Relationship of Tsunami Intensity to Source Earthquake Magnitude as Retrieved from Historical Data View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2011-11

AUTHORS

Viacheslav K. Gusiakov

ABSTRACT

Operational prediction of near-field tsunamis in all existing Tsunami Warning Systems (TWSs) is based on fast determination of the position and size of submarine earthquakes. Exceedance of earthquake magnitude above some established threshold value, which can vary over different tsunamigenic zones, results in issuing a warning signal. Usually, a warning message has several (from 2 to 5) grades reflecting the degree of tsunami danger and sometimes contains expected wave heights at the coast. Current operational methodology is based on two main assumptions: (1) submarine earthquakes above some threshold magnitude can generate dangerous tsunamis and (2) the height of a resultant tsunami is, in general, proportional to the earthquake magnitude. While both assumptions are physically reasonable and generally correct, statistics of issued warnings are far from being satisfactory. For the last 55 years, up to 75% of warnings for regional tsunamis have turned out to be false, while each TWS has had at least a few cases of missing dangerous tsunamis. This paper presents the results of investigating the actual dependence of tsunami intensity on earthquake magnitude as it can be retrieved from historical observations and discusses the degree of correspondence of the above assumptions to real observations. Tsunami intensity, based on the Soloviev-Imamura scale is used as a measure of tsunami “size”. Its correlation with the Ms and Mw magnitudes is investigated based on historical data available for the instrumental period of observations (from 1900 to present). More... »

PAGES

2033-2041

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00024-011-0286-2

DOI

http://dx.doi.org/10.1007/s00024-011-0286-2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1042937042


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

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/2008/0404", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Geophysics", 
        "type": "DefinedTerm"
      }, 
      {
        "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"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Institute of Computational Mathematics and Mathematical Geophysics", 
          "id": "https://www.grid.ac/institutes/grid.465353.2", 
          "name": [
            "Institute of Computational Mathematics and Mathematical Geophysics, Siberian Division, Russian Academy of Sciences, Pr Lavrentieva, 6, 630090, Novosibirsk, Russia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Gusiakov", 
        "givenName": "Viacheslav K.", 
        "id": "sg:person.015652507131.69", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015652507131.69"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/0031-9201(72)90058-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006216000"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0031-9201(72)90058-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006216000"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/jb084ib05p02303", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050559580"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2011-11", 
    "datePublishedReg": "2011-11-01", 
    "description": "Operational prediction of near-field tsunamis in all existing Tsunami Warning Systems (TWSs) is based on fast determination of the position and size of submarine earthquakes. Exceedance of earthquake magnitude above some established threshold value, which can vary over different tsunamigenic zones, results in issuing a warning signal. Usually, a warning message has several (from 2 to 5) grades reflecting the degree of tsunami danger and sometimes contains expected wave heights at the coast. Current operational methodology is based on two main assumptions: (1) submarine earthquakes above some threshold magnitude can generate dangerous tsunamis and (2) the height of a resultant tsunami is, in general, proportional to the earthquake magnitude. While both assumptions are physically reasonable and generally correct, statistics of issued warnings are far from being satisfactory. For the last 55 years, up to 75% of warnings for regional tsunamis have turned out to be false, while each TWS has had at least a few cases of missing dangerous tsunamis. This paper presents the results of investigating the actual dependence of tsunami intensity on earthquake magnitude as it can be retrieved from historical observations and discusses the degree of correspondence of the above assumptions to real observations. Tsunami intensity, based on the Soloviev-Imamura scale is used as a measure of tsunami \u201csize\u201d. Its correlation with the Ms and Mw magnitudes is investigated based on historical data available for the instrumental period of observations (from 1900 to present).", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s00024-011-0286-2", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.5360105", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.5372631", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1136817", 
        "issn": [
          "0033-4553", 
          "1420-9136"
        ], 
        "name": "Pure and Applied Geophysics", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "11", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "168"
      }
    ], 
    "name": "Relationship of Tsunami Intensity to Source Earthquake Magnitude as Retrieved from Historical Data", 
    "pagination": "2033-2041", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "cc862ab861649d67f05414b6cb75b3512389bb764a8a3745e4efe9fba32ea836"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s00024-011-0286-2"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1042937042"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s00024-011-0286-2", 
      "https://app.dimensions.ai/details/publication/pub.1042937042"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T19:05", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8678_00000496.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007/s00024-011-0286-2"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

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/s00024-011-0286-2'

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/s00024-011-0286-2'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00024-011-0286-2'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00024-011-0286-2'


 

This table displays all metadata directly associated to this object as RDF triples.

