Ontology type: schema:ScholarlyArticle
2017-08-22
AUTHORSA. Mukherjee, D. Shankar, Abhisek Chatterjee, P. N. Vinayachandran
ABSTRACTWe simulate the East India Coastal Current (EICC) using two numerical models (resolution 0.1∘×0.1∘),\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0.1^{\circ } \times 0.1^{\circ }),$$\end{document} an oceanic general circulation model (OGCM) called Modular Ocean Model and a simpler, linear, continuously stratified (LCS) model, and compare the simulated current with observations from moorings equipped with acoustic Doppler current profilers deployed on the continental slope in the western Bay of Bengal (BoB). We also carry out numerical experiments to analyse the processes. Both models simulate well the annual cycle of the EICC, but the performance degrades for the intra-annual and intraseasonal components. In a model-resolution experiment, both models (run at a coarser resolution of 0.25∘×0.25∘\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0.25^{\circ } \times 0.25^{\circ }$$\end{document}) simulate well the currents in the equatorial Indian Ocean (EIO), but the performance of the high-resolution LCS model as well as the coarse-resolution OGCM, which is good in the EICC regime, degrades in the eastern and northern BoB. An experiment on forcing mechanisms shows that the annual EICC is largely forced by the local alongshore winds in the western BoB and remote forcing due to Ekman pumping over the BoB, but forcing from the EIO has a strong impact on the intra-annual EICC. At intraseasonal periods, local (equatorial) forcing dominates in the south (north) because the Kelvin wave propagates equatorward in the western BoB. A stratification experiment with the LCS model shows that changing the background stratification from EIO to BoB leads to a stronger surface EICC owing to strong coupling of higher order vertical modes with wind forcing for the BoB profiles. These high-order modes, which lead to energy propagating down into the ocean in the form of beams, are important only for the current and do not contribute significantly to the sea level. More... »
PAGES3949-3980
http://scigraph.springernature.com/pub.10.1007/s00382-017-3856-x
DOIhttp://dx.doi.org/10.1007/s00382-017-3856-x
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1091285802
JSON-LD is the canonical representation for SciGraph data.
TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT
[
{
"@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json",
"about": [
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/04",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Earth Sciences",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0405",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Oceanography",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "CSIR-National Institute of Oceanography, Goa, India",
"id": "http://www.grid.ac/institutes/grid.436330.1",
"name": [
"ESSO-Indian National Centre for Ocean Information Services (INCOIS), Hyderabad, India",
"CSIR-National Institute of Oceanography, Goa, India"
],
"type": "Organization"
},
"familyName": "Mukherjee",
"givenName": "A.",
"id": "sg:person.016040443345.26",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016040443345.26"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "CSIR-National Institute of Oceanography, Goa, India",
"id": "http://www.grid.ac/institutes/grid.436330.1",
"name": [
"CSIR-National Institute of Oceanography, Goa, India"
],
"type": "Organization"
},
"familyName": "Shankar",
"givenName": "D.",
"id": "sg:person.011737006645.02",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011737006645.02"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "CSIR-National Institute of Oceanography, Goa, India",
