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Deep-Sea Research Part I

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Contrasting the upper ocean response to two intense cyclones in the Bay ofBengal

K.N. Navaneeth, M.V. Martin∗, K. Jossia Joseph, R. VenkatesanOcean Observation Systems, National Institute of Ocean Technology (NIOT), Chennai, India

A R T I C L E I N F O

Keywords:PhailinHudhudRestratificationSubmesoscale featuresThermal frontsHaline frontsPrice–Weller–Pinkel modelTranslation speed

A B S T R A C T

The contrasting upper ocean responses of the Bay of Bengal to two intense cyclones, Phailin and Hudhud, whichtraversed similar paths and occurred at nearly the identical time of year, were analysed using observations frommoored buoys, satellite observations, and modelling. Our analyses revealed that the upper ocean was highlystratified prior to Phailin compared to the case for Hudhud. The stratification in the near surface prior to theonset of Phailin (Hudhud) was predominantly driven by vertical gradients in salinity (temperature). The upperocean response to the passage of Phailin (Hudhud) was characterised by notable changes in sea surface salinity(sea surface temperature). In addition, enhancement of chlorophyll-a was observed over an extensive area fol-lowing the passage of Hudhud but was confined to a mesoscale eddy after Phailin. The presence of strong near-surface haline stratification sustained temperature inversion and resulted in weak sea surface temperaturecooling in the wake of Phailin. The mixing centred along the trajectory of a cyclone in a haline (thermally)-stratified ocean leads to fronts having strong horizontal haline (thermal) gradients in the wake. Cross-frontageostrophic submesoscale circulation features resulted in rapid fluctuations of salinity in the wake of Phailinand temperature in the wake of Hudhud. The cross-front ageostrophic circulation features and post-storm windsplayed a critical role in controlling mixed layer restratification after the cyclones.

1. Introduction

The Bay of Bengal (BoB), a tropical semi-enclosed basin located inthe north-eastern part of the Indian Ocean, is one of the potential re-gions for tropical cyclone (TC) formation. In the BoB, TCs form morefrequently during the pre-monsoon and post-monsoon seasons. The TCsformed during the post-monsoon season are most intense. In the BoB,strong near-surface haline stratification restricts cyclone-induced ver-tical mixing (Girishkumar et al., 2013). Because the near-surface halinestratification exhibits a pronounced north–south gradient, the upperocean response to TCs is less pronounced in the northern BoB than thesouthern BoB (Vinayachandran, 2013).

Several studies have documented the upper ocean response of cy-clones using satellite data (Subrahmanyam et al., 2002; Chen et al.,2013), Argo profiles (Tummala et al., 2009; Vissa et al., 2012), andmodelling studies (Price, 1981; Huang et al., 2009; Chen et al., 2010).Remote sensing offers spatial and temporal observations of synopticfeatures. However, most of the remote-sensing systems are limited to afew millimetres at the ocean surface and have low temporal resolution.Additionally, cloud coverage obscures infrared and ocean colour sen-sors during cyclones. The through-cloud capabilities of the microwave

radiometers of the Tropical Rainfall Measuring Mission (TRMM) Mi-crowave Imager (TMI) provide valuable information of sea surfacetemperature (SST) during cyclones. However, compared to infraredSST, microwave retrievals have low spatial resolution (1–4 km for in-frared compared to 25 km for microwave). The in situ data gathered bythe Argo floats have an arbitrary spatio-temporal distribution and fail tocapture the rapid temporal variability in the upper ocean during cy-clones. In addition, Argo floats cannot provide measurements of surfacemeteorological parameters. Modelling, on the other hand, provides analternative for investigating the various processes controlling the upperocean response to cyclones. Neetu et al. (2012), using numericalmodels, reported that the thicker barrier layers in the post-monsoonseason are responsible for the limited oceanic response. Because theBoB is a salinity-stratified basin, a better representation of river runoffand TCs-related precipitation is needed for an improved representationof the mixed layer in models. In addition, high-resolution models (re-solution < 1 km) are needed to resolve the submesoscale processes inthe restratification of the mixed layer (Trotta et al., 2017). Further-more, for a realistic simulation of the upper ocean response to a TCforcing, good knowledge of the initial oceanic state, forcing fields, andparameterisation schemes for mixing during extreme events such as TCs

https://doi.org/10.1016/j.dsr.2019.03.010Received 26 March 2018; Received in revised form 28 March 2019; Accepted 29 March 2019

∗ Corresponding author. Ocean Observation Systems, NIOT, Chennai, India.E-mail address: vmartinmathew@gmail.com (M.V. Martin).

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Please cite this article as: K.N. Navaneeth, et al., Deep-Sea Research Part I, https://doi.org/10.1016/j.dsr.2019.03.010

is required (Jacob and Shay, 2003; Zedler et al., 2009). Numericalmodelling studies in the BoB also advocate the need for in situ ob-servation-based analyses to decipher the upper ocean response to TCs(Neetu et al., 2012).

The moored buoys provide simultaneous time series measurementsof both surface meteorological and subsurface oceanographic para-meters at selected locations. The high-frequency in situ observations intandem with other in situ and synoptic remote-sensing observationscould be helpful for deciphering the temporal evolution of the upperocean structure during cyclones. Maneesha et al. (2012), using in situobservations from Argo and moored buoys together with satellite ob-servations, studied the upper ocean variability of the BoB to pre-mon-soon cyclones Nargis (category 4) and Laila (category 1). In this study,we analysed contrasting upper ocean responses of two intense tropicalcyclones that traversed nearly identical paths in the BoB at around thesame period of the year. Post-monsoon cyclones Phailin (category 5)and Hudhud (category 4), which developed during 9–12 October 2013and 8–12 October 2014, respectively, resulted in distinct oceanic re-sponses in the northern BoB. The study utilised multiple moored buoyobservations in the vicinity of the cyclone tracks, remote-sensing ob-servations, and one-dimensional modelling to identify the cause of thedistinct oceanic response during both cyclones. The paper is organisedas follows. Section 2 describes the data used for the study. Section 3discusses the contrasting upper ocean responses of Phailin and Hudhudand the physical mechanisms controlling the upper ocean responses. Asummary and conclusions follow in Section 4.

