, 11, x FOR warming PEER REVIEW during Sarika was caused by the combination effect of mixing 14and of 23 downwelling, while the subsurface warming during Haima was mainly caused by downwelling.

Δ FigureFigure 12. 12.Change Change of temperature of temperature (T), net (T), temperature net temperature (Tp), temperature (Tp), temperature anomaly (∆ T),anomaly net temperature ( T), net anomalytemperature (∆Tp), anomaly and temperature (ΔTp), and change temperature caused by change mixing, caused horizontal by mixing, advection, horizontal vertical advectionadvection, andvertical net vertical advection advection and net simulated vertical byadvection 3DPWP simulated model during by 3DPWP Sarika (amodel–h) and during Haima Sarika (i–p). (a-h) and Haima (i-p). In a word, Sarika and Haima both induce net surface cooling and net subsurface/deeper ocean warming.4. Discussion Surface cooling was due to the effects of mixing and horizontal advection, while subsurface warming was induced by the combination effects of mixing and downwelling (Sarika) or mainly Here, we simplify the response of the upper ocean temperature at Station 2 to a TC. Because the downwelling (Haima). Downwelling also further warmed the deeper ocean. surface heat flux made only a little contribution to the change in the upper ocean heat content (Figures 4.9b Discussion and 9d), the temperature response at Station 2 was therefore mainly controlled by mixing and advection (vertical and horizontal). Here,Figure we 13 simplify is a simplified the response sketch of of the the upper temperatur oceane temperature response at atStation Station 2. 2In to the a TC. case Because of only themixing surface (Figure heat 13a), flux madethe surface only awarming little contribution anomaly and to the subsurface change incooling the upper anomaly ocean are heat comparable, content (Figurewith the9b,d), change the temperaturein the upper ocean response heat at content Station be 2ing was zero. therefore Because mainly Sarika controlled also caused by downwelling, mixing and advectionthe temperature (vertical profile and horizontal). is pushed downward. In addition, when the mixed layer depth was increased throughFigure downwelling, 13 is a simplified the entrainment sketch of the rate temperature at the bottom response of the at mixed Station layer 2. In might the case have of onlybeen mixing weaker (Figurethan the 13 a),case the of surface only mixing, warming resulting anomaly in andweaker subsurface sea surface cooling cooling. anomaly Horizontal are comparable, advection with also thecaused change some in the cooling upper in ocean the mixed heat content layer. beingThe subsurface zero. Because warming Sarika anomaly also caused caused downwelling, by Sarika thewas temperaturegreater than profile the surface is pushed cooling downward. anomaly, Inresulting addition, in whena positive the mixedupper layerocean depth heat (Figures was increased 9d and through13b). Haima downwelling, further deepened the entrainment the mixed rate layer, at the cool bottomed surface, of the and mixed warmed layer might subsurface/deeper have been weaker ocean thanthrough the case the ofsame only (but mixing, weaker) resulting processes, in weaker with seathe surfacecombination cooling. of mixing Horizontal and advectionadvection also(Figure caused 12c) somefurther cooling increasing in the mixedupper ocean layer. Theheat subsurfacecontent at Station warming 2 (Figure anomaly 9d caused and 13c). by Sarika was greater than the surfaceThe upper cooling ocean anomaly, temperature resulting response in a positive to the two upper sequential ocean heat TCs (Figures at Statio9nd 2 and was 13 ab). special Haima case because the temperature profile variation was caused by sequential mixing and downwelling. As observed in previous studies [15,22,30], the oceanic response to a TC at an observation station depends on the position of the station relative to the TC track, as well as the TC characteristics such as intensity, size, translation speed, and ocean stratification. For example, there is net upwelling near the TC track and net downwelling around the net upwelling zone [22], and the mixed layer depth varies with the TC translation speed [30]. So the temperature response to sequential TCs at a station can be complicated and different from Figure 13. In some regions with high ocean precipitation, the uniform-density mixed layer is shallower than the isothermal layer, and this generates a barrier layer that reduces the TC-induced vertical mixing and sea surface cooling [60,61].