"id": "http://www.grid.ac/institutes/grid.436330.1",
"name": [
"ESSO-Indian National Centre for Ocean Information Services (INCOIS), Hyderabad, India",
"CSIR-National Institute of Oceanography, Goa, India"
],
"type": "Organization"
},
"familyName": "Chatterjee",
"givenName": "Abhisek",
"id": "sg:person.010755512233.85",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010755512233.85"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Centre for Atmospheric and Oceanic Sciences, Indian Institute of Science, Bengaluru, India",
"id": "http://www.grid.ac/institutes/grid.34980.36",
"name": [
"Centre for Atmospheric and Oceanic Sciences, Indian Institute of Science, Bengaluru, India"
],
"type": "Organization"
},
"familyName": "Vinayachandran",
"givenName": "P. N.",
"id": "sg:person.016113470637.60",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016113470637.60"
],
"type": "Person"
}
],
"citation": [
{
"id": "sg:pub.10.1007/s12040-007-0025-3",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1022343975",
"https://doi.org/10.1007/s12040-007-0025-3"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s12040-014-0471-7",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1014500824",
"https://doi.org/10.1007/s12040-014-0471-7"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s10872-008-0069-2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1030185843",
"https://doi.org/10.1007/s10872-008-0069-2"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/bf02744586",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1004267261",
"https://doi.org/10.1007/bf02744586"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s12040-014-0449-5",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1029262368",
"https://doi.org/10.1007/s12040-014-0449-5"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s12040-012-0258-7",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1002333848",
"https://doi.org/10.1007/s12040-012-0258-7"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s12040-007-0030-6",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1053197588",
"https://doi.org/10.1007/s12040-007-0030-6"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s12040-012-0191-9",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1028595004",
"https://doi.org/10.1007/s12040-012-0191-9"
],
"type": "CreativeWork"
}
],
"datePublished": "2017-08-22",
"datePublishedReg": "2017-08-22",
"description": "We simulate the East India Coastal Current (EICC) using two numerical models (resolution 0.1\u2218\u00d70.1\u2218),\\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym}\n\t\t\t\t\\usepackage{amsfonts}\n\t\t\t\t\\usepackage{amssymb}\n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$0.1^{\\circ } \\times 0.1^{\\circ }),$$\\end{document} an oceanic general circulation model (OGCM) called Modular Ocean Model and a simpler, linear, continuously stratified (LCS) model, and compare the simulated current with observations from moorings equipped with acoustic Doppler current profilers deployed on the continental slope in the western Bay of Bengal (BoB). We also carry out numerical experiments to analyse the processes. Both models simulate well the annual cycle of the EICC, but the performance degrades for the intra-annual and intraseasonal components. In a model-resolution experiment, both models (run at a coarser resolution of 0.25\u2218\u00d70.25\u2218\\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym}\n\t\t\t\t\\usepackage{amsfonts}\n\t\t\t\t\\usepackage{amssymb}\n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$0.25^{\\circ } \\times 0.25^{\\circ }$$\\end{document}) simulate well the currents in the equatorial Indian Ocean (EIO), but