Sub-seasonal to Seasonal Hindcasts of Stratospheric SuddenWarming by BCC_CSM1.1(m): A Comparison with ECMWF View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-05

AUTHORS

Jian Rao, Rongcai Ren, Haishan Chen, Xiangwen Liu, Yueyue Yu, Yang Yang

ABSTRACT

This study focuses on model predictive skill with respect to stratospheric sudden warming (SSW) events by comparing the hindcast results of BCC_CSM1.1(m) with those of the ECMWF’s model under the sub-seasonal to seasonal prediction project of the World Weather Research Program and World Climate Research Program. When the hindcasts are initiated less than two weeks before SSW onset, BCC_CSM and ECMWF show comparable predictive skill in terms of the temporal evolution of the stratospheric circumpolar westerlies and polar temperature up to 30 days after SSW onset. However, with earlier hindcast initialization, the predictive skill of BCC_CSM gradually decreases, and the reproduced maximum circulation anomalies in the hindcasts initiated four weeks before SSW onset replicate only 10% of the circulation anomaly intensities in observations. The earliest successful prediction of the breakdown of the stratospheric polar vortex accompanying SSW onset for BCC_CSM (ECMWF) is the hindcast initiated two (three) weeks earlier. The predictive skills of both models during SSW winters are always higher than that during non-SSW winters, in relation to the successfully captured tropospheric precursors and the associated upward propagation of planetary waves by the model initializations. To narrow the gap in SSW predictive skill between BCC_CSM and ECMWF, ensemble forecasts and error corrections are performed with BCC_CSM. The SSW predictive skill in the ensemble hindcasts and the error corrections are improved compared with the previous control forecasts. More... »

PAGES

479-494

References to SciGraph publications

  • 2015-07. Parallel comparison of the northern winter stratospheric circulation in reanalysis and in CMIP5 models in ADVANCES IN ATMOSPHERIC SCIENCES
  • 2013-10. Variability of the Indian Ocean SST and its possible impact on summer western North Pacific anticyclone in the NCEP Climate Forecast System in CLIMATE DYNAMICS
  • 2016-06. A decomposition of ENSO’s impacts on the northern winter stratosphere: competing effect of SST forcing in the tropical Indian Ocean in CLIMATE DYNAMICS
  • 2014-03. Improvement of 6–15 day precipitation forecasts using a time-lagged ensemble method in ADVANCES IN ATMOSPHERIC SCIENCES
  • 2008-06. Prediction of carbon exchanges between China terrestrial ecosystem and atmosphere in 21st century in SCIENCE IN CHINA SERIES D EARTH SCIENCES
  • 2017-09. Parallel comparison of the 1982/83, 1997/98 and 2015/16 super El Niños and their effects on the extratropical stratosphere in ADVANCES IN ATMOSPHERIC SCIENCES
  • 2017-05. MJO prediction using the sub-seasonal to seasonal forecast model of Beijing Climate Center in CLIMATE DYNAMICS
  • 2016-02. Evaluation of the tropical variability from the Beijing Climate Center’s real-time operational global Ocean Data Assimilation System in ADVANCES IN ATMOSPHERIC SCIENCES
  • 2012-12. Asian summer monsoon prediction in ECMWF System 4 and NCEP CFSv2 retrospective seasonal forecasts in CLIMATE DYNAMICS
  • 2010-01. The Beijing Climate Center atmospheric general circulation model: description and its performance for the present-day climate in CLIMATE DYNAMICS
  • 2014-02. An overview of BCC climate system model development and application for climate change studies in ACTA METEOROLOGICA SINICA
  • 2018-09. Varying stratospheric responses to tropical Atlantic SST forcing from early to late winter in CLIMATE DYNAMICS
  • 2017-05. Tracking the delayed response of the northern winter stratosphere to ENSO using multi reanalyses and model simulations in CLIMATE DYNAMICS
  • 2012-04. Observational evidence of the delayed response of stratospheric polar vortex variability to ENSO SST anomalies in CLIMATE DYNAMICS
  • 2017-07. Lessened response of boreal winter stratospheric polar vortex to El Niño in recent decades in CLIMATE DYNAMICS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s00376-018-8165-8

