Evidence map›Paper›PMID 39390007›Full record

ArticleScientific data2024

A high temporal resolution global gridded dataset of human thermal stress metrics.

Hongdeng Jian, Zhenzhen Yan, Xiangtao Fan, Qin Zhan, Chen Xu, Weijia Bei, Jianhao Xu, Mingrui Huang, Xiaoping Du, Junjie Zhu and 3 more

Abstract readDataset
In one paragraph

Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Hongdeng JianInternational Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China.ORCID 0009-0007-3635-2082
Zhenzhen YanInternational Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China. yanzz@radi.ac.cn.
Xiangtao FanInternational Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China. fanxt@radi.ac.cn.
Qin ZhanInternational Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China.
Chen XuInternational Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China.
Weijia BeiInternational Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China.
Jianhao XuInternational Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China.
Mingrui HuangInternational Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China.
Xiaoping DuInternational Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China.
Junjie ZhuInternational Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China.
Zhimin TaiInternational Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China.
Jiangtao HaoInternational Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China.
Yanan HuInternational Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The human thermal stress indices and datasets are vital for promoting public health and reducing negative environmental impacts as global climate change and extreme meteorological events increase. The current thermal indices generally use an instantaneous or average value to describe thermal stress which cannot reflect the distribution of thermal comfort conditions over time, and there are no global-scale thermal stress datasets with both 0.1° or higher spatial resolution and hourly temporal resolution available yet. A novel human thermal metric, Thermal Stress Duration (TSD), is proposed to represent the accumulative time of different thermal stress levels within a certain period. A high temporal resolution global gridded dataset of human thermal stress metrics (HiGTS) is presented, which consists of hourly gridded maps of Universal Thermal Climate Index (UTCI), Universal Thermal Stress (UTS), and daily TSD at 0.1° × 0.1° spatial resolution over the global land surface, spanning from January 1, 2000, to December 31, 2023.

Indexed as

Climate ChangeHumans

Identifiers

PMID39390007
PMCPMC11467259

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.