1. Introduction
According to the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5), the global temperature has increased by approximately 0.78°C (0.72°–0.85°C) in 2003–12 relative to that in 1850–1900 (IPCC 2013). Recent increases in the global mean temperature can be linked to an increase in the occurrence of extreme weather events (e.g., heat waves, heavy rainfall) around the world (Pall et al. 2011; King et al. 2015; Perkins and Gibson 2015; Black and Karoly 2016; Hope et al. 2016; Uhe et al. 2016; Xia et al. 2016; van der Wiel et al. 2017; Ding et al. 2019; Im et al. 2019; Xu et al. 2019).
Heat waves can lead to a significant impact on the social and economic losses. According to the World Meteorological Organization (WMO 2013), the number of deaths due to heat waves in 2001–10 increased by 2300% relative to the number of deaths in 1991–2000. The increase in the number of deaths due to heat waves was much larger than the overall increase of 20% due to various extreme weather events, including droughts, storms, and floods. For example, a heat wave over Europe in 2010 caused more than 55 000 deaths and led to a total economic loss of $15 billion (U.S. dollars; Peters et al. 2010). In the summer of 2015, there were at least 2500 deaths in India due to severe heat (Ratnam et al. 2016; Ghatak et al. 2017).
In future climate change scenarios, extreme weather events are predicted to be more frequent, intense, and persistent across the globe with significant impacts on human health, infrastructure, industry, and ecosystems (Meehl and Tebaldi 2004; Trewin and Vermont 2010; Schiermeier 2011; Oliver et al. 2018). The World Health Organization (WHO) reported that there will be approximately 92 000 deaths per year from heat waves by 2030 in various parts o\f the world, especially in sub-Saharan Africa, Latin America, and South and Southeast Asia (WHO 2014).
Extreme temperature events have become an important public concern, and recent studies have focused on analyzing the mechanism and atmospheric circulation patterns of extreme temperature events (Lee and Lee 2016; Lu and Chen 2016; Wang et al. 2017; Yeh et al. 2018; Su and Dong 2019). An extreme temperature event is caused by a high pressure system that brings clear skies and enhances the effect of solar radiation. Luo et al. (2020) reported that extreme temperature over China is associated with the Pacific meridional mode on interannual time scales. Lee and Lee (2016) found that circulation anomalies affecting the interannual and decadal variability of heat waves in South Korea are similar. Lee et al. (2020) indicated that the heat wave index that uses large-scale circulation patterns associated with heat waves, defined as the vorticity difference at 200 hPa between the South China Sea and Northeast Asia, can predict the heat waves over South Korea based on The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) data in the medium range. Extreme temperatures over East Asia (South Korea, China, and Japan) have also been attributed to the variations in the western North Pacific subtropical high (WNPSH). Luo and Lau (2017), for example, suggested that the westward movement of the WNPSH is responsible for the occurrence of heat waves over the southern part of China. Yoon et al. (2018) used K-means cluster analysis to find that severe heat waves over South Korea in 2015 were strongly related to the WNPSH. Extreme heat waves caused the death of more than 80 people in Japan in July 2018 and were directly associated with the northward movement of the WNPSH causing a tropospheric anticyclone with a barotropic structure across northeastern Asia (Liu et al. 2019).
Previous studies have focused only on the effect of temperature even though the combined effects of temperature and humidity pose risks to human health (Sherwood and Huber 2010; Fischer et al. 2012; Willett and Sherwood 2012; Im et al. 2017). Under warm and humid conditions, the human body naturally starts to heat up and release sweat. However, it is difficult to lose heat through evaporation (sweating) when the atmospheric moisture content is high. The combination of environmental heat and internal body heat generated as a by-product of metabolism may cause physical disorders and even death (Sherwood and Huber 2010; WMO 2020).
Recently, a few studies have reported on human-perceived temperature (HPT), considering the effect of the humidity on human body. To the best of our knowledge, those studies have estimated the impacts of HPT under climate change scenarios using global climate models (Fischer and Knutti 2013; Im et al. 2017; Matthews et al. 2017; Russo et al. 2017; Coffel et al. 2018; Lee and Min 2018; W. Li et al. 2019; Sun et al. 2019). Most of these studies have shown that, as a result of the increase in both temperature and humidity, HPT will intensify throughout the twenty-first century at a higher rate than the temperature.
South Korea is one of the countries most affected by heat stress. Summers in South Korea are characterized by hot and humid conditions under the influence of the East Asian monsoon. Yoon et al. (2014) reported that South Korea had a heat-related burden of 6.85 disability-adjusted life years per 1000 people in 2008, and this number is expected to increase in the future. Lee and Min (2018) and Im et al. (2017) projected future intensification of heat stress over South Korea under global warming scenarios. A comprehensive understanding of the spatiotemporal variations in HPT and related large-scale atmospheric circulation patterns as well as future changes in HPT across South Korea is necessary to predict and mitigate the effects of HPT.
