3.1 Relationship between heat wave days (HWD) in Korea and TC genesis frequency (TCGF) over the western North Pacific (WNP)
Figure 2a shows the TCGF in the WNP and the time series of HWD in Korea during July and August. Both time series show distinct interannual variations rather than decadal variations. Meanwhile, the linear trend of the TCGF is statistically insignificant because it shows little change, but the HWD in Korea shows an increasing linear trend due to the effect of global warming. This increasing linear trend is significant at the 95% confidence level. A close observation of these two time-series reveals an in-phase trend between the two variables. Thus, a correlation analysis between the two variables shows a strong positive correlation of 0.57. This correlation is significant at the 99% confidence level. This means that the higher the TCGF in the WNP during July and August, the higher the HWD in Korea. However, this correlation may change if the linear trend is removed from the two variables. Therefore, the correlation was analyzed again after removing the linear trend from the two variables. However, it did not show a significant difference from the original correlation (Corr = 0.55, which is significant at the 99% confidence level). Furthermore, the correlation between tropical night in Korea and the TCGF in the WNP during July and August also shows a high correlation of 0.60 (not shown). This correlation is also significant at the 99% confidence level.
Meanwhile, to examine in more detail on the correlation between HWD in Korea and TCGF in the WNP during July and August, the WNP was divided into the following four areas (Fig. 3a): Northwest (NW) area, Southwest (SW) area, Northeast (NE) area, Southeast (SE) area. This distinction was based on 16°N and 141°E, according to as the average TC genesis location for 46 years. Among these four areas, the area that showed the highest correlation between TCGF and HWD in Korea during July and August is SE area with a correlation of 0.63. This correlation is significant at the 99% confidence level. The next is NW area in which the TCGF during July and August in this area and the HWD in Korea have a correlation of 0.52. This correlation is also significant at the 99% confidence level. The correlation between the two variables in the other two regions is low at 0.25 or lower. This correlation in these two regions is significant at 90% confidence level. Consequently, the two variables tend to have a high correlation only in the NW and SE areas in the WNP. This appears to be because a monsoon trough develops from the northwest to southeast direction in the tropical and subtropical WNP in general, and TCs tend to occur along this monsoon trough (Matsuura et al. 2003).
Therefore, the time series of TCGF during July and August in the NW and SE areas were analyzed (Figs. 3b and 3c). The time series of TCGF in the NW area shows the lowest frequency in the late 2000s and tend to increase rapidly since 2010 (Fig. 3b). However, the linear trend changed very little during the total analysis period of 46 years. However, a correlation analysis was conducted after removing the linear trend from the two variables because the linear trend of the HWD tended to increase in Korea, but it was not much different from the original correlation (Corr = 0.51, which is significant at the 99% confidence level). The TCGF time series in the SE area has a strong interannual variation in general, but a weak interdecadal variation can be seen as well. They also show a rapidly increasing trend since the early 2010s (Fig. 3c). This time series also shows very little change in linear trend, and the correlation did not change even when the linear trend was removed from the two time series (Corr = 0.62, which is significant at the 99% confidence level).
3.2 Spatiotemporal distribution of air temperature and rainfall
To examine the reason for the high positive correlation between the TCGF during July and August in the WNP and the high HWD in Korea from the above analysis results, 15 years with the highest frequency in the TCGF time series in the WNP during July and August out of the 46 years and 15 years with the lowest frequency out of the 46 years were selected and defined as high TCGF years and low TCGF years, respectively (Table 1). The selected 30 years have a number of samples large enough to occupy about 70% of the total analysis period. Then the mean difference between high TCGF years and low TCGF years was analyzed. The mean HWD in Korea for 46 years is 10.9 days, and there are only four years among the high TCGF years that did not exceed this mean HWD (1981, 1989, 1992, 2002) and only four years among the low TCGF years that did not exceed this mean HWD (1983, 1995, 2008, 2010). Hence, the mean HWD of high TCGF years is 15.4 days, but the mean HWD of low TCGF years is 8.0 days, and the difference in the mean HWD between the two groups is 7.4 days. This mean difference is significant at the 95% confidence level.
Table 1
Heat wave days (HWD) in Korea in high tropical cyclone genesis frequency (TCGF) years and low TCGF years.
