Madden–Julian Oscillation and the Winter Rainfall in Taiwan

Chih-wen Hung Department of Geography, National Taiwan Normal University, Taipei, Taiwan

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Ho-Jiunn Lin Department of Geography, National Taiwan Normal University, Taipei, Taiwan

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Huang-Hsiung Hsu Research Center for Environmental Change, Academia Sinica, Taipei, Taiwan

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Abstract

This study discusses major impacts of the Madden–Julian oscillation (MJO) on the winter (November–April) rainfall in Taiwan. The results show that Taiwan has more rainfall in MJO phases 3 and 4 (MJO convectively active phase in the Indian Ocean and the western part of the Maritime Continent), and less rainfall in phases 7 and 8 (the western Pacific warm pool area). Mechanisms associated with the MJO are suggested as follows. 1) The tropics to midlatitude wave train: when the MJO moves to the middle Indian Ocean, a Matsuno–Gill-type pattern is induced. The feature of this tropical atmospheric response to the MJO diabatic heating is a pair of upper-level anomalous anticyclones symmetric about the equator to the west of the heating. The northern anomalous anticyclone over the Arabian Sea and northern India induces a northeastward-propagating wave train to the midlatitudes. The wave pattern consists of a cyclonic anomaly centered at East Asia that enhances the winter rainfall in Taiwan. 2) Increase of moisture supply from the South China Sea: when the MJO convection approaches Sumatra and Java of the Maritime Continent, the eastward penetration of equatorial convection enhances a low-level southerly flow that transports the moisture northward to Taiwan and southern China. As a consequence, with the increase of moisture supply from the south, more winter monsoon rainfall is observed in Taiwan.

Corresponding author address: Chih-wen Hung, Department of Geography, National Taiwan Normal University, 162 HePing East Rd., Section 1, Taipei 10610, Taiwan. E-mail: hungchihwen@gmail.com

Abstract

This study discusses major impacts of the Madden–Julian oscillation (MJO) on the winter (November–April) rainfall in Taiwan. The results show that Taiwan has more rainfall in MJO phases 3 and 4 (MJO convectively active phase in the Indian Ocean and the western part of the Maritime Continent), and less rainfall in phases 7 and 8 (the western Pacific warm pool area). Mechanisms associated with the MJO are suggested as follows. 1) The tropics to midlatitude wave train: when the MJO moves to the middle Indian Ocean, a Matsuno–Gill-type pattern is induced. The feature of this tropical atmospheric response to the MJO diabatic heating is a pair of upper-level anomalous anticyclones symmetric about the equator to the west of the heating. The northern anomalous anticyclone over the Arabian Sea and northern India induces a northeastward-propagating wave train to the midlatitudes. The wave pattern consists of a cyclonic anomaly centered at East Asia that enhances the winter rainfall in Taiwan. 2) Increase of moisture supply from the South China Sea: when the MJO convection approaches Sumatra and Java of the Maritime Continent, the eastward penetration of equatorial convection enhances a low-level southerly flow that transports the moisture northward to Taiwan and southern China. As a consequence, with the increase of moisture supply from the south, more winter monsoon rainfall is observed in Taiwan.

Corresponding author address: Chih-wen Hung, Department of Geography, National Taiwan Normal University, 162 HePing East Rd., Section 1, Taipei 10610, Taiwan. E-mail: hungchihwen@gmail.com

1. Introduction

The eastward-moving Madden–Julian oscillation (MJO; Madden and Julian 1971, 1972, 1994; Zhang 2005) is an intraseasonal phenomenon that has broad influences on the global weather and climate including precipitation, surface temperature, tropical cyclones, monsoons, and others (Zhang 2013). The MJO deep convection and circulation associated with it propagate eastward from eastern Africa and the Indian Ocean to the Maritime Continent. The convection of the MJO dissipates near the international date line, while the signal of the circulation continues to propagate around the globe. When the MJO moves to the Indian Ocean and the western Pacific Ocean, it has impact on the tropical to the subtropical climate over the Asian–Australian monsoon region (e.g., Goswami 2012; Hsu 2012; Wheeler et al. 2009).

During the boreal summer, the northward transport of the MJO signals is shown by Yasunari (1979, 1980, 1981). The interactions between the MJO and synoptic-scale disturbances over the western North Pacific are also discussed in Murakami et al. (1986), Hsu et al. (2011), and Hsu and Li (2011). In Hung and Hsu (2008), the first transition of the Asian summer monsoon and the onset of Taiwan’s mei-yu associated with MJOs are discussed. They found that the evolution of the large-scale monsoon circulation and convection is related to an eastward-propagating MJO from eastern Africa to the Maritime Continent. When the MJO arrives at the Maritime Continent, a sharp onset of the Asian summer monsoon (the first transition) occurs and a channel delivering the moisture across the Indian Ocean to the South China Sea (SCS) is well established. This efficient and persistent transport of moisture to the SCS provides a favorable condition for the maintenance of the monsoon system. A similar impact of the MJO on the SCS monsoon is also discussed in Mao and Chan (2005) and Straub et al. (2006). In addition to the MJO influences on the Asian summer monsoon, Hung and Yanai (2004) investigated the Australian summer monsoon and found four major factors contributing to its onset. In their study, the MJO is the most important trigger among these factors.

In contrast, there is little research discussing the impact of the MJO on the winter monsoon. During the boreal winter, the MJO tends to move along the equator. However, the intraseasonal signal can still be transported to the subtropical regions. In Li et al. (2013), they showed the strongest East Asian winter monsoon (EAWM) and the deepest southern trough over the Bay of Bengal occurred when the MJO convectively active phase moves to the Indian Ocean. The MJO impacts on China for all seasons, including the winter season, are also discussed. In Jia et al. (2011), the impact of the MJO on winter rainfall and circulation in China was studied. They showed that the rainfall in the Yangtze River basin and southern China systematically changed according to the eastward-moving MJO. The propagation of low-frequency perturbations to the mid- to high latitudes and the moisture transport from the Bay of Bengal to the SCS are the major modulating mechanisms from the MJO.

