Transient twenty-first century changes in daily-scale temperature extremes in the United States View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2013-07-04

AUTHORS

Martin Scherer, Noah S. Diffenbaugh

ABSTRACT

A key question for climate mitigation and adaptation decisions is how quickly significant changes in temperature extremes will emerge as greenhouse gas concentrations increase, and whether that emergence will be uniform between hot and cold extremes and across different geographic areas. We use a high-resolution, multi-member ensemble climate model experiment over the United States (U.S.) to investigate the transient response of the annual frequency, duration and magnitude of 8 daily-scale extreme temperature indices during the twenty-first century of the A1B emissions scenario. We evaluate the time of emergence of a permanent exceedance (PE) above the colder part of the historical (1980–2009) extremes distribution, and the time of emergence of a new norm (NN) centered on the historical maxima (for hot extremes) or minima (for cold extremes). We find that during the twenty-first century, hot extremes permanently exceed the historical distribution’s colder half over large areas of the U.S., and that the hot extremes distribution also becomes centered on or above the historical distribution’s maxima. The changes are particularly robust for the exceedance of the annual 95th percentile of daily maximum temperature over the West and the Northeast (with the earliest emergence of a PE by 2030 and of a NN by 2040), for warm days over the Southwest (with the earliest emergence of a PE by 2020 and of a NN by 2030), and tropical nights over the eastern U.S. (with the earliest emergence of a PE by 2020 and of a NN by 2030). Conversely, no widespread emergence of a PE or a NN is found for most cold extremes. Exceptions include frost day frequency (with a widespread emergence of a PE below the historical median frequency by 2030 and of a NN by 2040 over the western U.S.), and cold night frequency (with an emergence of a PE below the historical median frequency by 2040 and of a NN by 2060 in virtually the entire U.S.). Our analysis implies a transition over the next half century to a climate of recently unprecedented heat stress in many parts of the U.S., along with cold extremes that, although less frequent, remain at times as long and as severe as are found in the current climate. More... »

PAGES

1383-1404

References to SciGraph publications

  • 2011-07-22. Global changes in extreme events: regional and seasonal dimension in CLIMATIC CHANGE
  • 2007-03-15. Going to the extremes in CLIMATIC CHANGE
  • 2004-01. Hydrologic Implications of Dynamical and Statistical Approaches to Downscaling Climate Model Outputs in CLIMATIC CHANGE
  • 2005-09. Europe-wide reduction in primary productivity caused by the heat and drought in 2003 in NATURE
  • 2012-11-18. Adaptation of US maize to temperature variations in NATURE CLIMATE CHANGE
  • 2011-06-07. Observational and model evidence of global emergence of permanent, unprecedented heat in the 20th and 21st centuries in CLIMATIC CHANGE
  • 2010-05-16. Consistent geographical patterns of changes in high-impact European heatwaves in NATURE GEOSCIENCE
  • 2011-10-23. Projections of when temperature change will exceed 2 °C above pre-industrial levels in NATURE CLIMATE CHANGE
  • 2004-08-20. Changes in frost days in simulations of twentyfirst century climate in CLIMATE DYNAMICS
  • 2012-05-18. Using climate impacts indicators to evaluate climate model ensembles: temperature suitability of premium winegrape cultivation in the United States in CLIMATE DYNAMICS
  • 2011-09-08. Near-term increase in frequency of seasonal temperature extremes prior to the 2°C global warming target in CLIMATIC CHANGE
  • 2009-08-18. Future changes in Central Europe heat waves expected to mostly follow summer mean warming in CLIMATE DYNAMICS
  • 2004-12. Human contribution to the European heatwave of 2003 in NATURE
  • 2010-12-31. Uncertainty in climate change projections: the role of internal variability in CLIMATE DYNAMICS
  • 2008-05-15. North Pacific cyclonic and anticyclonic transients in a global warming context: possible consequences for Western North American daily precipitation and temperature extremes in CLIMATE DYNAMICS
  • 2005-11. Impact of regional climate change on human health in NATURE
  • 2012-02-05. Global warming under old and new scenarios using IPCC climate sensitivity range estimates in NATURE CLIMATE CHANGE
  • 2009-06-30. Evaluation of high-resolution simulations of daily-scale temperature and precipitation over the United States in CLIMATE DYNAMICS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s00382-013-1829-2

