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    (a) The geographical location of Hainan, (b) the location of 18 major meteorological stations and the topography (m), and (c) area-mean climatological monthly precipitation (mm day−1) of Hainan (bar) and south China (dashed line) and the interannual standard deviation (mm day−1) of monthly precipitation of Hainan (solid line). The reference period for precipitation climatology is 1965–2010.

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    (a) The leading EOF mode of interannual variations (shaded) and standard deviation (solid contours, mm day−1), (b) the climatological mean of total (shaded, mm day−1) and TC-related (solid contours, mm day−1) precipitation, (c) the time series of the first principal component (dashed line) and area-mean precipitation anomalies in Hainan (solid line, mm day−1), and (d) percentage of area-mean precipitation anomalies in Hainan. The dashed lines in (a) and (b) indicate the topography at altitudes of 400 and 600 m. A threshold of 40% is used to define the wet (gray bar) and dry (hatched bar) years in (d). The precipitation refers to September–October mean.

  • View in gallery

    (a),(b) Composite anomalies of 850-hPa horizontal wind fields (m s−1); (c),(d) vertically integrated moisture flux (500 kg m s−1); (e),(f) 850-hPa velocity potential (contour, interval: 0.3 × 10−6 m2 s−1) with divergent winds (2 m s−1; vectors); and (g),(h) equatorial Walker circulation (streamline) averaged over 5°S–5°N in the (left) WYs and (right) DYs. Shaded areas are statistically significant at the 95% confidence level. The magnitudes of vectors in (a),(b) smaller than 0.5 m s−1 and in (c),(d) smaller than 40 kg m s−1 are omitted.

  • View in gallery

    (a),(b) Composite anomalies of SST (contour interval 0.2°C) in the WYs and DYs, respectively. Light (dark) gray areas indicate significance exceeding the 90% (95%) confidence level. (c),(d) The time series of composite anomalies of SST (°C) in the ECP (open circle) and MC (solid circle) from January to December in the WYs and DYs, respectively. Dashed line denotes the 95% confidence level. The ECP and MC regions are indicated by boxes in (a) and (b).

  • View in gallery

    The tracks of TCs impacting Hainan in each (a) WY and (b) DY. Here TD, TS, TY, and STY denote tropical depression, tropical storm, typhoon, and supertyphoon, respectively, which are coded with different colors (TD, green; TS, yellow; and TY and STY, red). The black box enclosing Hainan represents the impact zone (15.5°–22.5°N, 106°–113.5°E).

  • View in gallery

    The temporal evolution of daily rainfall (bars, mm day−1) with its 10–20- (dashed) and 30–60-day (solid) ISO signal from 1 September to 30 October for each WY. The precipitation caused by TCs is colored red with the names of TCs nearby.

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    Composite 10–20-day filtered OLR anomalies (W m−2; shaded) and 850-hPa horizontal wind anomalies (m s−1; vectors) with day 0 referring to the maximum filtered rainfall in Hainan.

  • View in gallery

    As in Fig. 7, but for 30–60-day filtered anomalies.

  • View in gallery

    Composite 10–20-day filtered OLR anomalies (W m−2, shaded) and 850-hPa horizontal wind anomalies (m s−1; vectors) for 20 west-northwestward moving TCs with day 0 referring to the maximum TC-induced rainfall in Hainan. Red dots represent the location of corresponding TCs.

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Factors for Interannual Variations of September–October Rainfall in Hainan, China

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  • 1 Center for Monsoon and Environment Research/Department of Atmospheric Science, Sun Yat-sen University, Guangzhou, and Hainan Meteorological Service, Meteorological Administration, Hainan, China
  • | 2 Institute of Space and Earth Information Science and Department of Physics, Chinese University of Hong Kong, Hong Kong, China
  • | 3 Center for Monsoon and Environment Research/Department of Atmospheric Science, Sun Yat-sen University, Guangzhou, China
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Abstract

The present study investigates the year-to-year variations of September–October rainfall in Hainan, China, for the period 1965–2010. The dominant circulation anomalies feature a cyclone (an anticyclone) over the Indochina Peninsula and northern South China Sea, an anticyclone (a cyclone) over subtropical western North Pacific and lower-level convergence (divergence) over the Maritime Continent in the wet (dry) years. These circulation anomalies are responses to an east–west sea surface temperature (SST) anomaly pattern with negative (positive) SST anomalies in the equatorial central Pacific and positive (negative) SST anomalies around the Maritime Continent in the wet (dry) years. Although the SST anomaly pattern is similar (but with opposite anomaly), the SST signal in the equatorial central Pacific is more significant in the dry years than in the wet years. This difference indicates a larger case-to-case variability in the wet years than in the dry years. The large variability in the wet years is attributed to contributions of tropical cyclones (TCs) and intraseasonal oscillations (ISOs). There are more TCs impinging on Hainan and the TC tracks are closer to the island in the wet years than in the dry years. The rainfall shows large intraseasonal variations with periods of 10–20 and 30–60 days during September–October in the wet years. The 10–20-day ISO originates from the Maritime Continent, whereas the 30–60-day ISO develops over tropical Indian Ocean and propagates northeastward to northern South China Sea. In contrast, the ISO signal is much weaker in the dry years.

Corresponding author address: Zhiping Wen, Center for Monsoon and Environment Research/Department of Atmospheric Science, Sun Yat-sen University, No. 135, Xingang West Road, Guangzhou 510275, China. E-mail: eeswzp@mail.sysu.edu.cn

Abstract

The present study investigates the year-to-year variations of September–October rainfall in Hainan, China, for the period 1965–2010. The dominant circulation anomalies feature a cyclone (an anticyclone) over the Indochina Peninsula and northern South China Sea, an anticyclone (a cyclone) over subtropical western North Pacific and lower-level convergence (divergence) over the Maritime Continent in the wet (dry) years. These circulation anomalies are responses to an east–west sea surface temperature (SST) anomaly pattern with negative (positive) SST anomalies in the equatorial central Pacific and positive (negative) SST anomalies around the Maritime Continent in the wet (dry) years. Although the SST anomaly pattern is similar (but with opposite anomaly), the SST signal in the equatorial central Pacific is more significant in the dry years than in the wet years. This difference indicates a larger case-to-case variability in the wet years than in the dry years. The large variability in the wet years is attributed to contributions of tropical cyclones (TCs) and intraseasonal oscillations (ISOs). There are more TCs impinging on Hainan and the TC tracks are closer to the island in the wet years than in the dry years. The rainfall shows large intraseasonal variations with periods of 10–20 and 30–60 days during September–October in the wet years. The 10–20-day ISO originates from the Maritime Continent, whereas the 30–60-day ISO develops over tropical Indian Ocean and propagates northeastward to northern South China Sea. In contrast, the ISO signal is much weaker in the dry years.

