1. Introduction
Greenhouse gases (GHGs) have been warming the atmosphere, land, and ocean since Industrial Revolution, and each decade in the last 40 years has been warmer than any previous decades since 1850 (IPCC 2021). According to the Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC), the global land surface temperature in 2011–2020 was 1.6 °C higher than that in 1850–1900. The characteristics of extreme weather and climate events are projected to change in response to the warming climate. Extreme hot temperature events are expected to occur more frequently and intensely with global warming. Compared with that in 1850–1900, global terrestrial 10-year extreme heat events are expected to occur 3.1 times more frequently, with an intensity that is 1.9 °C higher, if the global warming level reaches 1.5 °C (IPCC 2021).
The present study is focused on heatwaves, as a type of extremely high-temperature event. Heatwaves typically refer to a prolonged period of excessively hot days, although no universal definition is available. Heatwaves are usually defined in terms of absolute or relative criteria. According to an absolute criterion, a heatwave is defined as a prolonged period with daily maximum temperatures exceeding a fixed value (e.g., 35 °C) (Wang et al. 2017). According to a relative criterion, a heatwave is a prolonged period with daily maximum temperatures exceeding a certain percentile (e.g., the 90th percentile) for a long-term temperature histogram (Ding et al. 2010). The present study adopts the Hong Kong Observatory’s threshold for defining a heatwave event (daily maximum temperature exceeding 33 °C for at least three days) using an absolute criterion. This definition is based on the humid and hot subtropical climate in the Pearl River Delta (PRD), which is the target area of this research. Moreover, Chan et al. (2011) highlighted that help-seeking behaviors are expected to intensify when the temperature rises to 30–32 °C. For a regional heatwave analysis, the frequency, intensity, and duration of a heatwave event can be represented by metrics such as the hot day frequency (Yang et al. 2017), heatwave frequency (Perkins and Alexander 2013), heatwave duration (Perkins et al. 2012), heatwave temperature (Perkins 2015), very hot day hours (Shi et al. 2019), and nighttime heatwaves (Thomas et al. 2020).
Heatwaves can adversely influence human health, ecological environment, social infrastructure, and the overall economy. Specifically, intense heatwaves can increase human morbidity and mortality. Heat-related illnesses include heat cramps, exhaustion, and stroke. Females, the elderly, and people engaged in physical work in outdoor environments are more vulnerable to extreme heat (Ebi et al. 2021). In the summer of 2003, Europe experienced the hottest heatwave recorded since 1540, which led to the death of 70,000 people (Robine et al. 2008). Many countries in the northern hemisphere suffered severe heatwaves in 2010, including China, European continent, North Africa, the United States, and Russia. In Russia, over 55,000 people died during the heatwave (Horton et al. 2016). In 2022, record-breaking heatwaves swept through Europe, South America, India, and China, killing more than 12,000 people. Heatwaves can also exacerbate wildfires and drought. In the hot and dry meteorological conditions induced by extreme heat, the vegetation becomes devoid of moisture and can fuel wildfires that can spread extensively and burn for considerable periods. The emergence of more frequent and intense heatwaves burdens the social infrastructure, such as healthcare, power supply, and agriculture. For example, railway tracks may buckle, and roofs may melt at high temperatures. Additionally, heatwaves can deteriorate the labor productivity and overall economy, especially in low- and low-middle-income countries (Chavaillaz et al. 2019). For every trillion tons of carbon emissions, the global annual productivity loss is expected to increase by 3% and 3.6% of the total GDP in representative concentration pathway (RCP) scenarios RCP4.5 and RCP8.5, respectively (Chavaillaz et al. 2019).
Spatial heterogeneity exists in the occurrence of heatwaves. For example, studies have found that heatwaves are more frequent and intense in urban areas compared to rural areas due to urbanization, with urban areas contributing over 45% to heatwaves in southwestern, northern, and southern China (Wu et al. 2020). The frequency and intensity of heatwaves also vary greatly between regions and climatic zones, depending on factors such as latitude and altitude. For instance, during heatwaves, the Yangtze River and the Beijing-Tianjin-Hebei region experience ’very hot’ thermal comfort levels, which have been attributed to the movement of the sub-high-pressure belt to the Yangtze River area in summer. On the other hand, the southwest of Tibet, which is at higher altitudes, has the lowest thermal index despite their proximity to lower latitudes (Wu et al. 2022). Considerable research has been performed to project future heatwave trends on both the global and regional scales using climate models. By the end of this century, in business-as-usual scenarios, heatwaves as severe as the Russian heatwave in 2010 will become the norm and are projected to occur every two years in regions such as southern Europe, North America, and Indonesia (Russo et al. 2014). Projections for China show that regions such as Yangtze River and Southern China, which suffered from heatwaves in previous climate conditions, will experience more frequent and severe heatwaves under global warming (Guo et al. 2017; Wang et al. 2017).
To better respond and adapt to changes in future extreme climate events, IPCC AR6 established five new illustrative future climate scenarios, i.e., shared socioeconomic pathways (SSPs): SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. The numbers represent the combination of SSPs and RCPs, representing radiative forcing values of 1.9 W·m−2, 2.6 W·m−2, 4.5 W·m−2, 3.7 W·m−2 and 8.5 W·m−2 to be achieved under different socioeconomic assumptions, climate mitigation levels, precursors of aerosols and non-methane ozone, and air pollution controls in the year 2100, respectively (IPCC 2021). These RCPs used in IPCC AR5 were replaced with these new future scenarios to provide a more comprehensive overview of different climate outcomes. In the present study, SSP1-2.6, SSP2-4.5, and SSP5-8.5, representing low, intermediate, and very high GHG emissions, respectively, were selected to explore future climate outcomes in the mid-term (2040–2049) and long term (2090–2099). In all emission scenarios, the global surface temperature is expected to keep increasing until at least mid-century, and global warming levels of 1.5 °C and 2 °C are expected to be exceeded by the end of this century unless the GHG levels significantly decrease. Compared with 1850–1900, the global mean surface temperature in 2081–2100 will potentially increase by 1.3–2.4 °C, 2.1–3.5 °C, and 3.3–5.7 °C in SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively.
Studies utilizing climate output data from the recently released phase 6 of the Coupled Model Intercomparison Project (CMIP6) are still limited, as CMIP5 data is currently more widely used. However, there is a need to update research using CMIP6 to improve our understanding of future climate scenarios. Compared with CMIP5, CMIP6 provides finer-resolution climate model data and a more comprehensive set of future pathways. In terms of extreme climate events, CMIP6 can capture spatiotemporal trend patterns (with the observations as reference) more accurately than CMIP5 (Fan et al. 2020; Chen et al. 2020). Therefore, there is a growing need to update future climate projections using CMIP6 output data. Typically, the resolution of global climate models (GCMs) ranges between 100 km and 600 km, which is too coarse for regional climate analyses. Several physical processes, such as those related to cloud microphysics, deep convections, as well as topographic drags, cannot be appropriately resolved using GCMs. Therefore, by using the dynamical downscaling method to explore regional heatwaves, we downscaled the resolution of GCM to 1 km on the PRD, which is one of the most densely urbanized and populated regions worldwide. Such urban regions are expected to suffer more from extreme heat events in the future compared with other regions (IPCC 2021).
This paper comprehensively describes the daytime and nighttime heatwave trends in the PRD region by the middle and end of the century under different emission pathways. The remaining paper is structured as follows: Section 2 describes the methods used and the heatwave metrics considered. Section 3 presents the results, and Section 4 presents the concluding remarks.