NUMERICAL SIMULATION OF NORTH INDIAN OCEAN

FEATURES USING ROMS WITH AN EMPHASIS ON THE

BAY OF BENGAL

SANDEEP K K

CENTRE FOR ATMOSPHERIC SCIENCES

INDIAN INSTITUTE OF TECHNOLOGY DELHI

APRIL 2019

© Indian Institute of Technology Delhi (IITD), New Delhi, 2019

NUMERICAL SIMULATION OF NORTH INDIAN OCEAN

FEATURES USING ROMS WITH AN EMPHASIS ON THE

BAY OF BENGAL

by

SANDEEP K K

Centre for Atmospheric Sciences

Submitted

in fulfilment of the requirements of the degree of

DOCTOR OF PHILOSOPHY

to the

INDIAN INSTITUTE OF TECHNOLOGY DELHI

APRIL 2019

Dedicated to my Parents

Certificate

This is to certify that the thesis entitled "Numerical simulation of north Indian

Ocean features using ROMS with an emphasis on the Bay of Bengal" being

submitted by Mr. Sandeep K K to the Indian Institute of Technology Delhi for

the award of the degree of DOCTOR OF PHILOSOPHY is a record of original

bonafide research carried out by him. Mr. Sandeep K K has worked under our

guidance and supervision and has fulfilled the requirements for the submission of

this thesis. The results contained in this thesis have not been submitted in part or

full to any other University or Institute for the award of any degree or diploma.

(Prof. Vimlesh Pant) (Prof. A D Rao)

Associate Professor, Professor,

Centre for Atmospheric Sciences Centre for Atmospheric Sciences

Indian Institute of Technology Delhi Indian Institute of Technology Delhi

New Delhi-110016, INDIA New Delhi-110016, INDIA

Acknowledgements

I would like to express my deepest gratitude and sincere thanks to my supervisor

Prof. Vimlesh Pant for his proficient guidance, suggestions, encouragement and

constant support throughout the tenure of PhD. He inspired me with his

innovative thinking, dedication and progressive outlook towards science. His

patience and encouragement helped me to overcome many difficulties and achieve

my best. Without his support I would not have reached this point now.

I am greatly indebted to my co-supervisor Prof. A D Rao for his invaluable

scientific insights and advices during my research work. As a great teacher and

mentor he has taught me to think better and write more carefully and clearly. I

consider myself very fortunate for being able to work with a very considerate

and encouraging professor like him.

My sincere thanks to Prof. Manju Mohan, Head, Centre for Atmospheric Sciences

and all the faculty members of the Centre for their support throughout the course

of the research.

My sincere and heartfelt thanks to Dr. M.S. Girishkumar for his support and

encouragement from the very beginning of my research career. I am grateful to Dr.

P.A. Francis for his timely scientific advices and support.

I would like to thank Indian Institute of Technology Delhi for the fellowship

support, infrastructure, and HPC facility as the computational resource.

I feel very fortunate to have been part of the Ocean Computing Laboratory, CAS

and would like to thank all my fellow colleagues and friends for their support and

kind help to carry out my research work.

I am deeply indebted to my parents, wife and all our family members for their

never ending support and esteem. Above all I am thankful to Almighty God for

his Eternal Blessings and Benevolence.

Sandeep K K

New Delhi

i

Abstract

The unique geographical and meteorological characteristics of the Indian Ocean (IO) cause

and enforce variability in its upper oceanic physical processes with a vast range of temporal and

spatial scales. In recent decades, the IO has been identified to have substantial impact on the

regional and global climate variability. Thus, a better understanding of the processes in the IO

through observational and modeling studies has become an important scientific and societal

necessity. In the present thesis, the dynamic and thermodynamic variability of the northern IO,

particularly in the Bay of Bengal (BoB) at different timescales are studied using a high resolution

3D Regional Ocean Modeling System (ROMS). The ROMS model is configured over the tropical

IO extending from 30°E to 120°E and 30°S to 30°N with an eddy permitting grid resolution of

1/8° × 1/8° in horizontal and 40 terrain following sigma levels in the vertical. The daily mean

values of atmospheric variables obtained from the TropFlux and QuikSCAT/ASCAT data are used

for the computation of surface heat and momentum fluxes as surface forcing fields. The K-Profile

Parameterization (KPP) mixing scheme formulation is used for the vertical turbulent mixing.

