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Data Impacts and Lessons Learned from Ocean Observing Systems Worldwide

Volume 50 Number 3 May/June 2016

The International, Interdisciplinary Society Devoted to Ocean and Marine Engineering, Science, and Policy

JournalVolume 50

P A P E R

India’s Ocean Observation Network:Relevance to SocietyA U T H O R SRamasamy VenkatesanRanganathan SundarNarayanaswamy VedachalamKarakunnel Jossia JosephEarth System Science Organization,National Institute of OceanTechnology, Chennai, India

A B S T R A C TSustained and real-time ocean observation systems using moored data buoys

are vital for understanding ocean dynamics and the variability required for improv-ing oceanographic services, including weather prediction, ocean state forecast,and climate change studies. This paper presents the effectiveness of India’s mooreddata buoy network in capturing the response in the ocean during the cyclonic dis-turbances formed in the Bay of Bengal (BoB) and the Arabian Sea (AS) during thelast 5-year period. Themoored buoy network provided critical information about theevolution and intensification of low-pressure systems and supported the IndiaMeteorological Department to improve prediction capabilities by incorporatingreal-time data. The lowest mean sea-level pressure of 920 hPa was recorded in theBoB during the very severe cyclonic storm Phailin. The warning systems adopted forthe effective dissemination of the ocean forecast services to the user community havesignificantly reduced the loss of life and property in coastal states.Keywords: cyclones, data buoys, forecast, Indian Ocean, ocean observation

Introduction

South Asia has a long coastline ofover 12,000 km and a high populationdensity over long stretches of low-lyingareas. The maritime zone is dominatedby a range of economic activities in-cluding port operations, conventionalfishing, hydrocarbon exploration,transportation, marine research, anddefense activities. The subcontinenthas been perennially plundered bythe fury of tropical cyclones (TC; SouthAsian Disaster Knowledge Network,2009; Unnikrishnan et al., 2011).More than 95% of the major TC-baseddisasters experienced in the world havetaken place in South Asia, with thefrequency of intense cyclones on theuptrend (Landsea, 2000). Because ofthe unique geography, the incidenceof TC is higher in the Bay of Bengal(BoB) than in the Arabian Sea (AS;Obasi, 1997; Maneesha et al., 2012;SAARC, 2008). Cyclones that formin the south and central BoB initiallymove toward the northwest and north,and then they turn toward the north-east, commonly striking the Arakancoasts in April and the Andhra-Orissa-West Bengal coasts of India and thoseof Bangladesh in the month of May.

TCs also form in southeast and ad-joining central AS during the monthsof May, October, November, andDecember and in east central ASduring the month of June (Kumar& Ravichandran, 2012). Some of theTCs that originate in the BoB travelacross peninsular India weaken andmerge into the AS as low-pressure sys-tems. Although, it is not possible tocompletely avoid natural disasters,their effects can be minimized by tak-ing some long-term and short-termmitigation measures and improvedresponse mechanism (Schiller &Brassington, 2011). Continuous oceanobservation and timely disseminationof information to various end users isessential. The advancements in tech-nologies including the availabilityof real-time ocean observations, datasharing, understanding global phenom-ena, satellite imagery, and advancedmodeling techniques help to have bet-

ter prediction and forewarning, assist-ing policy makers to take preventivemeasures and administrators to safe-guard coastal lives (Venkatesan et al.,2013a). The establishment of mooredbuoy networks has vastly improvedIndia’s capability in observing theNorthern Indian Ocean (NIO), andthe observations have revealed signif-icant information such as reversingwinds/currents, warm pools in theSouth Eastern AS, and barrier layersin BoB (Kumar & Ravichandran,2012; Thusara & Vinayachandran,2014). The incorporation of mooredbuoy data has greatly enhanced thecapabilities including ocean state fore-cast, cyclone warning, monsoon stud-ies, climate research, validation ofmodel results and satellite observa-tions, port operations support, marinetraffic management and support forcoastal and offshore developmen-tal activities (Sabique et al., 2012;

34 Marine Technology Society Journal

Mujumdar et al., 2011; Vimala et al.,2014; Krishnan et al., 2015; Mohantyet al., 2012). The present study de-tails the observation networks in theIndian Ocean and the moored surfacebuoys (MSB) operated by the Na-tional Institute of Ocean Technology(NIOT), the oceanic responses cap-tured by the moored buoy networkduring various cyclonic events, andthe ocean forecast services and datadissemination to the user community.