High TCGF years | | Low TCGF years |
Year | HWD | | | Year | HWD | |
1973 | 16.2 | | | 1975 | 10.0 | |
1978 | 17.0 | | | 1977 | 10.9 | |
1981 | 9.3 | | | 1979 | 5.9 | |
1989 | 4.7 | | | 1980 | 0.8 | |
1992 | 6.7 | | | 1983 | 11.3 | |
1994 | 31.1 | | | 1995 | 11.8 | |
1997 | 12.8 | | | 1998 | 2.6 | |
2000 | 12.4 | | | 2003 | 1.6 | |
2001 | 12.7 | | | 2007 | 9.8 | |
2002 | 5.9 | | | 2008 | 12.5 | |
2004 | 16.0 | | | 2009 | 4.2 | |
2013 | 18.5 | | | 2010 | 13.9 | |
2016 | 22.4 | | | 2011 | 7.5 | |
2017 | 14.4 | | | 2014 | 7.4 | |
2018 | 31.5 | | | 2015 | 10.1 | |
Average | 15.4 | | | Average | 8.0 | |
First, we examined the spatial distribution of the mean SAT in July and August for the two groups (left panel of Figs. 4a and 4b). The spatial distributions of the two groups appear similar in general. The northeast region in Korea shows the lowest SAT whereas the southeast inland and west inland areas show somewhat high SATs. However, most areas excluding the northeast region in high TCGF years show SATs higher than 30°C (left panel of Fig. 4a), whereas in low TCGF years, most areas in Korea show SATs lower than 30°C (left panel of Fig. 4b). The difference between the two groups shows positive anomaly in all areas in Korea (left panel of Fig. 4c), and the largest value in the central region of the east coast. Meteorologically, this region is known to have relatively high temperatures during summer in the country (Ko et al. 2006). The daily time series of the difference between the two groups for SAT indicate that the high TCGF years have higher values from January to August whereas the low TCGF years have higher values from September to November (left panel of Fig. 4d). The largest variations in the SAT during the year appear in these two periods.
The reason that the SAT is high (low) may be because there are few (many) clouds in the atmosphere and there is a low (high) possibility of precipitation. Hence, the spatial distribution of total rainfalls in July and August for the two groups were analyzed (right panel of Figs. 4a and 4b). As expected, the spatial distributions of the two groups appear similar overall. The rainfall is relatively large in the northern region of Korea, whereas the rainfall is low in the eastern region and the west coast region. During the high TCGF years, the rainfall in the northern region of Korea is only 600mm (right panel of Fig. 4a), but during the low TCGF years, it is higher than 700 mm in the region (right panel of Fig. 4b). In particular, the rainfall in the eastern region of Korea is lower during the high TCGF years. The difference between the two groups shows negative anomaly in most areas excluding the northeast coastal region and part of the southeast coast region (right panel of Fig. 4c). This means that there were large rainfalls during the low TCGF years than during the high TCGF years. The largest difference appears in the northeast and southeast regions of Korea. The daily time series of the difference in rainfall between the two groups showed strong negative anomaly during July and August, indicating that the HWD could increase in Korea during the high TCGF years (right panel of Fig. 4d).
3.3 Large-scale environments and atmospheric circulations
This study first analyzed the difference in 2m air temperature (Air2m) between the two groups in Asia (Fig. 5). In the mid-latitude region of East Asia (30°-40°N), the Air2m is higher during the high TCGF years, whereas the spatial distribution is higher during the low TCGF years in other regions. Thus, it can be seen from this analysis that the increase of HWD during the high TCGF years is likely to occur in the entire mid-latitude region of East Asia as well as in Korea. Then the East Asia was divided into Northeast (NE) Asia area (30°-40°N, 115°-140°E) and South China (SC) area (20°-30°N, 110°-120°E). The time series of Air2m area-averaged in each region and the TCGF time series during July and August in the WNP are shown in Figs. 2b and 2c. First, the Air2m time series area-averaged in the NE Asia area shows strong interannual variations and weak interdecadal variations (Fig. 2b). The linear trend of this time series shows an increasing linear trend, which is significant at the 95% confidence level. This increasing trend may be due to the effect of global warming. Furthermore, the two time series shows an in-phase trend, and an analysis of the correlation between these two variables showed a positive correlation of 0.43. This correlation is significant at the 99% confidence level. This implies that if the TCGF in the WNP increases during July and August, there is a possibility that the HWD in the NE Asia area can increase as well. Since the two time series show a distinctly increasing linear trend, the correlation may be changed if the linear trend is removed from the two time series. Therefore, the correlation was reanalyzed after removing the trend from the two time series. As a result, the correlation became higher than the original correlation (Corr = 0.46, which is significant at the 95% confidence level). The Air2m time series area-averaged in the SC area shows interannual and interdecadal variations (Fig. 2c). This time series also shows an increasing linear trend due to the effect of global warming, and this increasing linear trend is significant at the 95% confidence level. Furthermore, since these two time series show a trend of out-of-phase, the correlation between the two variables was analyzed. The result showed a negative correlation of -0.47 and this correlation is significant at the 99% confidence level. This indicates the possibility of decreasing HWD in the SC area where the TCGF increases during July and August in the WNP. When the correlation was reanalyzed after removing the linear trend from the two time series, the negative correlation was strengthened to some extent (Corr = -0.49, which is significant at the 99% confidence level).