A brief review of the important pioneer works on IO dynamics and its variability with

special reference to the BoB has been discussed in Chapter 1. Chapter 2 describes the model

formulation and its validation, methodology followed in the study and details of the various data

sets used. In Chapter 3, the impact of continental (riverine) freshwater discharge on the sea surface

salinity (SSS) simulations over the IO is examined. The daily climatological atmospheric forcing

and monthly river discharges are used to force the model. All the rivers draining into the IO from

the Indian subcontinent, Africa, Australia, and Indonesia are incorporated in the model. Two

numerical experiments are carried out with different freshwater forcing to identify the impact of

river discharges on the salinity variability. The first one, i.e., No-River Experiment (NR-Expt),

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treats the evaporation (E) and precipitation (P) as the surface freshwater flux (E-P). The riverine

freshwater discharge (R) is added to the surface freshwater flux in the second experiment, i.e.

River Experiment (R-Expt). The model simulated SSS in the R-Expt shows a better agreement

with the observed SSS from Aquarius satellite and buoys, as compared to the NR-Expt. The mixed

layer salt budget analysis highlights the dominant contributions from (E-P) and horizontal

advection terms in controlling the mixed layer salinity (MLS) over most of the IO domain.

Seasonal variability in the salinity and salt budget terms over the ten hydrologically different

regions in the northern and southern tropical IO are analyzed. The northern BoB (N-BoB) is found

to have the highest impact of river discharges on the SSS and MLS simulations during the

southwest monsoon (June-September) season. The salinity is reduced by ~4 psu with salinity

tendency up to -0.05 psu day-1 in the N-BoB, when river discharges are incorporated in the model.

The effect of river discharge on the MLS in the southeastern AS appears in the late winter and pre-

monsoon seasons. The eastern equatorial IO (EEIO) acts as a source of low-saline waters in the

IO.

In Chapter 4, the interannual simulations performed for years 2000-2014, are analyzed after

a validation against available buoy measurements and satellite data over the IO. Model simulated

daily fields are evaluated extensively by using multiple statistical metrics. The model simulated

sea surface temperature (SST) at different moored buoy locations exhibits high correlation

coefficient (R~0.9) with the ranges of standard deviation of simulated SST consistent with the

corresponding buoy observations. Intraseasonal and interannual variability of depth of 20oC

isotherm are simulated reasonably well as observed at the respective buoy locations. The Dipole

Mode Index derived from the simulated SST reproduces the positive/negative Indian Ocean Dipole

(IOD) events that occurred during the simulation period. Interannual variability in temperature,

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currents, and oceanic mixed layer depth is analyzed in response to IOD events. The anomalies in

equatorial currents are found to affect the strength of coastal currents along the Indian coastlines.

Model simulations show that the enhanced (suppressed) coastal upwelling process along the

Sumatra coast that leads to anomalous cooling (warming) off the Sumatra coast during the positive

(negative) IOD events. The composite analysis reveals that the surface meridional salt transports

along the east coast of India and EEIO region are characterized by the reverse salt transports in

response to the positive IOD and negative IOD events. During August-September months of the

positive IOD events, the meridional salt transport is northward in the southwestern boundary of

the BoB, which can be attributed to the northward current anomalies along the east coast of India.

Within the IO, the BoB shows distinct features in the sea surface salinity and surface

currents. The large amount of freshwater added to the BoB through surplus precipitation over

evaporation and river runoff makes it the lowest saline region in the IO. In Chapter 5, the role of

winds in determining the dispersal pattern of the freshwater plumes in the BoB is investigated

using a high-resolution regional ocean model with the realistic coastline, bathymetry, and river

discharge data. Multiple experiments are carried out with the idealized winds having different

directions and speeds, which represent the seasonal wind patterns in the BoB. The plume is

channelized along the coast in the cases of southeasterly and northeasterly winds but is forced

towards the central BoB under the southwesterly winds. Riverine plumes tend to confine in the

northern and northeastern BoB when forced with moderate winds. The spatial coverage of low-

saline waters is observed over most of the domain or in the eastern BoB under low-wind or

moderate wind conditions. The high-wind condition in the bay confines the freshwater mostly in

the northernmost part of the BoB. It is found that an increase in wind speed from 2 to 8 ms-1 results

in the enhanced southward meridional salt transport from 2 to 10 kg m-2 s-1 along 16oN latitude in

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the eastern BoB. Thus, the distinct roles of wind speed and direction on the characteristics of the

freshwater plume in the BoB are evident from the idealized numerical experiments.

The general conclusions from the study and future scope of the work is given in Chapter

6. After a successful validation, ROMS model was used to assess the impact of riverine freshwater

on the SSS simulations in the IO. The northeastern IO shows larger influence of river discharge

on salinity as compared to the western IO. In the southern tropical IO, the effect of river discharge

on mixed layer salinity variability found to be minimum among the different sectors of IO. The

composite analysis is carried out for the IOD events from the interannual simulation for the period

of 2000-2014. It was found from the analysis that the depth of 20oC isotherm shoals from 100-110

m in nIOD to 70-80 m in pIOD during October in the EEIO. The westward salt transport is

enhanced (suppressed) during pIOD (nIOD) events in the eastern equatorial IO. A set of model

sensitivity experiments highlight the crucial role of wind speed and direction in modulating the

freshwater plume pathways and the salt transport in the BoB.

