Pure Appl. Geophys. Ó 2018 Springer International Publishing AG, part of Springer Nature https://doi.org/10.1007/s00024-018-1932-8 Pure and Applied Geophysics

Upper Ocean and Subsurface Variability in the During : A Synergistic View Using In Situ and Satellite Observations

1 1 1 2 SAMIRAN MANDAL, SOURAV SIL, ABHIJIT SHEE, and R. VENKATESAN

Abstract—In this study, the upper ocean and subsurface vari- 1. Introduction ability during the different phases of the cyclonic storm ROANU along the western Bay of Bengal (BoB) in May 2016 are investi- gated by using the moored buoys, Argos, HF radar and satellite The Bay of Bengal (BoB) is one of the tropical datasets in the proximity of the cyclone track. The moored buoy basins in the world, which is prone to cyclonic storms observations recorded a decrease of (SST) (CS) due to its unique oceanic and meteorological by * 1 °C all over the track, whereas increase in salinity by * 1.5 PSU was detected along with the highest wind speed of conditions. During the pre- (April–May) and 16 m s-1, pressure drop of 14 hPa and air temperature drop of the post-monsoon months (October–November), the 4 °C. The cooling at the cyclone centers from the satellite data BoB experiences intense tropical cyclones, with indicated higher (lower) SST drops when translation speed of the cyclone was low (high) and took more (less) time to recover to its considerable inter-annual variability of the cyclone pre-cyclone state in southern (northern) BoB. Mostly, higher SST intensities (Obasi 1997; McPhaden and Vialard 2009; drop was observed along the right side of the cyclone track. Maneesha et al. 2012; Vissa et al. 2012). Numerous Interestingly, the opposite phenomenon occurred before landfall, studies have reported remarkable changes in the where SST drop was higher on the left due to upwelling in the head bay as observed both from wave rider buoy (WRB) at Digha and upper ocean in terms of sea surface temperature satellite SST. The WRB near Vizag showed the maximum increase (SST), sea surface salinity (SSS), circulation as well in significant wave heights by * 2.4 m during the passage of as the thermohaline structure of the ocean mostly cyclone. Argos also captured cyclone-induced drop in temperature due to upwelling and entrainment reasonably well. In the south- using satellite, few in situ observations and models western bay, significant upwelling was observed from the Argos (Ali et al. 2007; Sengupta et al. 2008; Vissa et al. with drop in temperature and increase in salinity in the upper 2012; Wang et al. 2012; Girishkumar et al. 2014; layers. However, a strong stratification was observed from Argos in the northwestern BoB due to lesser salinity and higher precipita- Prakash and Pant 2017). Due to efficient availability tion. The currents from in situ as well as HF radar datasets of satellite datasets, most of the studies are confined measured the increase in current magnitude during the passage of to the upper ocean to analyze the factors involved in ROANU. Rotary spectral analysis showed strong inertial currents cyclone formation and intensification. The quantity of with frequency * 2.1 days at BD11 location, with higher ampli- tudes of the clockwise component during the cyclone period. change in SST and related oceanic processes depend on the speed of the cyclones. It is reported that Key words: Bay of Bengal, ROANU cyclone, Argo, OMNI upwelling has a negligible relationship with the buoys, Inertial currents, HF radar. lowering of SST for fast-moving cyclones, whereas for slow-moving cyclones it plays a vital role (Price 1981; Black 1983; Bender et al. 1993; Behera et al. 1998; Yablonsky and Ginis 2013). Previous studies over the BoB have reported decline in SST by 0.3–6.0 °C, predominantly due to the cyclones, depending on their path, strength, location and time of occurrence (Rao 1987; 1 School of Earth, Ocean and Climate Sciences, Indian Gopalakrishna et al. 1993; Chinthalu et al. 2001; Institute of Technology Bhubaneswar, Jatni, 752050, India. Subrahmanyam et al. 2005; Sengupta et al. 2008; E-mail: [email protected] 2 Ocean Observation Systems Group, National Institute of Prasad et al. 2009; Pothapakula et al. 2017). The Ocean Technology, , India. S. Mandal et al. Pure Appl. Geophys. vertical mixing plays an important role in the surface Sect. 3, and the results from various observational layer cooling during the cyclone period (Maneesha datasets are described in Sect. 4, followed by dis- et al. 2012; Vissa et al. 2012, 2013). In case of pre- cussions in Sect. 5. Finally, the conclusions are monsoon cyclones, a decrease in SST by 2–3 °C and reported in Sect. 6. mixed layer depth (MLD) deepening up to 80 m is observed which is due to comparatively less salinity stratification in the western and southern BoB (Rao 2. ROANU Cyclone 1987; Gopalakrishna et al. 1993; Behera et al. 1998). On the contrary, along the northern and western BoB Cyclonic storm ROANU is a relatively weaker during post-monsoon seasons, less SST cooling in terms of intensity, which matured (* 0.3 °C) is observed due to intensive salinity over the BoB during 14–22 May 2016 and followed a stratification and temperature inversion layer in the unique track (source: IMD), moving very close to Sri upper ocean. The cyclones-induced vertical mixing Lanka and along the western BoB denoted by A to I leads to the entrainment of warm water, followed by (Fig. 1). It initially developed at 0300 UTC of 14 less cooling after the passage of cyclone (Sengupta May 2016 as a low-pressure system with very low et al. 2008). The increased buoyancy flux due to cyclone intensity (CI) over the southwestern BoB (A rainfall can lower down the cyclone-induced SST and B). Moving northward along the western BoB, it drop by making an increase in the near surface lay as a well-marked low-pressure area adjoining Sri stratification (Jourdain et al. 2013). However, the Lanka at 0300 UTC of 15 May 2016 near location C. same study reported that SST drop in BoB is less It concentrated into a depression (CI: 1.5) and lay influenced by rainfall stratification, since the subsur- centered over southwest BoB off coast face saline water entrainment into the ML overcomes on 17 May 2016 (E). The system continued to skirt the attenuation consequence of rainfall. Previous along the western boundary of the BoB. While studies in BoB have also reported an overall rise of moving northward it intensified (CI: 2) to a deep SSS by 1 PSU (McPhaden and Vialard 2009; depression (DD) due to the favorable environmental Maneesha et al. 2012). conditions near on 18 May 2016 (F). Since the last decade, a remarkable development It intensified into a CS over west-central BoB and lay in ocean observing systems (OOS Programme), viz., centered near position G with a maximum wind speed more numbers of moored buoys in the , of * 20 m s-1 at 0600 UTC of 19 May 2016 (CI: 2) make us capable of observing and analyzing the and to 24 m s-1 at 1800 UTC of 20 May 2016 (CI: 3) extreme weather events and associated dynamical (H) (IMD 2016). The system maintained its intensity processes in the BoB (Venkatesan et al. 2016). The of 24 m s-1 and crossed coast near advancements are primarily because of persistency location I (91.60°E, 22.60°N), to the north of Chit- and higher accuracy of the observations using Ocean tagong around 1000 UTC of 21 May 2016 as a CS. A Moored Buoy Network for northern Indian Ocean synoptic situation of intensification to CS on 19 May (OMNI) buoys, gauges and acoustic doppler 2016 has been well captured from KALPANA-1 current profilers (ADCPs). In this paper, we have satellite showing higher cloud coverage along the highlighted the development of an observation sys- cyclone track with associated lower outgoing long- tem over the BoB toward the analysis of extreme wave radiation (OLR) magnitude of * 110 W m-2 events like cyclone. It focuses not only on the vari- (Fig. 2) (Subrahmanyam et al. 2005). The synoptic ation of the thermal structure of the upper ocean, but OLR distribution and associated wind pattern show also describes the variability of the subsurface ocea- the influence region of the cyclone on the nearby nic parameters in the ocean before, during and after buoys. After landfall, the system started to weaken the passage of the cyclonic storm ROANU. due to land interactions. Continuing its northeastward The structure of the paper is as follows; the brief journey, the CS gradually degraded into a DD over description of ROANU cyclone passage is presented Mizoram at 1800 UTC of 21 May 2016, into a in Sect. 2, the data and methodology are discussed in depression over and adjoining Manipur at Upper Ocean and Subsurface Variability in the Bay of Bengal During Cyclone ROANU

