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Spatiotemporal variation of heat and cold waves and their potential relation with the large-scale atmospheric circulation across Inner Mongolia, China

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Abstract

Global warming has exerted increasingly serious impacts on the society, economy, and environment across Inner Mongolia, China. In this context, Sen’s slope method and Morlet wavelet transformation were employed to analyze the spatiotemporal variation characteristics of heat waves (HWs) and cold waves (CWs) based on excess factors (EFs) during 1961–2016. The Pearson correlation coefficient was applied to explore four climate indices’ potential relation with the EFs. The results show that the intensity and frequency of excess heat factors (EHFs) were increasing, and the increasing rate in high-latitude regions was higher than that in low-latitude regions. Excess cold factors (ECFs) showed a decreasing trend in almost all meteorological stations; severity of ECFs was increasing in the northeastern region. The EFs had a periodic variation of 1–4 years and crossover on the interdecadal scale. Climatic indices had a greater relation with ECFs than EHFs, but the previous year remained stable with a greater link with EHFs in the same year for climatic indices. The Arctic Oscillation index (AOI) and the North Atlantic Oscillation (NAO) were negatively correlated with the duration and frequency of ECFs for most meteorological stations, but there was a significant positive correlation with their severity. Multivariate El Niño/Southern Oscillation (ENSO) index (MEI) and Pacific Decadal Oscillation (PDO) had higher link with ECFs in the midwest than that in other regions. MEI and AOI had a notable relation with the severity and frequency of EHFs compared with the other two climatic indices. In the warm and cold periods, the atmospheric circulation showed different airflow convergence and divergence around Inner Mongolia, which may affect the spatiotemporal characteristics of CWs and HWs.

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Abbreviations

HWs:

Heat waves

CWs:

Cold waves

EFs:

Excess factors

EHFs:

The excess heat factors

ECFs:

The excess cold factors

NCEP:

The National Center for Environmental Prediction

ECAR:

National Center for Atmospheric Research

CWN:

The number of individual cold wave that occur each year

CWF:

The number of days that contribute to CWs

CWD:

The length of the longest cold wave identified by CW

CWM:

The mean temperature of all CWs

CWA:

The minimum daily value in the coldest CWs

HWN:

The number of individual heatwaves that occur each summer. A heatwave is defined as 3 or more days where the EHF is positive

HWF:

The number of days that contribute to HWs

HWD:

The length of the longest HW

HWM:

The mean temperature of all HWs

HWA:

The peak daily value in the hottest HW (defined as the heatwave with highest HWM)

ENSO:

El Niño/Southern Oscillation

PDO:

Pacific Decadal Oscillation

MEI:

Multivariate ENSO index

NAO:

North Atlantic Oscillation

AOI:

Arctic Oscillation index

CCl:

Commission for Climatology

WMO:

World Meteorological Organization

Tm :

Mean temperature

Tx :

Maximum temperature

Tn :

Minimum temperature

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Acknowledgments

The authors are grateful to the anonymous reviewers for their insightful and helpful comments to improve the manuscript.

Funding

This work was supported by the National Science Foundation for Young Scientists of China (No. 41807507), the Drought Meteorology Science Research Program (IAM201904), the high-level introduction of talent research start-up fund in Inner Mongolia Normal University (2018YJRC008), the Key Program of National Natural Science Foundation of China (No.61631011), the National Key Research and Development Program of China (No.2017YFE0109100), and the Science and technology planning project in Inner Mongolia (No.201702116).

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Authors and Affiliations

  1. College of Geographical Science, Inner Mongolia Normal University, Hohhot, 010022, People’s Republic of China

    Enliang Guo, Yongfang Wang, Yuhai Bao, Yulong Bao & Lai Quan

  2. Inner Mongolia Key Laboratory of Disaster and Ecological Security on the Mongolian Plateau, Hohhot, 010022, People’s Republic of China

    Enliang Guo, Yongfang Wang & Yulong Bao

  3. Lanzhou Institute of Arid Meteorology, China Meteorological Administration, Lanzhou, 730020, People’s Republic of China

    Enliang Guo

  4. Inner Mongolia Key Laboratory of Remote Sensing and Geographic Information Systems, Inner Mongolia Normal University, Hohhot, 010022, People’s Republic of China

    Yuhai Bao & Lai Quan

  5. College of Ecology and Environment, Hainan University, Haikou, 570228, People’s Republic of China

    Zhongyi Sun

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  1. Enliang Guo
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Correspondence to Yuhai Bao.

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Guo, E., Wang, Y., Bao, Y. et al. Spatiotemporal variation of heat and cold waves and their potential relation with the large-scale atmospheric circulation across Inner Mongolia, China. Theor Appl Climatol 142, 643–659 (2020). https://doi.org/10.1007/s00704-020-03331-z

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