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.