    DOI

    http://dx.doi.org/10.1007/s00376-018-8165-8

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1112965226


    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/2008/0401", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Atmospheric Sciences", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/04", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Earth Sciences", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Hebrew University of Jerusalem", 
              "id": "https://www.grid.ac/institutes/grid.9619.7", 
              "name": [
                "Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, 210044, Nanjing, China", 
                "State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, 100029, Beijing, China", 
                "Fredy and Nadine Herrmann Institute of Earth Sciences, The Hebrew University of Jerusalem, Edmond J. Safra Campus, 91904, Givat Ram Jerusalem, Israel"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Rao", 
            "givenName": "Jian", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Institute of Atmospheric Physics", 
              "id": "https://www.grid.ac/institutes/grid.424023.3", 
              "name": [
                "Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, 210044, Nanjing, China", 
                "State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, 100029, Beijing, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Ren", 
            "givenName": "Rongcai", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Nanjing University of Information Science and Technology", 
              "id": "https://www.grid.ac/institutes/grid.260478.f", 
              "name": [
                "Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, 210044, Nanjing, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Chen", 
            "givenName": "Haishan", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "China Meteorological Administration", 
              "id": "https://www.grid.ac/institutes/grid.8658.3", 
              "name": [
                "Climate Model Division, National Climate Center, China Meteorological Administration, 100081, Beijing, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Liu", 
            "givenName": "Xiangwen", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Nanjing University of Information Science and Technology", 
              "id": "https://www.grid.ac/institutes/grid.260478.f", 
              "name": [
                "Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, 210044, Nanjing, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Yu", 
            "givenName": "Yueyue", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "China Meteorological Administration", 
              "id": "https://www.grid.ac/institutes/grid.8658.3", 
              "name": [
                "Institute of Urban Meteorology, China Meteorological Administration, 100089, Beijing, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Yang", 
            "givenName": "Yang", 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1029/2007jd008481", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002167410"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1175/bams-d-16-0017.1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004447550"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1175/1520-0442(2004)017<3548:uwafaa>2.0.co;2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004729525"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00382-016-3340-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005098207", 
              "https://doi.org/10.1007/s00382-016-3340-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00382-016-3340-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005098207", 
              "https://doi.org/10.1007/s00382-016-3340-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00382-016-3238-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006504688", 
              "https://doi.org/10.1007/s00382-016-3238-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00382-016-3238-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006504688", 
              "https://doi.org/10.1007/s00382-016-3238-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1175/1520-0493(1981)109<0784:titghf>2.0.co;2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006533719"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00376-015-4282-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006843260", 
              "https://doi.org/10.1007/s00376-015-4282-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s13351-014-3041-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010421819", 
              "https://doi.org/10.1007/s13351-014-3041-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1175/1520-0477(1996)077<0437:tnyrp>2.0.co;2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011849757"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00376-014-4192-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012578497", 
              "https://doi.org/10.1007/s00376-014-4192-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1029/2006gl027927", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012770867"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1175/jcli-d-13-00471.1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014250669"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/qj.2256", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014794635"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.5194/os-1-45-2005", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016656091"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.5194/os-1-45-2005", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016656091"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/qj.2432", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017182118"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1175/jcli3996.1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017645244"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1175/2010bams3013.1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017763926"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/2015jd024520", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019897188"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00382-015-2797-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020598332", 
              "https://doi.org/10.1007/s00382-015-2797-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1175/2009bams2752.1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021621452"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1063315", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021850180"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00382-012-1470-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022910618", 
              "https://doi.org/10.1007/s00382-012-1470-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00382-013-1934-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027485413", 
