A Diagnostic Study of the Evolution of the MJO from Indian Ocean to Maritime Continent: Wave Dynamics versus Advective Moistening Processes

Ching-Shu Hung Department of Atmospheric Science, National Taiwan University, Taipei, Taiwan

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Chung-Hsiung Sui Department of Atmospheric Science, National Taiwan University, Taipei, Taiwan

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Abstract

The evolution processes for propagating Madden–Julian oscillations with strong magnitude over the Indian Ocean (IO) and Maritime Continent (MC) are investigated through a diagnosis of ECMWF reanalysis data for November–April 1982–2011. A scale-separated lower-tropospheric (1000–700 hPa) moisture budget is analyzed for four stages of composite life cycle: suppressed, cloud developing, convective, and decaying. Overall, the budgets in the IO and MC are dominated by wave-induced boundary layer convergence in the anomalous easterlies (WC) and advection. Starting from the suppressed stage in the central IO, moistening by WC and advection by easterly anomalies contributes to an initiation of the MJO convection in the western IO while surface evaporation and/or shallow convection moistens the central IO. In the following cloud developing and convective stage in the central IO, moistening by WC and advection by the downstream Kelvin–Rossby wave east of central IO lead to eastward propagation of deep convection. In the MC, the suppressed stage coincides with the convective stage in the central IO that promotes anomalous easterlies, subsidence, and enhanced rain rate over islands. Unlike WC and advective moistening in the IO that both occur in the equatorial zone, advective moistening in MC tends to be negative (positive) on windward (leeward) side of the major islands in the equatorial zone and more organized over the Arafura Sea, conducive to a southward detour of the eastward-propagating MJO.

Denotes content that is immediately available upon publication as open access.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Chung-Hsiung Sui, sui@as.ntu.edu.tw

Abstract

The evolution processes for propagating Madden–Julian oscillations with strong magnitude over the Indian Ocean (IO) and Maritime Continent (MC) are investigated through a diagnosis of ECMWF reanalysis data for November–April 1982–2011. A scale-separated lower-tropospheric (1000–700 hPa) moisture budget is analyzed for four stages of composite life cycle: suppressed, cloud developing, convective, and decaying. Overall, the budgets in the IO and MC are dominated by wave-induced boundary layer convergence in the anomalous easterlies (WC) and advection. Starting from the suppressed stage in the central IO, moistening by WC and advection by easterly anomalies contributes to an initiation of the MJO convection in the western IO while surface evaporation and/or shallow convection moistens the central IO. In the following cloud developing and convective stage in the central IO, moistening by WC and advection by the downstream Kelvin–Rossby wave east of central IO lead to eastward propagation of deep convection. In the MC, the suppressed stage coincides with the convective stage in the central IO that promotes anomalous easterlies, subsidence, and enhanced rain rate over islands. Unlike WC and advective moistening in the IO that both occur in the equatorial zone, advective moistening in MC tends to be negative (positive) on windward (leeward) side of the major islands in the equatorial zone and more organized over the Arafura Sea, conducive to a southward detour of the eastward-propagating MJO.

Denotes content that is immediately available upon publication as open access.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Chung-Hsiung Sui, sui@as.ntu.edu.tw

1. Introduction

The Madden–Julian oscillation (MJO) is the dominant intraseasonal variability in the tropical atmosphere. It can be described as a tropical planetary-scale circulation system coupled with a multiscale convective complex and propagating eastward slowly with a rearward tilted vertical structure and a mixed Kelvin–Rossby wave horizontal structure (Madden and Julian 1972; Wheeler and Kiladis 1999; Wheeler et al. 2000; Kiladis et al. 2005; Wang 2012). The planetary-scale circulation anomalies associated with the MJO significantly modulate the tropical weather, such as monsoon onset, tropical cyclone genesis, and ENSO development. Through tropical–extratropical teleconnections, the MJO can influence the midlatitude weather as well. Therefore, understanding the dynamics of the MJO is important for the diagnosis and prediction of global weather and climate. However, state-of-art general circulation models (GCMs) still simulate the MJO with an unsatisfactory skill (e.g., Ahn et al. 2017), and recent studies have shown that there is a gap of 20–25 days between the potential and practical predictability of the MJO (H.-M. Kim et al. 2014; Neena et al. 2014). To improve the MJO simulation and to advance the medium-range predictability, a better understanding of the fundamental processes driving the MJO dynamics (e.g., the slow eastward propagation, intraseasonal time scale, planetary zonal scale, and interaction with convection) is required.

A variety of theories have been proposed to explain the growth and propagation of the MJO. They can be roughly separated into two categories: dynamics and thermodynamics. The former explains the MJO by forced tropical wave dynamics, whereas the latter emphasizes the role of physical processes (e.g., moistening, surface turbulent fluxes, and radiative fluxes). Yet, it should be noted that most of the theories in the second set also require coupling to the dynamics, such as the coupled Kelvin–Rossby wave (e.g., Emanuel 1987; Neelin et al. 1987).

In the wave dynamics theories, the MJO is first interpreted as viscous Kelvin waves by Chang (1977) and further elaborated by Lau and Peng (1987) as moist Kelvin–Rossby waves with an instability arising from the interaction between convective heating and large-scale wave motion, known as the wave-conditional instability of the second kind (wave-CISK). This convective coupling reduces the effective static stability and thus slows down the propagation speed of Kelvin wave (~19 m s−1). The intraseasonal period of the MJO is determined by the time needed for the moist Kelvin wave to circumnavigate the globe. However, the speed of the moist Kelvin wave is still significantly faster than the observed MJO propagation speed (~5 m s−1), and the mode is most unstable in small wavelength, which is opposite to the observed planetary zonal scale. To solve these problems, Wang and Li (1994) introduced a boundary layer into the traditional wave-CISK model framework. The heating associated with the boundary layer friction-induced convergence ahead of the free tropospheric wave convergence can couple the Kelvin and Rossby waves and select a slow eastward propagation with a planetary zonal scale (Wang and Chen 2017).

The second set of theories include the recharge–discharge theory (Bladé and Hartmann 1993; Hu and Randall 1994; Kemball-Cook and Weare 2001; Stephens et al. 2004; Benedict and Randall 2007), wind–evaporation feedback (Emanuel 1987; Neelin et al. 1987), cloud–radiative feedback (Hu and Randall 1994; Andersen and Kuang 2012), and moisture mode theory (Raymond 2001; Sobel and Maloney 2012, 2013; Adames and Kim 2016). Several observational studies have shown that the development and propagation of the MJO are closely related to atmospheric moisture, radiation, and surface turbulent fluxes (Sobel et al. 2014; Johnson et al. 2015; Tseng et al. 2015). Moreover, the MJO simulations in some GCMs are also improved when convection is made more sensitive to environmental moisture (Hannah and Maloney 2011) and become weaker when cloud–radiative interaction is turned off (Andersen and Kuang 2012; Crueger and Stevens 2015). The one-dimensional modeling study by Hu and Randall (1994) has demonstrated that the interactions among radiation, convection, and surface turbulent fluxes can set up an oscillating diabatic heat source with a period similar to that of the observed MJO, and the time scale of this oscillation is determined by the recharge and discharge time of local instability. This gradual buildup of local instability is well consistent with the cloud evolution of the MJO from shallow cumuli and congestus cloud to deep convection (Benedict and Randall 2007). Through the diagnosis of moisture and moist static energy (MSE) budget, some key processes contributing to the evolution of local instability are identified. While horizontal and vertical moisture advection are responsible for eastward propagation, growth and maintenance are associated with radiation and surface turbulent fluxes (e.g., Sobel et al. 2014; Tseng et al. 2015; Kerns and Chen 2014; D. Kim et al. 2014; Zhao et al. 2013; Hsu and Li 2012; Maloney 2009; Kiranmayi and Maloney 2011).