Corresponding author address: Zhiping Wen, Center for Monsoon and Environment Research/Department of Atmospheric Science, Sun Yat-sen University, No. 135, Xingang West Road, Guangzhou 510275, China. E-mail: eeswzp@mail.sysu.edu.cn

1. Introduction

Hainan Island (or simply Hainan) is a tropical island located in the northwestern South China Sea (SCS) off the coast of southern China (Fig. 1a). The island terrain is characterized by a mountain called the Wuzhi (meaning five figures) Mountain (Fig. 1b). Geographically, Hainan, Guangdong, and Guangxi provinces belong to south China. However, the climate of Hainan is distinctively different from that of south China (e.g., Wei et al. 1982; Chen et al. 1986; Gao 1988). Figure 1c shows area-mean climatological monthly precipitation of Hainan (gray bar) and south China (only Guangdong and Guangxi provinces, dashed line), respectively. Two rainy periods are obvious in south China with the primary one in April–June and the secondary one in July–September. In contrast, the precipitation in Hainan peaks in September with only one rainy period spanning summer and autumn seasons, in agreement with Li et al. (2006). The interannual standard deviation of monthly precipitation in Hainan (solid line) is appreciably larger in September and October than in other months, consistent with Li et al. (2006). Moreover, the standard deviation and correlation distributions (not shown) clearly show that the variability of September–October rainfall in Hainan is large and distinct from most of south China, the Indochina Peninsula, and most of the SCS. Thus, it is necessary to investigate the variability of Hainan rainfall in September–October.

Fig. 1.
Fig. 1.

(a) The geographical location of Hainan, (b) the location of 18 major meteorological stations and the topography (m), and (c) area-mean climatological monthly precipitation (mm day−1) of Hainan (bar) and south China (dashed line) and the interannual standard deviation (mm day−1) of monthly precipitation of Hainan (solid line). The reference period for precipitation climatology is 1965–2010.

Citation: Journal of Climate 26, 22; 10.1175/JCLI-D-12-00728.1

Autumn is the time when flooding and droughts frequently occur in Hainan. In October of 2010, during the Chinese Golden Week holiday, Hainan experienced the worst rainstorm in the last half century, which submerged 1160 villages and 3 cities, destroyed 4480 houses, ravaged 237 920 kha of cultivable land and trapped 600 000 people (http://www.hainan.gov.cn/news/2010/11/116435/). The drought of 2004 is the most severe one in the last 50 years, afflicting the entire area of southern China (Niu and Li 2008). Resulting in more and more direct and indirect economic loss, the disastrous flooding and drought in Hainan (an important agricultural region in China) should be investigated to understand the possible factors in order to aid better planning for sustainable socioeconomic development.

The year-to-year variations of seasonal precipitation are affected by many factors, such as sea surface temperature (SST), snow, and soil moisture. Previous literature has demonstrated the importance of SST in the climate variability of China by its vital forcing of the atmospheric circulation (e.g., Huang and Wu 1989; Wang and Li 1990; Wu and Liu 1992; Lau and Weng 2001; Wu and Wang 2002; Wu et al. 2003; Feng and Hu 2004; Gao et al. 2006; Jiang et al. 2006; Zhou et al. 2010; Weng et al. 2011). The large east–west gradient in tropical SST anomalies (Rasmusson and Carpenter 1982) can alter the intensity and longitudinal position of the Walker circulation (e.g., Walker and Bliss 1932; Bjerknes 1969; Lindzen and Nigam 1987), which consequently exerts influence on the transportation of water vapor to China from the tropical Indian and Pacific Oceans. Li et al. (2006) revealed that two anomalous airflows attached to the Walker circulation coming from the Indian and Pacific Oceans converge around Hainan with plentiful moisture when autumn precipitation is greater than normal in Hainan and proposed that SST anomalies of equatorial central and eastern Pacific may be the possible factor. However, more details about the roles of SST in autumn precipitation of Hainan are still unclear. Thus, SST anomaly pattern related to autumn rainfall anomalies of Hainan will be examined further in this study.

The tropical cyclone (TC) is one of the most destructive weather systems. It often produces heavy rainfall and strong winds along its pass, causing economic and human losses in many countries each year. Being one of areas most frequently and seriously affected by TCs in China (Liu and Chan 2002), Hainan receives more than one-third of annual rainfall by TCs in the main typhoon season (June–November) and 40%–80% of extreme precipitation events are TC-related (Wu et al. 2007). Wei et al. (1982) noted that there is a positive correlation between precipitation and the number of TC days in Hainan. Therefore, the issue of how the TCs contribute to the variability of Hainan precipitation in autumn is addressed in the present study.

The intraseasonal oscillation (ISO), which is first proposed by Madden and Julian (1971, 1972), has become a focal point in recent years for its potential association with the long-range weather or short-term climate variation. The ISO has been identified over the summer monsoon region of East Asia and India in the broad period ranging from 10 to 20 and 30 to 60 days (e.g., Krishnamurti and Ardanuy 1980; Krishnamurti and Subrahmanyam 1982; Krishnamurti 1985; Chen et al. 1988a,b; Lau et al. 1988). Precipitation variability in monsoon regions involves pronounced ISO signals (e.g., Li and Li 1997; Chen et al. 2001; Yang and Li 2003; Zhang et al. 2009). As Hainan is located in the tropical monsoon region, precipitation variability during the rainy season is likely affected largely by the ISOs. Thus, the contribution of the ISOs to anomalous autumn rainfall on Hainan Island will be investigated in this study as well.

