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  • View in gallery

    Mean rainfall averaged distribution at different distances from the TC center.

  • View in gallery

    A schematic diagram illustrating how TC rainfall is tracked in the present study. The thick solid line represents the prevailing track of a TC, while the dotted red circles denote its effective influence zone. Rainfall recorded at a station is classified as TC rainfall when the station falls within the effective radius of a TC, as indicated by the darker magenta dots.

  • View in gallery

    Mean (a) TC rainfall (mm month−1), (b) total rainfall (mm month−1), (c) percentage of total rainfall that is TC rainfall (%), and (d) percentage of the variance (%) in the total rainfall explained by TC rainfall during boreal summer (JAS) 1960–2009.

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    (a),(c) The first two leading EOF modes of TC precipitation, (b),(d) the associated standardized PC time series (bars), and (e) the Lepage test statistics of PC1 during boreal summer 1960–2009. Black dots in (a) represent the stations in southeast China and the two boxes represent the southern and eastern regions. The green line in (b) represents the average over the periods 1960–78, 1979–92, and 1993–2009. The dashed lines in (e) denote when the Lepage test exceeds 90% and 95% confidence. A year that exceeds the confidence level indicates that the 10-yr average of PC1 prior to that year is statistically different from the average following that year.

  • View in gallery

    Composites of (a)–(c) TC rainfall anomalies (mm month−1), (d)–(f) total rainfall anomalies (mm month−1), and (g)–(i) the ratio of TC rainfall to total rainfall anomalies (%) during the periods (left) 1960–78, (center) 1979–92, and (right) 1993–2009. Green circles indicate anomalies that are significant at 90% confidence.

  • View in gallery

    Contributions of (left) TC rainfall frequency , (center) TC rainfall intensity , and (right) the nonlinear effect to the overall TC rainfall anomalies during the periods (a)–(c) 1960–78, (d)–(f) 1979–92, and (g)–(i) 1993–2009. Regions enclosed by rectangles represent SSC and ESC.

  • View in gallery

    Contributions of each term to the overall TC rainfall anomalies over SSC and ESC during (a) 1960–78, (b) 1979–92, and (c) 1993–2009. The bars enclosed by rectangles indicate the dominant term.

  • View in gallery

    Composites of (a) TC passage frequency anomalies; the contributions from Eq. (5) of the (b) genesis effect, (c) track effect, and (d) nonlinear effect; and (e) the contributions associated averages over SSC and ESC during 1960–78. Dots in (a) denote the anomalies that are significant at 90% confidence, while the bars enclosed by rectangles in (e) indicate the dominant term.

  • View in gallery

    As in Fig. 8, but for the period 1979–92.

  • View in gallery

    As in Fig. 8, but for the period 1993–2009.

  • View in gallery

    Composites of TC intensity anomalies (kt; 1 kt ≈ 0.51 m s−1) in each 5° × 5° grid during (a) 1960–78, (b) 1979–92, and (c) 1993–2009. Dots indicate that the anomalies are significant at 90% confidence.

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Interdecadal Changes in Summertime Tropical Cyclone Precipitation over Southeast China during 1960–2009

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  • 1 Guy Carpenter Asia-Pacific Climate Impact Center, School of Energy and Environment, City University of Hong Kong, Hong Kong, China
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Abstract

This study examines the changes in tropical cyclone (TC) precipitation and the associated contributing factors over southeast China during 1960–2009. Climatologically, TC rainfall accounts for approximately 20%–40% of the total rainfall over southeast China during boreal summer, and the contribution can even reach 50% for some of the coastal provinces, such as Guangdong, Fujian, Zhejiang, and Hainan. The dominant mode of TC rainfall reveals a dipole pattern over southern southeast China (SSC) and eastern southeast China (ESC), and the associated principal component time series exhibits remarkable interdecadal variations, with two potential change points being identified in the late 1970s and early 1990s. These interdecadal shifts in TC rainfall are also found to be synchronous with two regime shifts in total rainfall, and they can account for more than 40% of the total rainfall anomalies over the coastal regions of southeast China.

To discover the dominant factors responsible for the interdecadal variations, the overall TC rainfall anomalies are broken down into three different components (rainfall frequency, rainfall intensity, and nonlinear terms) based on a new empirical statistical approach. It is found that the interdecadal variation in TC precipitation over SSC is controlled predominantly by changes in TC rainfall intensity as well as TC rainfall frequency, while that over ESC depends mainly on the intensity and the nonlinear terms. Further examination of the TC passage frequency (TPF) suggests that the significant reduction in TPF and TC rainfall frequency over SSC during 1979–92 is associated mainly with suppressed TC genesis (negative genesis effect), while the increase in TPF and TC rainfall frequency during 1993–2009 can be attributed primarily to the enhanced passage probability (positive track effect) over SSC. Meanwhile, variations in TC rainfall intensity seem to be unrelated to the TC’s own intensity change.