Taiwan is an island located to the east of China. The climatic features of Taiwan are unique and different from those of continental China. In a very early study by Ogasahara (1939), a so-called three-point observation method was used to predict rainfall in Taiwan. The three points are Pratas (on the SCS), Ishigaki (part of the Okinawa islands), and Shanghai, which represent the moisture from the SCS, the strength of the Pacific subtropical high, and the cold air mass from the north, respectively. This early study argued that Taiwan is located at a unique point for the research of meteorology and climatology in East Asia, due to its location at the boundary between continent and ocean, its latitudes between the tropics and subtropics, and its position on the major routes of the western North Pacific typhoon tracks.

According to many previous works and the analysis of the century-long Taiwan rainfall index (TRI, more details in the next section), the major rainy season in Taiwan is from mei-yu in May to the end of the typhoon season in autumn (Fig. 1). On average, the summer-half year (from May to October) brings three-quarters of the total annual rainfall to Taiwan. Therefore, the remaining one-quarter of annual rainfall from the winter-half year [from November to April (NDJFMA)] is characterized as the dry season and received less attention from researchers. However, the rainfall amount in the winter-half year is still a very important climate issue in Taiwan for the water resource arrangement because of agricultural needs, especially for the rice crops.

Fig. 1.
Fig. 1.

The mean annual cycle of the rainfall in Taiwan represented by the 1900–2010 TRI (%). The annual cycle is repeated twice to show a completed winter season. NDJFMA and May–October (MJJASO) stand for the winter-half and summer-half, respectively.

Citation: Journal of Climate 27, 12; 10.1175/JCLI-D-13-00435.1

The MJO impact on the mei-yu in Taiwan has been studied in Hung and Hsu (2008). The relationship between typhoons and the MJO was also addressed by Liebmann et al. (1994) and Maloney and Hartmann (2001). It would be interesting to investigate the impact of the MJO on the winter rainfall in Taiwan and the related modulating mechanisms. The results would be important for local weather forecasters to predict the wintertime rainfall in Taiwan on the intraseasonal time scale. The rest of this study is organized as follows. The data used in this work are provided in section 2. The winter rainfall in Taiwan as a function of MJO phase is presented in section 3. The MJO impacts on the winter rainfall in Taiwan are discussed in sections 4. Conclusions are presented in section 5.

2. Data

In the present study, several 1974–2009 global gridded variables in the winter-half season (November–April) including horizontal and vertical velocity, specific humidity, and geopotential height are obtained from the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) and the ECMWF Interim Re-Analysis (ERA-Interim) (Uppala et al. 2005; Dee et al. 2011). The daily outgoing longwave radiation (OLR) measurements (Liebman and Smith 1996) since 1974 are also used. To clearly see the signal of intraseasonal time scale, the bandpass filter that isolates the 20–100-day components is applied here for these variables.

The MJO phases are determined by the daily real-time multivariate MJO (RMM) index from Wheeler and Hendon (2004). The full cycle of the MJO is divided into eight phases by a combined empirical orthogonal function (EOF) analysis of OLR and upper/lower-level zonal wind. The principle components of the first two EOFs are used to derive the RMM index. Since the index is normalized by their standard deviation, the amplitude of RMM index greater than 1 is considered to be significant MJO signal in the present study.

The TRI, the longest rainfall index in Taiwan’s meteorological history, beginning in 1900, was constructed by Hung (2012). The TRI is based on the richest data from observational stations in Taiwan. More than 1000 stations on the island are used including observations from conventional weather stations, the newly acquired Water Resources Agency-Irrigation Associations data and Central Weather Bureau (CWB) automatic rainfall station data. Similar to the “all India monsoon rainfall index” (Parthasarathy et al. 1995), which represents the condition of the Indian monsoon rainfall, the TRI represents the variations of Taiwan rainfall well and can be used to determine the rainfall condition in Taiwan. The daily time series of the index are the rainfall averages of each station divided by its own climatology of annual sum. Therefore, the sum of daily TRI for any specific year is close to 1, and the value of TRI in any time step indicates its proportion of the yearly climatology mean. The comparison and verification of this index with the previous CWB-only station data were done in Hung (2012), and the results show the index can be used to describe the rainfall condition in Taiwan for various time-scale phenomena. The TRI, including more than 1000 stations, made the index more representative than previous studies, which used data from only 20–30 CWB conventional stations. Similar to the data source of TRI, the gridded version of the rainfall data in Taiwan (Weng and Yang, 2012) created by the Kriging method is used in the present study, too.

In addition to the rainfall data, the surface weather map provided by the Japan Meteorological Agency (JMA) since 1974 was obtained to determine whether there were fronts passing through Taiwan.

