1. Introduction
With the significant influences of the Asian-Pacific summer monsoon and the Tibetan Plateau (Wu et al. 2007), heavy rainfall occurs frequently over China during the warm season (Tao et al. 1979). Under the background of climate warming, the trends of extreme precipitation over the Asian monsoon regions show a positive and negative scattered distribution (Wang and Zhou 2005; Zhai et al. 2005; Alexander et al. 2006; Min et al. 2011), while the occurrence frequency of extreme precipitation and its contribution to total precipitation amount have increased over many regions, particularly North America and Europe (Alexander et al. 2006). The increasing extreme precipitation is partially attributed to the increasing atmospheric water storage capacity (saturated water vapor pressure) as the atmospheric temperature rises (Trenberth 1999; Zhang et al. 2017).
The rise in temperature makes extreme precipitation tend to occur in a shorter period of time (e.g., Trenberth 1999); for example, there were higher growth rates of subdaily extreme precipitation than those of daily extreme precipitation over the Netherlands and Australia (Lenderink and van Meijaard 2008; Jones et al. 2010). However, climate changes of extreme hourly precipitation (EXHP; usually defined using the 95th percentile as threshold; e.g., Wu et al. 2019; Jiang et al. 2020) are less known globally than those of extreme precipitation on a longer temporal scale (e.g., daily), due to lack of long-term observations of hourly precipitation, limited knowledge about the physical mechanisms governing the evolution of convective events, and large uncertainties of climate models in representing the mesoscale and microscale processes associated with the EXHP production (Zhang et al. 2017).
The lack of a spatially consistent increase of extreme precipitation over China is due to the complicated impacts of atmospheric dynamic processes and underlying surface forcing at regional and local scales (Luo et al. 2020). Such factors include the decadal variations associated with the “southern flood–northern drought” phenomenon of the East Asian summer monsoon rainfall (Ding and Chan 2005; Zhou et al. 2009b, 2020), the East Asian monsoon changes (Ding et al. 2009; Lin et al. 2016), the changes in tropical cyclones (TCs) (Chen et al. 2010; Chang et al. 2012), and the local anthropogenic effects induced by urbanization (Fu et al. 2019; Wu et al. 2019; Jiang et al. 2020). Among them, the impact of TCs is remarkable. Only several studies have focused on EXHP changes during the past several decades in China. It was found that the EXHP has an increasing trend in most areas of eastern China (Xiao et al. 2016), with varying scaling relationships between the precipitation extremes and temperature across China (Guo et al. 2020). The top-10 hourly precipitation over eastern China during 1970–2017 has intensified at a super-Clausius–Clapeyron rate with detectable contribution by anthropogenic warming (Chen et al. 2021). Moreover, a rainy island effect has been found over the urban agglomerations in coastal southern and eastern China, including the Pearl River Delta (PRD) and Yangtze River Delta (YRD) areas, with contrasting contributions from TCs (Liang and Ding 2017; Wu et al. 2019; Jiang et al. 2020). The increasing rate of EXHP over the PRD urban agglomeration during 1971–2016, particularly the rapid urbanization period since early-to-mid 1990s, would be lower if the TC-induced EXHP were included (Wu et al. 2019). However, TC-induced EXHP can contribute positively to the increasing rate of EXHP over the YRD urban agglomeration during 1975–2018 (Jiang et al. 2020). Therefore, the spatiotemporal variations of the TC-induced EXHP over China and its change during the past several decades remain unclear.
Occurrence and development of TCs influencing China are primarily affected by the underlying surface conditions [especially the sea surface temperature (SST)] and the atmospheric dynamic and thermal conditions (such as stability, moisture, and vertical wind shear) over tropical and subtropical oceans (Zhao et al. 2020). Recent studies suggest that there is a significant increasing trend in SST in the coastal oceans near East Asia and in water vapor over eastern Asia (Liu et al. 2020). Meanwhile, the motion of TCs over the western North Pacific seems to show a slowing trend, allowing TCs to cause greater impacts even after making landfall (Liu and Wang 2020; Zhang et al. 2020). Moreover, the occurrence frequency of TCs since 1980 has substantially decreased in the South China Sea and Philippine Sea, but has increased in the East China Sea (Zhang et al. 2020), consistent with the different changes of TC-induced precipitation over southern and eastern China, respectively (Liu and Wang 2020).