In conclusion, the motivation of our study is to investigate the interannual variability of autumn rainfall in Hainan with three conceivable factors—SSTs, TCs, and ISOs. The key questions raised in this study are as follows:

  • What are the relative contributions of different factors to the variability of autumn rainfall in Hainan?
  • What are the differences between the wet and dry years in characteristics of atmospheric circulation and causes?
  • Where are the origins of the ISO modes associated with strong autumn rainfall in Hainan?

The paper is organized as follows. Section 2 provides a brief description of the datasets and analysis methods. Dominant temporal and spatial characteristics of autumn rainfall are examined in section 3. Section 4 analyzes large-scale atmospheric and oceanic fields linked to the rainfall anomalies. Section 5 discusses the influences of SST anomalies. The contributions of TCs and ISOs are explored in section 6. In section 7, the results are summarized.

2. Data and methodology

a. Data

The datasets used in the present study include the following:

  1. daily in situ precipitation records at 18 stations (Fig. 1b) in Hainan covering the period 1965–2010 with no missing data, obtained from the Hainan Meteorological Bureau;
  2. the National Centers for Environmental Prediction (NCEP)–National Center for Atmospheric Research (NCAR) reanalysis (Kalnay et al. 1996) monthly mean and daily mean outputs provided by the National Oceanic and Atmospheric Administration (NOAA)/Earth System Research Laboratory (ESRL) with a 2.5° × 2.5° grid starting from January 1965;
  3. the NOAA extended reconstructed sea surface temperature (ERSST.v3b; Smith et al. 2008) data on a 2° × 2° grid starting from January 1965, obtained from the National Climate Data Center (NCDC) through anonymous ftp (ftp://ftp.ncdc.noaa.gov/pub/data/cmb/ersst/v3b/);
  4. the TC track data from the Joint Typhoon Warning Center (JTWC) western North Pacific best track for the period 1965–2010;
  5. the Climate Diagnostics Center's (CDC's) interpolated daily outgoing longwave radiation (OLR) data (Liebmann and Smith 1996) on a 2.5° × 2.5° grid for the period 1979–2010; and
  6. the Tropical Rainfall Measuring Mission (TRMM) 3B42 rainfall observations (Huffman et al. 2007) based on multisatellite and rain gauge analysis with a spatial resolution of 0.25° × 0.25° during 1998–2010.

b. Methodology

All the monthly anomalies are departures from their respective climatological mean values averaged over the period from 1965 to 2010. The September–October monthly anomalies are then averaged for the two months (September and October) to get the autumn season mean anomalies. Area mean climatological monthly precipitation (Fig. 1c) and autumn season mean anomalies (Fig. 2c) are the average of 18 stations in Hainan and 47 stations in south China.

Fig. 2.
Fig. 2.

(a) The leading EOF mode of interannual variations (shaded) and standard deviation (solid contours, mm day−1), (b) the climatological mean of total (shaded, mm day−1) and TC-related (solid contours, mm day−1) precipitation, (c) the time series of the first principal component (dashed line) and area-mean precipitation anomalies in Hainan (solid line, mm day−1), and (d) percentage of area-mean precipitation anomalies in Hainan. The dashed lines in (a) and (b) indicate the topography at altitudes of 400 and 600 m. A threshold of 40% is used to define the wet (gray bar) and dry (hatched bar) years in (d). The precipitation refers to September–October mean.

Citation: Journal of Climate 26, 22; 10.1175/JCLI-D-12-00728.1

The empirical orthogonal function (EOF) analysis is used to derive the spatial pattern of autumn rainfall variations in Hainan Island. A composite analysis is applied to precipitation, atmospheric circulation, and SST anomalies in the wet and dry years that are defined when the precipitation anomaly exceeds 40% of climatological mean precipitation. The Student's t test is employed to examine the significance of the composite anomalies. A Butterworth bandpass filter (10–20 and 30–60 days) is used to extract intraseasonal signal within the periods of 10–20 and 30–60 days.

The TC-induced rainfall is estimated adopting Chen et al. (2010)'s approach. Chen et al. (2010) pointed out that a distance of 2.5° in longitude and latitude should capture the majority of TC-related rainfall given that a TC's major rainbands are normally within a region of two to three hundred kilometers from the TC center. Following Chen et al. (2010), we define the impact zone as 15.5°–22.5°N, 106°–113.5°E for Hainan. When the TC's center falls in this impact zone, rainfall occurring in Hainan is considered to be induced by the TC and categorized as TC rainfall.

3. Dominant pattern of September–October rainfall variations

An EOF analysis is applied to autumn rainfall anomalies in Hainan. The first EOF mode explains about 73.7% of the total variance and it is well separated from the rest modes based on the 95% confidence level according to North et al. (1982)'s rule for estimating the sampling errors. This mode features a same sign variation in the whole island with larger loading in eastern part of Hainan and smaller loading in southwestern part of the island (Fig. 2a, shaded). Besides, a large value center is located near the northeastern edge of the mountainous region. This distribution resembles closely the distribution of climatological mean of autumn rainfall (Fig. 2b, shaded) and the standard deviation (Fig. 2a, solid contour). As pointed out by Li et al. (2006), the spatial distribution is strongly associated with the presence of central mountainous region in Hainan. In autumn, the effect of orographic lifting enhances precipitation in eastern Hainan but reduces precipitation in the western leeward side. The TC-induced climatological mean rainfall displays a distribution similar to the total precipitation, implying an important contribution of TCs.

To examine the influence of topography on our results, we performed a parallel EOF analysis by excluding the mountainous station, Qiongzhong, where the largest mean and standard deviation are observed (Figs. 2a,b). The obtained EOF1 pattern is similar and the time series is nearly identical with a correlation coefficient of 0.99 (not shown). Moreover, TRMM precipitation data for the period 1998–2010 are analyzed for comparison. Both the climatological mean rainfall in September–October and the standard deviation show a distribution similar to those based on the station rainfall data in Hainan (not shown). Thus, the 18 station data analyzed here are of sufficiently spatial coverage to capture the spatial distribution.