Figure 1 Best estimated track (source: IMD) of the ROANU cyclone (black line) with centers at every 1200 UTC from 13 to 21 May 2016. Pink, green and blue squares indicate depression, deep depression and cyclonic storm stages of the cyclone, respectively. Observational data were taken from wave rider buoys (WRB) (blue diamonds) at Pondicherry (WRBPY), Vizag (WRBVG) and Digha (WRBDG), OMNI buoys (black triangles) and Argos of platform numbers 5904334 (black dots), 6901557 (pink dots), 2902194 (blue dots), 2902087 (red dots), 6901562 (green) and 2902196 (cyan). The shaded contour denotes the bathymetry of the whole basin, with the black contour denoting - 2500 m bathymetry

0000 UTC of 22nd May 2016 and into a well-known given in Table 1. These datasets enabled constant low-pressure area over Myanmar adjacent to Naga- monitoring of the cyclone during its different phases, land and Manipur at 0300 UTC of 22 May 2016 from evolution to landfall, as they continuously (IMD 2016). measure parameters such as air temperature, rainfall, wind speed, air pressure, wind gust and subsurface temperature, salinity and currents. In the BoB, the 3. Data and Methodology OMNI buoys withstood the strongest winds and sur- face as well as subsurface ocean currents associated In the present study, the met-ocean parameters with many cyclones. The datasets are well validated from moored OMNI buoys (BD08, BD09, BD11 and in many previous studies (Venkatesan et al. BD14) and significant wave height and SST data 2013, 2016; Girishkumar et al. 2014), which moti- from the wave rider buoys at Digha, Pondichery and vated us to study the variability of oceanic parameters Vizag (WRBDG, WRBPY and WRBVG), deployed during cyclonic storm ROANU using these in situ in the BoB by ESSO-INCOIS, have been used. The datasets. The best estimated track of the cyclone and OMNI buoys and WRBs which are relatively close to other relevant information of ROANU were obtained the cyclone track are considered (Fig. 1). The loca- from the India Meteorological Department (IMD) tions of the in situ observations and parameters are tropical cyclone best track data site. Temperature and S. Mandal et al. Pure Appl. Geophys.

