1. Introduction
Previous studies have shown significant atmospheric intraseasonal oscillations (ISOs) in the tropical Atlantic and West African sector (e.g., Park and Schubert 1993; Shapiro and Goldenberg 1993; Foltz and McPhaden 2004; Gu and Adler 2004; Gu 2009). A few processes have been suggested to be able to cause these oscillations: the global propagation of the Madden–Julian oscillation (MJO; Madden and Julian 1971, 1972) originating in the Indo-Pacific Ocean (e.g., Park and Schubert 1993; Hendon and Salby 1994; Foltz and McPhaden 2004; Yu et al. 2011), intraseasonal convection in the African monsoon region (e.g., Grodsky and Carton 2001; Thorncroft et al. 2003; Maloney and Shaman 2008; Janicot et al. 2009; Gu 2009), and atmospheric variability from midlatitudes (e.g., Park and Schubert 1993; Shapiro and Goldenberg 1993; Hoskins and Yang 2000; Pan and Li 2008). The MJO and intraseasonal convection of the African monsoon, however, are not completely independent. It has been shown that the MJO can affect the intraseasonal convection of the West African monsoon (e.g., Gu and Adler 2004; Maloney and Shaman 2008).
Han et al. (2008) showed strong 40–60-day variability in surface winds, sea level, and thermocline depth along the Atlantic equator during 2002. Yu et al. (2011) suggested that the strong 40–60-day surface winds in the western and central equatorial Atlantic during January–May 2002 result primarily from the MJO, which propagates eastward from the Pacific into the Atlantic through the Isthmus of Panama and Central America where land barriers are small. It remains unclear, however, what causes the 40–60-day wind anomalies during summer and fall, which exhibit westward propagation in the central and eastern equatorial Atlantic basin.
Observational evidence shows that boreal summer wind and precipitation associated with the West African monsoon, which have 10–25-day and 25–60-day dominant periods, can affect the east-central tropical Atlantic Ocean, especially the intertropical convergence zone (ITCZ; e.g., Grodsky and Carton 2001; Janicot and Sultan 2001; Redelsperger et al. 2002, 2006; Nicholson and Grist 2003; Thorncroft et al. 2003; Sultan and Janicot 2003b; Maloney and Shaman 2008; Mounier et al. 2008; Janicot et al. 2009). Janicot et al. (2011) identified three intraseasonal modes in African monsoon precipitation by empirical orthogonal function (EOF) analysis: the quasi-biweekly zonal dipole mode (Mounier et al. 2008; Janicot et al. 2011), the “Sahel” mode (Sultan and Janicot 2003a; Janicot et al. 2011), and the “African MJO” mode (Matthews 2004; Janicot et al. 2009). The intraseasonal signals of quasi-biweekly zonal dipole mode propagates eastward with possibility of modulating convection over the Indian Ocean, and the mechanisms of this mode appear to be controlled both by equatorial atmospheric disturbances propagating eastward and by radiation–atmosphere interaction processes over Africa (Mounier et al. 2008). The Sahel mode shows 10–25-day intraseasonal signals in African monsoon precipitation, propagating westward with extended impacts on the western Atlantic until it dissipates over the tropical Atlantic.
Even though the influences of the MJO and convectively coupled Rossby waves have been separately examined, their relative importance in determining intraseasonal surface winds and convection in different regions of the tropical Atlantic Ocean for different seasons has not yet been systematically studied. It is not clear whether the westward-propagating signals in the tropical Atlantic can also originate and subsequently enhance over the Atlantic Ocean, or if they can only be excited by the African monsoon precipitation as assessed by existing studies. In this paper, we document intraseasonal convection and surface wind in the tropical Atlantic Ocean and explore the relative importance of the MJO and Rossby waves in explaining the observed intraseasonal variability using satellite observations and reanalysis data. In addition, we provide evidence for intraseasonal Rossby waves that originate in the eastern tropical Atlantic Ocean and subsequently enhance while they propagate westward. The MJO and equatorial wave signals are identified based on the dispersion relation of equatorially trapped waves. Brief introductions to the datasets and analysis methods are provided in section 2. Results are reported in section 3. Summary and conclusions are given in section 4.