Ocean Observationsand Indian OceanObservation Network

Ocean observation systems areclassified as remote and in situ types.Remote sensing systems such as satel-lites, aircraft, and radar capture spatialand temporal variations and providehorizontal distribution of surface vari-ables, such as temperature, sea surfaceheight, ocean color, as well as severalmeteorological parameters for the cal-culation of the air-sea momentum,heat and fresh water fluxes. In situmea-surements using sensors mounted onships, MSB, and coastal stations areclassified as Eulerian and Lagrangiantypes. Eulerian are fixed point obser-vations made either using MSB orfrom the repeated occupation of off-shore stations, while Lagrangian in-volve spatiotemporal measurementsusing mobile platforms. Successful insitu ocean observation systems requirereliable moorings, power systems, pre-cision sensors and best applicationpractices, and telemetry for near-real-time transmission of both observationsand relevant metadata. The IndianOcean observational network estab-lished by theMinistry of Earth Sciences(MoES) comprises an optimized suiteof Lagrangian and Eulerian observa-tion systems designed to take into

consideration the existing IndOOSobserving systems in the Indian Oceanestablished under the Global OceanObservation System (GOOS) ofUNESCO-IOC (Meyers & Boscolo,2006). The network is configured forreal-time and delayed-mode coastaland offshore observations facilitatingdata assimilation and real-time valida-tion of operational nowcast/forecastof ocean variables in and around theIndian Seas.

India’s ocean observation networkcomprises moored buoys, both off-shore and coastal Acoustic DopplerCurrent Profile moorings, deep oceanwave buoys, coastal wave rider buoys,equatorial current meter moorings,the Bay of Bengal Observatory, andtsunami buoys for deep-sea water levelmeasurements. Argo profiling floats,drifters, gliders, shipborne observationssuch as Expendable Bathythermographs/(XBT)/Expendable Conductivity/Temperature/Depth Profiling System(XCTD), automatic weather stations,wave measurements from ships, con-ductivity-temperature-depth (CTD)data, land-basedHF radars, and coastaltide gauges are used to support thesatellite observations (Ravichandran,2015). In addition, the network in-cludes the Research Moored Array forAfrican-Asian-Australian MonsoonAnalysis and Prediction mooring net-work, ship-based, autonomous instru-ments, and coastal current meter arrays(McPhaden et al., 1998). The spatio-temporal meteorological and oceano-graphic measurement capabilities ofthe systems are summarized in Table 1.Among these ocean observations, theimportance of moored buoy data forcyclone tracking is discussed in thispaper.

The Ocean Observation Systems(OOS) group of the NIOT has beenmaintaining moored buoy networks

in the BoB and the AS since 1997to provide continuous time-seriesmeasurements of meteorological andoceanographic parameters to under-stand the ocean dynamics and to refinethe measurement methods and tech-niques. Currently, the OOS mooredbuoy networks include coastal buoysand deep sea buoys called the OceanMoored Buoy Network in NorthernIndian Ocean (OMNI) (Venkatesanet al., 2013b). The moored buoy net-work operational during the periodfrom July 2010 to December 2015 isshown in Figure 1.

The OMNI MSBs measure 104parameters, including meteorological,sea surface and subsurface oceano-graphic parameters, which are mea-sured at up to 500-m water depthsin the Indian Seas. The maintenanceof the MSB is carried out every yearor whenever required by the NIOTteam along with an intercomparisonof the buoy subsurface conductivityand temperature data with the ship-borne CTD sampling using the Indianresearch vessels Sagar Nidhi, SagarKanya, and Sagar Manjusha. TheMSB-acquired parameters are trans-mitted in real time to the mission con-trol center (MCC) at NIOT usingINMARSAT/INSAT/GPRS communi-cation (Sundar et al., 2015; Venkatesanet al., 2015d). In order to ensure max-imum data availability based on theachieved reliability and the recordedmean time to repair, the MSBs areset to transmit the acquired data andsystem health status to NIOT-MCCevery 3 h. The reporting interval con-forms the system to IEC 61508 stan-dards. An in-house-developed softwaretool called Advanced Data Receptionand Analysis System (ADDRESS) isdeveloped for data monitoring, analysis,and management. The software com-plies with international data quality

May/June 2016 Volume 50 Number 3 35

control standards coupled with analy-sis and visualization facilities. Thehardware architecture of ADDRESSis configured to be at SIL4 level ofsafety reliability (Venkatesan et al.,2015a).