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सारााश

ह िद म ासागर (IO) की अहितीय भौगोहिक और मौसम सिबिधी हिशषताएि इसकी ऊपरी म ासागरीय भौहतक

परहियाओि म पररिततनशीिता को वयापक सामहयक और सथाहनक पमान म उतपनन एिि हनधातररत करती । ाि क

दशकोि म, IO को कषतरीय और िहिक जििाय पररिततनशीिता पर पयातपत परभाि डािन क हिए प चाना गया । इस

परकार, अििोकन और मॉडहििग अधययन क माधयम स IO म परहियाओि की ब तर समझ एक म तवपरत िजञाहनक

और सामाहजक आिशयकता बन गई । िततमान थीहसस म उततरी IO क गहतशीि और तापगहतशीि (थमोडायनाहमक)

पररिततनशीिता, हिशष रप स बिगाि की खाडी (BoB) म, अिग-अिग समय पर एक उचच ररजॉलयशन 3-डायमनशन

‘रीजनि ओशन मॉडहििग हससटम’ (ROMS) का उपयोग करक अधययन हकया गया । ROMS मॉडि को

उषणकहिबिधीय IO पर 30 °E स 120°E और 30°S स 30°N तक 1/8° × 1/8° कषहतज और 40 भभाग का अनसरर

करन िाि ऊरधातधर सतरोि क एडडी-अनमहत हिड ररजॉलयशन क साथ कॉननिगर हकया गया । िर ॉपफलकस और

निकसकि / एएससीएिी आिकडोि (डिा) स परापत िायमिडिीय पराचिोि क दहनक औसत मलयोि का उपयोग सत ी ऊषमा

और सििग परिा (फलकस) की गरना कर सत पर फोहसिग क रप म हकया । K- परोफाइि परामीिराइजशन (KPP)

हमनकसिग सकीम सतर का परयोग ऊरधातधर िबतिि हमनकसिग क हिए हकया गया ।

IO की गहतशीिता और इसकी पररिततनशीिता पर म तवपरत अिरी कायो की सिहकषपत समीकषा, BoB क

हिशष सिदभत क साथ, अधयाय 1 म की गई । अधयाय 2 म मॉडि तयार करन और इसकी मानयता, अधययन म परयकत

कायतपररािी, और हिहभनन आिकडोि का िरतन हकया गया । अधयाय 3 म, समदरी सत की ििरता (SSS) पर कॉनिनिि

(ररिररन) ताज पानी (फरशिािर) क हनित न क परभाि की जािच की गई । मॉडि को िोसत करन क हिए दहनक

जििाय िायमिडिीय फोहसिग और माहसक नदी हनित न (ररिर हडसचाजत) आिकडोि का उपयोग हकया गया । भारतीय

उपम ािीप, अफरीका, ऑसटर हिया और इिडोनहशया स IO म ब न िािी सभी नहदयाा मॉडि म शाहमि की गई ।

ििरता पररिततनशीिता पर नदी हनित न क परभाि की प चान करन क हिए अिग-अिग फरशिािर फोहसिग क साथ

दो सिखयातमक परयोग हकए गए । प िा िािा, यानी, नो-ररिर एकसपररमि (NR-Expt), िाषपीकरर (ई) और िषात (पी)

को सत क ताज पानी क परिा (ई-पी) क रप म मानता । नदी क ताज पानी का हनित न (R) दसर परयोग अथातत

vi

नदी परयोग (R-Expt) म सत क ताज पानी क परिा म जोडा गया । R-Expt म SSS का मॉडि हसमिशन NR-

Expt की तिना म ऐिाररस उपि और पलाि (बॉय) स माप गए SSS क साथ एक ब तर तािमि दशातता । हमहित

परत ििर बजि हिशलषर IO डोमन क अहधकािश भाग पर हमहित परत ििरता (MLS) को हनयिहतरत करन म (ई-

पी) और कषहतज अिसारर स परमख योगदान पर परकाश डािता । उततरी और दहकषरी उषणकहिबिधीय IO म दस

ाइडर ोिॉहजकि रप स हिहभनन कषतरोि म ििरता और ििर बजि क भागोि म मौसमी पररिततनशीिता का हिशलषर

हकया गया । उततरी BoB (N-BoB) म दहकषर-पहिम मानसन (जन-हसतिबर) क मौसम क दौरान SSS और MLS

हसमिशन पर नदी क हनित न का सबस अहधक परभाि पाया जाता । जब नदी क हनित न को मॉडि म शाहमि हकया