2. Data and methods

The temporal evolution of meteorological and oceanographicparameters during the TC events was studied primarily using in situobservations from moored buoys BD09 [17.85° N, 89.67° E] and BD10[16.5° N, 88.0° E] on the right side of the TC tracks and BD11 [13.5° N,83.99° E] and BD13 [13.99° N, 86.99° E] on the left side (Fig. 1). Thebuoys, deployed by the National Institute of Ocean Technology (NIOT),measure meteorological parameters and subsurface parameters such astemperature, conductivity, and currents (Venkatesan et al., 2013).Furthermore, data obtained from various remote-sensing platformswere used to analyse the synoptic patterns of the meteorological andoceanographic parameters. The high-resolution (1 km) foundation SSTfrom the Group for High Resolution Sea Surface Temperature (GHRSST)level 4 gridded products (Donlon et al., 2007) was used. We also used1.1-km resolution NOAA Advanced Very High Resolution Radiometer(AVHRR) level-2 SST (Bernstein, 1982) and multi-sensor chl-a datadeveloped as a part of the European Space Agency's Climate ChangeInitiative (OC-CCI) mission (Hollmann et al., 2013). Compared to chl-adatasets obtained from single-satellite sensors, the advantages of themulti-sensor OC-CCI version-3 chl-a data are improved spatial coverageand pixel-by-pixel error characterisation. The 5-day average OceanSurface Current Analysis-Real time (OSCAR) data with a high hor-izontal resolution of (⅓° ×⅓°) were used to study the cold-core eddiesnear the tracks of the cyclones (Bonjean and Lagerloef, 2002). Daily seasurface salinity (SSS) data from Aquarius (Lee et al., 2012) and TRMM3B42 V7 rainfall data (Huffman et al., 2007) were used for the presentstudy. Advanced Scatterometer (ASCAT) winds (Bentamy and Fillon,2012) were also used to analyse spatial wind fields of the TCs. TheEkman pumping velocity (EPV) was calculated as

⎜ ⎟= ⎛⎝

∇ × ⎞⎠

EPVρf

τ1(1)

where ρ is the density of the sea water, τ is the wind stress, and f is theCoriolis parameter. The tracks of TCs Phailin and Hudhud were ob-tained from the Joint Typhoon Warning Centre.

The impacts of translation speed and storm intensity on cold wakewas studied using an analytical model (Balaguru et al., 2015). The

analytical model calculated the SST cooling induced by the TC as aconsequence of changes in the mixing length L given by equation (2):

⎜ ⎟= + ⎛⎝

⎞⎠

∗L hρ u tκgα

2 03

13

(2)

where h is the initial mixed layer depth, ρ0 is the density of the seawater, ∗u is the friction velocity, t is the time period of mixing, κ is thevon Karman constant, g is the acceleration due to gravity, and α is therate of increase of potential density with depth beneath the mixed layer.The temperature and salinity profiles from the buoys were used tocalculate the initial mixed layer depth (h). The time period of mixing (t)was calculated as =t R

u , where R is the approximate mean radius ofmaximum winds and u is the translation speed. The advantage of theaforementioned formulation is that it explicitly accounts for the stra-tification of the ocean while calculating the mixing length. The SSTcooling was computed from the dynamic temperature Tdy, which is theSST felt by the core of the TC, defined as

∫=TL

T dz1dy

L

Z0

( )(3)

Isothermal layer depth (ILD) and mixed layer depth (MLD) werecalculated relative to the 10m reference level. ILD was calculated basedon a temperature difference criterion of 0.5 °C. MLD was calculated asthe depth at which the density increases from the reference level cor-responding to an equivalent temperature change of 0.5 °C:

= − −Δσ σ T S P σ T S P( 0.5, , ) ( , , )θ θ θ (4)

where Δσθ is the computed density difference criterion, σ T S P( , , )θ isthe potential density computed based on temperature and salinity at thereference level (10m), and −σ T S P( 0.5, , )θ is the potential densitycomputed equivalent to a temperature difference of 0.5 °C from thereference level. A one-dimensional Price–Weller–Pinkel (PWP) model(Price et al., 1986) was used to study the process controlling the evo-lution of MLD during the cyclones.

3. Results and discussion

3.1. Sea level pressure and wind fields during the cyclones

Phailin was one of the most severe cyclones in the past 14 years inthe BoB (category 5 cyclone on the Saffir–Simpson scale). Before thepassage of cyclone Phailin, the SLP was ∼1008 hPa with wind speed inthe range of 3–7ms−1 (Fig. 2c and a). Note that BD10, which was di-rectly under the eye of cyclone Phailin (∼7.5 km from the track), re-corded the highest drop in SLP and maximum wind speeds (37ms−1).The SLP dropped to 920 hPa at BD10 (Fig. 2c). The spatial ASCATaverage wind speeds during cyclone Phailin revealed that the maximumwind speeds were observed in the north-western BoB (Fig. 1b).

Hudhud developed from a low-pressure area over the Tenasserimcoast. It attained its maximum intensity of category 4 and made landfallon 12 October 2014. Fig. 2d shows the hourly observations of SLP fromthe buoys during Hudhud. The maximum drop in SLP was observed atBD13, moored at a distance of 87 km, which recorded a minimumpressure of 994.6 hPa on 10 October 2014 with wind speeds reaching24ms−1 (Fig. 2d and b). The spatial ASCAT average wind speeds duringthe days of maximum intensities of cyclone Hudhud along with thetrack are shown in Fig. 1e. The highest wind speeds (∼16ms−1) wereobserved in the central BoB. Compared to cyclone Phailin, the windsprior to the onset of Hudhud were weak (Fig. 1a and d).

3.2. SST, SSS, and chl-a response

TCs have significant physical and biological impacts on the upperocean, which manifest as SST cooling, SSS increase, enhancement of

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chl-a concentration, etc. Fig. 3 shows 7-day average SST during the pre-cyclonic and post-cyclonic periods of both cyclones. For the analysis,we considered the pre-cyclonic period in the case of Phailin (Hudhud)as 1–7 October 2013 (1–7 October 2014) and the post-cyclonic periodfor Phailin (Hudhud) as 14–20 October 2013 (13–19 October 2014).Before the passage of Phailin, the SST in the BoB was about 28.5–29 °C(Fig. 3a). The SST prevalent before the onset of Hudhud was muchhigher (29.5–31 °C) than that of Phailin (Fig. 3d). The warmer SST priorto cyclone Hudhud (Fig. 3d) was due to strong diurnal warming aidedby weak winds (Fig. 1d and Supplementary Fig. S1). Besides, the upperocean heat content prior to the onset of Hudhud was higher than that ofPhailin in most of the BoB, except for the BD09 location(Supplementary Fig. S2). The spatial patterns of SST cooling after thepassage of the two TCs were different (Fig. 3b and e). Intense SSTcooling (> 2 °C) confined to a small area bounded by 17–18° N,84.5–86° E (box B) was observed for Phailin (Fig. 3c). The SST cooledby up to 1 °C in the region 16.5–19° N, 84–88° E (box A). However, nosignificant SST cooling was noticed in the BoB east of 88° E after thepassage of Phailin. An extensive SST cooling, roughly up to 1.5 °C, wasobserved along the track of Hudhud (Fig. 3f).