Corresponding author address: Dr. Wen Zhou, Guy Carpenter Asia-Pacific Climate Impact Center, School of Energy and Environment, City University of Hong Kong, Hong Kong, China. E-mail: wenzhou@cityu.edu.hk

Abstract

This study examines the changes in tropical cyclone (TC) precipitation and the associated contributing factors over southeast China during 1960–2009. Climatologically, TC rainfall accounts for approximately 20%–40% of the total rainfall over southeast China during boreal summer, and the contribution can even reach 50% for some of the coastal provinces, such as Guangdong, Fujian, Zhejiang, and Hainan. The dominant mode of TC rainfall reveals a dipole pattern over southern southeast China (SSC) and eastern southeast China (ESC), and the associated principal component time series exhibits remarkable interdecadal variations, with two potential change points being identified in the late 1970s and early 1990s. These interdecadal shifts in TC rainfall are also found to be synchronous with two regime shifts in total rainfall, and they can account for more than 40% of the total rainfall anomalies over the coastal regions of southeast China.

To discover the dominant factors responsible for the interdecadal variations, the overall TC rainfall anomalies are broken down into three different components (rainfall frequency, rainfall intensity, and nonlinear terms) based on a new empirical statistical approach. It is found that the interdecadal variation in TC precipitation over SSC is controlled predominantly by changes in TC rainfall intensity as well as TC rainfall frequency, while that over ESC depends mainly on the intensity and the nonlinear terms. Further examination of the TC passage frequency (TPF) suggests that the significant reduction in TPF and TC rainfall frequency over SSC during 1979–92 is associated mainly with suppressed TC genesis (negative genesis effect), while the increase in TPF and TC rainfall frequency during 1993–2009 can be attributed primarily to the enhanced passage probability (positive track effect) over SSC. Meanwhile, variations in TC rainfall intensity seem to be unrelated to the TC’s own intensity change.

Corresponding author address: Dr. Wen Zhou, Guy Carpenter Asia-Pacific Climate Impact Center, School of Energy and Environment, City University of Hong Kong, Hong Kong, China. E-mail: wenzhou@cityu.edu.hk

1. Introduction

Understanding and accurately predicting rainfall variability has long been a primary concern of climate research because of its overwhelming impacts on human societies and the natural environment. Heavy rainfall can induce severe flooding and landslides, causing tremendous loss of lives and properties in China every year. During the last few decades, a great deal of effort has been directed toward advancing our understanding of rainfall variability over different parts of China (e.g., Tao 1980; Ding 1992; Huang et al. 1999; Zhou and Chan 2007; Ding et al. 2008, 2009; Gu et al. 2009a,b; Zhou et al. 2009b; Wang et al. 2011; Yan et al. 2011; H. P. Chen et al. 2012; Wang et al. 2012a). At the interdecadal time scale, it was found that the rainfall regime in China has undergone two remarkable shifts in recent decades (Huang et al. 1999; Zhou and Huang 2003; Chan and Zhou 2005; Zhou et al. 2006; Kwon et al. 2007; Ding et al. 2008, 2009; Zhou et al. 2009b; Wu et al. 2010; Liu et al. 2011; Li et al. 2012). The first shift occurred in the late 1970s, with a significant increase in precipitation over the Yangtze River basin and rainfall deficits and prolonged droughts over northern and northeastern China (Huang et al. 1999; Zhou and Huang 2003). Such an interdecadal shift has been proposed to be related to the significant weakening of the East Asian summer monsoon, which suppresses northward moisture transport and convergence and results in moisture supply deficits over northern China (Ding et al. 2008, 2009; Li et al. 2012). Yu et al. (2004) and Yu and Zhou (2007) also suggested that such an interdecadal change in East Asian summer precipitation might be related to the tropospheric cooling, which results in southward shifts in the upper-level westerly jet and the subsequent weakening of the East Asian summer monsoon. The second shift, which is noticeable in the early 1990s, is characterized by a farther southward displacement of the precipitation zone from the Yangtze–Huaihe River valley into southern China, leading to an abrupt increase in south China rainfall, with a magnitude even stronger than that of the first shift (Ding et al. 2008; Wu et al. 2010; Li et al. 2012). Kwon et al. (2007) noticed a significant weakening in the upper-tropospheric westerly jet over northern China and an increase in the number of typhoons passing through southern China during this period. Wu et al. (2010) attributed the second rainfall shift to the enhanced moisture convergence over southern China, which was possibly induced by a pair of anomalous anticyclones over northern China–Mongolia and over the South China Sea–subtropical western North Pacific (WNP) during boreal summer. The development of the northern anticyclonic anomalies was found to be related to an increase in the Tibetan Plateau snow cover in the preceding winter and spring that results in an increase in surface pressure extending northward from the plateau, while the occurrence of the southern anticyclonic anomalies was possibly linked to an increase in sea surface temperature in the equatorial Indian Ocean that results in anomalous descent and low-level anticyclonic anomalies over southern China. Similarly, Li et al. (2012) related the second rainfall shift to the anomalous water vapor transport from both the WNP and northern China. Apart from these, Zhou et al. (2009b) conducted a detailed review on the multidecadal variability of the East Asian summer monsoon and concluded five factors, including the oceanic forcing (Zhou et al. 2008a,b; Li et al. 2010), the Tibetan Plateau forcing (Wang et al. 2008; Wu et al. 2010), the aerosol forcing (Lau et al. 2008a,b), the Pacific decadal oscillation (Chan and Zhou 2005; Zhou et al. 2013; Qian and Zhou 2014), and the internal variability (Ding et al. 2008, 2009), that are important in shaping the multidecadal changes of the East Asian summer monsoon.