Many studies have discussed the role of moisture, radiation, and surface turbulent fluxes in the development and propagation of the MJO, but most of them focus on the Indian Ocean, where the MJO initiates and starts propagating eastward. However, the eastward propagation is not a smooth path, as the strength of convective activities changes substantially in different locations. For a typical MJO life cycle, the convective envelopes initiate from the western Indian Ocean, strengthen over the central Indian Ocean, bifurcate while passing through the Maritime Continent, reintensify upon reaching the western Pacific, and finally dissipate around date line. The key processes identified over the Indian Ocean may not be of equal importance in other regions, especially over the Maritime Continent. The complex topography and land–sea contrast over the Maritime Continent strongly modulate the MJO convective envelopes as they pass through. Wu and Hsu (2009) suggest that the distribution of mountainous islands seems to result in the southward detour of the eastward-propagating MJO and the sudden shift of deep convection between major islands. The topographic blocking and mountain wave–making effect create extra lifting and sinking within the large-scale circulation of the MJO. Peatman et al. (2014) further found that the strong diurnal cycle over land and coastal regions interacts with the large-scale circulation of the MJO and causes the vanguard of precipitation jumping ahead of the main MJO convective envelopes by six days (approximately one phase).

Apart from the distinct regional difference, the variation among individual MJO events is also significant. Some studies point out that the circulation of preceding MJO events may help to generate the next MJO (Matthews 2008; Zhao et al. 2013; D. Kim et al. 2014) and the model prediction skill of the MJO becomes better when the forecasts are initialized with a strong MJO compared to those initialized with a weak or nonexistent MJO (H.-M. Kim et al. 2014). Therefore, the identification of individual attribution from current and previous events is crucial to advance understanding for the initiation and propagation mechanism of the MJO and to improve model prediction skills.

Previous studies have identified several key processes controlling the MJO evolution through the diagnosis of moisture and MSE budget over the Indian Ocean (e.g., Sobel et al. 2014; Tseng et al. 2015; Kerns and Chen 2014; Hsu and Li 2012; Zhao et al. 2013; D. Kim et al. 2014; Jiang 2017). Zhao et al. (2013) and D. Kim et al. (2014) suggest that horizontal advection induced by the downstream suppressed convection drive the eastward propagation, while Hsu and Li (2012) emphasized the role of wave-induced boundary layer moisture convergence in anomalous easterlies. With respect to growth and maintenance, Sobel et al. (2014) suggest that radiation and surface turbulent fluxes are the key processes, whereas Zhao et al. (2013) point out that zonal advection by the downstream suppressed convection contributes to the initiation over western Indian Ocean. The eastward propagation mechanisms of the MJO from Indian Ocean to Maritime Continent have also been explored, with some studies stressing advective moistening and others underlining the role of wave-induced boundary layer convergence (Feng et al. 2015; de Szoeke et al. 2015; Adames and Wallace 2015; DeMott et al. 2016; Kim et al. 2017). Building on this body of research, this study aims to investigate the relative contribution of large-scale wave dynamics, advective moistening, radiation, and surface turbulent fluxes to the convective initiation, propagation, and maintenance of successive MJO events (Matthews 2008) with 30-yr reanalysis data. The contrast between the propagation mechanisms over the Indian Ocean and Maritime Continent and the possible effect of the Maritime Continent are discussed. The remainder of this article is organized as follows. Section 2 describes the data and methods of analysis employed in this study. In section 3, the evolution of composite successive MJO events is discussed through the diagnosis of moisture and MSE budget. Finally, concluding remarks are offered in section 4.

2. Data and methods

a. Data

The datasets used in this study include 1) the interpolated daily outgoing longwave radiation (OLR) obtained from National Oceanic and Atmospheric Administration (NOAA) polar-orbiting satellites (Liebmann and Smith 1996) and 2) the ERA-Interim data from the European Centre for Medium-Range Weather Forecasts (ECMWF). The abovementioned data are available from the website of the NOAA/OAR/ESRL PSD (Boulder, Colorado; https://www.esrl.noaa.gov/psd/data/gridded/data.interp_OLR.html) and ECMWF (https://www.ecmwf.int/en/forecasts/datasets/archive-datasets/reanalysis-datasets/era-interim). The OLR data are used to represent the deep convection and to identify significant intraseasonal oscillation (ISO) events. They have a horizontal resolution of 2.5° × 2.5°, with temporal resolution of 1 day. The ERA-Interim data are utilized to diagnose the moisture and MSE budget and to describe the overall structure of the MJO. They contain zonal and meridional winds, vertical pressure velocity, geopotential, and specific humidity at 20 levels from 1000 to 100 hPa. In addition, the surface product is used to estimate the boundary fluxes at the surface and top of the atmosphere (e.g., longwave and shortwave radiative flux and surface latent and sensible heat flux). To unify the resolutions among datasets, the 6-hourly 1.5° ERA-Interim data are interpolated into daily and 2.5° grid. The 0.75° ERA-Interim dataset is further used in section 3c to portray detailed structures over the Maritime Continent. The analysis covers the period from 1982 to 2011.

b. Bimodal ISO indices: The MJO and BSISO mode

Given the observational evidence that the ISO shows distinct behaviors between two solstice seasons, the traditional all-season real-time multivariate MJO (RMM) index (Wheeler and Hendon 2004) may not resolve the regional features of the annual variation properly (e.g., Lee et al. 2013). Therefore, the method developed by Kikuchi et al. (2012) is adopted to construct bimodal ISO indices. An empirical orthogonal function (EOF) analysis is performed on the 25–90-day fast Fourier transform (FFT)-filtered OLR in the tropical region (30°S–30°N) during boreal winter (DJF) and summer (JJA), with the resultant two leading EOF modes defined as the MJO (Fig. 1) and boreal summer intraseasonal oscillation (BSISO) mode. The 25–90-day filtered OLR data are then projected onto the two leading EOF modes derived from winter and summer season respectively to obtain the corresponding principal components (PCs). The normalized PCs of the MJO and BSISO mode then form the bimodal ISO indices in a way similar to the RMM index, with amplitude representing strength and phase angle representing its phase time. Days with amplitude greater than one are identified as significant events for each mode. More detail can be found in Kikuchi et al. (2012). The composite eight-phase life cycle and seasonal distribution (figure not shown) of the two modes are in good agreement with Kikuchi et al. (2012). Whereas the MJO mode shows a predominant eastward propagation along the equator with a southward detour over the Maritime Continent during December–April, the BSISO mode has a prominent northward propagation in off-equatorial monsoon trough regions during June–October. May and November are the transitional months with comparable active days between the MJO and BSISO. In current study, we focus on the boreal winter MJO mode only. The BSISO mode will be analyzed in future study.

Fig. 1.
Fig. 1.

EOF patterns of 25–90-day filtered OLR during boreal winter (DJF). Percentages in parentheses show the contribution of each EOF mode to total variance. OLR values are multiplied by one standard deviation of the corresponding PCs to obtain a typical value and unit (W m−2) for ISOs.

Citation: Journal of Climate 31, 10; 10.1175/JCLI-D-17-0139.1

c. Successive and primary events

Since some conventional MJO analysis techniques (e.g., lag regression) tend to produce a repeating MJO cycle, it is difficult to separate the individual attribution from current and previous events. To explore this issue, Matthews (2008) utilized the phase diagram of an OLR-based MJO index to classify the MJO into primary and successive events. First, he divided the MJO life cycle into four categories (A, B, C, and D). Category A contains the traditional RMM phases 2 and 3, category B includes phases 4 and 5, and so forth. A complete MJO life cycle is represented by the string ABCD. Second, the days with amplitude below critical value (Ac = 0.4) were assigned to category N, denoting weak MJO signals. Finally, the primary MJO events with no preceding cycle of MJO were defined as NABCD, whereas the successive MJO events influenced by previous MJO were defined as DABCD. It should be noted that, under this definition, the selected successive events could either actually follow on from a precedent MJO event (primary or successive) or simply start with a strong suppressed convection over the Maritime Continent, marked by the category D, without a complete MJO cycle ahead. In our study, we extend this case selection method to the bimodal ISO indices derived in section 2b to identify both MJO and BSISO events. Based on the bimodal ISO index of the MJO mode with Ac setting to one, 22 successive and 5 primary events with strong magnitude (i.e., amplitude larger than 1) and clear propagation (i.e., complete anticlockwise circuit) are selected during the period of interest, 1982–2011. Examples of one successive and primary MJO event are presented in Fig. 2. As can be seen, both events show strong eastward propagation signals in the Hovmöller diagram (Figs. 2a,b) and go through complete anticlockwise circuits in the phase diagram constructed by PCs (Figs. 2c,d). However, the successive event has clear eastward propagating anomalies prior to its initiation, whereas the primary event has no coherent signal before initiation. This structure difference is consistent with the composite result presented by Straub (2013), which selects successive and primary events based on RMM index. The local precursor signals, such as the low-level easterlies over the Indian Ocean and suppressed convection over the western Pacific, identified by Straub (2013), are also seen in some of the primary events selected in this study (figure not shown). In this study, only the successive MJO events are analyzed. The primary events occurring infrequently with large irregularities are subject to individual case studies in the future.