We have applied the EOF analysis to TC-induced and ISO rainfall (not shown). The obtained leading EOF modes show a distribution similar to the total rainfall EOF1 mode, with large loading in the east and small loading in the southwest and the maximum value to the east slope of the mountain. The distribution of 10–20-day rainfall EOF1 mode shows somewhat of a difference with the large loading region extending more northwestward. The percent variance explained by the EOF1 mode is 78.4% (TC), 68.0% (10–20-day ISO), and 60.0% (30–60-day ISO).

Temporal variations of autumn rainfall in Hainan are depicted in Fig. 2c by the time series of the first principal component (PC1; dashed line). For comparison, area mean autumn rainfall anomalies (solid line) averaged for the 18 stations are shown in Fig. 2c as well. The two curves almost overlap with each other with a simultaneous correlation coefficient of 0.99. They both reveal a remarkable interannual variability of autumn rainfall in Hainan. The year 2010 is the wettest year and 2004 is the driest year during the analysis period. The PC1 time series show very high correlation coefficients (reaching the 99.9% confidence level) with rainfall anomalies at most of the 18 stations except for the three stations in the southwest part (not shown). Thus, the temporal evolution of the time series can well represent the rainfall variability over most of Hainan Island.

To understand the features of atmospheric circulation relevant to the variations of September–October rainfall in Hainan, we use the time series of area-mean precipitation anomaly percentage with respect to climatological mean precipitation to select the wet and dry years based on a threshold of 40% for composite analysis (Fig. 2d). This criterion is used to obtain a nearly same number of wet years and dry years with rainfall significantly separated from that in the normal years. Seven wet years (WYs; gray bars; 1973, 1978, 1996, 2000, 2008, 2009, and 2010) and eight dry years (DYs; hatched bars; 1965, 1966, 1969, 1977, 1987, 1991, 2004, and 2006) are identified, respectively, during the analysis period.

4. Atmospheric circulation and SST anomaly pattern

The composite atmospheric circulation patterns related to anomalous autumn precipitation of Hainan are shown in Fig. 3 for 7 WYs and 8 DYs. The composite SST anomaly patterns are shown in Figs. 4a and 4b. The shading in the maps indicates statistical significance at the 95% confidence level according to the one-tailed Student's t test.

Fig. 3.
Fig. 3.

(a),(b) Composite anomalies of 850-hPa horizontal wind fields (m s−1); (c),(d) vertically integrated moisture flux (500 kg m s−1); (e),(f) 850-hPa velocity potential (contour, interval: 0.3 × 10−6 m2 s−1) with divergent winds (2 m s−1; vectors); and (g),(h) equatorial Walker circulation (streamline) averaged over 5°S–5°N in the (left) WYs and (right) DYs. Shaded areas are statistically significant at the 95% confidence level. The magnitudes of vectors in (a),(b) smaller than 0.5 m s−1 and in (c),(d) smaller than 40 kg m s−1 are omitted.

Citation: Journal of Climate 26, 22; 10.1175/JCLI-D-12-00728.1

Fig. 4.
Fig. 4.

(a),(b) Composite anomalies of SST (contour interval 0.2°C) in the WYs and DYs, respectively. Light (dark) gray areas indicate significance exceeding the 90% (95%) confidence level. (c),(d) The time series of composite anomalies of SST (°C) in the ECP (open circle) and MC (solid circle) from January to December in the WYs and DYs, respectively. Dashed line denotes the 95% confidence level. The ECP and MC regions are indicated by boxes in (a) and (b).

Citation: Journal of Climate 26, 22; 10.1175/JCLI-D-12-00728.1

In the WYs, an anomalous cyclone appears over northern SCS and the Indochina Peninsula and an anomalous anticyclone controls the northwestern Pacific (NWP). Anomalous easterlies from the equatorial Pacific and anomalous westerlies from the equatorial eastern Indian Ocean (IO) converge over the Maritime Continent (Fig. 3a). Hainan Island is under the influence of easterly flows from northern SCS, which transport more water vapor to the island (Fig. 3c), favorable for precipitation. The results signify the enhancement of subtropical NWP high and lower-level convergence over Hainan. Indeed, 850-hPa convergent winds extend from the Maritime Continent to northern SCS (Fig. 3e). This forms an east–west contrast with divergent winds over the equatorial central Pacific.

In the DYs, opposite circulation features are seen. A pronounced anomalous anticyclone covers India, the Indochina Peninsula, and northern SCS and an anomalous cyclone is present over the NWP (Fig. 3b). Meanwhile, equatorial flows are westerly over the western Pacific and easterly over the Indian Ocean. Hainan is under the control of dry northwesterly flows with a divergence of anomalous water vapor flux (Fig. 3d) that are unfavorable for rainfall. The above results are consistent with Li et al. (2006). The 850-hPa divergent winds control the Maritime Continent and the SCS and convergent winds dominate the equatorial central Pacific (Fig. 3f), in sharp contrast to those in the WYs.

The contrast of anomalous flows near the equator is further demonstrated in Figs. 3g and 3h, which display a vertical section along the equator (5°S–5°N average). In the WYs, lower-level convergence over the Maritime Continent is accompanied by ascent and upper-level divergence. Over the equatorial central Pacific, there are upper-level convergence and descent overlying the lower-level divergence (Fig. 3g). This signifies an enhanced Walker circulation. In the DYs, nearly opposite convergence and vertical motion are seen (Fig. 3h), signifying a weakened Walker circulation.