The reliability of the buoy positionmoorings and other electronic systemswas improved by adopting the bestpractices from IEC 61508 and DNV

POSMOOR standards (DNV, 2010;IEC 61508, 2000). MSB positionmoorings, which have cumulativelyclocked over 0.85 million harsh off-shore hours, are matured to have anMTBF of 12.2 years (Venkatesanet al., 2015b; Kaliyaperumal et al.,2015). TheMSB onboard energy stor-age system is optimized to have thebest tradeoff between reliability with

a Safety Integrity Level 4 (SIL4) andbattery cost, thus achieving an energycost of transmission of U.S.1.7 perdata set (Venkatesan et al., 2015c).The moored buoy instruments thathave cumulatively clocked more than7.3 million demanding offshore in-strument hours are maintained, basedon the four-slot annual maintenanceprogram, and as a result, the meteo-rological sensor achieved a data re-turn of 97.9% during the past 5 years(Venkatesan et al., 2016).

The data received from the MSBare sent from MCC to INCOIS inHyderabad after the data quality check.The buoy data are also made availablein the global telecommunication system(GTS) to facilitate global use throughthe World Meteorological Organiza-tion. MSB data are of immense use tothe Indian Metrological Department(IMD) for supporting the four-stagewarning system, including pre-cyclonewatch, cyclone alert, cyclone warning,and post-landfall outlook (IMD, 2013).The sea surface temperature (SST) isused for monsoon forecast by the

FIGURE 1

MSBs maintained by NIOT.

TABLE 1

Details of the measurement capabilities of IndOOS systems (McPhaden et al., 1998; Ravichandran, 2015).

Parameters/Systems Salinity

Sea SurfaceTemperature

Current Speedand Direction

AtmosphericTemperature

AtmosphericPressure

RelativeHumidity

Wind Speedand Direction Precipitation

Indian mooredbuoys

✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓

AUPD/ARGO ✓ ✓ NA NA NA NA NA NA

Drifter NA ✓ NA NA ✓ NA NA NA

Subsurfacemooring

NA NA ✓ NA NA NA NA NA

XBT/XCTD ✓ ✓ NA NA NA NA NA NA

Ship boardmeasurements

NA NA NA ✓ ✓ ✓ ✓ ✓

RAMA buoy ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓

SatelliteObservation

✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓


IMD, ocean state forecast by theINCOIS, and weather forecast viathe global data assimilation system.

Relevance to Society:Cyclones in NIO

The occurrence of TCs in the BoBand AS is in the ratio of ~ 4:1. An anal-ysis of the frequency of cyclones on theeast and west coasts of India between1891 and 1990 shows that nearly262 cyclones occurred (92 of these se-vere) in a 50-km-wide strip on the eastcoast of India. Less severe cyclonic ac-tivity has been noticed on the westcoast, where 33 cyclones occurred atthe same period, of which 19 were se-vere. On average about five to six TCs(maximum sustained wind > 34 knots)form in the BoB every year, of whichtwo to three reach the severe stage (max-imum sustained wind > 48 knots).Some of the disastrous TCs of the20th century include the Orissa Supercyclone (October 1999), Kandla cy-clone (1998), Porbandar cyclone(1976), and Bombay cyclone (1948).The False Point cyclone (Orissa) thatoccurred in 1885 was reported to beassociated with the highest stormsurge of 22 feet.

These TCs are associated withlow atmospheric pressure and strongwinds, which induce divergent cir-culation in the upper ocean (Kumaret al., 2014). The response to these ep-isodic events can be seen in the upper-most layer (200–300 m) of the ocean(Premkumar et al., 2000). The deep-ening of the mixed layer by tens ofmeters and cooling of SST by a fewdegrees are observed during cyclones;a severe cyclone can cause a decreaseof up to 5°C (Maneesha et al., 2012;Emanuel, 2003). Deep convectiveclouds formed over the oceans duringcyclones reduce the incident solar radi-

ation on the surface of the ocean. Thehigh winds produce large amounts ofair-sea energy exchange, which leadto the subsequent cooling of the seasurface (Price, 1981). The impact ofa cyclone in the ocean as well in theatmosphere is very rapid due to thepresence of strong winds. TCs charac-terized by destructive winds, torrentialrainfall, and storm surges disrupt nor-mal life by heavy floods, erode beachesand embankments, destroy vegetation,and reduce soil fertility.

