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    Fig. 1.

    Climatological distribution of (a) daily-mean precipitation (mm day−1) and (b) its std dev.

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    Fig. 2.

    Average precipitation rates (mm day−1) in each of the categorized MJO phases, represented as differences from the winter-mean values. Squares indicate the stations where the composite values are significant at the 99% confidence level.

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    Fig. 3.

    Difference in (a) rainy day (≥0.1 mm day−1) and (b) heavy rain (top 10% precipitation amount) day frequency between MJO phases 2–3 and 6–7, represented as a percentile relative to the total number of rainy and heavy rain days, respectively. (c) Frequency distribution of precipitation (day−1) categorized by 5 mm day–1 intervals of precipitation rates in phases 2–3 and 6–7, averaged over all stations. The abscissa is the precipitation category (mm day−1), and the ordinate is the relative frequency (day−1) for each MJO period. (d) Product of the relative frequency and accumulated precipitation in each precipitation category, averaged over all stations (mm day−1).

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    Fig. 4.

    Composite anomalies of the streamfunction at 700 hPa (contours, 0.5 × 106 m2 s−1) superimposed on the low-level specific humidity averaged from 1000 to 700 hPa (shading) in each of categorized MJO phases.

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    Fig. 5.

    Composite anomalies of the streamfunction at 300 hPa (contours, 1.0 × 106 m2 s−1) superimposed on the OLR anomalies (shaded) in each of the categorized MJO phases.

  • View in gallery
    Fig. 6.

    Composite anomalies of the vertical velocity (contours, 1 × 10−3 Pa s−1, negative values are dashed) in each of the categorized MJO phase.

  • View in gallery
    Fig. 7.

    Results of the iterative calculation of the generalized ω equations; ω is forced by (a), (c) quasigeostrophic forcings (FQG) and by (b), (d) diabatic heating (FH) at 300 hPa using the composite fields in MJO phases 2–3 and 6–7.

  • View in gallery
    Fig. 8.

    (left) Power spectra of the daily anomalies of the vertical velocity in a selected region over East Asia (20°–50°N, 90°–150°E), calculated using the entire time series in winter. The thin solid curve represents the Markov red-noise spectrum, and two thin dashed curves represent 5% and 95% confidence intervals, respectively. The two vertical lines in the middle of the figure indicate 80 and 20 days, respectively. (right) Lag correlations between the vertical velocity averaged over the selected region and the two RMM series. The solid and dashed lines represent RMM2 and RMM1, respectively. The thick lines represent the values calculated by using the indices passing through the conventional 20–80-day filtering, and the thin lines are calculated by using the raw indices.

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    Fig. 9.

    (left) Time–longitude plot of OLR anomalies averaged over tropical latitudes (15°S–15°N) (shaded). The contours indicate the 15-day moving averaged values. Thin vertical solid lines indicate 80° and 100°E longitude. (right) Vertical velocity anomalies averaged over the selected region in East Asia. The dashed line indicates the 15-day moving average time series.

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    Fig. 10.

    (a) Synoptic variance (2–8 days) of the meridional wind at 850 hPa. The regions where the synoptic variance explains more than 40% of the total variance are stippled. (b), (c) Synoptic variance during the categorized MJO phases relative to the total synoptic variance.

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Systematic Variation in Wintertime Precipitation in East Asia by MJO-Induced Extratropical Vertical Motion

Jee-Hoon JeongSchool of Earth and Environmental Sciences, Seoul National University, Seoul, South Korea

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Baek-Min KimSchool of Earth and Environmental Sciences, Seoul National University, Seoul, South Korea

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Chang-Hoi HoSchool of Earth and Environmental Sciences, Seoul National University, Seoul, South Korea

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Yeon-Hee NohSchool of Earth and Environmental Sciences, Seoul National University, Seoul, South Korea

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Abstract

The variations in the wintertime precipitation over East Asia and the related large-scale circulation associated with the Madden–Julian oscillation (MJO) are examined. By analyzing the observed daily precipitation for the period 1974–2000, it is found that the MJO significantly modulates the distribution of precipitation over four East Asian countries; the precipitation rate difference between wet and dry periods over East Asia, when the centers of MJO convective activities are located over the Indian Ocean and western Pacific, respectively, reaches 3–4 mm day−1, which corresponds to the climatological winter-mean value.

Composite analysis with respect to the MJO suggests that the MJO–precipitation relation is mostly explained by the strong vertical motion anomalies near an entrance region of the East Asia upper-tropospheric jet and moisture supply in the lower troposphere. To elucidate different dynamic origins of the vertical motion generated by the MJO, diagnostic analysis of a generalized omega equation is adopted. It is revealed that about half of the vertical motion anomalies in East Asia are induced by the quasigeostrophic forcings by the MJO, while diabatic heating forcings explain a very small fraction, less than 10% of total anomalies.

Corresponding author address: Chang-Hoi Ho, Climate Physics Laboratory, School of Earth and Environmental Sciences, Seoul National University, Seoul 151-742, South Korea. Email: hoch@cpl.snu.ac.kr

Abstract

The variations in the wintertime precipitation over East Asia and the related large-scale circulation associated with the Madden–Julian oscillation (MJO) are examined. By analyzing the observed daily precipitation for the period 1974–2000, it is found that the MJO significantly modulates the distribution of precipitation over four East Asian countries; the precipitation rate difference between wet and dry periods over East Asia, when the centers of MJO convective activities are located over the Indian Ocean and western Pacific, respectively, reaches 3–4 mm day−1, which corresponds to the climatological winter-mean value.