The spatial maps of 7-day average ASCAT winds overlaid on 7-dayaverage Aquarius SSS prior to and after the passage of the cyclones areshown in Fig. 4. SSS in the coastal waters was low (< 28 PSU) beforethe passage of cyclones Phailin and Hudhud (Fig. 4a and d). Low valuesof SSS were observed extending to open ocean waters north of 16° N(Fig. 4a). The offshore advection of low-salinity surface water couldapparently be driven by the prevailing stronger south-westerly winds

(Sree Lekha et al., 2018) during the pre-Phailin days. The SSS responsesto the two cyclones were very distinct. Significant SSS differences oc-curred in the region where SSS values were less than 31 PSU prior toonset of both cyclones. SSS increased by at least 1 PSU everywhere inthe BoB north of 16° N following the passage of Phailin (Fig. 4c),whereas the significant difference in SSS associated with Hudhud wasmostly confined to western coastal regions of the BoB (Fig. 4f).

The upper ocean response to TCs also manifests as enhancement ofchl-a concentration. The intense mixing by strong TC winds increasesthe chl-a concentration in the upper ocean due to the increased nutrientsupply (Walker et al., 2005). Fig. 5a and b shows the OC-CCI version-3chl-a concentration in the vicinity of the track before and after thepassage of Phailin. The chl-a concentration in the open ocean was lessthan 0.2 mgm−3 along the track before the onset of Phailin, but after itspassage chl-a was enhanced to 0.6 mgm−3. A significant enhancementof chl-a concentration to 1.5mgm−3 (about seven times) was observedin box B (Fig. 5a). The chl-a concentration prior to Hudhud was0.2 mgm−3 and a nine-fold enhancement of chl-a was observed afterHudhud throughout the track (Fig. 5c and d).

The upper ocean response of the BoB to these two intense cyclones,Phailin and Hudhud, which traversed very similar paths at nearlyidentical times in 2013 and 2014, was entirely different in terms of SSTand SSS responses as well as biological productivity. The oceanic con-ditions prior to the onset of Hudhud were characterised by warm SST inthe BoB. On the other hand, the pre-cyclonic days of Phailin exhibitedlow SSS. Hudhud induced extensive SST cooling and enhanced chl-aconcentration along the track. However, SST cooling and chl-a

Fig. 1. ASCAT wind speed (ms−1) in the Bay of Bengal averaged for the following periods: (a) pre-Phailin period (5–7 October 2013), (b) duration of Phailin (9–12October 2013), (c) post-Phailin period (15–17 October 2013), (d) pre-Hudhud period (5–7 October 2014), (e) duration of Hudhud (8–12 October 2014), and (f) post-Hudhud period (15–17 October 2014). Red star markers indicate the locations of the moored buoys. The colour code in the cyclone trajectory indicates the intensityof the cyclone based on the Saffir–Simpson hurricane wind scale. (For interpretation of the references to colour in this figure legend, the reader is referred to the Webversion of this article.)

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enhancement in response to Phailin were mostly restricted to a smallregion in the north-western BoB (box B, Figs. 3c and 5b). Nevertheless,following the passage of Phailin, SSS in the BoB north of 16° N in-creased by more than 1 PSU. Intense winds during cyclone Phailin(Hudhud) induced noticeable changes in SSS (SST) over an extensivearea in the northern BoB. The difference in the near-surface thermal orhaline stratification prior to the onset of the cyclones could have ap-parently been caused this distinct response. In addition to near-surfacestratification, the upper ocean response to TC is governed by a

multitude factors including the intensity of TC, translation speed, up-welling (Ekman pumping), entrainment, intensification of pre-existingcyclonic eddies (Vincent et al., 2012), and inertial oscillations (Price,1981; Cuypers et al., 2013). The paucity of ADCP observations frommoorings in the vicinity of Hudhud's track restricted us from exploringthe role of inertial oscillations when contrasting upper ocean response.In the subsequent sections, the plausible mechanisms for the distinctupper ocean responses during these two cyclones are analysed usingobservations and the one-dimensional PWP model.

Fig. 2. Hourly data obtained from measurements of moored buoys BD09, BD10, BD11, and BD13. Wind speed at 10m height during (a) cyclone Phailin in October2013 and (b) cyclone Hudhud in October 2014. SLP during (c) cyclone Phailin in October 2013 and (d) cyclone Hudhud in October 2014. Downwelling shortwaveradiation during (e) cyclone Phailin in October 2013 and (f) cyclone Hudhud in October 2014. Rain rate (mm day−1) during (g) cyclone Phailin in October 2013 and(h) cyclone Hudhud in October 2014.

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3.3. Mechanisms controlling the upper ocean response of the cyclones

3.3.1. UpwellingThe TC winds are the strongest forcing that affects the ocean. The

divergence created by the cyclonic wind stress curl induces upwelling ofthermocline waters, which results in shoaling of the thermocline (Jacobet al., 2000). The EPV estimated from the ASCAT wind stress fields(spatial resolution of 25 km) during the intense days of both cycloneevents is shown in Fig. 6a and b. Positive (negative) value of EPV in-dicates upwelling (downwelling) within the thermocline. High positivevalues of EPV were mostly confined along the cyclone tracks for bothcyclones. The EPV values were observed to be high (∼5×10−4 ms−1)in the north-western BoB for Phailin. The hourly temperature mea-surements from the buoys BD10 (Phailin) and BD13 (Hudhud), locatedon both sides of the cyclone tracks, were analysed and are shown inFig. 7. The profiles from these buoys were considered because of theirproximity to the tracks of the cyclones, and they recorded comparablewind speeds and SLP drop. The mooring BD10 was located roughly130 km from the region where high EPV values were observed. Thedepth of the 26 °C isotherm (D26) shoaled from 75 to 40m at the lo-cation of BD10 after the passage of cyclone Phailin (Fig. 7a). In the post-cyclone days, D26 exhibited pronounced oscillations apparently due tointernal solitary waves (Cuypers et al., 2013; Xu et al., 2011; Guanet al., 2017). The oscillations observed in the temperature profile couldalso be an artefact of change in depth levels of sensors due to stretchesin mooring under extreme weather conditions. EPV during Hudhud wasrelatively weaker than that during Phailin (Fig. 6b). The highest EPVvalues (< 4×10−4 ms−1) observed during Hudhud were in the centralBoB. Moored buoy BD13 was located roughly 150 km south of thestrongest patch of EPV observed during Hudhud. At the BD13 location,

the D26 shoaled from 60 to 55m after the passage of the cyclone.

