A comparison of climate feedbacks in general circulation models View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2003-03-20

AUTHORS

R. Colman

ABSTRACT

. A comparison is performed for water vapour, cloud, albedo and lapse rate feedbacks taken from published results of 'offline' feedback calculations for general circulation models (GCMs) with mixed layer oceans performing 2 × CO2 and solar perturbation experiments. All feedbacks show substantial inter-model spread. The impact of uncertainties in feedbacks on climate sensitivity is discussed. A negative correlation is found between water vapour and lapse rate feedbacks, and also between longwave and shortwave components of the cloud feedback. The mean values of the feedbacks are compared with results derived from model intercomparisons which evaluated cloud forcing derived feedbacks under idealized climate forcing. Results are found to be comparable between the two approaches, after allowing for differences in experimental technique and diagnostic method. Recommendations are made for the future reporting of climate feedbacks. More... »

PAGES

865-873

References to SciGraph publications

  • 2001-11. Climate feedbacks in a general circulation model incorporating prognostic clouds in CLIMATE DYNAMICS
  • 2001-03. On the vertical extent of atmospheric feedbacks in CLIMATE DYNAMICS
  • 1996. Water Vapour and Cloud Feedback in the BMRC AGCM in CLIMATE SENSITIVITY TO RADIATIVE PERTURBATIONS
  • 1988. Quantitative Analysis of Feedbacks in Climate Model Simulations of CO2-Induced Warming in PHYSICALLY-BASED MODELLING AND SIMULATION OF CLIMATE AND CLIMATIC CHANGE
  • 1987-09. Cloud optical depth feedbacks and climate modelling in NATURE
  • 1997-10. Non-linear climate feedback analysis in an atmospheric general circulation model in CLIMATE DYNAMICS
  • 1996. Feedback Processes in the GFDL R30-14 Level General Circulation Model in CLIMATE SENSITIVITY TO RADIATIVE PERTURBATIONS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s00382-003-0310-z

    DOI

    http://dx.doi.org/10.1007/s00382-003-0310-z

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1084987147


    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/2008/0401", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Atmospheric Sciences", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Bureau of Meteorology Research Centre, GPO Box 1289K Melbourne 3001, Australia", 
              "id": "http://www.grid.ac/institutes/grid.1527.1", 
              "name": [
                "Bureau of Meteorology Research Centre, GPO Box 1289K Melbourne 3001, Australia"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Colman", 
            "givenName": "R.", 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1038/329138a0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021469757", 
              "https://doi.org/10.1038/329138a0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-61053-0_13", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014423153", 
              "https://doi.org/10.1007/978-3-642-61053-0_13"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-61053-0_19", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034388592", 
              "https://doi.org/10.1007/978-3-642-61053-0_19"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s003820000111", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015378410", 
              "https://doi.org/10.1007/s003820000111"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s003820050193", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033088945", 
              "https://doi.org/10.1007/s003820050193"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-94-009-3043-8_2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006030199", 
              "https://doi.org/10.1007/978-94-009-3043-8_2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s003820100162", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011851178", 
              "https://doi.org/10.1007/s003820100162"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2003-03-20", 
        "datePublishedReg": "2003-03-20", 
        "description": "Abstract. \nA comparison is performed for water vapour, cloud, albedo and lapse rate feedbacks taken from published results of 'offline' feedback calculations for general circulation models (GCMs) with mixed layer oceans performing 2 \u00d7 CO2 and solar perturbation experiments. All feedbacks show substantial inter-model spread. The impact of uncertainties in feedbacks on climate sensitivity is discussed. A negative correlation is found between water vapour and lapse rate feedbacks, and also between longwave and shortwave components of the cloud feedback. The mean values of the feedbacks are compared with results derived from model intercomparisons which evaluated cloud forcing derived feedbacks under idealized climate forcing. Results are found to be comparable between the two approaches, after allowing for differences in experimental technique and diagnostic method. Recommendations are made for the future reporting of climate feedbacks.", 
        "genre": "article", 
        "id": "sg:pub.10.1007/s00382-003-0310-z", 
        "isAccessibleForFree": false, 
        "isPartOf": [
          {
            "id": "sg:journal.1049631", 
            "issn": [
              "0930-7575", 
              "1432-0894"
            ], 
            "name": "Climate Dynamics", 
            "publisher": "Springer Nature", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "7-8", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "20"
          }
        ], 
        "keywords": [
          "general circulation model", 
          "lapse rate feedback", 
          "climate feedbacks", 
          "circulation model", 
          "substantial inter-model spread", 
          "water vapor", 
          "mixed layer ocean", 
          "inter-model spread", 
          "rate feedback", 
          "cloud feedback", 
          "layer ocean", 
          "climate sensitivity", 
          "\u00d7 CO2", 
          "model intercomparison", 
          "idealized climate", 
          "perturbation experiments", 
          "feedback calculation", 
          "impact of uncertainty", 
          "cloud", 
          "vapor", 
          "Ocean", 
          "albedo", 
          "intercomparison", 
          "climate", 
          "mean value", 
          "negative correlation", 
          "feedback", 
          "CO2", 
          "uncertainty", 
          "model", 
          "comparison", 
          "impact", 
          "correlation", 
          "future reporting", 
          "results", 
          "components", 
          "values", 
          "calculations", 
          "spread", 
          "experiments", 
          "differences", 
          "sensitivity", 
          "experimental techniques", 
          "technique", 
          "approach", 
          "method", 
          "recommendations", 
          "reporting", 
          "diagnostic methods"
        ], 
        "name": "A comparison of climate feedbacks in general circulation models", 
        "pagination": "865-873", 
        "productId": [
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1084987147"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s00382-003-0310-z"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s00382-003-0310-z", 
          "https://app.dimensions.ai/details/publication/pub.1084987147"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2022-12-01T06:23", 
        "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_364.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://doi.org/10.1007/s00382-003-0310-z"
      }
    ]
     