2. Data and method
MJO propagation can be effectively diagnosed using outgoing longwave radiation (OLR) and winds (e.g., Arkin and Ardanuy 1989; Liebmann and Smith, 1996; Jones et al. 2004; Matthews 2000). Hence, 3-day mean, Quick Scatterometer (QuikSCAT) ocean surface wind vectors, daily National Oceanic and Atmospheric Administration (NOAA) interpolated OLR, and daily interim European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-Interim) winds with 1.5° × 1.5° resolution are used to diagnose atmospheric intraseasonal variability. To minimize the influence of missing values due to incomplete sampling and rain contamination, we averaged the 0.25° × 0.25° resolution QuikSCAT winds onto 2.5° × 2.5° grids. To support the convective activity diagnosed by the OLR, we also analyzed the 1° × 1° daily Global Precipitation Climatology Project (GPCP; Xie and Arkin 1996) precipitation data and daily 1.5° × 1.5° ERA-Interim precipitation (Simmons et al. 2007).
To assess the relative importance of the MJO and intraseasonal waves, we need to isolate their signals. Based on the space–time spectral analysis of Wheeler and Kiladis (1999), the MJO and each type of the equatorial waves have their dominant frequencies and wavenumbers. We create a similar figure using OLR data during 1980–2008 (Fig. 1) and obtain similar results. Note that there are two parts in Fig. 1: the antisymmetric and symmetric OLR power relative to the background power that are statistically significant above the background at the 95% level (shading) and the frequency–wavenumber dispersion curves of the different waves (lines) based on the shallow-water theory. The former is calculated from the global OLR data averaged from 15°S to 15°N. The later provides the reference for filtering different waves using the space–time filter in rectangular windows described below (also see Fig. 1b). Because the MJO and equatorial Rossby and Kelvin waves have global scales and can affect the Atlantic Ocean, even though they may not obtain the maximum variance over the Atlantic, this figure can be used as a guide to isolate different ISO signals.
A space–time filter is applied to isolate the signals associated with each type of ISO. Liebmann et al. (2009) used similar method to identify the convective events to study the mechanisms of the initiation of the Kelvin waves in Amazon region. Here we focus on the propagation features in the Atlantic for MJO with a wider 20–100-day band and westward-propagating Rossby wave signals. Specifically, to assess the MJO signals, OLR, precipitation, and wind data were first filtered to 20–100-day periods with a Lanczos digital filter (Duchon 1979) and then further filtered to eastward wavenumbers 1–6, following the suggestion of the U.S. Climate Variability and Predictability Research Program (CLIVAR) MJO working group (Waliser et al. 2009). Based on the dispersion relation (Fig. 1), the above filter primarily extracts the MJO signals, even though it may also contain some Kelvin wave signals. Here, the combined MJO and Kelvin wave signals are collectively referred to as the MJO. To further demonstrate that they are indeed the MJO-related signals over the Atlantic and African monsoon region, the MJO events (OLR and surface winds) are also obtained by creating the multivariate global MJO index (Wheeler and Hendon 2004) using daily OLR and ERA-Interim 850- and 200-hPa zonal winds during 2000–08. Similarly, a 20–100-day filter with westward wavenumbers 1–6 is used to isolate the convectively coupled Rossby waves, which has the maximum power in this frequency–wavenumber domain [Fig. 1; see also Fig. 3 of Wheeler and Kiladis (1999)]. A wider 10–100-day filter with westward wavenumbers 1–8, which essentially covers the entire intraseasonal Rossby wave power (Fig. 1b), is also tested to confirm the Rossby wave signals filtered by the 20–100-day westward wavenumber 1–6 filter.