जाता तो N-BoB म ििरता ~4 psu और ििरता की परिहतत -0.05 psu हदन -1 तक कम ो जाती । दहकषरपिी

अरब सागर (AS) म MLS पर नदी क हनित न का परभाि सहदतयोि क अित और परी-मॉनसन सीजन म हदखाई दता ।

पिी हिषित IO (EEIO) कम खार पानी क सरोत क रप म कायत करता ।

अधयाय 4 म िषत 2000-2014 क हिए हकए गए इििरएनअि हसमिशन का हिशलषर, IO क ऊपर उपिबध

पलाि (बॉय) माप और उपि डिा क साथ सतयापन क बाद हकया गया । कई सािनखयकीय महिरकस का उपयोग करक

मॉडि हसमििड दहनक पराचिोि का बड पमान पर मलयािकन हकया । मॉडि हसमििड समदर की सत का तापमान

(SST) हिहभनन जग ोि पर सथाहपत पलाि िारा माप गए SST क साथ उचच स सिबिध गरािक (R ~ 0.9) परदहशतत करता

और हसमििड SST क मानक हिचिन की सीमाएि सिबिहधत पलाि परकषरोि क अनरप । 20oC समताप रखा की ग राई

की इििर ासीजनि और इििरएनअि पररिततनशीिता सिबिहधत पलाि सथानोि पर परकषरोि क अनरप यथोहचत रप स

हसमििड । हसमििड SST स परापत डाईपोि मोड इिडकस हसमिशन अिहध क दौरान हई पॉहजहिि / हनगहिि

इिहडयन ओशन डाईपोि (IOD) घिनाओि को दो राता । तापमान, धाराओि, और म ासागरीय हमहित परत की ग राई

की इििरएनअि पररिततनशीिता का हिशलषर IOD घिनाओि क सनदभत म हकया गया । भमधयरखीय धाराओि म

हिसिगहतयाा भारतीय ति रखाओि पर तिीय धाराओि की शनकत को परभाहित करती । मॉडि हसमिशन स पता चिता

हक समातरा ति क साथ बढी हई (घिी हई) तिीय अपिहििग परहिया सकारातमक (नकारातमक) IOD घिनाओि क

दौरान समातरा ति पर हििकषर ठि डी (गमी) करती । समि हिशलषर स पता चिता हक भारत क पिी ति और

vii

EEIO कषतर क साथ सत मररहडयनि ििर पररि न सकारातमक IOD और नकारातमक IOD घिनाओि क सनदरभ म

हिपरीत ििर पररि न को दशातता । सकारातमक IOD घिनाओि क अगसत-हसतिबर म ीनोि क दौरान, BoB क दहकषर-

पहिमी सीमा म मररहडयनि ििर पररि न उततर की ओर , हजस भारत क पिी ति पर उततरिती धाराओि की

हिसिगहतयोि क साथ समबदध हकया जा सकता ।

IO क भीतर, BoB समदरी सत की ििरता और सत धाराओि म हभनन हिशषताएि हदखाता । िाषपीकरर

स अहधक िषात और नदी हनित न क माधयम स बडी मातरा म ताजा पानी BoB म जड जाता जो इस IO म सबस कम

खारा कषतर बनाता । अधयाय 5 म, BoB म ताज पानी क गबार (पलम) क फिाि क सवरप को हनधातररत करन म िाओि

की भहमका की जााच यथाथतिादी समदर ति, समदरति सत (बथीमीिरी) और नदी क हनित न आिकडोि क साथ एक

उचच-ररजॉलयशन कषतरीय म ासागर मॉडि का उपयोग करक की गई । हिहभनन हदशाओि और गहत िािी आदशत िाओि

क साथ कई परयोग हकए गए जो BoB म मौसमी िा क सवरप का परहतहनहधतव करत । दहकषर-पिी और उततर-पिी

िाओि क मामिोि म गबार ति क साथ सििगन र ता , िहकन दहकषर-पहिमी िाओि क त त गबार मधय-BoB की

ओर अिसर ोता । मधयम िाओि क त त नदी-हनित न गबार उततरी और पिोततर BoB म सीहमत र त । कम- िा

या मधयम िा की नसथहत म कम-खार पानी का सथाहनक फिाि अहधकािश डोमन या पिी BoB म दखा जाता । खाडी

म उचच िा की नसथहत जयादातर BoB क उततरी भाग म ताज पानी को सीहमत रखती । य पाया गया हक िा की

गहत म 2 स 8 ms-1 िनदध ोन स पिी BoB म 16oN अकषािश पर दहकषरिती ििर पररि न 2 स 10 kg m-2 s-1 बढ जाता