In this study, we investigated the spatiotemporal characteristics including long-term trends and changepoints of HPT over South Korea during 1981–2018 based on the observations and analyzed large-scale atmospheric circulation patterns that affect the variations in HPT.
2. Data and method
a. Datasets
The daily minimum, mean, and maximum temperature and relative humidity observations from 45 synoptic weather observation stations (Automated Synoptic Observation System), operated by the Korea Meteorological Administration (KMA), were used in this study. The stations were selected based on the availability of continuous measurements longer than 30 years based on a consistent location and measurement techniques. Basic and extended quality checks were applied to the data, such as a plausible value check and internal consistency check based on the World Meteorological Organization guide (KMA 2016). In addition, these stations have been used as national climate observation sites to determine the climate variability over South Korea (KMA 2020). The distribution of 45 observational stations is shown in Fig. 1. The analysis was carried out in the summers of 1981–2018. Summers in South Korea typically occur from June to August, but the temperature characteristics in early and late summer vary slightly (Yeo et al. 2017). In early summer, the temperature is controlled by the land–sea thermal contrast in East Asia, whereas late summer temperatures are attributed to the enhanced convective activity over the western tropical Pacific. Therefore, we analyzed the data collected from July to August in this study.
Location of the research area, showing the distribution of surface observational stations. The numbers indicate weather station numbers. Refer to Table 1 for more details.
Citation: Journal of Climate 34, 4; 10.1175/JCLI-D-20-0344.1
To investigate the associated large-scale atmospheric circulation patterns and physical processes, the daily dataset from the European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim; Dee et al. 2011) was used, covering a period of 38 years from 1981 to 2018. The dataset includes the geopotential height, specific humidity, horizontal and meridional wind, and vertical velocity data at different pressure levels at a horizontal resolution of 1.5° × 1.5°. The 2-m temperature, precipitation, and outgoing longwave radiation data at the surface level are also included in the dataset. In addition, the Optimum Interpolation Sea Surface Temperature (OISST) dataset provided by the Climate Diagnostics Center of the U.S. National Oceanographic and Atmospheric Administration (NOAA) was used (Reynolds et al. 2007).
b. HPT indicators
Relationship between temperature (°C) and relative humidity (%) for human-perceived temperature (°C).
Citation: Journal of Climate 34, 4; 10.1175/JCLI-D-20-0344.1
c. Method
We used a composite analysis to estimate the impact of the variations in large-scale atmospheric circulation patterns on the spatiotemporal variations in extreme HPT during the study period and employed Student’s t test to determine the statistical significance levels. The extreme HPT days were defined as extreme caution, danger, and extreme danger categories in Table 1 (i.e., with the value of HPT exceeding 32°C).
Composite analysis, which defines the average field on preidentified dates, provides the physical mechanism and meteorological patterns in observations and climate models at various scales (Grotjahn and Faure 2008; Dole et al. 2011; Lee et al. 2016; Lee and Lee 2016). Freychet et al. (2017) constructed a time-lagged composite analysis to analyze the characteristics of the circulation associated with heat waves in China. Loikith and Broccoli (2015) used composite analysis to evaluate the large-scale atmospheric circulation associated with temperature extremes in a suite of global climate models contributing to the CMIP5 and found that the ensemble reproduced large-scale atmospheric circulation patterns on extreme temperature days over North America. Tomczyk and Owczarek (2020) showed that high pressure systems block zonal circulations on days with strong and very strong heat stress levels in Poland.
3. Results and discussion
a. Variability of temperature and relative humidity
Figure 3 and Table 2 indicate the average values of maximum temperature, HPT, and relative humidity over South Korea from 1981 to 2010. The maximum temperature ranged from 26.50° to 30.65°C, and HPT ranged from 28.33° to 34.55°C. The difference between the HPT and the maximum temperature caused by the combined effect of relative humidity and maximum temperature on the HPT ranged from 1.83° to 4.64°C. From the relationship between temperature, relative humidity, and HPT shown in Fig. 2, at high temperatures even a slight increase in temperature can lead to a considerable increase in HPT. The spatial distribution between the maximum temperature and HPT was similar (Fig. 3), depicting the influence of the complex mountainous topography of South Korea. For example, the maximum temperature and HPT are relatively low in the high-altitude area and eastern South Korea [e.g., Sokcho (station No. 90), Gangneung (105), and Uljuin (130)]. On the contrary, inland regions of the southern parts of the country [e.g., Daegu (143), Uiseung (278), Miryang (288), and Yeongcheon (281)] show the climatologically highest values of maximum temperature and HPT and lowest levels of humidity because of the southerly winds that bring warm and dry air in the summer due to topographic effects (Table 2).