Meanwhile, the differences in air temperature between the two groups were analyzed at lower-level (850 hPa), middle-level (500 hPa), and upper-level (300 hPa) (left panel of Fig. 6). At 850 hPa, a warm anomaly is located in the mid-latitude region of East Asia, at the center of which Korea exists (left panel of Fig. 6a). The warm anomaly in Korea is significant at the 95% confidence level. In addition, a weak warm anomaly appears in the WNP in which TCs occur. Although weak, this warm anomaly must have influenced the increase of TCGF. At 500 hPa, a warm anomaly located in the mid-latitude region of East Asia was shifted further north (left panel of Fig. 6b). Thus, the southern region of Korea is included in the cold anomaly, but it is not statistically significant. In the WNP, the area of warm anomaly was also shifted to the north. At 300 hPa, the warm anomaly in the mid-latitude region of East Asia moved much further to the north and the entire Korea shows a cold anomaly (left panel of Fig. 6c). The warm anomaly in the WNP is a little strengthened than at 850 and 500 hPa.
If the relative humidity is also high when the air temperature is high, people tend to feel more uncomfortable. Thus, the difference in relative humidity between the two groups was analyzed (middle panel of Fig. 6). At all levels, a negative anomaly is located in the Korean Peninsula. This is believed to be due to the evaporation of water vapor as the subsidence was strengthened by the formation of anomalous anticyclone in Korea. Meanwhile, in the WNP where TCs were generated, the positive anomaly appears at every level. This is an important factor in increasing the TCGF. Gray (1975) analyzed relative humidity at lower-level and middle-level is one of the important factors among the six physical parameters that influence TC genesis.
To examine the variations of the spatial distributions of air temperature and relative humidity according to the level analyzed above, the differences in atmospheric circulations at the three levels were analyzed (right panel of Fig. 6). In all the layers of the troposphere, anomalous anticyclonic circulations are strengthened in the mid-latitude region of East Asia and anomalous cyclonic circulations are strengthened in the WNP. This is similar to the Pacific-Japan (PJ) teleconnection pattern (Nitta 1986, 1987, 1989). The PJ pattern is an important pattern that influences the East Asian climate in summer (e.g., rainfall and air temperature) and TC genesis (Choi et al. 2010). Therefore, the correlations of the PJ index with the HWD in Korea and the TCGF in the WNP during July and August were analyzed (not shown). The results showed positive correlations of 0.43 and 0.41, respectively, and these correlations were significant at the 99% confidence level. This suggests that in Korea, subsidence developed and water vapors evaporated with the strengthening of the anomalous anticyclone, resulting in negative relative humidity at every level. Moreover, as it moves from the lower level to the upper level, the anomalous anticyclone in the mid-latitude of East Asia is shifted to the north. Consequently, as analyzed above, the warm anomaly in the mid-latitude region of East Asia was shifted to the north toward the upper level. Meanwhile, the anomalous cyclone strengthened in the WNP at the three levels became an important background in the increase of TCGF.
The increase or decrease of HWD in Korea is associated with the locations of western North Pacific subtropical high (WNPSH) and Tibetan high (TH) (Wu et al. 2012). Hence, the degree of development of WNPSH and TH was analyzed for the two groups (left panel of Fig. 7). Here, WNPSH (red line) and TH (blue line) are defined as areas larger than 5,870 gpm and 12,480 gpm. The WNPSH is strengthened northwest to the western sea of Korea during the high TCGF years (left panel of Fig. 6a), whereas during the low TCGF years, it is expanded southwest to the southeastern region of China (left panel of Fig. 6b). TH is located a little north in the high TCGF years than in the low TCGF years, and is further expanded to the east during the low TCGF years. Hence, two high pressure systems are overlapped in Korea in high TCGF years. Thus, it can be seen that the HWD increased as the solar radiation increased due to the strengthening of subsidence as the high pressure systems were located in the upper and lower layers of the troposphere in Korea. Furthermore, during the high TCGF years, the two high pressure systems shifted to the north and low pressure systems were strengthened in the WNP, thus increasing the TCGF.