Figure 2 Spatial variation of OLR from KALPANA-1 with wind vector (from ASCAT) on 19 May 2016. Pink, green and blue squares indicate depression, deep depression and cyclonic storm stages of the cyclone. Black line shows the cyclone track. The black triangles are OMNI buoys salinity profiles for the present study were obtained The hourly surface currents with spatial resolution from six Argos (5904334, 6901557, 2902087, of * 6 km are used after quality control (John et al. 2902194, 2902196 and 69021562) within the vicinity 2015; Mandal and Sil 2017; Mandal et al. 2018). of the cyclone track and used after quality control Further, to look into the surface circulation pattern, (Wong et al. 2009; Sil and Chakraborty 2012). algorithm-derived currents (ADC) are produced from ‘‘These data are collected and made freely available satellite observations. The ADC datasets are the by the International Argo Program and the national combination of three components of surface currents programs that contribute to it. (http://www.argo.ucsd. obtained from satellite products, namely, (i) the edu). The Argo Program is part of the Global Ocean wind-driven (Ekman) component from winds, (ii) the Observing System’’. The daily rainfall used for the geostrophic component from sea surface height present study were collected from WindSat with anomaly (SSHA) and (iii) the surface buoyancy spatial resolution of 1/4° (Freilich and Vanhoff component from SST, all on daily scale (Mandal 2006). et al. 2018). To derive ADC, daily winds from the In this study, the surface currents from the long Advanced Scatterometer (ASCAT) with spatial res- range SeaSonde HF radar systems (4.4 MHz), olution of 1/4° (Bentamy et al. 2012) are used. deployed and maintained by ESSO-NIOT, Chennai, Satellite altimetry-derived daily SSHA with spatial along the west coast of BoB are utilized (Table 1). resolution of 1/4° is used, which is produced by HF radar is a relatively latest technique since the last Ssalto/Duacs and distributed by Aviso, with support two decades for remotely measuring surface currents. from Cnes, http://www.aviso.altimetry.fr/duacs/. The Upper Ocean and Subsurface Variability in the Bay of Bengal During Cyclone ROANU

Table 1 Descriptions of the in situ and HF radar observations

Instruments Mean geographical locations Parameters used Frequency

A. OMNI buoys BD08 89.69°E, 18.20°N Air temperature, rainfall, SST, wind speed, wind 3h BD09 89.69°E, 17.89°N gust and pressure BD14 88.02°E, 07.04°N BD11 82.92°E, 14.03°N Same as BD08 ? currents, salinity and temperature B. Wave rider buoy (WRB) At Digha (WRBDG) 87.65°E, 21.29°N Significant wave height and SST 1 h At Vizag (WRBVG) 83.27°E, 17.63°N At Pondicherry 79.86°E, 11.92°N (WRBPY) C. HF radar Odisha coast Stations: Surface currents with spatial resolution of * 6km 1h : 85.86°E, 19.80°N Gopalpur: 84.96°E, 19.30°N Andhra Pradesh coast Stations: Machilipatnam: 81.24°E, 16.24°N S Yanam: 82.10°E, 16.48°N Tamil Nadu coast Stations: Cuddalore: 79.77°E, 11.69°N Kalpakkam: 80.16°E, 12.49°N

daily SST with spatial resolution of 1/12° was taken variability has been discussed in Sect. 4.4 from HF from Group of Higher Resolution Sea Surface Tem- radars, moored buoys and ADC along with the perature (GHRSST) to study the difference in the influence of the inertial currents on the circulation SST before, during and after the span of cyclone. The during the cyclone period. SST dataset has also been validated against the in situ observations at the buoy locations (BD08, BD09 and 4.1. Surface Met-Ocean Variability from OMNI BD14), which shows higher correlation (0.93–0.98) and Wave Rider Buoys and lower root mean square errors (0.24–0.29 °C). Also, daily OLR data from KALPANA-1 satellite The average air pressure (1008 hPa) was observed with spatial resolution of 1/4° were used to capture with moderate southwesterly winds (2–6 m s-1) at all the cloud coverage during the period of cyclone buoy locations, indicating the pre-monsoon condi- (source: https://mosdac.gov.in/). tions in the BoB before the passage of ROANU cyclone (1–12 May 2016) (Fig. 3). Initially, the buoy BD14 responded to the cyclone during period 12–14 4. Results May 2016, with an initial drop of air pressure (* 1003 hPa), increased wind speed (* 10 m s-1) In this section, at first the variability of met- and rainfall (10–25 mm) to provide first impressions oceanic surface parameters from OMNI buoys and of depression stage (CI: 1.5, IMD) of ROANU WRBs during the cyclone period has been discussed (figure not shown). The next signature of the cyclone in Sect. 4.1, followed by the illustration of spatio- was captured at WRBPY deployed at Pondicherry temporal variations of the SST from GHRSST in near location E on 17 May 2016. Drop in SST Sect. 4.2. Further in Sect. 4.3, the subsurface tem- by * 1 °C and increase in significant wave height perature and salinity have been interpreted from Argo by * 1 m (Fig. 4) were observed at WRBPY, when to OMNI buoys. The surface and subsurface current the cyclone moved as a DD with lower wind speed S. Mandal et al. Pure Appl. Geophys.