Remote Sens. 2019, 11, 2360 15 of 23 further deepened the mixed layer, cooled surface, and warmed subsurface/deeper ocean through the same (but weaker) processes, with the combination of mixing and advection (Figure 12c) further increasingRemote Sens. upper2019, 11, ocean x FOR PEER heat contentREVIEW at Station 2 (Figures9d and 13c). 15 of 23

Figure 13. Sketch of the vertical temperature profiles at Station 2 before (dashed lines) and after (solid lines)Figure (a )13. only Sketch mixing, of the (b) vertical Sarika, andtemperature (c) Haima. profiles The dotted at Station lines 2 in before (b) and (dashed (c) indicate lines) the and temperature after (solid profileslines) ( causeda) only bymixing, only mixing, (b) Sarika, while and the dot-dashed(c) Haima. lineThe indotted (c) indicates lines in that (b caused) and ( byc) Sarika.indicate The the redtemperature shading indicates profiles thecaused warming by only anomaly, mixing, and while the the blue dot-dashed shading the line cooling in (c) indicates anomaly. that caused by Sarika. The red shading indicates the warming anomaly, and the blue shading the cooling anomaly. The upper ocean temperature response to the two sequential TCs at Station 2 was a special case because5. Conclusion the temperature profile variation was caused by sequential mixing and downwelling. As observed in previous studies [15,22,30], the oceanic response to a TC at an observation station depends During their passage through the buoy and mooring array at our observation stations, the on the position of the station relative to the TC track, as well as the TC characteristics such as intensity, maximum wind speeds for Sarika and Haima were 38 and 42 m/s, respectively, with the winds biased size, translation speed, and ocean stratification. For example, there is net upwelling near the TC track to the right side of the TC tracks and the cloud and rainfall to the left. Sarika and Haima cooled the and net downwelling around the net upwelling zone [22], and the mixed layer depth varies with the TC sea surface as much as ~4 and ~2 °C, respectively, and increased salinity as much as ~1.2 and ~0.6 psu, translation speed [30]. So the temperature response to sequential TCs at a station can be complicated respectively. The maximum sea surface cooling occurred one day after the passage of the respective and different from Figure 13. In some regions with high ocean precipitation, the uniform-density TCs, with the heavy rainfall of Haima possibly refreshing the left side of its track. mixed layer is shallower than the isothermal layer, and this generates a barrier layer that reduces the Both Sarika and Haima increased the near-inertial oscillation from the upper ocean to the bottom TC-induced vertical mixing and sea surface cooling [60,61]. at Station 2. The maximum current speed in the mixed layer was ~80 cm/s. The phase delay of the 5.increase Conclusions in the near-inertial current in the deeper ocean was greater than that in the shallower ocean, resulting in an increase in the inclination of the current phase in the relaxation stage of the two typhoons.During The their near-inertial passage through currents the at buoyStations and 2 mooringcaused no array significant at our observationblue shifts in stations, the inertial the maximumfrequency, wind indicating speeds that for Sarikathe current and Haima at Station were 382 propagated and 42 m/s, away respectively, from the with source the winds region. biased The tocurrent the right spectrum side of theshows TC tracksweak signal and the at cloudtwice andthe inertial rainfall tofrequency the left. Sarika(2f). and Haima cooled the sea surfaceAt asStation much 2, as the ~4 two and typhoons ~2 ◦C, respectively, caused “cold–wa and increasedrm–cold” salinity vertical as temp mucherature as ~1.2 anomalies. and ~0.6 psu, The respectively.surface heat Theflux maximumdid not significantly sea surface impact cooling the occurred heat content one day variation after the of passage the upper of the ocean respective during TCs,either with of the the two heavy typhoons, rainfall so of the Haima upper possibly ocean ther refreshingmal response the left was side mainly of its track. due to the internal ocean processesBoth Sarika (mixing and and Haima advection). increased Sarika the near-inertialdeepened the oscillation mixed layer, from cooled the upper the sea ocean surface to the by bottom ~-1 °C, atand Station warmed 2. Thethe subsurface maximum by current ~1 °C; speedit also caused in the mixeda net downwelling layer was ~80 that cm increased/s. The phasethe heat delay content of theof the increase upper in ocean. the near-inertial Haima further current deepened in the the deeper mixed ocean layer was and greater pushed than the that subsurface in the shallower warming ocean,anomaly resulting caused in by an Sarika increase deeper in the into inclination the ocean of and the am currentplified phase it to ~1.8 in the °C. relaxation In addition, stage it further of the twoincreased typhoons. the upper The near-inertial ocean heat content currents at at Station Stations 2. 3DPWP 2 caused model no significant simulation blue shows shifts that in the the inertialsurface frequency,cooling was indicating caused by that the the effects current of mixing at Station and 2 propagatedhorizontal advection, away from while the source subsurface region. warming The current was spectruminduced by shows the weakcombination signal at effects twice theof mixing inertial and frequency downwelling (2f ). (Sarika) or mainly downwelling (Haima).At Station Downwelling 2, the two also typhoons further causedwarmed “cold–warm–cold” the deeper ocean. The vertical maximum temperature sea surface anomalies. cooling Thewas surfacenearly one heat day flux after did Sarika, not significantly when the combination impact the heat cooling content effects variation of mixing of and the upperhorizontal ocean advection during eitherwere ofstrongest, the two typhoons,nearly the so half the period upper oceanof the thermalfirst near-inertial response was oscillation. mainly due The to sea the surface internal cooling ocean processesduring Haima (mixing seems and influenced advection). by Sarika the oscillation deepened theof surface mixed layer,cooling cooled caused the by sea Sarika. surface The by ~-1salinity◦C, andresponse warmed to the subsurfacetwo typhoons by ~1was◦C; similar it also to caused temperature a net downwelling response, except that increased that the therainfalls heat content during Sarika and Haima successively altered the surface salinity anomaly to ~–0.03 and ~–0.1 psu and also changed the positive subsurface salinity anomaly to negative. To summarize, Sarika and Haima sequentially induced a near-inertial current and modulated the ocean temperature and salinity structures. Especially, there was some downward push of warm water sequentially into deeper ocean by Sarika and Haima, which may have modulated the ocean interior and deeper ocean. The final oceanic response depends on the relative positions of the