To examine this, the 850 hPa geopotential height mean field was analyzed for the two groups (right panel of Fig. 7). Here, the dashed and solid lines indicate the monsoon trough and the ridge of WNPSH. The ridge of WNPSH is expanded northwest to the northeastern region of China in high TCGF years (right panel of Fig. 7a), but in low TCGF years, it is expanded west to the eastern coast of central China (right panel of Fig. 7b). As a result, in the high TCGF years when the ridge of WNPSH is shifted more to the north, the monsoon trough is strengthened east to 145°E (right panel of Fig. 7a). By contrast, in the low TCGF years, the monsoon trough is weakened only to 130°E. This suggests that the strengthening of the ridge of WNPSH and monsoon trough in high TCGF years is associated with the increase of HWD in Korea and the increase of TCGF in the WNP during July and August.
3.4 Local Hadley circulation
Meanwhile, the anomalous anticyclone strengthened in the mid-latitude region of East Asia and the anomalous cyclone strengthened in the WNP can be associated with local Hadley circulation. To examine this, the difference in the vertical meridional circulation averaged over the longitude range of 120°-130°E where Korea is located was analyzed (Fig. 8a). Anomalous upward flows are strengthened at 10°-30°N where the WNP is located and anomalous downward flows are strengthened at 30°-40°N where Korea is located. In particular, the center of anomalous upward motion in the WNP is located at 10°-20°N, and this is significant at the 95% confidence level. Furthermore, the center of anomalous downward motion at 30°-40°N is distributed at 30°-35°N where South Korea is located,which is placed in a region of the 95% confidence level. This anomalous vertical structure between the WNP and Korea means that the air rising in the WNP subsides in Korea. Therefore, the TCGF can increase in the WNP and can be an important background in which the HWD can increase in Korea. As a result of this, in the vertical structure of air temperature, a warm anomaly appears in the lower level of 30°-40°E where Korea is located, and in the higher level, a cold anomaly appears (Fig. 8b). This result is consistent with the result in Fig. 6, which showed that the warm anomaly in the mid-latitude region of East Asia is shifted to the north toward the upper level. In the vertical structure of relative humidity, a negative anomaly appears in every level of the latitude range of Korea, and this characteristic is also consistent with the result in Fig. 6 (Fig. 8c).
This local Hadley circulation that developed in high TCGF years can be also seen in the analysis of the differences in the horizontal divergence at lower and upper levels between the two groups (Fig. 9). At 850 hPa, a negative anomaly appears in the WNP and a positive anomaly appears in the longitude range of 20°-30°N (Fig. 9a). This means that anomalous convergence is strengthened in the WNP and anomalous divergence is strengthened at 20°-30°N. However, Korea shows a weak negative anomaly. At 200 hPa, a positive anomaly is strengthened in the WNP and a negative anomaly is located in the longitude range of 30°-35°N where South Korea is located (Fig. 9b). This implies that anomalous divergence is strengthened in the WNP and anomalous convergence is strengthened in the mid-latitude region of East Asia. Thus, such a structure of horizontal divergence formed in the lower and upper levels implies that the air rising in the WNP falls in the mid-latitude region of East Asia, and this indicates that local Hadley circulation is strengthened in high TCGF years.
In summer, the higher the HWD, the lower the precipitation becomes, which can cause a drought. Thus, the mean PDSI in Korea during July and August and the time series of HWD in Korea were analyzed (Fig. 10a). A smaller PDSI implies a worse drought. The time series of the PDSI has strong interannual variations and the drought has worsened until recently due to the effect of climate change. This linear trend is significant at the 95% confidence level. Meanwhile, there is a distinct in-phase trend between the two variables. An analysis of the correlation between the two variables shows a high negative correlation of -0.60. This high negative correlation is significant at the 99% confidence level. This means that in Korea, drought worsens as the HWD increases. The two time series show a distinct change in the linear trend, but the correlation did not show a significant difference from the original correlation even when the linear trend was removed from the two time series (Corr = -0.58, which is significant at the 99% confidence level). In addition, the mean PDSI during July and August in Korea and the time series of TCGF in the WNP during July and August were analyzed (Fig. 10b). There is a distinct out-of-phase trend between the two variables. Therefore, the correlation between the two variables was analyzed and it showed a negative correlation of -0.46. This correlation is significant at the 99% confidence level. This indicates that an increase of TCGF in the WNP strengthens drought in Korea, and this result is associated with the local Hadley circulation as analyzed above.