the performance of the high-resolution LCS model as well as the coarse-resolution OGCM, which is good in the EICC regime, degrades in the eastern and northern BoB. An experiment on forcing mechanisms shows that the annual EICC is largely forced by the local alongshore winds in the western BoB and remote forcing due to Ekman pumping over the BoB, but forcing from the EIO has a strong impact on the intra-annual EICC. At intraseasonal periods, local (equatorial) forcing dominates in the south (north) because the Kelvin wave propagates equatorward in the western BoB. A stratification experiment with the LCS model shows that changing the background stratification from EIO to BoB leads to a stronger surface EICC owing to strong coupling of higher order vertical modes with wind forcing for the BoB profiles. These high-order modes, which lead to energy propagating down into the ocean in the form of beams, are important only for the current and do not contribute significantly to the sea level.",
"genre": "article",
"id": "sg:pub.10.1007/s00382-017-3856-x",
"isAccessibleForFree": false,
"isPartOf": [
{
"id": "sg:journal.1049631",
"issn": [
"0930-7575",
"1432-0894"
],
"name": "Climate Dynamics",
"publisher": "Springer Nature",
"type": "Periodical"
},
{
"issueNumber": "11-12",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "50"
}
],
"keywords": [
"East India Coastal Current",
"oceanic general circulation model",
"equatorial Indian Ocean",
"Coastal Current",
"continental slope",
"acoustic Doppler current profiler",
"Modular Ocean Model",
"local alongshore winds",
"general circulation model",
"Doppler current profiler",
"higher order vertical modes",
"western BoB.",
"northern BoB.",
"western BoB",
"ocean model",
"alongshore winds",
"circulation model",
"intraseasonal component",
"intraseasonal periods",
"western Bay",
"Indian Ocean",
"Kelvin waves",
"sea level",
"current profiler",
"annual cycle",
"LCS model",
"background stratification",
"vertical modes",
"numerical model",
"BoB.",
"Ocean",
"wind",
"stratification experiment",
"Bob",
"slope",
"strong impact",
"numerical experiments",
"moorings",
"Ekman",
"current",
"equatorward",
"Bay",
"south",
"profiler",
"Bengal",
"numerical simulations",
"dominates",
"form of beams",
"stratification",
"strong coupling",
"model",
"waves",
"regime",
"cycle",
"period",
"profile",
"impact",
"simulations",
"experiments",
"process",
"mode",
"components",
"coupling",
"degrades",
"higher order modes",
"levels",
"mechanism",
"energy",
"form",
"performance degrades",
"performance",
"beam",
"observations"
],
"name": "Numerical simulation of the observed near-surface East India Coastal Current on the continental slope",
"pagination": "3949-3980",
"productId": [
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1091285802"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1007/s00382-017-3856-x"
]
}
],
"sameAs": [
"https://doi.org/10.1007/s00382-017-3856-x",
"https://app.dimensions.ai/details/publication/pub.1091285802"
],
"sdDataset": "articles",
"sdDatePublished": "2022-08-04T17:06",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-springernature-scigraph/baseset/20220804/entities/gbq_results/article/article_744.jsonl",
"type": "ScholarlyArticle",
"url": "https://doi.org/10.1007/s00382-017-3856-x"
}
]
Download the RDF metadata as: json-ld nt turtle xml License info
JSON-LD is a popular format for linked data which is fully compatible with JSON.
curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s00382-017-3856-x'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s00382-017-3856-x'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00382-017-3856-x'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00382-017-3856-x'
