{
  "abstract": "Most extreme-heat studies map high-resolution near-surface dry-bulb air temperature ( T a ), yet wet-bulb temperature ( T w ) fields that can capture the combined effects of T a and humidity to represent human heat stress remain limited. This data gap constrains investigation of intra-urban heat variability and the timing of peak heat stress. Here, based on the Rankine-Kirchhoff approximations of Romps, this study innovatively generates hourly 1-km T w by integrating crowdsourced station observations with remote sensing and reanalysis data in machine learning based downscaling frameworks. Taking London during the summers of 2019–2022 as a case study, the tuned RF-based downscaling approach achieved the best performance ( MAE = 0.65 °C, RMSE = 0.93 °C, R 2 = 0.91) among all models. The resulting T w patterns diverge from those commonly reported for T a : blue infrastructure shows no consistent cooling effect, whereas vegetated areas cool T w increasingly as tree cover rises, pointing to tree-dominated green infrastructure as a promising humid-heat countermeasure. Results further show that daily maximum T w occurs 0.7 h earlier than daily maximum T a in London, opposite to findings elsewhere, implying that climate type and coastal influence modulate the timing of peak T w , which may affect the attribution of excess nighttime mortality. Besides, a systematic global assessment of the mechanisms controlling T w extremes is also required in the future.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Civil Engineering, University of Bristol, Bristol BS8 1TR, UK",
    "School of Earth and Environmental Sciences, Cardiff University, Cardiff CF10 3AT, UK; Corresponding author.",
    "Department of Land, Air and Water Resources, University of California Davis, Davis, CA 95616, USA",
    "School of Mechanical, Aerospace and Civil Engineering, University of Sheffield, Sheffield S1 4DT, UK",
    "School of Geography, Nanjing Normal University, Nanjing 210023, China",
    "School of Geography and Planning, Sun Yat-Sen University & Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519000, China"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 7,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Zitong Wen"
    },
    {
      "affs": [
        1
      ],
      "name": "Lu Zhuo"
    },
    {
      "affs": [
        2
      ],
      "name": "Jiao Wang"
    },
    {
      "affs": [
        3
      ],
      "name": "Zeyi Jiang"
    },
    {
      "affs": [
        4
      ],
      "name": "Jingxuan Zhu"
    },
    {
      "affs": [
        5
      ],
      "name": "Ming Zhong"
    },
    {
      "affs": [
        0
      ],
      "name": "Dawei Han"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/bgt66hwseqrfc.bib",
  "cited_by": 0,
  "doi": "10.1016/j.jag.2026.105649",
  "fulltext_url": "http://www.sciencedirect.com/science/article/pii/S1569843226005650",
  "id": "bgt66hwseqrfc",
  "issns": [
    "1569-8432",
    "1872-826X"
  ],
  "landing_url": "https://doi.org/10.1016/j.jag.2026.105649",
  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "lcc",
      "GB3-5030"
    ],
    [
      "lcc",
      "GE1-350"
    ],
    [
      "openalex",
      "2305|Urban Heat Island Mitigation"
    ]
  ],
  "openalex": "W7223559750",
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-31",
  "publisher": "Elsevier",
  "ris": "https://research.draconitic.com/paper/bgt66hwseqrfc.ris",
  "sources": [
    {
      "first_seen": "2026-10-31T14:21:48Z",
      "native_id": "062d56c534a9476c9212cb495a937808",
      "source": "doaj",
      "url": "https://doi.org/10.1016/j.jag.2026.105649"
    }
  ],
  "subjects": [
    {
      "field": "earth",
      "origin": "openalex:2305|Urban Heat Island Mitigation",
      "subfield": "environmental-science"
    }
  ],
  "title": "High-resolution mapping of urban wet-bulb temperature and its intra-urban variability: A London case study",
  "title_text": "High-resolution mapping of urban wet-bulb temperature and its intra-urban variability: A London case study",
  "type": "peer-reviewed",
  "updated_at": "2026-10-31T14:21:48Z",
  "url": "https://research.draconitic.com/paper/bgt66hwseqrfc",
  "venue": "International Journal of Applied Earth Observations and Geoinformation",
  "versions": []
}