Remote Sens. 2019, 11, 2360 16 of 23 of the upper ocean. Haima further deepened the mixed layer and pushed the subsurface warming anomaly caused by Sarika deeper into the ocean and amplified it to ~1.8 ◦C. In addition, it further increased the upper ocean heat content at Station 2. 3DPWP model simulation shows that the surface cooling was caused by the effects of mixing and horizontal advection, while subsurface warming was induced by the combination effects of mixing and downwelling (Sarika) or mainly downwelling (Haima). Downwelling also further warmed the deeper ocean. The maximum sea surface cooling was nearly one day after Sarika, when the combination cooling effects of mixing and horizontal advection were strongest, nearly the half period of the first near-inertial oscillation. The sea surface cooling during Haima seems influenced by the oscillation of surface cooling caused by Sarika. The salinity response to the two typhoons was similar to temperature response, except that the rainfalls during Sarika and Haima successively altered the surface salinity anomaly to ~–0.03 and ~–0.1 psu and also changed the positive subsurface salinity anomaly to negative. To summarize, Sarika and Haima sequentially induced a near-inertial current and modulated the ocean temperature and salinity structures. Especially, there was some downward push of warm water sequentially into deeper ocean by Sarika and Haima, which may have modulated the ocean interior and deeper ocean. The final oceanic response depends on the relative positions of the successive TCs and the physical processes that they trigger at different locations, for example, the relative importance of mixing, horizontal advection, and vertical advection (upwelling and downwelling) successively caused by the two TCs determines the variations of temperature and salinity profiles. The present work is a case study. A blended data satellite model technique [62] can be used to further study the cases of sequential tropical cyclones. In a word, further study is needed to consider other cases and conduct more in-depth investigations.