Average of (a) maximum temperature (°C), (b) HPT (°C), and (c) minimum relative humidity (%) over South Korea from 1981 to 2010.
Citation: Journal of Climate 34, 4; 10.1175/JCLI-D-20-0344.1
Average and standard deviation for maximum (Tmax), HPT, and minimum relative humidity in South Korea from 1981 to 2010.
The average long-term minimum, mean, and maximum temperature, HPT, and relative humidity for 45 stations from 1981 to 2018 are shown in Fig. 4. The minimum, mean, and maximum temperatures and HPT increased by 0.36°, 0.30°, 0.27°, and by 0.29°C decade−1 for minimum, mean, and maximum temperatures and for HPT, respectively, during 1981–2018. The change in relative humidity was −1.10% decade−1. Overall, the results showed a clear interdecadal variation and an increasing trend in temperature and HPT. The relative humidity showed a decreasing trend. Note that the increasing trend of HPT, which measures the combined effect of temperature and relative humidity on the human body, was more pronounced than the trends in the maximum, mean, and minimum temperature during 1981–2018. These results are consistent with the findings of several recent studies (Russo et al. 2017; Li et al. 2018; Luo and Lau 2019).
Long-term variability of (a) the minimum, mean, and maximum temperature; HPT in South Korea; and the averaged maximum temperature and HPT over the land region within a latitudinal band (30°–40°N) similar to South Korea, and (b) minimum relative humidity (%) averaged for 45 stations in South Korea. The solid and dashed lines indicate the linear trends for different periods. One, two, and three asterisks denote statistically significant results at the 70%, 85%, and 90% confidence levels, respectively.
Citation: Journal of Climate 34, 4; 10.1175/JCLI-D-20-0344.1
In this study, the changepoint analysis was applied to the HPT time series to determine whether there is a climate regime shift. The analysis periods were divided into two periods around 2010 at 95% confidence level: 1981–2009 and 2010–18, with the largest absolute value of t (Fig. 5). The HPT has increased significantly in recent years when compared with the last three decades. The average HPT was 32.56°, 32.17°, 31.53°, and 33.66°C in 1981–90, 1991–2000, 2001–09, and 2010–18, respectively. The increasing trend in HPT was approximately 1.95°C decade−1 at a 70% confidence level during the period 2010–18 (Fig. 4). Furthermore, we performed a similar trend analysis to compare the effect of global warming on the averaged maximum temperature and HPT over the land region within a latitudinal band from 30° to 40°N similar to South Korea (Fig. 4) and the Northern Hemisphere (not shown). Because the daily data were available to calculate HPT over land region, we created the time series by replacing the trend of maximum temperature in South Korea with global maximum temperature based on monthly Hadley Centre Climatic Research Unit Temperature (HadCRUT) data. The HPT in land region increased at rate of 0.37° and 0.28°C decade−1 in 1981–2018 and 1981–2009, whereas it decreased −0.59°C decade−1 in 2010–18. In 1981–2018, the trend of HPT in South Korea is approximately 5 times that of land region. The increasing HPT trend in South Korea may also be a part of global warming, but the HPT variability in South Korea in recent times could not be fully explained by global warming. Moreover the maximum temperature in South Korea increased by 1.59°C decade−1 in 2010–18 relative to that in the land region (0.45°C decade−1). Zeng et al. (2019) reported that wind speed has been increasing rapidly across the globe since 2010 due to ocean–atmosphere oscillations. This led us to believe that the changes in large-scale atmospheric circulation patterns around 2010 likely have an impact on HPT in South Korea.
Decadal average of HPT averaged for 45 stations in South Korea and the t value of statistical changepoint analysis. The bars denote the HPT. Error bars indicate the minimum, median, and maximum t value for the decades. The minimum t value during the period 1981–2018 is in 2010.
Citation: Journal of Climate 34, 4; 10.1175/JCLI-D-20-0344.1
Figure 6 shows the spatial distribution of the HPT trends in 1981–2018, 1981–2009, and 2010–18. The black dot denotes the 70% confidence level. In Fig. 6a, HPT during 1981–2018 increased at most stations except for a few stations in western South Korea, but the increasing trend was statistically significant at the 70% confidence level at 50% of the stations. During 1981–2009, HPT at nearly all stations showed a decreasing trend, while it increased considerably in most parts of South Korea during 2010–18.
