The Tolerable Windows Approach: Theoretical and Methodological Foundations View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

1999-03

AUTHORS

Gerhard Petschel-Held, Hans-Joachim Schellnhuber, Thomas Bruckner, Ferenc L. Tóth, Klaus Hasselmann

ABSTRACT

The tolerable windows (TW) approach is presented as a novel scheme for integrated assessment of climate change. The TW approach is based on the specification of a set of guardrails for climate evolution which refer to various climate-related attributes. These constraints, which define what we call tolerable windows, can be purely systemic in nature – like critical thresholds for the North Atlantic Deep Water formation – or of a normative type – like minimum standards for per-capita food production worldwide. Starting from this catalogue of knock-out criteria and using appropriate modeling techniques, those policy strategies which are compatible with all the constraints specified are sought to be identified. In addition to the discussion of the basic elements and the general theory of the TW approach, a modeling exercise is carried out, based on simple models and assumptions adopted from the German Advisory Council on Global Change (WBGU). The analysis shows that if the global mean temperature is restricted to 2°C beyond the preindustrial level, the cumulative emissions of CO2 are asymptotically limited to about 1550 Gt C. Yet the temporal distribution of these emissions is also determined by the climate and socio-economic constraints: using, for example, a maximal tolerable rate of temperature change of 0.2°C/dec and a smoothly varying emissions profile, we obtain the maximal cumulative emissions, amounting to 370 Gt C in 2050 and 585 Gt C in 2100. More... »