While most previous studies have focused on the monsoon–rainfall relationship, another important rainfall component, tropical cyclone (TC)-related precipitation, has received relatively less attention. Being highly energetic tropical systems, TCs can trigger even stronger precipitation along their path, causing severe rainstorms, flooding, landslides, and storm surges over coastal regions. Some recent studies have started to recognize the nonnegligible contribution of TC precipitation during summer (Ren et al. 2006; Lau et al. 2008a,b; Wong et al. 2008; Kubota and Wang 2009; Chen et al. 2010; Chen and Chen 2011; J.-P. Chen et al. 2012; Chang et al. 2012). For example, Rodgers et al. (2000) first estimated monthly TC rainfall using Special Sensor Microwave Imager satellite data and found that about 12% of the summer rainfall over the WNP comes from TCs. Lau et al. (2008b) revealed that TCs are responsible for an increase in extreme rainfall events in both the North Atlantic and the WNP, while Kubota and Wang (2009) showed that TCs contribute substantially to seasonal and interannual rainfall variability over the WNP. Chen et al. (2010) and Chen and Chen (2011) later found that TC rainfall in Taiwan varies inversely with monsoon rainfall and accounts in opposite ways for the overall interannual and interdecadal rainfall variability over Taiwan because of the discrepancy in spatial position of the circulation anomalies that modulate moisture transport and TC activity in Taiwan. Recently, J.-P. Chen et al. (2012) suggested that an increase in south China summer rainfall around 1993 might be associated with a concomitant increase in TCs over the South China Sea. Chang et al. (2012) further emphasized the importance of TC rainfall in shaping the overall trend of rainfall extremes over China.

Yet, compared to the well-documented regime shifts in total rainfall, the interdecadal change in TC rainfall has not been thoroughly examined. Therefore, it is of interest to find out whether TC rainfall over China is subject to similar interdecadal shifts and to discover the contributing factors associated with these shifts. In this study, a new diagnostic approach, which takes into account both rainfall frequency and rainfall intensity, is used to quantify and assess the relative influences of these factors on the overall changes in TC rainfall. The rest of this paper is organized as follows: Section 2 introduces the data and methodology used in this study. Following that, the climatology and the dominant pattern of TC precipitation are presented in section 3. Section 4 investigates the interdecadal variability of TC rainfall and evaluates quantitatively the relative contributions of rainfall frequency, rainfall intensity, and nonlinearity to the overall rainfall changes. Section 5 further examines the influences associated with different TC parameters, and section 6 discusses and summarizes the results.

2. Data and methodology

a. Data

Daily precipitation data from 756 meteorological stations in China, which have been subjected to quality control procedures by the China Meteorological Administration, were used in this study to investigate the interdecadal variability of TC precipitation. Because of the existence of missing data in the 1950s in most parts of China, only the data for the period 1960–2009 were employed. In this study, we focus primarily on boreal summer [July–September (JAS)], during which TCs and synoptic disturbances are active over the WNP (Li 2012; Li et al. 2014). The TC dataset used in this study was acquired from the Joint Typhoon Warning Center (http://jtwccdn.appspot.com/NOOC/nmfc-ph/RSS/jtwc/best_tracks/) at 6-h intervals.

b. TC rainfall estimation

Thus far, TC rainfall has been commonly defined as the recorded rainfall within the effective radius of a TC (Jiang et al. 2008; Lau et al. 2008b; Kubota and Wang 2009; Chen et al. 2010; J.-P. Chen et al. 2012; Dare et al. 2012), yet no consensus has been reached regarding the optimum value of the effective radius, with a value ranging from 250 to 1000 km being defined in previous studies (Table 1). To determine the effective radius of influence, rainfall is averaged at different distances from the TC center, as shown in Fig. 1. It can be observed that the mean rainfall decreases exponentially with increasing distance from the TC center. At a distance of 800 km from the TC center, however, the change in rainfall starts to level off, which suggests that the TC influence is actually limited to this range. The result here is consistent with that of Kubota and Wang (2009), who found a similar change in TC rainfall with different effective radii from the TC center. Therefore, in this study, 800 km is chosen as the effective radius of influence of TCs. Nevertheless, it should be mentioned that the results of this study are generally insensitive to different TC effective radii. In a similar fashion as in previous studies (Lau et al. 2008b; Kubota and Wang 2009; Chen et al. 2010; J.-P. Chen et al. 2012; Dare et al. 2012), TC rainfall is tracked along the individual tracks of TCs. Daily rainfall recorded at a station is classified as TC rainfall when the station falls within the effective radius of a TC (Fig. 2). The monthly TC rainfall can then be obtained by summing the corresponding daily rainfall components. Note that the rainfall events due to remote TCs have not been considered in the present study.