    DOI

    http://dx.doi.org/10.1007/s00382-013-1829-2

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1022979088


    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": "Department of Environmental Earth System Science, Woods Institute for the Environment, Stanford University, 473 Via Ortega, 94305-4216, Stanford, CA, USA", 
              "id": "http://www.grid.ac/institutes/grid.168010.e", 
              "name": [
                "Department of Environmental Earth System Science, Woods Institute for the Environment, Stanford University, 473 Via Ortega, 94305-4216, Stanford, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Scherer", 
            "givenName": "Martin", 
            "id": "sg:person.012602560335.34", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012602560335.34"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Earth and Atmospheric Sciences, Purdue Climate Change Research Center, Purdue University, West Lafayette, IN, USA", 
              "id": "http://www.grid.ac/institutes/grid.169077.e", 
              "name": [
                "Department of Environmental Earth System Science, Woods Institute for the Environment, Stanford University, 473 Via Ortega, 94305-4216, Stanford, CA, USA", 
                "Department of Earth and Atmospheric Sciences, Purdue Climate Change Research Center, Purdue University, West Lafayette, IN, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Diffenbaugh", 
            "givenName": "Noah S.", 
            "id": "sg:person.07755742371.03", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07755742371.03"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1007/s00382-012-1377-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007728471", 
              "https://doi.org/10.1007/s00382-012-1377-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ngeo866", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050241953", 
              "https://doi.org/10.1038/ngeo866"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nclimate1261", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052952803", 
              "https://doi.org/10.1038/nclimate1261"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10584-011-0122-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040318214", 
              "https://doi.org/10.1007/s10584-011-0122-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nclimate1585", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022202325", 
              "https://doi.org/10.1038/nclimate1585"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature03089", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028450143", 
              "https://doi.org/10.1038/nature03089"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10584-007-9247-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006556053", 
              "https://doi.org/10.1007/s10584-007-9247-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature03972", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1030525946", 
              "https://doi.org/10.1038/nature03972"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00382-009-0603-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012170341", 
              "https://doi.org/10.1007/s00382-009-0603-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nclimate1385", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047584368", 
              "https://doi.org/10.1038/nclimate1385"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00382-008-0417-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040266860", 
              "https://doi.org/10.1007/s00382-008-0417-3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10584-011-0112-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006938098", 
              "https://doi.org/10.1007/s10584-011-0112-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00382-009-0641-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014042512", 
              "https://doi.org/10.1007/s00382-009-0641-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature04188", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027208376", 
              "https://doi.org/10.1038/nature04188"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00382-010-0977-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021861148", 
              "https://doi.org/10.1007/s00382-010-0977-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10584-011-0196-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019020685", 
              "https://doi.org/10.1007/s10584-011-0196-4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00382-004-0442-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025795726", 
              "https://doi.org/10.1007/s00382-004-0442-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1023/b:clim.0000013685.99609.9e", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019795211", 
              "https://doi.org/10.1023/b:clim.0000013685.99609.9e"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2013-07-04", 
        "datePublishedReg": "2013-07-04", 