Author Contributions: H.Z. formed the ideal and wrote the initial draft; X.L., R.W., X.X., C.Y., D.T. and W.Z. revised the manuscript and provide beneficial suggestions; F.L. visualized Figure2; L.Y., X.S. (Xiaodong Shang), Y.Q., Y.W., X.S. (Xunshu Song) deployed and recovered the moored observation array, and provide details of the moored data. Funding: This research was funded by the National Program on Global Change and Air-Sea Interaction (GASI-IPOVAI-04), the China Ocean Mineral Resources Research and Development Association Program (grant number DY135-E2-3-01), the Scientific Research Fund of the Second Institute of Oceanography, MNR (grant number JG1813), the National Natural Science Foundation of China (grant numbers 41806021, 41730535, 41705048, 41621064, 41630970, and 41876022), the Instrument Developing Project of the CAS (grant number YZ201432), and the National Key R&D Program of China (grant number 2018YFC1506403). Acknowledgments: We acknowledge the Joint Typhoon Warning Center (JTWC, http://www.usno.navy.mil/JTWC), the Japan Meteorological Agency (JMA, http://www.jma.go.jp/jma/jma-eng/jma-center/rsmc-hp-pub-eg/besttrack. html), and the China Meteorological Administration (CMA, http://tcdata.typhoon.gov.cn) for providing the tropical cyclone tracks, Meteorological Satellite Center of Japan Meteorological Agency and Kochi University (http://weather.is.kochi-u.ac.jp/sat/GAME/2016/Oct/IR1) for providing the cloud-top brightness temperature data of Himawari-8 (https://www.data.jma.go.jp/mscweb/en/index.html), Remote Sensing Systems (http://www.remss. com) for providing the CCMP Version-2.0 vector wind analyses, microwave OI SST data and SMAP salinity data, the National Oceanic and Atmospheric Administration (https://www.cpc.ncep.noaa.gov/products/janowiak/ cmorph_description.html) for providing CMORPH precipitation data, the Copernicus Marine and Environment Monitoring Service (CMEMS, http://www.marine.copernicus.eu) for providing sea surface height anomalies and geostrophic velocity anomalies. Conflicts of Interest: The authors declare no conflict of interest.

Appendix A. Observation at Mooring 1

Mooring 1 was deployed at 112◦10.699’ E and 17◦59.024’ N at 16:00 Beijing Time (08:00 UTC) on 6 August and recovered at 19:00 Beijing Time (11:00 UTC) on 27 October. See Figure A1 and Table A1 for the instruments installed at mooring 1 and the physical elements measured. Buoy 1 was deployed at 112◦10.699’E and 17◦59.024’N at 10:00 Beijing Time (02:00 UTC) on 6 August, and Buoy 3 was deployed at 114◦53.016’E and 16◦29.000’N at 08:30 Beijing Time (00:30 UTC) on 30 July. However, Buoy 1 was damaged after 5 August, and Buoy 3 was damaged after 29 August and 23 September sequentially, so there were no data from the two buoys during Sarika and Haima. Remote Sens. 2019, 11, 2360 17 of 23

Before the two typhoons, the background upper and bottom ocean currents were south-westward and north-eastward respectively at Station 1 (Figure A2a,b). Near-inertial oscillations occurred after Sarika and Haima at both Stations 1, with the maximum current speed reaching ~80 cm/s in the mixed layer. Sarika dramatically intensified the upper ocean current because it was very close to the TC track (only 15.77 km away), and Haima might also have intensified the near-inertial current and caused a slight distortion of the current phase. The results of the spectral analysis in Figure A2a,b reveals significant near-inertial, diurnal, and semidiurnal frequency signals of the current from the ocean surface to the bottom. There was ~10% blue shift of the near-inertial frequency at Station 1 (Figure A2e–h). This is consistent with Station 1 being close to the TC track (especially that of Sarika) where the near-inertial current was generated. The blue shift of the near-inertial frequency also decreased with increasing depth in the upper ocean at Station 1, as another consequence of the wave dispersion. It should be noted that there was also a weak super-inertial wave signal with a frequency twice the inertial frequency (2f ). At Station 1 (with the operation of Mooring 1, Figure A3), Sarika caused net upwelling and downwelling, which were respectively accompanied by uplifting and depression of the temperature profiles, respectively. Sarika uplifted the 10 ◦C isotherm as much as ~50 m in one day, then the 10 ◦C isotherm seems downward pushed back by Haima. The interior ocean exhibited ~–0.5 ◦C temperature anomaly after Sarika, with Haima, subsequently causing an alteration to a warming anomaly (~0.1 ◦C). As a result, the average temperature anomaly and heat content were also negative (~–250 m◦C in maximum) after Sarika and positive after Haima (~200 m◦C in maximum). It indicates that although Station 1 was far away (~535.57 km) from Haima, its downwelling effect cannot be ignored. However, the temperature anomaly may also have disturbed by the background current and the observation uncertainty. Figure A3a–d indicate that the uplifting effect of Sarika could have reached the bottom of the ocean. Figure A4 shows the salinity response during Sarika and Haima at Station 2. Because the salinity sensors may have some deviations and inaccuracy, the analysis of salinity response should be careful. Because of the subsurface salinity maximum in Station 2, upwelling (downwelling) caused salinity increase (decrease) upper (lower) than the subsurface maximum. The salinity anomaly between 280 m and 400 m was ~–0.02 psu after Sarika turned to ~0.01 psu after Haima at Mooring 1 (Figure A4a–c). Because there was a weak updrift of salinity profile during 16 October at Buoy 2 (Figure A4d–f), there was a weak increase of ~0.07 psu in the salinity between 40 m and 80 m after Sarika. However, Sarika’s rainfall reversed the surface salinity anomaly to ~–0.03 psu. Haima’s rainfall further refreshed the mixed layer, reducing the surface salinity anomaly to ~–0.1 psu; it also changed the positive salinity anomaly between depths of 40 and 80 m into a negative anomaly. Remote Sens. 2019, 11, x FOR PEER REVIEW 18 of 23 Remote Sens. 2019, 11, 2360 18 of 23