3. Winter rainfall in Taiwan associated with the MJO

Using the 1974–2009 TRI data, the rainfall condition in Taiwan associated with the different phases of the MJO can be analyzed. In Fig. 2a, the mean TRI values for each MJO phase (1–8) during NDJFMA are shown. The cases calculated here are only for those with RMM amplitudes greater than 1, meaning the significant MJO condition. In addition, days with typhoons near Taiwan, the center of typhoons located within the domains (19°–28°N, 117°–125°E) defined in Hung and Hsu (2010), are excluded. The results show that Taiwan has larger rainfall in MJO phases 3 and 4, and less rainfall in phases 7 and 8. This is not the same as Li et al. (2013) who show that the largest EAWM index has the largest value in phase 2, and the most significant rainfall in southern China are in phases 2 and 3. In addition, the rainfall in Taiwan also shows a distinct secondary minimum in phase 2. The reason for the different MJO phases of the rainfall in Taiwan and in southern China will be discussed later. However, a calculation of days with a frontal passage over the domain surrounding Taiwan (20°–28°N, 118°–124°E, and excluding the continental China area) for each MJO phase in 1974–2009 is provided in Fig. 2b. The result exhibits that there are more days with fronts in phases 3 and 4 over the Taiwan area. The frontal system is a synoptic feature, but the frequency of fronts or the average duration of the frontal life are the climate issues. The kind of large-scale circulation that could result in the differences of the local winter rainfall in Taiwan for each MJO phase will be analyzed in this study.

Fig. 2.
Fig. 2.

(a) The mean TRI values for MJO phases 1–8 during NDJFMA from 1974 to 2009. The numbers at each bar indicate the numbers of days for each MJO phase. The standard error for each phase is plotted in the figure. (b) The number of days with fronts over the Taiwan area (20°–28°N, 118°–124°E, and excluding the continental China area) for each MJO phase from 1974 to 2009.

Citation: Journal of Climate 27, 12; 10.1175/JCLI-D-13-00435.1

The effects of the Taiwan topography during the mei-yu season has been studied in previous works (e.g., Yeh and Chen 2002; Wang et al. 2005). Because of the orographic dynamic lifting effect, the low-level EAWM circulation can result in precipitation over the windward area, such as the coast of the Japan Sea in Japan, northern Taiwan, the eastern Philippines, and the eastern Indochinese peninsula. The topography and the sum of winter (NDJFMA) rainfall of Taiwan are shown in Figs. 3a and 3b, respectively. Because it is almost the dry season in southern Taiwan during winter, the major region of rain shown in Fig. 3b is seen over the middle to northern Taiwan.

Fig. 3.
Fig. 3.

(a) The topography of Taiwan (m). (b) The mean November–April rainfall for 1974–2009 (mm). (c),(d) The daily rainfall composites (mm day−1) for the front cases and northeasterly monsoon cases from Fig. 3 of Hung and Kao (2010), respectively. (e),(f),(g),(h) The mean anomalous rainfall patterns (mm day−1) in Taiwan for MJO phases 1 + 2, 3 + 4, 5 + 6, and 7 + 8 in 1974–2009, respectively.

Citation: Journal of Climate 27, 12; 10.1175/JCLI-D-13-00435.1

In northern Taiwan, the northeasterly monsoonal flow can produce orographic rain along the coastal regions during winter (Chen and Chen 2003; Chen and Huang 1999; Chen et al. 2002) as shown in Fig. 3b. However, in addition to this effect, the frontal system is another important factor in causing rainfall in Taiwan from the north to the middle of the island. Based on Hung and Kao (2010), the two major types of rainfall pattern in Taiwan during the winter season are (i) with frontal passage and (ii) under northeasterly monsoonal wind but without fronts. The rainfall patterns from the composite analysis in 1997–2005 for type (i) and type (ii) acquired from Hung and Kao (2010) are shown in Figs. 3c and 3d for comparison, respectively.

As shown in Fig. 3d, the type (ii) is basically confined to the northern and northeastern coastal regions, while the type (i) pattern shown in Fig. 3c has larger rainfall area over the island, in addition to the northern coast. Although the traditional wisdom from the local weather forecasters in Taiwan thought that the stronger northeasterly winter monsoonal wind would result in more rainfall in Taiwan (Wu 1998), the study by Hung and Kao (2010) argued that another mechanism, the frontal system along with rain belt that relates to the moisture supply from the SCS, also contributes an important role in the winter rainfall in Taiwan.

To visualize the MJO impact on the winter rainfall in Taiwan, based on the 1974–2009 gridded rainfall data of Taiwan (same source from TRI; Weng and Yang 2012), the anomalous horizontal rainfall patterns for MJO phases 1 + 2, 3 + 4, 5 + 6, and 7 + 8 are shown in Figs. 3e–h, respectively. Overall, Taiwan has more rainfall in the MJO phase 3 + 4 case, with less rainfall in the phase 7 + 8 case as shown in Fig. 2a. In addition, the northeastern part of Taiwan has slightly positive rain in phases 1 + 2 and 5 + 6, because this region is the windward coastal areas during the winter monsoon season most of the time, no matter what MJO phases are. However, only the phase 3 + 4 case has an island-wide positive rainfall anomaly. This implies that there is a large-scale circulation support associated with the frontal passage (similar to Fig. 3c), instead of the northeasterly monsoonal wind inducing the orographic rain over the northern and eastern coastal regions of Taiwan (similar to Fig. 3d).

The phase composites of OLR and the upward motion at 500 hPa display classic MJO movement for the associated deep convection. Figure 4 is the NDJFMA 20–100-day bandpass-filtered OLR anomaly (the NDJFMA mean is removed) for each MJO phase, and only cases with amplitude of RMM greater than 1 are used for the composites. The deep convection (OLR, Fig. 4) and stronger upward motion (similar to OLR, not shown) can be seen in phases 3 and 4 in the area near Taiwan to the Okinawa island and southern Japan, while shallower convection and anomalous downward motion occurred in phases 7 and 8 for the same region. The larger impact of the rainfall in Taiwan from the MJO during NDJFMA is in phases 3 and 4, which is consistent with Fig. 2a. In addition, the deep convection in phase 2 located at about 30°N, which is to the north of Taiwan, shows that Taiwan is not located at the main deep convection area. A second rainfall minimum in TRI in phase 2 is also shown in Fig. 2a. More explanation will be provided later.