        "description": "A key question for climate mitigation and adaptation decisions is how quickly significant changes in temperature extremes will emerge as greenhouse gas concentrations increase, and whether that emergence will be uniform between hot and cold extremes and across different geographic areas. We use a high-resolution, multi-member ensemble climate model experiment over the United States (U.S.) to investigate the transient response of the annual frequency, duration and magnitude of 8 daily-scale extreme temperature indices during the twenty-first century of the A1B emissions scenario. We evaluate the time of emergence of a permanent exceedance (PE) above the colder part of the historical (1980\u20132009) extremes distribution, and the time of emergence of a new norm (NN) centered on the historical maxima (for hot extremes) or minima (for cold extremes). We find that during the twenty-first century, hot extremes permanently exceed the historical distribution\u2019s colder half over large areas of the U.S., and that the hot extremes distribution also becomes centered on or above the historical distribution\u2019s maxima. The changes are particularly robust for the exceedance of the annual 95th percentile of daily maximum temperature over the West and the Northeast (with the earliest emergence of a PE by 2030 and of a NN by 2040), for warm days over the Southwest (with the earliest emergence of a PE by 2020 and of a NN by 2030), and tropical nights over the eastern U.S. (with the earliest emergence of a PE by 2020 and of a NN by 2030). Conversely, no widespread emergence of a PE or a NN is found for most cold extremes. Exceptions include frost day frequency (with a widespread emergence of a PE below the historical median frequency by 2030 and of a NN by 2040 over the western U.S.), and cold night frequency (with an emergence of a PE below the historical median frequency by 2040 and of a NN by 2060 in virtually the entire U.S.). Our analysis implies a transition over the next half century to a climate of recently unprecedented heat stress in many parts of the U.S., along with cold extremes that, although less frequent, remain at times as long and as severe as are found in the current climate.", 
        "genre": "article", 
        "id": "sg:pub.10.1007/s00382-013-1829-2", 
        "isAccessibleForFree": false, 
        "isFundedItemOf": [
          {
            "id": "sg:grant.2459048", 
            "type": "MonetaryGrant"
          }
        ], 
        "isPartOf": [
          {
            "id": "sg:journal.1049631", 
            "issn": [
              "0930-7575", 
              "1432-0894"
            ], 
            "name": "Climate Dynamics", 
            "publisher": "Springer Nature", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "5-6", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "42"
          }
        ], 
        "keywords": [
          "twenty-first century", 
          "United States", 
          "next half century", 
          "twenty-first century changes", 
          "new norms", 
          "half century", 
          "century", 
          "historical distribution", 
          "century changes", 
          "emergence", 
          "historical maximum", 
          "U.S.", 
          "cold extremes", 
          "key questions", 
          "West", 
          "eastern U.S.", 
          "southwest", 
          "climate", 
          "time of emergence", 
          "current climate", 
          "part", 
          "state", 
          "half", 
          "extremes", 
          "cold half", 
          "northeast", 
          "questions", 
          "temperature extremes", 
          "geographic areas", 
          "widespread emergence", 
          "time", 
          "greenhouse gas concentrations", 
          "climate model experiments", 
          "A1B emission scenario", 
          "norms", 
          "extreme temperature indices", 
          "coldest part", 
          "daily maximum temperature", 
          "frost day frequency", 
          "large areas", 
          "exception", 
          "emission scenarios", 
          "hot extremes", 
          "tropical nights", 
          "changes", 
          "temperature indices", 
          "day frequency", 
          "warm days", 
          "area", 
          "model experiments", 
          "annual frequency", 
          "night frequency", 
          "gas concentration", 
          "climate mitigation", 
          "extreme distribution", 
          "maximum temperature", 
          "adaptation decisions", 
          "exceedance", 
          "transition", 
          "maximum", 
          "distribution maximum", 
          "night", 
          "decisions", 
          "different geographic areas", 
          "significant changes", 
          "distribution", 
          "magnitude", 
          "mitigation", 
          "days", 
          "analysis", 
          "scenarios", 
          "minimum", 
          "temperature", 
          "heat stress", 
          "concentration", 
          "frequency", 
          "percentile", 
          "transient response", 
          "response", 
          "index", 
          "duration", 
          "experiments", 
          "stress", 
          "transients"
        ], 
        "name": "Transient twenty-first century changes in daily-scale temperature extremes in the United States", 
        "pagination": "1383-1404", 
        "productId": [
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1022979088"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s00382-013-1829-2"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s00382-013-1829-2", 
          "https://app.dimensions.ai/details/publication/pub.1022979088"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2022-12-01T06:30", 
        "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_585.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://doi.org/10.1007/s00382-013-1829-2"
      }
    ]
     

    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/s00382-013-1829-2'

    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/s00382-013-1829-2'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00382-013-1829-2'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00382-013-1829-2'


     