3.5 EASM and WNPSM
The anomalous anticyclone strengthened in the mid-latitude region of East Asia and the anomalous cyclone strengthened in the WNP can be associated with EASM and WNPSM, respectively. Hence, the time series of the HWD in Korea and the mean EASMI and WNPSMI during July and August were analyzed (Figs. 11a and 11b). The HWD in Korea and the EASMI showed an out-of-phase trend. When the correlation between the two variables was analyzed, the result showed a negative correlation of -0.57 (Fig. 11a). This correlation is significant at the 99% confidence level. This implies that as the EASM is strengthened (weakened), the HWD in Korea becomes lower (higher). The linear trend of the EASMI shows little change. Consequently, the correlation did not show a significant difference from the original correlation even when the linear trend was removed from the two time series (Corr = -0.56, which is significant at the 99 confidence level). The time series of the HWD in Korea and the mean WNPSMI during July and August were also analyzed (Fig. 11b). The two variables showed a distinct in-phase trend. When the correlation was analyzed, it showed a positive correlation of 0.56. This correlation is significant at the 99% confidence level. The WNPSMI has shown an increasing linear trend until recently, and this increasing linear trend is significant at the 90% confidence level. Therefore, the correlation was reanalyzed after removing the linear trend from the two time series, and it did not show a significant difference from the original correlation (Corr = 0.58, which is significant at the 99% confidence level). The above result suggests that the anomalous anticyclone strengthened in the mid-latitude region of East Asia during high TCGF years implies weakening of the EASM, and the anomalous cyclone strengthened in the WNP implies the strengthening of the WNPSM. Regarding this, Choi et al. (2016) have found that when the WNPSM is strengthened, the TCGF increases, but the EASM tends to be weakened.
To examine whether the EASM was weakened in the mid-latitude region of East Asia during high TCGF years and whether the WNPSM was strengthened in the WNP, the differences in the mean OLR, total cloud cover, and rainfall during July and August were analyzed (Figs. 11c, 11d, and 11e). In the analysis result of OLR, a negative anomaly appears in the WNP, whereas a positive anomaly appears in the mid-latitude region of East Asia (Fig. 11a). In particular, the center of positive anomaly in the mid-latitude region of East Asia is located in the zonal direction from the central eastern China to Korea and Japan. The positive anomaly in this region is significant at the 95% confidence level. From the above result, it can be seen that convective activity is strengthened in the WNP whereas the convective activity is weakened in the mid-latitude region of East Asia. As a result, a large amount of clouds is observed in the WNP regarding the total cloud cover and a negative anomaly appears in the mid-latitude region of East Asia (Fig. 11d). The negative anomaly in Korea is significant at the 95% confidence level. The large amount of clouds formed by the strengthening of convective activity in the WNP leads to a large amount of rainfalls, and the opposite characteristic appears in the mid-latitude region of East Asia (Fig. 11e).
3.6 ENSO
Meanwhile, to examine whether the El Niño-Southern Oscillation (ENSO) influences the HWD in Korea, the difference in the mean SST during July and August between the two groups was analyzed (Fig. 12a). In general, a strong cold anomaly appeared in the equatorial eastern Pacific, and this implies that the eastern Pacific (EP) La Niña strengthened during the high TCGF years. When the analysis result of the difference in velocity potential at lower and upper levels is examined, at the lower level, the center of anomalous convergence is located in the east-west direction from the eastern sea of Australia to the offshore of Peru. At the upper level, the center of anomalous divergence is located in subtropical and tropical central pacific (Figs. 12b and 12c). Therefore, the correlation between the Niño-3 index and the HWD in Korea was analyzed (not shown). These two variables showed a negative correlation of -0.25 at the 90% confidence level. However, the correlation analysis between the Niño-3 index and the TCGF in the WNP during July and August showed a negative correlation of -0.17, which is statistically insignificant. Thus, a partial correlation analysis was conducted to examine whether the ENSO influenced the high positive correlation between HWD in Korea and TCGF in the WNP during July and August (Table 2). When the Niño-3 index was set as a control variable, the HWD in Korea and the TCGF in the WNP during July and August showed a positive correlation of 0.50. This correlation was significant at the 99% confidence level. This result suggests that the effect of ENSO on the high positive correlation between the two variables is small.
