ClimateEU, scale-free climate normals, historical time series, and future projections for Europe View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2020-12-04

AUTHORS

Maurizio Marchi, Dante Castellanos-Acuña, Andreas Hamann, Tongli Wang, Duncan Ray, Annette Menzel

ABSTRACT

Interpolated climate data have become essential for regional or local climate change impact assessments and the development of climate change adaptation strategies. Here, we contribute an accessible, comprehensive database of interpolated climate data for Europe that includes monthly, annual, decadal, and 30-year normal climate data for the last 119 years (1901 to 2019) as well as multi-model CMIP5 climate change projections for the 21st century. The database also includes variables relevant for ecological research and infrastructure planning, comprising more than 20,000 climate grids that can be queried with a provided ClimateEU software package. In addition, 1 km and 2.5 km resolution gridded data generated by the software are available for download. The quality of ClimateEU estimates was evaluated against weather station data for a representative subset of climate variables. Dynamic environmental lapse rate algorithms employed by the software to generate scale-free climate variables for specific locations lead to improvements of 10 to 50% in accuracy compared to gridded data. We conclude with a discussion of applications and limitations of this database. More... »

PAGES

428

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41597-020-00763-0

DOI

http://dx.doi.org/10.1038/s41597-020-00763-0

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1133089047

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/33277489


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/2008/04", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Earth Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing 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/2008/0806", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information Systems", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "CNR - Institute of Biosciences and BioResources (IBBR), Florence division, Via Madonna del Piano 10, I-50019 Sesto Fiorentino (Florence), Italy", 
          "id": "http://www.grid.ac/institutes/None", 
          "name": [
            "CNR - Institute of Biosciences and BioResources (IBBR), Florence division, Via Madonna del Piano 10, I-50019 Sesto Fiorentino (Florence), Italy"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Marchi", 
        "givenName": "Maurizio", 
        "id": "sg:person.016247371162.63", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016247371162.63"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Renewable Resources, University of Alberta, 751 General Services Building, Edmonton, AB T6G 2H1 Canada", 
          "id": "http://www.grid.ac/institutes/grid.17089.37", 
          "name": [
            "Department of Renewable Resources, University of Alberta, 751 General Services Building, Edmonton, AB T6G 2H1 Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Castellanos-Acu\u00f1a", 
        "givenName": "Dante", 
        "id": "sg:person.012734674606.54", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012734674606.54"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Renewable Resources, University of Alberta, 751 General Services Building, Edmonton, AB T6G 2H1 Canada", 
          "id": "http://www.grid.ac/institutes/grid.17089.37", 
          "name": [
            "Department of Renewable Resources, University of Alberta, 751 General Services Building, Edmonton, AB T6G 2H1 Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hamann", 
        "givenName": "Andreas", 
        "id": "sg:person.01262175510.96", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01262175510.96"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Centre for Forest Conservation Genetics, Department of Forest and Conservation Sciences, University of British Columbia, Vancouver, BC V6T 1Z4 Canada", 
          "id": "http://www.grid.ac/institutes/grid.17091.3e", 
          "name": [
            "Centre for Forest Conservation Genetics, Department of Forest and Conservation Sciences, University of British Columbia, Vancouver, BC V6T 1Z4 Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Wang", 
        "givenName": "Tongli", 
        "id": "sg:person.0610307552.05", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0610307552.05"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Forest Research, Northern Research Station, Roslin, Midlothian, Scotland United Kingdom", 
          "id": "http://www.grid.ac/institutes/grid.479676.d", 
          "name": [
            "Forest Research, Northern Research Station, Roslin, Midlothian, Scotland United Kingdom"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ray", 
        "givenName": "Duncan", 
        "id": "sg:person.015003751127.90", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015003751127.90"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Ecology and Ecosystem Management, Technical University of Munich, 85354 Freising, Germany", 