Figure A1. Design of buoy and mooring at Station 1.

Table A1. ObservationFigure 1. instrumentsDesign of buoy and and measured mooring elements at Station at Mooring1. 1 *.

Observation Instruments Designed Depth (m) Resolution (s) Elements SBE-37 T, S, P 315/330/345/360/375/400/450/500/L160/L140/L120/L80/L40 120 Table 1. Observation instruments and measured elements at Mooring 1*. SBE-39 T, P L200/L180/L100/L60 120 Seaguard ObservationU, V 450/600/700/800/L100 600Resolutio Instruments location: 500 m, uplooking;Designed ﬁrst depth bin: 24.42 (m) m; last bin: RDI 75K-ADCP U, V 600 elements 600.42 m; bin size: 16 m n (s) location:315/330/345/360/375/400/450/500/L160/L140/L120/L8 L80 m, downlooking; ﬁrst bin: 6.17 m; last RDISBE-37 75K-ADCP T, S,U, P V 600 120 bin: 110.17 m; bin0/L40 size: 4 m *SBE-39 L: above ocean bottom;T, for P example, L140 means 140 mL200/L180/L100/L60 above the ocean bottom. T, S, P, U, and V respectively120 Seaguarddenote temperature, salinity,U, V pressure, eastward current speed,450/600/700/800/L100 and northward current speed, respectively. 600 RDI 75K- location: 500 m, uplooking; first bin: 24.42 m; last U, V 600 ADCP bin: 600.42 m; bin size: 16 m RDI 75K- location: L80 m, downlooking; first bin: 6.17 m; last U, V 600 ADCP bin: 110.17 m; bin size: 4 m * L: above ocean bottom; for example, L140 means 140 m above the ocean bottom. T, S, P, U, and V respectively denote temperature, salinity, pressure, eastward current speed, and northward current speed, respectively.

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Figure 2. Eastward and northward current (a–d) at Station 1. Spectra of the eastward and northward Figure A2. Eastward and northward current (a–d) at Station 1. Spectra of the eastward and northward currentsFigure 2. at Eastward (e–h) Station and northward1 between currentOctober ( a13–d and) at Station26. The 1. black Spectra dashed of the lines eastward indicate and the northward inertial, currents at (e–h) Station 1 between October 13 and 26. The black dashed lines indicate the inertial, diurnal,currents and at ( semidiurnale–h) Station frequencies.1 between October The violet 13 anddashed 26. linesThe blackindicate dashed twice lines the inertial indicate frequency. the inertial, diurnal, and semidiurnal frequencies. The violet dashed lines indicate twice the inertial frequency. diurnal, and semidiurnal frequencies. The violet dashed lines indicate twice the inertial frequency.