    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/s00382-003-0310-z'

    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/s00382-003-0310-z'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00382-003-0310-z'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00382-003-0310-z'


     

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

    133 TRIPLES      21 PREDICATES      80 URIs      65 LITERALS      6 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s00382-003-0310-z schema:about anzsrc-for:04
    2 anzsrc-for:0401
    3 schema:author N3789dac7cfa84feca8486c3fddb0755c
    4 schema:citation sg:pub.10.1007/978-3-642-61053-0_13
    5 sg:pub.10.1007/978-3-642-61053-0_19
    6 sg:pub.10.1007/978-94-009-3043-8_2
    7 sg:pub.10.1007/s003820000111
    8 sg:pub.10.1007/s003820050193
    9 sg:pub.10.1007/s003820100162
    10 sg:pub.10.1038/329138a0
    11 schema:datePublished 2003-03-20
    12 schema:datePublishedReg 2003-03-20
    13 schema:description Abstract. A comparison is performed for water vapour, cloud, albedo and lapse rate feedbacks taken from published results of 'offline' feedback calculations for general circulation models (GCMs) with mixed layer oceans performing 2 × CO2 and solar perturbation experiments. All feedbacks show substantial inter-model spread. The impact of uncertainties in feedbacks on climate sensitivity is discussed. A negative correlation is found between water vapour and lapse rate feedbacks, and also between longwave and shortwave components of the cloud feedback. The mean values of the feedbacks are compared with results derived from model intercomparisons which evaluated cloud forcing derived feedbacks under idealized climate forcing. Results are found to be comparable between the two approaches, after allowing for differences in experimental technique and diagnostic method. Recommendations are made for the future reporting of climate feedbacks.
    14 schema:genre article
    15 schema:isAccessibleForFree false
    16 schema:isPartOf N9bdb651a1ec943e485d7723ceb712002
    17 Nc7bfa1699ed34a25a952084376b21425
    18 sg:journal.1049631
    19 schema:keywords CO2
    20 Ocean
    21 albedo
    22 approach
    23 calculations
    24 circulation model
    25 climate
    26 climate feedbacks
    27 climate sensitivity
    28 cloud
    29 cloud feedback
    30 comparison
    31 components
    32 correlation
    33 diagnostic methods
    34 differences
    35 experimental techniques
    36 experiments
    37 feedback
    38 feedback calculation
    39 future reporting
    40 general circulation model
    41 idealized climate
    42 impact
    43 impact of uncertainty
    44 inter-model spread
    45 intercomparison
    46 lapse rate feedback
    47 layer ocean
    48 mean value
    49 method
    50 mixed layer ocean
    51 model
    52 model intercomparison
    53 negative correlation
    54 perturbation experiments
    55 rate feedback
    56 recommendations
    57 reporting
    58 results
    59 sensitivity
    60 spread
    61 substantial inter-model spread
    62 technique
    63 uncertainty
    64 values
    65 vapor
    66 water vapor
    67 × CO2
    68 schema:name A comparison of climate feedbacks in general circulation models
    69 schema:pagination 865-873
    70 schema:productId Necef3f600aa24f398d8aa4a778c3a709
    71 Ned2ba309b53d4780bceb2099fbfa3469
    72 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084987147
