Intensification of heatwaves in China in recent decades: Roles of climate modes

Heatwaves pose significant threats to ecosystems and human society, causing detrimental impacts on health, agriculture, and natural hazards. With the ongoing increase in global temperatures due to climate change, the frequency and intensity of heatwaves are escalating worldwide, raising significant public concern. While large-scale climate variability modes, such as ENSO, AMO, and IOD, are known to influence global weather patterns and intensify heatwaves in various regions, their specific impact on heatwaves in China remains unclear. China has experienced a pronounced warming trend in the past century, coupled with rapid population growth and urbanization, leading to more frequent and intense summer heat events. These changes negatively affect soil moisture, crops, vegetation, and water resources, threatening food security and water sustainability. Existing studies primarily focus on increasing trends related to anthropogenic factors (greenhouse gas warming, urban heat islands) and isolated drivers at regional scales. This study aims to systematically assess the changing behavior of summertime heatwave intensity across distinct geographic regions in China, utilizing reliable meteorological observations and advanced statistical and model techniques to understand the role of climate modes and their underlying mechanisms. The goal is to provide improved decadal predictions and near-term projections of heatwaves in various regions of China.

The literature extensively documents the significant impacts of heatwaves on various aspects of human society and the environment. Studies highlight the detrimental effects on human health (Guo et al., 2018), primary productivity (Ciais et al., 2005), and natural hazards (Easterling et al., 2000). The global increase in temperature due to climate change has been well-established (Hansen et al., 2010; Coumou & Rahmstorf, 2012; Oliver et al., 2018; Moron et al., 2016; Smale et al., 2019; Mukherjee & Mishra, 2021; Zheng et al., 2021). The role of climate modes in modulating these extremes is also recognized, with ENSO, AMO, and IOD shown to influence the duration, frequency, and intensity of heatwaves (Niedzielski, 2014; Seager & Hoerling, 2014; Murari et al., 2016; Zhou & Wu, 2016; Zhou et al., 2019; Luo & Lau, 2019a). However, the interplay between anthropogenic warming and internal climate modes in the context of Chinese heatwaves remains understudied. Previous research on heatwaves in China has largely focused on increasing trends associated with anthropogenic influences and localized drivers, with limited understanding of the physical processes leading to heatwave intensification (Sun et al., 2014; Kang & Eltahir, 2018; Li et al., 2018; Li et al., 2020). A prior study revealed an abrupt intensification of nationwide heatwave magnitude around 1996–1997, linking it to increased global temperature (Wei et al., 2020). This current study expands upon this previous work by providing a systematic assessment across different regions in China and investigating the underlying mechanisms through the use of a Bayesian dynamic linear model and atmospheric general circulation model.

This study uses daily maximum and minimum temperatures from 718 meteorological stations across China (1961–2017) obtained from the China Meteorological Administration. Data underwent quality control. Three dominant climate modes influencing Asian climate were examined: ENSO (represented by the Niño3.4 index), AMO (AMO index), and IOD (DMI). The Interdecadal Pacific Oscillation (IPO) index was also analyzed, exhibiting high correlation with ENSO decadal variability. Data included monthly JJA (June, July, August) means, with 1961–2017 climatology removed. Daily data from ERA5 and NCEP/NCAR reanalysis products were used for comparison and mechanism analysis. ERA5 data were used for further analysis. Seven distinct heatwave variability regions were identified using the Fuzzy C-Means algorithm. The Excess Heat Factor (EHF) was used to quantify heatwave intensity, incorporating both excessive heat and heat stress. The Pettitt and moving t-tests were applied to detect abrupt changes in heatwave intensity. The Bayesian Dynamic Linear Model (DLM) was used to assess the non-stationary impacts of ENSO, AMO, and IOD on heatwave intensity, addressing limitations of conventional linear regression models. Partial Bayesian DLM was used to investigate the independence of ENSO and IOD impacts. Atmospheric General Circulation Model (AGCM) experiments (using ECHAM4.6) were conducted to investigate the effects of IPO and AMO on heatwave intensification. Four AGCM experiments were performed: Exp-IPO, Exp-AMO, Exp-(IPO+AMO), and Exp-(IPO+AMO+ENSO). Spatial patterns of SSTAs associated with each climate mode were obtained through regression. A sinusoidal wave with a 40-year period was used to represent the observed inter-decadal changes in IPO and AMO. A 2-year period sinusoidal wave represented ENSO interannual variability. The control experiment (CTRL) was forced by climatological SST. The impacts of IPO, AMO, and their combination were quantified by comparing the sensitivity experiments to CTRL.