          "id": "http://www.grid.ac/institutes/grid.6936.a", 
          "name": [
            "Department of Ecology and Ecosystem Management, Technical University of Munich, 85354 Freising, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Menzel", 
        "givenName": "Annette", 
        "id": "sg:person.01115715530.48", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01115715530.48"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1038/s41597-020-0453-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1126104248", 
          "https://doi.org/10.1038/s41597-020-0453-3"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2020-12-04", 
    "datePublishedReg": "2020-12-04", 
    "description": "Interpolated climate data have become essential for regional or local climate change impact assessments and the development of climate change adaptation strategies. Here, we contribute an accessible, comprehensive database of interpolated climate data for Europe that includes monthly, annual, decadal, and 30-year normal climate data for the last 119 years (1901 to 2019) as well as multi-model CMIP5 climate change projections for the 21st century. The database also includes variables relevant for ecological research and infrastructure planning, comprising more than 20,000 climate grids that can be queried with a provided ClimateEU software package. In addition, 1\u2009km and 2.5\u2009km resolution gridded data generated by the software are available for download. The quality of ClimateEU estimates was evaluated against weather station data for a representative subset of climate variables. Dynamic environmental lapse rate algorithms employed by the software to generate scale-free climate variables for specific locations lead to improvements of 10 to 50% in accuracy compared to gridded data. We conclude with a discussion of applications and limitations of this database.", 
    "genre": "article", 
    "id": "sg:pub.10.1038/s41597-020-00763-0", 
    "inLanguage": "en", 
    "isAccessibleForFree": true, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.7553117", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1050678", 
        "issn": [
          "2052-4463"
        ], 
        "name": "Scientific Data", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "7"
      }
    ], 
    "keywords": [
      "climate data", 
      "climate variables", 
      "climate change impact assessment", 
      "climate change projections", 
      "change impact assessment", 
      "weather station data", 
      "climate change adaptation strategies", 
      "change adaptation strategies", 
      "change projections", 
      "historical time series", 
      "station data", 
      "future projections", 
      "climate normals", 
      "climate grids", 
      "adaptation strategies", 
      "time series", 
      "impact assessment", 
      "infrastructure planning", 
      "specific locations", 
      "rate algorithm", 
      "projections", 
      "ecological research", 
      "software package", 
      "Europe", 
      "data", 
      "comprehensive database", 
      "representative subset", 
      "software", 
      "estimates", 
      "discussion of applications", 
      "location", 
      "century", 
      "database", 
      "resolution", 
      "download", 
      "algorithm", 
      "series", 
      "grid", 
      "variables", 
      "accuracy", 
      "years", 
      "package", 
      "planning", 
      "applications", 
      "assessment", 
      "quality", 
      "limitations", 
      "subset", 
      "development", 
      "research", 
      "improvement", 
      "addition", 
      "strategies", 
      "discussion", 
      "normals", 
      "sup", 
      "local climate change impact assessments", 
      "normal climate data", 
      "multi-model CMIP5 climate change projections", 
      "CMIP5 climate change projections", 
      "ClimateEU software package", 
      "ClimateEU estimates", 
      "Dynamic environmental lapse rate algorithms", 
      "environmental lapse rate algorithms", 
      "lapse rate algorithms", 
      "scale-free climate variables", 
      "ClimateEU", 
      "scale-free climate normals"
    ], 
    "name": "ClimateEU, scale-free climate normals, historical time series, and future projections for Europe", 
    "pagination": "428", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1133089047"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1038/s41597-020-00763-0"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "33277489"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1038/s41597-020-00763-0", 
      "https://app.dimensions.ai/details/publication/pub.1133089047"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-01-01T19:00", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220101/entities/gbq_results/article/article_870.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1038/s41597-020-00763-0"
  }
]
 

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.10.1038/s41597-020-00763-0'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/s41597-020-00763-0'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/s41597-020-00763-0'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/s41597-020-00763-0'


 