In the WYs, the SST anomaly distribution features positive anomalies around the Maritime Continent and negative anomalies in the equatorial central Pacific (Fig. 4a). In the DYs, the SST anomalies are opposite in the above regions (Fig. 4b). Thus, a dominant feature is an east–west contrast between the Maritime Continent and the equatorial central Pacific corresponding to anomalous rainfall in Hainan. This SST anomaly pattern displays a distribution similar to that seen in ENSO years but with the SST anomalies shifting to the equatorial central Pacific. The SST signal in the equatorial central Pacific was already pointed out by Li et al. (2006). However, they did not separate the wet and dry years. The present study shows that the impacts of SST anomalies in the equatorial central Pacific are more significant in the DYs than in the WYs. The influence of the ENSO-related east–west SST anomaly pattern on large-scale circulation over East Asia and the SCS has been indicated in previous studies (e.g., R. Wu et al. 2012). In addition to the asymmetric influence of the equatorial central Pacific SST anomalies, the present study indicates that the SST anomalies in the Maritime Continent may play a large independent role in the September–October rainfall variability in Hainan. Furthermore with a combination of influence of opposite sign SST anomalies in the equatorial central Pacific and the Maritime Continent, the SST anomaly pattern with a large east–west contrast is expected to have a more significant impact.

The discrepancy in the significance of the SST anomalies between the WYs and DYs indicates a larger internal variability in the WYs than in the DYs. The internal variability is likely related to high-frequency variations, such the TCs and ISOs. In contrast, the internal variability is relatively smaller in the DYs. As such, the SST signal appears more robust and more easily to be detected in the DYs.

5. Influence of SST anomalies in the dry years

Results in section 4 indicate opposite tropospheric circulation anomalies between the WYs and the DYs. Opposite SST anomalies are observed as well. The atmospheric circulation anomalies are responses to the SST anomalies as elaborated below for the DYs.

Near the equator, positive SST anomalies in the equatorial central Pacific induce anomalous lower-level convergence and upward motion. At the upper level, anomalous divergence is expected to occur. Negative SST anomalies around the Maritime Continent are expected to induce anomalous lower-level divergence, downward motion, and upper-level convergence. As such, the circulation anomalies over the Maritime Continent and the equatorial Pacific are induced by the east–west SST anomaly pattern (Rasmusson and Carpenter 1982).

The cyclonic wind anomalies over the NWP can be interpreted as a Rossby wave–type response (e.g., Matsuno 1966; Gill 1980) to anomalous heating associated with positive SST anomalies in the equatorial central Pacific (Wang et al. 2000). The anticyclonic wind anomalies over the northern SCS and the Indochina Peninsula can be interpreted as a Rossby wave–type response to anomalous cooling associated with negative SST anomalies around the Maritime Continent. An alternative interpretation is that the anomalous anticyclone is a response to positive SST anomalies in the equatorial central Pacific. Anomalous heating due to warm SST anomalies in the equatorial central Pacific induces anomalous upper-level convergence and lower-level divergence over the SCS and NWP (Wu and Wang 2000), which leads to the formation of lower-level anticyclones. It is likely that both the remote forcing from the equatorial central Pacific and the Rossby wave response to the SST anomalies around the Maritime Continent contribute to the large anticyclone.

The SST anomalies often persist for months or seasons and thus may provide information for short-term climate prediction. Here, in order to examine the precursory signals of SST anomalies, we show in Figs. 4c and 4d the evolution of monthly mean SST anomalies in two key regions: the Maritime Continent (MC; 20°S–0°, 110°–150°E) and the equatorial central Pacific (ECP; 10°S–10°N, 180°–140°W). As seen from Figs. 4c and 4d, significant MC SST anomalies start in the preceding summer and are maintained until November in both the WYs and DYs. The ECP SST anomalies are significant only in the DYs, not in the WYs. Thus, the SST anomalies in the above two regions provide a precursory signal in the DYs, which may be used in the prediction of Hainan rainfall in September–October. In the WYs, only the MC SST anomalies provide a useful precursory signal.

To delineate the respective and combined influences of SST anomalies in the above two regions, we have calculated the correlation coefficients of Hainan rainfall with the SST anomalies in the above two regions and the difference of their normalized values (MC minus ECP). The obtained correlation coefficients are, respectively, 0.46, 0.40, and 0.48 for the MC SST, ECP SST, and the SST difference, which are all significant at the 99% confidence level. Comparing the SST difference and the Hainan rainfall time series, 5 out of 7 wet years correspond to a large and positive SST difference and all 8 dry years correspond to a large and negative SST difference. The 850-hPa wind anomalies (not shown) obtained by regression against the SST difference display features similar to the composite shown in Figs. 3a and 3b.

Although the significance level of the SST anomalies in the WYs is lower than that in the DYs, the processes for the influence of SST anomalies on Hainan rainfall in the WYs are likely the same as in the DYs since the circulation patterns are similar (with opposite signs). On the other hand, the low significance of SST anomalies in the WYs indicates large case-to-case variability, which may be due to contributions of high-frequency variations, such as TCs and ISOs. The contributions of TCs and ISOs to Hainan rainfall variability in the WYs are examined in detail in section 6.

6. Contributions of tropical cyclones and intraseasonal oscillations in the WYs

In this section, we first discuss the TCs and ISOs and their influences on the Hainan rainfall in the WYs. Then, we describe the propagation of the 10–20- and 30–60-day ISOs that affect Hainan. The TCs, ISO, and SST anomalies are interlinked with each other. Thus, we devote a subsection to addressing the influence of the SST anomalies on the TCs and ISOs and the influence of the ISOs on the TCs.

a. TCs

TCs can bring a large amount of rainfall to southern China, especially along the coast (e.g., Ren et al. 2002, 2006; Wang et al. 2008; Chen et al. 2012). To understand the contributions of TCs, we show in Fig. 5a the tracks of TCs that enter the impact zone during September–October in every WY. Different colors indicate the change in the intensity of the TCs [green for tropical depression (TD); yellow for tropical storm (TS); red for typhoon (TY) or supertyphoon (STY)]. Figure 5b is the same as Fig. 5a but for the DYs (no TCs in 1966, 1987, 1991 and 2004). Table 1 presents the number of TDs, TSs, TYs, and TCs (containing TDs, TSs, and TYs) in each WY and DY. The contribution of TCs to total rainfall in percentage is shown in the table as well.

Fig. 5.
Fig. 5.