The study detected robust intensification of heatwave magnitudes across China over the past two decades, with an abrupt increase around the mid-1990s in northern and western China. This intensification persisted even after removing the linear trend attributed to anthropogenic warming. The combined effects of ENSO, AMO, and IOD explained a significant portion (62.35–70.01%) of the observed heatwave intensification in several regions. While the amplitudes of ENSO, AMO, and IOD indices remained relatively constant, their impacts on heatwave intensity significantly increased during the post-abrupt period, implying a change in their influence. Analysis revealed that ENSO had the largest effect, with a negative relationship suggesting that La Niña (negative IPO) enhanced heatwave intensity. AMO's impact was more complex, changing from negative to positive after ~2008. IOD's impact also increased during the post-abrupt period, but with a change in sign in the West II region. Composite analysis confirmed La Niña and negative IPO phases enhanced heatwaves, particularly in northern China. Positive AMO and IOD phases generally intensified heatwaves. Analysis of reanalysis data showed an enhanced high-pressure system over Eurasia during the post-abrupt period, leading to increased surface air temperature through adiabatic heating, reduced cloud cover, and decreased latent heat loss. AGCM experiments showed that the concurrent phase transitions of IPO (positive to negative) and AMO (negative to positive) around the mid-1990s caused heatwave intensification by modulating atmospheric internal variability and ENSO's interannual impacts. Nonlinear interactions between IPO and AMO effects also played a significant role.

The findings address the research question by demonstrating that the observed abrupt intensification of heatwaves in China during the past two decades is significantly influenced by changes in the impacts of major climate modes, particularly driven by concurrent interdecadal phase transitions of the IPO and AMO. The results highlight the importance of considering both anthropogenic warming and the non-stationary impacts of climate modes when assessing and predicting heatwave occurrences. The increased influence of ENSO, AMO, and IOD during the post-abrupt period, despite their relatively stable amplitudes, indicates a shift in the atmospheric conditions conducive to heatwave development. The identification of the enhanced Eurasian high-pressure system and its associated mechanisms provides valuable insight into the physical processes driving the observed heatwave intensification. The agreement between the AGCM experiments and observational analysis strengthens the conclusion that the concurrent phase transitions of the IPO and AMO are a primary driver of the observed abrupt change in heatwave intensity. These findings are highly relevant to the field of climate change and extreme weather events, improving our understanding of the complex interplay between climate modes and anthropogenic warming in shaping heatwave behavior.

This study demonstrates a robust intensification of heatwaves in China, particularly in northern and western regions, driven by enhanced impacts of climate modes (ENSO, AMO, IOD) and linked to the concurrent phase transitions of the IPO and AMO. The findings underscore the importance of considering the non-stationary effects of climate modes in heatwave predictions. Future research should focus on a deeper understanding of atmospheric internal variability and its interaction with climate modes to improve decadal predictions and near-term projections of heatwaves.

The study's use of idealized SSTAs in AGCM experiments simplifies the complex interaction between climate modes and atmospheric circulation. The reliance on a specific AGCM may also introduce some model-related uncertainties. The sparse meteorological stations in certain regions (e.g., West II) could potentially affect the accuracy of heatwave intensity estimations. Further investigation is needed to fully understand the sources of atmospheric internal variability and their interactions with climate modes.