Fig. 4.
Fig. 4.

The 20–100-day filtered anomalous OLR (red/blue shading; W m−2) for MJO phases 1–8.

Citation: Journal of Climate 27, 12; 10.1175/JCLI-D-13-00435.1

4. MJO impacts on the winter rainfall in Taiwan

a. Tropics to midlatitude wave train

When the major convection of the MJO moves from eastern Africa to the middle Indian Ocean (phase 2), a classic Matsuno–Gill-type pattern (Matsuno 1966; Gill 1980) can be seen in Figs. 4 and 5. The major MJO deep convection (shown by OLR in Fig. 4b) is located at 60°–90°E. The feature of the tropical atmospheric response to the MJO diabatic heating is a pair of upper-level anomalous anticyclones (the Rossby wave response) symmetric about the equator to the west of the heating (Hsu 1996; Yihui and Yanju 2001). The northern anomalous anticyclone is clearly seen over the Arabian Sea during phase 2 (Fig. 5a). This anomalous anticyclone can induce a northeastward-propagating wave train to the midlatitudes. The wave pattern consists of a cyclonic anomaly centered in China and an anticyclonic anomaly located in the middle of Japan during phase 2. The cyclonic anomaly in China can enhance the convection and results in the increase of rainfall over southern China (Fig. 5d). This is why southern China starts to have rainfall in MJO phase 2 as discussed in Li et al. (2013). However, when the MJO-related rainfall starts to increase in southern China (phase 2), Taiwan is still not located at the major anomalous cyclonic area. Therefore, a small rainfall value represented by the TRI in phase 2 is observed (Fig. 2a).

Fig. 5.
Fig. 5.

(a) MJO phase 2 composites (20–100-day filtered) for the anomalies of 200-hPa geopotential height (in red/blue shading; m) and 200-hPa streamline. The “A” and “C” stand for anticyclone and cyclone, respectively. The wave train pattern is connected by the white lines. (b),(c) As in (a), but for phases 3 and 4, respectively. (d),(e),(f) As in (a),(b),(c), but for 850 hPa, respectively. The “L” stands for low. The values at 850 hPa over the Tibetan Plateau are masked by the white color in (d),(e), and (f) due to the high elevations.

Citation: Journal of Climate 27, 12; 10.1175/JCLI-D-13-00435.1

When the MJO continues to move eastward, the wave train pattern shifts following the moving MJO heat source. In phases 3 and 4, the Rossby wave–related pair of anomalous anticyclones is located at about 80°E (in northern India and the middle of the southern Indian Ocean, Fig. 5b). The associated cyclonic anomaly at the subtropics and the anticyclonic anomaly at the midlatitudes move eastward following the shift of the wave pattern. A clear cyclonic anomaly at the lower level can be seen at 850 hPa along southern China and Taiwan in phase 3 (Fig. 5e) and moves to the Okinawa island and Taiwan area in phase 4 (Fig. 5f). This MJO-related tropical-midlatitude wave train mechanism brings larger rainfall to the Taiwan area in phases 3 and 4. However, during the MJO phases 7 and 8 (Figs. 4g and 4h), an opposite situation occurs in contrast, and less rainfall is observed in Taiwan due to the anticyclonic anomaly located in the Taiwan area.

b. Increase of the moisture supply from the SCS

In addition to rainfall in Taiwan caused by the MJO-related large-scale wave train, the moisture supply associated with the MJO from the south plays another important role, too. The seasonal transition features of large-scale moisture transport over the Asian–Australian monsoon region have been studied in He et al. (2007). The moisture supply from the south that enhances the monsoonal rain in the mei-yu season of Taiwan is also discussed in Hung and Hsu (2008). When the MJO convection approaches Sumatra and Java, vertical motion starts to occur and induces subsidence adjacent to the Maritime Continent (Fig. 6a). The interactions between the MJO and the disturbances over the western North Pacific have been discussed in Hsu et al. (2011) and Hsu and Li (2011). The eastward penetration of equatorial convection can induce local meridional circulation to its north and south. In phases 2 and 3, the subsidence separated into the northern and southern branches (Figs. 6a and 6b). The southern branch of the subsidence appears near northern Australia and the Southern Pacific convergence zone region, while the northern branch is located over the southern SCS to the Philippine Sea area at about 110°–140°E. The northern branch of the subsidence induces a low-level southerly flow, which transports the moisture northward to Taiwan and southern China in phases 2 and 3 (Figs. 6a and 6b), and the flow switches to the east–west direction in phase 4.

Fig. 6.
Fig. 6.

(a) MJO phase 2 composites (20–100-day filtered) for the anomalies of 500-hPa vertical velocity (in red/blue shading; 10−2 Pa s−1) and 850-hPa streamline. (b),(c) As in (a), but for phases 3 and 4, respectively. (d),(e),(f) As in (a),(b),(c), but for the 850-hPa moisture transport shown by the vectors uqi and υqj (q is the specific humidity) and the moisture divergence shown in the red/blue shading (red = divergence; blue = convergence), respectively (10−9 s−1). The values at 850 hPa over the Tibetan Plateau are masked by the black color due to the high elevations.

Citation: Journal of Climate 27, 12; 10.1175/JCLI-D-13-00435.1

The low-level 850-hPa moisture convergence/divergence is calculated by the velocities multiplying the specific humidity (uqi and υqj; where q is the specific humidity). The phase 2–4 composites are shown in Figs. 6d–f, respectively. In phase 2, the moisture convergence region is located at 26°–30°N, which is to the north of Taiwan and not yet reaching Taiwan. Therefore, a distinct secondary rainfall minimum in phase 2 in addition to phases 7 and 8 can be seen in Fig. 2a. However, in phases 3 and 4, the moisture convergence area reaches Taiwan. As a consequence, with the increase of the moisture supply from the south, more winter monsoon rainfall during phases 3 and 4 of the MJO is observed in Taiwan.