              "https://doi.org/10.1007/s00382-013-1934-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1175/bams-d-14-00287.1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028621073"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00376-013-3037-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031783407", 
              "https://doi.org/10.1007/s00376-013-3037-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1175/jcli-d-12-00437.1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031787174"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11430-008-0039-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1032373430", 
              "https://doi.org/10.1007/s11430-008-0039-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1029/2005gl025024", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1032537182"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1029/2005gl025024", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1032537182"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1029/1999jd900445", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1032859313"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1175/2008mwr2272.1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033352339"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00382-011-1137-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034754408", 
              "https://doi.org/10.1007/s00382-011-1137-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1175/jas-d-14-0390.1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037277365"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1175/jcli-d-13-00190.1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038241443"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1088/1748-9326/aa538a", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038322719"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00382-016-3264-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039236540", 
              "https://doi.org/10.1007/s00382-016-3264-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00382-016-3264-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039236540", 
              "https://doi.org/10.1007/s00382-016-3264-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/qj.828", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039601605"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/2015jd024521", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039935723"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.5194/acp-12-5259-2012", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042082690"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1088/1748-9326/7/1/015602", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045262730"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00382-008-0487-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045325006", 
              "https://doi.org/10.1007/s00382-008-0487-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00382-008-0487-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045325006", 
              "https://doi.org/10.1007/s00382-008-0487-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1175/jas-d-13-0349.1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1049288261"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1175/mwr-d-15-0010.1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051167964"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1175/bams-d-11-00094.1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051805105"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1175/1520-0426(2000)017<0525:artlsi>2.0.co;2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1063421195"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00376-017-6260-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1090993346", 
              "https://doi.org/10.1007/s00376-017-6260-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00376-017-6260-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1090993346", 
              "https://doi.org/10.1007/s00376-017-6260-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00382-017-3998-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1092615879", 
              "https://doi.org/10.1007/s00382-017-3998-x"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2019-05", 
        "datePublishedReg": "2019-05-01", 
        "description": "This study focuses on model predictive skill with respect to stratospheric sudden warming (SSW) events by comparing the hindcast results of BCC_CSM1.1(m) with those of the ECMWF\u2019s model under the sub-seasonal to seasonal prediction project of the World Weather Research Program and World Climate Research Program. When the hindcasts are initiated less than two weeks before SSW onset, BCC_CSM and ECMWF show comparable predictive skill in terms of the temporal evolution of the stratospheric circumpolar westerlies and polar temperature up to 30 days after SSW onset. However, with earlier hindcast initialization, the predictive skill of BCC_CSM gradually decreases, and the reproduced maximum circulation anomalies in the hindcasts initiated four weeks before SSW onset replicate only 10% of the circulation anomaly intensities in observations. The earliest successful prediction of the breakdown of the stratospheric polar vortex accompanying SSW onset for BCC_CSM (ECMWF) is the hindcast initiated two (three) weeks earlier. The predictive skills of both models during SSW winters are always higher than that during non-SSW winters, in relation to the successfully captured tropospheric precursors and the associated upward propagation of planetary waves by the model initializations. To narrow the gap in SSW predictive skill between BCC_CSM and ECMWF, ensemble forecasts and error corrections are performed with BCC_CSM. The SSW predictive skill in the ensemble hindcasts and the error corrections are improved compared with the previous control forecasts.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1007/s00376-018-8165-8", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": [
          {
            "id": "sg:journal.1135901", 
            "issn": [
              "0256-1530", 
              "1861-9533"
            ], 
            "name": "Advances in Atmospheric Sciences", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "5", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "36"
          }
        ], 
        "name": "Sub-seasonal to Seasonal Hindcasts of Stratospheric SuddenWarming by BCC_CSM1.1(m): A Comparison with ECMWF", 
        "pagination": "479-494", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "6430d30b8c74a5d8dc3dba6b09898355ac4911fe59861b1a52d859fffcd34410"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s00376-018-8165-8"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1112965226"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s00376-018-8165-8", 
          "https://app.dimensions.ai/details/publication/pub.1112965226"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T13:18", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000368_0000000368/records_78944_00000001.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://link.springer.com/10.1007%2Fs00376-018-8165-8"
      }
    ]
     