Composite analysis with respect to the MJO suggests that the MJO–precipitation relation is mostly explained by the strong vertical motion anomalies near an entrance region of the East Asia upper-tropospheric jet and moisture supply in the lower troposphere. To elucidate different dynamic origins of the vertical motion generated by the MJO, diagnostic analysis of a generalized omega equation is adopted. It is revealed that about half of the vertical motion anomalies in East Asia are induced by the quasigeostrophic forcings by the MJO, while diabatic heating forcings explain a very small fraction, less than 10% of total anomalies.

Corresponding author address: Chang-Hoi Ho, Climate Physics Laboratory, School of Earth and Environmental Sciences, Seoul National University, Seoul 151-742, South Korea. Email: hoch@cpl.snu.ac.kr

1. Introduction

Since the introduction of the tropical intraseasonal oscillation—the Madden–Julian oscillation (MJO)—into climate research by Madden and Julian (1971, 1972), extensive understanding of its dynamical origin has been gained and its relation with climate variables and influence on various weather/climate phenomena have been determined (Madden and Julian 1994; Zhang 2004; and many references therein). In particular, it is considered that the MJO fills up the so-called prediction gap between synoptic and seasonal forecasting because of its potential application to climate prediction on time scales of 30–60 days.

Many studies have investigated the direct influence of the MJO on weather/climate variations over the tropics: the tropical cyclone (e.g., Maloney and Hartmann 2000; Ho et al. 2006), deep cumulus convection (e.g., Madden and Julian 1972; Hendon and Salby 1994), and Indian and Australian monsoon (e.g., Wang and Rui 1990; Hendon and Liebmann 1990). The extent of MJO influence is not confined to the tropics. The MJO significantly modulates the weather/climate in the subtropics and midlatitudes. This subseasonal linkage between the tropics and the extratropics often has been explained by the framework of barotropic Rossby wave propagation forced by the Rossby wave source or by the excitation of the barotropic normal mode triggered by tropical convection. Recently, Kim et al. (2006) showed that the strong baroclinicity of the Asian–Pacific jet should be considered to explain the dipole pattern of the teleconnection. Hence, it is commonly accepted that the low-frequency variabilities in the midlatitudes exhibit a systematic linkage to the MJO life cycles (e.g., Lau and Phillips 1986; Simmons et al. 1983; Sardeshmukh and Hoskins 1988). Many studies have demonstrated such remote influences of the MJO on the weather phenomena in the extratropics: precipitation in the United States (e.g., Mo and Higgins 1998; Jones 2000; Bond and Vecchi 2003), South America (Paegle et al. 2000), and southwest Asia (Barlow et al. 2005); temperature in the northern high latitudes (Vecchi and Bond 2004); and cold surge occurrence in East Asia (Jeong et al. 2005). Even near-global impacts on precipitation are suggested (Donald et al. 2006)

Among the global midlatitudes where the anomalous circulation induced by the MJO extends, East Asia is known as the region in which the most dominant signals are observed. Although the prominent convective activities of the MJO are limited to the equatorial tropics from the Indian Ocean to the tropical western Pacific, highly energetic basic states over East Asia might enable the MJO-related perturbations to create strong systematic responses. For example, in relation to the MJO life cycle, the subseasonal fluctuation of the Asia–Pacific jet is well represented and is further linked to a north–south dipole of the streamfunction in the upper troposphere over the extratropical western Pacific (Knutson and Weickmann 1987; Hsu 1996). In particular, distinct anomalous vertical motion, associated with the subtropical divergence–convergence as a counterpart of the MJO, is found near the entrance region of the jet stream in East Asia. A recent diagnostic study by Kim et al. (2006) has suggested that a strong vertical motion occurs to meet the quasigeostrophic balance as the subtropical Rossby gyres of the MJO pass the strong baroclinic zone near the Asia–Pacific jet.

Despite the above-mentioned conspicuous subseasonal modulations by the MJO, detailed impact studies focused on East Asia have not been conducted sufficiently. Therefore, the present study explores the variation in wintertime precipitation and its related large-scale circulation features. A statistical analysis using daily station records and reanalysis data and dynamic diagnostics are performed in order to elucidate the relationship between the systematic variation in the precipitation and the large-scale circulations associated with the MJO.

This paper is organized as follows. A description of the data used and analysis technique is presented in section 2. In section 3, the variation in the precipitation over East Asia with respect to the MJO is explored and the intraseasonal vertical motion with coherent large-scale circulations is discussed. Further, dynamic diagnostics are also performed by applying the generalized ω equation. A summary and discussion are presented in section 4.

2. Data and analysis methods

a. Data

The daily precipitation in four countries in East Asia has been analyzed in this study. The surface stations include 187 Chinese, 8 Korean, 3 Taiwanese, and 41 Japanese meteorological stations, whose data were compiled from the China Meteorology Administration, Korea Meteorological Administration, Taiwanese Central Weather Bureau, and Japan Meteorological Agency, respectively. These stations are selected by considering their regional representative characteristics and suitable map spacing.