Figure 3 Variation of met parameters: a rainfall, b air pressure, c air temperature, d wind speed, e sea surface temperature and f wind gust from OMNI buoys (BD08, BD09 and BD11). The black, blue and red lines denote BD08, BD09 and BD11 buoys, respectively. The blue band shows the intensified stages of the cyclonic storm during 17–18 May 2016 and the red band during 19–20 May 2016. SST data at BD11 were not available in the above period near Tamil Nadu. The wave heights retained their noticed for a longer period in BD11, thereby pre-cyclone values on 19 May 2016 as the cyclone indicating the slow movement of the cyclone. More- departed to G. over, the effect of the cyclone was noticed in the As the cyclone advanced northward along the other buoys BD08 and BD09 as it passed through the Andhra Pradesh coast, it got intensified to DD as northwestern BoB. The cyclone got intensified observed from BD11. A moderate drop in the sea- further to its highest CI (4) near Odisha with the level pressure from 1009 hPa during 15 May to highest drop in air pressure to 996 hPa (Fig. 3b) and 999 hPa by 18 May 2016 was observed (Fig. 3b), highest wind speed of 17 m s-1 as observed from with higher wind speed reaching up to 14 m s-1 both BD08 and BD09 (Fig. 3d), before it dissipated (Fig. 3d). A wind gust of 20 m s-1 was recorded at and made landfall on 21 May 2016 at Bangladesh. A the same time (Fig. 3f). On 19 May, the WRBVG cooling was observed with SST drop of * 1 °C and close to G captured a drop in SST by 1 °C, from 30.5 an air temperature drop of 4–5 °C (Fig. 3c) at both to 29.5 °C (red line, Fig. 4b) with an abrupt rise in buoy locations. A heavy rainfall of * 40 mm was the wave heights by * 2.4 m. It attained maximum observed at BD09 (BD08) during 18 (20) May 2016. significant wave height of 3.4 m (Fig. 4a) due to Additionally, BD09 also captured * 30 mm of rain- surges and finally took * 10 days to recover to pre- fall on 21 May 2016 after the cyclone passed the cyclonic state (* 1.0 m). A sudden drop in air location (Fig. 3a). A drop in SST by * 1 °C along temperature from 32 to 27.5 °C as well as drop in with a significant wave height of nearly 3 m was also SST by * 1 °C was observed (Fig. 3e) along with noticed from WRBDG deployed at Digha (Fig. 4). the highest rainfall of 40 mm (Fig. 3a) from BD11. During the whole span of the cyclone, minimum The variations of the met-ocean parameters were air pressure of 996 hPa along with high wind speed of Upper Ocean and Subsurface Variability in the Bay of Bengal During Cyclone ROANU

Figure 4 Hourly variation of a significant wave height and b sea surface temperature (SST) from wave rider buoys (WRBs) at Digha (black), Pondicherry (blue) and Vizag (red), respectively. The cyclone passed near Pondicherry, Vizag and Digha on 17, 19 and 20 May 2016, denoted by blue, red and gray bands, respectively

17 m s-1 was observed at both BD08 and BD09 throughout the above oceanic processes are discussed locations. The comparably higher SST drop was in detail in the forthcoming sections. observed on the right side (from OMNI buoys) than the left side (from WRBs) of the track. The possible 4.2. Spatiotemporal Variability of SST from Satellite factors involved behind the fall in SST described above are cyclone-induced upwelling, favorable wind The SST is one of the main parameters for the stress curl and high rainfall events. During 18–19 evolution of cyclones. The response of SST on May 2016, the air temperature was less than 26 °C, cyclones and vice versa has been widely studied which indicated a clear fall in the temperature during the cyclone periods using satellite observa- (4–5 °C) at the BD08, BD09 and BD11 locations. tions. This section presents the analysis of the The sudden drop in air pressure and air temperature cyclone-induced changes in SST to quantify the and increase in wind speed may induce strong air–sea SST drop and its recovery time to the pre-cyclone fluxes near the ocean surface. The decrease in air conditions. The utmost SST reductions are normally temperature can be attributed to the downdraft observed along the right side of the track in the associated with deep thunderstorm cloud (Houze Northern Hemisphere (Black and Dickey 2008), 2004). The maximum wind gust observed was whereas to the left of the track in the Southern 25 m s-1 at both BD08 and BD09. A maximum Hemisphere (Dare and McBride 2011). However, the wave height of 3.4 m was observed along the Andhra oceanic responses show larger variations in the upper Pradesh coast near location G. The factors involved surface as the cyclone continues along the track. In S. Mandal et al. Pure Appl. Geophys.

Figure 5 a Evolution of sea surface temperature (SST) at the locations (C–H) as shown in Fig. 1 for 10 days before and 30 days after the passage of cyclone from GHRSST. Dotted black line indicates the day when the cyclone passed the corresponding location. b SST drop calculated as the difference of mean SST 10 days before the arrival and 3 days after the passage of cyclone this work, the daily variations of SST at the cyclone northern BoB, the recovery time decreased. Earlier centers (C to H) were studied for 10 days before and studies have reported that, in case of 88% of the 30 days after the passage of cyclone using GHRSST tropical cyclones, SST recovered to the pre-cyclone (Fig. 5). The daily SST anomaly was calculated by value within 30 days, where the magnitude of cooling subtracting the daily climatology, generated using is a function of CI (Hart et al. 2007; Dare and 10 years of daily data during the period 2007–2016 to McBride 2011). Also, it has been reported that both remove the seasonal cycle (Balaguru et al. 2014; Dare the CI and translational speed affect the SST and McBride 2011). In addition, the temperature on variations both in terms of drop and recovery. Since the day of the cyclone was also removed. The time the ROANU cyclone moved slowly, the drop was evolution of the SST anomalies shows the SST drop more significant in its initial stage, whereas less drop near (at C and D) was around 1.0–1.5 °C was noticed at the mature stage associated with the and took a longer time ([ 30 days) to recover to the highest translation speed (Sun et al. 2010). In addition pre-cyclonic state. However, near Odisha (at G and to the translation speed, the oceanic conditions play a H), the drop was comparatively lesser and recovery vital role in SST evolution which can be inferred was faster (6 days) than that of C and D. Moreover, at from the subsurface parameters. locations E and F, the SST drop of 0.5–0.8 °C was It was observed that on average, the maximum observed, and recovery to pre-cyclone state was SST drop occurred 3 days after the passage of 10 days after cyclone passage (Fig. 5a). It is to be cyclone at the respective cyclone centers (Fig. 5a). noted that as the cyclone moved from the southern to Therefore, the SST drop was quantified at the cyclone Upper Ocean and Subsurface Variability in the Bay of Bengal During Cyclone ROANU

