Effective radiative forcing from historical land use change View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2016-08-05

AUTHORS

Timothy Andrews, Richard A. Betts, Ben B. B. Booth, Chris D. Jones, Gareth S. Jones

ABSTRACT

The effective radiative forcing (ERF) from the biogeophysical effects of historical land use change is quantified using the atmospheric component of the Met Office Hadley Centre Earth System model HadGEM2-ES. The global ERF at 2005 relative to 1860 (1700) is −0.4 (−0.5) Wm−2, making it the fourth most important anthropogenic driver of climate change over the historical period (1860–2005) in this model and larger than most other published values. The land use ERF is found to be dominated by increases in the land surface albedo, particularly in North America and Eurasia, and occurs most strongly in the northern hemisphere winter and spring when the effect of unmasking underlying snow, as well as increasing the amount of snow, is at its largest. Increased bare soil fraction enhances the seasonal cycle of atmospheric dust and further enhances the ERF. Clouds are shown to substantially mask the radiative effect of changes in the underlying surface albedo. Coupled atmosphere–ocean simulations forced only with time-varying historical land use change shows substantial global cooling (dT = −0.35 K by 2005) and the climate resistance (ERF/dT = 1.2 Wm−2 K−1) is consistent with the response of the model to increases in CO2 alone. The regional variation in land surface temperature change, in both fixed-SST and coupled atmosphere–ocean simulations, is found to be well correlated with the spatial pattern of the forced change in surface albedo. The forcing-response concept is found to work well for historical land use forcing—at least in our model and when the forcing is quantified by ERF. Our results suggest that land-use changes over the past century may represent a more important driver of historical climate change then previously recognised and an underappreciated source of uncertainty in global forcings and temperature trends over the historical period. More... »

PAGES

3489-3505

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00382-016-3280-7

DOI

http://dx.doi.org/10.1007/s00382-016-3280-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1052491449