Table 1.

Summary of the effective radius of influence of TCs as defined in previous studies.

Table 1.
Fig. 1.
Fig. 1.

Mean rainfall averaged distribution at different distances from the TC center.

Citation: Journal of Climate 28, 4; 10.1175/JCLI-D-14-00246.1

Fig. 2.
Fig. 2.

A schematic diagram illustrating how TC rainfall is tracked in the present study. The thick solid line represents the prevailing track of a TC, while the dotted red circles denote its effective influence zone. Rainfall recorded at a station is classified as TC rainfall when the station falls within the effective radius of a TC, as indicated by the darker magenta dots.

Citation: Journal of Climate 28, 4; 10.1175/JCLI-D-14-00246.1

c. Diagnosis of TC rainfall

The amount of TC rainfall at a station depends on the combined effects of TC rainfall frequency and TC rainfall intensity. An enhancement in TC rainfall over a region can be caused by either an increase in TC rainfall frequency or a strengthening in TC rainfall intensity. To quantitatively address the relative influences of these two factors on the overall changes in TC rainfall, a new empirical statistical analysis of TC rainfall is carried out. In this method, the climatological TC rainfall at a station for a certain period can be expressed as
e1
where P is the TC precipitation, F is the TC rainfall frequency (total number of TC rainfall days), and I is the TC rainfall intensity (mean TC rainfall amount per number of TC rainfall days). A TC rainfall anomaly, with respect to its climatology, can then be evaluated as
e2
where the prime denotes the corresponding anomaly. Equation (2) consists of three terms, which illustrate different contributions of these factors to the overall changes in rainfall. The first term () denotes the contribution from anomalous TC rainfall frequency to the overall TC rainfall anomaly when the rainfall intensity is kept constant. The second term represents the contribution from anomalous TC rainfall intensity, while the third term is the nonlinear term associated with changes in both the frequency and intensity. The nonlinear term actually arises mathematically as TC precipitation is the product of TC rainfall frequency and TC rainfall intensity. The contribution of the nonlinear term becomes larger when the changes in both the rainfall frequency and rainfall intensity are much larger than their climatological means. In other words, a larger contribution of the nonlinear term to overall TC rainfall anomaly is expected when the mean TC rainfall is small and the TC rainfall frequency and intensity both change substantially during that particular period.

d. Diagnosis of TC passage frequency

To reveal the interdecadal changes in TC activity, TC passage frequency (TPF) is computed by binning the WNP TCs into 5° × 5° grids. Since the passage frequency is affected simultaneously by both the genesis frequency and the preferable track, we also diagnose the associated changes in TPF in terms of these two factors, following Yokoi and Takayabu (2013) and Murakami et al. (2013). The climatological TPF in a specific 5° × 5° grid cell A can be written as
e3
where is the frequency of cyclogenesis in grid cell A0 (calculated by counting the number of TCs formed in grid cell A0); is the probability that a TC formed in grid cell A0 passes through grid cell A (calculated by dividing the number of TCs that pass through grid cell A by the total number of TCs formed in grid cell A0); and C is the domain of integration, which spans the entire WNP. Equation (3) suggests that the TPF for each grid cell is influenced by both the local as well as remote TC genesis and TC track. In this way, TPF in a specific period can be obtained by considering the anomaly from its climatological mean,
e4
Subtracting Eq. (3) from Eq. (4) then gives the TPF anomaly,
e5
Hence, changes in TPF can be attributed to three factors, namely, the genesis effect (first term), the track effect (second term), and the nonlinear effect (third term). By this decomposition, the contribution of each of the terms integrated over the entire domain of the WNP to the local change in TPF can be assessed.

3. Climatology and dominant mode of TC precipitation

a. Climatology of TC precipitation

To start, Figs. 3a and 3b first show the climatology of TC precipitation and the total precipitation during boreal summer, respectively. TC rainfall is confined mainly in southeast China over the lower reaches of the Yangtze River, with most precipitation being along the coastal regions. On the other hand, the total rainfall maximum not only appears in southeast China but also extends northward to the Yangtze River and even to northeastern China and has a much greater magnitude. In general, TC rainfall contributes approximately 20%–40% of the total rainfall over southeast China during boreal summer (Fig. 3c), and the contribution can even reach 50% for some of the coastal stations along Guangdong, Fujian, Zhejiang, and Hainan provinces. Meanwhile, it can also be observed that TC rainfall can explain a considerable portion of the variance in the total rainfall over southeast China (Fig. 3d). The explained variances increase significantly from the inland to more than 50% along the coast, suggesting the nonnegligible role of TCs in controlling the summer rainfall variability. The variations in TC rainfall should therefore also be taken into account when predicting rainfall changes in southeast China.