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

    226 TRIPLES      21 PREDICATES      126 URIs      100 LITERALS      6 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s00382-013-1829-2 schema:about anzsrc-for:04
    2 anzsrc-for:0401
    3 schema:author Nd5177b74b5df459183aae5caf10c7693
    4 schema:citation sg:pub.10.1007/s00382-004-0442-9
    5 sg:pub.10.1007/s00382-008-0417-3
    6 sg:pub.10.1007/s00382-009-0603-y
    7 sg:pub.10.1007/s00382-009-0641-5
    8 sg:pub.10.1007/s00382-010-0977-x
    9 sg:pub.10.1007/s00382-012-1377-1
    10 sg:pub.10.1007/s10584-007-9247-2
    11 sg:pub.10.1007/s10584-011-0112-y
    12 sg:pub.10.1007/s10584-011-0122-9
    13 sg:pub.10.1007/s10584-011-0196-4
    14 sg:pub.10.1023/b:clim.0000013685.99609.9e
    15 sg:pub.10.1038/nature03089
    16 sg:pub.10.1038/nature03972
    17 sg:pub.10.1038/nature04188
    18 sg:pub.10.1038/nclimate1261
    19 sg:pub.10.1038/nclimate1385
    20 sg:pub.10.1038/nclimate1585
    21 sg:pub.10.1038/ngeo866
    22 schema:datePublished 2013-07-04
    23 schema:datePublishedReg 2013-07-04
    24 schema:description A key question for climate mitigation and adaptation decisions is how quickly significant changes in temperature extremes will emerge as greenhouse gas concentrations increase, and whether that emergence will be uniform between hot and cold extremes and across different geographic areas. We use a high-resolution, multi-member ensemble climate model experiment over the United States (U.S.) to investigate the transient response of the annual frequency, duration and magnitude of 8 daily-scale extreme temperature indices during the twenty-first century of the A1B emissions scenario. We evaluate the time of emergence of a permanent exceedance (PE) above the colder part of the historical (1980–2009) extremes distribution, and the time of emergence of a new norm (NN) centered on the historical maxima (for hot extremes) or minima (for cold extremes). We find that during the twenty-first century, hot extremes permanently exceed the historical distribution’s colder half over large areas of the U.S., and that the hot extremes distribution also becomes centered on or above the historical distribution’s maxima. The changes are particularly robust for the exceedance of the annual 95th percentile of daily maximum temperature over the West and the Northeast (with the earliest emergence of a PE by 2030 and of a NN by 2040), for warm days over the Southwest (with the earliest emergence of a PE by 2020 and of a NN by 2030), and tropical nights over the eastern U.S. (with the earliest emergence of a PE by 2020 and of a NN by 2030). Conversely, no widespread emergence of a PE or a NN is found for most cold extremes. Exceptions include frost day frequency (with a widespread emergence of a PE below the historical median frequency by 2030 and of a NN by 2040 over the western U.S.), and cold night frequency (with an emergence of a PE below the historical median frequency by 2040 and of a NN by 2060 in virtually the entire U.S.). Our analysis implies a transition over the next half century to a climate of recently unprecedented heat stress in many parts of the U.S., along with cold extremes that, although less frequent, remain at times as long and as severe as are found in the current climate.
    25 schema:genre article
    26 schema:isAccessibleForFree false
    27 schema:isPartOf N559c4ff1a5fb44ad815466212ab29595
    28 Ndbe4d49637c1446c8e0524d2cab190b6
    29 sg:journal.1049631
    30 schema:keywords A1B emission scenario
    31 U.S.
    32 United States
    33 West
    34 adaptation decisions
    35 analysis
    36 annual frequency
    37 area
    38 century
    39 century changes
    40 changes
    41 climate
    42 climate mitigation
    43 climate model experiments
    44 cold extremes
    45 cold half
    46 coldest part
    47 concentration
    48 current climate
    49 daily maximum temperature
    50 day frequency
    51 days
    52 decisions
    53 different geographic areas
    54 distribution
    55 distribution maximum
    56 duration
    57 eastern U.S.
    58 emergence