Information on the zonal and meridional wind, geopotential height, temperature, specific humidity, and vertical velocity was obtained from the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis (Kalnay et al. 1996) with a longitude–latitude resolution of 2.5° × 2.5°. The daily averaged interpolated outgoing longwave radiation (OLR) data produced by the Climatic Diagnostics Center (CDC) at the National Oceanic and Atmospheric Administration (NOAA) is utilized for analyzing the convective activity of the MJO (Liebmann and Smith 1996; available online at http://www.cdc.noaa.gov/cdc/data.interp_OLR.html). OLR data from 1 June 1974 to the present is available with a missing period from 1 March to 31 December 1978 due to satellite failure.

b. Composite analysis

The daily precipitation data of the 239 stations, daily anomalies of NCEP–NCAR reanalysis, and OLR data are used for composite analysis. To obtain the daily anomaly, the daily climatological cycle is subtracted from the raw data. Here, the daily climatological cycle is obtained from a 31-day running mean (±15 days) of the simple mean over every 365 days for the entire period. Then, composite analyses are performed in order to represent the systematic variation in the wintertime precipitation over East Asia and the coherent large-scale circulation features associated with the MJO.

To categorize the phase and amplitude of the MJO, the real-time multivariate MJO index (RMM) suggested by Wheeler and Hendon (2004) is adopted. The spatial-time evolution of the MJO is monitored on the basis of a pair of empirical orthogonal functions (EOFs) of the near-equatorial (15°S–15°N) averaged daily zonal wind at 850 and 200 hPa and the satellite-retrieved OLR data along the equator. The projection of the two leading multiple-variable EOFs onto the daily data produces a pair of normalized principal component (PC) time series (i.e., RMM1 and RMM2). The lead–lag behavior of the two leading PCs determines the phase of the eastward-propagating MJO, and the square root of the sum of the squares of these two PCs represents the relative MJO amplitude. In this study, the phase of the MJO, that is, the geographical location of the positive convection center associated with the MJO is divided into eight phases. Phase 1 denotes the center of the convective activities located near Africa; phase 2–3, the Indian Ocean; phase 4–5, the Maritime Continent; phase 6–7, the western Pacific; and phase 8, the eastern Pacific. The details of the MJO index and the real-time data compiled from 1974 to the present are available online at http://www.bom.gov.au/bmrc/clfor/cfstaff/matw/maproom/RMM/. The composite analysis is performed based on these phases and amplitude information during an active MJO period, when the amplitude of the MJO is greater than 1. The analysis period covers 26 winters from November to March, when the East Asian winter monsoon is usually dominant in East Asia (Ding 1994), for the period 1974/75–1999/2000, by considering the availability and quality of the data. The fraction of active MJO days to total analysis days is 63.09%.

c. Dynamic diagnosis of the vertical motion

Since the tropical influence of the MJO may result in complicated features due to an interaction with the large-scale circulation of the Asian winter monsoon, it is difficult to provide a physical explanation on the subtropical modulation of the precipitation by MJO. To overcome this difficulty, Kim et al. (2006) have used the generalized ω equation to determine the cause of the subtropical vertical motion, which is clearly observed during the MJO life cycle. They have shown that the interaction between the wintertime East Asian jet and the subtropical Rossby gyres induced by the tropical heating of the MJO can result in strong vertical motion near the East Asian jet region.

It appears plausible that the subtropical modulation of the precipitation by the MJO is related to the vertical motion described by Kim et al. (2006). To estimate the dynamic factor that contributes to the modulation of precipitation over the subtropics during the MJO life cycle, the vertical motion on the subseasonal time scale is examined by applying the quasigeostrophic ω equation to the composite anomalies described in the previous section. The quasigeostrophic ω equation adopted in this study is a simplified form of the generalized ω equation described in Krishnamurti (1968). Neglecting the intensification of vertical motion due to the small-scale motion, the linearized form of the quasigeostrophic ω equation can be written as follows:
i1520-0442-21-4-788-e1
where the overbar denotes the winter-mean basic state, terms grouped by FQG represent the quasigeostrophic forcing, those grouped by FH represent the diabatic heating, π = RT/pθ, and other parameters have their conventional meaning in the atmospheric sciences. In this formulation, terms involving the variation of static stability have been neglected because of the smallness of basic-state vertical velocity.

The forcing terms on the right-hand side can be directly estimated by using the composite anomalies and winter means of the zonal and meridional wind, temperature, and derived variables of vorticity (ζ) and streamfunction (ψ). Among various contributions to the diabatic heating, we examine only the latent heat released by the convective anomaly of the MJO. For this purpose, we assume that the horizontal pattern of latent heating is identical to that of the composite OLR anomaly. The vertical structure of heating is adopted from an idealized profile used by Jin and Hoskins (1995) that exhibits its maximum at 400 hPa. The multiplication of these two factors yields the three-dimensional heating rate. Since the formulation is linear, the contribution of each forcing term on the right-hand side can be assessed independently. The computational details are described in Kim et al. (2006).

Based on the above diagnostic tool, different dynamic origins of the vertical motion, which is generated by the tropical–extratropical interaction in each phase of MJO, are discussed in section 3c.