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/2008/0405", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Oceanography", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Met Office Hadley Centre, FitzRoy Road, EX1 3PB, Exeter, UK", 
          "id": "http://www.grid.ac/institutes/grid.17100.37", 
          "name": [
            "Met Office Hadley Centre, FitzRoy Road, EX1 3PB, Exeter, UK"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Andrews", 
        "givenName": "Timothy", 
        "id": "sg:person.016440513017.22", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016440513017.22"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Met Office Hadley Centre, FitzRoy Road, EX1 3PB, Exeter, UK", 
          "id": "http://www.grid.ac/institutes/grid.17100.37", 
          "name": [
            "Met Office Hadley Centre, FitzRoy Road, EX1 3PB, Exeter, UK"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Betts", 
        "givenName": "Richard A.", 
        "id": "sg:person.01362076543.08", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01362076543.08"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Met Office Hadley Centre, FitzRoy Road, EX1 3PB, Exeter, UK", 
          "id": "http://www.grid.ac/institutes/grid.17100.37", 
          "name": [
            "Met Office Hadley Centre, FitzRoy Road, EX1 3PB, Exeter, UK"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Booth", 
        "givenName": "Ben B. B.", 
        "id": "sg:person.0704545361.18", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0704545361.18"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Met Office Hadley Centre, FitzRoy Road, EX1 3PB, Exeter, UK", 
          "id": "http://www.grid.ac/institutes/grid.17100.37", 
          "name": [
            "Met Office Hadley Centre, FitzRoy Road, EX1 3PB, Exeter, UK"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Jones", 
        "givenName": "Chris D.", 
        "id": "sg:person.0752721043.33", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0752721043.33"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Met Office Hadley Centre, FitzRoy Road, EX1 3PB, Exeter, UK", 
          "id": "http://www.grid.ac/institutes/grid.17100.37", 
          "name": [
            "Met Office Hadley Centre, FitzRoy Road, EX1 3PB, Exeter, UK"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Jones", 
        "givenName": "Gareth S.", 
        "id": "sg:person.012111414471.07", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012111414471.07"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1038/35041545", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038976212", 
          "https://doi.org/10.1038/35041545"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00382-014-2421-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033339265", 
          "https://doi.org/10.1007/s00382-014-2421-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nclimate1294", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012464699", 
          "https://doi.org/10.1038/nclimate1294"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00382-005-0092-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053155278", 
          "https://doi.org/10.1007/s00382-005-0092-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00382-004-0402-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000675318", 
          "https://doi.org/10.1007/s00382-004-0402-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10584-011-0153-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050130719", 
          "https://doi.org/10.1007/s10584-011-0153-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00382-014-2430-z", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031728932", 
          "https://doi.org/10.1007/s00382-014-2430-z"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature10946", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046726171", 
          "https://doi.org/10.1038/nature10946"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2016-08-05", 
    "datePublishedReg": "2016-08-05", 
