Ontology type: schema:ScholarlyArticle Open Access: True
2021-12-14
AUTHORSLinh N. Luu, Paolo Scussolini, Sarah Kew, Sjoukje Philip, Mugni Hadi Hariadi, Robert Vautard, Khiem Van Mai, Thang Van Vu, Kien Ba Truong, Friederike Otto, Gerard van der Schrier, Maarten K. van Aalst, Geert Jan van Oldenborgh
ABSTRACTIn October 2020, Central Vietnam was struck by heavy rain resulting from a sequence of 5 tropical depressions and typhoons. The immense amount of water led to extensive flooding and landslides that killed more than 200 people, injured more than 500 people, and caused direct damages valued at approximately 1.2 billion USD. Here, we quantify how the intensity of the precipitation leading to such exceptional impacts is attributable to anthropogenic climate change. First, we define the event as the regional maximum of annual maximum 15-day average rainfall (Rx15day). We then analyse the trend in Rx15day over Central Vietnam from the observations and simulations in the PRIMAVERA and CORDEX-CORE ensembles, which pass our evaluation tests, by applying the generalised extreme value (GEV) distribution in which location and scale parameters exponentially covary with increasing global temperatures. Combining these observations and model results, we find that the 2020 event, occurring about once every 80 years (at least 17 years), has not changed in either probability of occurrence (a factor 1.0, ranging from 0.4 to 2.4) or intensity (0%, ranging from −8 to +8%) in the present climate in comparison with early-industrial climate. This implies that the effect of human-induced climate change contributing to this persistent extreme rainfall event is small compared to natural variability. However, given the scale of damage of this hazard, our results underline that more investment in disaster risk reduction for this type of rainfall-induced flood hazard is of importance, even independent of the effect of anthropogenic climate change. Moreover, as both observations and model simulations will be extended with the passage of time, we encourage more climate change impact investigations on the extreme in the future that help adaptation and mitigation plans and raise awareness in the country. More... »
PAGES24
http://scigraph.springernature.com/pub.10.1007/s10584-021-03261-3
DOIhttp://dx.doi.org/10.1007/s10584-021-03261-3
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1143851428
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/2008/0401",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Atmospheric Sciences",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0406",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Physical Geography and Environmental Geoscience",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "Vietnam Institute of Meteorology Hydrology and Climate Change, Hanoi, Vietnam",
"id": "http://www.grid.ac/institutes/None",
"name": [
"Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands",
"Vietnam Institute of Meteorology Hydrology and Climate Change, Hanoi, Vietnam"
],
"type": "Organization"
},
"familyName": "Luu",
"givenName": "Linh N.",
"id": "sg:person.013617357062.81",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013617357062.81"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Institute for Environmental Studies, Vrije Universiteit Amsterdam, Amsterdam, Netherlands",
"id": "http://www.grid.ac/institutes/grid.12380.38",
"name": [
"Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands",
"Institute for Environmental Studies, Vrije Universiteit Amsterdam, Amsterdam, Netherlands"
],
"type": "Organization"
},
"familyName": "Scussolini",
"givenName": "Paolo",
"id": "sg:person.01175513306.41",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01175513306.41"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands",
"id": "http://www.grid.ac/institutes/grid.8653.8",
"name": [
"Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands"
],
"type": "Organization"
},
"familyName": "Kew",
"givenName": "Sarah",
"id": "sg:person.012576657501.96",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012576657501.96"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands",
"id": "http://www.grid.ac/institutes/grid.8653.8",
"name": [
"Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands"
],
"type": "Organization"
},
"familyName": "Philip",
"givenName": "Sjoukje",
"id": "sg:person.014116526631.03",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014116526631.03"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands",
"id": "http://www.grid.ac/institutes/grid.8653.8",
"name": [
"Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands"
],
"type": "Organization"
},
"familyName": "Hariadi",
"givenName": "Mugni Hadi",
"id": "sg:person.013417612611.26",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013417612611.26"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Laboratoire des Sciences du Climat et de l\u2019Environnement, UMR 8212 CEA-CNRS-UVSQ, Universit\u00e9 Paris-Saclay and IPSL, Gif-sur-Yvette, France",