This article aims to explore the long-term changes of TC-induced EXHP in the warm season (May–September) during 1975–2018 over China by using a high-quality gauge-based hourly precipitation dataset. Specifically, this study classifies the TCs into three groups according to the number of EXHP produced by each TC during their impact period, referred to as high-, mid-, and low-EXHP TCs (their definitions will be given in section 2), seeking to answer the following questions. 1) What are the major differences in the spatiotemporal distributions of EXHP over China among the three TC groups? What are the long-term changes of each TC group and the associated EXHP during 1975–2018? 2) How are the differences related to the TC characteristics (such as intensity, moving speed, and track)? What are the possible reasons for the TC-induced EXHP changes over China?
The rest of the paper is organized as follows. Section 2 describes the data and analysis methods used in this study. Section 3 explores the characteristics in different TC groups and the associated TC-EXHP. The trends of TC-induced EXHP in different groups are presented in section 4. Section 5 discusses the possible reasons responsible for the observed changes and the involved mechanisms in the low- and high-EXHP TC groups. Finally, the primary findings are summarized in the last section.
2. Data and statistical methods
a. Data
This study utilizes the gauge-based hourly precipitation data during the 1975–2018 warm seasons (May–September) to analyze the characteristics and changes of TC-induced EXHP. Note that October is excluded because the stations located from Inner Mongolia to northeastern China only have rainfall records from May to September. These stations routinely stopped taking rainfall measurement in the freezing conditions of the winter season under certain regulations (Luo et al. 2016). This dataset has been quality-controlled by the National Meteorological Information Center (NMIC) of the China Meteorological Administration (CMA; http://data.cma.cn/data/online.html?t=1), including a climatological limit value test, a station extreme value test, an internal consistency test, and a comparison with manually checked daily precipitation data (Wu et al. 2019), and has been widely used to investigate precipitation on subdaily scales and long-term trends (e.g., Zhang and Zhai 2011; Chen et al. 2013; Luo et al. 2016; Chen et al. 2021). Additionally, these hourly data have been compared with manually checked daily rainfall data. The hourly records were replaced with missing values if the daily rainfall data are >5 mm day−1 and the relative difference [(daily data − 24-h accumulated hourly data)/daily data] is >0.2, or the daily rainfall data are ≤5 mm day−1 and the absolute difference is >1 mm (Luo et al. 2016). All the quality-controlled records with continuous hourly precipitation during the 1975–2018 warm seasons have been used in the present study in order to obtain more complete results in terms of the temporal and spatial coverages. These stations are more densely distributed over southern and southeastern China with influences by landfalling and sideswiping TCs (Feng et al. 2020).
The best track TC dataset used in this study is acquired from the Shanghai Typhoon Institute of China Meteorological Administration (STI/CMA), which includes latitude and longitude of the TC center and TC intensity in terms of the maximum sustained surface wind speed and central sea level pressure at 6-h intervals (http://tcdata.typhoon.org.cn/wxfxzl_zlhq.html). TCs including tropical depressions and extratropical transition processes during 1975–2018 are considered in our analyses. This study investigates TCs that produced at least one record of hourly precipitation ≥ 0.1 mm h−1 over the analysis region (shown in Fig. 1). In this study, the CMA/STI best-track dataset is used as the primary TC data because relatively more observational data were available over mainland China when the postseason TC analysis was conducted to generate the best-track TC data. Actually, the annual postseason analysis of TC data is performed by STI/CMA to reduce uncertainties and improve the accuracy using all available data, including station observations, ship weather reports, automated surface observations, synoptic charts, radiosonde data, aircraft reconnaissance, satellite, coastal radar observations, and the real-time TC warming advice from various agencies (Ying et al. 2014). Although the TC dataset over the offshore area and mainland China has temporal inhomogeneity due to the development of radar network and station observation network, the CMA dataset used in this study is reliable (Ying et al. 2014).