Spatial distribution of the trends of HPT during 1981–2018, (b) 1981–2009, and (c) 2010–2018. The black dots denote statistically significant results at a 70% confidence level. The orientation of the triangles gives the direction of the trend, and the color of the triangle gives the magnitude of the trend.
Citation: Journal of Climate 34, 4; 10.1175/JCLI-D-20-0344.1
Figure 7 indicates the interannual variations in the frequency of HPT based on four categories. During 1981–2010, 53 days of HPT occurred at the levels of caution, extreme caution, and danger. However, between the periods of 1981–2009 (53 days) and 2010–18 (57 days), the frequency of HPT at four levels has increased by approximately 4 days. In 2013, 61 days of HPT with human health risks occurred. This indicates that South Korea frequently suffers from heat stress in summer. The frequency of caution and extreme caution days decreased, but the frequency of danger days increased. In particular, the frequency of danger days exhibited a significant increase in recent years, similar to the trend of HPT. This result suggests that the increasing trends in the combined effect of high temperature and humidity have posed substantial health risks to human health in South Korea in recent years.
Interannual frequency variability of HPT on the basis of four categories: caution, extreme caution, danger, and extreme danger. The solid and dashed lines indicate the linear trends for different periods.
Citation: Journal of Climate 34, 4; 10.1175/JCLI-D-20-0344.1
b. Changes in large-scale circulation associated with increasing HPT between 1981–2009 and 2010–18
The variability in HPT is linked to large-scale atmospheric circulation patterns. To analyze the cause of the rapid increase in HPT in South Korea since the late 2000s, we performed a composite analysis. Figure 8a shows the composite difference in the 500-hPa geopotential height anomaly between 1981–2009 and 2010–18. The stippling in the figure indicates statistically significant results at the 95% confidence level with the Student’s t test. The contour lines denote the location of the WNPSH, which is at the 5880-gpm isopleth (He et al. 2015; Yoon et al. 2018), during 1981–2009 (solid line) and 2010–18 (dashed line), respectively. Figure 8a shows the positive anomalies of the 500-hPa geopotential height over the western North Pacific (WNP) and South Korea. The geopotential height at 200 hPa in Fig. 8b was similar to that at 500 hPa. This result indicates that the WNPSH has enhanced and expanded westward since the late 2000s, increasing the temperatures in the region that extends from northern China to Japan (Luo and Lau 2017; Yoon et al. 2018; Liu et al. 2019).
Differences in large-scale atmospheric circulation patterns for (a) geopotential height at 500 hPa (shading, with 2-gpm interval), (b) geopotential height at 200 hPa (shading, with 6-gpm interval), (c) zonal wind at 200 hPa (shading, with 0.4 m s−1 interval), (d) outgoing longwave radiation (shading, with 1 W m−2 interval), (e) meridional vertical circulation (vectors; 10−3m s−1) and vertical velocity (shading; 10−3 m s−1) averaged over 125°–130°E, and (f) sea surface temperature (shading, with 0.2°C interval) between 2010–18 and 1981–2009. Stippling indicates statistical significance exceeding the 95% confidence level with Student’s t test. The contour lines in (a) denote the location of the WNPSH during 1981–2009 (solid line) and 2010–18 (dashed line). In (e), positive values indicate upward motion and negative values represent downward motion.
Citation: Journal of Climate 34, 4; 10.1175/JCLI-D-20-0344.1
The upper-level tropospheric jet is one of the major factors affecting the summer climate system (Chen et al. 2016; Wang and Zuo 2016). As shown in Fig. 8c (the difference in the 200-hPa zonal wind), the upper-level tropospheric jet shifted northward from the climatological position (40°N). Note that the zonal wind was negative between 20° and 30°N, suggesting a weakened upper-level tropospheric jet stream in association with the changes in large-scale atmospheric circulation patterns since the late 2000s. In general, the upper-level tropospheric jet stream leads to the convergence of air, which can increase the upward motion and subsequently induce more precipitation, and vice versa (Wei et al. 2019; Choi et al. 2019). Thus, the decreased precipitation from the middle of China to southern Japan and South Korea in Fig. 8d can be explained by a weakened upper-level tropospheric jet stream. According to Tao and Wei (2006) and Enomoto et al. (2003), the movement of the WNPSH is also related to the Eurasian Rossby wave train along the upper-level tropospheric jet stream, which is associated with energy propagation. Therefore, an anomalous anticyclone appears in the upper-level troposphere by the positive geopotential height of 500 and 200 hPa over South Korea. It lead to the negative anomalies of meridional winds at 200 hPa (Figs. 8a,c).