Composite analyses are performed to demonstrate each type of ISO impacts. First, we analyze the time series of total 20–100-day filtered OLR without wavenumber filtering, 20–100-day filtered OLR with eastward wavenumber 1–6 filtering (MJO), 20–100-day OLR with westward wavenumber 1–6 filtering, and 10–100-day OLR with westward wavenumber 1–8 filtering (Rossby wave), respectively, for a specific region of the tropical Atlantic Ocean or West African monsoon during 2000–08. Indices of convective events are chosen when both the total 20–100-day OLR and the MJO (or Rossby wave) signals reach maxima and each exceeds one standard deviation (STD) of the total 20–100-day OLR time series. These events are referred to as “MJO-dominated” (or “Rossby wave–dominated”). When both the MJO and Rossby wave are equally important and exceeding one STD, these cases will be picked up by MJO-dominated and Rossby wave–dominated events, respectively. In this study, we only see two cases that appear in both MJO-dominated and Rossby wave–dominated events in African monsoon region. To confirm the MJO-dominated events above, the multivariate global MJO index (Wheeler and Hendon 2004) is also used, and the two methods yield consistent MJO events (see section 3c). The filtered fields for the MJO- and Rossby wave–dominated events are also compared with the unfiltered fields, in order to demonstrate the MJO and Rossby wave impacts on the total fields and to confirm the effectiveness of our space–time filtering approach.
Then, composite fields of 20–100-day (and 10–100-day) OLR, ERA-Interim, and QuikSCAT winds, together with GPCP precipitation, are created based on the indices obtained above. Note that even though indices are chosen based on both total 20–100-day (10–100-day) OLR and the MJO (Rossby wave) signals with wavenumber filtering, the composite fields shown later for the MJO-dominated (Rossby wave–dominated) events are based on the total 20–100-day (10–100-day) fields without further wavenumber filtering. Intraseasonal variances and spectral coherence analysis are performed using OLR to examine the effects of the MJO and Rossby waves on convection in the tropical Atlantic Ocean.
3. Results
In section 3a, we examine the impacts of MJO and Rossby waves on surface winds and convection over the Atlantic Ocean and African monsoon region. In section 3b we assess the relative importance of MJO and intraseasonal Rossby waves. In sections 3c and 3d, we demonstrate the spatial structure and temporal evolution of convection and surface winds associated with the MJO and Rossby waves over the tropical Atlantic Ocean using composite techniques.
a. MJO and Rossby waves in the tropical Atlantic and African monsoon region
Figure 2 shows longitude–time diagrams of the 20–100-day bandpass filtered QuikSCAT surface zonal wind averaged from 15°S to 15°N during 2003 and 2005, which includes both the eastward- and westward-propagating signals. Similar eastward (westward)-propagating signals are also observed during other years. Consistent with Yu et al. (2011), the MJO-related maximum surface wind anomalies are first observed in the Indian Ocean and western Pacific during spring 2003, and subsequently propagate eastward into the Atlantic Ocean to 40°W, and the Atlantic manifestation of the wind anomalies is weaker relative to the Indo-Pacific sector. Eastward-propagating MJO events occur primarily during boreal winter and spring, becoming weaker during summer. A similar situation exists for 2005, and the eastward-propagating MJO signals are even stronger. During summer and fall, however, westward-propagating signals are evident. As we shall see in the following sections, Rossby waves contribute to the westward-propagating intraseasonal signals in the tropical Atlantic.