"id": "http://www.grid.ac/institutes/grid.457340.1",
"name": [
"Laboratoire des Sciences du Climat et de l\u2019Environnement, UMR 8212 CEA-CNRS-UVSQ, Universit\u00e9 Paris-Saclay and IPSL, Gif-sur-Yvette, France"
],
"type": "Organization"
},
"familyName": "Vautard",
"givenName": "Robert",
"id": "sg:person.0637243716.97",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0637243716.97"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "National Centre for Hydro - Meteorological Forecasting, Hanoi, Vietnam",
"id": "http://www.grid.ac/institutes/None",
"name": [
"National Centre for Hydro - Meteorological Forecasting, Hanoi, Vietnam"
],
"type": "Organization"
},
"familyName": "Van Mai",
"givenName": "Khiem",
"type": "Person"
},
{
"affiliation": {
"alternateName": "Vietnam Institute of Meteorology Hydrology and Climate Change, Hanoi, Vietnam",
"id": "http://www.grid.ac/institutes/None",
"name": [
"Vietnam Institute of Meteorology Hydrology and Climate Change, Hanoi, Vietnam"
],
"type": "Organization"
},
"familyName": "Van Vu",
"givenName": "Thang",
"id": "sg:person.015251066270.22",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015251066270.22"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Vietnam Institute of Meteorology Hydrology and Climate Change, Hanoi, Vietnam",
"id": "http://www.grid.ac/institutes/None",
"name": [
"Vietnam Institute of Meteorology Hydrology and Climate Change, Hanoi, Vietnam"
],
"type": "Organization"
},
"familyName": "Truong",
"givenName": "Kien Ba",
"id": "sg:person.015013617450.34",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015013617450.34"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Grantham Institute, Imperial College London, London, UK",
"id": "http://www.grid.ac/institutes/grid.7445.2",
"name": [
"Grantham Institute, Imperial College London, London, UK"
],
"type": "Organization"
},
"familyName": "Otto",
"givenName": "Friederike",
"id": "sg:person.01326463237.80",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01326463237.80"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands",
"id": "http://www.grid.ac/institutes/grid.8653.8",
"name": [
"Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands"
],
"type": "Organization"
},
"familyName": "van der Schrier",
"givenName": "Gerard",
"id": "sg:person.011357474467.78",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011357474467.78"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "International Research Institute for Climate and Society, Columbia University, New York, NY, USA",
"id": "http://www.grid.ac/institutes/grid.21729.3f",
"name": [
"Faculty of Geo-information Science and Earth Observation, University of Twente, Enschede, The Netherlands",
"Red Cross Red Crescent Climate Centre, The Hague, The Netherlands",
"International Research Institute for Climate and Society, Columbia University, New York, NY, USA"
],
"type": "Organization"
},
"familyName": "van Aalst",
"givenName": "Maarten K.",
"id": "sg:person.014603673361.32",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014603673361.32"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands",
"id": "http://www.grid.ac/institutes/grid.8653.8",
"name": [
"Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands"
],
"type": "Organization"
},
"familyName": "van Oldenborgh",
"givenName": "Geert Jan",
"id": "sg:person.014342146261.81",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014342146261.81"
],
"type": "Person"
}
],
"citation": [
{
"id": "sg:pub.10.1007/s10584-017-1906-3",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1083420168",
"https://doi.org/10.1007/s10584-017-1906-3"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00382-021-05671-6",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1135138646",
"https://doi.org/10.1007/s00382-021-05671-6"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00382-020-05494-x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1132474141",
"https://doi.org/10.1007/s00382-020-05494-x"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11069-018-3202-6",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1101017573",
"https://doi.org/10.1007/s11069-018-3202-6"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s10584-018-2252-9",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1105601377",
"https://doi.org/10.1007/s10584-018-2252-9"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/s41467-018-07882-8",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1110929190",
"https://doi.org/10.1038/s41467-018-07882-8"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/s41598-020-73508-z",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1131429789",
"https://doi.org/10.1038/s41598-020-73508-z"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/s41586-018-0673-2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1109832848",
"https://doi.org/10.1038/s41586-018-0673-2"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00382-021-05728-6",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1136956491",