5. Conclusions and discussion

In this study, the major impacts of the MJO on the winter rainfall (November–April) in Taiwan are discussed. The results show that Taiwan has more winter rain in the MJO phases 3 and 4 (MJO convection located at the Indian Ocean and the western part of the Maritime Continent). In contrast, during phases 7 and 8 of the MJO (Figs. 4g and 4h), an opposite situation occurs, and less rainfall is observed in Taiwan. As summarized in the conceptual model in Fig. 7, the mechanism suggested in this work is presented as follows.

  1. Tropics to midlatitude wave train: when the MJO moves to the middle Indian Ocean, a classic Matsuno–Gill-type pattern can be seen. The feature of this tropical atmospheric response to the MJO diabatic heating is a pair of anomalous anticyclones (the Rossby wave response) symmetric about the equator to the west of the heating. The northern anomalous anticyclone over the Arabian Sea induces a northeastward-propagating wave train to the midlatitudes. The wave pattern consists of a cyclonic anomaly (southern China and Taiwan) and an anticyclonic anomaly (Japan), which can move following the eastward-moving MJO and result in the increase of winter rainfall in Taiwan in phases 3 and 4.

  2. Increase of moisture supply from the SCS: when the MJO convection approaches the areas of Sumatra and Java in the Maritime Continent, the eastward penetration of equatorial convection induces meridional circulation to its north and south. The northern branch of the circulation is located over the SCS to the Philippine Sea area at about 110°–120°E and induces a low-level southerly flow that transports the moisture northward. The moisture convergence area is located in Taiwan and its adjacent area in phases 3 and 4. As a consequence, more winter rainfall is observed in Taiwan.

Fig. 7.
Fig. 7.

The conceptual model used to explain two major mechanisms of the MJO impacts on the winter rainfall in Taiwan. Dark and light gray shadings represent the deep convection and subsidence regions, respectively. “A” and “C” stand for upper-level anticyclone and cyclone, respectively. “MJO” indicates the major MJO convection. The big black arrow indicates the moving direction of the MJO, and the small black arrow refers to the southerly flow transport the moisture to Taiwan. The wave train pattern shifts following the eastward-moving MJO. The locations of phase 2 and phases 3 + 4 wave trains are plotted in light gray and black, respectively.

Citation: Journal of Climate 27, 12; 10.1175/JCLI-D-13-00435.1

In Li et al. (2013), they show that the strongest EAWM and the deepest southern trough over the Bay of Bengal are in phase 2. For the southern China region, phases 2 and 3 have more rainfall during the wintertime (Jia et al. 2011). The winter rainfall in Taiwan, on the other hand, is larger in phases 3 and 4, which are slightly later in time. This is because the wave train pattern shifts eastward following the MJO-related heat source moving eastward (as shown in Figs. 57). During phase 2, the Rossby wave response from the diabatic heating of the MJO convection over the Indian Ocean creates a pair of anticyclonic anomalies over the Arabian Sea that then produces a northeastward-propagating wave train to set up a upper-level cyclonic anomaly over China. This signal from the tropics can provide a better environment for convections to develop in China. However, Taiwan is located outsides of this cyclonic anomaly. Therefore, the Taiwan rainfall represented by the TRI shows smaller rainfall in phase 2. However, in phases 3 and 4, the wave train pattern has moved eastward following the eastward-moving MJO and the strong cyclonic anomaly covered Taiwan and its adjacent area. This enhanced cyclonic anomaly with the extra moisture supply from the south results in more rainfall in Taiwan at the phases 3 and 4.

The present study demonstrated the locality of the impacts of MJO on the Asian winter monsoon. As discussed above, the MJO impact on the winter rainfall in China are in phases 2 and 3, while the larger rainfall that occur in Taiwan are in phases 3 and 4. This suggests the importance of local studies on the global moving MJO and that the local responses of the MJO require more detailed study. The results in this work are informative for the weather forecasters in Taiwan to project the possible wet or dry conditions during the winter season. The two mechanisms provided in this study can be used for intraseasonal weather prediction as a conceptual model, too.

Acknowledgments

The authors thank three reviewers for their useful comments on the manuscript. Special thanks are extended to Y.-M. Li for his help in figure preparation. This work was supported by the National Science Council under Grants NSC 99-2111-M-003-001-MY3, NSC 102-2621-M-492-001, and NSC 102-2111-M-003-003.

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  • Hung, C.-w., and H.-H. Hsu, 2008: The first transition of the Asian summer monsoon, intraseasonal oscillation, and Taiwan mei-yu. J. Climate, 21, 15521568, doi:10.1175/2007JCLI1457.1.

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    • Export Citation
  • Hung, C.-w., and H.-H. Hsu, 2010: Contribution of typhoons to the rainfall in Taiwan. Proc. 14th Int. Conf. on Geography in Taiwan, Taipei, Taiwan, National Taiwan Normal University, C3 1-8.

  • Hung, C.-w., and P.-K. Kao, 2010: Weakening of the winter monsoon and abrupt increase of winter rainfall over northern Taiwan and southern China in the early 1980s. J. Climate, 23, 23572367, doi:10.1175/2009JCLI3182.1.

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  • Jia, X., L. Chen, F. Ren, and C. Li, 2011: Impacts of the MJO on winter rainfall and circulation in China. Adv. Atmos. Sci., 28, 521533, doi:10.1007/s00376-010-9118-z.

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    • Export Citation
  • Li, C., J. Pan, and J. Song, 2013: Progress on the MJO research in recent years (in Chinese). Chin. J. Atmos. Sci., 37, 229252, doi:10.3878/j.issn.1006-9895.2012.12318.