। इस परकार, BoB म ताज पानी क गबार की हिशषताओि पर िा की गहत और हदशा की अिग-अिग भहमकाएा

आदशत सिखयातमक परयोगोि स सपषट ोती ।

परसतत कायत क सामानय हनषकषत और भहिषय कायत क अिसर अधयाय 6 म हदए गए । एक सफि सतयापन

क बाद, ROMS मॉडि का उपयोग IO म SSS हसमिशन पर नदी क ताज पानी क परभाि का आकिन करन क हिए

हकया गया । पहिमी IO की तिना म पिोततर IO म ििरता पर नदी क हनित न का अहधक परभाि हदखता । दहकषरी

उषणकहिबिधीय IO म, हमहित परत ििरता पररिततनशीिता पर नदी क हनित न का परभाि IO क हिहभनन कषतरोि क बीच

नयनतम पाया गया। िषत 2000-2014 की अिहध क इििरएनअि हसमिशन स IOD घिनाओि क हिए समि हिशलषर

viii

हकया गया। हिशलषर स य पाया गया हक EEIO म अकटबर क दौरान 20oC समताप रखा की ग राई nIOD म 100-

110 मीिर स घिकर pIOD म 70-80 मीिर र गई। पिी भमधयरखीय IO म पहिमोततर ििर पररि न pIOD (nIOD)

की घिनाओि क दौरान बढा (घिा) । मॉडि सििदनशीिता परयोगोि िारा ताज पानी क गबार क मागत और BoB म

ििर पररि न को सिशोहधत करन म िा की गहत और हदशा की म तवपरत भहमका को उजागर हकया गया ।