Figure 8e shows the meridional vertical circulation averaged over 125°–130°E, where South Korea is located, during 1981–2009 and 2010–18. The strengthened convective activities over 20°–30°N and at 30°–38°N were the opposite of each other. This pattern supports the strengthened WNPSH and northward upper-level tropospheric jet. From 1981 to 2009, an anomalous downward motion developed around South Korea at all vertical levels of the troposphere. Strong vertical convection is necessary to transport the moisture; therefore, it may have induced anomalous divergence of air over South Korea and anomalous convergence over the lower latitudes in the upper level, accompanied by the strengthened WNPSH and northward upper-level tropospheric jet. These results are consistent with those of several previous studies, which suggested that the enhancement of WNPSH and convective activities are important factors leading to heat waves in South Korea (Lee et al. 2020; Xu et al. 2019). Thus, as displayed in Fig. 8d, an enhanced outgoing longwave radiation anomaly appeared around South Korea, while a decreased outgoing longwave radiation anomaly with convective activity appeared in the South China Sea in recent decades. This result reveals that the changes in the outgoing longwave radiation field over South Korea were caused by the descending motion in the airflows that are related to the northward upper-level tropospheric jet.
We further explored the differences in the SST during both periods because SST can directly and robustly affect the atmospheric circulation through air–sea interactions (Deser et al. 2004; Zhou and Wu 2015; Wei et al. 2019). The positive SST anomalies in Fig. 8f occur in most parts of the North Pacific and the Maritime Continent with at least 95% confidence. This result suggests that the variability of SST corresponds well with the changes in the middle- and upper-level geopotential heights during 1981–2009 and 2010–18 (Figs. 8a,b). The SST variability also plays an important role in strengthening and maintaining the WNPSH, and the WNPSH variability is related to the SST in the Pacific (Xiang et al. 2013; Choi and Kim 2019). The positive SST over the Maritime Continent and the tropics can modulate the WNPSH variability by its association with the anomalous Hadley circulation (Sui et al. 2007; Wu and Zhou 2008). In other words, the SST over the WNP has changed since the late 2000s relative to that in 1981–2009, which may strengthen the thermal forcing effect over the WNPSH, resulting in an extreme HPT over South Korea.
Therefore, we detected significant differences in large-scale atmospheric circulation patterns such as the northward upper-level subtropical jet, strengthened downward motion, anomalous anticyclones around South Korea, and increased SST over the northern Pacific, between 2010–18 and 1981–2009. These differences are related to the enhancement and westward expansion of WNPSH and are responsible for increasing HPTs over South Korea since the late 2000s.
c. Relationship between the position of WNPSH and extreme HPT days
In section 3b, we showed that the atmospheric circulation patterns that are related to the increasing HPTs are associated with the northward and westward expansion of the WNPSH since the late 2000s. The WNPSH plays an important role in the weather patterns that affect the changes in temperature and precipitation over East Asia (Yang et al. 2003; Zhou and Yu 2005; Zhou et al. 2009; Guan et al. 2019). The WNPSH also exhibits both meridional and zonal movement from subseasonal to interannual time scales (Ren et al. 2013; Yang et al. 2017; Wang et al. 2019). Therefore, the position of the WNPSH may affect the variability of the HPT over South Korea. In this section, we analyze the relationship between the meridional and zonal movement of the WNPSH and extreme HPT days in South Korea. The extreme HPT days was defined as when extreme HPT occurs with extreme caution, danger and extreme danger, that is, where the value of HPT exceeds 32°C.
The WNPSH is usually measured using the geopotential height over WNP (Chung et al. 2011; Chen et al. 2019; He et al. 2015; Yoon et al. 2018; M. Li et al. 2019) and some previous studies have revealed a need for caution to interpret the decadal change of WNPSH because the geopotential height increase with global warming according to the hypsometric equation (He et al. 2018; Hu et al. 2018). Thus eddy geopotential height (Huang et al. 2015; Wu and Wang 2015; He et al. 2018) or streamfunction (Li et al. 2012) have been proposed to consider precipitation and wind field. Therefore, we also compared the position of WNPSH using the eddy geopotential height and geopotential height. It was found that eddy geopotential height was inconsistent with the change in circulation of wind and the East Asian rain belt, which is usually located on the northwest of WNPSH (not shown). Herein, we used the geopotential height to determine the western edge and intensity of WNPSH. Mathematically, the western ridge of the WNPSH defines the intersection between the zonal winds with zero and 5880-gpm isopleths (He et al. 2015; Yoon et al. 2018; M. Li et al. 2019) because there is wind reversion from easterly to westerly along the ridge line shown in Fig. 9. Climatologically, the western ridge of the WNPSH is located at approximately 29°N, 132°E. To investigate the relationship between the western ridge of the WNPSH and the extreme HPT days over South Korea, we divided the study domain into four regions around the climatological position of the western ridge of the WNPSH: northeast (NE), northwest (NW), southwest (SW), and southeast (SE) (Fig. 9).