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    • Export Citation
  • Liebmann, B., and C. A. Smith, 1996: Description of a complete (interpolated) outgoing longwave radiation dataset. Bull. Amer. Meteor. Soc., 77, 12751277.

    • Search Google Scholar
    • Export Citation
  • Liebmann, B., H. H. Hendon, and J. D. Glick, 1994: The relationship between tropical cyclones of the western Pacific and Indian Oceans and the Madden–Julian oscillation. J. Meteor. Soc. Japan, 72, 401412.

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    • Export Citation
  • Madden, R. A., and P. R. Julian, 1971: Detection of a 40–50 day oscillation in the zonal wind in the tropical Pacific. J. Atmos. Sci., 28, 702708, doi:10.1175/1520-0469(1971)028<0702:DOADOI>2.0.CO;2.

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  • Madden, R. A., and P. R. Julian, 1972: Description of global scale circulation cells in the tropics with 40–50 day period. J. Atmos. Sci., 29, 11091123, doi:10.1175/1520-0469(1972)029<1109:DOGSCC>2.0.CO;2.

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    • Export Citation
  • Madden, R. A., and P. R. Julian, 1994: Observations of the 40–50-day tropical oscillation—A review. Mon. Wea. Rev., 122, 814837, doi:10.1175/1520-0493(1994)122<0814:OOTDTO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Maloney, E. D., and D. L. Hartmann, 2001: The Madden–Julian oscillation, barotropic dynamics, and North Pacific tropical cyclone formation. Part I: Observations. J. Atmos. Sci., 58, 25452558, doi:10.1175/1520-0469(2001)058<2545:TMJOBD>2.0.CO;2.

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  • Mao, J., and J. C. L. Chan, 2005: Intraseasonal variability of the South China Sea summer monsoon. J. Climate, 18, 23882402, doi:10.1175/JCLI3395.1.

    • Search Google Scholar
    • Export Citation
  • Matsuno, T., 1966: Quasi-geostrophic motions in the equatorial area. J. Meteor. Soc. Japan, 44, 2543.

  • Murakami, T., L.-X. Chen, and A. Xie, 1986: Relationship among seasonal cycles, low-frequency oscillations, and transient disturbances as revealed from outgoing longwave radiation data. Mon. Wea. Rev., 114, 14561465, doi:10.1175/1520-0493(1986)114<1456:RASCLF>2.0.CO;2.

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  • Ogasahara, K., 1939: On the mechanism of formation of summer squall in the southwest plain region of Formosa for the synoptic meteorologist. J. Soc. Trop. Agric., 11, 1556.

    • Search Google Scholar
    • Export Citation
  • Parthasarathy, B., A. A. Munot, and D. R. Kothawale, 1995: Monthly and Seasonal Rainfall Series for All-India Homogeneous Regions and Meteorological Subdivisions: 1871-1994. Indian Institute of Tropical Meteorology, 113 pp.

  • Straub, K. H., G. N. Kiladis, and P. E. Ciesielski, 2006: The role of equatorial waves in the onset of the South China Sea summer monsoon and the demise of El Niño during 1998. Dyn. Atmos. Oceans, 42, 216238.

    • Search Google Scholar
    • Export Citation
  • Uppala, S. M., and Coauthors, 2005: The ERA-40 Re-Analysis. Quart. J. Roy. Meteor. Soc., 131, 29613012, doi:10.1256/qj.04.176.

  • Wang, C.-C., G. T.-J. Chen, T.-C. Chen, and K. Tsuboki, 2005: A numerical study on the effects of Taiwan topography on a convective line during the mei-yu season. Mon. Wea. Rev., 133, 32173242, doi:10.1175/MWR3028.1.

    • Search Google Scholar
    • Export Citation
  • Weng, S.-P., and C.-T. Yang, 2012: The construction of monthly rainfall and temperature datasets with 1km gridded resolution over Taiwan area (1960-2009) and its application to climate projection in the near future (2015-2039) (in Chinese). Atmos. Sci., 40, 349369.

    • Search Google Scholar
    • Export Citation
  • Wheeler, M. C., and H. H. Hendon, 2004: An all-season real-time multivariate MJO index: Development of an index for monitoring and prediction. Mon. Wea. Rev.,132, 1917–1932, doi:10.1175/1520-0493(2004)132<1917:AARMMI>2.0.CO;2.

  • Wheeler, M. C., H. H. Hendon, S. Cleland, H. Meinke, and A. Donald, 2009: Impacts of the MJO on Australian rainfall and circulation. J. Climate, 22, 14821497, doi:10.1175/2008JCLI2595.1.

    • Search Google Scholar
    • Export Citation
  • Wu, M. J., 1998: Climate variation in Taiwan—Temperature and precipitation. Amer. Sci., 20, 295318.

  • Yasunari, T., 1979: Cloudiness fluctuations associated with the Northern Hemisphere summer monsoon. J. Metor. Soc. Japan,57, 227–242.

  • Yasunari, T., 1980: A quasi-stationary appearance of 30 to 40 day period in the cloudiness fluctuations during the summer monsoon over India. J. Meteor. Soc. Japan,58, 225–229.

  • Yasunari, T., 1981: Structure of an Indian summer monsoon system with around 40-day period. J. Meteor. Soc. Japan,59, 336–354.

  • Yeh, H.-C., and Y.-L. Chen, 2002: The role of offshore convergence on coastal rainfall during TAMEX IOP 3. Mon. Wea. Rev., 130, 27092730, doi:10.1175/1520-0493(2002)130<2709:TROOCO>2.0.CO;2.

