{
  "abstract": "Subseasonal prediction of Northern Hemisphere extratropical cyclones (ETCs) is critical for anticipating associated weather extremes, yet biases and predictability limits of ETC activity in current forecast systems remain insufficiently quantified. Here, using hindcasts from ten state-of-the-art subseasonal-to-seasonal (S2S) prediction systems within a Lagrangian tracking framework, we uncover a common and pervasive bias: the multi-model ensemble consistently predicts fewer and weaker cyclones at a one-month lead, underestimating frequency by 10-18% and intensity by approximately 13%, with more pronounced frequency deficits exceeding 26% specifically for winter bomb cyclones. These biases are dynamically driven by misrepresented meridional temperature gradients, which contribute to weaker and meridionally displaced upper-tropospheric jets and reduced peak baroclinic instability, thereby suppressing ETC formation and intensification. We further reveal that regional ETC frequency prediction skill during their respective peak seasons is limited to approximately 9–18 days, with substantial regional contrasts: the longest predictability horizon extends over the North Pacific, whereas the horizon is shortest over the North Atlantic. These regional differences are associated with variations in the dominant large-scale atmospheric drivers and their predictability over different regions. These findings establish an event-based benchmark for evaluating subseasonal ETC predictions and underscore key forecast bottlenecks in current S2S systems. Improving the representation of large-scale baroclinic environments and further unravelling the interactions between regional ETC activity and predictability sources will be essential for advancing reliable subseasonal predictions of ETC-related hazards.",
  "abstract_shown": true,
  "affiliations": [
    "Beijing Normal University Faculty of Geographical Science",
    "Beijing Normal University",
    "The Hong Kong University of Science and Technology",
    "Chinese Acad Sci",
    "National Climate Center, China Meteorological Administration",
    "Met Office"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 7,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Shentong Li",
      "orcid": "0009-0006-4351-4783"
    },
    {
      "affs": [
        1
      ],
      "name": "Jing Yang",
      "orcid": "0000-0001-7063-6264"
    },
    {
      "affs": [
        0
      ],
      "name": "Anling Liu"
    },
    {
      "affs": [
        2
      ],
      "name": "Mengqian Lu"
    },
    {
      "affs": [
        3
      ],
      "name": "Qing Bao",
      "orcid": "0000-0003-1719-6540"
    },
    {
      "affs": [
        4
      ],
      "name": "Jie Wu",
      "orcid": "0000-0002-7806-6718"
    },
    {
      "affs": [
        5
      ],
      "name": "Stacey New",
      "orcid": "0000-0001-7992-2179"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/617nq236g7g8g.bib",
  "cited_by": 0,
  "doi": "10.1088/1748-9326/aebbd7",
  "fulltext_url": null,
  "id": "617nq236g7g8g",
  "issns": [
    "1748-9326"
  ],
  "landing_url": "https://iopscience.iop.org/article/10.1088/1748-9326/aebbd7",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "feed-journal",
      "earth/environmental-science"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://iopscience.iop.org/article/10.1088/1748-9326/aebbd7/pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-30",
  "publisher": "IOP Publishing",
  "ris": "https://research.draconitic.com/paper/617nq236g7g8g.ris",
  "sources": [
    {
      "first_seen": "2026-10-31T00:21:15Z",
      "native_id": "10.1088/1748-9326/aebbd7",
      "source": "crossref",
      "url": "https://iopscience.iop.org/article/10.1088/1748-9326/aebbd7"
    },
    {
      "first_seen": "2026-11-09T12:20:32Z",
      "native_id": "10.1088/1748-9326/aebbd7",
      "source": "feed-iop",
      "url": "https://iopscience.iop.org/article/10.1088/1748-9326/aebbd7"
    }
  ],
  "subjects": [
    {
      "field": "earth",
      "origin": "feed-journal:earth/environmental-science",
      "subfield": "environmental-science"
    }
  ],
  "title": "Biases and predictability limits of Northern Hemisphere extratropical cyclones in subseasonal prediction systems",
  "title_text": "Biases and predictability limits of Northern Hemisphere extratropical cyclones in subseasonal prediction systems",
  "type": "peer-reviewed",
  "updated_at": "2026-11-09T18:20:18Z",
  "url": "https://research.draconitic.com/paper/617nq236g7g8g",
  "venue": "Environmental Research Letters",
  "versions": []
}