This table displays all metadata directly associated to this object as RDF triples.
187 TRIPLES
21 PREDICATES
105 URIs
89 LITERALS
6 BLANK NODES
Subject | Predicate | Object | |
---|---|---|---|
1 | sg:pub.10.1007/s00382-017-3856-x | schema:about | anzsrc-for:04 |
2 | ″ | ″ | anzsrc-for:0405 |
3 | ″ | schema:author | Nb0586573fecf4091b79896f93f786b8d |
4 | ″ | schema:citation | sg:pub.10.1007/bf02744586 |
5 | ″ | ″ | sg:pub.10.1007/s10872-008-0069-2 |
6 | ″ | ″ | sg:pub.10.1007/s12040-007-0025-3 |
7 | ″ | ″ | sg:pub.10.1007/s12040-007-0030-6 |
8 | ″ | ″ | sg:pub.10.1007/s12040-012-0191-9 |
9 | ″ | ″ | sg:pub.10.1007/s12040-012-0258-7 |
10 | ″ | ″ | sg:pub.10.1007/s12040-014-0449-5 |
11 | ″ | ″ | sg:pub.10.1007/s12040-014-0471-7 |
12 | ″ | schema:datePublished | 2017-08-22 |
13 | ″ | schema:datePublishedReg | 2017-08-22 |
14 | ″ | schema:description | We simulate the East India Coastal Current (EICC) using two numerical models (resolution 0.1∘×0.1∘),\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0.1^{\circ } \times 0.1^{\circ }),$$\end{document} an oceanic general circulation model (OGCM) called Modular Ocean Model and a simpler, linear, continuously stratified (LCS) model, and compare the simulated current with observations from moorings equipped with acoustic Doppler current profilers deployed on the continental slope in the western Bay of Bengal (BoB). We also carry out numerical experiments to analyse the processes. Both models simulate well the annual cycle of the EICC, but the performance degrades for the intra-annual and intraseasonal components. In a model-resolution experiment, both models (run at a coarser resolution of 0.25∘×0.25∘\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0.25^{\circ } \times 0.25^{\circ }$$\end{document}) simulate well the currents in the equatorial Indian Ocean (EIO), but the performance of the high-resolution LCS model as well as the coarse-resolution OGCM, which is good in the EICC regime, degrades in the eastern and northern BoB. An experiment on forcing mechanisms shows that the annual EICC is largely forced by the local alongshore winds in the western BoB and remote forcing due to Ekman pumping over the BoB, but forcing from the EIO has a strong impact on the intra-annual EICC. At intraseasonal periods, local (equatorial) forcing dominates in the south (north) because the Kelvin wave propagates equatorward in the western BoB. A stratification experiment with the LCS model shows that changing the background stratification from EIO to BoB leads to a stronger surface EICC owing to strong coupling of higher order vertical modes with wind forcing for the BoB profiles. These high-order modes, which lead to energy propagating down into the ocean in the form of beams, are important only for the current and do not contribute significantly to the sea level. |
15 | ″ | schema:genre | article |
16 | ″ | schema:isAccessibleForFree | false |
17 | ″ | schema:isPartOf | N70a9a35c96fa489b802b64c1e0935a09 |
18 | ″ | ″ | N70d13f4b8dc94088a445fa086e63621b |
19 | ″ | ″ | sg:journal.1049631 |
20 | ″ | schema:keywords | Bay |
21 | ″ | ″ | Bengal |
22 | ″ | ″ | BoB. |
23 | ″ | ″ | Bob |
24 | ″ | ″ | Coastal Current |
25 | ″ | ″ | Doppler current profiler |
26 | ″ | ″ | East India Coastal Current |
27 | ″ | ″ | Ekman |
28 | ″ | ″ | Indian Ocean |
29 | ″ | ″ | Kelvin waves |
30 | ″ | ″ | LCS model |
31 | ″ | ″ | Modular Ocean Model |
32 | ″ | ″ | Ocean |
33 | ″ | ″ | acoustic Doppler current profiler |
34 | ″ | ″ | alongshore winds |
35 | ″ | ″ | annual cycle |
36 | ″ | ″ | background stratification |
37 | ″ | ″ | beam |
38 | ″ | ″ | circulation model |
39 | ″ | ″ | components |
40 | ″ | ″ | continental slope |
41 | ″ | ″ | coupling |
42 | ″ | ″ | current |