3.3.2. EntrainmentTC winds generate strong velocity shear in the upper ocean, which

induces intense mixing and entrainment of colder thermocline watersinto the mixed layer, resulting in the lowering of SST (Emanuel, 2001).The friction velocity ( ∗u ) is used to infer the relationship between thewind stress and the surface mixing in the ocean. The turbulent windmixing in the ocean is directly proportional to the cube of friction ve-locity ( ∗u 3) (Klinger et al., 2006). Fig. 6c and d shows the friction ve-locity, computed from ASCAT daily wind stress components, for bothcyclones. During Phailin, friction velocity exceeding 1.75 cms−1 wasobserved over a wider area in the north-western BoB. The highest va-lues of friction velocity (2.5 cms−1) observed during Phailin co-oc-curred with locations of strong Ekman pumping. The upper oceancondition preceding Phailin was characterised by strong near-surfacehaline stratification, shallow MLD (<12m), warm isothermal layer upto 40m, and thick barrier layer (∼23m, Figs. 7a and 8a). The thickbarrier layer sustained temperature inversion at 20–30m depth. As thecyclone approached the location, the intense TC winds of Phailineroded the barrier layer and briefly deepened the mixed layer to 45m.Following the passage of the cyclone, cold saltier water from thethermocline entrained into the mixed layer, resulting in SST cooling of1 °C and surface salinity increase of 2 PSU (Fig. 8a). However, in theregion where SST cooled by > 2 °C and chl-a enhanced significantly(box B, Figs. 3c and 5b), both EPV and friction velocity exhibited lowvalues (Fig. 6a and c).

During Hudhud, the friction velocities exceeding 2 cms−1 observedin the central BoB (Fig. 6d) were co-located with high EPV values. Thesalinity profiles prior to Hudhud (Fig. 8b) were characterised by no or

Fig. 3. Colour shading shows SST based on GHRSST in the Bay of Bengal. 7-day mean SST during (a) pre-Phailin days 1–7 October 2013, (b) post-Phailin days 14–20October 2013, (d) pre-Hudhud days 1–7 October 2014 and (e) post-Hudhud days 13–19 October 2014. (c) SST changes following the passage of cyclone Phailincomputed by subtracting SST data in (b) from (a). (f) Same as 3(c), but showing SST changes after the passage of Hudhud. Colour bars on the bottom left side are for7-day mean SST. Colour bar for SST changes shown in (c) and (f) is given on the bottom right-hand side. Colour shading of the triangular markers in (c) and (f)indicates the translation speed in ms−1 for cyclones Phailin and Hudhud, respectively. Colour scale for the translation speed is given on the right side of the figure.(For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

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Fig. 4. 7-day mean ASCAT winds overlaid on 7-day mean Aquarius SSS in the Bay of Bengal during (a) pre-Phailin days 1–7 October 2013, (b) post-Phailin days14–20 October 2013, (d) pre-Hudhud days 1–7 October 2014, and (e) post-Hudhud days 13–19 October 2014. (c) SSS differences following the passage of cyclonePhailin computed by subtracting SSS data in (b) from (a). (f) Same as 4(c), but showing SSS differences following the passage of Hudhud. Colour bar for 7-day averageSSS in (a), (b), (d), and (e) is shown in the bottom-left side. Colour shading for SSS differences in (c) and (f) is shown in the bottom-right side.

Fig. 5. 7-day average OC-CCI chl-a data (a) during 1–7 October 2013 before thepassage of Phailin, (b) during 14–20 October 2013 after the passage of Phailin,(c) during 1–7 October 2014 before the passage of Hudhud, and (d) during13–19 October 2014 after the passage of Hudhud.

Fig. 6. Ekman pumping velocity averaged during (a) 9–12 October 2013 forcyclone Phailin, (b) 8–12 October 2014 for cyclone Hudhud, and (c) frictionvelocity averaged during (a) 9–12 October 2013 for cyclone Phailin and (d)8–12 October 2014 for cyclone Hudhud. Stars indicate the locations of themoored buoys BD10 and BD13.

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negligible haline stratification up to 50m depth and a high surfacesalinity of 33.5 PSU. The ILD and MLD were observed at the same depthof about 20m and a barrier layer was absent. The isothermal layer waswarmer (∼29.5 °C) and thinner compared to that of Phailin. The near-surface stratification prior to Hudhud was driven by a vertical gradient

in temperature. As the cyclone approached the BD13 location, thesalinity in the top 30m of the water column briefly decreased by ∼0.7PSU (Fig. 8b). The reduction in the salinity coincided with a local cu-mulative rainfall of ∼240mm over the 3-day period of 8–10 October2014. The influx of fresh water from precipitation was insufficient tolower the salinity in the top 30m of the water column beyond 0.3 PSU.Thus, it appears that both local rainfall and horizontal advection con-tributed the salinity changes observed at the BD13 location duringHudhud. Following the passage of Hudhud, the ILD shoaled and en-trained cold saltier water into the mixed layer and subsequently bothILD and MLD deepened. The temperature in the top 30m of the watercolumn decreased by ∼1.3 °C following the passage of Hudhud.

The observations from the moored buoys showed that the presenceof strong near-surface haline stratification with a thick barrier layerduring the pre-Phailin days confined the mixing to the warm isothermallayer, which resulted in weak SST cooling. However, the SSS increasedsignificantly after passage of Phailin. On the other hand, the upperocean condition prior to Hudhud was characterised by negligible near-surface haline stratification and strong vertical gradients in tempera-ture, resulting in significant SST cooling following the cyclone passage.

3.3.3. Intensification of pre-existing cyclonic eddiesMesoscale eddies play a significant role in modulating the upper

ocean response to TCs (Jacob and Shay, 2003; Sun et al., 2014; Meiet al., 2013; Zheng et al., 2010). The cyclonic eddies seem to providerelatively favourable conditions, for the upper ocean response inducedby TC, due to the shallow mixed layer at the centre of the eddy. TCs arealso known to intensify pre-existing cyclonic eddies (Walker et al.,2005; Sun et al., 2014; Vidya et al., 2017; Chacko, 2017). Becausemesoscale eddies are ubiquitous in the BoB (Prasanna Kumar et al.,2004), we analysed the evolution of the eddies using SSHA data. Fig. 9aand b as well as 9d and 9e show 5-day average OSCAR currents overlaidon 7-day average SSHA before and after the passage of both cyclones.Pre-existing cyclonic eddies can be seen in both cyclone cases—in box Afor cyclone Phailin (Fig. 9a) and in 86°–92° E and 13°–16° N for cycloneHudhud (Fig. 9d). The pre-existing cyclonic eddy in box A intensified,leading to decrease in SSHA (∼15 cm), which could be seen after thepassage of cyclone Phailin (Fig. 9c). This could have contributed to thesignificant SST cooling observed in the region away from the TC track.In the case of Hudhud also, intensification of pre-existing cyclonic cir-culation bounded by the region of 86°–92° E and 13°–16° N can beobserved (Fig. 9e). The presence of cyclonic eddies enhanced oceanicresponse in both cases, but a pronounced impact due to intensificationof eddies restricted to a small area was observed only in the case ofPhailin.