Climatological position of the western ridge of WNPSH (yellow dot), geopotential height at 500 hPa (contours, with 20-gpm interval), and wind at 850 hPa (vectors; m s−1) during 1981–2010.
Citation: Journal of Climate 34, 4; 10.1175/JCLI-D-20-0344.1
Figure 10 indicates the occurrence rate of the western ridge of the WNPSH in extreme HPT days during 1981–2009 (Fig. 10a) and 2010–18 (Fig. 10b). In 1981–2009, the western ridge of the WNPSH exhibited an occurrence rate of 25.4% in the SW and 38.1%, 13.3%, and 23.2% in the NW, SE, and NE, respectively. In 2010–18, the western ridge of the WNPSH was located in the SW, NW, SE, and NE with rates of occurrence of 34.9%, 39.2%, 11.8%, and 14%, respectively (Fig. 10). Figure 11 shows the normalized intensity of WNPSH following He et al. (2018), which was calculated as the sum of geopotential height at 500 hPa minus 5870 gpm for all of the grid points with geopotential height greater than that of 5880 gpm over the region 110°–180°E, 10°–85°N. It illustrated that the WNPSH was intensified after 2010 even accounting for interannual variability. These results confirm the westward extension and intensification of the WNPSH since the late 2000s, as described in section 3b. Therefore, we focused on the analysis of the position of the western ridge of the WNPSH in the NW and SW regions during 1981–2018 to identify the common characteristics of extreme HPT days.
Occurrence rate of the western ridge of WNPSH for extreme HPT days during (a) 1981–2009 and (b) 2010–18. The values in the respective corners indicate the occurrence rate of the western ridge of WNPSH in the northwest (NW), southwest (SW), northeast (NE), and southeast (SE).
Citation: Journal of Climate 34, 4; 10.1175/JCLI-D-20-0344.1
Normalized intensity of WNPSH from 1981 to 2018. The two horizontal lines indicate the average of normalized intensity of WNPSH during 1981–2009 and 2010–18.
Citation: Journal of Climate 34, 4; 10.1175/JCLI-D-20-0344.1
To examine the large-scale atmospheric circulation patterns associated with the movement of the western ridge of the WNPSH, we performed a composite analysis excluding trend to eliminate the effect of global warming. Figure 12 presents the temperature anomalies at 2 m above ground, geopotential height at 500 hPa, sea level pressure and zonal wind at 200 hPa, vertically integrated moisture flux and wind at 850 hPa, and SST when the ridge was located in the NW region relative to its climatological position during 1981–2010. An anomaly of temperature 2 m above ground (Fig. 12a) indicated that most of the positive temperature anomalies occurred in South Korea and extended farther into the west and north of the country. The geopotential height anomaly at 500 hPa was positive, with its center over South Korea, while a negative geopotential height anomaly was observed over the South China Sea (Fig. 12b). This meridional wave pattern with cyclone–anticyclone anomalies from south to north along the East Asian coast resembles the Rossby wave and is known as the Pacific–Japan pattern, associated with extreme temperatures over East Asia (Xu et al. 2019). Moreover, the sea level pressure anomaly was positive (Fig. 12c) around South Korea and Japan and negative over the South China Sea. These features with anomalous anticyclonic circulation at the upper and lower levels over South Korea may be attributable to the downward motion and tend to increase the temperature at the upper and lower levels through adiabatic atmospheric warming caused by subsidence and enhanced solar radiation. These structures are similar to large-scale atmospheric circulation patterns associated with heat waves over South Korea (Lee and Lee 2016; Lee et al. 2016). The composite of the zonal wind anomaly at 200 hPa (Fig. 12d) is characterized by weakened westerly winds in South Korea, indicating a northward shift of the upper-level tropospheric jet. In general, upper-level divergence (convergence) is associated with upward (downward) vertical motion. The weakened westerly upper-level tropospheric jet leading convergence at upper levels along the middle of China and South Korea decreases (for divergence) the vertical integral of moisture (Fig. 12e) (Lin 2013; Xie et al. 2015).
Composite anomaly map of (a) temperature 2 m above ground (shading, with 0.2°C interval), (b) geopotential height at 500 hPa (shading, with 4-gpm interval), (c) sea level pressure (shading, with 0.5-hPa interval), (d) zonal wind at 200 hPa (shading, with1 m s−1 interval), (e) vertical integrated moisture (shading, with 104 kg m−2 s−1 interval) and wind at 850 hPa (vectors; m s−1), and (f) sea surface temperature (shading, with 0.2°C interval) when the western ridge is located in the northwest region relative to its climatological position in 1981–2018. The stippling indicates statistical significance exceeding the 95% confidence level with Student’s t test.