43 | ″ | ″ | current profiler |
44 | ″ | ″ | cycle |
45 | ″ | ″ | degrades |
46 | ″ | ″ | dominates |
47 | ″ | ″ | energy |
48 | ″ | ″ | equatorial Indian Ocean |
49 | ″ | ″ | equatorward |
50 | ″ | ″ | experiments |
51 | ″ | ″ | form |
52 | ″ | ″ | form of beams |
53 | ″ | ″ | general circulation model |
54 | ″ | ″ | higher order modes |
55 | ″ | ″ | higher order vertical modes |
56 | ″ | ″ | impact |
57 | ″ | ″ | intraseasonal component |
58 | ″ | ″ | intraseasonal periods |
59 | ″ | ″ | levels |
60 | ″ | ″ | local alongshore winds |
61 | ″ | ″ | mechanism |
62 | ″ | ″ | mode |
63 | ″ | ″ | model |
64 | ″ | ″ | moorings |
65 | ″ | ″ | northern BoB. |
66 | ″ | ″ | numerical experiments |
67 | ″ | ″ | numerical model |
68 | ″ | ″ | numerical simulations |
69 | ″ | ″ | observations |
70 | ″ | ″ | ocean model |
71 | ″ | ″ | oceanic general circulation model |
72 | ″ | ″ | performance |
73 | ″ | ″ | performance degrades |
74 | ″ | ″ | period |
75 | ″ | ″ | process |
76 | ″ | ″ | profile |
77 | ″ | ″ | profiler |
78 | ″ | ″ | regime |
79 | ″ | ″ | sea level |
80 | ″ | ″ | simulations |
81 | ″ | ″ | slope |
82 | ″ | ″ | south |
83 | ″ | ″ | stratification |
84 | ″ | ″ | stratification experiment |
85 | ″ | ″ | strong coupling |
86 | ″ | ″ | strong impact |
87 | ″ | ″ | vertical modes |
88 | ″ | ″ | waves |
89 | ″ | ″ | western Bay |
90 | ″ | ″ | western BoB |
91 | ″ | ″ | western BoB. |
92 | ″ | ″ | wind |
93 | ″ | schema:name | Numerical simulation of the observed near-surface East India Coastal Current on the continental slope |
94 | ″ | schema:pagination | 3949-3980 |
95 | ″ | schema:productId | N4c2b51c5bc6041dbb120c4197e568b5b |
96 | ″ | ″ | Nd5544bc295024a7b9b56f186fbd527d8 |
97 | ″ | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1091285802 |
98 | ″ | ″ | https://doi.org/10.1007/s00382-017-3856-x |
99 | ″ | schema:sdDatePublished | 2022-08-04T17:06 |
100 | ″ | schema:sdLicense | https://scigraph.springernature.com/explorer/license/ |
101 | ″ | schema:sdPublisher | N09824181bff14c158874b41ffb245501 |
102 | ″ | schema:url | https://doi.org/10.1007/s00382-017-3856-x |
103 | ″ | sgo:license | sg:explorer/license/ |
104 | ″ | sgo:sdDataset | articles |
105 | ″ | rdf:type | schema:ScholarlyArticle |
106 | N09824181bff14c158874b41ffb245501 | schema:name | Springer Nature - SN SciGraph project |
107 | ″ | rdf:type | schema:Organization |
108 | N2c275877ead84cf5b6df1d519e3ba513 | rdf:first | sg:person.010755512233.85 |
109 | ″ | rdf:rest | N42c6d61cd79b45a19bebdc16270048eb |
110 | N42c6d61cd79b45a19bebdc16270048eb | rdf:first | sg:person.016113470637.60 |
111 | ″ | rdf:rest | rdf:nil |
112 | N4c2b51c5bc6041dbb120c4197e568b5b | schema:name | doi |
113 | ″ | schema:value | 10.1007/s00382-017-3856-x |
114 | ″ | rdf:type | schema:PropertyValue |
115 | N70a9a35c96fa489b802b64c1e0935a09 | schema:issueNumber | 11-12 |
116 | ″ | rdf:type | schema:PublicationIssue |
117 | N70d13f4b8dc94088a445fa086e63621b | schema:volumeNumber | 50 |
118 | ″ | rdf:type | schema:PublicationVolume |
119 | Nb0586573fecf4091b79896f93f786b8d | rdf:first | sg:person.016040443345.26 |
120 | ″ | rdf:rest | Nbda07dc13eb14c60899d7d32dd54425e |
121 | Nbda07dc13eb14c60899d7d32dd54425e | rdf:first | sg:person.011737006645.02 |
122 | ″ | rdf:rest | N2c275877ead84cf5b6df1d519e3ba513 |
123 | Nd5544bc295024a7b9b56f186fbd527d8 | schema:name | dimensions_id |
124 | ″ | schema:value | pub.1091285802 |
125 | ″ | rdf:type | schema:PropertyValue |
126 | anzsrc-for:04 | schema:inDefinedTermSet | anzsrc-for: |
127 | ″ | schema:name | Earth Sciences |
128 | ″ | rdf:type | schema:DefinedTerm |
129 | anzsrc-for:0405 | schema:inDefinedTermSet | anzsrc-for: |
130 | ″ | schema:name | Oceanography |
131 | ″ | rdf:type | schema:DefinedTerm |