3.3.4. Translation speedThe upper ocean response to TC depends on the intensity of the TC

as well as its translation speed (Price, 1981). The translation speeddetermines the forcing time available for a TC to generate strong up-welling and entrainment in the ocean, thereby affecting the upperocean response. Slow moving cyclones (translation speed≤ 4ms−1)have longer forcing times (Mei et al., 2015; Pun et al., 2018; Sun et al.,2010; Zhao et al., 2008). Fig. 3c and f shows the translation speedcomputed from six-hourly cyclone track positions overlaid on the SSTanomaly for both cyclones Phailin and Hudhud, respectively. Wequantified the impact of translation speed on SST cooling using ananalytical model (Balaguru et al., 2015). The vertical profiles of tem-perature and salinity, which represent the typical strong haline strati-fication scenario (as in the case of cyclone Phailin) and the weak halinestratification scenario (as in the case of cyclone Hudhud) were con-sidered assuming the base state of the entire ocean to be the same(Fig. 10a). The base profiles were then subjected to pairs of translationspeed and winds. Fig. 10b and c shows the SST cooling, from the model,for a strongly stratified profile and a weakly stratified profile.

During the intense phase of Phailin, the wind speed and translation

Fig. 7. Temporal evolution of vertical profile of temperature based on hourlymoored buoy observations during (a) Phailin in October 2013 at BD10 locationand (b) Hudhud in October 2014 at BD13 location. The thick white line in thefigure shows mixed layer depth (MLD), the blue line indicates isothermal layerdepth (ILD), and the dotted black lines denote the depth of the 26 °C isotherm(D26). The black vertical lines denote the cyclone period, and the red verticalline indicates the time when the cyclones were close to the moorings. The starmarks in the vertical axis indicate the depths of the temperature sensors in themoorings. (For interpretation of the references to colour in this figure legend,the reader is referred to the Web version of this article.)

Fig. 8. Temporal evolution of vertical profile of salinity based on hourlymoored buoy observations during (a) Phailin in October 2013 at BD10 locationand (b) Hudhud in October 2014 at BD13 location. The thick white line in thefigure shows mixed layer depth (MLD), and the blue line indicates isothermallayer depth (ILD). The black vertical lines denote the cyclone period, and thepurple vertical line indicates the time when the cyclones were close to themoorings. The star marks in the vertical axis indicate the depths of the con-ductivity sensors in the moorings. (For interpretation of the references to colourin this figure legend, the reader is referred to the Web version of this article.)

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speed were typically in the range of 51–72ms−1 and 2.5–5ms−1, re-spectively (black star-shaped markers in Fig. 10b and c). The modelresults suggest that the role of translation speed in SST cooling isnegligible for wind speeds less than 25ms−1. The mean wind speed andmean translation speed, after discounting the data for wind speeds lessthan 25ms−1, were about 59.6 and 3.5 ms−1, respectively (blue star-

shaped marker). The SST cooling obtained from the model for the meanwind speed and translation speed of Phailin for a stratified profile was∼0.6 °C (Fig. 10b). The same wind speed and translation speed ofPhailin over a weakly stratified oceanic state, as in the case of Hudhud,could have yielded SST cooling ∼1.8 °C (Fig. 10c). During the intensephase of Hudhud, the wind speed and translation speed were in the

Fig. 9. 5-day mean surface current vectors based on OSCAR overlaid on 7-day mean SSHA in the Bay of Bengal during (a) pre-Phailin days 1–7 October 2014, (b)post-Phailin days 14–20 October 2013, (d) pre-Hudhud days 1–7 October 2014, and (e) post-Hudhud days 13–19 October 2014, and (c) differences in SSHA andcurrents following the passage of Phailin based on SSHA and current data in (b) from (a). (f) Same as 9(c), but showing differences in SSHA and currents following thepassage of Hudhud.

Fig. 10. (a) Temperature and salinity profiles representing the strong and weak haline stratification scenarios used for the dynamic model. The colour shading in (b)and (c) shows the SST cooling, obtained from the dynamic model, for different pairs of wind speed and translation speed. The star and circle-shaped markers in blackcolour indicate translation speed and maximum wind speed at 6-h intervals for cyclones Phailin and Hudhud, respectively. The blue-coloured star and circle-shapedmarkers denote the mean translation speed and mean wind speed for cyclones Phailin and Hudhud, respectively. (For interpretation of the references to colour in thisfigure legend, the reader is referred to the Web version of this article.)

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range of 25–62ms−1 and 2–4ms−1, respectively (black circle-shapedmarkers in Fig. 10b and c). The mean wind speed and translation speedin the case of Hudhud after discounting data for wind speed less than25ms−1 were 42.6 and 2.93ms−1, respectively (blue circle-shapedmarker). The SST cooling obtained from the model for the mean windspeed and translation speed for a weakly stratified profile was ∼1 °C(Fig. 10c). The same wind speed and translation speed over a stratifiedocean state, as in the case of Phailin, could have yielded only ∼0.4 °CSST cooling (Fig. 10b). The difference in mean translation speed for thecyclones (0.6 ms−1) could have contributed to ∼0.1 °C SST cooling forboth strongly and weakly stratified profiles. Translation speed did notplay a significant role in contributing to the differences in SST coolinginduced by Phailin and Hudhud.