Table 2
Statistical result of partial correlation analysis.
Control variable | Correlation variable | HWD | TCGF |
Nino 3 index | HWD | 1.0 | 0.50 |
TCGF | 0.50 | 1.0 |
3.7 Scandinavia teleconnection pattern
To determine the cause of the formation of anomalous anticyclone in the mid-latitude region of East Asia and the formation of anomalous cyclone in the WNP during the high TCGF years, the 500 hPa wave activity flux was analyzed (Fig. 13a). The wave activity flux originates from the North Atlantic passes through the Scandinavian Peninsula, the North coast of Russia and East Siberia before reaching Korea and the WNP. The analysis of the difference in the 500 hPa geopotential height between the two groups shows a positive anomaly in the western sea of the UK, the Scandinavian Peninsula, northwestern coast of Russia, and the regions from Central Asia to the Bering Sea (shading in Fig. 13a). This spatial distribution is similar to the Scandinavia teleconnection pattern. Therefore, it can be seen that the anomalous anticyclone formed in the mid-latitude region of East Asia and the anomalous cyclone formed in the WNP during the high TCGF years are associated with the Scandinavia teleconnection pattern. To examine whether the HWD in Korea and the TCGF during July and August are associated with the Scandinavia teleconnection pattern, the Scandinavia index and the time series between the two variables were analyzed (Figs. 13b and 13c). Both variables showed an in-phase trend with the Scandinavia index. The Scandinavia index showed a significant positive correlation of 0.45 with the HWD in Korea at the 99% confidence level (Fig. 13b). The correlation analysis with the TCGF in the WNP during July and August showed a positive correlation of 0.49 at the 99% confidence level (Fig. 13c). This shows that when the Scandinavia teleconnection pattern is strengthened, the HWD in Korea and the TCGF in the WNP during July and August are increased.
3.8 TC activity
TCs can also influence the HWD in Korea in summer. Therefore, the differences in the TCGF and TC passage frequency (TCPF) during July and August between the two groups were analyzed (Figs. 14a and 14b). The spatial distribution of the TCGF shows a higher genesis frequency during high TCGF years in general (Fig. 14a). In particular, significantly large differences at the 95% confidence level appear in the South China Sea (SCS) and the northeastern sea of the WNP. The SCS and the northeast seas of WNP show significantly large differences at the 95% confidence level. Meanwhile, the spatial distribution of the TCPF shows the spatial distribution of a dipole pattern. In other words, a negative anomaly appears in the Indochina Peninsula and SCS and the southeast region of China, and a positive anomaly in the remaining areas. The cause of such a difference in spatial distribution of the TCGF difference between the two groups can be seen from the analysis result of the difference in the 500 hPa stream flow between the two groups (right panel of Fig. 6b). In the Indochina Peninsula, SCS and the southeastern region of China, anomalous northerlies are strengthened by anomalous cyclonic circulation formed in the WNP. These anomalous northerlies can play the role of steering flows that block TCs that move toward this area. By contrast, the mid-latitude region of East Asia including Korea is influenced by anomalous southesaterlies due to anomalous anticyclonic circulation, and these anomalous southesaterlies, which play the role of steering flows that move TCs to this region. This trend is associated with the location of WNPSH for the two groups (left panel of Fig. 7). TCs generally tend to move along the western edge of WNPSH. Since the WNPSH is extended in the northwest to the western sea of Korea. Thus, TCs can easily move toward Korea and the mid-latitude region of East Asia. By contrast, during the low TCGF years, the WNPSH is extended southwest toward the southern eastern China, and TCs move to the Indochina Peninsula, SCS and the southeast region of China. Therefore, the time series of the HWD in Korea and the TCPF in the SC area were analyzed (Figs. 14c and 14d). The TCPF in Korea shows an in-phase trend with the HWD in Korea (Fig. 14c), whereas it shows an out-of-phase trend with the TCPF in the SC area (Fig. 14d). In particular, the TCPF in Korea shows a decreasing linear trend, which is significant at the 90% confidence level. According to the correlation analysis, the HWD in Korea and the TCPF in Korea shows a significant positive correlation of 0.42 at the 99% confidence level, whereas the HWD in Korea and the TCPF in the SC area shows a significant negative correlation of -0.51 at the 99% confidence level. Therefore, it can be seen that the TCPF in Korea increases, but it decreases in the SC area during the high TCGF years. Consequently, even if the TCPF in Korea increased during the high TCGF years, it could not have contributed to mitigating the heat wave.