The two seas around India, theBoB and AS, react differently to thefeedback cycles. The AS cools rapidly,and its SST cannot sustain convection.The cooling occurs because of theoverturning triggered by seasonal up-welling favorable winds along thecoast of Somalia and due to the me-ridional overturning. The BoB stayswarm enough to sustain an active con-vection. The north-south gradient inSST over the BoB is important in de-termining the intraseasonal oscillation.Figure 2 shows the TC tracking bythe NIOT operated MSB during the

period 2010–2015, with each measuredparameter contributing to the betterunderstanding of the upper oceanresponses and also improving themeasurement technology. The atmo-spheric and oceanic responses duringthe major TCs are detailed.

Jal Cyclone—November 2010The cyclone Jal developed as a low-

pressure system in the South ChinaSea, intensified into a depression,and entered the BoB after crossingthe Malay Peninsula on November 1(Kumar et al., 2014; Srinivas et al.,2013). The storm continued to grow,became a severe cyclonic storm, and at-tained cyclonic strength byNovember 7,2010. The system moved west-north-westward, weakened into a deep de-pression, and made landfall in northTamil Nadu. The surface meteorolog-ical and oceanographic parameters in-cluding wind speed, wind direction, airpressure, and inertial oscillations wererecorded by theMSB deployed at 18N/89E and in nearby locations in thenorthern BoB (Figure 3).

FIGURE 2

Major TCs tracked by NIOT MSB between 2010 and 2015. (Color version of figures are availableonline at: http://www.ingentaconnect.com/content/mts/mtsj/2016/00000050/00000003.)


During the passage of the Jal, thewind speed reached a maximum of14 m/s, air pressure dropped to a min-imum value of 997.2 mb at 09 UTCon November 5, and the averageair temperature reduced by 1°C andreached 27°C. The sudden reductionin air temperature was due to the in-tense local rains during the cyclonepassage. After the passage of the Jal,the wind direction changed from south-westerly to northeasterly, and sub-sequently, the north-east monsoonconditions prevailed in this region.The severity of the TC was also under-stood from the inertial oscillations ob-served at the buoy site for a period of4 weeks starting from November 5,2010 (Kaliyaperumal et al., 2015).

Lehar Cyclone—November 2013The Lehar cyclone initially formed

as a tropical depression in the SouthChina Sea on November 18, 2013,moved northeastward, and intensifiedas a very severe cyclonic storm on No-vember 26, 2013 near southeast BoB.It rapidly weakened into a deep depres-sion and crossed the Andhra Pradeshcoast close to south of Machilipatnamon November 28, 2013 (IMD-Lehar,2013). Figure 4 shows the meteo-

rological and oceanographic responsesduring the period. TheOMNIbuoy lo-cated at 10.5N/94E, near the AndamanSea, recorded a minimum atmosphericpressure of 999 hPa and a temperaturedrop of 2.6°C. Another MSB locatedin the Andaman Sea also recorded aminimum pressure of 993 hPa. AsLeharmoved in theNortheast direction,it passed near the three other MSBslocated at 14N/87E, 16.5N/88E, and13.5N/84E in the central and north-east, with the MSB at 14N/87E only19 nm away from the cyclone track re-cording a maximum wind speed of

18.6 m/s. During the period, the low-est pressures recorded by these MSBswere 994.2, 1005.7, and 1004.7 hPa,respectively. Due to the massive cloudcoverage, the solar irradiancemeasuredby the MSB at locations 14N/87E and16.5N/88E also reduced to half thepeak time irradiance. As Lehar was as-sociated with heavy rainfall, the precip-itation sensor in the buoy at location10.5N/94E measured a maximumrainfall of 139 mm/day, which was arecord rainfall at a particular locationassociated with a cyclone evermeasuredin the BoB (Krishnan et al., 2015). Theincreased wind speed is normally re-flected by an increase in the significantwave height (Price, 1981). The wavemeasurements are done only at certainlocations, and the maximum signifi-cant wave height measured during theLehar cyclone was 4.6 m.

The MSB located at 11.5/92.5Erecorded a decrease in SST by 1.5°C,which was due to the huge air-sea heatflux exchange and rainfall during theLehar TC. The surface salinity de-creased by 1 PSU associated withthe heavy rainfall, and the subsurfacesalinity measurements at 10 m depthshowed an increase of 0.7 PSU due

FIGURE 3

Responses observed by MSB during cyclone Jal.

FIGURE 4

Responses observed by MSB during the Lehar cyclone.


to the upwelling of high subsurfacesaline waters during the TC. The cur-rent speed recorded by the buoys at14N/87E and 10.5N/94E (within25 nm from the cyclone track) crossed60 cm/s during the passage.

