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Dominant modes of summer wet bulb temperature in China

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Abstract

As a combination of temperature and humidity, wet-bulb temperature (WBT) is useful for assessing heat stress and its societal and economic impacts. However, spatial and temporal behaviors of summer WBT in China remain poorly understood. In this study, we investigate the dominant spatiotemporal modes of summer (June–July–August) WBT in the mainland of China during 1960–2017 by using empirical orthogonal function (EOF) analysis and reveal their corresponding underlying mechanisms. The leading mode (EOF1) of summer WBT in China shows a nationwide increasing WBT with a stronger magnitude in northern and western than southeastern China. The second mode (EOF2) displays a zonal pattern with anomalously increased WBT in the west and decreased WBT in the east. The third mode (EOF3) shows a meridional feature with the largest WBT trends appearing in the Yangtze River valley. Further examinations suggest that EOF1 exhibits remarkable interdecadal/long-term variations and is likely connected with global warming and the Atlantic Multidecadal Oscillation (AMO), which induce an anomalous anticyclone centering over northern China and covering nearly the whole country. This anticyclone not only plays a key role in the nationwide WBT increases, but also dominates the spatial pattern of EOF1 by modulating relative humidity. EOF2 and EOF3 reflect interannual variations and show significant correlations with the El Niño-Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO), respectively. A zonal wavelike pattern with troughs over Balkhash and northeastern China, and Mongolia high substantially modulates the water vapor transport in China, thus playing a key role in EOF2. In the case of EOF3, an anomalous anticyclone in the middle-upper troposphere and a shallow intensified cyclone in the lower troposphere collectively format the spatial pattern of EOF3 by inducing significant increases in temperature in central-eastern China and transporting a large amount of water vapor to northeastern China, respectively. These findings are critical to improve our understanding of summer WBT in China and to mitigate the negative effects of heat stress.

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Data availability statement

The daily mean temperature data used in this study are available on the following website: http://data.cma.cn. The daily mean relative humidity data are available from the homogenized relative humidity dataset (ChinaRHv1.0) (http://www.scidb.cn/en/detail?dataSetId=633694461334913025&language=zh_CN&dataSetType=personal). NCEP-NCAR reanalysis dataset, the monthly Extended Reconstructed Sea Surface Temperature version 4, and the monthly precipitation are available from the following websites: https://psl.noaa.gov/data/gridded/data.ncep.reanalysis.pressure.html#, https://psl.noaa.gov/data/gridded/data.noaa.ersst.v5.html, and https://psl.noaa.gov/data/gridded/data.prec.html, respectively. The authors are greatly thankful to three anonymous reviewers for their constructive suggestions and comments that improve our paper.

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Acknowledgements

This study is funded by the National Natural Science Foundation of China (No. 41871029 and 91644226) and the National Key R&D Program of China (2019YFC1510400). The appointment of M. Luo at Sun Yat-sen University is partially supported by the Pearl River Talent Plan of Guangdong Province, China (2017GC010634). Z. Liu is supported by the Institute for Basic Science (IBS), Republic of Korea (IBS-R028-D1).

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Authors and Affiliations

  1. School of Geography and Planning, Sun Yat-Sen University, Guangzhou, 510006, China

    Guicai Ning, Ming Luo & Peng Wang

  2. The Gansu Key Laboratory of Arid Climate Change and Reducing Disaster, College of Atmospheric Sciences, Lanzhou University, Lanzhou, 730000, China

    Guicai Ning & Shigong Wang

  3. Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Sha Tin, N.T., Hong Kong, China

    Ming Luo

  4. Sichuan Key Laboratory for Plateau Atmosphere and Environment, School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, 610225, China

    Shigong Wang

  5. Center for Climate Physics, Institute for Basic Science, Busan, South Korea

    Zhen Liu

  6. Pusan National University, Busan, South Korea

    Zhen Liu

  7. School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing, China

    Yuanjian Yang

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  1. Guicai Ning
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Ning, G., Luo, M., Wang, S. et al. Dominant modes of summer wet bulb temperature in China. Clim Dyn 59, 1473–1488 (2022). https://doi.org/10.1007/s00382-021-06051-w

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