Fig. 2.
Fig. 2.

(a) Hovmöller diagram of 10°S–10°N averaged, 20–60-day filtered OLR (shading; W m−2) and 1000–700-hPa averaged zonal winds (contours; interval of 1 m s−1) for a successive event with a 101-day period (day 0 ± 50 days) from 15 Feb to 26 May 1990. Day 0 is defined as the day when the amplitude of PCs is maximum in category A. (c) The corresponding phase diagram for the successive event in (a). The first (t = −50), central (t = 0), and last (t = 50) days are denoted by a filled circle, a filled diamond, and a filled square, respectively. (b),(d) As in (a),(c), but for a primary event with a 101-day period from 10 Dec 2000 to 20 Mar 2001. The letter N denotes the region where the amplitude is smaller than 1. See text for details.

Citation: Journal of Climate 31, 10; 10.1175/JCLI-D-17-0139.1

d. Scale-separated moisture and MSE budget

The budget analysis of the selected MJO events is performed based on the ERA-Interim. To further examine the contribution of nonlinear scale interaction to intraseasonal variability, a scale-separated lower-tropospheric moisture budget is calculated by decomposing moisture q and zonal, meridional, and vertical winds, u, υ, and ω, respectively, each into three components [a = a1 + a2 + a3; where a1, a2, and a3 denote low-frequency (LF; >60 days), MJO (20–60 days), and high-frequency (HF; <20 days) bands, respectively], and the contributions of each component to the MJO-scale moisture tendency are estimated by
e1
where the prime denotes the bandpass filtered at MJO scale and the square brackets denote vertical integration in the lower troposphere from the surface to 700 hPa. The residual of the moisture budget, known as the moisture sink Q2, includes the subgrid-scale contributions of condensation c, evaporation e, and eddy moisture flux convergence (Yanai et al. 1973):
e2
The column-integrated Q2, defined as vertical integration from the surface PS to the top PT of the troposphere, represents the net moisture sink between precipitation P and surface evaporation E:
e3
To further identify the role of radiation and surface turbulent fluxes, a column-integrated MSE budget is analyzed by the equation
e4
The notation is same as the moisture equation except that h represents MSE and the angle brackets now denote vertical integration from the surface to 100 hPa. The residual of the dry static energy (DSE) budget, known as the apparent heat source Q1, includes the subgrid-scale contribution of c e, radiative heating QR, and eddy DSE flux convergence (Yanai et al. 1973):
e5
The column-integrated Q1 represents the net heating between precipitation, surface sensible heat flux SH, longwave radiation LW, and shortwave radiation SW:
e6
where Δ is defined as the difference between the values at the surface and the top of the atmosphere.

3. Composite result of successive MJO events

In this section, the evolution of the successive MJO is analyzed based on the composite of the 22 events identified in section 2c. The reference day (day 0) in each event is defined as the day when the amplitude in phase diagram is at its maximum in category A (the red diamond in Fig. 2c), which corresponds to the convective active phase over the Indian Ocean.

a. Large-scale environment and MJO overall evolution

The column-integrated LF moisture and low-level wind fields averaged over all composite days are shown in Fig. 3a. In the Indo-Pacific warm pool region where the MJO is most active, moisture gradually increases eastward toward the Maritime Continent, and low-level off-equatorial easterlies converge equatorward and further turn into westerlies over the equatorial Indian Ocean. Several studies have suggested that these mean state features significantly influence the evolution of the MJO. From the 32-yr reanalysis, Kim et al. (2017) reveal that the steeper zonal gradient of mean moisture in the southern Maritime Continent than in the central Maritime Continent results in stronger moisture advection over the southern Maritime Continent, causing the southward detour of the MJO. On the other hand, by inspecting 23 GCM simulations Gonzalez and Jiang (2017) found that the MJO eastward propagation is highly correlated with the model skill of the Maritime Continent winter mean low-level moisture pattern, which was poorly simulated in models with low MJO skill. To reveal the relationship between mean state and intraseasonal variability, mean precipitation during boreal winter is superimposed onto the standard deviation of 20–60-day filtered OLR (Fig. 3b). As can be seen, the maximum MJO activity coincides with the seasonal mean precipitation zone, suggesting the large-scale control of mean circulation on the MJO. The result also shows a significant land–sea difference in the Maritime Continent where the climatological precipitation maximizes over main islands including Sumatra, Borneo, and New Guinea (Qian 2008) while intraseasonal variability is stronger over the surrounding oceans (Sobel et al. 2010). This distinct land–sea difference might relate to the active diurnal cycle over land and coastal regions. Peatman et al. (2014) reports that 80% of the MJO precipitation signal over the Maritime Continent is accounted for by changes in the amplitude of the diurnal cycle. Since the MJO activity, mean state fields, and topographic distribution vary significantly over the Indo-Pacific warm pool regions, detailed diagnoses of the MJO structure and budget balance are conducted and discussed over the central Indian Ocean and the Maritime Continent respectively as specified in Fig. 3b.

Fig. 3.
Fig. 3.

(a) The 1000–100-hPa integrated LF moisture (shading; mm) and 1000–700-hPa averaged LF wind fields (vector; m s−1). (b) Standard deviation of 20–60-day filtered OLR (shading; W m−2) and seasonal mean precipitation (contours; mm day−1) during boreal winter. The purple boxes mark the locations of two MJO activity centers: the CIO (10°S–10°N, 70°–90°E) and MC (12.5°S–7.5°N, 100°–155°E).

Citation: Journal of Climate 31, 10; 10.1175/JCLI-D-17-0139.1

The overall evolution of the successive events is illustrated in Fig. 4a. Two slowly eastward-propagating (~5 m s−1) convective envelopes with one following the other are revealed. Although the eastward propagation of convection is clear, regional variation is distinct. The large-scale convective envelopes initiate from the western Indian Ocean (WIO; 50°–70°E), strengthen over the central Indian Ocean (CIO; 70°–90°E), weaken while passing through the Maritime Continent (MC; 100°–120°E), reintensify upon reaching the western Pacific (WP; 130°E–180°), and finally dissipate around the date line. From Fig. 4a, it can be seen that the initiation of convection over the WIO (day −15) is preceded by an increase of lower-tropospheric moisture anomalies at about −10 days. After the initial development over the WIO, the increased (decreased) low-level moisture to the east (west) of the MJO convection center further leads to the eastward propagation (Hsu and Li 2012). This low-level moisture buildup to the east of the convection center is illustrated more clearly in Fig. 4b. While convection (green line; Fig. 4b, bottom) is most active over the Indian Ocean and is in phase with column-integrated moisture (light blue line), the low-level moisture tongue expanding from the surface to 700 hPa (blue line) has already developed in the Maritime Continent. This zonal asymmetry of low-level moisture can be seen through the entire MJO life cycle.

Fig. 4.
Fig. 4.

(a) Composite Hovmöller diagram of 10°S–10°N averaged, 20–60-day filtered OLR (shading; W m−2) and 1000–700-hPa integrated lower-tropospheric moisture (contours; interval of 0.4 mm). The purple solid (dashed) lines mark the location of OLR max (min). The red letter D, denoting category D defined in section 2c, indicates the suppressed convection associated with previous event. (b) The top panel shows the zonal distribution of 10°S–10°N averaged, 20–60-day filtered moisture (shading; g kg−1) [y axis is pressure (hPa)]; the bottom panel shows 1000–100-hPa integrated moisture (light blue), 1000–700-hPa integrated moisture (medium blue), and OLR (green) at pentad day 0. (c) Composite time series of 20–60-day filtered OLR (green solid line) and 1000–700-hPa integrated lower-tropospheric moistures (blue line) over the CIO. The composite life cycle is divided into four stages (see text for definition) shown by shading: suppressed (red), cloud developing (blue), convective (green), and decaying (pink). Numbers above the x axis are the corresponding MJO bimodal index phase. (d) As in (c), but for the MC.