The European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim) data at a horizontal resolution of 0.75° × 0.75° (Dee et al. 2011) during the 1979–2018 warm seasons with an interval of 6 h are used to examine the large-scale environmental conditions that are relevant to the observed changes in the characteristics of TC-induced EXHP over China.
b. Methods
Considering the substantial regional variations of the hourly precipitation intensity over China (Luo et al. 2016; Zheng et al. 2016), this study utilizes the widely used percentile-threshold method to obtain the statistically significant number of EXHP samples (Zhai et al. 2005; Xiao et al. 2016; Chen and Zhai 2017; Zheng et al. 2016). The hourly precipitation (≥0.1 mm) at each station during the 30-yr (1975–2004) warm seasons is sorted from weak to strong, and then the precipitation intensity at the 95th percentile is taken as the EXHP threshold for the station (Fig. 3a). All the hourly precipitations exceeding the threshold are considered as EXHP at the station.
In this study, the objective synoptic analysis technique (OSAT) developed by Ren et al. (2006, 2007) is adopted to isolate the TC-induced rainfall from the total daily precipitation. TC precipitation can result from the TC eyewall and spiral rainbands, or far away from the TC’s center produced by the interactions between the TC circulation and other weather systems. The OSAT method imitates the process by which a weather forecaster manually analyzes a synoptic map. There are two primary steps: 1) separating the daily precipitation into several independent rainbands and 2) distinguishing which rainbands are related to the TC according to the distance function between the TC center and the distribution of the rainbands. The details of the method can be found in Ren et al. (2006, 2007). In this study, if daily rainfall at one station is related to the TC, the hourly precipitation observations at this station during that day all belong to TC precipitation.
In total 554 TCs are found, including 526 EXHP-producing TCs (i.e., with at least one EXHP event occurring over the analysis region). The total number of EXHP over land for each TC is the sum of all EXHP events within the TC’s influence area during the TC’s whole lifetime, which is determined by the impact period and the influence area of the TC. In general, more than one TC-EXHP event occurs in one impact hour within the influence range of the TC. The length of impact period for each TC is the hours when there are TC-induced EXHP events occurred during the TC’s whole lifetime. The total number of EXHP for each TC varies from 0 to 1084 (by Typhoon Winnie, CMA No. 9711). According to the total number of TC-induced EXHP for each TC, we can classify TCs into high-, mid-, or low-EXHP TC groups. TCs with numbers of EXHP events greater than 400 are defined as the high-EXHP TCs, which account for about 9.9% of total TCs (Table 1 and Fig. 2); those with numbers of EXHP events less than or equal to 160 (the mean frequency of TC-induced EXHP) are grouped as low-EXHP TCs, which account for about 25.8% of total TCs; the remaining TCs (with 161–400 EXHP) are classified as the mid-EXHP TCs, which account for about 64.3%. For each EXHP-producing TC, its moving speed is calculated for each time step (i.e., 6 h) using the spherical distance that the TC’s center has moved during the 6 h. The peak intensity of a TC is estimated as the minimum sea level pressure (Pmin) and maximum sustained wind speed (Vmax) during its impact period.
The TC-induced EXHP frequency (black line) and the ratio of EXHP frequency to total EXHP (black bar) with the increasing numbers of EXHP produced by each TC. The red lines are the dividing lines for low-, mid-, and high-EXHP TC groups.
Citation: Journal of Climate 35, 22; 10.1175/JCLI-D-21-0736.1
Number of EXHP-producing TCs and TC-induced EXHP in low-, mid-, and high-EXHP TC groups. The values in parentheses represent the contribution of different groups to total TCs and total TC-induced EXHP.
In this study, the Kruskal–Wallis nonparametric significance test is used to examine the significance of different distributions between different TC groups. Meanwhile, the Mann–Kendall nonparametric test is utilized to examine the significant trend of annual frequency of EXHP-producing TCs, the TC-induced EXHP, and the TC-induced EXHP amount during 1975–2018.