Fig. 3.
Fig. 3.

Mean (a) TC rainfall (mm month−1), (b) total rainfall (mm month−1), (c) percentage of total rainfall that is TC rainfall (%), and (d) percentage of the variance (%) in the total rainfall explained by TC rainfall during boreal summer (JAS) 1960–2009.

Citation: Journal of Climate 28, 4; 10.1175/JCLI-D-14-00246.1

b. Dominant pattern of TC precipitation

To delineate the dominant spatial and temporal pattern of the TC rainfall, an empirical orthogonal function (EOF) analysis is carried out. Southeast China (16°–37°N, 105°–125°E) is chosen to be the domain for the EOF analysis because most of the TC precipitation and associated variation are concentrated over this region, as discussed previously in section 3a. Figure 4a reveals the two leading EOF modes of the TC rainfall during boreal summer. According to the criterion of North et al. (1982), the first mode explains about 40% of the variance and is well separated from the other modes (the explained variance of the subsequent EOF modes are 11%, 7.8%, and 5.3%, respectively). It is characterized by a prominent dipole pattern with opposite rainfall distribution over southern southeast China (SSC; 18°–28°N, 105°–117°E) and eastern southeast China (ESC; 25°–34°N, 117°–123°E). Further examination of the corresponding principal component (PC) time series reveals that this mode exhibits noticeable interdecadal variation (Fig. 4b). The PC time series changes from slightly positive to negative values after 1978 and tends to shift to positive values again in the early 1990s. In contrast, the second EOF mode, accounting for 11% of the total variance, features variations in TC rainfall mainly in the eastern part (Fig. 4c). The associated PC time series exhibits much clear interannual variation (Fig. 4d), which is out of the scope of the present study and will be considered separately in subsequent works.

Fig. 4.
Fig. 4.

(a),(c) The first two leading EOF modes of TC precipitation, (b),(d) the associated standardized PC time series (bars), and (e) the Lepage test statistics of PC1 during boreal summer 1960–2009. Black dots in (a) represent the stations in southeast China and the two boxes represent the southern and eastern regions. The green line in (b) represents the average over the periods 1960–78, 1979–92, and 1993–2009. The dashed lines in (e) denote when the Lepage test exceeds 90% and 95% confidence. A year that exceeds the confidence level indicates that the 10-yr average of PC1 prior to that year is statistically different from the average following that year.

Citation: Journal of Climate 28, 4; 10.1175/JCLI-D-14-00246.1

To further verify the interdecadal change in association with the first mode, the Lepage test (Lepage 1971) is performed on the corresponding PC time series. It is a nonparametric, two-sample test for location and dispersion and for significant difference between two samples, even if the parent distribution is not known. Following previous studies (Yonetani and McCabe 1994; Liu et al. 2011; Wang et al. 2012b), the Lepage statistics are evaluated by comparing data of a time series in the following manner: data n yr prior to a specified year are compared to data n yr after the specified year (n = 10 yr is chosen in the present study in order to investigate the interdecadal change). This test has proven useful in detecting abrupt climate changes (Hirakawa 1974) and has been widely applied in previous studies to identify different kinds of interdecadal shifts, such as changes in summer rainfall (Liu et al. 2011) and summer TC frequency (Wang et al. 2012b). As shown in Fig. 4e, two significant change points can be identified based on the Lepage test, one in the late 1970s and the other in the early 1990s, and these match well with the two regime shifts in total rainfall as shown in previous studies (Huang et al. 1999; Ding et al. 2008; Li et al. 2012). Therefore, in the following sections, the study period is divided into three subperiods (1960–78, 1979–92, and 1993–2009) to further investigate the associated changes in TC rainfall.

4. Interdecadal variability of TC precipitation

a. Interdecadal variability

Section 3 has shown that the dominant mode of TC precipitation is subject to significant interdecadal variability, which is approximately synchronous with the two regime shifts in total rainfall. To further confirm the interdecadal variability and to quantify the contribution of TC rainfall to total rainfall changes, Fig. 5 shows the anomalies of TC rainfall, total rainfall, and the associated percentage contribution during the periods 1960–78, 1979–92, and 1993–2009. During 1960–78, TC rainfall is characterized by a positive EOF1 pattern, with above-normal (below normal) precipitation over SSC (ESC), though the anomalies appear to be insignificant (Fig. 5a). This is followed by a significant reduction (enhancement) in TC precipitation over SSC (ESC) during 1979–92 (Fig. 5b), which resembles that of the negative EOF1 pattern. After that, during 1993–2009, the prevailing rainfall pattern changes again (Fig. 5c), with positive (negative) rainfall anomalies dominating over SSC (ESC). The shifts in the TC rainfall pattern agree well with the corresponding changes in the PC time series (Fig. 4b), suggesting that the interdecadal changes in TC rainfall being identified in section 3b do stand out in nature. It is also worth mentioning that the results here have been tested by reextracting TC rainfall using different effective radii (400 and 600 km), and similar shifts in the rainfall pattern can be observed. Our results here are also consistent with those of J.-P. Chen et al. (2012), who found a similar significant increase in TC rainfall over southern China after the early 1990s.