Citation: Journal of Climate 31, 10; 10.1175/JCLI-D-17-0139.1

Following the definition proposed by Tseng et al. (2015), the MJO life cycle is further separated into four stages based on the evolution of OLR and low-level moisture anomalies (Figs. 4c,d): suppressed (OLR′ is positive and [q]′ is low), cloud developing (OLR′ turns negative and [q]′ grows to a maximum), convective (OLR′ reaches maximum), and decaying (OLR′ increases and [q]′ decreases). The above four stages roughly correspond to the MJO bimodal index phases 567, 81, 2, and 34 for the CIO (Fig. 4c) and 781, 23, 4, and 56 for the MC (Fig. 4d). The vertical structure of important thermodynamic and dynamic fields during the four stages over the CIO (solid line) and MC (dashed line) are shown in Figs. 5a–d. In the suppressed stage, intraseasonal downward motion causes a strong dryness in the middle troposphere and associated anomalous easterlies in the lower troposphere. In the cloud developing stage, as low-level moisture has been built up, the atmosphere becomes relatively unstable, which provides favorable conditions for convection to develop and changes the environment into upward motion. In the convective stage, the middle troposphere becomes rather moist, with strong upward motion peaking at 300–400 hPa and anomalous westerlies establishing in the lower troposphere. In the decaying stage, the westerlies become strong and extend to the middle troposphere, while low-level moisture anomalies now turn negative with downward motion developing in the lower troposphere. The vertical structure over the MC is generally consistent with that over the CIO but of weaker amplitude except that the zonal wind anomalies during the convective stage differ in the two regions. Such a difference implies different advective moistening in the IO and MC as will be discussed in sections 3c and 3d.

Fig. 5.
Fig. 5.

Vertical structure of 20–60-day filtered (a) moisture (L is absorbed into q), (b) MSE, (c) pressure velocity, and (d) zonal winds during four stages (suppressed in red, cloud developing in blue, convective in green, and decaying in pink) over the CIO (10°S–10°N, 70°–90°E; solid lines) and MC (12.5°S–7.5°N, 100°–155°E; dashed lines).

Citation: Journal of Climate 31, 10; 10.1175/JCLI-D-17-0139.1

b. Lower-tropospheric moisture budget: Overall evolution

Since the buildup of low-level moisture is essential to the development of the MJO convection, a 1000–700-hPa integrated moisture budget is performed to diagnose the key processes responsible for the moisture evolution. Figure 6 exhibits the Hovmöller diagram of the anomalous lower-tropospheric moisture budget terms together with the moisture anomalies. The result shows that vertical advection (Fig. 6b) and −Q2 (Fig. 6c) in phase and out of phase with moisture anomalies respectively are the dominant terms with magnitude one order larger than tendency (Fig. 6a) and horizontal advection (Fig. 6d). Since these two terms are mostly out of phase and thus cancel each other, the overall evolution of tendency bears a strong resemblance to the horizontal advection. Note, however, that an overall projection of vertical advection on moisture tendency is positive and comparable to the projection of horizontal advection on moisture tendency as shown in Fig. 7 (to be discussed below). The horizontal advection term has a prominent positive contribution around 100°E–180° between negative and positive moisture anomalies, suggesting its important role for the eastward propagation over the MC and WP (e.g., Kiranmayi and Maloney 2011; Wolding and Maloney 2015; D. Kim et al. 2014). On the other hand, over the IO, moistening from horizontal advection occurs when moisture anomalies are also positive, and this in-phase relation would further amplify the moisture anomalies and contribute to the growth and maintenance of the MJO convection (e.g., Adames and Wallace 2015). To identify the process responsible for the horizontal advection, the advection term is further decomposed into its zonal and meridional parts. The result shows that while meridional advection (Fig. 6f) dominates over the MC and WP and mostly contributes to the eastward propagation, zonal advection (Fig. 6e) plays a more important role for the growth over the IO.

Fig. 6.
Fig. 6.

Composite Hovmöller diagram of 10°S–10°N averaged, 20–60-day filtered 1000–700-hPa integrated lower-tropospheric moisture budget terms (shading; W m−2): (a) tendency, (b) vertical advection, (c) −Q2, (d) horizontal advection, and (e) zonal and (f) meridional advection. Budget terms are shown only when they are statistically significant at 95% confidence level. Contoured in each panel is the lower-tropospheric moisture anomalies with contour interval of 1 × 106 J m−2 (L is absorbed into q). The purple solid (dashed) lines mark the location of OLR max (min).

Citation: Journal of Climate 31, 10; 10.1175/JCLI-D-17-0139.1

Fig. 7.
Fig. 7.

Projection of scale-separated 1000–700-hPa integrated lower-tropospheric moisture budget terms to local moisture tendency over the (a) CIO (10°S–10°N, 70°–90°E) and (b) MC (12.5°S–7.5°N, 100°–155°E), showing, for both (a) and (b), the total moisture budget in the top panel, scale-separated vertical advection in the middle panel, and scale-separated horizontal advection in the bottom panel (a1 for LF; a2 for MJO; and a3 for HF). All terms are normalized by the projection of moisture tendency itself (all variables are nondimensional); 95% statistically significant budget terms are shown in red, with vertical bars denoting the standard deviation.

Citation: Journal of Climate 31, 10; 10.1175/JCLI-D-17-0139.1

The influence of scale interaction on intraseasonal variability is further investigated by the scale-separated budget described in section 2d. To determine the relative contribution of different processes to local moisture evolution, the time series of each budget term is projected onto time series of local tendency. It is calculated as
e7
where f represents each budget term and the angled brackets denote the inner product (Andersen and Kuang 2012). Since the MJO is an eastward propagating disturbance, the projection onto local tendency can be interpreted as the contribution to eastward propagation. The result shows that, over the central IO (Fig. 7a), both horizontal (especially the zonal component) and vertical advection have positive contributions to the tendency, whereas the contribution from the subgrid-scale processes (−Q2) is negative. As found in much research (Hsu and Li 2012; D. Kim et al. 2014; Gonzalez and Jiang 2017), the leading term in the moisture advection, both horizontal and vertical, is the advection of LF moisture q1 by the MJO flow U2. On the other hand, over the MC (Fig. 7b) the eastward propagation is dominated by horizontal advection with insignificant contribution from vertical advection and −Q2. Nonlinear advection by synoptic disturbances (v3 ⋅ ∇q3) also has a relatively small but nonnegligible contribution as revealed by Andersen and Kuang (2012) in the superparameterized Community Atmosphere Model (SPCAM) simulation and Tseng et al. (2015) in the DYNAMO period. The weak correlation between vertical advection and tendency might be because moisture tendency diverts southward when the MJO reaches the MC (see Fig. 10c) with the wave-induced boundary layer convergence still confined in the equatorial MC regions (see Fig. 10d). The topography over the MC islands might also disrupt the wave-induced moisture convergence as the MJO convective envelopes approach. The evolution of the strength of wave-induced boundary layer moisture convergence in the equatorial zone along the MJO eastward propagation path is shown in Fig. 8. Since the strength of convective heating varies with time and location, the 1000–700- or 1000–850-hPa integrated vertical moisture advection east of convection is normalized by the precipitation averaged around the convection center. The ratio of vertical moisture advection to precipitation indicates the efficiency of boundary layer moisture convergence generated by the wave dynamics interaction with convective heating. As can be seen, the ratio decreases substantially when the MJO convective envelope moves into the eastern IO (~80°E); at this time, the wave-induced boundary layer moisture convergence has shifted into the MC (~90°–120°E). This drop of the ratio suggests that the complex topography over the MC islands might disrupt wave-induced boundary layer moisture convergence.
Fig. 8.
Fig. 8.

Strength of wave-induced boundary layer convergence to the east of convective heating along the MJO eastward propagation path: 1000–700-hPa (solid line) and 1000–850-hPa (dashed line) integrated vertical moisture advection (averaged over 5°S–5°N, and between 10° and –40° longitude east of max precipitation) is normalized by precipitation (averaged over 10°S–10°N and between ±7.5° longitude about max precipitation). The ratio is calculated only for the time when precipitation at the convection center is larger than 20 W m−2, with each dot representing one time step and the corresponding latitude in the x axis denoting the location of convection center. Color of the symbols indicates the magnitude of precipitation at the convection center.