1) Observation of MJO
To further demonstrate the MJO influence, we create the multivariate global MJO index (e.g., Wheeler and Hendon 2004; Maloney et al. 2010) based on OLR data and ERA-Interim 850- and 200-hPa zonal winds, each averaged over the latitudes of 15°S–15°N from 2000–08. The optimal range of latitudes over which to average has been investigated by Wheeler and Hendon (2004) and the range of 15°S–15°N is recommended for EOF analysis to effectively extract MJO signals. The extracted MJO signals (not shown), which are defined as the leading pair of EOFs, show MJO structures similar to those in Wheeler and Hendon (2004, see their Fig. 1). The time series of the first two principal components (PCs) of the EOFs are combined to derive the phase information. The phase space spanning 0°–360° is partitioned into eight equal-angle “MJO phases” into which high-amplitude events are binned based on phase information derived from the PCs. For each MJO phase, days with global MJO index (amplitude) exceeding 1 are averaged together to generate a composite event. Here the global MJO index is defined as the sum of the squares of the first two principal components: (PC1)2 + (PC2)2. The composite maps of MJO cycles are shown in Fig. 3, in which eight phases are shown with 45° intervals from 0° to 360° to reveal the MJO propagation. For the winter MJO (Fig. 3, left panels), phases P1 and P2 show the familiar MJO convective dipole, with enhanced convection (negative OLR anomalies) in the Indian Ocean and reduced convection (positive OLR anomalies) in the western Pacific. The westerly (easterly) wind anomalies are located to the west (east) of the enhanced convection, as shown by Wheeler and Hendon (2004). Associated with the eastward propagation of convection, the 850-hPa easterly and westerly wind anomalies propagate eastward, entering the Atlantic through Central America and Isthmus of Panama during phases P2–P4 and P5–P8, and affecting the tropical Atlantic Ocean. The negative convection anomalies of the MJO weaken in the eastern Pacific and enhance in the eastern equatorial Atlantic and West Africa, suggesting the MJO influence on these regions (phases P6–P8, left panels of Fig. 3). In contrast, during boreal summer (Fig. 3, right panels), even though surface wind and convection associated with the MJO have apparent influence on the tropical Atlantic, the amplitudes shown by OLR anomalies are weaker compared to those of boreal winter. These results are consistent with our discussion above (Fig. 2) and previous studies (e.g., Ventrice et al. 2011; Yu et al. 2011; Alaka and Maloney 2012).
2) Evidence of Rossby waves
Interestingly, evident westward-propagating signals that originate from West Africa are seen in the eastern and central Atlantic during most part of 2003 and during summer and fall of 2005 (Fig. 2) when the MJO has weaker influence than winter and spring (Figs. 2 and 3). To reveal the role played by the Rossby waves, we analyze the space–time filtered Rossby wave signals (Fig. 4, left panels) and compare them with the 20–100-day filtered fields without wavenumber filtering (right panels) for 850-mb winds and OLR during May and June 2003, which is associated with a westward-propagating event shown in Fig. 2. From 22 to 28 May, strong convection (large-amplitude negative OLR anomalies) develops over West Africa and moves westward along the equator (Fig. 4, left panels). The Rossby wave structure is seen with a negative OLR anomaly near the equator accompanying positive OLR anomalies off the equator. The maximum westerly wind anomaly is located in the west of the convective center accompanied with two off-equator cyclonic wind shears, consistent with the n = 1 equatorial Rossby wave structures (Kiladis and Wheeler 1995; Molinari et al. 2007). On 2 June, the convection reaches its maximum amplitude and propagates westward. Meanwhile, the Rossby wave structure is more evident in OLR and wind fields. In the central and eastern tropical Atlantic, westerly wind anomalies prevail. By 8 June, the Rossby wave continuously propagates westward, affecting the northern part of South America.
The westward propagation and spatial structure of the Rossby wave can also be identified in the 20–100-day filtered OLR and 850-mb wind fields (Fig. 4, right panels), although the signals are noisier than the wavenumber filtered Rossby waves (left panels). These results suggest that the observed westward-propagating 20–100-day zonal surface wind anomalies in the tropical Atlantic during May and June of 2003 (Fig. 2) are associated with Rossby waves.