ix

Table of Contents Certificate

Acknowledgements

Abstract i-viii

Table of Contents ix-xii

List of Figures xiii-xviii

List of Tables xix

Chapter 1 INTRODUCTION 1-31

1.1 Background of the Study 2

1.2 Major Characteristics of the Indian Ocean 4

1.2.1 Surface winds 4

1.2.2 Sea surface temperature 5

1.2.3 Sea surface salinity

1.2.4 Surface fluxes

1.2.5 Upper-ocean circulation

1.2.6 Unique features of the Arabian Sea and the Bay of Bengal

7

8

14

16

1.3 Literature Review 22

1.4 Motivation of the Study 29

1.5 Outline of the Thesis 30

Chapter 2 MODEL, DATA AND METHODOLOGY 32-63

2.1 Introduction 33

2.2 Model Formulation 34

2.2.1 Governing equations 34

2.2.2 Vertical boundary conditions 36

2.2.3 Horizontal boundary conditions

2.2.4 Horizontal discretization

2.2.5 Vertical discretization

2.2.6 Viscosity and diffusivity

2.2.7 Point sources

37

38

39

40

41

x

2.3 Model Configuration 42

2.3.1 Domain and bathymetry 42

2.3.2 Model input

2.3.3 Pre- and post-processing tools

44

47

2.4 Reference Data 47

2.4.1 RAMA

2.4.2 OSCAR

2.4.3 TMI-AMSRE SST

2.4.4 North Indian Ocean Climatological Atlas (NIOA)

47

48

48

48

2.5

Model Validation

2.5.1 Annual mean and seasonal variability of SST

2.5.2 Annual mean and seasonal SSS distribution over the IO

2.5.3 Validation of model simulated daily parameters with

RAMA buoy data

2.5.4 Annual mean and seasonal variability of surface currents

49

49

52

55

57

2.6 Conclusions 62

Chapter 3 IMPACT OF RIVER DISCHARGE ON THE

THERMOHALINE CHARACTERISTICS OF THE

INDIAN OCEAN

64-90

3.1 Introduction 65

3.2 Model and Methodology

3.2.1 Model configuration

3.2.2 Incorporation of continental (river) discharge and numerical

experiments

3.2.3 Mixed layer salinity budget analysis

67

67

69

71

3.3 Results and Discussion

3.3.1 Mixed layer salinity budget

3.3.2 Effect of continental freshwater discharge

73

73

80

3.4 Conclusions 88

xi

Chapter 4 INTERANNUAL VARIABILITY OF THE INDIAN OCEAN

FEATURES

91-125

4.1 Introduction 92

4.2 Model Configuration 94

4.3 Data and Methodology 94

4.4 Results and Discussion

4.4.1 Interannual variations in the IO thermodynamic features

4.4.1.1 Sea surface temperature

4.4.1.2 Subsurface temperature

4.4.1.3 Depth of 20oC isotherm

4.4.1.4 Zonal and meridional currents

4.4.2 IOD events during the simulation period

4.4.2.1 Variability of surface currents in response to IOD

Events

4.4.2.2 Coastal oceanic processes

4.4.2.3 Surface salt transport

96

96

96

103

109

110

113

114

116

120

4.5 Conclusions 123

Chapter 5 EFFECT OF WIND ON THE FRESHWATER PLUME IN

THE BAY OF BENGAL: A SENSITIVITY STUDY

126-155

5.1 Introduction 127

5.2 Numerical Modelling and Methodology

5.2.1 Model configuration and forcing

5.2.2 Incorporation of river discharge

5.2.3 Numerical experiments and methodology

5.2.3.1 Equivalent depth of freshwater

5.2.3.2 Surface salt transport estimates

129

129

131

132

134

134

5.3 Results and Discussion

5.3.1 Model validation

5.3.2 Role of wind direction in plume dispersion

5.3.3 Role of wind speed in plume dispersion

135

135

137

140

xii

5.3.4 Dynamical mechanism in the plume dispersion under

different wind conditions

5.3.5 Vertical extent of freshwater under different wind

conditions

5.3.6 Surface salt transport variability and its response to winds

143

148

150

5.4 Conclusions 154

Chapter 6 CONCLUSIONS AND FUTURE SCOPE OF THE WORK 156-165

6.1 Conclusions 157

6.2 Future Work 164

References 166-184

List of Acronyms 185-188

List of Websites 189

Biographical Sketch 190-193

xiii

List of Figures

Figure No. Title Page

No.

Figure 1.1 The IO domain used for the present study along with the bathymetry

derived from the modified ETOPO2v2.

4

Figure 1.2 Climatology of the seasonal wind stress in Nm-2 (contour-fill) and wind

speed in ms-1 (vectors) over the IO derived from TropFlux data.

5

Figure 1.3 Seasonal SST climatology over the IO. 6

Figure 1.4 Seasonal SSS climatology over the IO. 8

Figure 1.5 Climatology of seasonal LHF over the IO derived from TropFlux data. 10

Figure 1.6 Seasonal SHF climatology over the IO derived from TropFlux data. 11

Figure 1.7 Seasonal net SWR climatology over the IO derived from TropFlux data. 12

Figure 1.8 Seasonal LWR climatology over the IO derived from TropFlux data. 13

Figure 1.9 Seasonal NHF climatology over the IO derived from TropFlux data. 13

Figure 1.10a A schematic showing the major summer (southwest) monsoon current

pattern and circulation in the IO.

15

Figure 1.10b A schematic showing the major winter (northeast) monsoon current

pattern and circulation in the IO.

16

Figure 1.11 The SSS annual mean distribution in the northern IO showing the

contrasting surface salinity characteristics of the AS and the BoB. The

locations of the last gauging station of major rivers draining into the two

basins according to Dai et al., 2009 are also shown.

17

Figure 1.12 A schematic showing the comparison between the feedback cycles in the

AS and BoB.

19

Figure 2.1 Illustration of the model state variables arranged over an Arakawa C-grid

in the horizontal direction of the ROMS grids.

39

Figure 2.2 Illustration of the model state variables arranged in the vertical direction

of the ROMS grids.

40

Figure 2.3 Illustration of the indexing of the point source in ROMS. In case (a), river

enters into ,i j cell from the left u-face. In case (b), river enters from the

right u-face into the same cell.

42

Figure 2.4 The model domain used for the present study along with the bathymetry

(m) derived from the modified ETOPO2v2 data.

43

xiv

Figure 2.5 Sections of the model sigma-coordinate vertical layers along 65°E in the

domain.

43

Figure 2.6 Comparison of annual mean SST (oC) over the IO from the TMI (top-right

panel) and the same from the ROMS model (top-left panel).The

difference (Model-TMI) in SST is shown in the middle panel. SD of

monthly mean SST from TMI (bottom-right panel) and ROMS model

(bottom-left).

50

Figure 2.7 Comparison of the seasonal SST (oC) over the IO as simulated by ROMS

model (left panel) and from the TMI data (middle panel) and the

difference between them (right panel).

51

Figure 2.8 Comparison of annually averaged SSS (psu) over the IO as observed from

the Aquarius (top-right panel) and from the ROMS model (top-left panel).

The SSS difference (Model-Aquarius) is shown in the middle panel. SD

of monthly mean SSS from both Aquarius (bottom-right panel) and

ROMS model (bottom-left).

54

Figure 2.9 Comparison of the seasonal SSS (psu) over the IO as simulated by ROMS

model (left panel) and from the Aquarius data (middle panel) and the

difference between them (right panel). The locations of the RAMA buoys

used for validation over the IO are shown with stars in the middle panel of

the top row.

55

Figure 2.10 Comparison of the daily climatological SSS (psu) and SST (oC) estimated

from the daily RAMA buoy data in the IO and the same extracted from

the ROMS model.