"https://doi.org/10.1007/s00382-021-05728-6"
],
"type": "CreativeWork"
}
],
"datePublished": "2021-12-14",
"datePublishedReg": "2021-12-14",
"description": "In October 2020, Central Vietnam was struck by heavy rain resulting from a sequence of 5 tropical depressions and typhoons. The immense amount of water led to extensive flooding and landslides that killed more than 200 people, injured more than 500 people, and caused direct damages valued at approximately 1.2 billion USD. Here, we quantify how the intensity of the precipitation leading to such exceptional impacts is attributable to anthropogenic climate change. First, we define the event as the regional maximum of annual maximum 15-day average rainfall (Rx15day). We then analyse the trend in Rx15day over Central Vietnam from the observations and simulations in the PRIMAVERA and CORDEX-CORE ensembles, which pass our evaluation tests, by applying the generalised extreme value (GEV) distribution in which location and scale parameters exponentially covary with increasing global temperatures. Combining these observations and model results, we find that the 2020 event, occurring about once every 80 years (at least 17 years), has not changed in either probability of occurrence (a factor 1.0, ranging from 0.4 to 2.4) or intensity (0%, ranging from \u22128 to +8%) in the present climate in comparison with early-industrial climate. This implies that the effect of human-induced climate change contributing to this persistent extreme rainfall event is small compared to natural variability. However, given the scale of damage of this hazard, our results underline that more investment in disaster risk reduction for this type of rainfall-induced flood hazard is of importance, even independent of the effect of anthropogenic climate change. Moreover, as both observations and model simulations will be extended with the passage of time, we encourage more climate change impact investigations on the extreme in the future that help adaptation and mitigation plans and raise awareness in the country.",
"genre": "article",
"id": "sg:pub.10.1007/s10584-021-03261-3",
"inLanguage": "en",
"isAccessibleForFree": true,
"isPartOf": [
{
"id": "sg:journal.1028211",
"issn": [
"0165-0009",
"1573-1480"
],
"name": "Climatic Change",
"publisher": "Springer Nature",
"type": "Periodical"
},
{
"issueNumber": "3-4",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "169"
}
],
"keywords": [
"anthropogenic climate change",
"climate change",
"central Vietnam",
"human-induced climate change",
"extreme rainfall events",
"generalised extreme value distribution",
"torrential precipitation",
"present climate",
"tropical depression",
"rainfall events",
"natural variability",
"flood hazard",
"extensive flooding",
"model simulations",
"average rainfall",
"global temperature",
"extreme value distribution",
"regional maxima",
"heavy rain",
"model results",
"probability of occurrence",
"impact investigation",
"mitigation plans",
"scale of damage",
"disaster risk reduction",
"precipitation",
"climate",
"value distribution",
"exceptional impact",
"events",
"hazards",
"rainfall",
"typhoons",
"landslides",
"rain",
"flooding",
"extremes",
"variability",
"Vietnam",
"water",
"changes",
"ensemble",
"Primavera",
"intensity",
"maximum",
"occurrence",
"trends",
"simulations",
"immense amount",
"location",
"scale",
"attribution",
"distribution",
"temperature",
"passage",
"risk reduction",
"direct damage",
"scale parameter",
"impact",
"sequence",
"amount",
"years",
"future",
"results",
"comparison",
"importance",
"depression",
"investigation",
"time",
"passage of time",
"more investment",
"parameters",
"types",
"effect",
"probability",
"plan",
"damage",
"reduction",
"adaptation",
"USD",
"countries",
"test",
"evaluation tests",
"people",
"investment",
"awareness",
"observations"
],
"name": "Attribution of typhoon-induced torrential precipitation in Central Vietnam, October 2020",
"pagination": "24",
"productId": [
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1143851428"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1007/s10584-021-03261-3"
]
}
],
"sameAs": [
"https://doi.org/10.1007/s10584-021-03261-3",
"https://app.dimensions.ai/details/publication/pub.1143851428"
],
"sdDataset": "articles",
"sdDatePublished": "2022-05-20T07:38",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-springernature-scigraph/baseset/20220519/entities/gbq_results/article/article_893.jsonl",
"type": "ScholarlyArticle",
"url": "https://doi.org/10.1007/s10584-021-03261-3"
}
]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/s10584-021-03261-3'
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/s10584-021-03261-3'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10584-021-03261-3'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10584-021-03261-3'
This table displays all metadata directly associated to this object as RDF triples.
289 TRIPLES
22 PREDICATES
122 URIs
104 LITERALS
6 BLANK NODES