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Daytime and nighttime heat wave characteristics based on multiple indices over the China–Pakistan economic corridor

  • Safi Ullah
  • Qinglong YouEmail author
  • Waheed Ullah
  • Daniel Fiifi Tawia Hagan
  • Amjad Ali
  • Gohar Ali
  • Yuqing Zhang
  • Mushtaq Ahmad Jan
  • Asher Samuel Bhatti
  • Wenxin Xie
Article

Abstract

The sharp rise in temperature has increased the frequency, intensity, duration, and timing of heat waves (HWs) over different regions of the world. Due to climate change, the China–Pakistan Economic Corridor (CPEC) is one of the highly vulnerable regions to HWs and needs comprehensive research studies to investigate the HW phenomenon in the region. This study analyzed the spatial and temporal changes in the daytime and nighttime HW characteristics based on multiple indices over the CPEC region. We used daily maximum and minimum temperatures (hereafter Tmax and Tmin) of 48 meteorological stations for the time period of 1980–2016. The non-parametric modified Mann–Kendall, Theil–Sen’s test, least square method, student t-test, and chi-square goodness-of-fit test techniques were used to analyze the long-term spatiotemporal changes in the daytime and nighttime HW characteristics. The results of the study show that the number of annual daytime/nighttime HW events, annual sum of participating daytime/nighttime HW days, the average length of annual daytime/nighttime HW events, duration of the longest annual daytime/nighttime HW event, the average magnitude of all annual daytime/nighttime HW events, amplitude of the hottest annual daytime/nighttime HW event, and the ending date of annual last daytime/nighttime HW event exhibited significant increasing trends at the rate of 0.78/1.43 events decade−1, 10/11.82, 2/1.74, 2.16/1.52 days decade−1, 0.40/0.59, 0.24/0.73 °C decade−1, and 12.29/10 days decade−1, respectively. Despite all, the onset date of the annual first daytime/nighttime HW event has shown a significant decreasing trend of − 5.71/− 5 days decade−1. The obvious positive trend of HW behaviors indicates that the country has experienced more frequent, stronger, more intense, and longer HWs during the study period. The spatial pattern of the trend indicates that the southern, central and eastern parts of Pakistan exhibited prominent and consistent HW activities, while the northwestern mountainous regions showed high spatial variability with some stations exhibited decreasing trends in HW indices. The findings of this study will be a base for the projection and mitigation of HWs in the region. Based on the study findings, we recommend that the mechanism of HW and its natural and anthropogenic drivers should be thoroughly investigated over the study region.

Keywords

Heat waves Multiple indices CPEC Theil–Sen’s (TS) test Modified Mann–Kendall (m-MK) test 

Notes

Acknowledgements

This study was supported by National Key R&D Program of China (2017YFA0603804) and National Natural Science Foundation of China (41771069). This study was also funded by “The Priority Academic Program Development of Jiangsu Higher Education Institutions” (PAPD). The authors would also like to acknowledge Pakistan Meteorological Department (PMD) for providing temperature data. We are very grateful to the anonymous reviewers for their constructive comments and thoughtful suggestions.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Safi Ullah
    • 1
  • Qinglong You
    • 1
    • 2
    Email author
  • Waheed Ullah
    • 3
  • Daniel Fiifi Tawia Hagan
    • 3
  • Amjad Ali
    • 4
  • Gohar Ali
    • 5
    • 6
  • Yuqing Zhang
    • 7
  • Mushtaq Ahmad Jan
    • 4
  • Asher Samuel Bhatti
    • 3
  • Wenxin Xie
    • 1
  1. 1.Key Laboratory of Meteorological Disaster, Ministry of EducationNanjing University of Information Science and Technology (NUIST)NanjingChina
  2. 2.Department of Atmospheric and Oceanic Sciences & Institute of Atmospheric SciencesFudan UniversityShanghaiChina
  3. 3.School of Geographical SciencesNUISTNanjingChina
  4. 4.Centre for Disaster Preparedness and ManagementUniversity of PeshawarPeshawarPakistan
  5. 5.School of Atmospheric PhysicsNUISTNanjingChina
  6. 6.Pakistan Meteorological DepartmentIslamabadPakistan
  7. 7.School of Urban and Environmental ScienceHuaiyin Normal UniversityHuai’anChina

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