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    • Export Citation
  • Yihui, D., and L. Yanju, 2001: Onset and the evolution of the summer monsoon over the South China Sea during SCSMEX Field Experiment in 1998. J. Meteor. Soc. Japan, 79, 255276, doi:10.2151/jmsj.79.255.

    • Search Google Scholar
    • Export Citation
  • Zhang, C., 2005: Madden-Julian oscillation. Rev. Geophys., 43, RG2003, doi:10.1029/2004RG000158.

  • Zhang, C., 2013: Madden–Julian oscillation: Bridging weather and climate. Bull. Amer. Meteor. Soc., 94, 18491870, doi:10.1175/BAMS-D-12-00026.1.

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  • Hung, C.-w., and M. Yanai, 2004: Factors contributing to the onset of the Australian summer monsoon. Quart. J. Roy. Meteor. Soc., 130, 739758, doi:10.1256/qj.02.191.

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  • Hung, C.-w., and H.-H. Hsu, 2008: The first transition of the Asian summer monsoon, intraseasonal oscillation, and Taiwan mei-yu. J. Climate, 21, 15521568, doi:10.1175/2007JCLI1457.1.

    • Search Google Scholar
    • Export Citation
  • Hung, C.-w., and H.-H. Hsu, 2010: Contribution of typhoons to the rainfall in Taiwan. Proc. 14th Int. Conf. on Geography in Taiwan, Taipei, Taiwan, National Taiwan Normal University, C3 1-8.

  • Hung, C.-w., and P.-K. Kao, 2010: Weakening of the winter monsoon and abrupt increase of winter rainfall over northern Taiwan and southern China in the early 1980s. J. Climate, 23, 23572367, doi:10.1175/2009JCLI3182.1.

    • Search Google Scholar
    • Export Citation
  • Jia, X., L. Chen, F. Ren, and C. Li, 2011: Impacts of the MJO on winter rainfall and circulation in China. Adv. Atmos. Sci., 28, 521533, doi:10.1007/s00376-010-9118-z.

    • Search Google Scholar
    • Export Citation
  • Li, C., J. Pan, and J. Song, 2013: Progress on the MJO research in recent years (in Chinese). Chin. J. Atmos. Sci., 37, 229252, doi:10.3878/j.issn.1006-9895.2012.12318.

    • Search Google Scholar
    • Export Citation
  • Liebmann, B., and C. A. Smith, 1996: Description of a complete (interpolated) outgoing longwave radiation dataset. Bull. Amer. Meteor. Soc., 77, 12751277.

    • Search Google Scholar
    • Export Citation
  • Liebmann, B., H. H. Hendon, and J. D. Glick, 1994: The relationship between tropical cyclones of the western Pacific and Indian Oceans and the Madden–Julian oscillation. J. Meteor. Soc. Japan, 72, 401412.

    • Search Google Scholar
    • Export Citation
  • Madden, R. A., and P. R. Julian, 1971: Detection of a 40–50 day oscillation in the zonal wind in the tropical Pacific. J. Atmos. Sci., 28, 702708, doi:10.1175/1520-0469(1971)028<0702:DOADOI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Madden, R. A., and P. R. Julian, 1972: Description of global scale circulation cells in the tropics with 40–50 day period. J. Atmos. Sci., 29, 11091123, doi:10.1175/1520-0469(1972)029<1109:DOGSCC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Madden, R. A., and P. R. Julian, 1994: Observations of the 40–50-day tropical oscillation—A review. Mon. Wea. Rev., 122, 814837, doi:10.1175/1520-0493(1994)122<0814:OOTDTO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Maloney, E. D., and D. L. Hartmann, 2001: The Madden–Julian oscillation, barotropic dynamics, and North Pacific tropical cyclone formation. Part I: Observations. J. Atmos. Sci., 58, 25452558, doi:10.1175/1520-0469(2001)058<2545:TMJOBD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Mao, J., and J. C. L. Chan, 2005: Intraseasonal variability of the South China Sea summer monsoon. J. Climate, 18, 23882402, doi:10.1175/JCLI3395.1.

    • Search Google Scholar
    • Export Citation
  • Matsuno, T., 1966: Quasi-geostrophic motions in the equatorial area. J. Meteor. Soc. Japan, 44, 2543.

  • Murakami, T., L.-X. Chen, and A. Xie, 1986: Relationship among seasonal cycles, low-frequency oscillations, and transient disturbances as revealed from outgoing longwave radiation data. Mon. Wea. Rev., 114, 14561465, doi:10.1175/1520-0493(1986)114<1456:RASCLF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Ogasahara, K., 1939: On the mechanism of formation of summer squall in the southwest plain region of Formosa for the synoptic meteorologist. J. Soc. Trop. Agric., 11, 1556.

    • Search Google Scholar
    • Export Citation
  • Parthasarathy, B., A. A. Munot, and D. R. Kothawale, 1995: Monthly and Seasonal Rainfall Series for All-India Homogeneous Regions and Meteorological Subdivisions: 1871-1994. Indian Institute of Tropical Meteorology, 113 pp.

  • Straub, K. H., G. N. Kiladis, and P. E. Ciesielski, 2006: The role of equatorial waves in the onset of the South China Sea summer monsoon and the demise of El Niño during 1998. Dyn. Atmos. Oceans, 42, 216238.

    • Search Google Scholar
    • Export Citation
  • Uppala, S. M., and Coauthors, 2005: The ERA-40 Re-Analysis. Quart. J. Roy. Meteor. Soc., 131, 29613012, doi:10.1256/qj.04.176.

  • Wang, C.-C., G. T.-J. Chen, T.-C. Chen, and K. Tsuboki, 2005: A numerical study on the effects of Taiwan topography on a convective line during the mei-yu season. Mon. Wea. Rev., 133, 32173242, doi:10.1175/MWR3028.1.