    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/s00376-018-8165-8'

    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/s00376-018-8165-8'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00376-018-8165-8'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00376-018-8165-8'


     

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

    256 TRIPLES      21 PREDICATES      73 URIs      19 LITERALS      7 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s00376-018-8165-8 schema:about anzsrc-for:04
    2 anzsrc-for:0401
    3 schema:author N4b9d0d93b89449cab70b05b7d579e2f0
    4 schema:citation sg:pub.10.1007/s00376-013-3037-8
    5 sg:pub.10.1007/s00376-014-4192-2
    6 sg:pub.10.1007/s00376-015-4282-9
    7 sg:pub.10.1007/s00376-017-6260-x
    8 sg:pub.10.1007/s00382-008-0487-2
    9 sg:pub.10.1007/s00382-011-1137-7
    10 sg:pub.10.1007/s00382-012-1470-5
    11 sg:pub.10.1007/s00382-013-1934-2
    12 sg:pub.10.1007/s00382-015-2797-5
    13 sg:pub.10.1007/s00382-016-3238-9
    14 sg:pub.10.1007/s00382-016-3264-7
    15 sg:pub.10.1007/s00382-016-3340-z
    16 sg:pub.10.1007/s00382-017-3998-x
    17 sg:pub.10.1007/s11430-008-0039-y
    18 sg:pub.10.1007/s13351-014-3041-7
    19 https://doi.org/10.1002/2015jd024520
    20 https://doi.org/10.1002/2015jd024521
    21 https://doi.org/10.1002/qj.2256
    22 https://doi.org/10.1002/qj.2432
    23 https://doi.org/10.1002/qj.828
    24 https://doi.org/10.1029/1999jd900445
    25 https://doi.org/10.1029/2005gl025024
    26 https://doi.org/10.1029/2006gl027927
    27 https://doi.org/10.1029/2007jd008481
    28 https://doi.org/10.1088/1748-9326/7/1/015602
    29 https://doi.org/10.1088/1748-9326/aa538a
    30 https://doi.org/10.1126/science.1063315
    31 https://doi.org/10.1175/1520-0426(2000)017<0525:artlsi>2.0.co;2
    32 https://doi.org/10.1175/1520-0442(2004)017<3548:uwafaa>2.0.co;2
    33 https://doi.org/10.1175/1520-0477(1996)077<0437:tnyrp>2.0.co;2
    34 https://doi.org/10.1175/1520-0493(1981)109<0784:titghf>2.0.co;2
    35 https://doi.org/10.1175/2008mwr2272.1
    36 https://doi.org/10.1175/2009bams2752.1
    37 https://doi.org/10.1175/2010bams3013.1
    38 https://doi.org/10.1175/bams-d-11-00094.1
    39 https://doi.org/10.1175/bams-d-14-00287.1
    40 https://doi.org/10.1175/bams-d-16-0017.1
    41 https://doi.org/10.1175/jas-d-13-0349.1
    42 https://doi.org/10.1175/jas-d-14-0390.1
    43 https://doi.org/10.1175/jcli-d-12-00437.1
    44 https://doi.org/10.1175/jcli-d-13-00190.1
    45 https://doi.org/10.1175/jcli-d-13-00471.1
    46 https://doi.org/10.1175/jcli3996.1
    47 https://doi.org/10.1175/mwr-d-15-0010.1
    48 https://doi.org/10.5194/acp-12-5259-2012
    49 https://doi.org/10.5194/os-1-45-2005
    50 schema:datePublished 2019-05
    51 schema:datePublishedReg 2019-05-01
    52 schema:description This study focuses on model predictive skill with respect to stratospheric sudden warming (SSW) events by comparing the hindcast results of BCC_CSM1.1(m) with those of the ECMWF’s model under the sub-seasonal to seasonal prediction project of the World Weather Research Program and World Climate Research Program. When the hindcasts are initiated less than two weeks before SSW onset, BCC_CSM and ECMWF show comparable predictive skill in terms of the temporal evolution of the stratospheric circumpolar westerlies and polar temperature up to 30 days after SSW onset. However, with earlier hindcast initialization, the predictive skill of BCC_CSM gradually decreases, and the reproduced maximum circulation anomalies in the hindcasts initiated four weeks before SSW onset replicate only 10% of the circulation anomaly intensities in observations. The earliest successful prediction of the breakdown of the stratospheric polar vortex accompanying SSW onset for BCC_CSM (ECMWF) is the hindcast initiated two (three) weeks earlier. The predictive skills of both models during SSW winters are always higher than that during non-SSW winters, in relation to the successfully captured tropospheric precursors and the associated upward propagation of planetary waves by the model initializations. To narrow the gap in SSW predictive skill between BCC_CSM and ECMWF, ensemble forecasts and error corrections are performed with BCC_CSM. The SSW predictive skill in the ensemble hindcasts and the error corrections are improved compared with the previous control forecasts.