57

Figure 2.11 Annual mean surface currents (ms-1) over the IO from the ROMS model

(top panel), OSCAR data (middle panel), and the corresponding

difference between them (bottom panel).

60

Figure 2.12 Comparison of the seasonally averaged surface currents (ms-1) in the

northern IO from the ROMS model (left panels) and the corresponding

OSCAR currents (right panel). The thick black arrows represent the

prominent currents in the region.

61

Figure 2.13 Comparison of the surface currents (ms-1) in the STIO from the model

(upper panel) and from the OSCAR data (lower panel). The thick black

arrows represent the prominent currents in the region.

62

Figure 3.1 Model domain along with the bathymetry (meters) derived from modified

ETOPOv2. Locations of the last gauging stations of all the rivers draining

into the IO (Dai et al., 2009), which incorporated in the model are shown as

red dots. The boxes marked in the figure represent regions used for the

salt budget analysis.

69

Figure 3.2 Monthly climatology of river discharge (m3s-1) from major rivers (having

peak discharge > 500 m3s-1) included in the model. The bottom panel

shows total river discharge in different sectors of the IO as marked in

71

xv

Figure 3.1.

Figure 3.3 The annual mean mixed layer salt budget terms (psu day-1) in the top and

middle rows. The annual mean salinity (psu) and currents (ms-1) within

the mixed layer are shown in the bottom row.

76

Figure 3.4 Model simulated (R-Expt) seasonal variability of the salinity (psu) shown

in shades overlaid with the currents (ms-1) in vectors within the mixed

layer.

77

Figure 3.5 The mixed layer salt budget terms (psu day-1) from the R-Expt experiment

for the summer monsoon season (June-September) over the IO.

79

Figure 3.6 Same as in Figure 3.5 except for the winter monsoon season (December-

February).

80

Figure 3.7 Comparison of model simulated SSS (psu) in the two experiments. First

column-without river (NR-Expt) simulations, second column- with river

(R-Expt) simulations, third column- difference (R-Expt minus NR-Expt).

81

Figure 3.8 Time series of the area averaged SSS (psu) within the ten regions (marked

boxes in Figure 3.1) before (dashed lines, NR-Expt.) and after (solid lines,

R-Expt.) adding the riverine freshwater discharges into the model.

83

Figure 3.9 Balance of mixed layer salt budget terms (psu day-1) over the ten selected

regions (boxes marked in Figure 3.1) in the IO before (dashed lines, NR-

Expt.) and after (solid lines, R-Expt.) adding the riverine freshwater

discharges into the model.

85

Figure 4.1 Model domain along with bathymetry derived from ETOPO2v2. The

locations of the RAMA buoys used for validating the ROMS model are

also shown as white boxes.

94

Figure 4.2 Comparison of the SST data from RAMA buoys of IO at different

locations and ROMS for 2013.

97

Figure 4.3 Comparison of the SST (°C) data from RAMA buoys of IO at different

locations and ROMS for 2014.

99

Figure 4.4 Scatter plot diagram for SST (°C) from the RAMA buoys located at

different locations in different years and corresponding data from ROMS.

101

Figure 4.5 Comparison of model simulated SST (°C) for the entire simulation years

(2000 to 2014) with the two buoys (located at (1.5oS, 90oE) and (5oS,

95oE)).

101

Figure 4.6 Comparison of multi-year (2000-2014) seasonal average and SD of SST

(oC) from model and TMI for the DJF, MAM, JJAS and ON seasons. The

seasonal average surface currents (ms-1) from the model and OSCAR data

are overlaid over the SST average panels. The boxes marked in the figure

(j) show the different geographic regions in IO used for present analysis.

103

xvi

Figure 4.7 Comparison of subsurface temperature profile, D20 (dashed lines) and

MLD (continuous lines) from the model simulation and Argo data area

averaged over the three different regions (AS, BoB and CEIO) in the IO.

105

Figure 4.8 Comparison of vertical temperature profile (°C) and D20 (m) from

RAMA buoys located at different locations and ROMS. The D20 are

shown as black continuous line.

107

Figure 4.9 Scatter plot for the vertical temperature profile (°C) from RAMA buoy

and ROMS.

108

Figure 4.10 Statistical comparison of vertical temperature profiles (°C) from different

buoys located over the IO. (a) SD of vertical temperature at each RAMA

buoy locations (continuous lines) and the corresponding ROMS (dashed

lines), (b) RMSD between model and buoy SST (°C) at each locations.

108

Figure 4.11 Comparison of D20 (m) from RAMA buoy located at (1.5oS, 90oE) and

ROMS for different years.

110

Figure 4.12 Meridional velocity component (ms-1) from RAMA buoys and ROMS

model at different locations in the IO.