3. Results

a. MJO–precipitation relation in East Asia

During winter, a strong winter monsoon system is dominant over East Asia; it is accompanied by a prevailing northeasterly wind in the lower troposphere that originates from the vast anticyclonic circulation over Siberia (i.e., the Siberian high). As a consequence, most interior regions of East Asia have cold and dry weather. However, a relatively large amount of precipitation (approximately 2–4 mm day−1) is still found in some regions such as the eastern and southern coastal regions of China, Korea, and Japan (Fig. 1a). The day-to-day variability of this precipitation, that is, its standard deviation, shown in Fig. 1b, is very high and it reaches levels of approximately 6–10 mm day−1; this pattern is similar to that of the mean precipitation. This regional feature can be explained by the influence of the warm Kuroshio combined with the low-level East Asian winter monsoon circulation. When the cold continental air meets the relatively warm and moist air overlying the warm ocean surface, the enhanced synoptic activity due to the strong temperature gradient and moisture convergence leads to a large amount of precipitation in the vicinity of the well-developed coastal trough (Chan and Li 2004).

To understand the MJO–precipitation relation, we first examine the variations in the precipitation with respect to the MJO phase. Figure 2 shows the mean daily precipitation rate averaged during each MJO phase, represented as deviation from the winter-mean value of whole analysis period. The approximate location of the MJO convection center corresponding to each phase is described in each panel. The most notable variation is found in phase 2–3 (Fig. 2a), when the MJO-related convection center is located near the Indian Ocean. The precipitation increases considerably in most parts of the East Asian region except in northwest China. The magnitudes of the composite anomalies reach 1.5–2 mm day−1, which is comparable even to the winter-mean value (see Fig. 1a). The signals are statistically significant at the 99% confidence level over most of the East Asian region. In phase 4–5, the centers of the positive precipitation anomalies appear to move further south toward southern China, and those of the negative anomalies are found over mid-China and Korea (Fig. 2b). In phase 6–7, the variations in the precipitation exhibit a pattern similar to those of phase 2–3, but with a sign reversal (Fig. 2c). However, the signals are relatively weak, and meaningful signals are found only over the regions from southeast China to Japan. The MJO–precipitation relationship becomes significantly weaker during phase 8–1; however, the pattern is a mirror image of that in phase 4–5 (Fig. 2d).

The composite precipitation can be significantly changed by a relatively small number of heavy rainfall events. Hence, the frequencies of rainy days (days on which the daily rainfall is greater than 0.1 mm) and heavy rain days (days on which the rain intensity is within the top 10% among all the rainy days) are examined. In Figs. 3a and 3b, the difference between phases 2–3 and 6–7 is presented because their changes are the most prominent. For most parts of the East Asian region, the rainfall events in phase 2–3 generally increase by approximately 10%–30% in comparison with those in phase 6–7. The frequency of heavy rainfall events exhibits a similar pattern. However, the changes are relatively moderate; the difference is up to +10% relative to the total number of heavy rainfall events (Fig. 3b). As seen from the frequency distribution of precipitation (Fig. 3c), the increase in the rainy day frequency is evident in the entire precipitation category, and its rate of change between the two phases is roughly uniform. Accordingly, the categorized contribution to the total precipitation rates (Fig. 3d), manifested by the product of the frequency and accumulated precipitation in each phase, shows the importance of relatively light rain of less than 15 mm day−1. Therefore, the variation in the precipitation with respect to the MJO is deemed to result from the general strengthening of the precipitation rate and not from the extraordinary heavy rainfall events.

In summary, the composite results of the observation reveal the strong modulation of precipitation by the tropical MJO, both in amount and in frequency over East Asia. The following subsection discusses the systematic variation in the large-scale circulation that affects such a tropical–extratropical remote relation.

b. Coherent large-scale circulation

The eastward-propagating large-scale ensemble of westward-traveling mesoscale convective anomalies forms the center of the MJO (Hendon and Liebmann 1994). Such convective activities are mainly found in the tropical region from 15°S to 15°N during boreal winter (Sperber 2003; Wheeler and Hendon 2004). Hence, with regard to the geographical location of East Asia, the precipitation change with respect to the MJO in this region is hardly explained by a direct extension of MJO-related tropical convection. Instead, a remote response to the divergent dynamical/physical forcing of the tropical MJO would account for the changes in the large-scale circulation in the subtropics or midlatitudes, which, in turn, would induce anomalous precipitation in East Asia.

The composite distributions of the lower- and upper-tropospheric circulations and their corresponding convective activities are presented in Fig. 4. This figure shows a composite map of the streamfunction anomaly (ψ′) at 700 hPa for each of the four categorized MJO phases. Overall, in the tropical lower troposphere, two well-known Rossby gyres located west of the deep convection regions straddle the tropics, and a strong easterly (or westerly) wind anomaly, which can be substantially projected onto the equatorial Kelvin wave structure, exists on the eastern side along a narrow equatorial region. The general features of ψ700 are consistent with previous results (cf. Rui and Wang 1990; Wheeler and Hendon 2004).