To further demonstrate the westward-propagating signals, which are most apparent during boreal summer and fall, we choose the 5°–10°N, 5°W–0° area from the West African monsoon region (e.g., Sultan and Janicot 2003a) as a reference and perform coherence analysis during 2000–08 (Fig. 5). When we use the total 20–100-day filtered OLR data, which include the influence of both the MJO and Rossby waves, significant coherence (with coherence squared values above 0.3) is trapped to the eastern tropical Atlantic without apparent westward propagation (Fig. 5a). To exclude the MJO effect, we first extract the MJO signals by regressing the OLR data onto the global MJO index derived in section 3a(1) and then remove the MJO signals from the 20–100-day OLR field. After the MJO signals are removed, coherence squared values above 0.3 across the tropical Atlantic basin are observed. The phase vector is northward in West Africa and northeastward near 35°W along the equator. The clockwise rotation of the phase vector indicates a possible westward propagation from West Africa to the central Atlantic. Indeed, the 20–100-day westward wavenumber 1–6 filtered OLR data (Fig. 5c), which consist primarily of westward-propagating Rossby waves (Fig. 1), show stronger coherence and clearer westward propagation from the West African monsoon region across the tropical Atlantic compared to Fig. 5b. These results further demonstrate that intraseasonal convection over the tropical Atlantic and African monsoon region can be affected by the MJO, and that the West African monsoon can affect the entire tropical Atlantic possibly via westward-propagating Rossby waves. We also notice that the phase vector rotation from West Africa to the eastern Atlantic is not clear in Fig. 5b, which does not explain the evolution of the demonstrated Rossby wave case as in Fig. 4. This could be related to the impacts of other mechanisms in West Africa, such as the land–atmosphere processes (Janicot et al. 2011). Therefore it is helpful to isolate the westward and eastward signals in order to clearly demonstrate their effects on intraseasonal variations in the Atlantic basin.
b. Influence of MJO and Rossby waves
To quantify the impacts of the MJO and Rossby waves, we choose three representative regions in the western Atlantic (WA; 0°–15°N, 50°–40°W), central Atlantic (CA; 5°S–15°N, 30°–20°W), and the African monsoon region (AF; 0°–14°N, 10°W–10°E). Here we choose the same African monsoon region as used by previous studies (Sultan and Janicot 2003a; Redelsperger et al. 2002; Gu 2009). The WA region is located within the propagation path of MJO surface wind from Indo-Pacific to tropical Atlantic (Yu et al. 2011). Geographic locations of these regions are shown in Fig. 6a.
Figures 6b–d show strong intraseasonal variations of 20–100-day filtered OLR above one STD (horizontal solid lines) occurring in the three regions (dashed line), which often correspond to either eastward wavenumber 1–6 OLR anomalies (solid line) that are primarily associated with the MJO or westward wavenumber 1–6 OLR anomalies (dotted line) that are associated with the Rossby waves. The STDs of the MJO and Rossby waves comparing to the STD of 20–100-day OLR are 63% and 77% in the western Atlantic, 68% and 62% in the central Atlantic, and 83% and 50% in the African monsoon region (Table 1). The variance of the MJO and Rossby waves comparing to that of 20–100-day OLR are 11% and 17% in the western Atlantic, 17% and 15% in the central Atlantic, and 25% and 10% in the African monsoon region. The correlation coefficient between the 20–100-day OLR and the MJO (Rossby waves) during 2000–08 period is 0.51 (0.67) in the western Atlantic, 0.63 (0.59) in the central Atlantic, and 0.8 (0.62) in the African monsoon region. These results suggest that the strong convective events are more related to the MJO in the African monsoon region, to Rossby waves in the western Atlantic, and equally to the MJO and Rossby waves in the central Atlantic.
Domain-averaged 20–100-day variability. The percentage is relative to the total 20–100-day OLR. Units of OLR are W m−2.