Citation: Journal of Climate 31, 10; 10.1175/JCLI-D-17-0139.1

The projection of each budget term onto moisture anomalies (q2) is further calculated to evaluate its contribution to local moisture growth and maintenance. The result over both regions reveals that vertical advection and −Q2 are the dominant moisture source and sink terms (figure not shown). While upward motion causes strong moistening, the intense precipitation (i.e., positive Q2) efficiently removes moisture from the atmosphere (Sobel et al. 2014; Tseng et al. 2015). The horizontal advection term has a small contribution to the growth only in the MC.

c. Lower-tropospheric moisture budget: Indian Ocean versus Maritime Continent

To better understand the relative role of wave dynamics and moistening processes to the MJO evolution and further identify the contrast between the IO and MC, the horizontal distributions of dominant budget terms are examined in the four stages defined in section 3a, and the corresponding area-averaged moisture budgets are shown in Table 1. Since the cloud developing and decaying stages are in the transition phase, their key features are consistent with the convective and suppressed stages. For conciseness, we show only the distribution in the suppressed and convective stages over the central IO (Figs. 9 and 10, respectively), which respectively correspond to the decaying and suppressed stages over the MC. The results of the cloud developing and decaying stages over the central IO are discussed in the text and Table 1 (figures not shown). For all stages over both regions, the vertical advection and −Q2 (Figs. 9d,f and 10d,f) collocating with low-level moisture anomalies dominate the moisture budget with magnitude 2 times larger than other terms. Yet, because of the large cancellation (Figs. 9b and 10b), the distribution of moisture tendency (Figs. 9c and 10c) closely resembles that of the horizontal advection (Figs. 9e and 10e) with comparable area-averaged values (Table 1). This result is coherent with the Hovmöller diagram analysis illustrated in Fig. 6. The detailed features for each stage over the central IO are discussed below.

Table 1.

The 1000–700-hPa integrated moisture budget (W m−2) during four stages over the CIO and MC; 95% statistically significant budget terms are shown in boldface.

Table 1.
Fig. 9.
Fig. 9.

The horizontal distribution of 20–60-day filtered OLR (shading; W m−2), 1000–700-hPa averaged low-level winds (vector; m s−1), and 1000–700-hPa integrated lower-tropospheric moisture budget terms (shading; W m−2) during the CIO suppressed stage: (a) OLR, (b) , (c) tendency, (d) vertical advection, (e) horizontal advection, (f) −Q2, (g) zonal advection of LF moisture (q1) by MJO flow (U2), and (h) meridional advection of LF moisture by MJO flow. Note that the scale for vertical advection and −Q2 are two times larger than other terms. Contours in (b)–(f) are lower-tropospheric moisture anomalies with contour interval of 2.5 × 106 J m−2.

Citation: Journal of Climate 31, 10; 10.1175/JCLI-D-17-0139.1

Fig. 10.
Fig. 10.

As in Figs. 9a–f, but for the CIO convective (MC suppressed) stage. (The green box marks the MC region in Fig. 11.)

Citation: Journal of Climate 31, 10; 10.1175/JCLI-D-17-0139.1

In the suppressed stage (Fig. 9), the strong suppressed convection over the IO induces anomalous easterlies in the equatorial lower troposphere (Fig. 9a). The easterlies are attributed to the Rossby wave response of negative heating over the IO in previous studies (Zhao et al. 2013; D. Kim et al. 2014). Nonetheless, the interaction of Kelvin wave dynamics with suppressed convection should also contribute to the prevailing equatorial easterlies over the western–central IO, with anomalous easterlies (westerlies) established west (east) of negative heating [refer to the observation structure and theoretical solution of Kelvin wave in Figs. 5 and 6 of Wheeler et al. (2000)]. At the same time, a positive moisture tendency (Fig. 9c) develops in the equatorial lower troposphere over the central IO while moisture anomalies are still negative. The dominant moisture source over the central IO is the subgrid-scale convective processes (−Q2; Fig. 9f), which represents the collective moistening effect of cloud and eddy fluxes. By examining DYNAMO sounding array observation data, Tseng et al. (2015) found that the moistening from subgrid-scale convective processes in the suppressed stage is mainly contributed by the reevaporation of shallow convection and congestus (refer to their Fig. 6). These nonprecipitating clouds act like a humidity pump, transporting moisture from the moist ocean boundary layer to the lower troposphere. However, this substantial moistening is largely balanced by the vertical dry advection of intraseasonal downward motion associated with previous event (Fig. 9d). Their net effects (; Fig. 9b), representing the net moistening from large-scale vertical advection, vertical eddy moisture flux, and microphysical processes, are referred to as column processes in several studies (Chikira 2014; Wolding and Maloney 2015). These column processes (Fig. 9b) together with the horizontal advection (Fig. 9e) premoisten the western–central IO (Fig. 9c). The horizontal advection is dominated by zonal advection of LF moisture by anomalous easterlies associated with the downstream Kelvin–Rossby wave response of the suppressed convection (Fig. 9g). Moreover, at this time, positive low-level moisture anomalies have developed over the western IO, accompanied by upward motion (Fig. 9d) that is consistent with Kevin wave dynamics interacting with suppressed convective heating over the central IO.

In the cloud developing stage (Table 1), the suppressed convection shifts eastward to the MC with convection growing over the central IO, and the lower troposphere is dominated by strong anomalous easterlies. As the low-level moisture approaches maximum in this stage, a positive moisture tendency establishes to its east. This moistening is mainly contributed by the advection of mean moisture by anomalous easterlies and the boundary layer moisture convergence induced by the free-tropospheric heating of main MJO (Wang and Li 1994).

In the convective stage (Fig. 10), the IO deep convection along with MC suppressed convection induces anomalous low-level westerlies over the IO and easterlies over the MC (Fig. 10a); meanwhile, a drying and moistening tendency develop over the equatorial central IO and southern MC, respectively (Fig. 10c). The equatorial IO drying is caused by the horizontal dry advection by the westerlies (Fig. 10e) and the net column drying effect (Fig. 10b) between intense precipitation (i.e., positive Q2; Fig. 10f) and vertical moist advection (Fig. 10d). On the other hand, the wave-induced boundary layer moisture convergence over the equatorial MC regions (Fig. 10d) is largely balanced by Q2 (increased rainfall over MC islands; Fig. 10f) with a net column drying effect over equatorial MC (Fig. 10b), whereas the meridional advection by the Rossby anticyclonic gyres of MC suppressed convection moistens the southeastern IO and southern MC over the Arafura Sea (Fig. 10e). This north–south asymmetric distribution in moisture tendency (Fig. 10c) leads to the southward detour of the eastward-propagating MJO when it approaches the MC (Kim et al. 2017; Gonzalez and Jiang 2017).

In the decaying stage (Table 1), convection marches to the eastern IO and southern MC inducing strong low-level westerlies over the central IO. While the westerlies bring in dry air from the west, causing widespread drying over the central IO (Kerns and Chen 2014), the poleward flow induced both by the suppressed and active convection cause strong moistening over the off-equatorial regions around the MC and continue the southward detour of the MJO when it passes through the MC (Kim et al. 2017).

To first order, the area-averaged moisture budget (Table 1) shows that the moisture evolution over the MC is in accordance with that over the IO, except that the meridional advection is more significant. Nonetheless, an inspection of the horizontal distribution of moisture advection shows some interesting contrast between the suppressed stage of the central IO (Fig. 9e) and MC (Fig. 10e), presumably related to the complex topography and land–sea contrast over the MC.

To investigate the regional contrast in the moisture budget, we zoom in the MC regions during the convective stage of the central IO while the MC is in the suppressed stage (green box in Fig. 10). First we note that the vanguard of precipitation discovered by Peatman et al. (2014) with TRMM observation is confirmed by Q2 in Fig. 10f (loosely related to precipitation) peaking over the MC islands when the MJO convective envelope is in the IO [refer to the composite brightness temperature in Fig. 4 and precipitation in Fig. 5 for the MJO phase 2 in Peatman et al. (2014)]. During this period, the large-scale environment in the MC is controlled by upper-level subsidence as shown in Fig. 11c, while positive low-level moisture anomalies have developed in the equatorial MC regions (Fig. 10c), providing a favorable condition for the convection to develop. However, the positive moisture tendency (Fig. 10c) residing in the southern MC regions favors a southward detour of the MJO convection in the next stage. Similar to the moisture budget in the IO, the dominant moisture source and sink term in the MC are vertical advection and −Q2, which largely cancel each other; the moistening in the MC is mostly from the horizontal advection (Fig. 10e). The large moistening in the southern MC is contributed by both zonal and meridional advection (figure not shown) as revealed in Kim et al. (2017). In addition, it is interesting to note that the horizontal advection shows a regional variation with drying and moistening to the east and west of the MC islands and the two northern Australian peninsulas (Fig. 10e).