PAGES

303-331

Identifiers

URI

http://scigraph.springernature.com/pub.10.1023/a:1005487123751

DOI

http://dx.doi.org/10.1023/a:1005487123751

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1010887986


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/2008/06", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Biological Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0699", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Other Biological Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Telegrafenberg, Potsdam Institute for Climate Impact Research, D-14473, Potsdam, Germany", 
          "id": "http://www.grid.ac/institutes/grid.4556.2", 
          "name": [
            "Telegrafenberg, Potsdam Institute for Climate Impact Research, D-14473, Potsdam, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Petschel-Held", 
        "givenName": "Gerhard", 
        "id": "sg:person.012072022706.51", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012072022706.51"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Telegrafenberg, Potsdam Institute for Climate Impact Research, D-14473, Potsdam, Germany", 
          "id": "http://www.grid.ac/institutes/grid.4556.2", 
          "name": [
            "Telegrafenberg, Potsdam Institute for Climate Impact Research, D-14473, Potsdam, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Schellnhuber", 
        "givenName": "Hans-Joachim", 
        "id": "sg:person.01153320406.73", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01153320406.73"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Telegrafenberg, Potsdam Institute for Climate Impact Research, D-14473, Potsdam, Germany", 
          "id": "http://www.grid.ac/institutes/grid.4556.2", 
          "name": [
            "Telegrafenberg, Potsdam Institute for Climate Impact Research, D-14473, Potsdam, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Bruckner", 
        "givenName": "Thomas", 
        "id": "sg:person.013140325577.04", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013140325577.04"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Telegrafenberg, Potsdam Institute for Climate Impact Research, D-14473, Potsdam, Germany", 
          "id": "http://www.grid.ac/institutes/grid.4556.2", 
          "name": [
            "Telegrafenberg, Potsdam Institute for Climate Impact Research, D-14473, Potsdam, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "T\u00f3th", 
        "givenName": "Ferenc L.", 
        "id": "sg:person.011062750647.61", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011062750647.61"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Max-Planck Institute for Meteorology, Bundesstra\u00dfe 55, D-20146, Hamburg, Germany", 
          "id": "http://www.grid.ac/institutes/grid.450268.d", 
          "name": [
            "Max-Planck Institute for Meteorology, Bundesstra\u00dfe 55, D-20146, Hamburg, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hasselmann", 
        "givenName": "Klaus", 
        "id": "sg:person.011507631147.31", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011507631147.31"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1038/42224", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033418695", 
          "https://doi.org/10.1038/42224"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/379240a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004656114", 
          "https://doi.org/10.1038/379240a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/a:1005339625015", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008670842", 
          "https://doi.org/10.1023/a:1005339625015"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/a:1005347001731", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029301888", 
          "https://doi.org/10.1023/a:1005347001731"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s001140050525", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041217800", 
          "https://doi.org/10.1007/s001140050525"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01054491", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040451933", 
          "https://doi.org/10.1007/bf01054491"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/372082a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031127096", 
          "https://doi.org/10.1038/372082a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/a:1019076603956", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039634230", 
          "https://doi.org/10.1023/a:1019076603956"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00939454", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006536024", 
          "https://doi.org/10.1007/bf00939454"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/367133a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028087951", 
          "https://doi.org/10.1038/367133a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/378145a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048482035", 
          "https://doi.org/10.1038/378145a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00691574", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035393269", 
          "https://doi.org/10.1007/bf00691574"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "1999-03", 
    "datePublishedReg": "1999-03-01", 
    "description": "The tolerable windows (TW) approach is presented as a novel scheme for integrated assessment of climate change. The TW approach is based on the specification of a set of guardrails for climate evolution which refer to various climate-related attributes. These constraints, which define what we call tolerable windows, can be purely systemic in nature \u2013 like critical thresholds for the North Atlantic Deep Water formation \u2013 or of a normative type \u2013 like minimum standards for per-capita food production worldwide. Starting from this catalogue of knock-out criteria and using appropriate modeling techniques, those policy strategies which are compatible with all the constraints specified are sought to be identified. In addition to the discussion of the basic elements and the general theory of the TW approach, a modeling exercise is carried out, based on simple models and assumptions adopted from the German Advisory Council on Global Change (WBGU). The analysis shows that if the global mean temperature is restricted to 2\u00b0C beyond the preindustrial level, the cumulative emissions of CO2 are asymptotically limited to about 1550 Gt C. Yet the temporal distribution of these emissions is also determined by the climate and socio-economic constraints: using, for example, a maximal tolerable rate of temperature change of 0.2\u00b0C/dec and a smoothly varying emissions profile, we obtain the maximal cumulative emissions, amounting to 370 Gt C in 2050 and 585 Gt C in 2100.", 
    "genre": "article", 
    "id": "sg:pub.10.1023/a:1005487123751", 
    "isAccessibleForFree": false, 
    "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": "41"
      }
    ], 
    "keywords": [
      "Tolerable Windows Approach", 
      "Gt C", 
      "North Atlantic Deep Water formation", 
      "deep water formation", 
      "global mean temperature", 
      "cumulative emissions", 
      "climate evolution", 
      "water formation", 
      "preindustrial levels", 
      "Gt C.", 
      "climate change", 
      "German Advisory Council", 
      "temporal distribution", 
      "mean temperature", 
      "tolerable windows", 
      "global change", 
      "temperature changes", 
      "integrated assessment", 
      "appropriate modeling techniques", 
      "tolerable rate", 
      "critical threshold", 
      "climate", 
      "simple model", 
      "emission", 
      "socio-economic constraints", 
      "changes", 
      "constraints", 
      "CO2", 
      "food production", 
      "evolution", 
      "modeling techniques", 
      "catalogue", 
      "capita food production", 
      "formation", 
      "distribution", 
      "temperature", 
      "window approach", 
      "elements", 
      "emission profiles", 
      "profile", 
      "model", 
      "window", 
      "assessment", 
      "set", 
      "assumption", 
      "threshold", 
      "production", 
      "analysis", 
      "example", 
      "rate", 
      "approach", 
      "attributes", 
      "scheme", 
      "basic elements", 
      "levels", 
      "addition", 
      "technique", 
      "foundation", 
      "discussion", 
      "standards", 
      "Advisory Council", 
      "criteria", 
      "Council", 
      "policy strategies", 
      "guardrails", 
      "strategies", 
      "theory", 
      "specification", 
      "C.", 
      "general theory", 
      "exercise", 
      "novel scheme", 
      "methodological foundations", 
      "minimum standards", 
      "TW approach"
    ], 
    "name": "The Tolerable Windows Approach: Theoretical and Methodological Foundations", 
    "pagination": "303-331", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1010887986"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1023/a:1005487123751"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1023/a:1005487123751", 
      "https://app.dimensions.ai/details/publication/pub.1010887986"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-12-01T06:22", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20221201/entities/gbq_results/article/article_305.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1023/a:1005487123751"
  }
]
 

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.10.1023/a:1005487123751'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1023/a:1005487123751'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1023/a:1005487123751'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1023/a:1005487123751'


 