    53 schema:genre research_article
    54 schema:inLanguage en
    55 schema:isAccessibleForFree false
    56 schema:isPartOf N195c80a996c049b48a4a82febbf78639
    57 Nf405cf96f7024b729bda255eee64335a
    58 sg:journal.1135901
    59 schema:name Sub-seasonal to Seasonal Hindcasts of Stratospheric SuddenWarming by BCC_CSM1.1(m): A Comparison with ECMWF
    60 schema:pagination 479-494
    61 schema:productId N142a5c5f282a40aeadf8cfd534b68ef8
    62 N1ba4b25daf464e6895b68e595b0288db
    63 N3ff69a2ad7044db4b62d37f129f60314
    64 schema:sameAs https://app.dimensions.ai/details/publication/pub.1112965226
    65 https://doi.org/10.1007/s00376-018-8165-8
    66 schema:sdDatePublished 2019-04-11T13:18
    67 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    68 schema:sdPublisher Nc5a0319e6c2c4b188c4614eca6e00ad8
    69 schema:url https://link.springer.com/10.1007%2Fs00376-018-8165-8
    70 sgo:license sg:explorer/license/
    71 sgo:sdDataset articles
    72 rdf:type schema:ScholarlyArticle
    73 N142a5c5f282a40aeadf8cfd534b68ef8 schema:name readcube_id
    74 schema:value 6430d30b8c74a5d8dc3dba6b09898355ac4911fe59861b1a52d859fffcd34410
    75 rdf:type schema:PropertyValue
    76 N195c80a996c049b48a4a82febbf78639 schema:issueNumber 5
    77 rdf:type schema:PublicationIssue
    78 N1ba4b25daf464e6895b68e595b0288db schema:name dimensions_id
    79 schema:value pub.1112965226
    80 rdf:type schema:PropertyValue
    81 N219fccfd7fd64d98892a510a39d972b5 rdf:first N39b397937712406aa012a04ca6eab619
    82 rdf:rest N371bc8ad87b44185a87f118cd327b945
    83 N35a545dbdc884a9cb9d4324a8b84ad69 schema:affiliation https://www.grid.ac/institutes/grid.260478.f
    84 schema:familyName Chen
    85 schema:givenName Haishan
    86 rdf:type schema:Person
    87 N371bc8ad87b44185a87f118cd327b945 rdf:first N5b59d706477a459f974db3be5e3ea30f
    88 rdf:rest N7560233208a641e3a3f482d3f6604a7b
    89 N39b397937712406aa012a04ca6eab619 schema:affiliation https://www.grid.ac/institutes/grid.8658.3
    90 schema:familyName Liu
    91 schema:givenName Xiangwen
    92 rdf:type schema:Person
    93 N3ff69a2ad7044db4b62d37f129f60314 schema:name doi
    94 schema:value 10.1007/s00376-018-8165-8
    95 rdf:type schema:PropertyValue
    96 N4b9d0d93b89449cab70b05b7d579e2f0 rdf:first Nedb87a46abcf4d98ac7554196efef5da
    97 rdf:rest N660160db0c094117b43182cd774187c7
    98 N5b59d706477a459f974db3be5e3ea30f schema:affiliation https://www.grid.ac/institutes/grid.260478.f
    99 schema:familyName Yu
    100 schema:givenName Yueyue
    101 rdf:type schema:Person
    102 N646024b2dc5a4a1d855a7c43b322b8dd schema:affiliation https://www.grid.ac/institutes/grid.424023.3
    103 schema:familyName Ren
    104 schema:givenName Rongcai
    105 rdf:type schema:Person
    106 N660160db0c094117b43182cd774187c7 rdf:first N646024b2dc5a4a1d855a7c43b322b8dd
    107 rdf:rest Nb5f9f65c8b1e4489ad1e360fd2f6163a
    108 N7560233208a641e3a3f482d3f6604a7b rdf:first Ne4726a14f9aa42b2bab6a410709a85b2
    109 rdf:rest rdf:nil
    110 Nb5f9f65c8b1e4489ad1e360fd2f6163a rdf:first N35a545dbdc884a9cb9d4324a8b84ad69
    111 rdf:rest N219fccfd7fd64d98892a510a39d972b5
    112 Nc5a0319e6c2c4b188c4614eca6e00ad8 schema:name Springer Nature - SN SciGraph project
    113 rdf:type schema:Organization
    114 Ne4726a14f9aa42b2bab6a410709a85b2 schema:affiliation https://www.grid.ac/institutes/grid.8658.3
    115 schema:familyName Yang
    116 schema:givenName Yang
    117 rdf:type schema:Person
    118 Nedb87a46abcf4d98ac7554196efef5da schema:affiliation https://www.grid.ac/institutes/grid.9619.7
    119 schema:familyName Rao
    120 schema:givenName Jian
    121 rdf:type schema:Person
    122 Nf405cf96f7024b729bda255eee64335a schema:volumeNumber 36
    123 rdf:type schema:PublicationVolume
    124 anzsrc-for:04 schema:inDefinedTermSet anzsrc-for:
    125 schema:name Earth Sciences
    126 rdf:type schema:DefinedTerm
    127 anzsrc-for:0401 schema:inDefinedTermSet anzsrc-for:
    128 schema:name Atmospheric Sciences
    129 rdf:type schema:DefinedTerm
    130 sg:journal.1135901 schema:issn 0256-1530
    131 1861-9533
    132 schema:name Advances in Atmospheric Sciences
    133 rdf:type schema:Periodical
    134 sg:pub.10.1007/s00376-013-3037-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031783407
    135 https://doi.org/10.1007/s00376-013-3037-8
    136 rdf:type schema:CreativeWork