Fig. 11.
Fig. 11.

Horizontal distribution of 1000–700-hPa integrated lower-tropospheric scaled-separated moisture advection in the CIO convective (MC suppressed) stage: (a) horizontal advection of LF moisture (q1) by MJO flow (U2) (shading) and low-level MJO flow (vector), (b) horizontal advection of MJO moisture (q2) by LF flow (U1) (shading) and low-level LF flow (vector), and (d) horizontal advection of HF moisture (q3) by HF flow (U3) (shading) and moisture anomalies (contours; scaled by 2.5 × 106 J m−2). (c) Zonal–vertical cross section of LF moisture (shading; g kg−1), intraseasonal zonal velocity (m s−1), and pressure velocity (Pa s−1; scaled by a factor of 50) over the equatorial band [y axis is pressure (hPa)]. The zonal mean vertical structure for LF moisture is removed to emphasize the variation between land and ocean.

Citation: Journal of Climate 31, 10; 10.1175/JCLI-D-17-0139.1

The scale-separated moisture budget reveals that the advection of LF moisture by the MJO flow (Fig. 11a) is the dominant term contributing to the east–west asymmetric moistening pattern seen in total horizontal advection (Fig. 10e). A zonal–vertical cross section for the MJO circulation and LF moisture at the equatorial band is shown in Fig. 11c. As can been seen, intraseasonal easterlies prevail in the lower troposphere up to 400 hPa, and low-level mean moisture extending from 900 to 700 hPa is higher over the islands than the surrounding oceans. This is suggested to be the result of enhanced horizontal and vertical mixing over the large MC islands as supported by the active land–sea breeze and large diurnal amplitude of rainfall (e.g., Qian 2008; Vincent and Lane 2016) that is significantly correlated with daily mean rain rate shown in Peatman et al. (2014). The prevailing low-level easterlies cause drying and moistening on the east and west side of islands, respectively. This east–west asymmetric moistening matches the spatial distribution of diurnal amplitude in the MJO phase 2 in Fig. 7 of Peatman et al. (2014), suggesting that additional moistening over the leeward side might provide more available potential energy for convection to develop. Furthermore, this east–west moistening symmetry resulting from the diurnal modulation of mean moisture might contribute to the southward detour of the MJO convection, as the moisture advection becomes disorganized in the MC relative to the more organized moist advection over the Arafura Sea south of the MC. Besides the diurnal-modulated mean moisture, islands may also block the intraseasonal winds and reduce the magnitude of moisture advection in the MC.

While the advection of LF moisture by the MJO flow is the dominant moistening process diverting moisture southward, advection of the MJO moisture by LF flow (Fig. 11b) also contributes to the north–south asymmetry of moisture tendency. The northeast winter monsoon flow advecting intraseasonal dry air into the moisture-enhanced MC cause strong drying over the northern MC regions. In addition, when the monsoon flow reaches the MC, it is blocked by MC islands and become weak or turn westerly; this wind pattern advects intraseasonal moisture from eastern IO to the southern MC, further strengthening the north–south moistening asymmetry. Nonlinear moisture advection by high-frequency disturbances also makes relatively small but nonnegligible contributions to the southward detour, as high-frequency disturbances act as a diffusive process diffusing the positive moisture anomalies over the MC to the south and north side (Fig. 10f).

d. Moisture budget in the lower and upper troposphere

In previous sections, the evolution of lower-tropospheric moisture budget is investigated. Yet, several studies have found that the moisture variation in the middle and upper troposphere is also large (Chikira 2014; Adames and Wallace 2015; Wolding and Maloney 2015). Adames and Wallace (2015) showed a substantial amount of positive moisture tendency by horizontal advection in the middle troposphere ahead of the major MJO convection (refer to their Fig. 15). The evolution of upper-tropospheric moisture budget, vertically integrated from 700 to 100 hPa, is further explored and discussed together with the lower-tropospheric moisture budget.

The upper- and lower-tropospheric moisture budgets during four stages over the central IO and MC are displayed in Fig. 12. Overall, in the upper troposphere, vertical advection and −Q2 are still the dominant terms with opposite sign as found in the lower-tropospheric moisture budget analysis, whereas horizontal advection is in phase with the lower troposphere but of larger magnitude. Although vertical advection and −Q2 largely cancel each other, it is interesting to note that in the upper troposphere the vertical advection is always larger than −Q2 with net drying (moistening) in the suppressed (convective) stage, whereas in the lower troposphere the moistening from −Q2 can exceed vertical dry advection during the central IO suppressed stage. This result is consistent with the westward-tilted vertical structure obtained from warm-pool composite shown in Adames and Wallace (2015), with net moistening in the lower troposphere east of the convection and in the upper troposphere around the convection center (refer to their Fig. 15). The detailed features for each stage over the central IO are discussed below.

Fig. 12.
Fig. 12.

Upper- and lower-tropospheric moisture budget, vertically integrated from 700 to 100 hPa and from 1000 to 700 hPa respectively, during four stages over the CIO and MC (values separated by vertical lines); 95% statistically significant budget terms (W m−2) are shown in boldface with positive (negative) values in red (blue). Notation in the figure: moisture anomaly q (106 J m−2), moisture tendency qt, horizontal advection HA, vertical advection VA, surface latent heat flux LH, and precipitation P.

Citation: Journal of Climate 31, 10; 10.1175/JCLI-D-17-0139.1

In the suppressed stage, horizontal advective moistening in the upper troposphere is compensated by net column drying between large-scale subsidence dry advection and −Q2, so moisture tendency there is relatively weak while major moisture tendency changes are confined to the lower troposphere. In the cloud developing stage, horizontal advection has comparable moistening in the upper and lower troposphere but large net moistening between vertical advection and −Q2, resulting in the stronger moisture tendency in the upper troposphere. In the convective stage, the moisture tendency is still positive in the upper troposphere, while the lower troposphere has begun drying. This vertical shift is due to the much stronger vertical moist advection over the upper troposphere. In the decaying stage, both the upper and lower troposphere show substantial drying accompanied with strong horizontal dry advection. Note that the sign of vertical advection and −Q2 is opposite between the upper and lower troposphere; while upper-level upward motion moistens and condensation dries the upper troposphere, low-level downward motion dries and surface latent heat flux (LH) moistens the lower troposphere. Since the net effect between vertical advection and −Q2 is relatively small, the moisture budgets for the upper and lower troposphere are both dominated by horizontal dry advection. Overall, the evolution of the upper tropospheric moisture budget over the MC is consistent with that over the central IO.

e. Column-integrated MSE budget

Although the diagnosis of the moisture budget has provided much insight into the initiation and propagation mechanisms for the MJO, the budget residual (Q2) is one order larger than the terms that we identify as key processes, such as the horizontal advection. The small moisture tendency is the result of a near balance between large vertical advection and budget residual. This strong cancellation makes it difficult to assess an accurate calculation of the moisture budget. The use of the MSE budget can partly alleviate this problem as MSE is conserved during diabatic processes; therefore, the challenge of accurately measuring rainfall is removed. Moreover, as radiation and surface turbulent fluxes are source and sink terms in the column-integrated MSE budget, the role of these local physical processes in the evolution of the MJO can be explored explicitly.