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

190 TRIPLES      22 PREDICATES      97 URIs      86 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1038/s41597-020-00763-0 schema:about anzsrc-for:04
2 anzsrc-for:0401
3 anzsrc-for:08
4 anzsrc-for:0806
5 schema:author N83a2f8b4c314434dbc7555fe50d5edc4
6 schema:citation sg:pub.10.1038/s41597-020-0453-3
7 schema:datePublished 2020-12-04
8 schema:datePublishedReg 2020-12-04
9 schema:description Interpolated climate data have become essential for regional or local climate change impact assessments and the development of climate change adaptation strategies. Here, we contribute an accessible, comprehensive database of interpolated climate data for Europe that includes monthly, annual, decadal, and 30-year normal climate data for the last 119 years (1901 to 2019) as well as multi-model CMIP5 climate change projections for the 21<sup>st</sup> century. The database also includes variables relevant for ecological research and infrastructure planning, comprising more than 20,000 climate grids that can be queried with a provided ClimateEU software package. In addition, 1 km and 2.5 km resolution gridded data generated by the software are available for download. The quality of ClimateEU estimates was evaluated against weather station data for a representative subset of climate variables. Dynamic environmental lapse rate algorithms employed by the software to generate scale-free climate variables for specific locations lead to improvements of 10 to 50% in accuracy compared to gridded data. We conclude with a discussion of applications and limitations of this database.
10 schema:genre article
11 schema:inLanguage en
12 schema:isAccessibleForFree true
13 schema:isPartOf N53795b52f8714bcca75a57b94ac4265f
14 N71a0214e451b4b59887dfbd7d9388653
15 sg:journal.1050678
16 schema:keywords CMIP5 climate change projections
17 ClimateEU
18 ClimateEU estimates
19 ClimateEU software package
20 Dynamic environmental lapse rate algorithms
21 Europe
22 accuracy
23 adaptation strategies
24 addition
25 algorithm
26 applications
27 assessment
28 century
29 change adaptation strategies
30 change impact assessment
31 change projections
32 climate change adaptation strategies
33 climate change impact assessment
34 climate change projections
35 climate data
36 climate grids
37 climate normals
38 climate variables
39 comprehensive database
40 data
41 database
42 development
43 discussion
44 discussion of applications
45 download
46 ecological research
47 environmental lapse rate algorithms
48 estimates
49 future projections
50 grid
51 historical time series
52 impact assessment
53 improvement
54 infrastructure planning
55 lapse rate algorithms
56 limitations
57 local climate change impact assessments
58 location
59 multi-model CMIP5 climate change projections
60 normal climate data
61 normals
62 package
63 planning
64 projections
65 quality
66 rate algorithm
67 representative subset
68 research
69 resolution
70 scale-free climate normals
71 scale-free climate variables
72 series
73 software
74 software package
75 specific locations
76 station data
77 strategies
78 subset
79 sup
80 time series
81 variables
82 weather station data
83 years
84 schema:name ClimateEU, scale-free climate normals, historical time series, and future projections for Europe
85 schema:pagination 428
86 schema:productId N434421b6b4fe421fa6dfc7c1f7077324
87 N753e572915a846468be3cdecafd205b1
88 Nda2a173206c84598bece07f072d56771
89 schema:sameAs https://app.dimensions.ai/details/publication/pub.1133089047
90 https://doi.org/10.1038/s41597-020-00763-0
91 schema:sdDatePublished 2022-01-01T19:00
92 schema:sdLicense https://scigraph.springernature.com/explorer/license/
93 schema:sdPublisher N92793505384242e6ad258e4315d9099d
94 schema:url https://doi.org/10.1038/s41597-020-00763-0
95 sgo:license sg:explorer/license/
96 sgo:sdDataset articles
97 rdf:type schema:ScholarlyArticle
98 N33888aeae6f54622ba9c3c42db02e0c0 rdf:first sg:person.0610307552.05
99 rdf:rest Na3e4a19a8c5c42a6925032d03ed3ee26
100 N434421b6b4fe421fa6dfc7c1f7077324 schema:name doi
101 schema:value 10.1038/s41597-020-00763-0
102 rdf:type schema:PropertyValue
103 N53795b52f8714bcca75a57b94ac4265f schema:volumeNumber 7
104 rdf:type schema:PublicationVolume
105 N68ee2e72fa484e15a9daf79bd78b6b85 rdf:first sg:person.01115715530.48
106 rdf:rest rdf:nil
107 N71a0214e451b4b59887dfbd7d9388653 schema:issueNumber 1
108 rdf:type schema:PublicationIssue
109 N753e572915a846468be3cdecafd205b1 schema:name dimensions_id
110 schema:value pub.1133089047
111 rdf:type schema:PropertyValue
112 N83a2f8b4c314434dbc7555fe50d5edc4 rdf:first sg:person.016247371162.63
113 rdf:rest Ne58ead82ffb948c58583579ef41097c7