3.4. One-dimensional model for mixed layer evolution during cyclones

A one-dimensional PWP model was used to study the contribution ofdifferent processes affecting the evolution of the surface mixed layer.The PWP model (Price et al., 1986) is a mixed-layer model, which si-mulates the mixed layer variability in response to radiation and verticalwind mixing, driven by the local surface fluxes of heat, momentum, andfresh water without accounting for lateral advection. The modellingwas carried out for three moorings (located nearest to the track and oneither side of the track) for each cyclone event. For cyclone Phailin, themodel simulations were performed on the moorings BD09, BD10, andBD13. For Hudhud, moorings BD10, BD13, and BD11 were considered.The surface forcing fields needed for the PWP, such as sensible heat flux(SHF), latent heat flux (LHF), freshwater flux, momentum flux, and netshortwave radiation, were calculated using the hourly observationsfrom the moored buoys. Net longwave radiation obtained from theNational Centers for Environmental Prediction (NCEP-DOE) reanalysiswas used. The calculation of LHF in the case of BD10 during Phailin andBD13 during Hudhud utilised relative humidity data from the NCEP-DOE reanalysis. SHF for BD10 during Phailin was obtained from theNCEP-DOE reanalysis due to erroneous air temperature measurements.The forcing fields used for the PWP model are shown in Fig. 11. Themodels were initialised with temperature and salinity profiles from therespective moored buoys at 00GMT, 1 October in 2013 and 2014.Fig. 12 shows the density profiles at 00GMT, 1 October 2013 and 2014

The model was forced for 1 month from initialisation. We carriedout a control run and four experiments for each mooring. The experi-ments were designed to study the influence of stratification prior to theonset of cyclones (Experiment 1), post-storm winds (Experiment 2 andExperiment 3), and precipitation (Experiment 4) on mixed layer depthevolution. The evolution of MLD observed from the moored buoys andthe simulated MLD from different experiments are shown in Fig. 13.The MLD was calculated using the variable density criterion corre-sponding to an equivalent temperature difference of 0.5 °C from thereference level at 10m (equation (4)). The model-simulated SST andSSS (at 0.25m depth) corresponding to each experiment are shown inSupplementary Fig. S3. In the control run, the model was initialisedwith observations from the moored buoys at 00GMT, 1 October, prior toPhailin and Hudhud. The air–sea flux fields derived from the respectivebuoy observations (Fig. 11) were used to force the model in the controlrun experiment. The major features of MLD evolution in the control runwere in good agreement with observed MLD (Fig. 13). However, a fewsignificant deviations in the MLD were observed due to processes notconsidered in the PWP model. For example, in the case of BD11 duringHudhud (Fig. 13f), the control run accurately simulated the initialshoaling and deepening of MLD, but it failed to reproduce the shoalingof MLD after the passage of the cyclone. The observations from mooringBD11 revealed that the shoaling of MLD after the passage of the cyclonewas driven by the horizontal advection of low-salinity water (figure notshown). The MLD computed from the control run deviated significantlyfrom that of the observation at the BD11 location as horizontal ad-vection is not considered in the PWP model.

We analysed the model simulated SST and SSS to explore the sig-nature of the entrainment. The water column immediately below themixed layer was characterised by relatively cooler, lower salinity(warmer, saltier) water prior to the onset of Phailin (Hudhud) (Figs. 7and 8). The entrainment across the strong vertical gradient of salinity atthe BD10 location during Phailin (Fig. 8a) caused an ∼2 PSU increasein SSS (Supplementary Fig. S3c) and an ∼1 °C decrease in SST for thecontrol run. The influence of initial stratification on the MLD evolutionduring the cyclone events was studied in Experiment 1. The densityprofiles from the moored buoys prior to cyclones (Fig. 12) revealed theprevalence of relatively weaker near-surface stratification in the case ofHudhud compared to Phailin. Hence, in Experiment 1, the profiles usedto initialise the model were swapped for the respective buoys for thesimulation of Phailin and Hudhud, while the forcing fields were re-tained as in the control run. When relatively less-stratified initial con-ditions prior to cyclone Hudhud were used to initialise the model si-mulation for the respective buoys in the case of Phailin, the MLDdeepened by ∼10m from the control run (Fig. 13a, c and 13e). How-ever, SST and SSS were higher compared to the control run in the caseof BD10 (Supplementary Figs. S3a and S3c). The warmer SST in Ex-periment 1 could be a consequence of higher heat content in the profileused to initialise the model, as evident from the Tropical Cyclone HeatPotential (TCHP) data (Supplementary Fig. S2). Experiment 1 suggeststhat the strong haline stratification prior to cyclone Phailin restrictedthe deepening of MLD and entrainment of cooler thermocline waterinto the mixed layer.

Post-storm winds can hasten or delay restratification of mixed layerafter cyclone passage. A strong post-storm wind can deepen the mixedlayer due to the vertical turbulent mixing and can slow the warming ofsurface water (Mei and Pasquero, 2012). The influence of post-stormwinds in the restratification after cyclones Phailin and Hudhud wasstudied in Experiments 2 and 3. For Experiment 2, the wind stress forcyclones Phailin and Hudhud was swapped after 13 October for therespective buoys for simulation of the cyclones. All forcing fields andinitial conditions as well as wind stress prior to 13 October were re-tained as in the control run. As the wind speed was weak and nearlyidentical on 13 October after cyclones Phailin and Hudhud at all buoylocations (Fig. 2a and b), the transition from the wind stress prevalentduring Phailin to Hudhud or vice versa did not induce any significantjumps. Deviations in MLD from the control run were expected in Ex-periment 2 due solely to the differences in the strength of post-stormwinds. The analysis of wind speeds from the buoys (Fig. 2a and b) andsatellite data (Fig. 1c and f) revealed that the post-storm winds wererelatively weak during 13–19 October for both cyclones. However, atthe BD10 location, the wind speed during Hudhud was about 5ms−1

higher than that during Phailin for the period 19–21 October (Fig. 2aand b). When the relatively strong post-storm winds of Hudhud wereused to replace the weaker post-storm winds of Phailin for Experiment 2in the case of BD10 (Fig. 13a), MLD shoaled compared to the controlrun by about 20m, which is contrary to the expected result. On theother hand, when the relatively weaker post-storm winds of Phailinwere used to replace the stronger post-storm winds of Hudhud, re-stratification of MLD took a longer time compared to the control run(Fig. 13d). These deviations from the expected results could be an ar-tefact of the criterion chosen for the MLD calculation and model phy-sics. A relatively weak wind forcing could restrict mixing of buoyantsurface water (warm, low salinity) to depths shallower than the re-ference level used to compute MLD. Consequently, weakening of windforcing could lead to reduction in rate of mixed layer restratification inExperiment 2. The reduction in the SST and increase in the SSS at theBD10 location for Experiment 2 (Supplementary Figs. S3a and S3c)associated with increase in post-storm wind speed supports the afore-mentioned hypothesis. In Experiment 2, the impact of post-storm windson MLD was analysed by modifying the wind stress data used to forcethe model. However, LHF and SHF are also functions of wind speed.Hence, in Experiment 3, wind stress, LHF, and SHF were swapped after