    59 emission scenarios
    60 exceedance
    61 exception
    62 experiments
    63 extreme distribution
    64 extreme temperature indices
    65 extremes
    66 frequency
    67 frost day frequency
    68 gas concentration
    69 geographic areas
    70 greenhouse gas concentrations
    71 half
    72 half century
    73 heat stress
    74 historical distribution
    75 historical maximum
    76 hot extremes
    77 index
    78 key questions
    79 large areas
    80 magnitude
    81 maximum
    82 maximum temperature
    83 minimum
    84 mitigation
    85 model experiments
    86 new norms
    87 next half century
    88 night
    89 night frequency
    90 norms
    91 northeast
    92 part
    93 percentile
    94 questions
    95 response
    96 scenarios
    97 significant changes
    98 southwest
    99 state
    100 stress
    101 temperature
    102 temperature extremes
    103 temperature indices
    104 time
    105 time of emergence
    106 transient response
    107 transients
    108 transition
    109 tropical nights
    110 twenty-first century
    111 twenty-first century changes
    112 warm days
    113 widespread emergence
    114 schema:name Transient twenty-first century changes in daily-scale temperature extremes in the United States
    115 schema:pagination 1383-1404
    116 schema:productId Ne2d7cdbd82514c2e9959389e3d2752ce
    117 Nf5a39bc423f045b6a115842c8ef350a5
    118 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022979088
    119 https://doi.org/10.1007/s00382-013-1829-2
    120 schema:sdDatePublished 2022-12-01T06:30
    121 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    122 schema:sdPublisher N2167f71b25e8484192546784cf61b556
    123 schema:url https://doi.org/10.1007/s00382-013-1829-2
    124 sgo:license sg:explorer/license/
    125 sgo:sdDataset articles
    126 rdf:type schema:ScholarlyArticle
    127 N2167f71b25e8484192546784cf61b556 schema:name Springer Nature - SN SciGraph project
    128 rdf:type schema:Organization
    129 N559c4ff1a5fb44ad815466212ab29595 schema:volumeNumber 42
    130 rdf:type schema:PublicationVolume
    131 N5913953cd9af41168c3359108bb7caef rdf:first sg:person.07755742371.03
    132 rdf:rest rdf:nil
    133 Nd5177b74b5df459183aae5caf10c7693 rdf:first sg:person.012602560335.34
    134 rdf:rest N5913953cd9af41168c3359108bb7caef
    135 Ndbe4d49637c1446c8e0524d2cab190b6 schema:issueNumber 5-6
    136 rdf:type schema:PublicationIssue
    137 Ne2d7cdbd82514c2e9959389e3d2752ce schema:name dimensions_id
    138 schema:value pub.1022979088
    139 rdf:type schema:PropertyValue
    140 Nf5a39bc423f045b6a115842c8ef350a5 schema:name doi
    141 schema:value 10.1007/s00382-013-1829-2
    142 rdf:type schema:PropertyValue
    143 anzsrc-for:04 schema:inDefinedTermSet anzsrc-for:
    144 schema:name Earth Sciences
    145 rdf:type schema:DefinedTerm
    146 anzsrc-for:0401 schema:inDefinedTermSet anzsrc-for:
    147 schema:name Atmospheric Sciences
    148 rdf:type schema:DefinedTerm
    149 sg:grant.2459048 http://pending.schema.org/fundedItem sg:pub.10.1007/s00382-013-1829-2
    150 rdf:type schema:MonetaryGrant
    151 sg:journal.1049631 schema:issn 0930-7575
    152 1432-0894
    153 schema:name Climate Dynamics
    154 schema:publisher Springer Nature
    155 rdf:type schema:Periodical
    156 sg:person.012602560335.34 schema:affiliation grid-institutes:grid.168010.e
    157 schema:familyName Scherer
    158 schema:givenName Martin
    159 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012602560335.34
    160 rdf:type schema:Person
    161 sg:person.07755742371.03 schema:affiliation grid-institutes:grid.169077.e
    162 schema:familyName Diffenbaugh
    163 schema:givenName Noah S.
    164 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07755742371.03
    165 rdf:type schema:Person
    166 sg:pub.10.1007/s00382-004-0442-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025795726
    167 https://doi.org/10.1007/s00382-004-0442-9
    168 rdf:type schema:CreativeWork
    169 sg:pub.10.1007/s00382-008-0417-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040266860