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

211 TRIPLES      21 PREDICATES      112 URIs      92 LITERALS      6 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1023/a:1005487123751 schema:about anzsrc-for:06
2 anzsrc-for:0699
3 schema:author Nb01d767acdcd4f4a929fe6c44f762ea0
4 schema:citation sg:pub.10.1007/bf00691574
5 sg:pub.10.1007/bf00939454
6 sg:pub.10.1007/bf01054491
7 sg:pub.10.1007/s001140050525
8 sg:pub.10.1023/a:1005339625015
9 sg:pub.10.1023/a:1005347001731
10 sg:pub.10.1023/a:1019076603956
11 sg:pub.10.1038/367133a0
12 sg:pub.10.1038/372082a0
13 sg:pub.10.1038/378145a0
14 sg:pub.10.1038/379240a0
15 sg:pub.10.1038/42224
16 schema:datePublished 1999-03
17 schema:datePublishedReg 1999-03-01
18 schema:description The tolerable windows (TW) approach is presented as a novel scheme for integrated assessment of climate change. The TW approach is based on the specification of a set of guardrails for climate evolution which refer to various climate-related attributes. These constraints, which define what we call tolerable windows, can be purely systemic in nature – like critical thresholds for the North Atlantic Deep Water formation – or of a normative type – like minimum standards for per-capita food production worldwide. Starting from this catalogue of knock-out criteria and using appropriate modeling techniques, those policy strategies which are compatible with all the constraints specified are sought to be identified. In addition to the discussion of the basic elements and the general theory of the TW approach, a modeling exercise is carried out, based on simple models and assumptions adopted from the German Advisory Council on Global Change (WBGU). The analysis shows that if the global mean temperature is restricted to 2°C beyond the preindustrial level, the cumulative emissions of CO2 are asymptotically limited to about 1550 Gt C. Yet the temporal distribution of these emissions is also determined by the climate and socio-economic constraints: using, for example, a maximal tolerable rate of temperature change of 0.2°C/dec and a smoothly varying emissions profile, we obtain the maximal cumulative emissions, amounting to 370 Gt C in 2050 and 585 Gt C in 2100.
19 schema:genre article
20 schema:isAccessibleForFree false
21 schema:isPartOf N3dd8c30508584ccb9163341eb582827c
22 N6239f49844684753ba3ef2e749be9426
23 sg:journal.1028211
24 schema:keywords Advisory Council
25 C.
26 CO2
27 Council
28 German Advisory Council
29 Gt C
30 Gt C.
31 North Atlantic Deep Water formation
32 TW approach
33 Tolerable Windows Approach
34 addition
35 analysis
36 approach
37 appropriate modeling techniques
38 assessment
39 assumption
40 attributes
41 basic elements
42 capita food production
43 catalogue
44 changes
45 climate
46 climate change
47 climate evolution
48 constraints
49 criteria
50 critical threshold
51 cumulative emissions
52 deep water formation
53 discussion
54 distribution
55 elements
56 emission
57 emission profiles
58 evolution
59 example
60 exercise
61 food production
62 formation
63 foundation
64 general theory
65 global change
66 global mean temperature
67 guardrails
68 integrated assessment
69 levels
70 mean temperature
71 methodological foundations
72 minimum standards
73 model
74 modeling techniques
75 novel scheme
76 policy strategies
77 preindustrial levels
78 production
79 profile
80 rate
81 scheme
82 set
83 simple model
84 socio-economic constraints
85 specification
86 standards
87 strategies
88 technique
89 temperature
90 temperature changes
91 temporal distribution
92 theory
93 threshold
94 tolerable rate
95 tolerable windows
96 water formation
97 window
98 window approach
99 schema:name The Tolerable Windows Approach: Theoretical and Methodological Foundations
100 schema:pagination 303-331
101 schema:productId N2371df68b78242d4948a12d6b401a07e
102 N9c45c59d8d194764b452d07d0c5733f9
103 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010887986
104 https://doi.org/10.1023/a:1005487123751
105 schema:sdDatePublished 2022-12-01T06:22
106 schema:sdLicense https://scigraph.springernature.com/explorer/license/
107 schema:sdPublisher N36ae850fd37743f59f84de31b053642c
108 schema:url https://doi.org/10.1023/a:1005487123751
109 sgo:license sg:explorer/license/
110 sgo:sdDataset articles
111 rdf:type schema:ScholarlyArticle
112 N1e64eb71c8434249967d53419221fc07 rdf:first sg:person.011507631147.31
113 rdf:rest rdf:nil
114 N2371df68b78242d4948a12d6b401a07e schema:name dimensions_id
115 schema:value pub.1010887986
116 rdf:type schema:PropertyValue
117 N36ae850fd37743f59f84de31b053642c schema:name Springer Nature - SN SciGraph project
118 rdf:type schema:Organization
119 N3dd8c30508584ccb9163341eb582827c schema:volumeNumber 41
120 rdf:type schema:PublicationVolume
121 N5318b3cac5754345bd0416313310afd0 rdf:first sg:person.01153320406.73