    73 https://doi.org/10.1007/s00382-003-0310-z
    74 schema:sdDatePublished 2022-12-01T06:23
    75 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    76 schema:sdPublisher N8ff870d43aed4eb691db178769bdf918
    77 schema:url https://doi.org/10.1007/s00382-003-0310-z
    78 sgo:license sg:explorer/license/
    79 sgo:sdDataset articles
    80 rdf:type schema:ScholarlyArticle
    81 N3789dac7cfa84feca8486c3fddb0755c rdf:first N7d4791ab6bb94aadb62df50184972d8b
    82 rdf:rest rdf:nil
    83 N7d4791ab6bb94aadb62df50184972d8b schema:affiliation grid-institutes:grid.1527.1
    84 schema:familyName Colman
    85 schema:givenName R.
    86 rdf:type schema:Person
    87 N8ff870d43aed4eb691db178769bdf918 schema:name Springer Nature - SN SciGraph project
    88 rdf:type schema:Organization
    89 N9bdb651a1ec943e485d7723ceb712002 schema:volumeNumber 20
    90 rdf:type schema:PublicationVolume
    91 Nc7bfa1699ed34a25a952084376b21425 schema:issueNumber 7-8
    92 rdf:type schema:PublicationIssue
    93 Necef3f600aa24f398d8aa4a778c3a709 schema:name dimensions_id
    94 schema:value pub.1084987147
    95 rdf:type schema:PropertyValue
    96 Ned2ba309b53d4780bceb2099fbfa3469 schema:name doi
    97 schema:value 10.1007/s00382-003-0310-z
    98 rdf:type schema:PropertyValue
    99 anzsrc-for:04 schema:inDefinedTermSet anzsrc-for:
    100 schema:name Earth Sciences
    101 rdf:type schema:DefinedTerm
    102 anzsrc-for:0401 schema:inDefinedTermSet anzsrc-for:
    103 schema:name Atmospheric Sciences
    104 rdf:type schema:DefinedTerm
    105 sg:journal.1049631 schema:issn 0930-7575
    106 1432-0894
    107 schema:name Climate Dynamics
    108 schema:publisher Springer Nature
    109 rdf:type schema:Periodical
    110 sg:pub.10.1007/978-3-642-61053-0_13 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014423153
    111 https://doi.org/10.1007/978-3-642-61053-0_13
    112 rdf:type schema:CreativeWork
    113 sg:pub.10.1007/978-3-642-61053-0_19 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034388592
    114 https://doi.org/10.1007/978-3-642-61053-0_19
    115 rdf:type schema:CreativeWork
    116 sg:pub.10.1007/978-94-009-3043-8_2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006030199
    117 https://doi.org/10.1007/978-94-009-3043-8_2
    118 rdf:type schema:CreativeWork
    119 sg:pub.10.1007/s003820000111 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015378410
    120 https://doi.org/10.1007/s003820000111
    121 rdf:type schema:CreativeWork
    122 sg:pub.10.1007/s003820050193 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033088945
    123 https://doi.org/10.1007/s003820050193
    124 rdf:type schema:CreativeWork
    125 sg:pub.10.1007/s003820100162 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011851178
    126 https://doi.org/10.1007/s003820100162
    127 rdf:type schema:CreativeWork
    128 sg:pub.10.1038/329138a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021469757
    129 https://doi.org/10.1038/329138a0
    130 rdf:type schema:CreativeWork
    131 grid-institutes:grid.1527.1 schema:alternateName Bureau of Meteorology Research Centre, GPO Box 1289K Melbourne 3001, Australia
    132 schema:name Bureau of Meteorology Research Centre, GPO Box 1289K Melbourne 3001, Australia
    133 rdf:type schema:Organization
     




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


    ...