Madi Cyclone—December 2013Madi cyclone originated as a

well-marked low-pressure area oversouthwest BoB and emerged as a de-pression on December 6. It intensifiedinto a severe cyclonic storm, “Madi,”on December 7 and further intensifiedinto a very severe cyclonic stormon December 8. It weakened intocyclonic storm and then into deep de-pression on December 11. It crossedTamil Nadu coast on December 12and then emerged into south east Ara-bian Sea as a well-marked low-pressurearea on October 13 (IMD-Madi,2013).

During the Madi TC, the MSBlocated at 13.5N/84E (8 nm awayfrom the track of the TC) recordedthe lowest atmospheric pressure of991.8 hPa and a maximum windspeed of 25.7 m/s. The responsesduring the period are shown in Fig-ure 5. A rainfall of 60 mm/day and

a decrease in the atmospheric tem-perature by 1°C was measured at anMSB located at 14N/87E, 130 nmaway from the cyclone track. Theirradiance measured by both the MSBreduced by about 10% of the peaktime measured irradiance during thecyclone period.

During the period, the maximumsignificant wave height measured bythe buoy was 7.7 m. The MSBs wereequipped with a downward lookingAcoustic Doppler Current Profiler op-erating at 150 kHz frequency suitablefor measuring the surface water cur-rent speeds. The MSBs at 14N/87Eand 7N/88E locations recorded themaximum surface current speeds of62.5 and 70.3 cm/s, respectively. Thecurrent speed at 10-m depth measuredby the MSB located at 13.5N/84Ecrossed 100 cm/s.

Phailin Cyclone—October 2013A low-pressure area developed into

a depression over north Andaman Seaon October 8 and intensified into acyclonic storm, “Phailin,” over eastcentral BoB on October 9, 2013. Itfurther intensified into a very severecyclonic storm over northwest BoB

on October 12, 2013 and crossed thecoast near Gopalpur (Odisha) onthe same day (IMD-Phailin, 2013).The Phailin TC, declared at Category 4level, was the most furious in thepast 14 years that hit Gopalpur in thestate of Odisha on October 12 withwind speeds reaching a maximumof 215 km/h and a significant waveheight of 7.5 m (Venkatesan et al.,2014; IMD-Phailin, 2013). Aided bythe data from six MSBs, the IMD pre-dicted the track and intensity of thecyclone with wind speed of up to220 km/h and a significant waveheight of 10 feet. The accurate cyclonepredictionmade by the IMDhelped insaving many lives. The emergency re-lief measures taken up by the OdishaState Disaster Management Authority,through the relocation of as many as0.9 million people living in the lowlying coastal belt of Odisha, savedmany lives compared to the recordeddeath toll of 10,000 during the 1999super cyclone. This has clearly provedthe importance of the network ofMSBsin the open ocean, which transmittedthe surface meteorological and oceano-graphic conditions in real time, havinghelped various organizations to ingestthese data into the operational models,leading to effective forecasting (Johnet al., 2015).

Six MSBs in the BoB that werewithin a radius of 4–160 nm fromthe cyclone track could reliably with-stand the harsh cyclonic conditionsand constantly monitored the cyclonethroughout its journey from evolutiontill landfall. Initially, two MSBs lo-cated at 11.5N/92.5E and 10.5N/94Ein the Andaman Sea showed the re-sponse of the cyclonic depression by adrop in the atmospheric pressure andincreased wind speed, and the MSBlocated at 14N/87E was the first toshow the response of the cyclone as

FIGURE 5

Responses observed by the MSB during cyclone Madi (IMD-Madi, 2013).


soon as it entered the BoB. The mete-orological and oceanographic param-eters recorded are shown in Figures 6and 8, respectively.

The earlier records of mean sealevel pressure during cyclone passagenever recoded lower than 990 hPa,but during the passage of the Phailincyc lone , the MSB deployed in16.5N/88E recorded the minimumpressure of 920.6 hPa (a reduction of83.7 hPa within a day), which wasthe lowest ever recorded pressure byany instrument during a cyclone inthe NIO. The MSB instruments thatrecorded a wind gust of 35 m/s alsorecorded a decrease in wind speed of13 m/s from a maximum recordedvalue of 22.7–9.8 m/s, which gave anindication of the MSB’s proximity tothe eye of the cyclone. The MSBs atlocations 18N/89E, 16.5N/88E, and14N/87E recorded the maximumrainfall on October 11 of 36.6, 71,and 43.4 mm/day, respectively. Thelowering of short wavelength solar irra-diance on the 12th due to the massivecloud cover during the cyclone periodwas observed from theMSB in locationsat 16.5N/88E, 18N/89E, 18N/90E,and 14N/87E, recording 96.6 (noon

time), 417.5, 284.2, and 61.6 W/m2,respectively.