    137 sg:pub.10.1007/s00376-014-4192-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012578497
    138 https://doi.org/10.1007/s00376-014-4192-2
    139 rdf:type schema:CreativeWork
    140 sg:pub.10.1007/s00376-015-4282-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006843260
    141 https://doi.org/10.1007/s00376-015-4282-9
    142 rdf:type schema:CreativeWork
    143 sg:pub.10.1007/s00376-017-6260-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1090993346
    144 https://doi.org/10.1007/s00376-017-6260-x
    145 rdf:type schema:CreativeWork
    146 sg:pub.10.1007/s00382-008-0487-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045325006
    147 https://doi.org/10.1007/s00382-008-0487-2
    148 rdf:type schema:CreativeWork
    149 sg:pub.10.1007/s00382-011-1137-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034754408
    150 https://doi.org/10.1007/s00382-011-1137-7
    151 rdf:type schema:CreativeWork
    152 sg:pub.10.1007/s00382-012-1470-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022910618
    153 https://doi.org/10.1007/s00382-012-1470-5
    154 rdf:type schema:CreativeWork
    155 sg:pub.10.1007/s00382-013-1934-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027485413
    156 https://doi.org/10.1007/s00382-013-1934-2
    157 rdf:type schema:CreativeWork
    158 sg:pub.10.1007/s00382-015-2797-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020598332
    159 https://doi.org/10.1007/s00382-015-2797-5
    160 rdf:type schema:CreativeWork
    161 sg:pub.10.1007/s00382-016-3238-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006504688
    162 https://doi.org/10.1007/s00382-016-3238-9
    163 rdf:type schema:CreativeWork
    164 sg:pub.10.1007/s00382-016-3264-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039236540
    165 https://doi.org/10.1007/s00382-016-3264-7
    166 rdf:type schema:CreativeWork
    167 sg:pub.10.1007/s00382-016-3340-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1005098207
    168 https://doi.org/10.1007/s00382-016-3340-z
    169 rdf:type schema:CreativeWork
    170 sg:pub.10.1007/s00382-017-3998-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1092615879
    171 https://doi.org/10.1007/s00382-017-3998-x
    172 rdf:type schema:CreativeWork
    173 sg:pub.10.1007/s11430-008-0039-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1032373430
    174 https://doi.org/10.1007/s11430-008-0039-y
    175 rdf:type schema:CreativeWork
    176 sg:pub.10.1007/s13351-014-3041-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010421819
    177 https://doi.org/10.1007/s13351-014-3041-7
    178 rdf:type schema:CreativeWork
    179 https://doi.org/10.1002/2015jd024520 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019897188
    180 rdf:type schema:CreativeWork
    181 https://doi.org/10.1002/2015jd024521 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039935723
    182 rdf:type schema:CreativeWork
    183 https://doi.org/10.1002/qj.2256 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014794635
    184 rdf:type schema:CreativeWork
    185 https://doi.org/10.1002/qj.2432 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017182118
    186 rdf:type schema:CreativeWork
    187 https://doi.org/10.1002/qj.828 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039601605
    188 rdf:type schema:CreativeWork
    189 https://doi.org/10.1029/1999jd900445 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032859313
    190 rdf:type schema:CreativeWork
    191 https://doi.org/10.1029/2005gl025024 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032537182
    192 rdf:type schema:CreativeWork
    193 https://doi.org/10.1029/2006gl027927 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012770867
    194 rdf:type schema:CreativeWork
    195 https://doi.org/10.1029/2007jd008481 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002167410
    196 rdf:type schema:CreativeWork
    197 https://doi.org/10.1088/1748-9326/7/1/015602 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045262730
    198 rdf:type schema:CreativeWork
    199 https://doi.org/10.1088/1748-9326/aa538a schema:sameAs https://app.dimensions.ai/details/publication/pub.1038322719
    200 rdf:type schema:CreativeWork
    201 https://doi.org/10.1126/science.1063315 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021850180
    202 rdf:type schema:CreativeWork