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13 October for the respective buoys for the simulation of Phailin andHudhud. All other forcing fields and initial conditions as well as windstress, LHF, and SHF prior to October 13 were identical to those in thecontrol run. At the BD10 location, the sum of LHF and SHF was about200 Wm-2 higher during the post-Hudhud period from 19 to 21 October2014 than in the same period after cyclone Phailin (Fig. 11c–f). Whenthe higher values of wind stress, LHF, and SHF during the post-stormperiod of Hudhud were used to replace the post-storm flux data inExperiment 3 for Phailin at the BD10 location, the resultant MLD wasdeeper than that of the control run (Fig. 13a). In addition, the MLD

from Experiment 3 at the BD10 location was deeper than that obtainedfrom Experiment 2 by about 20m, suggesting that the LHF and SHFhave a significant impact on MLD. The post-storm MLD from Experi-ment 3 at the BD10 location during Phailin (forced by Hudhud post-storm winds, LHF, and SHF, Fig. 13a) reproduced the major features ofMLD in the control run for Hudhud at the BD10 location (Fig. 13d) andvice-versa. Similar features were also observed in the MLD computedfrom the control run and Experiment 3 at the BD13 location for cy-clones Phailin and Hudhud (Fig. 13e and b). Experiments 2 and 3suggest that variation in strength of post-storm winds with

Fig. 11. Hourly measurements from moored buoys BD09, BD10, BD11, and BD13. Wind stress at 10m height during (a) cyclone Phailin in October 2013 and (b)cyclone Hudhud in October 2014. SHF during (c) cyclone Phailin in October 2013 and (d) cyclone Hudhud in October 2014. LHF during (e) cyclone Phailin inOctober 2013 and (f) cyclone Hudhud in October 2014. Freshwater flux during (g) cyclone Phailin in October 2013 and (h) cyclone Hudhud in October 2014.

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accompanying variations in LHF and SHF is critical in the control ofMLD restratification after a cyclone.

The significance of precipitation in the evolution of MLD was stu-died in Experiment 4. The precipitation for Experiment 4 was assumedas zero, while retaining evaporation, all forcing fields, and initial con-ditions as in the control run. Intense precipitation during a cyclonerestricts the deepening of MLD. For example, during Hudhud, 240mmof precipitation over a 3-day period (8–10 October 2014) restricted thedeepening of MLD by about 5m (Figs. 2h and 13b).

3.5. Impact of horizontal advection on post-storm restratification

The restratification of temperature and salinity profiles followingthe passage of Phailin and Hudhud was analysed. Rapid salinity fluc-tuations were observed in the top 40m of the water column at the BD10location after the passage of Phailin (Fig. 8a). These salinity jumps hadmagnitude of ∼1.5 PSU within a time period of 4 h. Associated withthese salinity jumps, MLD and ILD also oscillated rapidly up to 30m.Variations in near-surface salinity can be driven by local rainfall, windmixing, or horizontal advection (Liu et al., 2017). However, the localrainfall and mixing (Fig. 2g and a, and Supplementary Fig. S4) at theBD10 location cannot account for the observed rapid fluctuations insalinity in the wake of Phailin (Fig. 8a). The MLD computed using thecontrol run of the 1D-PWP model could not reproduce the abruptfluctuations in observed MLD due to the salinity variations (Fig. 13a).Hence, it is apparent that the salinity variations and associated MLDvariations were driven by processes not considered in the 1D-PWPmodel, such as horizontal advection. Sengupta et al. (2016) reportedabrupt salinity fluctuations in the near-surface layer of the BoB due tosubmesoscale fronts advected past the mooring. The salinity fluctua-tions following the passage of Hudhud at the BD13 location were notpronounced compared to those observed at BD10 following the passageof Phailin. These submesoscale salinity fronts are fuelled by stronghorizontal gradients in salinity (Ramachandran et al., 2018; SpiroJaeger and Mahadevan, 2018). Post-Phailin SSS in the northern BoB ischaracterised by strong horizontal gradients in salinity. The strongest

gradients in salinity (1.2 PSU within 110 km) were observed in thewake of cyclone Phailin (Fig. 4b). Horizontal gradients in salinity werealso observed in the wake of Hudhud. However, the salinity gradientsfollowing the passage of Hudhud were relatively weak compared to thegradients of Phailin (Fig. 4b and e). Upper ocean conditions prior to theonset of Phailin were characterised by strong vertical gradients insalinity (Figs. 4a and 8a) and relatively weak vertical gradients intemperature (Figs. 3a and 7a). The mixing induced by Phailin caused1–4 PSU increase in SSS (Fig. 4c) and less than 1 °C decrease in SST(Fig. 3c). In contrast, upper ocean conditions prior to the onset ofHudhud were characterised by weak vertical gradients in salinity(Figs. 4d and 8b) and strong vertical gradients in temperature (Figs. 3dand 7b). The mixing induced by Hudhud resulted in a less than 2 PSUincrease in SSS, which was confined to coastal waters (Fig. 4f), and a1–2.5 °C decrease in SST (Fig. 3f). Thus, the passage of cyclone Phailinresulted in strong horizontal gradients in near-surface salinity, whereasHudhud resulted in strong horizontal gradients in temperature (up to0.5 °C within 12.5 km). Baroclinic instability in the fronts generated inthe wake of cyclones causes cross-front ageostrophic submesoscalecirculation cells. Submesoscale salinity fronts in the wake of Phailincould have caused the abrupt jumps of salinity (∼1.5 PSU) at the BD10location (Fig. 8a). Similarly, the horizontal gradients in temperature ledto the formation of submesoscale filaments with distinct temperaturecharacteristics in the wake of cyclone Hudhud (Fig. 14). The tempera-ture fronts generated in the wake of Hudhud could have caused theabrupt variations in temperature (∼4 °C within 2 h) at 50m depth atthe BD13 location (Supplementary Figure S5b). However, temperature(salinity) fluctuations in the wake of Phailin (Hudhud) at mooringswere less prominent (Supplementary Figure S5a and Fig. 8b) due to therelatively weaker horizontal temperature (salinity) gradients. Thecross-front ageostrophic submesoscale circulation features play a pi-votal role in the conversion of horizontal gradients into vertical gra-dients and eventual restratification (Mei and Pasquero, 2012). Theupper ocean conditions prior to the onset of a cyclone dictate the pat-terns of restratification following cyclone passage.

Fig. 12. Density profiles from mooringsBD09, BD10, BD11, and BD13 prior to onsetof cyclone (a) Phailin (1 October 2013,00GMT) and (b) Hudhud (1 October 2014,00GMT) used for initialisation of the PWPmodel. The circular markers indicate theMLD calculated using equation (4), and thestar-shaped markers indicate ILD. Both MLDand ILD are calculated based on a 10-mreference level.