The effect of the Phailin cycloneon the SST (dropped by 0.7°C) andthe diurnal variability in SST wasmore pronounced during the post-cyclone period, obtained from buoysat 16.5N/88E location as shown inFigure 7. The conductivity-temperature(CT) sensor attached at 10 m depthrecorded a drop of 1°C within 3 daysand the salinity at 10 m depth was in-creased by 2 PSU at the same location.

During the cyclone period, theMSBs at 10.5N/94E, 16.5N/88E,

and 18N/89E recorded the maximumcurrent speeds of 74.2, 138.67, and60.55 cm/s, respectively, on October10. The inertial oscillation is expectedto have a periodicity of 1.618 days at18°N and the position vector plottedbased on the surface current data ob-tained from the MSB revealed the in-ertial oscillation excited on the surfaceof the ocean due to the cyclone.

Cyclonic wind forcing induceshigh waves in the ocean. The increasein wave height is reflected very well intheMSB observations, with a recordedmaximum significant wave height of6.27 m as observed by the MSB at8N/89E location, which was 140 nmaway from the cyclone track. A waverider buoy located near Gopalpur at19N/85E recorded a maximum waveheight of 7.5 m on October 12, 2013,when the cyclone made landfall.

Hud-Hud Cyclone—October 2014A depression formed over north

Andaman near latitude 12.3N/92.9Eon October 7, 2014 intensified intothe Hud-Hud cyclonic storm onOctober 8 and moved in the west-northwestward direction (IMD-Hudhud, 2014). The system crossednorth coastal Andhra Pradesh and the

FIGURE 6

Meteorological responses observed during the cyclone Phailin.

FIGURE 7

Temperature and salinity profile during the Phailin cyclone.


southOdisha coast near Visakhapatnamaround noon of October 12, 2014.

The observations from the OMNIMSB (Figure 8) located in the BoB atBD12, CB01, and BD13 locations inthe proximity of the cyclone trackshowed its severity. The buoys BD11and BD10 were within the cyclonicradius of influence, and the signatureof the cyclone passage was capturedby these buoys too. The buoys BD08,BD09, and BD14 were away from thecyclone track, with very little responsein the met and ocean parameters.

During the cyclone passage, the val-ues of minimum air pressure recordedwere 994.6 hPa and 996.58 hPaat BD13 and BD10, respectively,on October 10, 2014. The severity ofthe cyclone is reflected in the highwind speeds of 21.3 m/s at BD13 and16.13 m/s at BD10 on the same day.The maximum surface current speedobserved is 143 cm/s at BD13 followedby 94 cm/s at BD11 during the cyclonepassage. The maximum wave height of4.86 m at BD11 on October 12 and4.27m at BD08 onOctober 11 also in-dicates the wide spread oceanic responseassociated with cyclone passage. Thetemperature and the salinity recordedby MSB BD11 are shown in Figure 9.

Nanauk Cyclone—June 2014The TCNANAUK initially formed

in the Central AS on June 10, 2014.It moved north-northwestward andintensified into a cyclonic storm onJune 11, 2014. The Nanauk cycloneweakened into a deep depression inthe afternoon of June 13 over west cen-tral AS and into a depression in the eve-ning and further into a well-markedlow-pressure area over the same regionon June 14 (IMD-Nanuk , 2014). This

TC was formed in the month of June,and it caused a temporary hiatus in theprogress of the monsoon over southIndia. MSBs AD06, AD07, and AD08captured the responses during the cy-clone passage. During the period, theminimum air pressures measuredwere 983, 993, and 997 hPa at AD07,AD06, and AD08, respectively (Fig-ure 10). The wind speedmeasurementsfrom the MSB show the highest valueof 21m/s at AD07 on June 10 followedby 12.6 m/s on June 11 at AD06.

The drop in the SST of 2.4°C atAD07 and 2°C at AD08 shows the in-tense oceanic response. At AD06 loca-tion, the pre-cyclone mixed layer depth(MLD) was very shallow (~12 m) andMLD was restricted by salinity stratifi-cation in the near surface layer. Afterthe cyclone, stratification completelydisappeared and MLD deepened upto 35 m.