The tracks of TCs impacting Hainan in each (a) WY and (b) DY. Here TD, TS, TY, and STY denote tropical depression, tropical storm, typhoon, and supertyphoon, respectively, which are coded with different colors (TD, green; TS, yellow; and TY and STY, red). The black box enclosing Hainan represents the impact zone (15.5°–22.5°N, 106°–113.5°E).

Citation: Journal of Climate 26, 22; 10.1175/JCLI-D-12-00728.1

Table 1.

The number of TCs entering the impact zone, the TC-induced rainfall, and the proportion with respect to total rainfall (in percentage) during September–October in each WY and DY. Here TD, TS, and TY denote different categories of TCs based on the maximum intensity of TC reached in the impact zone. Shown in the last column is the average. For DYs, years in boldface have no TCs.

Table 1.

Comparing the two types of years, several prominent features can be noticed. First, there are more TCs entering the impact zone in the WYs than in the DYs. Among the 7 WYs, 5 years have 3 or more TCs. Among the 8 DYs, there are 4 years of no TCs. On average, there are 3.4 TCs in the WYs and only 1.3 TCs in the DYs (Table 1). Second, the TC tracks are closer to the center of the impact zone (i.e., Hainan Island) in the WYs than in the DYs (Fig. 5). There are two TCs that are worthy of special note. One is TY 27 in 1996 that revolved around Hainan and maintained a prolonged impact on the island (Fig. 5a). The other is TD 14 in 2010 that crossed the island from south to north. Although it was only a TD, it produced a huge amount of rainfall (Table 1). Third, on average, the TC-induced rainfall in the WYs (6.92 mm day−1) is about an order of magnitude larger than that in the DYs (0.49 mm day−1) (Table 1). The percentage of TC-related rainfall on average is about 44.90% in the WYs, but only 9.75% in the DYs. In conclusion, in terms of the number and track of TCs as well as the contribution of TC rainfall, there are pronounced differences between the WYs and the DYs. The TC rainfall varies from year to year due to the number and track changes, leading to large internal variability in the WYs and thus reducing the significance of SST influence on Hainan rainfall variability. In contrast, the TC contribution to rainfall variability in the DYs is smaller.

b. ISOs

By Morlet wavelet analysis, 10–20 and 30–60 days are confirmed as the two primary periods in the intraseasonal variations of area-mean rainfall of Hainan in the 7 WYs during September–October (not shown). Using the Butterworth bandpass filter, we extract 10–20- and 30–60-day ISO signals of rainfall for each WY to illustrate their variations. Figure 6 shows the temporal evolution of 10–20- (dashed line) and 30–60-day (solid line) ISO components and total daily rainfall (bar) for the 7 WYs. Clearly, in many cases, the rainfall intraseasonal variations may be contributed by the TCs; for example, during mid-October 1973 (Fig. 6a) and late September–mid-October 2008 (Fig. 6e). In some cases, the TC is embedded in the ISO wet phase. For example, a TS occurred in mid-October 2000 (Fig. 6d) and a TD during early October 2010 (Fig. 6g), both of which are in the wet phase of the ISOs. It is not clear how much of the rainfall during these TC days is really due to the TCs, although the method we used attributes all the rainfall in these days to the TCs. This may overestimate the TC rainfall.

Fig. 6.
Fig. 6.

The temporal evolution of daily rainfall (bars, mm day−1) with its 10–20- (dashed) and 30–60-day (solid) ISO signal from 1 September to 30 October for each WY. The precipitation caused by TCs is colored red with the names of TCs nearby.

Citation: Journal of Climate 26, 22; 10.1175/JCLI-D-12-00728.1

According to Fig. 6, the intraseasonal variations in rainfall are obvious. In 1973, an ISO signal appeared during 17–30 September (Fig. 6a). In 1978, two obvious 10–20-day ISOs were seen during 1–12 September and 16–28 October (Fig. 6b). In 1996, the ISO-induced rainfall appeared small if the large rainfall during 6–29 September was attributed to the TCs (Fig. 6c). During 7–22 October 2000, 10–20- and 30–60-day ISOs were both important in addition to the TC contribution (Fig. 6d). ISOs had a small contribution in 2008 (Fig. 6e), and there were three 10–20-day ISOs in 2009 (Fig. 6f). In 2010, two heavy rain periods were observed during 30 September–18 October (Fig. 6g). The first one appears to be contributed by 10–20- and 30–60-day ISOs as well as the TD. In this period, 10–20- and 30–60-day ISOs both peaked on 5 October. The combined contributions of the TD and ISOs lead to a persistent heavy precipitation, with the most severe episode during September–October of the analysis period. In the second period, the 30–60-day ISO was transforming from a positive to a negative phase. As such, its contribution to rainfall is smaller. As one would imagine, the second rainfall is weaker and shorter than the first one.

We have also analyzed the rainfall variations in the DYs. Although ISO signals can be detected, they are generally much weaker compared to the WYs. As such, the rainfall variability due to persistent SST anomalies may be more significant in the DYs than in the WYs.

c. Propagation of the ISOs

We have inspected the origins and propagations of the ISOs that affect Hainan in the WYs based on filtered OLR and 850-hPa wind fields. The 10–20-day ISOs tend to originate from the Maritime Continent–equatorial western Pacific and move northward to Hainan. In contrast, the 30–60-day ISOs appear to belong to an eastward extension of the northward-propagating ISOs from the equatorial Indian Ocean. Figure 7 shows the composite of the 10–20-day filtered OLR field, which represents convection, along with the filtered 850-hPa wind field for a total of 24 10–20-day ISO cases during the 7 WYs. The selection of the cases is based on the criterion that the maximum filtered Hainan rainfall exceeds the 0.5 standard deviation. The reference time for the composite (day 0) is the day when peak rainfall occurs. Figure 8 is similar to Fig. 7 except for the 30–60-day filtered fields and for a total of nine 30–60-day ISO cases selected with the 1.0 standard deviation as the criterion. The composite fields are shown every other day from day −8 to 2 in Fig. 7 and every three days from day −12 to 3 in Fig. 8.

Fig. 7.
Fig. 7.