112

Figure 4.13 Zonal velocity component (ms-1) from RAMA buoy at (1.5oN, 90oE) and

ROMS model for different years.

113

Figure 4.14 Comparison of DMI (IOD index) during the simulation period (2000 to

2014) dashed lines are drawn at +/-0.48oC for qualification as IOD.

114

Figure 4.15 Comparison of model simulated SST (°C) and current anomalies (ms-1)

estimated from the pIOD, nIOD and normal year composites during 2000

-2014.

116

Figure 4.16 Model simulated temperature profile (°C) composite over the southeastern

box of IOD estimated for the (a) normal year, (b) nIOD, and (c) pIOD

years during 2000-2014. The thick black line denotes the D20 in each

figure.

118

Figure 4.17 Composites of model simulated zonal (a, b and c) and meridional (d, e

and f) velocity components (ms-1) estimated from the pIOD, nIOD, and

normal years during 2000-2014.

119

Figure 4.18 Composites of model simulated MLD (shaded, in meters) and D20

(contours, in meters) estimated from the pIOD, nIOD, and normal years

during 2000-2014 period.

120

Figure 4.19 Comparison of the composites of surface meridional salt transport (kg m-2

s-1) estimated from model simulations for the pIOD, nIOD, and normal

years during 2000-2014.

121

Figure 4.20 Comparison of the composites of surface zonal salt transport (kg m-2s-1)

estimated from model simulations for the pIOD, nIOD, and normal years

122

xvii

during 2000-2014.

Figure 5.1 The model domain along with bathymetry (m) derived from the modified

Etopo2v2. Locations of river mouths (nearest location where the data is

available before discharge) of major rivers also marked with red circles on

the map.

130

Figure 5.2 Monthly climatology of freshwater discharges (m3s-1) from the seven

major rivers in the BoB.

132

Figure 5.3 The idealized winds (ms-1) used to force the model. 133

Figure 5.4 The maximum volume of monthly climatological freshwater discharge

(m3s-1) of the seven major rivers in the BoB.

133

Figure 5.5 Comparison of the model simulated seasonal SSS (psu) with NIOA

climatology, Aquarius and the difference (ROMS-NIOA).

136

Figure 5.6 Comparison of the model simulated seasonal surface current vectors with

OSCAR currents data. Magnitude of current (ms-1) represented by colour

shading.

137

Figure 5.7 Temporal evolution of simulated SSS (psu) under different wind

directions in the BoB. The isohaline contour at 31 psu is shown with a

white thick line.

138

Figure 5.8 Vertical section of salinity (psu) under different idealized wind directions.

The isohaline contour at 31 psu is shown with a thick line.buoy.

140

Figure 5.9 Temporal evolution of simulated SSS (psu), showing features of low

saline plume, under varied wind speeds (low, moderate, high and very

high wind). The isohaline contour at 31 psu is shown with a white thick

line.

142

Figure 5.10 Comparison of vertical section of model simulated salinity (psu) along

21oN in the BoB under different wind speeds after 15 days, 30 days, 45

days, and 60 days of model integration.

143

Figure 5.11 Comparison of salinity profiles along the zonal cross section at 20°N in

the BoB and the associated meridional momentum balancing terms in the

plume from the sensitivity experiments with different wind directions.

145

Figure 5.12 Comparison of salinity profiles along the meridional cross section at 90°E

in the BoB and the associated zonal momentum balancing terms in the

plume from the sensitivity experiments with different wind directions.

146

Figure 5.13 The comparison of vertical salinity structure along the zonal cross section

at 20°N in the BoB and the associated meridional momentum balancing

terms in the plume from the sensitivity experiments with different wind

speeds.

147

xviii

Figure 5.14 The comparison of vertical salinity structure along the meridional cross

section at 90°E in the BoB and the associated zonal momentum balancing

terms in the plume from the sensitivity experiments with different wind

speeds.

148

Figure 5.15 The equivalent depth of freshwater (m) in the BoB for different idealized

wind directions.

149

Figure 5.16 The equivalent depth of freshwater (m) in the BoB for different idealized

wind speeds.

150

Figure 5.17 Zonal and meridional surface salt transport (kg m-2s-1) variability in the

BoB estimated from model simulations (a-h). Time-Longitude section of

surface salt transport along 16oN latitude (shown as black line in figure

(h)) in BoB (i-j).

152

Figure 5.18 Inter-comparison of meridional and zonal surface salt transport (kg m-2s-1)

under different wind directions (a-h) and wind speeds (i-p).

154

xix

List of Tables

Table No. Title Page

No.

Table 2.1 List of variables used in the governing equations of the model. 37

Table 2.2 Details of the parameters used in the ROMS model configuration. 46