Figure 6 Sea surface temperature (SST) drop calculated using the same methodology as above on a 19 May 2016 and b 21 May 2016, c variation of SST between 14 and 25 May 2016 from BD08 (black), BD09 (blue) and WRBDG (red) centers (Fig. 5b) and in the entire BoB (Fig. 6a, b) as situation is entirely opposite due to the interaction the difference between the SST anomalies 3 days with the shallow bathymetry in coastal waters. It is to after the arrival and 10 days averaged SST anomaly be noted that at the landfall location, maximum SST prior to the day of arrival of the cyclone. The highest drop is observed along the left side of the track (lowest) SST drop * 0.8 (0.2) °C was observed at F (Fig. 6b). This result is also strongly supported by the (H) where the cyclone stayed for the longest (short- in situ observations (Fig. 6c), where the SST drop est) time with the highest CI of magnitude 4. was more at WRBDG (left of the cyclone) as Figure 5b clearly depicts that SST drop is dependent compared to BD08 and BD09 (right of the cyclone) on the cyclone translation speed. The same explana- on 21 May 2016. So, along the coastline, why does tions also hold good for the SST drop at other the left side of the track show higher cooling? As the locations C, D and E. cyclone propagates toward the coastal waters, the net The spatial distribution of SST variation (Fig. 6a, Ekman transport would be toward the coast, owing to b) also satisfies the well-known convention that the the northerly winds along the front edge of the maximum SST drop is usually observed along the cyclone . All along this period, the onshore right side of the cyclone track mainly due to the transport was observed along the right side of the higher wind stress. However, just before landfall, the track. However, as the cyclone enhanced further S. Mandal et al. Pure Appl. Geophys. toward the head bay region, SST cooling was cyclone position E (81.20°E, 11.30°N). A tempera- observed to the left of the cyclone track, which is ture drop of 1 °C and salinity rise of * 0.6 PSU at predominantly attributed to the coastal upwelling depth level 0–40 m were observed, which lasted for favorable winds and the offshore transport (along the about 5–7 days after the cyclone passed by (Fig. 7a, left side of the track). Thus, this phenomenon along b). But freshening was observed with lower salinity with the coastal bathymetry/geomorphology of the during the passage of cyclone from both the Argos, head BoB inhibits the Ekman transport, causing which was attributed to the intense rainfall at the piling up of the water during the landfall time on the nearby locations (Fig. 9). However, higher salinity right side of the track. Previous studies have shown and lower temperature were observed from both the that the phenomenon responsible for the piling up of floats due to upwelling at 60 m depth, leading to water due to onshore transport is relatively higher subsurface cooling (Fig. 7c, d). Near Andhra Pradesh surges on the right of the landfall (Khan et al. 2000). on 18–19 May 2016, the cyclone got intensified from This characteristic of the coast in a limited region, DD to CS stage at location F (81.6°E, 14.6°N). The influencing the thermal structure of the upper ocean, Argo floats (2902087 and 2902194) as well as the has not been discussed yet due the lack of moored buoy BD11 were located near the cyclone observations. position from where the temperature and salinity profiles could be observed (Fig. 1). The rise in salinity (1 PSU) as well as the drop in temperature 4.3. Variability at Subsurface from BD11 and Argos (3 °C) was observed from both the floats at depth due The section describes the temperature and salinity to strong upwelling at the subsurface (up to 120 m) variations at the subsurface as observed from six near F (Fig. 7e–h). Similar results were observed Argo floats (Fig. 7) and OMNI buoys (Fig. 8) near from BD11, which depicted that salinity dropped the cyclone track before, during and after the passage significantly at 10, 15, 20 and 30 m depths, whereas of the cyclone. The vertical profiles of Argos clearly an abrupt escalation was observed at 50 m (Fig. 8b) depict the absence of inversion layers during May along with cooling both at the surface and subsurface 2016 (summer session) in the present study, which is (Fig. 8a). The upper surface temperature dropped to in good agreement with an earlier study on BoB 22 °C (Fig. 7e) and salinity increased to * 34 PSU (Vissa et al. 2012). Before ROANU, pre-monsoon (Fig. 7f) as observed from Argo float 2902087 due to conditions dominated the bay and thereby limited upwelling from * 100 m depth. Similar results were variations were observed in temperature and salinity obtained from another float (2902194) near location at the subsurface, depicting that the MLD was F; however, the results were more significant from shallow (20–30 m). On the upper surface, tempera- the former float. After the passage of the cyclone on ture decreased by about 2 °C from about 30 °Cto 18 May 2016, it took nearly 8 days to regain the pre- 28 °C at all the Argo locations, which was similar to cyclonic conditions, i.e., the observed Argo profiles the average SST change of * 2 °C during 16–18 were identical to those observed before the cyclone. May 2016 at the locations D and E (Fig. 4b). At the This associated drop in the SST and the presence of subsurface, higher variability was observed at all the higher saline waters were the consequence of strong locations (Figs. 7, 8a). As the cyclone approached mixing and upwelling of the cold subsurface waters northward near Odisha, limited variations in both to the surface. Comparatively, higher temperature temperature and salinity at the subsurface were (Figs. 7e, g, 8a) associated with warm core eddy in observed due to the rapid movement of cyclone and the upper surface, observed near F, was one of the lack of vertical mixing. key factors for the cyclone intensification (Yablonsky As the cyclone moved along the Tamil Nadu coast and Ginis 2013). Along the Odisha coast (G and H), near the location E on 17 May 2016, where the highly stratified upper layers associated with lower cyclone was in its depression stage, the floats salinity (Fig. 7j, l) were observed from the floats 5904334 and 6901557 were chosen for analysis, as 2902196 and 6901562, which did not allow vertical they were located within the range of 200 km of the mixing. A drop of temperature by * 0.6 °C was Upper Ocean and Subsurface Variability in the Bay of Bengal During Cyclone ROANU