Fig. 5.
Fig. 5.

Composites of (a)–(c) TC rainfall anomalies (mm month−1), (d)–(f) total rainfall anomalies (mm month−1), and (g)–(i) the ratio of TC rainfall to total rainfall anomalies (%) during the periods (left) 1960–78, (center) 1979–92, and (right) 1993–2009. Green circles indicate anomalies that are significant at 90% confidence.

Citation: Journal of Climate 28, 4; 10.1175/JCLI-D-14-00246.1

On the other hand, changes in total rainfall, as already discussed extensively in many previous studies (Huang et al. 1999; Ding et al. 2008; Wu et al. 2010; Li et al. 2012), are characterized by a southward migration of the major rain belt from northern China to the Yangtze River after 1978 and then to southern China after 1992 (Figs. 5d–f). When considering the TC contribution, we can see that TC precipitation can indeed account for more than 40% of the total rainfall anomalies over the coastal regions of southeast China (Figs. 5g–i). This further highlights the importance of TC rainfall, which should not be neglected when changes in rainfall over southeast China are discussed.

b. Contribution of TC rainfall frequency and intensity to TC rainfall changes

Given evident interdecadal changes in TC rainfall, the next task is to examine the contributions of different related factors responsible for such changes. By breaking down TC rainfall into frequency, intensity, and nonlinear terms according to Eq. (2), the relative contributions of these terms to the overall changes in TC rainfall can be evaluated. Figure 6 shows the interdecadal anomalies of these three contributing terms during the periods 1960–78, 1979–92, and 1993–2009, while Fig. 7 displays the associated averages over SSC and ESC. During 1960–78 (Figs. 6a–c and 7a), positive TC rainfall anomalies over SSC (Fig. 5a) are mainly the result of an increase in TC rainfall intensity as well as TC rainfall frequency, whereas the negative TC rainfall anomalies over ESC (Fig. 5a) are associated largely with a reduction in TC rainfall intensity, which outweighs the secondary important positive nonlinear effect. During 1979–92 (Figs. 6d–f and 7b), the rainfall intensity effect still plays a decisive role in determining the overall changes in TC rainfall. In SSC, the overall reduction in TC rainfall (Fig. 5b) is attributed primarily to the concomitant decrease in TC rainfall intensity during this period. The frequency effect ranks second, and it also contributes substantially to the overall deficits in TC rainfall over SSC. In contrast, an increase in TC rainfall intensity and the positive nonlinear term lead to an overall increase in TC rainfall over ESC. Finally, during 1993–2009 (Figs. 6g–i and 7c), increased TC rainfall frequency is found to be the primary contributor to the overall increase in TC rainfall over SSC. The second largest factor is the intensity term, with a magnitude comparable to that of the frequency term, and this serves as another important source for the positive enhancement in TC rainfall during this period. In contrast, ESC is affected mainly by a reduction in TC rainfall intensity, which overwhelms the increase in TC rainfall frequency and the positive nonlinear effect, resulting in a significant suppression in TC rainfall during this period.

Fig. 6.
Fig. 6.

Contributions of (left) TC rainfall frequency , (center) TC rainfall intensity , and (right) the nonlinear effect to the overall TC rainfall anomalies during the periods (a)–(c) 1960–78, (d)–(f) 1979–92, and (g)–(i) 1993–2009. Regions enclosed by rectangles represent SSC and ESC.

Citation: Journal of Climate 28, 4; 10.1175/JCLI-D-14-00246.1

Fig. 7.
Fig. 7.

Contributions of each term to the overall TC rainfall anomalies over SSC and ESC during (a) 1960–78, (b) 1979–92, and (c) 1993–2009. The bars enclosed by rectangles indicate the dominant term.

Citation: Journal of Climate 28, 4; 10.1175/JCLI-D-14-00246.1

Previous studies (Kwon et al. 2007; J.-P. Chen et al. 2012) have suggested that an increase in TC rainfall around 1993 over southern China is mainly due to an increase in TC rainfall frequency. Our analysis here discovers that, apart from the changes in TC rainfall frequency, variations in TC rainfall intensity are also prominent over SSC and ESC and contribute substantially to the interdecadal TC rainfall anomalies. Overall, it is found that the interdecadal changes in TC rainfall over SSC are controlled predominantly by changes in TC rainfall intensity as well as TC rainfall frequency, while changes over ESC depend mainly on the intensity and the nonlinear effect.

