Preprints
https://doi.org/10.5194/essd-2023-379
https://doi.org/10.5194/essd-2023-379
04 Dec 2023
 | 04 Dec 2023
Status: a revised version of this preprint was accepted for the journal ESSD and is expected to appear here in due course.

GloUTCI-M: A Global Monthly 1 km Universal Thermal Climate Index Dataset from 2000 to 2022

Zhiwei Yang, Jian Peng, Yanxu Liu, Song Jiang, Xueyan Cheng, Xuebang Liu, Jianquan Dong, Tiantian Hua, and Xiaoyu Yu

Abstract. Climate change has precipitated recurrent extreme events and emerged as an imposing global challenge, exerting profound and far-reaching impacts on both the environment and human existence. The Universal Thermal Climate Index (UTCI), serving as an important approach to human comfort assessment, plays a pivotal role in gauging how the human adapts to meteorological conditions and copes with thermal and cold stress. However, the existing UTCI datasets still grapple with limitations in terms of data availability, hindering their effective application across diverse domains. We have produced the GloUTCI-M, a monthly UTCI dataset boasting global coverage, an extensive time series spanning from March 2000 to October 2022, and a high spatial resolution of 1 km. This dataset is the product of a comprehensive approach leveraging multiple data sources and advanced machine learning models. Our findings underscore the superior predictive capabilities of CatBoost in forecasting UTCI (MAE = 0.747 °C, RMSE = 0.943 °C, R2 = 0.994) when compared to machine learning models such as XGBoost and LightGBM. Utilizing GloUTCI-M, the geographical boundaries of cold stress and thermal stress areas on a global scale were effectively delineated. Over the span of 2001 to 2021, the mean annual global UTCI registers at 17.24 °C, with a pronounced upward trend. Countries like Russia and Brazil emerge as key contributors to the mean annual global UTCI increase, while countries like China and India exert a more inhibitory influence on this trend. Furthermore, in contrast to existing UTCI datasets, GloUTCI-M excels at portraying UTCI distribution at finer spatial resolutions, augmenting data accuracy. This dataset enhances our capacity to evaluate thermal stress experienced by the human, offering substantial prospects across a wide array of applications. The GloUTCI-M is publicly available at https://doi.org/10.5281/zenodo.8310513 (Yang et al., 2023).

Zhiwei Yang, Jian Peng, Yanxu Liu, Song Jiang, Xueyan Cheng, Xuebang Liu, Jianquan Dong, Tiantian Hua, and Xiaoyu Yu

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2023-379', Anonymous Referee #1, 12 Dec 2023
    • AC1: 'Reply on RC1', Jian Peng, 31 Jan 2024
  • RC2: 'Comment on essd-2023-379', Anonymous Referee #2, 19 Dec 2023
    • AC2: 'Reply on RC2', Jian Peng, 31 Jan 2024

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2023-379', Anonymous Referee #1, 12 Dec 2023
    • AC1: 'Reply on RC1', Jian Peng, 31 Jan 2024
  • RC2: 'Comment on essd-2023-379', Anonymous Referee #2, 19 Dec 2023
    • AC2: 'Reply on RC2', Jian Peng, 31 Jan 2024
Zhiwei Yang, Jian Peng, Yanxu Liu, Song Jiang, Xueyan Cheng, Xuebang Liu, Jianquan Dong, Tiantian Hua, and Xiaoyu Yu

Data sets

GloUTCI-M: A Global Monthly 1 km Universal Thermal Climate Index Dataset from 2000 to 2022 Zhiwei Yang, Jian Peng, and Yanxu Liu https://doi.org/10.5281/zenodo.8310513

Zhiwei Yang, Jian Peng, Yanxu Liu, Song Jiang, Xueyan Cheng, Xuebang Liu, Jianquan Dong, Tiantian Hua, and Xiaoyu Yu

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Short summary
The Universal Thermal Climate Index (UTCI) plays a pivotal role in gauging how the human adapts to meteorological conditions and copes with thermal and cold stress. We produced the GloUTCI-M, a monthly UTCI dataset boasting global coverage, an extensive time series spanning from March 2000 to October 2022, and a high spatial resolution of 1 km. We analyzed the global spatiotemporal characteristics and pattern evolution of UTCI based on GloUTCI-M.
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