To demonstrate the MJO and Rossby wave influences on total convection and to test the validity of the filtering approach, we compare the filtered fields with the unfiltered OLR data. The correlation coefficient between the unfiltered OLR data (with annual and semiannual harmonic fits removed) and the MJO (Rossby waves) during 2000–08 period is 0.27 (0.36) in the western Atlantic, 0.39 (0.36) in the central Atlantic, and 0.49 (0.38) in the African monsoon region above 95% significance. The correlations between the full OLR and the MJO increase toward the east, consistent with what we derived from 20–100-day OLR and the MJO. In the African monsoon region, almost all of the enhanced convective events above one STD correspond to significant MJO events (Fig. 6d). The fact that both the eastward-propagating MJO and westward-propagating Rossby waves are important in the tropical Atlantic basin is consistent with the lack of westward propagation detected in Fig. 5a.
As we shall see below, since MJO signals often strengthen while they propagate across the tropical Atlantic, MJO-dominated convective events increase toward the east. Similarly, since the Rossby wave signals can enhance over the Atlantic Ocean while they propagate westward, and some even appear to be generated in the eastern Atlantic basin, Rossby wave–dominated convective events increase toward the west.
To further quantify the relative contribution of MJO and Rossby waves, we first create the convective indices for different regions by choosing the date of the enhanced convective events when the domain-averaged maximum negative 20–100-day OLR amplitudes exceed one STD, and then we further categorize these convective events as MJO dominated or Rossby wave dominated. The MJO (Rossby wave)-dominated convective events are defined as the maximum negative 20–100-day with eastward (westward) wavenumber 1–6 filtered OLR amplitudes exceeding one STD of the total 20–100-day OLR time series and have the same phase. Finally, we calculate the time distribution of the convective indices for May–October and November–April. As demonstrated in sections 3c and 3d, the composite maps configured from the MJO (Rossby wave)-dominated convective indices do show the MJO (Rossby wave) structures.
As shown in Fig. 7, the MJO- and Rossby wave–dominated convective events (relative to the total 20–100-day events) are 17 (32%) and 29 (55%) in the western Atlantic, 18 (35%) and 20 (39%) in the central Atlantic, and 32 (62%) and 12 (23%) in the African monsoon region. This further demonstrates that Rossby waves and the MJO have different impacts in different regions across the tropical Atlantic Ocean, with more frequent Rossby wave–dominated events in the western Atlantic and MJO-dominated events in the African monsoon region, and they are almost equally important in the central Atlantic. Given that cold SST in the eastern Pacific inhibits convection and the Central American continent blocks continuous air–sea interaction, MJO-related convection is generally weaker in the western Atlantic after MJO propagates into the Atlantic than in the Indo-Pacific Ocean, consistent with Fig. 3. Note that convection anomalies associated with the MJO and Rossby waves are stronger during November–April than during May–October in all three regions (Fig. 6). The OLR STDs for winter (summer) MJO are 4.6 (4.2) in the western Atlantic, 5.4 (4.3) in the central Atlantic, and 7.8 (5.6) in the African monsoon region, and for winter (summer) Rossby waves are 5.7 (4.4) in the western Atlantic, 4.9 (3.7) in the central Atlantic, and 4.5 (3.6) in the African monsoon region. The numbers of MJO-dominated convective events are smaller during May–October than during November–April, with 3 versus 14 events in the western Atlantic, 4 versus 14 in the central Atlantic, and 10 versus 22 in the African monsoon region (Fig. 7), consistent with the seasonal variation of MJO activities (Madden and Julian 1994; Matthews 2000; Jones et al. 2004; Maloney et al. 2008; Yu et al. 2011; Fig. 2). In contrast, the Rossby wave–dominated convective events are more evenly distributed during May–October and November–April in both the western and central Atlantic, with 14 versus 15 in the western Atlantic and 9 versus 11 in the central Atlantic. In the African monsoon region, the numbers of Rossby wave events are 9 during November–April and 3 during May–October.