Composite 10–20-day filtered OLR anomalies (W m−2; shaded) and 850-hPa horizontal wind anomalies (m s−1; vectors) with day 0 referring to the maximum filtered rainfall in Hainan.

Citation: Journal of Climate 26, 22; 10.1175/JCLI-D-12-00728.1

Fig. 8.
Fig. 8.

As in Fig. 7, but for 30–60-day filtered anomalies.

Citation: Journal of Climate 26, 22; 10.1175/JCLI-D-12-00728.1

For the 10–20-day ISO, at day −8, cyclonic winds dominate southern SCS and Borneo (Fig. 7a). At this time, Hainan is under the control of westerly winds between an anticyclone over the Indochina Peninsula and a cyclone over south China. The convection is enhanced over southern SCS and suppressed over northern SCS. From day −6 to −2, the cyclone move north-northwestward from southern SCS to northern SCS–Indochina Peninsula (Figs. 7b–d). The associated convection region also moves northward with an increase in the intensity. In contrast, the positive OLR over the coast of south China decreases quickly. At day 0, the strong convection region controls Hainan Island and the neighboring regions, accompanied by cyclonic winds (Fig. 7e). At day 2, the convection and the cyclonic winds move farther northward and start to weaken (Fig. 7f).

For the 30–60-day ISO, at day −12, cyclonic winds extend from eastern Indian Ocean to the central SCS, which is accompanied by weak convection (Fig. 8a). Both the cyclonic winds and convection intensify over eastern Indian Ocean and northern SCS at day −9 (Fig. 8b). From day −9 to −3, the cyclone and convection over eastern Indian Ocean move northward with a weakening in the intensity (Figs. 8b–d). The cyclone and convection over the SCS move northward as well but with an increase in the intensity. At day 0, the cyclonic winds and convection control Hainan Island and the neighboring regions (Fig. 8e). At day 3, the winds and convection start to weaken (Fig. 8f). During the evolution, the cyclone over the SCS appears to be clearly connected with the one over eastern Indian Ocean at days −12, 0, and 3, but less so at days −9, −6, and −3, which is likely due to the effect of the land ridge.

Overall, the 10–20-day ISO displays a clear northward propagation from the Maritime Continent and southern SCS. The northward propagation is also seen for the 30–60-day ISO. In comparison, the 10–20-day ISO is confined to the SCS, whereas the 30–60-day ISO appears to belong to an eastward extension from the eastern Indian Ocean with a separate center. The connection of cyclonic winds between eastern Indian Ocean and the SCS appears to be disrupted sometimes because of the effect of lands of the Indochina Peninsula, which limits the moisture supply for deep convection.

d. Discussion of the influence of ISOs and SST anomalies on the TCs

In the previous subsections, we focused on the contributions of TCs and ISOs to the Hainan rainfall in the WYs. The large TC-related rainfall and active ISOs lead to large case-to-case variability of rainfall in the WYs. On the other hand, the TCs and ISOs may be influenced by large-scale circulation pattern associated with the SST anomalies. The ISOs may modulate the occurrence, movement, and intensity of the TCs as well. In this subsection, we discuss the influences of the ISOs and SST anomalies on the TCs as well as the impact of the SST anomalies on the ISOs.

The modulation of the ISOs on the TC activity over the SCS and NWP has been shown in previous studies (e.g., Camargo et al. 2009; Huang et al. 2011; Li et al. 2012). The TC geneses tend to be clustered in the cyclonic circulation within the ISO westerly phase (e.g., Camargo et al. 2009; Huang et al. 2011) because of the favorable environment (e.g., Liebmann et al. 1994; Kim et al. 2008). Figure 6 shows several TCs that are embedded in the ISO wet phases, which makes it difficult to separate exactly the contributions of TCs and ISOs to rainfall in Hainan. It is also possible that the ISOs and TCs may interact, enhancing rainfall and leading to severe flood (Chen and Shih 2012).

As seen in Fig. 7, the lower-level cyclonic vorticity associated with the 10–20-day ISOs reaches the northern South China Sea at days −4 and −2 (Figs. 7c,d). This provides a favorable condition for the TCs to intensify in the SCS as well as to move westward across the SCS. After the TCs reach Hainan Island, the TCs and ISOs may interact, amplifying the precipitation, in particular on the east side of the island where winds blow onshore. To confirm the relationship of the TC movement to the ISOs, we selected 20 TCs with west-northwestward movement in the WYs (Fig. 5a). The composite of 10–20-day filtered 850-hPa wind and OLR fields is shown in Fig. 9. Day 0 is defined as the day when the TC-related rainfall in Hainan reaches a maximum. From Fig. 9, it is obvious that the TCs are clustered in the region of cyclonic winds. Following the northwestward propagation of intraseasonal cyclonic wind and convection region, the TCs move westward to the region around Hainan Island.

Fig. 9.
Fig. 9.

Composite 10–20-day filtered OLR anomalies (W m−2, shaded) and 850-hPa horizontal wind anomalies (m s−1; vectors) for 20 west-northwestward moving TCs with day 0 referring to the maximum TC-induced rainfall in Hainan. Red dots represent the location of corresponding TCs.

Citation: Journal of Climate 26, 22; 10.1175/JCLI-D-12-00728.1

The impacts of tropical Pacific SST anomalies on the TC activity in the NWP have been recognized (Chen et al. 1998; Wang and Chan 2002; Camargo and Sobel 2005; Chan 2005; Camargo et al. 2007; Chen 2011; Kim et al. 2011; Zhan et al. 2011; L. Wu et al. 2012). The SST anomalies modulate the NWP subtropical high and the monsoon trough, leading to a longitudinal shift in the location of TC occurrence (e.g., Wang and Chan 2002; Camargo et al. 2007; L. Wu et al. 2012). In the WYs, the positive SST anomalies in the Philippine Sea (Fig. 4a) provide a favorable condition for more TC formation. The anomalous easterly winds to the south flank of the anomalous anticyclone over the NWP (Fig. 3a) may likely steer the TCs to move westward and enter the SCS. These TCs may move farther westward under the influence of the ISOs. Therefore, more TCs may impact Hainan Island in the WYs. In the DYs, the low SST in the Philippine Sea (Fig. 4b) is unfavorable for TC formation. The anomalous cyclone over subtropical NWP and the associated anomalous westerly winds (Fig. 3b) shift the region of TC genesis to the east and the TCs are more likely to recurve northward (Wang and Chan 2002). As such, fewer TCs may enter the SCS and impinge on Hainan Island in the DYs.