Ocean State ForecastPrior information on the state

of the seas surrounding the Indian

FIGURE 8

Responses observed by MSB during the Hud-Hud cyclone.

FIGURE 9

Temperature and salinity profile during Hud-Hud cyclone.


subcontinent is vital for smooth oper-ational activities, not only for thosewho are venturing out into the sea butalso for those on the seashore. Theusers can make informed decisions tosave life and property based on thesea state forecast. Thus, there is an in-herent economic benefit to the usersof ocean state forecast information.For the efficient operation at commer-cial and fishing ports, information onsea state parameters in the vicinity,like locally generated wind waves, re-motely generated swell waves, currents,winds, and tides, is critical. Anotherapplication of sea state forecast infor-mation is recreational tourism at theseaside, including the operations of seaplanes, recently introduced at some lo-cations along the Indian coastline. Fur-thermore, this information is importantduring contingencies like search andrescue operations in the sea and duringoil spills. During cyclones and other ex-treme situations, based on the forecastinformation, alerts are issued to thegeneral public as well as the adminis-trators of the coastal stretch under riskso that the population under threat isrelocated to safer places.

Forecasting of oceanographic pa-rameters (both surface and subsurface)

at different time scales is thus extremelyimportant for a wide spectrum of usersranging from fishermen to offshore in-dustries. The Earth System ScienceOrganization-Indian National Centrefor Ocean Information Services (ESSO-INCOIS) has therefore established theintegrated Indian Ocean ForecastingSystem (INDOFOS), capable of predict-ing the surface and subsurface featuresof the Indian Ocean reasonably well inadvance (Sandra et al., 2012). At pres-ent, ESSO-INCOIS provides forecastson the height, direction, and period (ofboth wind waves and swell waves); seasurface currents; SST; MLD; depth ofthe 20 degree isotherm (a measure ofthe depth of the thermocline); astro-nomical tides; wind speed and direc-tion; and oil spill trajectory (Incois,2013). Ocean state information is pro-vided to all the seafaring communitieslike fishermen, the Indian Navy, Indi-an Coast Guard, merchant and passen-ger shipping agencies, offshore oil andgas exploration agencies, and researchorganizations. In addition, all coastalcommunities are also informed. Theforecast is divided for the regions in-cluding the AS, BoB, NIO, SouthernIndian Ocean, Red Sea, Persian Gulf,and South China Sea. Furthermore, it

provides detailed forecast informa-tion for specific locations like fishlanding centers, small fishing harbors,commercial ports, etc., as well as forthe coastal waters of the maritime states,union territories, and island regionsof India.

The forecasts are generated by a suiteof state-of-the-art numerical models,which are customized to simulate andpredict the features accurately. Themodels used include WAVEWATCHIII, MIKE21, Regional Ocean Model-ing System (ROMS), and GeneralNOAA Oil Modeling Environment(GNOME). Atmospheric forecastproducts from differentmeteorologicalforecasting agencies (NCMRWF andECMWF) are used for forcing thesemodels in the forecast mode. Globalforecast and deep sea forecasts differmainly in the spatial and temporalresolution of the forecasts, extent ofvalidations carried out, etc. In coastalforecasts, the models are set up usingthe concept of a “multiple grid” withcoarse resolution in the open ocean re-gion and very fine resolution for thespecified coast, providing more accu-rate data at the coast. These forecastsare generated operationally using thelatest information and computationaltechnology tools and run on high per-formance computers (Nair et al, 2013).

For validating the accuracy and re-liability of the model products, in situand satellite measurements (near shorewave rider buoys, deep sea buoys, ship-borne wave height meters, and otherdeep sea met-ocean buoys as well asAutomatic Weather Stations) are used.Validation is done routinely for thedifferent seasons, as well as duringextreme cyclonic conditions. Near-real-time validation is carried out forsite-specific forecasts as well as thosebased on satellite passes over the IndianOcean region. All the services to the

FIGURE 10

Responses observed by MSB during the Nanauk cyclone.


public are released after thorough in-house validation of the data by ESSO-INCOIS, using thesemeasuring systems,along with other remotely sensed satel-lite data. To further enhance the qualityof this forecasting system, ESSO-INCOIS plans to expand the waverider buoy network ensuring that aminimum of two wave rider buoysare deployed along each Indian coastalstate (including the island territories).It also proposes to increase the deploy-ments of ship-mounted AutomaticWeather Stations (AWS) to 100 innumber, so that the data will be assim-ilated in real time in the numericalmodels.