    "description": "The effective radiative forcing (ERF) from the biogeophysical effects of historical land use change is quantified using the atmospheric component of the Met Office Hadley Centre Earth System model HadGEM2-ES. The global ERF at 2005 relative to 1860 (1700) is \u22120.4 (\u22120.5)\u00a0Wm\u22122, making it the fourth most important anthropogenic driver of climate change over the historical period (1860\u20132005) in this model and larger than most other published values. The land use ERF is found to be dominated by increases in the land surface albedo, particularly in North America and Eurasia, and occurs most strongly in the northern hemisphere winter and spring when the effect of unmasking underlying snow, as well as increasing the amount of snow, is at its largest. Increased bare soil fraction enhances the seasonal cycle of atmospheric dust and further enhances the ERF. Clouds are shown to substantially mask the radiative effect of changes in the underlying surface albedo. Coupled atmosphere\u2013ocean simulations forced only with time-varying historical land use change shows substantial global cooling (dT\u00a0=\u00a0\u22120.35\u00a0K by 2005) and the climate resistance (ERF/dT\u00a0=\u00a01.2\u00a0Wm\u22122\u00a0K\u22121) is consistent with the response of the model to increases in CO2 alone. The regional variation in land surface temperature change, in both fixed-SST and coupled atmosphere\u2013ocean simulations, is found to be well correlated with the spatial pattern of the forced change in surface albedo. The forcing-response concept is found to work well for historical land use forcing\u2014at least in our model and when the forcing is quantified by ERF. Our results suggest that land-use changes over the past century may represent a more important driver of historical climate change then previously recognised and an underappreciated source of uncertainty in global forcings and temperature trends over the historical period.", 
    "genre": "article", 
    "id": "sg:pub.10.1007/s00382-016-3280-7", 
    "inLanguage": "en", 
    "isAccessibleForFree": false, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.3790347", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.7037241", 
        "type": "MonetaryGrant"
      }
    ], 
    "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": "48"
      }
    ], 
    "keywords": [
      "effective radiative forcing", 
      "historical land use change", 
      "atmosphere-ocean simulations", 
      "land use change", 
      "surface albedo", 
      "use change", 
      "climate change", 
      "land surface temperature change", 
      "surface temperature changes", 
      "Northern Hemisphere winter", 
      "land surface albedo", 
      "amount of snow", 
      "historical period", 
      "bare soil fraction", 
      "important anthropogenic drivers", 
      "historical climate change", 
      "land-use change", 
      "biogeophysical effects", 
      "global cooling", 
      "global forcing", 
      "effective radiative", 
      "atmospheric dust", 
      "atmospheric component", 
      "seasonal cycle", 
      "temperature trends", 
      "radiative forcing", 
      "radiative effects", 
      "forcing", 
      "anthropogenic drivers", 
      "climate resistance", 
      "spatial patterns", 
      "albedo", 
      "temperature changes", 
      "past century", 
      "North America", 
      "regional variation", 
      "snow", 
      "important driver", 
      "soil fractions", 
      "HadGEM2-ES", 
      "Eurasia", 
      "winter", 
      "spring", 
      "radiative", 
      "cooling", 
      "dust", 
      "changes", 
      "drivers", 
      "CO2", 
      "period", 
      "cloud", 
      "America", 
      "variation", 
      "trends", 
      "model", 
      "uncertainty", 
      "simulations", 
      "century", 
      "source", 
      "cycle", 
      "patterns", 
      "increase", 
      "fraction", 
      "amount", 
      "components", 
      "values", 
      "results", 
      "relatives", 
      "effect", 
      "response", 
      "underappreciated source", 
      "concept", 
      "resistance", 
      "Met Office Hadley Centre Earth System model HadGEM2-ES", 
      "Office Hadley Centre Earth System model HadGEM2-ES", 
      "Hadley Centre Earth System model HadGEM2-ES", 
      "Centre Earth System model HadGEM2-ES", 
      "Earth System model HadGEM2-ES", 
      "System model HadGEM2-ES", 
      "model HadGEM2-ES", 
      "global ERF", 
      "land use ERF", 
      "use ERF", 
      "hemisphere winter", 
      "time-varying historical land use change", 
      "substantial global cooling", 
      "forcing-response concept", 
      "historical land use forcing", 
      "land use forcing", 
      "use forcing"
    ], 
    "name": "Effective radiative forcing from historical land use change", 
    "pagination": "3489-3505", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1052491449"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s00382-016-3280-7"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s00382-016-3280-7", 
      "https://app.dimensions.ai/details/publication/pub.1052491449"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2021-12-01T19:35", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20211201/entities/gbq_results/article/article_699.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1007/s00382-016-3280-7"
  }
]
 