    • Search Google Scholar
    • Export Citation
  • Weng, S.-P., and C.-T. Yang, 2012: The construction of monthly rainfall and temperature datasets with 1km gridded resolution over Taiwan area (1960-2009) and its application to climate projection in the near future (2015-2039) (in Chinese). Atmos. Sci., 40, 349369.

    • Search Google Scholar
    • Export Citation
  • Wheeler, M. C., and H. H. Hendon, 2004: An all-season real-time multivariate MJO index: Development of an index for monitoring and prediction. Mon. Wea. Rev.,132, 1917–1932, doi:10.1175/1520-0493(2004)132<1917:AARMMI>2.0.CO;2.

  • Wheeler, M. C., H. H. Hendon, S. Cleland, H. Meinke, and A. Donald, 2009: Impacts of the MJO on Australian rainfall and circulation. J. Climate, 22, 14821497, doi:10.1175/2008JCLI2595.1.

    • Search Google Scholar
    • Export Citation
  • Wu, M. J., 1998: Climate variation in Taiwan—Temperature and precipitation. Amer. Sci., 20, 295318.

  • Yasunari, T., 1979: Cloudiness fluctuations associated with the Northern Hemisphere summer monsoon. J. Metor. Soc. Japan,57, 227–242.

  • Yasunari, T., 1980: A quasi-stationary appearance of 30 to 40 day period in the cloudiness fluctuations during the summer monsoon over India. J. Meteor. Soc. Japan,58, 225–229.

  • Yasunari, T., 1981: Structure of an Indian summer monsoon system with around 40-day period. J. Meteor. Soc. Japan,59, 336–354.

  • Yeh, H.-C., and Y.-L. Chen, 2002: The role of offshore convergence on coastal rainfall during TAMEX IOP 3. Mon. Wea. Rev., 130, 27092730, doi:10.1175/1520-0493(2002)130<2709:TROOCO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Yihui, D., and L. Yanju, 2001: Onset and the evolution of the summer monsoon over the South China Sea during SCSMEX Field Experiment in 1998. J. Meteor. Soc. Japan, 79, 255276, doi:10.2151/jmsj.79.255.

    • Search Google Scholar
    • Export Citation
  • Zhang, C., 2005: Madden-Julian oscillation. Rev. Geophys., 43, RG2003, doi:10.1029/2004RG000158.

  • Zhang, C., 2013: Madden–Julian oscillation: Bridging weather and climate. Bull. Amer. Meteor. Soc., 94, 18491870, doi:10.1175/BAMS-D-12-00026.1.

    • Search Google Scholar
    • Export Citation
  • Fig. 1.

    The mean annual cycle of the rainfall in Taiwan represented by the 1900–2010 TRI (%). The annual cycle is repeated twice to show a completed winter season. NDJFMA and May–October (MJJASO) stand for the winter-half and summer-half, respectively.

  • Fig. 2.

    (a) The mean TRI values for MJO phases 1–8 during NDJFMA from 1974 to 2009. The numbers at each bar indicate the numbers of days for each MJO phase. The standard error for each phase is plotted in the figure. (b) The number of days with fronts over the Taiwan area (20°–28°N, 118°–124°E, and excluding the continental China area) for each MJO phase from 1974 to 2009.

  • Fig. 3.

    (a) The topography of Taiwan (m). (b) The mean November–April rainfall for 1974–2009 (mm). (c),(d) The daily rainfall composites (mm day−1) for the front cases and northeasterly monsoon cases from Fig. 3 of Hung and Kao (2010), respectively. (e),(f),(g),(h) The mean anomalous rainfall patterns (mm day−1) in Taiwan for MJO phases 1 + 2, 3 + 4, 5 + 6, and 7 + 8 in 1974–2009, respectively.

  • Fig. 4.

    The 20–100-day filtered anomalous OLR (red/blue shading; W m−2) for MJO phases 1–8.

  • Fig. 5.

    (a) MJO phase 2 composites (20–100-day filtered) for the anomalies of 200-hPa geopotential height (in red/blue shading; m) and 200-hPa streamline. The “A” and “C” stand for anticyclone and cyclone, respectively. The wave train pattern is connected by the white lines. (b),(c) As in (a), but for phases 3 and 4, respectively. (d),(e),(f) As in (a),(b),(c), but for 850 hPa, respectively. The “L” stands for low. The values at 850 hPa over the Tibetan Plateau are masked by the white color in (d),(e), and (f) due to the high elevations.

  • Fig. 6.

    (a) MJO phase 2 composites (20–100-day filtered) for the anomalies of 500-hPa vertical velocity (in red/blue shading; 10−2 Pa s−1) and 850-hPa streamline. (b),(c) As in (a), but for phases 3 and 4, respectively. (d),(e),(f) As in (a),(b),(c), but for the 850-hPa moisture transport shown by the vectors uqi and υqj (q is the specific humidity) and the moisture divergence shown in the red/blue shading (red = divergence; blue = convergence), respectively (10−9 s−1). The values at 850 hPa over the Tibetan Plateau are masked by the black color due to the high elevations.

  • Fig. 7.

    The conceptual model used to explain two major mechanisms of the MJO impacts on the winter rainfall in Taiwan. Dark and light gray shadings represent the deep convection and subsidence regions, respectively. “A” and “C” stand for upper-level anticyclone and cyclone, respectively. “MJO” indicates the major MJO convection. The big black arrow indicates the moving direction of the MJO, and the small black arrow refers to the southerly flow transport the moisture to Taiwan. The wave train pattern shifts following the eastward-moving MJO. The locations of phase 2 and phases 3 + 4 wave trains are plotted in light gray and black, respectively.

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