The column-integrated MSE budget averaged over the central IO and MC during four stages is displayed in Table 2. The horizontal distributions of budget terms in the suppressed and convective stage over the central IO are displayed in Figs. 13 and 14, respectively. For all stages over both regions, the MSE tendency and horizontal advection term (Figs. 13a,c and 14a,c) are in agreement with the moisture budget analysis (Figs. 9c,e and 10c,e) as the temperature gradient in tropics is weak (e.g., Wolding et al. 2016). The main difference is that the sign of vertical advection since column-integrated MSE vertical advection is dominated by the transportation of upper-level geopotential energy (Sobel et al. 2014) (Figs. 13b and 14b; Table 2). It is worth noting that the magnitude of the vertical advection and budget residual (Q1Q2; Figs. 13d and 14d; Table 2) are of comparable magnitude to the horizontal advection (Figs. 13c and 14c; Table 2), as the large precipitation in the moisture budget residual is canceled by condensation heating; Q1Q2 now only includes the effect of radiative heating and surface turbulent fluxes. The decomposition (Figs. 13e,f and 14e,f; Table 3) shows that the evolution of Q1Q2 is dominated by the intraseasonal variation of longwave radiation (Sobel et al. 2014; D. Kim et al. 2014; Wolding and Maloney 2015). In the suppressed stage (Fig. 13e), radiative cooling is enhanced as a result of the lack of deep convection; in the convective stage (Fig. 14e), the widespread cloud coverage and elevated cloud top significantly decrease radiative cooling. The contribution from surface latent heat flux is small and negative (positive) in the suppressed (convective) stage as the intraseasonal easterlies (westerlies) are in the opposite (same) direction with mean-state westerlies over the equatorial warm pool region (Figs. 13f and 14f). During the decaying stage (figure not shown; see Table 3), accompanied with the strengthened anomalous westerlies induced by convective heating, the magnitude of surface latent heat flux anomalies becomes comparable with longwave heating (Wolding and Maloney 2015; de Szoeke et al. 2015). The variations of shortwave radiation and surface sensible heat flux are small compared to the other two terms (Table 3).

Table 2.

The 1000–100-hPa integrated MSE budget (W m−2) during four stages over the CIO and MC; 95% statistically significant budget terms are shown in boldface.

Table 2.
Fig. 13.
Fig. 13.

Horizontal distribution of 1000–100-hPa column-integrated MSE budget (shading; W m−2) during the CIO suppressed stage: (a) tendency, (b) vertical advection, (c) horizontal advection, (d) Q1Q2, (e) net longwave radiation, and (f) surface latent heat flux and intraseasonal winds at 925 hPa (vector). Contours in (a)–(e) are column-integrated MSE anomalies with contour interval of 2.5 × 106 J m−2. Vectors in (f) are red (blue) when LF and MJO zonal winds are in the same (opposite) direction.

Citation: Journal of Climate 31, 10; 10.1175/JCLI-D-17-0139.1

Fig. 14.
Fig. 14.

As in Fig. 13, but for the CIO convective (MC suppressed) stage.

Citation: Journal of Climate 31, 10; 10.1175/JCLI-D-17-0139.1

Table 3.

The decomposition of 1000–100-hPa integrated Q1Q2 (W m−2) during four stages over the CIO and MC; 95% statistically significant budget terms are shown in boldface.

Table 3.

To first order, the result of the MSE budget analysis over the MC is consistent with that over the central IO, except with a stronger contribution from surface latent heat flux during the suppressed stage (Fig. 14f) as the suppressed-heating-induced easterlies are larger over the MC than the central IO (Fig. 13f). Overall, the MSE budget results for the successive MJO are similar to previous research done in case studies, by model simulations, or with different case selections (e.g., Sobel et al. 2014; Wolding and Maloney 2015; D. Kim et al. 2014).

4. Summary and conclusions

In this study, 30 years (1982–2011) of ERA-Interim and NOAA OLR satellite observations are used to investigate the relative contribution of wave dynamics, moistening, radiative heating, and surface turbulent fluxes to the convective initiation, propagation, and maintenance of the MJO over the Indian Ocean and Maritime Continent within the successive event. A pair of OLR-based bimodal ISO indices by Kikuchi et al. (2012) is adopted to identify 22 successive events with strong magnitudes and clear propagation. The evolution of composite successive MJO events is analyzed through the diagnosis of lower- and upper-tropospheric moisture budget and column-integrated MSE budget.

The diagnosis of lower-tropospheric moisture budget shows that vertical advection and −Q2 collocating with low-level moisture anomalies are the dominant moisture sources and sinks with comparable magnitude but opposite sign. The evolution of the moisture tendency closely resembles horizontal advection that is dominated by advection of seasonal-scale moisture by the MJO flow. By projecting each budget term onto the moisture tendency and moisture anomaly, the relative contributions of different processes to the eastward propagation and growth of the MJO are identified. Over the central Indian Ocean, zonal advection and wave-induced boundary layer convergence dominate the eastward propagation, with negative contribution from Q2. On the other hand, over the Maritime Continent the eastward propagation is dominated by horizontal advection, with contribution from both zonal and meridional component. Nonlinear advection by synoptic disturbances acting as diffusive process has relatively small but nonnegligible contribution. With respect to growth and maintenance, vertical advection and Q2 are the dominant moisture source and sink respectively over both regions.

To better understand the relative role of wave dynamics and moistening processes with regard to the MJO evolution, the horizontal distribution of dominant moisture budget terms is discussed in the four stages defined by the evolution of 20–60-day filtered OLR and low-level moisture over the central Indian Ocean. In the suppressed stage, although surface evaporation and/or shallow convection (−Q2) substantially moistens the lower troposphere, it is largely balanced by vertical dry advection. The net moistening from column processes together with the moist advection by anomalous easterlies induced by negative heating over the Indian Ocean premoistens the western–central Indian Ocean for convection to develop. At the same time, the wave-induced boundary layer convergence establishes in the anomalous easterlies, contributing to an initiation of the MJO convection in the western Indian Ocean. In the following cloud developing and convective stages, the moist advection of seasonal-scale moisture by anomalous easterlies and wave-induced boundary layer moisture convergence ahead of the MJO deep convection drive the eastward propagation. On the other hand, the dry advection by the anomalous westerlies induced by Indian Ocean heating and intense precipitation causes widespread drying over the MJO convection center and regions west of it.

The contrast in the moistening processes between the Indian Ocean and the Maritime Continent and the effect of the Maritime Continent on the MJO evolution are discussed in the suppressed stage of the Maritime Continent. Unlike the wave convergence and advective moistening in the Indian Ocean, which both occur in the equatorial zone, advective moistening in the Maritime Continent is dominated by the advection of seasonal-scale moisture by intraseasonal easterlies, which shows a drying and moistening on the east and west sides, respectively, of large islands. This east–west asymmetric moistening on different mountain sides disorganizes the moisture advection in Maritime Continent relative to the more organized moisture advection over the Arafura Sea south of the Maritime Continent. Topographic blocking weakens the intraseasonal winds around the Maritime Continent and further reduces the moisture advection. In addition, the strong northeast winter monsoon flow advects intraseasonal dry air into the moisture-enhanced Maritime Continent, decreasing the moisture in the northern Maritime Continent. This drying in the north along with the widespread advective moistening over the Arafura Sea results in the north–south asymmetric moistening pattern over the Maritime Continent when the MJO convection approaches. The south–north asymmetry of moisture tendency disrupts the development of intraseasonal convection over the Maritime Continent and diverts the convective system southward without damping it.

Since moisture variation is also substantial in the middle troposphere, the evolution of upper-tropospheric moisture budget, vertically integrated from 700 to 100 hPa, is further explored. The vertical advection and −Q2 are still the dominant terms, largely cancelling each other with net drying (moistening) in the suppressed (convective) stage. On the other hand, the horizontal advection is in phase with that in the lower troposphere, showing moistening (drying) in the suppressed and cloud developing (convective and decaying) stage. This moistening pattern combined with the net lower-tropospheric moistening from vertical advection and −Q2 in the suppressed stage forms the westward-tilted structure of the moisture tendency, consistent with the result Adames and Wallace (2015) obtained from the warm-pool composite.

A column-integrated MSE budget, vertically integrated from the surface to 100 hPa, is further conducted to provide insight into the role of local physical processes. The result shows that longwave radiation dominates the intraseasonal evolution of Q1Q2, with enhanced (weakened) radiative cooling in the suppressed (convective) stage. The contribution from surface latent heat flux is prominent only in the decaying stage, as anomalous westerlies strengthen the mean-state westerlies over equatorial warm pool regions. This result suggests that MSE anomalies associated with the MJO are mainly maintained by cloud–radiative feedback, with wind–evaporation feedback playing a secondary role. The slight phase lag of longwave heating and surface latent heat flux with MSE anomalies also acts to slows down the eastward propagation (Sobel et al. 2014; Wolding and Maloney 2015; DeMott et al. 2016).