    203 https://doi.org/10.1175/1520-0426(2000)017<0525:artlsi>2.0.co;2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1063421195
    204 rdf:type schema:CreativeWork
    205 https://doi.org/10.1175/1520-0442(2004)017<3548:uwafaa>2.0.co;2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004729525
    206 rdf:type schema:CreativeWork
    207 https://doi.org/10.1175/1520-0477(1996)077<0437:tnyrp>2.0.co;2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011849757
    208 rdf:type schema:CreativeWork
    209 https://doi.org/10.1175/1520-0493(1981)109<0784:titghf>2.0.co;2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006533719
    210 rdf:type schema:CreativeWork
    211 https://doi.org/10.1175/2008mwr2272.1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033352339
    212 rdf:type schema:CreativeWork
    213 https://doi.org/10.1175/2009bams2752.1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021621452
    214 rdf:type schema:CreativeWork
    215 https://doi.org/10.1175/2010bams3013.1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017763926
    216 rdf:type schema:CreativeWork
    217 https://doi.org/10.1175/bams-d-11-00094.1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051805105
    218 rdf:type schema:CreativeWork
    219 https://doi.org/10.1175/bams-d-14-00287.1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028621073
    220 rdf:type schema:CreativeWork
    221 https://doi.org/10.1175/bams-d-16-0017.1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004447550
    222 rdf:type schema:CreativeWork
    223 https://doi.org/10.1175/jas-d-13-0349.1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049288261
    224 rdf:type schema:CreativeWork
    225 https://doi.org/10.1175/jas-d-14-0390.1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037277365
    226 rdf:type schema:CreativeWork
    227 https://doi.org/10.1175/jcli-d-12-00437.1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031787174
    228 rdf:type schema:CreativeWork
    229 https://doi.org/10.1175/jcli-d-13-00190.1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038241443
    230 rdf:type schema:CreativeWork
    231 https://doi.org/10.1175/jcli-d-13-00471.1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014250669
    232 rdf:type schema:CreativeWork
    233 https://doi.org/10.1175/jcli3996.1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017645244
    234 rdf:type schema:CreativeWork
    235 https://doi.org/10.1175/mwr-d-15-0010.1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051167964
    236 rdf:type schema:CreativeWork
    237 https://doi.org/10.5194/acp-12-5259-2012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042082690
    238 rdf:type schema:CreativeWork
    239 https://doi.org/10.5194/os-1-45-2005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016656091
    240 rdf:type schema:CreativeWork
    241 https://www.grid.ac/institutes/grid.260478.f schema:alternateName Nanjing University of Information Science and Technology
    242 schema:name Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, 210044, Nanjing, China
    243 rdf:type schema:Organization
    244 https://www.grid.ac/institutes/grid.424023.3 schema:alternateName Institute of Atmospheric Physics
    245 schema:name Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, 210044, Nanjing, China
    246 State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, 100029, Beijing, China
    247 rdf:type schema:Organization
    248 https://www.grid.ac/institutes/grid.8658.3 schema:alternateName China Meteorological Administration
    249 schema:name Climate Model Division, National Climate Center, China Meteorological Administration, 100081, Beijing, China
    250 Institute of Urban Meteorology, China Meteorological Administration, 100089, Beijing, China
    251 rdf:type schema:Organization
    252 https://www.grid.ac/institutes/grid.9619.7 schema:alternateName Hebrew University of Jerusalem
    253 schema:name Fredy and Nadine Herrmann Institute of Earth Sciences, The Hebrew University of Jerusalem, Edmond J. Safra Campus, 91904, Givat Ram Jerusalem, Israel
    254 Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, 210044, Nanjing, China
    255 State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, 100029, Beijing, China
    256 rdf:type schema:Organization
     




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


    ...