In phase 2–3, two anomalous circulations with opposite signs, centered in the Middle East and the west of Madagascar, appear and combine into the Rossby gyres to provide a low-level convergence west of the convection center over the equatorial Indian Ocean (Fig. 4a). Large anticyclonic and cyclonic circulation anomalies also exist over the Pacific, which merge into the strong easterlies in the equatorial western Pacific. Turning into southwesterlies over South Asia, the wind moves along the coastline of the East Asian continent and circulates over the northern Pacific. In phase 4–5, the MJO convective center is located over the region from the Maritime Continent to the western Pacific (Fig. 4b). The Rossby gyres move toward the Indian Ocean, and their northern part is located over the region from the Indian continent to South–East Asia. The equatorial easterlies move eastward over the central Pacific and weaken slightly. During the phases 6–7 (Fig. 4c) and 8–1 (Fig. 4d) that occur in succession, the patterns are almost mirror images of those in phases 2–3 and 4–5, respectively.

The variation in the low-level moisture field (q′) vertically integrated from 1000 to 700 hPa is shown in Fig. 4. In particular, in the prominent phase 2–3 (6–7), the positive (negative) band of q′ appears to originate from the enhanced (suppressed) MJO convection center over the region from the Indian Ocean through the eastern coastline of East Asia to the south of Japan, accompanied by the southwesterlies (northeasterlies). Such patterns appear to be consistent with the composite precipitation patterns shown in Figs. 2 and 3 in that they are highly indicative of the influence of moisture transport on the variation in the precipitation over East Asia in concert with the low-level circulation. As the western Rossby gyres move farther eastward in phase 4–5 (8–1), cyclonic (anticyclonic) circulations dominate over East Asia. However, these signals are accompanied by negative (positive) moisture and its relation to precipitation appears to be weak.

In Fig. 5, the atmospheric circulation in the upper troposphere and MJO convective activity are denoted by ψ300 and the OLR, respectively. The positive (negative) values of ψ300 north of the enhanced (suppressed) MJO convective region are found in the subtropical region from northeastern Africa to the Indian continent in phase 2–3 (6–7) (Figs. 5a and 5c). Overall, in these two phases, a well-organized extratropical north–south dipole pattern is distinct in the extratropical North Pacific. However, the features of these two dipoles are nearly opposite in sign. In phase 2–3, the anticyclonic circulation, the northern part of the dipole, is centered over Japan (40°N, 135°E) and the cyclonic circulation is located just south of the northern part. Such a circulation pattern indicates the weakening of the climatological jet stream over East Asia. In contrast, in phase 4–5 (8–1), the subtropical anticyclonic (cyclonic) circulation stretches farther toward the South China Sea, and the extratropical dipole pattern is observed in the eastern Pacific with a slight change in shape (Figs. 5b and 5d).

It is notable that negative (positive) OLR anomalies are found over the East China Sea during phase 2–3 (6–7). Although their magnitudes are significantly less than those of the tropical MJO signals, the enhanced (decreased) convective activities are highly consistent with the variation in precipitation. Interestingly, counterparts for these anomalies are found in the Southern Hemisphere over southern Australia in both phases 2–3 and 6–7.

c. Vertical motion and its diagnostics

To delineate the physical mechanism associated with the significant precipitation anomalies over East Asia with respect to the MJO, the composite pressure velocity anomalies of the reanalysis data at each of the MJO phases are analyzed (Fig. 6). The vertical motion fields essentially reveal the global nature of the MJO convective activities in the tropics and the MJO teleconnection in the extratropics. The eastward-propagating cluster of vertical motion anomalies, that is, the MJO convective activities, is evident over equatorial latitudes, which is highly consistent with the OLR pattern in Fig. 5. In phase 2–3, the center of the enhanced vertical motion is located over the Indian Ocean, while in phase 4–5, it moves eastward along the equator toward the maritime continents. Reaching the western Pacific, the convective center appears to propagate along the South Pacific convergence zone (SPCZ) in phases 6–7 and 8–1 and dissipates toward the eastern Pacific. Further, the systematic variation in the vertical motion in the extratropics is clearly observed around the latitude 30°N. In contrast to the continuously moving tropical anomalies associated with the MJO convective activities, the extratropical anomalies of the pressure velocity appear to be localized over particular geographical regions. The two representative regions are East Asia and the Middle East, over the regions 20°–40°N, 110°E–180°, and 30°–80°E, where the climatological upper-level jet stream is located. This coincidence suggests the existence of a mutual relationship between the direct upper-level response of the tropical MJO and the wintertime subtropical jet. In phases 2–3 and 6–7, the composite anomalies of the pressure velocity near the East Asian region are outstanding, and their magnitudes are comparable to that at the tropical center of the MJO convection. It is noteworthy to compare these patterns with those in Fig. 2 in that the pressure velocity anomalies coincide well with the precipitation anomalies in East Asia; the upward (downward) motion anomalies during phase 2–3 (6–7) centered at 25°N, 125°E, largely explain the increase (decrease) in the precipitation field, and the weak precipitation increments (decrements) over Japan in phase 4–5 (8–1) also exhibit a strong relation with the vertical motion. With regard to other strong vertical motion anomalies near Middle East, the downward (upward) motion anomalies are observed during phase 2–3 (6–7) centered at 25°N, 45°E and those move eastward about 20° longitude in the phase 4–5 (8–1). Barlow et al. (2005) showed similar vertical motion change over this region associated with the MJO, which also accompanies with the strong modulation of daily precipitation. In comparison with the signals in the Northern Hemisphere, the signals in the Southern Hemispher extratropics are very weak. Relatively strong signals are found over the southwestern Pacific along the SPCZ.