Figure 7 Temperature (left) and salinity (right) profiles from the selected Argo floats 5904334, 6901557, 2902087, 2902194, 2902196 and 6901562, respectively, from top to bottom during different phases of the ROANU cyclone. The x-axis represents the days in the month of May 2016 and y-axis indicates the depth in meters. The locations of the Argos are indicated in Fig. 1 S. Mandal et al. Pure Appl. Geophys.

Figure 8 Observed time series of a temperature from BD11, b salinity from BD11, current speed from c BD11 and d BD09 at various depths 10, 15, 20, 30 and 50 m Upper Ocean and Subsurface Variability in the Bay of Bengal During Cyclone ROANU

Figure 9 Precipitation rate (shaded, in mm h-1) from WindSat satellite on a 17 May 2016 and b 20 May 2016 from WindSat. Black line shows the track of the cyclone observed at the depth level of * 40 m (Fig. 7k), but western coast of the BoB usually varies between 0.6 the temperature variation was very less as compared and 1.0 m s-1 as observed from HF radar (Mandal to other floats. However, upwelling was observed at a and Sil 2017). During the reign of the cyclone depth between 40 and 60 m on around 20 May 2016, ROANU, an increase in current magnitudes as well as which could not break the fresh water layer in the unique flow patterns in all the three regions was upper surface. Despite the usual convention that observed. The current speed was observed to rise to salinity increases after the passage of cyclone, in the 1.5 m s-1 along the Odisha coast due to highest CI of present case the salinity decreased (Fig. 7l), possibly the cyclone (Fig. 10e). Increase in surface current because of the heavy rainfall (Fig. 9) and the lack of speeds was also noticed by buoys BD08 and BD09 vertical mixing due to the rapid movement of the due to high wind speeds (17 m s-1), but the magni- cyclone. tude observed was quite less as the buoys were far away from the cyclone location (Fig. 8). Near Andhra Pradesh, the current magnitude associated with an 4.4. Variability of the Ocean Currents from Moored anticyclonic eddy (Fig. 10c) rose to * 1.4 m s-1 Buoys, HF Radars and Satellites (Fig. 10e). The HF radar circulation pattern matched A comparative study of the ocean surface currents quite well with the circulation pattern as observed from the HF radars and ADC was done, followed by from ADC (Fig. 11a). Along the Tamil Nadu coast, the variability of subsurface currents from the moored significant changes in the surface current speed were buoys. The variation of inertial currents due to strong not observed (Fig. 10d), which can be attributed to prevailing winds was also studied from the moored the less intensification and slow movement of the buoy BD11. It is to be noted that the cyclone cyclone. However, this slight increase in ocean ROANU traveled through the HF radar coverage in surface currents was observed on 18 May 2016 the western BoB (Fig. 10). The magnitude of spring- (Fig. 10e). This HF radar network along the western time western boundary current (WBC) along the BoB may provide us an opportunity to study the S. Mandal et al. Pure Appl. Geophys.