3. Characteristics of TC-induced EXHP
The threshold values used to identify the EXHP (Fig. 3a) decrease largely from south to north, that is, from >12 mm h−1 over Hainan Island and the South China coastal area decreasing to about 4–8 mm h−1 over northeastern China. They also decrease westward, from 10 to 12 mm h−1 over the North China Plain to 2–4 mm h−1 at the northeastern edge of the Tibetan Plateau. With these thresholds, about 96.5% stations (1012 out of 1049) have at least one TC-EXHP occurring during the 1975–2018 warm seasons with an average frequency of 1.95 yr−1 per station. The TC-induced EXHP is extensively distributed over eastern China, from the coastline extending westward to the southeastern edge of the Tibetan Plateau and northward to northeastern China (Fig. 3b) with a sharp southeastward gradient. The highest frequencies (about 8–10 yr−1) are along the coastline of southeastern China, which decrease sharply to about 1–2 yr−1 over the northwestern inland regions. The spatial distribution of the ratio of the TC-EXHP frequency to the total EXHP frequency (Fig. 3c) is similar to that of the TC-induced EXHP frequency (Fig. 3b). The TC-EXHP contributes about 30%–40% to the total EXHP along the southeastern coastline, but less than 5% over the mountains to the west, generally consistent with the results of Luo et al. (2016) for the years of 1981–2015 (see Fig. 11 therein).
(a) The 95th percentile of hourly precipitation rates (≥0.1 mm h−1) during the 1975–2004 warm seasons, (b) the occurrence frequency (yr−1) of TC-induced EXHP during 1975–2018 warm seasons, and (c) the fractional contribution (%) of the TC-induced EXHP to total EXHP during the 1975–2018 warm seasons. Gray shadings represent topography.
Citation: Journal of Climate 35, 22; 10.1175/JCLI-D-21-0736.1
There are 55, 143, and 356 high-, mid-, and low-EXHP TCs accounting for 9.9%, 25.8%, and 64.3% of all the TCs, respectively (Table 1). Despite the small number of high-EXHP TCs, they contribute 36.0% of the TC-EXHP to total, more than the low-EXHP TCs (22.6%) and close to the mid-EXHP TCs (41.4%). The spatial distribution of TC-EXHP frequency of each group (Figs. 4a–c) resembles, to some extent, that of all TC-EXHP with the highest frequencies along the coastline of southeastern China (Fig. 3b). However, some differences among the groups are noticeable. The area of high frequency (>10 yr−1) produced by the low-EXHP TCs is mainly located over southern China such as Guangdong, Guangxi province, and Hainan Island (Fig. 4a), while the largest frequency produced by the high-EXHP TCs is mainly over southeastern China such as Fujian and Zhejiang Provinces (Fig. 4c), with that of the mid-EXHP TCs in between (Fig. 4b). This difference is more clearly shown in their contributions to total TC-EXHP frequency at the stations (Figs. 4d–f). Compared with the largest contribution occurred in the southern and southwestern area over China in the low-EXHP (Fig. 4d), the most prominent feature with fraction values over 70% (red and purple dots) in high-EXHP occurred over northern China and the Northeast China Plain (Fig. 4f). One reason for this is closely related to the more northwestward tracks of the high-EXHP TCs than those of the mid- and low-EXHP TCs. Figure 5 shows tracks of all sample TCs over China during the 1975–2018 warm seasons. The red lines represent tracks reaching north to at least 28°N latitude (i.e., northward turning TCs) and the blue lines represent tracks of the other westward moving TCs. All of the northward tracks in the high-EXHP TCs move over the inland areas (Fig. 5c), while only a few tracks in the low-EXHP counterparts reach the inland areas (Fig. 5a). The tracks in the high-EXHP group can arrive farther west and north compared to those in the low-EXHP group. This can be seen in Figs. 6a and 6b, in which the westward movement of the high-EXHP TCs can reach 22°–28°N, while tracks of the low-EXHP TCs are mostly situated south of 23°N latitude (Fig. 6b). Meanwhile, the average minimum longitude of the northward turning TCs in the high-EXHP group is about 117°E, while it is about 124°E in the low-EXHP TCs (Fig. 6a); the difference significance between the two subgroups is significant at over a 99% confidence level.
(a)–(c) The TC-induced EXHP frequencies (yr−1) in the low-, mid-, and high-EXHP TC groups, respectively, and (d)–(f) their corresponding fractions to total TC-induced EXHP frequency during the 1975–2018 warm seasons. Gray shadings denote topography.
Citation: Journal of Climate 35, 22; 10.1175/JCLI-D-21-0736.1
TC tracks for the (a) low-, (b) mid-, and (c) high-EXHP TCs, with blue lines representing the westward moving TCs and red lines representing the northward turning TCs, respectively. Dots on each track denote positions of each TC’s center when the TC produces EXHP during its impact periods.