132 | sg:journal.1049631 | schema:issn | 0930-7575 |
133 | ″ | ″ | 1432-0894 |
134 | ″ | schema:name | Climate Dynamics |
135 | ″ | schema:publisher | Springer Nature |
136 | ″ | rdf:type | schema:Periodical |
137 | sg:person.010755512233.85 | schema:affiliation | grid-institutes:grid.436330.1 |
138 | ″ | schema:familyName | Chatterjee |
139 | ″ | schema:givenName | Abhisek |
140 | ″ | schema:sameAs | https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010755512233.85 |
141 | ″ | rdf:type | schema:Person |
142 | sg:person.011737006645.02 | schema:affiliation | grid-institutes:grid.436330.1 |
143 | ″ | schema:familyName | Shankar |
144 | ″ | schema:givenName | D. |
145 | ″ | schema:sameAs | https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011737006645.02 |
146 | ″ | rdf:type | schema:Person |
147 | sg:person.016040443345.26 | schema:affiliation | grid-institutes:grid.436330.1 |
148 | ″ | schema:familyName | Mukherjee |
149 | ″ | schema:givenName | A. |
150 | ″ | schema:sameAs | https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016040443345.26 |
151 | ″ | rdf:type | schema:Person |
152 | sg:person.016113470637.60 | schema:affiliation | grid-institutes:grid.34980.36 |
153 | ″ | schema:familyName | Vinayachandran |
154 | ″ | schema:givenName | P. N. |
155 | ″ | schema:sameAs | https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016113470637.60 |
156 | ″ | rdf:type | schema:Person |
157 | sg:pub.10.1007/bf02744586 | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1004267261 |
158 | ″ | ″ | https://doi.org/10.1007/bf02744586 |
159 | ″ | rdf:type | schema:CreativeWork |
160 | sg:pub.10.1007/s10872-008-0069-2 | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1030185843 |
161 | ″ | ″ | https://doi.org/10.1007/s10872-008-0069-2 |
162 | ″ | rdf:type | schema:CreativeWork |
163 | sg:pub.10.1007/s12040-007-0025-3 | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1022343975 |
164 | ″ | ″ | https://doi.org/10.1007/s12040-007-0025-3 |
165 | ″ | rdf:type | schema:CreativeWork |
166 | sg:pub.10.1007/s12040-007-0030-6 | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1053197588 |
167 | ″ | ″ | https://doi.org/10.1007/s12040-007-0030-6 |
168 | ″ | rdf:type | schema:CreativeWork |
169 | sg:pub.10.1007/s12040-012-0191-9 | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1028595004 |
170 | ″ | ″ | https://doi.org/10.1007/s12040-012-0191-9 |
171 | ″ | rdf:type | schema:CreativeWork |
172 | sg:pub.10.1007/s12040-012-0258-7 | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1002333848 |
173 | ″ | ″ | https://doi.org/10.1007/s12040-012-0258-7 |
174 | ″ | rdf:type | schema:CreativeWork |
175 | sg:pub.10.1007/s12040-014-0449-5 | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1029262368 |
176 | ″ | ″ | https://doi.org/10.1007/s12040-014-0449-5 |
177 | ″ | rdf:type | schema:CreativeWork |
178 | sg:pub.10.1007/s12040-014-0471-7 | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1014500824 |
179 | ″ | ″ | https://doi.org/10.1007/s12040-014-0471-7 |
180 | ″ | rdf:type | schema:CreativeWork |
181 | grid-institutes:grid.34980.36 | schema:alternateName | Centre for Atmospheric and Oceanic Sciences, Indian Institute of Science, Bengaluru, India |
182 | ″ | schema:name | Centre for Atmospheric and Oceanic Sciences, Indian Institute of Science, Bengaluru, India |
183 | ″ | rdf:type | schema:Organization |
184 | grid-institutes:grid.436330.1 | schema:alternateName | CSIR-National Institute of Oceanography, Goa, India |
185 | ″ | schema:name | CSIR-National Institute of Oceanography, Goa, India |
186 | ″ | ″ | ESSO-Indian National Centre for Ocean Information Services (INCOIS), Hyderabad, India |
187 | ″ | rdf:type | schema:Organization |