Figure 10 a The circulation pattern as observed from HF radar datasets along the west coast of BoB with zoomed view for b Odisha, c Andhra Pradesh and d Tamil Nadu coast, respectively, during the passage of the cyclone, i.e., 20, 18 and 17 May, respectively. The shaded background shows the magnitude of the current in m s-1. The black line represents the track of the cyclone. The red dots indicate the radar stations. e The hourly variation of current speed (m s-1) from HF radars at the three locations. Black circles indicate the peaks of current speed during passage of cyclone interaction during the cyclonic event maximum current speed was recorded on 18 May along the east coast of India. 2016 at BD11 (Fig. 8c), whereas a similar increase Looking into the current speed at the subsurface was noticed on around 21 May 2016 at BD09 from moored buoys, it can be clearly observed that (Fig. 8d). Interestingly at BD11, the current speed Upper Ocean and Subsurface Variability in the Bay of Bengal During Cyclone ROANU

Figure 11 a The location of BD11 with the surface current on 18 May 2016 (from ADC), b the rotary spectra during the no-cyclone period January– March 2016. c The rotary spectra during the cyclone period in May 2016. The blue (red) line indicates the amplitude of the clockwise (counterclockwise) component of the surface currents from the BD11 buoy

(* 0.46 m s-1) at subsurface depths (at 30 and parameter dependent on the latitude. So, the period- 50 m) was higher than at the upper surface (at 10 and icity decreases toward the pole. As a result, the 20 m) where the current speed ranged between 0.20 clockwise component dominates the anticlockwise and 0.30 m s-1. However, at BD09, the upper surface component in the Northern Hemisphere, which current speed was observed to be high further results in the clockwise rotation of the inertial (* 0.60 m s-1) which decreased to 0.25 m s-1 as currents. During ROANU, the moored OMNI buoy the depth increased to 50 m (Fig. 8c, d). The higher BD11 (closest buoy to the track) followed a clock- subsurface current speed was due to strong mixing wise path similar to the surface circulation pattern, and turbulence near the BD11 location, which was which is attributed to the intensified inertial currents further due to strong mixing signatures (lower SST as a result of the stronger winds (Fig. 10a). The and higher salinity) from the Argo float 2902194. higher resolution (temporal and spatial) near surface The cyclonic wind-induced intensification of ocean currents from satellite were not available inertial currents have been reported with significant during May 2016; therefore, rotary spectral analysis results in an earlier study from in situ observation was performed using hourly surface current data from (Girishkumar et al. 2014). The inertial oscillations BD11. The periodicity (inertial frequency) of around have periodicity of 2p/f, where f is the Coriolis 2.1 days was observed, which matched well with the S. Mandal et al. Pure Appl. Geophys. maximum difference between the clockwise and observed. Hence, this upwelling is not a part of the anticlockwise components, obtained from the rotary coastal upwelling, as coastal upwelling is limited current spectra at the buoy location. The rise in the to * 50 km away from the coast (Shetye et al. energy/amplitude of the clockwise component was 1991). observed from the spectra during the cyclone period It is to be noted that before the passage of the (Fig. 11c) in comparison to the non-cyclonic period cyclone, the temperature and salinity profiles from (January to March 2016) (Fig. 11b) (Girishkumar the Argo floats and met-ocean parameters from the et al. 2014). OMNI buoys showed typical pre-monsoon conditions over the western BoB. During 13–16 May 2016, the cyclone was in its depression stage as captured from 5. Discussions the buoy (BD14) with high rainfall, high wind speed and low pressure (figure not shown). The significant Section 4 describes the signatures of ROANU wave heights at the WRBs showed the usual behavior cyclone from a number of datasets and highlights the before the cyclone reached Tamil Nadu (Fig. 4a). usefulness of these observation platforms toward The cyclone stayed for a longer time at D to give an monitoring a cyclone. This section will describe the SST drop of * 0.6 °C, although it was in depression physical processes associated with the different stage (Subrahmanyam et al. 2005; Sun et al. 2010). stages of cyclone using the results described above Also, 7 days after the passage of cyclone, the SST with supporting satellite winds dataset. dropped further and has been captured from satellite The cyclone-induced oceanic responses are (Fig. 5b) (Dare and McBride 2011; Balaguru et al. mainly due to the higher wind speeds. But the vari- 2014). On 17 May 2016, the ROANU intensified to ations in the responses depend on the ocean states and DD near location E. Increased WSC was observed the translation speed (Black 1983; Hart et al. 2007; from the ASCAT winds (Fig. 12b) which led to wind- Sengupta et al. 2008). The spatial distribution of wind induced mixing in the nearby region. An SST drop stress curl (WSC) has been shown to indicate was observed from WRBPY and satellite SST at the cyclone-induced upwelling during its reign (Fig. 12). same location. The upwelling signatures were also Higher WSC was noticed along the ROANU track observed nearly 6–7 days after the passage of the during the whole period at all the locations except cyclone from Argo float (6901557) (Fig. 7c, d). The along the Odisha coast (Fig. 12). This directly points salinity reduced at the upper surface due to heavy out the event of an intense divergence in the upper rainfall near this location (Fig. 9a). Also, the cyclone ocean underneath the track, which further led to an crossed through the HF radar coverage at Tamil Nadu upwelling at the base of the MLD as well as down- coast and an increase in the current speed was cap- welling away from the cyclone track on the edge of tured from these radars (Fig. 10e). divergence (Fig. 12). The WSC-induced upwelling It further intensified to CS on 18 May 2016, results in sea surface cooling along the boundary exhibiting higher wind speed for a longer time as (along and away) of the passage of the cyclone captured by BD11 (Fig. 3b). The associated maxi- (Fig. 6a, b). While the cyclone moved along the mum WSC near location F, as observed from satellite western BoB, a maximum wind speed of winds (Fig. 12d), led to maximum SST drop in about * 16 m s-1 was observed along the right side comparison to all other locations (Fig. 5b). The sig- of the track near the Odisha coast. Also, the time natures from the Argo floats (2902194 and 2902087) evolution of WSC within 1° 9 1° box average along were different along the right and left sides of the the path of ROANU was calculated using satellite cyclone track (Fig. 7e, f) (Vissa et al. 2012). winds (Fig. 12d). It clearly depicts the absence of Although similar uplifting of the isotherms was wind-driven upwelling before the arrival of cyclone observed from the subsurface in both Argos, the at all locations. As the cyclone stayed as CS for a colder and saltier water reached the near surface in long time at locations F (18 May 2016) and G (19 the right Argo (Fig. 7g, h). It satisfied the general May 2016), a maximum wind-induced upwelling was concept of higher SST drop along the right side of the Upper Ocean and Subsurface Variability in the Bay of Bengal During Cyclone ROANU