Citation: Journal of Climate 35, 22; 10.1175/JCLI-D-21-0736.1
Kernel density estimation of TC properties for the low-, mid-, and high-EXHP TCs during their impact periods: (a) the westernmost longitude of the northward turning TCs, (b) the northernmost latitude of the westward moving TCs, (c) the duration (h), (d) the moving speed (km h−1), (e) the minimum sea level pressure (SLP; hPa), and (f) the maximum sustained wind speed (m s−1). The box shows the upper extreme, 75th percentile, median, 25th percentile, and lower extreme in each. The red dot in box represents the mean value, and the gray shading areas represent the probability of samples. The gray area exceeding the upper/lower extremes represents the extreme outliers.
Citation: Journal of Climate 35, 22; 10.1175/JCLI-D-21-0736.1
In addition to the different distribution of TC tracks, the duration, the moving speed, and the peak intensity (i.e., Pmin and Vmax during the impact period) of TCs are also compared among the three TC groups (Figs. 6c–f). Results suggest that the duration differs significantly between each pair of TC groups, with the average duration about 136 h in high-EXHP and only about 57 h in low-EXHP. This prominent difference between them suggests that the length of the TC impact period is one of the key reasons for the high frequency produced by the high-EXHP TCs. Moreover, the intensity in high-EXHP TCs is apparently stronger than that in low-EXHP TCs, with the difference significant over 99% confidence level. Previous studies have shown that stronger TCs can produce more average total rainfall, larger average rain areas, or higher average rain rates (Jiang 2012; Yu et al. 2017; Liu et al. 2019). Note that the moving speeds of TCs during their impact periods show no obvious difference among the three groups (Fig. 6d), meaning that the moving speed of TCs has only a slight effect on the TC intensity and TC-induced EXHP.
4. Trends in TC-induced EXHP
This section presents the trends of the EXHP-producing TCs and the TC-induced EXHP during 1975–2018 over China. As shown in Fig. 7, the number of the EXHP-producing TCs exhibits a downward trend of −0.033 yr−1 (Fig. 7a). Among these three groups, the low-EXHP TCs similarly show a significant downward trend of −0.0785 yr−1 (Fig. 7b), which is statistically significant at over a 95% confidence level. In contrast, both the mid- and high-EXHP TCs increase during 1975–2018 (Figs. 7c,d), where the latter passes the 95% confidence level. Thus, the downward trend of the total number of TCs is contributed mostly by the decreasing number of low-EXHP TCs.
Time series and linear trends of the frequency of EXHP-producing TCs influencing China in the warm seasons during 1975–2018: (a) all TC samples and (b) low-, (c) mid-, and (d) high-EXHP TCs. The p value indicates the statistical significance at the 95% confidence level.
Citation: Journal of Climate 35, 22; 10.1175/JCLI-D-21-0736.1
The total frequency of TC-induced EXHP shows a significant upward trend of 17.17 yr−1 (Fig. 8a), which is statistically significant over 95% confidence level. The EXHP frequency from the mid- and high-EXHP TCs consistently increases during 1975–2018 (Figs. 8c,d), with the latter passing the 95% confidence level. In contrast, a negative trend is shown for the low-EXHP TC group (−5.16 yr−1; Fig. 8b), which is significant over the 95% confidence level. These results suggest that despite the decreasing in TC number, the TC-induced EXHP over China has increased during 1975–2018, mainly due to more EXHP produced by the high-EXHP TCs. This is contributed by the significant increase in high-EXHP TCs, as the two are very highly correlated with a correlation coefficient of 0.973.
As in Fig. 7, but for the frequency of TC-induced EXHP.