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Fig. 13. Evolution of MLD from moorings located in the vicinity of tracks during cyclone (a), (c), (e) Phailin and (b), (d), (f) Hudhud. Black lines denote observedMLD from the moored buoys. Red lines indicate MLD from the control run; blue, green, cyan, and yellow represent the MLD from Experiments 1–4, respectively. (Forinterpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 14. Submesoscale structures in the temperaturefronts generated in the wake of cyclone Hudhudbased on night time NOAA/AVHRR level 2 SST datawith 1.1-km resolution on 13 October 2014. Theregion shown in the figure is indicated by the thickblack box in the inset figure. The inset also shows thetrack of cyclone Hudhud overlaid on NOAA/AVHRRSST data.

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4. Summary and conclusions

The contrasting upper ocean response of the BoB to two intensecyclones, Phailin and Hudhud, which formed during same period in2013 and 2014, respectively, and followed nearly identical tracks, wasanalysed in this study. SST cooling (∼1.5 °C) and nine-fold enhance-ment in chl-a concentration were observed over an extensive area afterthe passage of Hudhud. However, significant SST cooling and chl-aenhancement were confined to a small region in the case of Phailin. SSSincreased (∼1 PSU) over an extensive area (north of 16° N) followingthe passage of Phailin. However, after Hudhud, SSS differences weremostly restricted to the coastal regions in the western BoB. Even thoughthese two cyclones were intense, the upper ocean responses were en-tirely different in terms of SST cooling, SSS increase, and enhancementof chl-a concentration.

The physical mechanisms responsible for the observed differences inupper ocean response to these intense cyclones were analysed usinghigh-frequency observations from multiple moorings located in the vi-cinity of the cyclone tracks, remote-sensing observations, and one-di-mensional modelling. The analyses revealed that the EPV and transla-tion speed did not significantly contribute to the distinct oceanresponses between the two cases. The intensification of the pre-existingcyclonic eddy could have contributed to the significant cooling con-fined to a small region for Phailin. The analysis of the in situ observa-tions from the moorings revealed the presence of strong near-surfacehaline stratification, which sustained temperature inversion prior to theonset of cyclone Phailin. In contrast, the upper ocean condition prior toHudhud was characterised by relatively weaker stratification, whichwas dominated by strong vertical temperature gradients. The presenceof strong haline stratification prior to onset of Phailin curtailed mixingand SST cooling. Process studies suggested that the strong winds ofPhailin over a weakly stratified ocean state, as in the case of Hudhud,could have deepened the MLD by an additional 10m. However, intenseprecipitation events associated with the cyclones could have restrictedMLD deepening. Restratification following the passage of a cyclone ispredominantly governed by horizontal advection, turbulent flux (LHFand SHF), and momentum flux. Advection across strong horizontal

density gradients formed in the wake of cyclones contributes sig-nificantly to post-storm restratification of the near-surface layer. Theupper ocean condition prior to cyclone onset determines the type ofhorizontal gradients observed in the wake of a cyclone. Strong near-surface haline stratification preceding Phailin resulted in horizontalfronts of salinity as the cyclone crossed the BoB. Likewise, the strongupper ocean thermal stratification prior to Hudhud led to horizontalthermal fronts. Following cyclone passage, cross-front ageostrophicsubmesoscale circulation features across the salinity or thermal frontlead to rapid fluctuations in upper ocean salinity and temperature, asobserved in the case of Phailin and Hudhud. These submesoscale cir-culation features are critical in the eventual restratification of the upperocean following cyclone passage. This study highlights that the pro-cesses controlling the oceanic response to TCs operate at time scales inthe range of less than 1 h to days and spatial scales in the range ofsubmesoscale to a few hundreds of kilometres. The study advocates therequirement for observational or numerical modelling techniques thatcan address the variability at time scales of less than an hour to daysand spatial scales ranging from submesoscale to a few hundreds ofkilometres to decipher the upper ocean response to TCs.

Acknowledgements

The authors thank Director, NIOT for the support and encourage-ment and are grateful to the Ministry of Earth Sciences (MoES),Government of India, for providing financial support for the research.The team efforts of NIOT technical team for the maintenance of mooredbuoys is also acknowledged. The authors also thank the anonymousreviewers for their valuable suggestions. The authors express sinceregratitude to Gregory Foltz, NOAA, and Tom Farrar, WHOI, USA, forproviding necessary codes and guidance for numerical models. We alsoacknowledge Mr. Rohith B., INCOIS, for providing necessary sugges-tions for improving the manuscript. The NOAA AVHRR SST dataset isavailable at the INCOIS website http://www.incois.gov.in/portal/remotesensing/TERA_display.html. This work was supported by MoESunder the National Monsoon Mission, Ocean Mixing and Monsoon(OMM) programme.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.dsr.2019.03.010.

Author Contributions

Contributor Role Contributors Role Definition

Conceptualisation Navaneeth K. N, Martin V.Mathew

Ideas; formulation or evolution of overarching research goals and aims

Methodology Navaneeth K. N., Martin V.Mathew

Development or design of methodology

Project Administration R. Venkatesan, Jossia Joseph Management and coordination responsibility for the research activity planning and executionSoftware Navaneeth K. N Programming, software development; designing computer programs; implementation of the computer code and

supporting algorithms; testing of existing code componentsSupervision R. Venkatesan, Jossia Joseph Oversight and leadership responsibility for the research activity planning and execution, including mentorship external

to the core teamVisualisation Navaneeth K. N, Martin V.

MathewPreparation, creation and/or presentation of the published work, specifically visualisation/data presentation

Writing – Original DraftPreparation

Navaneeth.K. N, Martin V.Mathew

Creation and/or presentation of the published work, specifically writing the initial draft (including substantivetranslation)

Writing – Review & Ed-iting

Navaneeth K. N, Martin V.Mathew, Jossia Joseph

Preparation, creation and/or presentation of the published work by those from the original research group, specificallycritical review, commentary or revision, including pre- or post-publication stages

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List of abbreviations

BoB: Bay of BengalArgo: Array for Real-Time Geostrophic Oceanographychl-a: Satellite-sensed surface chlorophyll-a concentrationTC: Tropical CycloneSST: Sea Surface TemperatureGHRSST: Group for High Resolution Sea Surface TemperatureOC-CCI: Ocean Colour data product of Climate Change InitiativeOSCAR: Ocean Surface Current Analysis-Real timeSSS: Sea Surface SalinityASCAT: Advanced Scatterometer (ASCAT)JTWC: Joint Typhoon Warning CentreSLP: Sea Level PressureSSH: Sea Surface HeightEPV: Ekman Pumping VelocityILD: Isothermal Layer DepthD26: Depth of 26 °C isothermSWR_Down: Downwelling Shortwave Radiation

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