The following is a diagnosis of the composite vertical motion field in a quasigeostrophic framework (see section 2c). Figure 7 shows the solution to the quasigeostrophic ω equation forced by each FQG (quasigeostrophic forcing) and (diabatic heating) in phases 2–3 (Figs. 7a and 7b) and 6–7 (Figs. 7c and 7d). By comparing the composite pressure velocities in Figs. 6a and 6c, it is clearly seen that the calculated pressure velocity forced by FQG (Figs. 7a and 7c) effectively explains the composite pressure velocity anomalies over the extratropics, particularly for East Asia, the Middle East, and the northern central Pacific near Hawaii.

The difference in the nature of the vertical motion related to the MJO teleconnection over the extratropics and the tropics is clearly observed by comparing Fig. 7a (Fig. 7c) and Fig. 7b (Fig. 7d). The vertical motion required by FH is largely confined to the tropics, where the MJO convective activities are pronounced. However, this vertical motion still appears to contribute to the vertical motion anomalies over East Asia. As suggested by Kim et al. (2006), the change in the latent heat release by anomalous convective activities results in additional vertical motion. Table 1 summarizes the relative contribution of FQG and FH to the vertical motion over East Asia (25°–40°N, 110°–135°E) in MJO phases 2–3 and 6–7. The diagnosis framework of current study accounts for about 60% (48%) of composited vertical velocity anomaly in MJO phase 2–3 (6–7). The FQG explains about half of the composite vertical motion anomalies shown in composite results (Fig. 6), but the contribution of FH is less than 10%.

One thing to note is that there can be a self-referential aspect to the diagnosed vertical motions by FQG and FH. The FH depends on the vertical velocity to some degree, of course, so it is not completely independent of the FQG. The diagnosis method in the present study cannot separate those two completely either; thus it should be rather emphasized that the MJO-induced vertical motion is really dominated by FQG outside of the tropics.

It should be also noted that the magnitudes of the vertical motion in phases 2–3 and 6–7 are asymmetrical. As shown in Figs. 6 and 7 and Table 1, particularly over East Asia, the magnitudes of the composite and calculated vertical motion anomalies are stronger in phase 2–3 than in phase 6–7. Interestingly, the same asymmetry exists in the result of the precipitation composite, as mentioned in section 3a; the magnitude of the precipitation increase in phase 2–3 is more prominent than the decrease in phase 6–7.

A similar diagnosis on MJO-induced vertical motion was performed by Barlow et al. (2005), but focused on West Asia instead of East Asia. Based on the thermodynamic equation, they showed that MJO temperature advection mostly contributes to vertical motion change over West Asia. Vertical motion change suggested in Barlow et al. (2005) is very similar to our composite results (Fig. 6) and appears to be mostly explained by FQG (Figs. 7a and 7c).

The diagnostic analysis leads to the conclusion that the nature of the remote vertical motion consonant with the tropical MJO is mainly due to the required quasigeostrophic balance caused by the prominent extratropical large-scale anomalies during the MJO. Furthermore, it appears that the modulation of the precipitation is closely related with this quasigeostrophic adjustment process.

d. Practical intraseasonal variation in vertical motion

Based on the statistical analyses and diagnostic ω equation, it is revealed that the dynamic relation between the vertical motion in East Asia and the tropical MJO is coherent. However, these coherences are, at best, derived by the analysis of the composite field; hence, its manifestation in practical weather/climate is still vague. Therefore, the assessment of the contribution of the vertical motion caused by the remote influence of the MJO with respect to the total natural variability is important. In this regard, we have additionally examined the vertical motion in East Asia using consecutive daily reanalysis fields to determine its intraseasonal variability and coherence to the MJO.

The power spectra of the wintertime daily anomalies of the average vertical velocity in East Asia (20°–50°N, 90°–150°E) is shown in Fig. 8a. The spectra are plotted as the logarithm of the frequency against the product of the frequency and power so that the variance is proportional to the area under the curve (Zangvil 1977). Most of the large (above the Markov red-noise spectrum; dashed curve) variance is on a synoptic to intraseasonal scale. The large variance on synoptic scale from 2 to 14 days is commonly expected from synoptic eddy activities, which are dominant in the extratropics. The large variance is also found on an intraseasonal scale (20–80 days) with two prominent peaks in approximately 30 and 45 days. Those peaks are statistically significant over the 95% confidence level and appear to be related to the tropical MJO.