Citation: Journal of Climate 35, 22; 10.1175/JCLI-D-21-0736.1
We further examine the spatial distribution of the trends of annual total TC-induced EXHP amount for different groups with the results shown in Fig. 9, excluding stations with less than 25 TC-EXHP. The annual total amount of TC-EXHP for each station is calculated as the accumulated EXHP amount in every year. Black circles indicate stations that pass the M-K test at 95% confidence level. The stations with significant increase trends are mostly located over the coastal areas of central eastern China and the Yangtze River basin, and some are scattered over southern China (Fig. 9a). This increasing trend is consistent with the results from Ying et al. (2011) and some other numerical simulations (e.g., Gualdi et al. 2008). Such increasing trends are mainly contributed by the high-EXHP TCs, as suggested by their similar distributions especially over the eastern area of China (Fig. 9d). Comparing with other groups, the region with significant increase of TC-EXHP amount in high-group is located farther north, which is consistent with the northwestward movement of these high-EXHP TCs (Fig. 5c). On the other hand, the TC-induced EXHP amounts from the low-EXHP TCs have slight increasing trends over the coastal area of eastern China, and significant decreasing trends over South China including Hainan Island (Fig. 9b), partially cancelling out the positive EXHP trends of the high-EXHP TCs there. Such decreasing trends of TC precipitation over southern China and the increasing trends over the central eastern China are largely consistent with the previous finding (e.g., Liu et al. 2020) and are, to a great extent, attributed to the strengthening of the western North Pacific subtropical high (WNPSH) (Wu et al. 2005; Fu et al. 2016; Zhao et al. 2020), which is discussed in detail in the following section.
Trends of the annual total TC-induced EXHP amount [mm (10 yr)−1] during the 1975–2018 warm seasons for (a) all TC samples and for (b) low-, (c) mid-, and (d) high-EXHP TCs. Black circles indicate the statistical significance at the 95% confidence level.
Citation: Journal of Climate 35, 22; 10.1175/JCLI-D-21-0736.1
5. Analysis of the related large-scale environmental conditions
To explore the possible mechanisms responsible for the different characteristics between the different EXHP-producing TC groups, we further analyze the large-scale environmental fields with respect to three groups by composite analysis, corresponding to the low-, mid-, and high-EXHP TC groups (Fig. 10). For a given group and field, the composite field is constructed by taking the average for all TCs over their whole lifetime. Note that the feature of the large-scale pattern in the midgroup is in between the low- and high-EXHP TC groups, so the figure of the mid-EXHP group is omitted here. The vertical wind shear is often considered as a key factor for the TC intensity change (e.g., Wang and Wu 2004; Wong and Chan 2004; Wang et al. 2015) and thus the deep-layer vertical wind shear between 850 and 200 hPa is compared between the high- and low-EXHP groups (shaded in Figs. 10a,b). The strong vertical wind shear mainly takes place over the northeastern area of China (about north of 40°N), which is largely due to the high-level jet stream. In the low-EXHP TC group, the vertical wind shear is stronger over the North China Plain, and is located farther south, compared with that in the high-EXHP group. The weaker vertical wind shear is favorable for TC intensification over the eastern area, especially over North China Plain, and for TCs to sustain after landfall, thus contributing to the increase in the length of TC impact period and TC intensity over the eastern area and North China Plain in the high-EXHP group (Fig. 6). The upper troposphere shows a remarkable positive divergence in high-EXHP over the eastern coastal area of China (Fig. 10a, black lines), which is also conducive to the maintenance and enhancement of TCs in the high-EXHP group. The importance and influence mechanism of upper-level divergence have been discussed in many previous studies (e.g., Park et al. 2011; Liu et al. 2020). In contrast, the large positive divergence in low-EXHP is mainly located over the Korean Peninsula and the northwest Pacific Ocean (Fig. 10b).
The composite environmental fields in the (left) high-EXHP and (right) low-EXHP TC groups during the 1979–2018 warm seasons: (a),(b) divergence (black lines; 10−6 s−1) at 200 hPa and vertical wind shear between 850 and 200 hPa (shading; m s−1); (c),(d) geopotential height (green lines; gpm), horizontal wind (a full wind bar is 2 m s−1) at 500 hPa, and vertically integrated water vapor content from the surface to 500 hPa (shading; mm). The wind barbs in bold indicate a significant difference over the 95% confidence level.