114 N92793505384242e6ad258e4315d9099d schema:name Springer Nature - SN SciGraph project
115 rdf:type schema:Organization
116 Na3e4a19a8c5c42a6925032d03ed3ee26 rdf:first sg:person.015003751127.90
117 rdf:rest N68ee2e72fa484e15a9daf79bd78b6b85
118 Nb76bc6df924849339be3a7758304a721 rdf:first sg:person.01262175510.96
119 rdf:rest N33888aeae6f54622ba9c3c42db02e0c0
120 Nda2a173206c84598bece07f072d56771 schema:name pubmed_id
121 schema:value 33277489
122 rdf:type schema:PropertyValue
123 Ne58ead82ffb948c58583579ef41097c7 rdf:first sg:person.012734674606.54
124 rdf:rest Nb76bc6df924849339be3a7758304a721
125 anzsrc-for:04 schema:inDefinedTermSet anzsrc-for:
126 schema:name Earth Sciences
127 rdf:type schema:DefinedTerm
128 anzsrc-for:0401 schema:inDefinedTermSet anzsrc-for:
129 schema:name Atmospheric Sciences
130 rdf:type schema:DefinedTerm
131 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
132 schema:name Information and Computing Sciences
133 rdf:type schema:DefinedTerm
134 anzsrc-for:0806 schema:inDefinedTermSet anzsrc-for:
135 schema:name Information Systems
136 rdf:type schema:DefinedTerm
137 sg:grant.7553117 http://pending.schema.org/fundedItem sg:pub.10.1038/s41597-020-00763-0
138 rdf:type schema:MonetaryGrant
139 sg:journal.1050678 schema:issn 2052-4463
140 schema:name Scientific Data
141 schema:publisher Springer Nature
142 rdf:type schema:Periodical
143 sg:person.01115715530.48 schema:affiliation grid-institutes:grid.6936.a
144 schema:familyName Menzel
145 schema:givenName Annette
146 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01115715530.48
147 rdf:type schema:Person
148 sg:person.01262175510.96 schema:affiliation grid-institutes:grid.17089.37
149 schema:familyName Hamann
150 schema:givenName Andreas
151 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01262175510.96
152 rdf:type schema:Person
153 sg:person.012734674606.54 schema:affiliation grid-institutes:grid.17089.37
154 schema:familyName Castellanos-Acuña
155 schema:givenName Dante
156 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012734674606.54
157 rdf:type schema:Person
158 sg:person.015003751127.90 schema:affiliation grid-institutes:grid.479676.d
159 schema:familyName Ray
160 schema:givenName Duncan
161 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015003751127.90
162 rdf:type schema:Person
163 sg:person.016247371162.63 schema:affiliation grid-institutes:None
164 schema:familyName Marchi
165 schema:givenName Maurizio
166 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016247371162.63
167 rdf:type schema:Person
168 sg:person.0610307552.05 schema:affiliation grid-institutes:grid.17091.3e
169 schema:familyName Wang
170 schema:givenName Tongli
171 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0610307552.05
172 rdf:type schema:Person
173 sg:pub.10.1038/s41597-020-0453-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1126104248
174 https://doi.org/10.1038/s41597-020-0453-3
175 rdf:type schema:CreativeWork
176 grid-institutes:None schema:alternateName CNR - Institute of Biosciences and BioResources (IBBR), Florence division, Via Madonna del Piano 10, I-50019 Sesto Fiorentino (Florence), Italy
177 schema:name CNR - Institute of Biosciences and BioResources (IBBR), Florence division, Via Madonna del Piano 10, I-50019 Sesto Fiorentino (Florence), Italy
178 rdf:type schema:Organization
179 grid-institutes:grid.17089.37 schema:alternateName Department of Renewable Resources, University of Alberta, 751 General Services Building, Edmonton, AB T6G 2H1 Canada
180 schema:name Department of Renewable Resources, University of Alberta, 751 General Services Building, Edmonton, AB T6G 2H1 Canada
181 rdf:type schema:Organization
182 grid-institutes:grid.17091.3e schema:alternateName Centre for Forest Conservation Genetics, Department of Forest and Conservation Sciences, University of British Columbia, Vancouver, BC V6T 1Z4 Canada
183 schema:name Centre for Forest Conservation Genetics, Department of Forest and Conservation Sciences, University of British Columbia, Vancouver, BC V6T 1Z4 Canada
184 rdf:type schema:Organization
185 grid-institutes:grid.479676.d schema:alternateName Forest Research, Northern Research Station, Roslin, Midlothian, Scotland United Kingdom
186 schema:name Forest Research, Northern Research Station, Roslin, Midlothian, Scotland United Kingdom
187 rdf:type schema:Organization
188 grid-institutes:grid.6936.a schema:alternateName Department of Ecology and Ecosystem Management, Technical University of Munich, 85354 Freising, Germany
189 schema:name Department of Ecology and Ecosystem Management, Technical University of Munich, 85354 Freising, Germany
190 rdf:type schema:Organization
 




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


...