Some observational and modeling analysis, however, suggest that internal processes within the extratropics can induce a separate intraseasonal oscillation with a period of approximately 40 days independent of the tropical activities (Simmons et al. 1983; Ghil and Mo 1991). By considering this, we examined the coherence between the vertical motion and the MJO. The lag correlations between the two RMMs and the vertical motion are shown in Fig. 8b. The two lag correlation curves have a periodicity of approximately 40 days and a phase difference of approximately 90°. The maximum correlation between the vertical motion and RMM2 is 0.76 at zero lag and −0.57 at a +9 day lag. The magnitude of the correlation of the raw time series (without bandpass filtering) is lower (0.44 with RMM2 at zero lag, 0.29 at −9 day lag); however, the value is still meaningful and significant, and the lead–lag phase relationship is nearly the same as that of the intraseasonal band. The lag correlation curve of RMM1 also exhibits a strong coherence with the vertical motion; it shows a lead over RMM1 of approximately 10 days, periodicity of approximately 40 days, and a maximum correlation of −0.57. Therefore, it is reasonable that substantial portion of the intraseasonal variation in the vertical motion seems to be directly related to the tropical MJO.

Specific examples of the intraseasonal modulation of the vertical motion with respect to the MJO are shown in Fig. 9. The two successive winters for the periods from November 1984 to April 1985 and November 1985 to April 1986 are selected, when the winter-mean amplitude of the MJO is greater than one standard deviation of the total years. The time–longitude plot (i.e., the Hovmöller diagram) of the OLR anomalies averaged over the tropical latitudes (15°S–15°N) are presented along with the time evolution of the vertical velocity averaged over the selected East Asian region. Two or three eastward-propagating enhanced (or suppressed) large-scale convective systems are observed in each winter. The vertical motion contains a major part of the synoptic variabilites; however, it still exhibits considerable intraseasonal variation, as shown in Fig. 8. Briefly, the vertical motion is covariant with the OLR anomalies over the western Indian Ocean (80°–100°E; the corresponding longitudes are indicated by thin vertical lines), as expected by the composite analyses and diagnostics of the vertical motion. Such coherence is particularly distinct when the MJO convective activities show clear eastward propagation from January to March 1985, January to February 1986, and March to April 1986.

4. Summary and discussion

This study demonstrates that the precipitation over East Asia varies significantly with respect to the MJO phase, and this variation reaches 1.5–2 mm day−1. The intraseasonal modulation of the large-scale circulation by the tropical MJO suggests that distinct changes in the low-level moisture transports and the vertical motion influence the MJO–precipitation relationship. Based on the diagnostic analysis of the generalized ω equation, it is revealed that the vertical motion is largely induced by quasigeostrophic forcings, and the associated latent heat release produces additional vertical motion.

These results indicate that the MJO systematically influences the extratropical weather/climate system, which may be helpful for synoptic or extended-range weather forecasting, considering the slow (approximately 5 m s−1) progression of the MJO. However, it should be noted that many limitations of the results in the present study are encountered when applied to practical weather/climate forecasting.

First, we focused only on the intraseasonal-to-intraseasonal relationship based on composite results. However, it can be speculated that the indirect modulation by the MJO can also affect the characteristics of the extratropical transient eddy activities. That is, the MJO induces a variation in the extratropical large-scale circulations, and then the changed basic flow further affects the genesis and growth of cyclones, or storm-track organization. Figure 10 exhibits this possibility that the synoptic activities are changed with respect to the MJO phase. The synoptic variance, derived by a 2–8-day bandpass-filtered meridional wind at 850 hPa, is mostly concentrated along the climatological position of the North Pacific storm tracks, but considerable synoptic variabilities are still found in East Asia along the northern flank of Tibetan Plateau to East Asian coastal trough (Fig. 10a). It is clearly observed that the synoptic variance generally increases (decreases) during the MJO phase 2–3 (6–7) as shown in Fig. 10b (Fig. 10c). This is consistent with the weakening (strengthening) of the upper-tropospheric jet in this region, as inferred from the dipole pattern (see Fig. 5). Over the coastal region of East Asia, the increase (decrease) in synoptic eddy activities is roughly coincident with the enhanced (suppressed) vertical motion and precipitation increase (decrease) in phase 2–3 (6–7). However, the dynamical interpretation of this eddy activity change appears to be very complicated to understand since the eddy activity usually increases when the baroclinicity of upper-tropospheric jet is strengthened. Our results would seem to indicate rather greater (weaker) eddy activity would tend to be associated with stronger (weaker) jet/greater baroclinicity in MJO phase 2–3 (6–7). The midwinter suppression of eddy activity suggested by Nakamura (1992) can be possibly related with this issue; there exists a wave saturation phenomenon when maximum wind speed of upper-tropospheric jet is stronger than critical maximum wind speed about 45 m s−1. The difference of zonal wind between phases 2–3 and 6–7 is about 7 m s−1 around East Asian upper-tropospheric jet, which can lead the wind speed to cross the critical value. More detailed examination is needed to address this issue.

Second, because of the limitation of composite analysis, the present study has only elucidated an overall look at the MJO-induced vertical motion and resulting daily precipitation variation in East Asia. Thus it should be noted for practical forecasting that the individual MJO events differ; there are significant variations in propagation speed and magnitude (i.e., growth and decay) of MJO. Those may complicate the forecasting of their effects.

Third, the wintertime precipitation over East Asia is largely determined by extratropical baroclinic eddies. Therefore, the extratropical large-scale circulation factors that modulate the characteristics of transient eddy activities, such as the East Asian winter monsoon circulation, Siberian high, and Arctic Oscillation (Thompson and Wallace 1998), may become major influences. The MJO should be considered as a supplementary influence on the intraseasonal time scale.