Figure 12 Spatial distribution of wind stress curl (shaded in N m-3)ona 18 May 2016, b 19 May 2016 and c 20 May 2016 with winds (vector) from ASCAT. Black line shows the track of the cyclone. d The evolution of wind stress curl at location A–H for 5 days before and 10 days after the passage of cyclone from ASCAT winds track due to stronger winds (Fig. 12a) (Maneesha supported by WRBVG (Fig. 4b). The influence of the et al. 2012; Pothapakula et al. 2017). Moreover, the cyclone was also noticed from the increase in sig- intensification of the cyclone at this location can be nificant wave height (* 2.4 m) at WRBVG on 19 strongly attributed to the interaction with the warm May 2016. core eddy (Ali et al. 2007; Yablonsky and Ginis The CS moved from the G to I with the highest 2013) near Andhra Pradesh, as observed from ADC translation speed with the observed highest wind (Fig. 11a) and well supported by HF radars (Fig. 10c) speed (* 17 m s-1) and lowest pressure (996 hPa) (John et al. 2015). Due to the strong winds and from BD08 to BD09 on 20 May 2016. It also induced anticyclonic circulation pattern, inertial oscillations higher surface current magnitudes (1.8 m s-1)as were observed to be intensified at the buoy location measured by HF radar along the Odisha coast. A (BD11) with a periodicity of * 2.1 days, which nominal SST drop (* 0.6 °C) was observed along persisted for the whole cyclone period (Girishkumar Odisha and the head BoB. This less drop was due to et al. 2014). The slow and gradual movement of the higher translation speed, lower WSC (Fig. 12) and CS continued till 19 May 2016 from location F to G. fresh layers with lower salinity at the upper surface The higher wind speed-induced upwelling was (up to 50 m) as observed from Argo floats (Fig. 7k, l) observed from the second highest peak in WSC (Sengupta et al. 2008). It is interesting to note that (Fig. 12d), leading to an SST drop of * 0.6 °C also drop in the SST is higher along the left side of the S. Mandal et al. Pure Appl. Geophys. track both from satellite (Fig. 6a, 6b) and in situ process in the BoB. In addition, the met parameters (Fig. 6c) datasets. This is due to the cyclonic wind available from the offshore observations may be used pattern near the coast. Along the right hand side of to study the meteorological phenomenon. The satel- the cyclone track, the surface winds move toward the lite chlorophyll datasets are unavailable due to the coast and along the left side it moves away from the cloud coverage, so as a part of a future study bio- coast (Fig. 12c). Therefore, the subsurface water logical processes will be explored using various comes to the surface to give colder water at the in situ datasets such as bio-argos. In future, the surface. dynamics of the water flow would be studied to give more insights into the understanding of the ocean circulation pattern in the region using HF radars. 6. Conclusions

The present study demonstrates and points out the Acknowledgements importance of the moored OMNI buoys, the Argo floats and the HF radars to understand the variability The authors appreciatively acknowledge the financial of the oceanographic and meteorological responses, support given by the Earth System Science Organi- both at surface and subsurface levels during ROANU zation (ESSO)—Indian National Centre for Oceanic over the BoB. However, remote sensing datasets Information Services (INCOIS), Ministry of Earth along with the satellite observations have also been Sciences (MoES), and Science and Engineering used to make a distinction between the different Research Board (SERB) of the Department of stages of the cyclone and thereby understand the Science and Technology (DST), Government of oceanic conditions before, during and after its pas- India. Also, the authors acknowledge Dr. B. K. Jena sage. The highest drop of SST and air temperature and his Coastal and Environmental Engineering was felt along the right side of the track, which could Group and the Ocean Observation Systems Group, be attributed to high wind speed, the upwelling National Institute of Ocean Technology (NIOT), (positive WSC) and air–sea fluxes associated with the Chennai, for constant monitoring of the HF radars cyclone, in complete agreement with previous stud- and the moored OMNI buoys, and DMG, INCOIS ies. The net heat loss at the sea surface and cyclone- Hyderabad, India, for making the data availability induced subsurface upwelling, together with the efficient. The authors are thankful to the editor, mixing-facilitated entrainment of cold and high saline associate editor and anonymous reviewers for their waters from deep, contributed to the observed SST valuable comments and suggestions, which have cooling in the wake of the cyclone. On the contrary, helped to improve the quality of the manuscript. no such surface and subsurface variability of the Finally, the authors also acknowledge the Indian oceanic and atmospheric parameters was observed Institute of Technology Bhubaneswar (IITBBS) for along the Odisha coast, as the cyclone propagated the infrastructure. very rapidly due to the lack of vertical mixing. The

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(Received September 8, 2017, revised May 16, 2018, accepted June 20, 2018)