DisseminationEven though the primary dissemi-

nation mode is the ESSO-INCOISwebsite, it also provides these servicesthrough other modes like e-mail,mobile phones, television, radio, andelectronic display boards to all thestakeholders (Incois, 2013). The infor-mation and communication technol-ogy tools have been maximized forproviding in-time quality forecaststo users. Furthermore, there is strongcollaboration with non-governmentalorganizations, coastal research centers,and universities for further dissemina-tion. In areas without electricity supplyor with serious power outages, the dis-semination is done through manualdisplay boards (e.g., Sundarbans re-gion) and black boards at other fishlanding centers.

New customized products havebeen developed for special applicationslike forecast along the ship tracks,Webmap services and forecast for ports andharbors. The high wave alert serviceis another important and popular ser-vice of ESSO-INCOIS issued duringcyclones and other extreme events.Figure 11 shows the INCOIS-Ocean

State Forecast page Web statistics dur-ing the Phailin cyclone landfall overGopalpur in Orissa during the periodOctober 7–14, 2013.

The feedback of users (includ-ing fishing and coastal populations,maritime boards, Indian Navy, IndianCoast Guard, shipping sector, energysector, offshore exploration industries,port authorities, pollution control boards,disaster management agencies, and otherresearch organizations) are collectedroutinely through mail, telephone, anduser interaction meetings at coastal lo-cations as well as at ESSO-INCOISto improve the dissemination system.

Fishermen Awareness MeetingsSystematic interactions are orga-

nized to bring awareness among thefishermen by organizing workshops

in minor ports and fish landing centers(Figure 12). During the last 4 years,more than 60 workshops were orga-nized. As there is intense fishing activ-ity by fishermen from neighboringcountries, in order to bring awareness,regional workshops were organizedin association with UNESCO-IOC,Data Buoy Cooperation Panel, andintergovernmental organizations suchas the Bay of Bengal Large MarineEcosystem (BOBLME) and Bay ofBengal Programme (BOBP) (SAARC,2008; NDMA, 2008; Potential Fish-ing Zone (PFZ) advisory; New IndianExpress, 2015; BOBLME, 2015). TheNational Cyclone Risk MitigationProject (NCRMP) is a pioneer projectdrawn up by the Ministry of HomeAffairs (MHA), Government of India,with the purpose of creating a suitable

FIGURE 11

Web statistics of INCOIS during the Phailin cyclone landfall (Incois, 2013).

FIGURE 12

Fisherman awareness meet conducted during February 2015.


infrastructure to mitigate the effects ofcyclones in the coastal states of Indiain a sustainable way. The project wastransferred to the National DisasterManagement Authority (NDMA) inSeptember 2006. The project hasidentified 13 cyclone prone states andUnion Territories, with varying levelsof vulnerability. These states/UTs havefurther been classified based on the fre-quency of the occurrence of cyclones,size of the population, and the existinginstitutional mechanism for disastermanagement.

ConclusionThis paper has presented the im-

portance of sustained and real-timeocean observation systems for theIndian Ocean. The effectiveness ofIndia’s moored data buoy networkin capturing the meteorological andoceanographic parameters and its im-mense use in tracking cyclones aredetailed. The capability of the networkand its usefulness to society was provedspecifically during the Phailin cyclone,when the cyclone was tracked fromits evolution until landfall. The im-portance of capturing the atmosphericand oceanographic responses duringcritical events and its use in effectivemodeling so as to ensure reliable andtimely advisories to the user commu-nity have been established. Further-more, the successful maintenance ofbuoy network for nearly two decadeshas engendered the confidence to de-velop and deploy customized mooredbuoy capable of measuring circulationand water masses in the Arctic region.

AcknowledgmentsWe thank the Ministry of Earth

Sciences, Government of India, forfunding this project and the members

of the National Expert Committee forevolving this program. We are gratefulto theDirector of INCOIS,Hyderabad,for providing all the facilities and logisticsupport. We deeply thank the Director,NIOT, for his constant support andguidance. We also thank the staff ofthe Ocean Observation Systems (OOS)group, Vessel Management Cell ofthe NIOT, and ship staff for their ex-cellent help and support onboard.

Corresponding Author:N. VedachalamEarth System Science Organization,National Institute of OceanTechnology, Chennai, IndiaEmail: [email protected]

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