122 rdf:rest Nce16322777ee4629be21d54690a0cd9e
123 N6239f49844684753ba3ef2e749be9426 schema:issueNumber 3-4
124 rdf:type schema:PublicationIssue
125 N9c45c59d8d194764b452d07d0c5733f9 schema:name doi
126 schema:value 10.1023/a:1005487123751
127 rdf:type schema:PropertyValue
128 Nb01d767acdcd4f4a929fe6c44f762ea0 rdf:first sg:person.012072022706.51
129 rdf:rest N5318b3cac5754345bd0416313310afd0
130 Nce16322777ee4629be21d54690a0cd9e rdf:first sg:person.013140325577.04
131 rdf:rest Nf43158865a4e433ead5d98caf52fb62d
132 Nf43158865a4e433ead5d98caf52fb62d rdf:first sg:person.011062750647.61
133 rdf:rest N1e64eb71c8434249967d53419221fc07
134 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
135 schema:name Biological Sciences
136 rdf:type schema:DefinedTerm
137 anzsrc-for:0699 schema:inDefinedTermSet anzsrc-for:
138 schema:name Other Biological Sciences
139 rdf:type schema:DefinedTerm
140 sg:journal.1028211 schema:issn 0165-0009
141 1573-1480
142 schema:name Climatic Change
143 schema:publisher Springer Nature
144 rdf:type schema:Periodical
145 sg:person.011062750647.61 schema:affiliation grid-institutes:grid.4556.2
146 schema:familyName Tóth
147 schema:givenName Ferenc L.
148 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011062750647.61
149 rdf:type schema:Person
150 sg:person.011507631147.31 schema:affiliation grid-institutes:grid.450268.d
151 schema:familyName Hasselmann
152 schema:givenName Klaus
153 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011507631147.31
154 rdf:type schema:Person
155 sg:person.01153320406.73 schema:affiliation grid-institutes:grid.4556.2
156 schema:familyName Schellnhuber
157 schema:givenName Hans-Joachim
158 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01153320406.73
159 rdf:type schema:Person
160 sg:person.012072022706.51 schema:affiliation grid-institutes:grid.4556.2
161 schema:familyName Petschel-Held
162 schema:givenName Gerhard
163 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012072022706.51
164 rdf:type schema:Person
165 sg:person.013140325577.04 schema:affiliation grid-institutes:grid.4556.2
166 schema:familyName Bruckner
167 schema:givenName Thomas
168 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013140325577.04
169 rdf:type schema:Person
170 sg:pub.10.1007/bf00691574 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035393269
171 https://doi.org/10.1007/bf00691574
172 rdf:type schema:CreativeWork
173 sg:pub.10.1007/bf00939454 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006536024
174 https://doi.org/10.1007/bf00939454
175 rdf:type schema:CreativeWork
176 sg:pub.10.1007/bf01054491 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040451933
177 https://doi.org/10.1007/bf01054491
178 rdf:type schema:CreativeWork
179 sg:pub.10.1007/s001140050525 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041217800
180 https://doi.org/10.1007/s001140050525
181 rdf:type schema:CreativeWork
182 sg:pub.10.1023/a:1005339625015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008670842
183 https://doi.org/10.1023/a:1005339625015
184 rdf:type schema:CreativeWork
185 sg:pub.10.1023/a:1005347001731 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029301888
186 https://doi.org/10.1023/a:1005347001731
187 rdf:type schema:CreativeWork
188 sg:pub.10.1023/a:1019076603956 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039634230
189 https://doi.org/10.1023/a:1019076603956
190 rdf:type schema:CreativeWork
191 sg:pub.10.1038/367133a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028087951
192 https://doi.org/10.1038/367133a0
193 rdf:type schema:CreativeWork
194 sg:pub.10.1038/372082a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031127096
195 https://doi.org/10.1038/372082a0
196 rdf:type schema:CreativeWork
197 sg:pub.10.1038/378145a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048482035
198 https://doi.org/10.1038/378145a0
199 rdf:type schema:CreativeWork
200 sg:pub.10.1038/379240a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004656114
201 https://doi.org/10.1038/379240a0
202 rdf:type schema:CreativeWork
203 sg:pub.10.1038/42224 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033418695
204 https://doi.org/10.1038/42224
205 rdf:type schema:CreativeWork
206 grid-institutes:grid.450268.d schema:alternateName Max-Planck Institute for Meteorology, Bundesstraße 55, D-20146, Hamburg, Germany
207 schema:name Max-Planck Institute for Meteorology, Bundesstraße 55, D-20146, Hamburg, Germany
208 rdf:type schema:Organization
209 grid-institutes:grid.4556.2 schema:alternateName Telegrafenberg, Potsdam Institute for Climate Impact Research, D-14473, Potsdam, Germany
210 schema:name Telegrafenberg, Potsdam Institute for Climate Impact Research, D-14473, Potsdam, Germany
211 rdf:type schema:Organization
 




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


...