Citation: Journal of Climate 34, 4; 10.1175/JCLI-D-20-0344.1
Another composite analysis was also performed for the atmospheric variables when the ridge was located in the SW region relative to its climatological position for 1981–2010. In this case, the western edge of the WNPSH shifted southwestward and reached the coastal regions of eastern China. Thus, the 500-hPa geopotential height anomaly centered over the South China Sea and South Korea was affected by the western edge of this anomalous anticyclone, accompanied by westerly winds (Figs. 13b,e). The vertical integral of the moisture anomaly when the western edge of WNPSH was located in the SW region showed negative anomalies over most parts of the South China Sea and South Korea near 110°–150°E and 10°–40°N (Fig. 13e). This means that convective activities were strongly suppressed over the South China Sea, but their intensity over South Korea was weak in comparison with the position of the western edge of the WNPSH in the NW. The SST anomaly was characterized by a positive anomaly in the South China Sea in contrast to a negative SST anomaly when the western edge of the WNPSH is located in the NW region (Fig. 13f).
As in Fig. 12, but when the western ridge is located in the southwest region relative to its climatological position in 1981–2018.
Citation: Journal of Climate 34, 4; 10.1175/JCLI-D-20-0344.1
To compare the position of the western edge of the WNPSH between extreme HPT days and extreme maximum temperature days, we applied the occurrence rate of the western ridge of WNPSH to the extreme maximum temperature days (Fig. 14). The extreme maximum temperature days were defined as above 32°C in the maximum temperature only. Unlike extreme HPT days, the western edge of the WNPSH was located in the NW region approximately 50% of the time when the extreme maximum temperature days occurred. They could be explained considering that the typical large-scale features associated with the extreme maximum temperature days over South Korea are characterized by the dominant anticyclone circulation centered on South Korea and the Pacific–Japan pattern (Lee and Lee 2016; Xu et al. 2019). Furthermore, to understand the difference in atmospheric circulation of extreme HPT and extreme maximum temperature days, we presented the composite differences between extreme HPT and extreme temperature days (Fig. 15). In the sea level pressure field during an extreme HPT day, an anomalous low is located over South Korea and an anomalous high is located over the south of Japan. The vertical integral of the moisture showed positive anomalies over South Korea. It is clear that extreme HPT days are associated with enhanced anticyclonic circulation over the south of Japan and increased moisture over South Korea, relative to the situation with extreme maximum temperature. These results indicate that the extreme HPT days can be caused by an increase in relative humidity. The frequency of extreme HPT days considering the combined effect between temperature and relative humidity was higher compared to the frequency when only temperature was considered (Fig. 14b). This implies that extreme days can be underestimated when only temperature not considering humidity to quantify heat hazard and heat risk assessment.
(a) Occurrence rate of the western ridge of WNPSH for extreme maximum temperature days during 1981–2009 and (b) the frequency of extreme maximum temperature and HPT days. The values in (a) in the respective corners indicate the occurrence rate of the western ridge of WNPSH in the NW, SW, NE, and SE.
Citation: Journal of Climate 34, 4; 10.1175/JCLI-D-20-0344.1
Difference map of (a) sea level pressure (shading, with 0.5-hPa interval) and (b) vertical integrated moisture (shading, with 104 kg m−2 s−1 interval) and wind at 850 hPa (vectors; m s−1) between extreme HPT and extreme maximum temperature days. The stippling indicates statistical significance exceeding 95% confidence level with Student’s t test.
Citation: Journal of Climate 34, 4; 10.1175/JCLI-D-20-0344.1
Table 3 and Fig. 16 indicate the observational average of HPT, maximum temperature, relative humidity, and the number of stations when the extreme HPT occurred over South Korea according to the position of the ridge of the WNPSH. When the ridge of WNPSH was in the NW region, approximately 37% of the stations in South Korea had an HPT of at least 34.06°C. This indicates a relatively higher average HPT and maximum temperature and relatively lower relative humidity when compared with the position of the western edge of the WNPSH in the SW (Figs. 16e,f). The higher maximum temperature and relatively lower relative humidity likely contribute to the occurrence of the extreme HPT when the western edge of the WNPSH is located in the NW.
The observational average of HPT (°C), maximum temperature (°C), relative humidity (%), and the rate of stations (%) when extreme HPT occurs with extreme caution, danger, and extreme danger (HPT > 32°C) in South Korea according to the position of the ridge of WNPSH in 1981–2018 and in 2010–18 (in parentheses).