5. Associated changes in TC properties

The previous section has revealed that both TC rainfall intensity and TC rainfall frequency have experienced significant changes and that these contribute jointly to the interdecadal rainfall anomalies over southeast China. Changes in TC rainfall intensity and TC rainfall frequency may, however, be rooted in corresponding changes in different TC properties in the WNP. As an extension, variations in TPF and intensity in the WNP will also be examined in this section to investigate their possible effects on TC rainfall.

a. TC passage frequency

Figures 810 show the anomalies of TPF together with the contributions of the genesis, track, and nonlinear terms during the periods 1960–78, 1979–92, and 1993–2009, respectively. During 1960–78, changes in TPF are insignificant over both SSC and ESC (Fig. 8a). This is consistent with our results in section 4 (Fig. 7a), which reveals that the TC rainfall anomalies during this period are induced mainly by changes in TC rainfall intensity rather than TC rainfall frequency. Following Yokoi and Takayabu (2013) and Murakami et al. (2013), decomposition of TPF further shows that the positive genesis and track effects during this period tend to be offset by the dominating negative nonlinear effect, giving rise to the insignificant change in TPF over both SSC and ESC (Figs. 8b–e). As for 1979–92, changes in TPF become more pronounced, with significant negative anomalies over SSC (Fig. 9a). The decrease in basinwide TC genesis over the WNP is found to be the primary contributor for such a reduction, which, together with the negative nonlinear effect, gives rise to the local negative TPF over SSC (Figs. 9b–e). The inactive cyclogenesis during this period has also been noted previously by Chan and Liu (2004) and Liu and Chan (2013). The suppressed TPF over SSC in turn results in reduced TC rainfall frequency, partly contributing to the overall suppressed TC rainfall during this period (Fig. 7b). Compared with SSC, the reduction in TPF over ESC is relatively smaller (Fig. 9), and the overall positive TC rainfall is caused primarily by the enhanced TC rainfall intensity during this period (Fig. 7b). Finally, after 1992, TPF shows a prominent increase, especially in SSC (Fig. 10a). During this period, the positive track effect dominates (Fig. 10c), indicating that there is an enhanced probability for WNP TCs to pass through SSC. The enhanced track effect outweighs the weaker genesis and nonlinear terms and is the major reason for the increase in TPF and hence TC rainfall frequency over SSC. Compared to SSC, however, the increase in TPF appears to be weaker in ESC (Fig. 10a) because of the cancelation by the more negative nonlinear term (Fig. 10e). This also explains why the change in TC rainfall frequency in ESC is smaller during this period compared to that in SSC (Fig. 7c).

Fig. 8.
Fig. 8.

Composites of (a) TC passage frequency anomalies; the contributions from Eq. (5) of the (b) genesis effect, (c) track effect, and (d) nonlinear effect; and (e) the contributions associated averages over SSC and ESC during 1960–78. Dots in (a) denote the anomalies that are significant at 90% confidence, while the bars enclosed by rectangles in (e) indicate the dominant term.

Citation: Journal of Climate 28, 4; 10.1175/JCLI-D-14-00246.1

Fig. 9.
Fig. 9.

As in Fig. 8, but for the period 1979–92.

Citation: Journal of Climate 28, 4; 10.1175/JCLI-D-14-00246.1

Fig. 10.
Fig. 10.

As in Fig. 8, but for the period 1993–2009.

Citation: Journal of Climate 28, 4; 10.1175/JCLI-D-14-00246.1

To sum up, the significant reduction in TPF and also TC rainfall frequency over SSC during 1979–92 is associated mainly with suppressed TC genesis (negative genesis effect), while the increase in TPF and TC rainfall frequency during 1993–2009 can be attributed primarily to the enhanced passage probability (positive track effect) over SSC. The inactive TC period from the late 1970s to the early 1990s has also been noted previously by Liu and Chan (2013), who suggested that the increase in vertical wind shear is the major cause for the low genesis frequency during this period. On the other hand, Ho et al. (2004) and Wu et al. (2005) reported that the prevailing TC tracks have tended to shift westward to southeast China in recent decades because of changes in the large-scale steering flow in association with the strengthening of the WNP subtropical high. Through a series of idealized numerical experiments, Zhou et al. (2009a) also found that the significant change in the WNP subtropical high could be partly attributed to the Indian Ocean–western Pacific warming. Such a warming enhances the convective heating over the Indian Ocean and Maritime Continent and forces an ENSO/Gill-type response that favors the westward extension of the WNP subtropical high, which might help explain the increase in TC passage probability over southeast China during 1993–2009.

b. TC intensity

Apart from TPF, it is also of interest to further examine whether the TC rainfall intensity is related to the TC’s own intensity change. Figure 11 shows the TC intensity anomalies in each 5° × 5° grid during 1960–78, 1979–92, and 1993–2009, respectively. As can be seen, changes in TC intensity are confined mainly in the region southeast of Japan, while changes over southeast China are not obvious. This suggests that the significant changes in TC rainfall intensity in southeast China as noted in section 4 seem to be unrelated to the TC’s own intensity. Besides, examinations of the percentage distribution of TC intensities over SSC and ESC also fail to reveal a significant relationship with TC rainfall intensity (not shown). The results here are similar to that of Chen et al. (2013), who found that the rainfall intensity associated with TC events in Taiwan is not determined by TC intensity but is modulated by the large-scale environmental flows associated with the 30–60-day and 10–20-day intraseasonal oscillation (Zhou and Chan 2005; Li and Zhou 2013a,b). It is possible that the interactions with the background monsoon circulations may play a role in modulating the TC rainfall intensity during these three periods. Further investigations are currently underway to explore in more detail the regulating processes associated with changes in the mean intensity of TC rainfall, and the results will be reported in subsequent studies.