Figure A3. Variations in the (a) temperature and (b) net temperature at Mooring 1 during Sarika and Figure 3. Variations in the (a) temperature and (b) net temperature at Mooring 1 during Sarika and Haima. The black dashed lines are the 10 C isotherms, and the brown lines indicate the times when Haima.Figure 3.The Variations black dashed in the lines (a) temperatureare the 10 °C◦ and isothe (b)rms, net andtemperature the brown at linesMooring indicate 1 during the times Sarika when and Sarika and Haima were closest to Mooring 1. (c) Average temperature proﬁles before the two typhoons SarikaHaima. and The Haima black dashed were closestlines are to the Mooring 10 °C isothe 1. (c)rms, Average and the temperature brown lines profiles indicate before the times the when two (black; averaged between 14 and 16 October), after Sarika (blue; averaged over one inertial period typhoonsSarika and (black; Haima averaged were closestbetween to 14 Mooring and 16 October) 1. (c) Average, after Sarika temperature (blue; averaged profiles over before one theinertial two after 18 October), and after Haima (red; averaged over one inertial period after 22 October). (d–f) periodtyphoons after (black; 18 October), averaged and between after Haima 14 and (red; 16 October) averaged, after over Sarika one inertial (blue; averaged period after over 22 one October). inertial Temperature anomaly parameters corresponding to the temperature parameters in (a–c). (g) Heat (periodd–f) Temperature after 18 October), anomaly and parameters after Haima correspond (red; averingaged to overthe temperatureone inertial periodparameters after in22 (October).a–c). (g) content anomaly and (h) net heat content anomaly observed between 300 and 410 m (red lines). The Heat(d–f) content Temperature anomaly anomaly and (h )parameters net heat content correspond anomalying observed to the temperature between 300 parameters and 410 m in(red (a–c lines).). (g) net temperature and net heat content are respectively the moving averages of the temperature and heat TheHeat net content temperature anomaly and and net (h )heat net heatcontent content are respec anomalytively observed the moving between averages 300 and of 410the mtemperature (red lines). content over one inertial period. andThe heatnet temperaturecontent over andone inertialnet heat period. content are respectively the moving averages of the temperature and heat content over one inertial period.

Remote Sens. 2019, 11, x FOR PEER REVIEW 20 of 23

Remote Sens. 2019, 11, 2360 20 of 23 Remote Sens. 2019, 11, x FOR PEER REVIEW 20 of 23

Figure 4. Variations in the salinity and net salinity in the inner (a–d) and bottom (e–h) ocean at FigureMooring A4. 1 duringVariations Sarika in theand salinityHaima. and net salinity in the inner (a–d) and bottom (e–h) ocean at Figure 4. Variations in the salinity and net salinity in the inner (a–d) and bottom (e–h) ocean at Mooring 1 during Sarika and Haima. AppendixMooring B: 1Bottom during SarikaTemperature and Haima. Appendix B. Bottom Temperature AppendixFigure B: B1 Bottom shows Temperaturethe bottom temperature observed at Mooring 1 and Mooring 2. There is diurnal and Figuresemidiurnal A5 shows temperature the bottom variation. temperature Figures observed B1a–B1d at Mooring indicate 1 that and the Mooring uplifting 2. There effect is of diurnal Sarika Figure B1 shows the bottom temperature observed at Mooring 1 and Mooring 2. There is diurnal andcould semidiurnal have reached temperature the bottom variation. of the ocean. Figure A5Thera–de is indicate a bottom that temperature the uplifting signal eﬀect with of Sarika the period could and semidiurnal temperature variation. Figures B1a–B1d indicate that the uplifting effect of Sarika havenearly reached three days the bottom at Mooring of the 2 ocean.(Figures There B1e-B1h). is a bottom temperature signal with the period nearly threecould days have at reached Mooring the 2 (Figurebottom A5 ofe–h). the ocean. There is a bottom temperature signal with the period nearly three days at Mooring 2 (Figures B1e-B1h).

FigureFigure A5. 1. Temperature,Temperature, net net temperature, temperature, and their anomalyanomaly during SarikaSarika andand HaimaHaima atat thethebottom bottom ofof MooringMooring 11 ((aa––dd)) andand MooringMooring 2 (e–h). Net Net temperature temperature is is the the one one in inertialertial period period running running mean mean of ofFiguretemperature temperature 1. Temperature, response. response. netThe The temperature, temperature temperature and anomaly anomaly their anom was was alycalculated calculated during Sarikaas as the and temperaturetemperature Haima at minustheminus bottom thethe averageofaverage Mooringtemperature temperature 1 (a–d) and overover Mooring thethe period period 2 (e–UTC UTCh). Net 00:00 00:00 temperature on on 13 13 October October is the to to one UTC UTC inertial 00:00 00:00 period on on 15 15 October. runningOctober. Dashed meanDashed of linestemperaturelines represent represent response. the the time time that thatThe Sarika Sarikatemperature and and Haima Haima anomaly were were closest wasclosest calculated to to the the stations. stations. as the temperature minus the average temperature over the period UTC 00:00 on 13 October to UTC 00:00 on 15 October. Dashed lines represent the time that Sarika and Haima were closest to the stations.

Remote Sens. 2019, 11, 2360 21 of 23

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