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/s00382-016-3280-7'

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/s00382-016-3280-7'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00382-016-3280-7'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00382-016-3280-7'


 

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

212 TRIPLES      22 PREDICATES      123 URIs      107 LITERALS      6 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s00382-016-3280-7 schema:about anzsrc-for:04
2 anzsrc-for:0405
3 schema:author N684de028e1c342b98c155b7046b78e2f
4 schema:citation sg:pub.10.1007/s00382-004-0402-4
5 sg:pub.10.1007/s00382-005-0092-6
6 sg:pub.10.1007/s00382-014-2421-0
7 sg:pub.10.1007/s00382-014-2430-z
8 sg:pub.10.1007/s10584-011-0153-2
9 sg:pub.10.1038/35041545
10 sg:pub.10.1038/nature10946
11 sg:pub.10.1038/nclimate1294
12 schema:datePublished 2016-08-05
13 schema:datePublishedReg 2016-08-05
14 schema:description The effective radiative forcing (ERF) from the biogeophysical effects of historical land use change is quantified using the atmospheric component of the Met Office Hadley Centre Earth System model HadGEM2-ES. The global ERF at 2005 relative to 1860 (1700) is −0.4 (−0.5) Wm−2, making it the fourth most important anthropogenic driver of climate change over the historical period (1860–2005) in this model and larger than most other published values. The land use ERF is found to be dominated by increases in the land surface albedo, particularly in North America and Eurasia, and occurs most strongly in the northern hemisphere winter and spring when the effect of unmasking underlying snow, as well as increasing the amount of snow, is at its largest. Increased bare soil fraction enhances the seasonal cycle of atmospheric dust and further enhances the ERF. Clouds are shown to substantially mask the radiative effect of changes in the underlying surface albedo. Coupled atmosphere–ocean simulations forced only with time-varying historical land use change shows substantial global cooling (dT = −0.35 K by 2005) and the climate resistance (ERF/dT = 1.2 Wm−2 K−1) is consistent with the response of the model to increases in CO2 alone. The regional variation in land surface temperature change, in both fixed-SST and coupled atmosphere–ocean simulations, is found to be well correlated with the spatial pattern of the forced change in surface albedo. The forcing-response concept is found to work well for historical land use forcing—at least in our model and when the forcing is quantified by ERF. Our results suggest that land-use changes over the past century may represent a more important driver of historical climate change then previously recognised and an underappreciated source of uncertainty in global forcings and temperature trends over the historical period.
15 schema:genre article
16 schema:inLanguage en
17 schema:isAccessibleForFree false
18 schema:isPartOf N6effaa4f379c40298e8292632ce70409
19 Nc15205d5a0c640a6bc6b0d338032643c
20 sg:journal.1049631
21 schema:keywords America
22 CO2
23 Centre Earth System model HadGEM2-ES
24 Earth System model HadGEM2-ES
25 Eurasia
26 HadGEM2-ES
27 Hadley Centre Earth System model HadGEM2-ES
28 Met Office Hadley Centre Earth System model HadGEM2-ES
29 North America
30 Northern Hemisphere winter
31 Office Hadley Centre Earth System model HadGEM2-ES
32 System model HadGEM2-ES
33 albedo
34 amount
35 amount of snow
36 anthropogenic drivers
37 atmosphere-ocean simulations
38 atmospheric component
39 atmospheric dust
40 bare soil fraction
41 biogeophysical effects
42 century
43 changes
44 climate change
45 climate resistance
46 cloud
47 components
48 concept
49 cooling
50 cycle
51 drivers
52 dust
53 effect
54 effective radiative
55 effective radiative forcing
56 forcing
57 forcing-response concept
58 fraction
59 global ERF
60 global cooling
61 global forcing
62 hemisphere winter
63 historical climate change
64 historical land use change
65 historical land use forcing
66 historical period
67 important anthropogenic drivers
68 important driver
69 increase
70 land surface albedo
71 land surface temperature change
72 land use ERF
73 land use change
74 land use forcing
75 land-use change
76 model
77 model HadGEM2-ES
78 past century
79 patterns
80 period
81 radiative
82 radiative effects
83 radiative forcing
84 regional variation
85 relatives
86 resistance
87 response
88 results
89 seasonal cycle
90 simulations
91 snow
92 soil fractions
93 source
94 spatial patterns
95 spring
96 substantial global cooling
97 surface albedo
98 surface temperature changes
99 temperature changes
100 temperature trends
101 time-varying historical land use change
102 trends
103 uncertainty
104 underappreciated source
105 use ERF
106 use change
107 use forcing
108 values
109 variation
110 winter
111 schema:name Effective radiative forcing from historical land use change
112 schema:pagination 3489-3505
113 schema:productId N4097b7862a654f099557dbddb76fc02f
114 Nc2fc6f6775724892b834236d7a38689d
115 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052491449