71 TRIPLES      21 PREDICATES      29 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s00024-011-0286-2 schema:about anzsrc-for:04
2 anzsrc-for:0404
3 schema:author Nff2177b70baa49fdb4761aef7dc1bc2e
4 schema:citation https://doi.org/10.1016/0031-9201(72)90058-1
5 https://doi.org/10.1029/jb084ib05p02303
6 schema:datePublished 2011-11
7 schema:datePublishedReg 2011-11-01
8 schema:description Operational prediction of near-field tsunamis in all existing Tsunami Warning Systems (TWSs) is based on fast determination of the position and size of submarine earthquakes. Exceedance of earthquake magnitude above some established threshold value, which can vary over different tsunamigenic zones, results in issuing a warning signal. Usually, a warning message has several (from 2 to 5) grades reflecting the degree of tsunami danger and sometimes contains expected wave heights at the coast. Current operational methodology is based on two main assumptions: (1) submarine earthquakes above some threshold magnitude can generate dangerous tsunamis and (2) the height of a resultant tsunami is, in general, proportional to the earthquake magnitude. While both assumptions are physically reasonable and generally correct, statistics of issued warnings are far from being satisfactory. For the last 55 years, up to 75% of warnings for regional tsunamis have turned out to be false, while each TWS has had at least a few cases of missing dangerous tsunamis. This paper presents the results of investigating the actual dependence of tsunami intensity on earthquake magnitude as it can be retrieved from historical observations and discusses the degree of correspondence of the above assumptions to real observations. Tsunami intensity, based on the Soloviev-Imamura scale is used as a measure of tsunami “size”. Its correlation with the Ms and Mw magnitudes is investigated based on historical data available for the instrumental period of observations (from 1900 to present).
9 schema:genre research_article
10 schema:inLanguage en
11 schema:isAccessibleForFree false
12 schema:isPartOf N4b2aa74170274677beea5ff864da1902
13 N5935d3ddf3e749f9b0b0c96a699d7e8b
14 sg:journal.1136817
15 schema:name Relationship of Tsunami Intensity to Source Earthquake Magnitude as Retrieved from Historical Data
16 schema:pagination 2033-2041
17 schema:productId N3e77e08ac375495face1c2d895424650
18 Nea7529d227954c939d6bda9d0dbbef2d
19 Nf5cba91e3e524d1092a377f92ffba1a8
20 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042937042
21 https://doi.org/10.1007/s00024-011-0286-2
22 schema:sdDatePublished 2019-04-10T19:05
23 schema:sdLicense https://scigraph.springernature.com/explorer/license/
24 schema:sdPublisher N2106fe0a5e034e57a7f75d57eee74c24
25 schema:url http://link.springer.com/10.1007/s00024-011-0286-2
26 sgo:license sg:explorer/license/
27 sgo:sdDataset articles
28 rdf:type schema:ScholarlyArticle
29 N2106fe0a5e034e57a7f75d57eee74c24 schema:name Springer Nature - SN SciGraph project
30 rdf:type schema:Organization
31 N3e77e08ac375495face1c2d895424650 schema:name dimensions_id
32 schema:value pub.1042937042
33 rdf:type schema:PropertyValue
34 N4b2aa74170274677beea5ff864da1902 schema:issueNumber 11
35 rdf:type schema:PublicationIssue
36 N5935d3ddf3e749f9b0b0c96a699d7e8b schema:volumeNumber 168
37 rdf:type schema:PublicationVolume
38 Nea7529d227954c939d6bda9d0dbbef2d schema:name readcube_id
39 schema:value cc862ab861649d67f05414b6cb75b3512389bb764a8a3745e4efe9fba32ea836
40 rdf:type schema:PropertyValue
41 Nf5cba91e3e524d1092a377f92ffba1a8 schema:name doi
42 schema:value 10.1007/s00024-011-0286-2
43 rdf:type schema:PropertyValue
44 Nff2177b70baa49fdb4761aef7dc1bc2e rdf:first sg:person.015652507131.69
45 rdf:rest rdf:nil
46 anzsrc-for:04 schema:inDefinedTermSet anzsrc-for:
47 schema:name Earth Sciences
48 rdf:type schema:DefinedTerm
49 anzsrc-for:0404 schema:inDefinedTermSet anzsrc-for:
50 schema:name Geophysics
51 rdf:type schema:DefinedTerm
52 sg:grant.5360105 http://pending.schema.org/fundedItem sg:pub.10.1007/s00024-011-0286-2
53 rdf:type schema:MonetaryGrant
54 sg:grant.5372631 http://pending.schema.org/fundedItem sg:pub.10.1007/s00024-011-0286-2
55 rdf:type schema:MonetaryGrant
56 sg:journal.1136817 schema:issn 0033-4553
57 1420-9136
58 schema:name Pure and Applied Geophysics
59 rdf:type schema:Periodical
60 sg:person.015652507131.69 schema:affiliation https://www.grid.ac/institutes/grid.465353.2
61 schema:familyName Gusiakov
62 schema:givenName Viacheslav K.
63 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015652507131.69
64 rdf:type schema:Person
65 https://doi.org/10.1016/0031-9201(72)90058-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006216000
66 rdf:type schema:CreativeWork
67 https://doi.org/10.1029/jb084ib05p02303 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050559580
68 rdf:type schema:CreativeWork
69 https://www.grid.ac/institutes/grid.465353.2 schema:alternateName Institute of Computational Mathematics and Mathematical Geophysics
70 schema:name Institute of Computational Mathematics and Mathematical Geophysics, Siberian Division, Russian Academy of Sciences, Pr Lavrentieva, 6, 630090, Novosibirsk, Russia
71 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...