The impact of the tropical Pacific SST anomalies on the ISOs over the NWP has been noted in previous studies. Teng and Wang (2003) indicated that the increase in the easterly vertical shears over the tropical western Pacific during July–October in the El Niño developing year enhances the NWP ISOs. Lau and Nath (2006) showed that the ENSO events could influence the amplitude of the intraseasonal variability by modulating the large-scale environmental flow. The ISOs related to rainfall in Hainan originate in the Maritime Continent and southern SCS (Figs. 7 and 8). Thus, they may be related to SST anomalies in the Maritime Continent. In the WYs, warmer SST in the Maritime Continent leads to strong convection, resulting in active ISOs. When these ISOs propagate to Hainan Island, they bring large intraseasonal rainfall variability. In the DYs, the SST is lower in the Maritime Continent. The associated downdraft is unfavorable for strong convection and thus the ISOs are weaker. To verify the relation of ISO rainfall variability to SST anomalies, we have calculated the standard deviations of 10–20- and 30–60-day filtered rainfall. For the 10–20-day ISOs, the average standard deviation is 9.56 mm day−1 in the WYs, but only 2.15 mm day−1 in the DYs. For the 30–60-day ISOs, the average value is 6.90 mm day−1 in the WYs and only 1.85 mm day−1 in the DYs.

Overall, the TCs, ISOs, and SST anomalies are interconnected. The SST anomalies and associated circulation pattern can modulate the ISOs and TCs. The ISOs can affect the TCs. The impacts of the SST anomalies on the TCs may occur through their modulation of the ISOs. The TCs and ISOs may interact to amplify their impacts on rainfall. Much more work is needed to understand these impacts.

7. Summary

Distinct from other regions in south China, Hainan Island features a peak climatological rainy season in September. The interannual variability of monthly rainfall in Hainan also peaks in September–October. Analysis shows that the year-to-year variations of September–October rainfall are highly consistent in the whole island although the magnitude is larger in eastern part of the island and smaller in southwestern part. The year-to-year variations in Hainan Island are also unique, with no obvious relationship to those in south China, the Indochina Peninsula, and the SCS.

Composite analysis shows that anomalous September–October precipitation in Hainan is related to obvious atmospheric circulation changes in the tropical Indo-Pacific region with nearly opposite features in the WYs and DYs. The dominant features in the WYs are an anomalous cyclone over northern SCS and the Indochina Peninsula, an anomalous anticyclone over the NWP, and an enhanced Walker circulation between the Maritime Continent and the equatorial central and eastern Pacific.

These circulation anomalies are associated with an east–west SST anomaly pattern between the Maritime Continent and the equatorial central Pacific. In the DYs, warm and negative SST anomalies are in the equatorial central Pacific and around the Maritime Continent, respectively. SST anomalies in the above regions are opposite in the WYs. In comparison, the SST signals are more significant in the DYs than in the WYs. This indicates a large case-to-case variation in the WYs, likely due to the impacts of TCs and ISOs.

The number of TCs impinging on Hainan Island during September–October is about 3 times more in the WYs than in the DYs. In addition, the TCs in the WYs either pass over or near the island, whereas the TCs in the DYs tend to stay away from the island. As a result, the TC-related rainfall accounts for a large percent (45%) of total September–October rainfall in the WYs. In contrast, the TC-related rainfall only accounts for a small percent (10%) of the total rainfall in the DYs.

Large ISOs are detected to affect Hainan Island during September–October in the WYs. In comparison, the ISOs are much weaker in the DYs. The two ISOs (10–20- and 30–60-day) affecting Hainan Island have different origins. The 10–20-day ISOs come from the Maritime Continent and move northward to Hainan. The 30–60-day ISOs appear to be an eastward extension from the tropical Indian Ocean, but also propagate northward through the Indochina Peninsula and the SCS to Hainan.

The number of TCs is likely modulated by the ISOs and the large-scale circulation pattern associated with the SST anomalies. The SST anomalies can also modulate the intensity of the ISOs. Thus, on the one hand, the SST anomalies modulate the large-scale circulation for the ISOs and TCs; on the other hand, the rainfall induced by TCs and ISOs leads to large case-to-case variability in the WYs. The case-to-case variability is weaker in the DYs as the number of TCs is smaller and the ISOs are weaker. As a result, the signal of SST influence on Hainan rainfall directly through the large-scale circulation appears less significant in the WYs than in the DYs.

As Hainan is located in northern SCS, some of the results of this study may be applicable to the SCS rainfall variability, such as the influence of the SST anomaly pattern, the ISOs, and the tropical cyclones. Indeed, the wind anomalies associated with wet and dry years in Hainan cover northern SCS (Fig. 3), as do the intraseasonal wind and OLR anomalies (Figs. 7 and 8). As the tropical cyclones that bring rainfall to Hainan pass through or form in the northern SCS (Fig. 5), they should have a large influence on the SCS rainfall as well. One difference is that September–October rainfall variability is much larger near Hainan than in the broad northern SCS region, which may be attributed to the effect of topography. The topographic effect may also account for the low correlation of year-to-year variations of September–October rainfall between Hainan and the broad northern SCS region (not shown).

Acknowledgments

This research is jointly supported by the National Key Basic Research Program of China (Grant 2009CB421404), the National Natural Science Foundation of China (Grants 41175076, 40730951, and 412111046), and the Fundamental Research Funds for the Central Universities (Grant 11lgjc10). We thank Hainan Meteorology Bureau for providing rain gauge data. RW acknowledges the support of a Direct Grant of the Chinese University of Hong Kong (2021105), a Hong Kong Research Grants Council grant (CUHK403612), and National Natural Science Foundation of China grants (412750851 and 41228006).

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