Composite maps of (a),(b) daily maximum temperature (°) and (d),(e) daily minimum relative humidity (%) when the western ridge is located in the (left) NW or (center) SW region relative to its climatological position in 1981–2018. Also shown are (c) the difference between (a) and (b) and (f) the difference between (d) and (e).
Citation: Journal of Climate 34, 4; 10.1175/JCLI-D-20-0344.1
There is a relatively lower temperature and higher relative humidity when the western edge of the WNPSH is located in the SW region. Approximately 32% of the stations in South Korea experienced extreme HPT days. The average HPT was 32.81°C when the western edge of the WNPSH was located in the SW. The average maximum temperature and relative humidity were 29.59°C and 60.64%, respectively. These results suggest that the occurrence of extreme HPT over South Korea was due to the lower maximum temperature and higher relative humidity due to the wind circulation pattern, bringing warm and moist air from the West (Yellow) Sea of South Korea along the ridge line of the WNPSH.
These results suggest that the position of the western edge of the WNPSH plays an important role in the variability of HPT in terms of intensity and spatial distribution. When the western edge of the WNPSH is located in the NW, a positive geopotential height anomaly at 500 hPa is centered over South Korea, which is associated with high temperature and low relative humidity. Otherwise, the southwestern extension of the WNPSH modifies the wind circulation pattern and brings warm and moist air from the West Sea along the ridge line of the WNPSH (Hong et al. 2018; M. Li et al. 2019; Ha et al. 2020; Yoon et al. 2020). Eventually, this leads to extreme HPT associated with high relative humidity and temperature in South Korea.
4. Summary and conclusions
In this study, we analyzed the temporal and spatial trends and changepoints in HPT in South Korea to investigate the potential impact of the combination of temperature and relative humidity on the human body in the summers of the years between 1981 and 2018. Our results showed clear interdecadal variations and a statistically significant increasing trend for temperature and HPT at the 70% confidence level. The trend of HPT is stronger than that of the minimum, mean, and maximum temperatures during 1981–2018. These results are in good agreement with those of recent studies; HPT increased faster than the air temperature (Li et al. 2018; Russo et al. 2017; Luo and Lau 2019). There was an abrupt change in temperature at the 95% confidence level between 1981–2009 and 2010–18. This detection point is likely related to the changes in large-scale atmospheric circulation patterns. In the interannual frequency variability of HPT, the category for danger has been established since the late 2000s. This result suggests that human health risks of the combined effects of high temperature and humidity have increased in South Korea since the late 2000s.
To determine the causes of the rapidly increasing trend of HPT over South Korea in recent years, we investigated the large-scale atmospheric circulations between two periods. We identified significant differences in large-scale atmospheric circulation patterns including a northward upper-level subtropical jet, strengthened downward motion, anomalous anticyclones, and increased SST over the northern Pacific, which are related to the enhancement and westward expansion of the WNPSH between 1981–2009 and 2010–18. These results suggest that the northward and westward expansion of the WNPSH is associated with the increasing HPT in South Korea since the late 2000s.
This study focused on the relationship between the position of the western edge of the WNPSH and the extreme HPT days in South Korea. When the western edge of the WNPSH was located in the northwest, a positive geopotential height anomaly at 500 hPa is centered over South Korea, which is associated with high temperature and low relative humidity. The southwestern extension of the WNPSH modifies the wind circulation pattern and brings warm and moist air from the South China Sea along the ridge line of the WNPSH. This leads to extreme HPTs in South Korea, particularly in the southern part of the country. The results of this study imply that the position of the western edge of the WNPSH plays an important role in the variability of HPT over South Korea. Although this study focused on the variability of HPT in South Korea and relationship between the position of WNPSH and the variability, WNPSH is one of the key factors modulating summer monsoon system on East Asia including Japan and China. Therefore, we concluded that monitoring and predicting the location of the WNPSH and understanding what mechanisms and factors cause the movement of WNPSH under global warming is necessary for predicting and coping with the extreme temperature events.
While the relationship between the position of the western edge of the WNPSH and extreme HPT days in South Korea is addressed in this study, the causes of the westward extension and intensification of the WPSH since the late 2000s are not discussed. Further research is needed based on a more quantitative and detailed analysis of the observations and climate models to simulate the WNPSH.
Acknowledgments
This research was jointly supported by the APEC Climate Center and Pusan National University. Further support was partially provided to this research by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2020R1A6A1A03044834). The authors acknowledge the use of ERA-Interim database, obtained from the European Centre for Medium Range Forecasts (ECMWF) (https://www.ecmwf.int/en/forecasts/datasets/archive-datasets/reanalysis-datasets/era-interim). SST data (OISST, version 2), which were obtained from NOAA/OAR/ESRL PSD (http://www.esrl.noaa.gov/psd/), are gratefully acknowledged.
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