116 https://doi.org/10.1007/s00382-016-3280-7
117 schema:sdDatePublished 2021-12-01T19:35
118 schema:sdLicense https://scigraph.springernature.com/explorer/license/
119 schema:sdPublisher N3ec8832134644348a6730049e9f18436
120 schema:url https://doi.org/10.1007/s00382-016-3280-7
121 sgo:license sg:explorer/license/
122 sgo:sdDataset articles
123 rdf:type schema:ScholarlyArticle
124 N3ec8832134644348a6730049e9f18436 schema:name Springer Nature - SN SciGraph project
125 rdf:type schema:Organization
126 N4097b7862a654f099557dbddb76fc02f schema:name doi
127 schema:value 10.1007/s00382-016-3280-7
128 rdf:type schema:PropertyValue
129 N59eed187098b4c39b98ce418a2604566 rdf:first sg:person.01362076543.08
130 rdf:rest Nd5996a902aa044aea0788b629ceec0fd
131 N684de028e1c342b98c155b7046b78e2f rdf:first sg:person.016440513017.22
132 rdf:rest N59eed187098b4c39b98ce418a2604566
133 N6effaa4f379c40298e8292632ce70409 schema:volumeNumber 48
134 rdf:type schema:PublicationVolume
135 N80e2701acc654536aafa8dc6ec0891f6 rdf:first sg:person.012111414471.07
136 rdf:rest rdf:nil
137 N9b009ce7740244a79f7338eaf808dac3 rdf:first sg:person.0752721043.33
138 rdf:rest N80e2701acc654536aafa8dc6ec0891f6
139 Nc15205d5a0c640a6bc6b0d338032643c schema:issueNumber 11-12
140 rdf:type schema:PublicationIssue
141 Nc2fc6f6775724892b834236d7a38689d schema:name dimensions_id
142 schema:value pub.1052491449
143 rdf:type schema:PropertyValue
144 Nd5996a902aa044aea0788b629ceec0fd rdf:first sg:person.0704545361.18
145 rdf:rest N9b009ce7740244a79f7338eaf808dac3
146 anzsrc-for:04 schema:inDefinedTermSet anzsrc-for:
147 schema:name Earth Sciences
148 rdf:type schema:DefinedTerm
149 anzsrc-for:0405 schema:inDefinedTermSet anzsrc-for:
150 schema:name Oceanography
151 rdf:type schema:DefinedTerm
152 sg:grant.3790347 http://pending.schema.org/fundedItem sg:pub.10.1007/s00382-016-3280-7
153 rdf:type schema:MonetaryGrant
154 sg:grant.7037241 http://pending.schema.org/fundedItem sg:pub.10.1007/s00382-016-3280-7
155 rdf:type schema:MonetaryGrant
156 sg:journal.1049631 schema:issn 0930-7575
157 1432-0894
158 schema:name Climate Dynamics
159 schema:publisher Springer Nature
160 rdf:type schema:Periodical
161 sg:person.012111414471.07 schema:affiliation grid-institutes:grid.17100.37
162 schema:familyName Jones
163 schema:givenName Gareth S.
164 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012111414471.07
165 rdf:type schema:Person
166 sg:person.01362076543.08 schema:affiliation grid-institutes:grid.17100.37
167 schema:familyName Betts
168 schema:givenName Richard A.
169 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01362076543.08
170 rdf:type schema:Person
171 sg:person.016440513017.22 schema:affiliation grid-institutes:grid.17100.37
172 schema:familyName Andrews
173 schema:givenName Timothy
174 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016440513017.22
175 rdf:type schema:Person
176 sg:person.0704545361.18 schema:affiliation grid-institutes:grid.17100.37
177 schema:familyName Booth
178 schema:givenName Ben B. B.
179 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0704545361.18
180 rdf:type schema:Person
181 sg:person.0752721043.33 schema:affiliation grid-institutes:grid.17100.37
182 schema:familyName Jones
183 schema:givenName Chris D.
184 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0752721043.33
185 rdf:type schema:Person
186 sg:pub.10.1007/s00382-004-0402-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000675318
187 https://doi.org/10.1007/s00382-004-0402-4
188 rdf:type schema:CreativeWork
189 sg:pub.10.1007/s00382-005-0092-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053155278
190 https://doi.org/10.1007/s00382-005-0092-6
191 rdf:type schema:CreativeWork
192 sg:pub.10.1007/s00382-014-2421-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033339265
193 https://doi.org/10.1007/s00382-014-2421-0
194 rdf:type schema:CreativeWork
195 sg:pub.10.1007/s00382-014-2430-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1031728932
196 https://doi.org/10.1007/s00382-014-2430-z
197 rdf:type schema:CreativeWork
198 sg:pub.10.1007/s10584-011-0153-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050130719
199 https://doi.org/10.1007/s10584-011-0153-2
200 rdf:type schema:CreativeWork
201 sg:pub.10.1038/35041545 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038976212
202 https://doi.org/10.1038/35041545
203 rdf:type schema:CreativeWork
204 sg:pub.10.1038/nature10946 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046726171
205 https://doi.org/10.1038/nature10946
206 rdf:type schema:CreativeWork
207 sg:pub.10.1038/nclimate1294 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012464699
208 https://doi.org/10.1038/nclimate1294
209 rdf:type schema:CreativeWork
210 grid-institutes:grid.17100.37 schema:alternateName Met Office Hadley Centre, FitzRoy Road, EX1 3PB, Exeter, UK
211 schema:name Met Office Hadley Centre, FitzRoy Road, EX1 3PB, Exeter, UK
212 rdf:type schema:Organization
 




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


...