Fig. 11.
Fig. 11.

Composites of TC intensity anomalies (kt; 1 kt ≈ 0.51 m s−1) in each 5° × 5° grid during (a) 1960–78, (b) 1979–92, and (c) 1993–2009. Dots indicate that the anomalies are significant at 90% confidence.

Citation: Journal of Climate 28, 4; 10.1175/JCLI-D-14-00246.1

6. Discussion and summary

This study examines changes in TC precipitation and the associated contributing factors over southeast China. Climatologically, TC rainfall contributes 20%–40% of the total rainfall over southeast China during boreal summer, and the contribution can even reach 50% for some of the coastal provinces, such as Guangdong, Fujian, Zhejiang, and Hainan. The dominant mode of TC rainfall is characterized by a dipole pattern over SSC and ESC, and the associated PC time series exhibits remarkable interdecadal variations, with two potential change points being identified in the late 1970s and early 1990s. The interdecadal shifts in TC rainfall occur concurrently with the two regime shifts in total rainfall and can account for more than 40% of the total rainfall anomalies over the coastal regions of southeast China.

To disentangle the factors responsible for the changes in interdecadal rainfall, the overall TC rainfall anomalies are broken down into three different components (rainfall frequency, rainfall intensity, and nonlinear terms) based on a new empirical statistical approach to assess the relative importance of these factors in inducing the changes in rainfall. It is found that the interdecadal variation in TC precipitation over SSC is controlled predominantly by changes in TC rainfall intensity as well as TC rainfall frequency, while that over ESC stems mainly from the alterations of the intensity and nonlinear terms. Further examinations of the TPF suggest that the significant reduction in TPF and TC rainfall frequency over SSC during 1979–92 is associated mainly with suppressed TC genesis (negative genesis effect), while the increase in TPF and TC rainfall frequency during 1993–2009 can be attributed primarily to the enhanced passage probability (positive track effect) over SSC. On the other hand, variations in TC rainfall intensity seem to be independent of the TC’s own intensity change.

While this study has shown that both the frequency and intensity of TC rainfall have undergone significant interdecadal changes, the exact physical mechanisms governing such changes remain uncertain. As shown in section 5, the changes in TC rainfall frequency are closely linked to the interdecadal variations in TPF. Yet the factors responsible for modifying the latter are still the subject of vigorous debate. Up to now, several external forcings have been proposed to be associated with the interdecadal changes in TC activity in the WNP and the South China Sea, including the Pacific decadal oscillation (Goh and Chan 2009; Wang et al. 2010; Liu and Chan 2013), the North Pacific Gyre Oscillation (Zhang et al. 2013), the Indian Ocean sea surface temperature (Wang and Huang 2013), and the zonal sea surface temperature gradient (Li and Zhou 2014). How these factors influence the changes in TC precipitation is an interesting topic that deserves further investigation. As for change in TC rainfall intensity, preliminary results suggest that it is independent of the TC’s own intensity change. As suggested by Wu et al. (2011) and Chen et al. (2013), TC rainfall intensity may be enhanced through interaction with the background monsoon circulations, which are also subjected to large interdecadal variability as discussed previously in the introduction (Huang et al. 1999; Kwon et al. 2007; Zhou et al. 2008a,b; Ding et al. 2008, 2009; Zhou et al. 2009b; Li et al. 2010). Zhou et al. (2009b) summarized five factors, including the oceanic forcing (Zhou et al. 2008a,b; Li et al. 2010), the Tibetan Plateau forcing (Wang et al. 2008; Wu et al. 2010), the aerosol forcing (Lau et al. 2008a,b), the Pacific decadal oscillation (Chan and Zhou 2005; Zhou et al. 2013; Qian and Zhou 2014), and the internal variability (Ding et al. 2008, 2009), which are important for governing the multidecadal changes of the East Asian summer monsoon. It is possible that the changes of these factors may also play some roles in modulating the TC rainfall intensity through affecting the background monsoon flow and moisture supply. This modulation process, which is certain to be complex and to involve interactions of systems at different time scales, will be the subject of our subsequent work.

Acknowledgments

This research is supported by Nature Science Foundation of China grants (41175079 and 41375096) and a CityU Strategic Research Grant 7004164. The authors would like to sincerely thank the three anonymous reviewers and the editor for the constructive comments and suggestions, which greatly improved this manuscript.

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