The composite of successive MJO events shows that the moisture advection by the coupled Kelvin–Rossby wave response to convective heating and suppressed cooling (D. Kim et al. 2014) and including the wave-induced boundary moisture convergence (Hsu and Li 2012) are the primary mechanisms for the evolution of the MJO over the Indo-Pacific warm pool region. The suppressed convection from previous MJO plays a vital role in the convective initiation of the successive MJO events through the following processes. The reevaporation of nonprecipitating shallow convection confined by the large-scale downward motion over the central Indian Ocean (Tseng et al. 2015), along with the enhanced radiative cooling (Stephens et al. 2004), destabilizes local atmosphere. At the same time, the suppressed-heating-induced large-scale circulation produces two moistening sources: moist advection by anomalous easterlies and boundary layer moisture convergence in the anomalous easterlies through its interaction with wave dynamics. After the convective initiation, the moist advection by the coupled Kelvin–Rossby wave response to suppressed convection is one of the major processes driving the eastward propagation.

Our results add supporting evidence for several key processes for the MJO evolution discussed in previous studies using field observations, reanalysis, and model simulations. Furthermore, we have made some new findings in this study. We show that the friction-induced boundary layer convergence in the anomalous easterlies induced by Kelvin wave dynamics can contribute significantly to the initiation of the MJO convection in the western Indian Ocean. We also discuss the possible effect on islands in the Maritime Continent on the advective moistening processes following the MJO evolution that might be associated with the east–west asymmetric spatial distribution of diurnal amplitude relative to the MC islands. The resultant spatial inhomogeneous distribution in moistening is suggested as one factor to disrupt the eastward propagation of the MJO.

Acknowledgments

Special thanks to Kai-Chih Tseng for his help in analysis and discussion. The authors appreciate the valuable comments of anonymous reviewers. This research was funded by the Ministry of Science and Technology in Taiwan. C.-S. H. and C.-H. S. were supported by MOST under Grant MOST 106-2111-M-002-003-MY2.

REFERENCES

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  • Andersen, J. A., and Z. Kuang, 2012: Moist static energy budget of MJO-like disturbances in the atmosphere of a zonally symmetric aquaplanet. J. Climate, 25, 27822804, https://doi.org/10.1175/JCLI-D-11-00168.1.

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    • Search Google Scholar
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  • Benedict, J. J., and D. A. Randall, 2007: Observed characteristics of the MJO relative to maximum rainfall. J. Climate, 64, 23322354, https://doi.org/10.1175/JAS3968.1.

    • Search Google Scholar
    • Export Citation
  • Bladé, I., and D. L. Hartmann, 1993: Tropical intraseasonal oscillations in a simple nonlinear model. J. Atmos. Sci., 50, 29222939, https://doi.org/10.1175/1520-0469(1993)050<2922:TIOIAS>2.0.CO;2.

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  • Chang, C.-P., 1977: Viscous internal gravity waves and low-frequency oscillations in the tropics. J. Atmos. Sci., 34, 901910, https://doi.org/10.1175/1520-0469(1977)034<0901:VIGWAL>2.0.CO;2.

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  • Chikira, M., 2014: Eastward-propagating intraseasonal oscillation represented by Chikira–Sugiyama cumulus parameterization. Part II: Understanding moisture variation under weak temperature gradient balance. J. Atmos. Sci., 71, 615639, https://doi.org/10.1175/JAS-D-13-038.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Crueger, T., and B. Stevens, 2015: The effect of atmospheric radiative heating by clouds on the Madden–Julian oscillation. J. Adv. Model. Earth Syst., 7, 854864, https://doi.org/10.1002/2015MS000434.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • DeMott, C. A., J. J. Benedict, N. P. Klingaman, S. J. Woolnough, and D. A. Randall, 2016: Diagnosing ocean feedbacks to the MJO: SST-modulated surface fluxes and the moist static energy budget. J. Geophys. Res., 121, 83508373, https://doi.org/10.1002/2016JD025098.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • de Szoeke, S., J. Edson, J. Marion, C. Fairall, and L. Bariteau, 2015: The MJO and air–sea interaction in TOGA COARE and DYNAMO. J. Climate, 28, 597622, https://doi.org/10.1175/JCLI-D-14-00477.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Emanuel, K. A., 1987: An air–sea interaction model of intraseasonal oscillations in the tropics. J. Atmos. Sci., 44, 23242340, https://doi.org/10.1175/1520-0469(1987)044<2324:AASIMO>2.0.CO;2.

    • Crossref
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    • Export Citation
  • Feng, J., T. Li, and W. Zhu, 2015: Propagating and nonpropagating MJO events over Maritime Continent. J. Climate, 28, 84308449, https://doi.org/10.1175/JCLI-D-15-0085.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gonzalez, A. O., and X. Jiang, 2017: Winter mean lower tropospheric moisture over the Maritime Continent as a climate model diagnostic metric for the propagation of the Madden-Julian oscillation. Geophys. Res. Lett., 44, 25882596, https://doi.org/10.1002/2016GL072430.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hannah, W. M., and E. D. Maloney, 2011: The role of moisture–convection feedbacks in simulating the Madden–Julian oscillation. J. Climate, 24, 27542770, https://doi.org/10.1175/2011JCLI3803.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hsu, P.-C., and T. Li, 2012: Role of the boundary layer moisture asymmetry in causing the eastward propagation of the Madden– Julian oscillation. J. Climate, 25, 49144931, https://doi.org/10.1175/JCLI-D-11-00310.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hu, Q., and D. A. Randall, 1994: Low-frequency oscillations in radiative–convective systems. J. Atmos. Sci., 51, 10891099, https://doi.org/10.1175/1520-0469(1994)051<1089:LFOIRC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jiang, X., 2017: Key processes for the eastward propagation of the Madden-Julian Oscillation based on multimodel simulations. J. Geophys. Res., 122, 755770, https://doi.org/10.1002/2016JD025955.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Johnson, R. H., P. E. Ciesielski, J. H. Ruppert, and M. Katsumata, 2015: Sounding-based thermodynamic budgets for DYNAMO. J. Atmos. Sci., 72, 598622, https://doi.org/10.1175/JAS-D-14-0202.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kemball-Cook, S. R., and B. C. Weare, 2001: The onset of convection in the Madden–Julian oscillation. J. Climate, 14, 780793, https://doi.org/10.1175/1520-0442(2001)014<0780:TOOCIT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kerns, B. W., and S. Chen, 2014: Equatorial dry air intrusion and related synoptic variability in MJO initiation during DYNAMO. Mon. Wea. Rev., 142, 13261343, https://doi.org/10.1175/MWR-D-13-00159.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kikuchi, K., B. Wang, and Y. Kajikawa, 2012: Bimodal representation of the tropical intraseasonal oscillation. Climate Dyn., 38, 19892000, https://doi.org/10.1007/s00382-011-1159-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kiladis, G. N., K. H. Straub, and P. T. Haertel, 2005: Zonal and vertical structure of the Madden–Julian oscillation. J. Atmos. Sci., 62, 27902809, https://doi.org/10.1175/JAS3520.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kim, D., J.-S. Kug, and A. H. Sobel, 2014: Propagating versus nonpropagating Madden–Julian oscillation events. J. Climate, 27, 111125, https://doi.org/10.1175/JCLI-D-13-00084.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kim, D., H. Kim, and M.-I. Lee, 2017: Why does the MJO detour the Maritime Continent during austral summer? Geophys. Res. Lett., 44, 25792587, https://doi.org/10.1002/2017GL072643.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kim, H.-M., P. J. Webster, V. E. Toma, and D. Kim, 2014: Predictability and prediction skill of the MJO in two operational forecasting systems. J. Climate, 27, 53645378, https://doi.org/10.1175/JCLI-D-13-00480.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kiranmayi, L., and E. D. Maloney, 2011: Intraseasonal moist static energy budget in reanalysis data. J. Geophys. Res., 116, D21117, https://doi.org/10.1029/2011JD016031.

    • Search Google Scholar
    • Export Citation
  • Lau, K.-M., and L. Peng, 1987: Origin of low-frequency (intraseasonal) oscillations in the tropical atmosphere. Part I: Basic theory. J. Atmos. Sci., 44, 950972, https://doi.org/10.1175/1520-0469(1987)044<0950:OOLFOI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lee, J.-Y., B. Wang, M. Wheeler, X. Fu, D. Waliser, and I.-S. Kang, 2013: Real-time multivariate indices for the boreal summer intraseasonal oscillation over the Asian summer monsoon region. Climate Dyn., 40, 493509, https://doi.org/10.1007/s00382-012-1544-4.

    • Crossref
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