    170 https://doi.org/10.1007/s00382-008-0417-3
    171 rdf:type schema:CreativeWork
    172 sg:pub.10.1007/s00382-009-0603-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1012170341
    173 https://doi.org/10.1007/s00382-009-0603-y
    174 rdf:type schema:CreativeWork
    175 sg:pub.10.1007/s00382-009-0641-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014042512
    176 https://doi.org/10.1007/s00382-009-0641-5
    177 rdf:type schema:CreativeWork
    178 sg:pub.10.1007/s00382-010-0977-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1021861148
    179 https://doi.org/10.1007/s00382-010-0977-x
    180 rdf:type schema:CreativeWork
    181 sg:pub.10.1007/s00382-012-1377-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007728471
    182 https://doi.org/10.1007/s00382-012-1377-1
    183 rdf:type schema:CreativeWork
    184 sg:pub.10.1007/s10584-007-9247-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006556053
    185 https://doi.org/10.1007/s10584-007-9247-2
    186 rdf:type schema:CreativeWork
    187 sg:pub.10.1007/s10584-011-0112-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1006938098
    188 https://doi.org/10.1007/s10584-011-0112-y
    189 rdf:type schema:CreativeWork
    190 sg:pub.10.1007/s10584-011-0122-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040318214
    191 https://doi.org/10.1007/s10584-011-0122-9
    192 rdf:type schema:CreativeWork
    193 sg:pub.10.1007/s10584-011-0196-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019020685
    194 https://doi.org/10.1007/s10584-011-0196-4
    195 rdf:type schema:CreativeWork
    196 sg:pub.10.1023/b:clim.0000013685.99609.9e schema:sameAs https://app.dimensions.ai/details/publication/pub.1019795211
    197 https://doi.org/10.1023/b:clim.0000013685.99609.9e
    198 rdf:type schema:CreativeWork
    199 sg:pub.10.1038/nature03089 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028450143
    200 https://doi.org/10.1038/nature03089
    201 rdf:type schema:CreativeWork
    202 sg:pub.10.1038/nature03972 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030525946
    203 https://doi.org/10.1038/nature03972
    204 rdf:type schema:CreativeWork
    205 sg:pub.10.1038/nature04188 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027208376
    206 https://doi.org/10.1038/nature04188
    207 rdf:type schema:CreativeWork
    208 sg:pub.10.1038/nclimate1261 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052952803
    209 https://doi.org/10.1038/nclimate1261
    210 rdf:type schema:CreativeWork
    211 sg:pub.10.1038/nclimate1385 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047584368
    212 https://doi.org/10.1038/nclimate1385
    213 rdf:type schema:CreativeWork
    214 sg:pub.10.1038/nclimate1585 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022202325
    215 https://doi.org/10.1038/nclimate1585
    216 rdf:type schema:CreativeWork
    217 sg:pub.10.1038/ngeo866 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050241953
    218 https://doi.org/10.1038/ngeo866
    219 rdf:type schema:CreativeWork
    220 grid-institutes:grid.168010.e schema:alternateName Department of Environmental Earth System Science, Woods Institute for the Environment, Stanford University, 473 Via Ortega, 94305-4216, Stanford, CA, USA
    221 schema:name Department of Environmental Earth System Science, Woods Institute for the Environment, Stanford University, 473 Via Ortega, 94305-4216, Stanford, CA, USA
    222 rdf:type schema:Organization
    223 grid-institutes:grid.169077.e schema:alternateName Department of Earth and Atmospheric Sciences, Purdue Climate Change Research Center, Purdue University, West Lafayette, IN, USA
    224 schema:name Department of Earth and Atmospheric Sciences, Purdue Climate Change Research Center, Purdue University, West Lafayette, IN, USA
    225 Department of Environmental Earth System Science, Woods Institute for the Environment, Stanford University, 473 Via Ortega, 94305-4216, Stanford, CA, USA
    226 rdf:type schema:Organization
     




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


    ...