Citation: Journal of Climate 35, 22; 10.1175/JCLI-D-21-0736.1
Previous research (e.g., Wu et al. 2005; Li et al. 2017; Liu et al. 2020) has indicated that the TC movement is primarily determined by large-scale steering airflow. Thus, WNPSH (5880 gpm at 500 hPa) and the wind barbs at 500 hPa in the high- and low-EXHP groups are shown in Figs. 10c and 10d, respectively. The wind barbs in bold indicate significant differences between the composite wind and the climatological mean wind field, with the statistically significance over the 95% confidence level. The WNPSH in high-EXHP TCs is apparently stronger than that in low-EXHP ones, extending more westward with the westernmost point reaching about 128°E. There are easterly and southerly steering airflows over the coastal area of eastern China (at about 25°–35°N and 120°–125°E), conducive to the prevailing track of landfalling TCs moving westward and northward (Figs. 6a,b) in the high-EXHP group, thus contributing to the increasing trend in the TC-induced EXHP amount over central eastern China (Fig. 9d). In contrast, the WNPSH in low-EXHP shrinks eastward with the westernmost point at about 135°E. There are westerly airflows over the eastern and southeastern area of mainland China (at about 20°–30°N and 115°–125°E), which prevents the westward moving of TCs, and contribute to the decreasing trend over southern China (Fig. 9b).
In addition, the increase of TC-EXHP in the high group is greatly attributed by the sufficient water vapor supply. The vertically integrated water vapor between the surface and 500 hPa is shown in Figs. 10c and 10d for the high- and low-EXHP groups, respectively. In the high-EXHP group, the high integrated water vapor content is mainly centered along the eastern coastline of China. There is obviously stronger convergence of water vapor, with plenty of moisture transported by the southeasterly and southwesterly airflows originating in tropical oceans (Fig. 10c), which is conducive to the occurrence of TC-induced EXHP over eastern China. However, the integrated water vapor content in the low-EXHP group has high values primarily over East China Sea with a smaller area of high content (>55 mm). The smaller amount of moisture could be attributed to the drier westerly airflows from southern China toward the East China Sea. Therefore, both the location and strength of water vapor supply impact the frequency of the TC-induced EXHP over the mainland of China.
The above analysis shows that the steering airflow dominated by the WNPSH is a dominant factor responsible for the prevailing track shift of TCs. Therefore, we further analyze the time series and trends of the westernmost point of the WNPSH (Fig. 11) to examine the long-term variation of WNPSH. The time series of the westernmost longitude of WNPSH shows a significant deceasing trend of −0.27° yr−1 passing the 90% confidence level (Fig. 11a) during 1979–2018; that is, the westernmost point of WNPSH extended westward and WNPSH became enhanced in recent decades. This is consistent with the results in previous studies (e.g., Wu et al. 2005; Sui et al. 2007; Zhou et al. 2009a). Meanwhile, there is an increasing linear trend in the westernmost latitude of WNPSH, meaning the westernmost point of WNPSH has shifted northward as well. The westward and northward movement of WNPSH is conducive to the northward shift of TC tracks, thus contributing to the high frequency of TC-induced EXHP over the eastern area of mainland China. As for the reason for the enhancement of WNPSH, previous studies have been carried out. For example, Zhou et al. (2009a) suggested that the stronger and the westward extension of the WNPSH since the late 1970s was a result of the negative heating in the central and eastern tropical Pacific and enhanced convective heating in the equatorial Indian Ocean and Maritime Continent. However, these arguments were challenged by other studies (e.g., He et al. 2015; Wu and Wang 2015). These more recent studies show that this decadal intensification of WNPSH cannot be observed when measuring the WNPSH using dynamic factors such as vorticity, and the so-called decadal westward extension of the WNPSH could be a manifestation of global warming.
Time series and trends of the (a) longitude and (b) latitude of the westernmost point of WNPSH (5880 gpm at 500 hPa) during the 1979–2018 warm seasons.
Citation: Journal of Climate 35, 22; 10.1175/JCLI-D-21-0736.1
In addition to the enhanced WNPSH, many other large-scale environmental factors and their corresponding trends are also conducive to the intensified TC precipitation, thus contributing to the increasing TC-induced EXHP. Liu and Wang (2020) have illustrated that the increasing trend of TC precipitation over China is largely contributed by the more moisture supplied in low-level atmosphere, the increase in the land surface soil moisture, and the near-surface temperature over southeastern and eastern China, thus leading to the increase in TC precipitation in recent decades. Meanwhile, both the landfall intensity (Mei and Xie 2016) and duration after landfall (Liu et al. 2020) of TCs increased noticeably in recent decades, due to the increase in the SST along the coastal oceans and the decrease in low-level vertical wind shear over China, which is conducive to increasing precipitation of TCs, finally resulting in the increase in TC-induced EXHP.