Fourth, even if such MJO–midlatitude teleconnection is completely understood, the proper simulation of MJO itself should be ensured for its practical usefulness to numerical weather/climate prediction. The simulation of MJO in the climate model is highly dependant on the underlying physical processes of the tropical convection, which still have considerable uncertainties, and hence most of atmosphere–ocean coupled models are not able to simulate a realistic MJO. Thus it is very restrictive to apply the present results to numerical prediction, but the empirical prediction of MJO and its application are more feasible for extratropical weather prediction.

Acknowledgments

This study was funded by the Korea Meteorological Administration Research and Development Program under Grant CATER 2006-4204. The authors sincerely appreciate the critical and valuable comments made by three anonymous reviewers.

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Fig. 1.
Fig. 1.

Climatological distribution of (a) daily-mean precipitation (mm day−1) and (b) its std dev.

Citation: Journal of Climate 21, 4; 10.1175/2007JCLI1801.1

Fig. 2.
Fig. 2.

Average precipitation rates (mm day−1) in each of the categorized MJO phases, represented as differences from the winter-mean values. Squares indicate the stations where the composite values are significant at the 99% confidence level.

Citation: Journal of Climate 21, 4; 10.1175/2007JCLI1801.1

Fig. 3.
Fig. 3.

Difference in (a) rainy day (≥0.1 mm day−1) and (b) heavy rain (top 10% precipitation amount) day frequency between MJO phases 2–3 and 6–7, represented as a percentile relative to the total number of rainy and heavy rain days, respectively. (c) Frequency distribution of precipitation (day−1) categorized by 5 mm day–1 intervals of precipitation rates in phases 2–3 and 6–7, averaged over all stations. The abscissa is the precipitation category (mm day−1), and the ordinate is the relative frequency (day−1) for each MJO period. (d) Product of the relative frequency and accumulated precipitation in each precipitation category, averaged over all stations (mm day−1).

Citation: Journal of Climate 21, 4; 10.1175/2007JCLI1801.1

Fig. 4.
Fig. 4.

Composite anomalies of the streamfunction at 700 hPa (contours, 0.5 × 106 m2 s−1) superimposed on the low-level specific humidity averaged from 1000 to 700 hPa (shading) in each of categorized MJO phases.

Citation: Journal of Climate 21, 4; 10.1175/2007JCLI1801.1

Fig. 5.
Fig. 5.

Composite anomalies of the streamfunction at 300 hPa (contours, 1.0 × 106 m2 s−1) superimposed on the OLR anomalies (shaded) in each of the categorized MJO phases.

Citation: Journal of Climate 21, 4; 10.1175/2007JCLI1801.1

Fig. 6.
Fig. 6.

Composite anomalies of the vertical velocity (contours, 1 × 10−3 Pa s−1, negative values are dashed) in each of the categorized MJO phase.

Citation: Journal of Climate 21, 4; 10.1175/2007JCLI1801.1

Fig. 7.
Fig. 7.

Results of the iterative calculation of the generalized ω equations; ω is forced by (a), (c) quasigeostrophic forcings (FQG) and by (b), (d) diabatic heating (FH) at 300 hPa using the composite fields in MJO phases 2–3 and 6–7.

Citation: Journal of Climate 21, 4; 10.1175/2007JCLI1801.1

Fig. 8.
Fig. 8.

(left) Power spectra of the daily anomalies of the vertical velocity in a selected region over East Asia (20°–50°N, 90°–150°E), calculated using the entire time series in winter. The thin solid curve represents the Markov red-noise spectrum, and two thin dashed curves represent 5% and 95% confidence intervals, respectively. The two vertical lines in the middle of the figure indicate 80 and 20 days, respectively. (right) Lag correlations between the vertical velocity averaged over the selected region and the two RMM series. The solid and dashed lines represent RMM2 and RMM1, respectively. The thick lines represent the values calculated by using the indices passing through the conventional 20–80-day filtering, and the thin lines are calculated by using the raw indices.

Citation: Journal of Climate 21, 4; 10.1175/2007JCLI1801.1

Fig. 9.
Fig. 9.

(left) Time–longitude plot of OLR anomalies averaged over tropical latitudes (15°S–15°N) (shaded). The contours indicate the 15-day moving averaged values. Thin vertical solid lines indicate 80° and 100°E longitude. (right) Vertical velocity anomalies averaged over the selected region in East Asia. The dashed line indicates the 15-day moving average time series.

Citation: Journal of Climate 21, 4; 10.1175/2007JCLI1801.1

Fig. 10.
Fig. 10.

(a) Synoptic variance (2–8 days) of the meridional wind at 850 hPa. The regions where the synoptic variance explains more than 40% of the total variance are stippled. (b), (c) Synoptic variance during the categorized MJO phases relative to the total synoptic variance.

Citation: Journal of Climate 21, 4; 10.1175/2007JCLI1801.1

Table 1.

Spatially averaged values of diagnosed vertical motion forced by FQG and FH over East Asia (25°–40°N, 110°–135°E) in MJO phases 2–3 and 6–7 (Pa s−1). Percentage values in parentheses are their relative fractions to the same values of composited results in Fig. 6.

Table 1.
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