6. Summary and conclusions
This paper analyzes the spatiotemporal distributions and the trend of TC-induced EXHP in the warm season (May–September) during 1975–2018 over mainland China and Hainan Island by using a high-quality gauge-based hourly precipitation dataset. According to the amount of EXHP (defined by the 95th percentile) over China produced by each TC, all TCs are divided into three groups: low-, mid-, and high-EXHP TCs. Although the proportion of high TCs is the lowest (only accounting for about 10%) of all sample TCs, the contribution of high-EXHP to total TC-EXHP is relatively large (about 36%).
The TC-induced EXHP frequency and its proportion to the total EXHP frequency decrease rapidly from the southeast coast to the northwest inland areas. Low-EXHP TCs make a greater contribution to the total TC-EXHP frequency over southwestern and southern coastal areas of China (accounting for about 30%), while high-EXHP TCs make a greater contribution over the eastern and northeastern China (accounting for about 70%). One reason for this is closely related to the more northwestward tracks of the high-EXHP TCs than those of the low-EXHP TCs. Moreover, the length of the impact period and the intensity of TCs differ significantly between each pair of TC groups. A longer impact period and stronger intensity of TCs can contribute to the higher frequency and higher precipitation rate, thus resulting in the significant differences of TC-EXHP among the three groups.
During the study period, despite the total frequency of EXHP-producing TCs showing a decreasing trend, which is largely contributed to by the decrease in frequency of low-group TCs, the total frequency of TC-induced EXHP shows a significant increasing trend during 1975–2018, which is mainly due to the increase in high-EXHP TCs. The spatial distribution exhibits that the stations with a significant increase in TC-induced EXHP amount are mainly located over the eastern coastal areas of China and Yangtze River Basin. Such increasing trends are mainly contributed by the high-EXHP TCs, as suggested by their similar distributions especially over the eastern mainland of China. In contrast, the EXHP amount of low-EXHP TCs shows significant decreasing trend over southern China, and slight increasing trend over eastern China.
To explore the possible mechanisms responsible for the different characteristics in the EXHP-producing TC groups, we further analyze the large-scale environmental conditions with respect to three groups by composite analysis. Apparently different distributions of large-scale environment are found between the high- and low-EXHP groups. The cooperation of large-scale environmental fields between high and low levels provides favorable conditions for intensification of TCs and enhancement of TC-induced precipitation in the high-EXHP group, including weaker vertical wind shear, stronger positive divergence in high levels, more sufficient water vapor, and more conducive steering airflow over the eastern area of mainland China. Moreover, the westward and northward shift of WNPSH during 1979–2018 is conducive to the northward shift of prevailing TCs track, thus contributing to the high frequency of TC-induced EXHP over the eastern and northeastern area of mainland China.
Note that this study considered TCs containing extratropical transition processes, including all cases with extratropical transition in the best track TC dataset. Some previous studies have discussed the influence of TC extratropical transition on the change of TC intensity, TC precipitation, or TC track (e.g., Klein et al. 2000; Ritchie and Elsberry 2001; Jones et al. 2003; Anwender et al. 2008). Therefore, TCs after extratropical transition may have certain impact on the distribution of the TC-EXHP frequency over the mainland, which can be examined separately in the future. Moreover, the spatial distribution trend of TC-induced EXHP amount could be partly contributed by the decadal/interdecadal variations, which needs further investigation. Nevertheless, results from this study imply an increasing stress of potential landfalling TC-induced extreme hourly precipitation in the populated southeastern and eastern coastal regions of mainland China if the trend continues in the near future.
Acknowledgments.
This study was supported by the National Natural Science Foundation of China (42030610, 42175011).
Data availability statement.
The hourly precipitation data are available at the National Meteorological Information Center (NMIC) of the China Meteorological Administration (http://data.cma.cn/en/?r=data/detail&dataCode=A.0012.0001). The TC best track data were obtained from the Shanghai Typhoon Institute of China Meteorological Administration (STI/CMA; http://tcdata.typhoon.org.cn). The ECMWF data used in this study were downloaded from http://apps.ecmwf.int/datasets/.
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