To verify the MJO-dominated indices in Fig. 7, we compare all of the MJO-dominated convective events in the three regions with the selected MJO events from global MJO index used in configuring the composite maps for Fig. 3. The results show that 91% of the MJO-dominated convective events in Fig. 7 are picked up by the global MJO index and 78% are located in phases 6–8. This result indicates that the categorized MJO-dominated convective events in Fig. 7 are a subset from the EOF-based global MJO index. The former can effectively reveal the regional variability of the MJO influence in the Atlantic and African monsoon regions.
c. Evolution of the MJO
The evolution of MJO- and Rossby wave–related deep convective anomalies over the tropical Atlantic and African monsoon region can be seen by a sequence of lagged composite maps of 20–100-day filtered fields during 2000–08, such as OLR, and surface wind fields, lagged with respect to OLR-categorized convective index in different regions shown in Figs. 7 and 6a. Day 0 corresponds to the time when convection attains its maximum strength. The composite 20–100-day filtered OLR and surface winds based on the MJO-dominated convective events in all three regions (Figs. 8a, 9, and 10, left panels) show an eastward propagation and affect the surface winds and convection variations on the Atlantic. The maximum convective anomalies first appeared in the Indo-Pacific warm pool. Subsequently, the convective anomalies, together with the westerly wind anomalies to the west and easterlies to the east, propagate eastward [also see Milliff and Madden (1996); Matthews (2000)], entering the Atlantic via Central America and the Isthmus of Panama and affecting the tropical Atlantic basin and African monsoon region.
Interestingly, the strength of the MJO convection varies following the MJO propagation from the western Atlantic to the African monsoon region for different MJO events. For the MJO-dominated western Atlantic events (Fig. 8a, left panels), convection obtains large amplitude in the western basin on day 0 and subsequently propagates eastward with weakened strength (day 6). These convective cases appear to be consistent with the MJO effects examined by Yu et al. (2011), which obtain their largest influence in the western tropical Atlantic Ocean. For the central Atlantic events (Fig. 9, left panels), MJO convection propagates eastward across the Atlantic basin without an apparent change in strength. In contrast, the situation for MJO-dominated convection in African monsoon region (Fig. 10, left panels) is more complex. Convection first weakens from the western to the central Atlantic basin (from day −12 to −6) and then significantly enhances as it propagates to the African monsoon region by day 0. These evolutionary processes are more evident in Fig. 11 (left panels). This result suggests that the MJO influence on the West African monsoon is not simply by direct eastward propagation of surface signatures. Rather, the MJO can be enhanced, likely due to upper-level atmospheric divergence, interaction with regional convective signals (Gu 2009), and possibly air–sea interaction over the Atlantic Ocean, all of which may contribute to an amplified influence in the West African monsoon region (Fig. 6; Table 1). Although the MJO-dominated cases mainly occur during November–April, they can also happen in May–October during the West African monsoon (Fig. 7). The possibility for air–sea interaction over the Atlantic Ocean to strengthen the MJO needs thorough investigation in future research.
The eastward propagation of the MJO signals can also be discerned in the composite maps of unfiltered OLR data with mean and seasonal cycle removed and total surface winds (Fig. 8a, right panels). A low OLR signal in the unfiltered field, which corresponds to the MJO in the filtered OLR (left panels), propagates eastward along the ITCZ (indicated by the wind convergence and low OLR values), enters the western Atlantic through the Isthmus of Panama (day −6), and strengthens the convection in the western Atlantic Ocean (days −6, 0, and 6). Throughout the process, persistent convections exist in the Indo-Pacific warm pool, Amazon area, and South African monsoon region (not shown). The eastward propagation of OLR from the Pacific to the Atlantic is also evident for the MJO-dominated central and eastern Atlantic cases (not shown). The consistency between the filtered MJO signals and the unfiltered fields provides direct evidence for the MJO impacts. It also demonstrates that the filtering technique used to extract the MJO is valid and serves our purpose.
d. Evolution of Rossby waves
Similarly, Rossby waves can dominate intraseasonal variability of convection and surface winds in the tropical Atlantic Ocean. Figure 8b (left panels) shows the development and propagation of the Rossby wave–dominated convective events in the western Atlantic basin. The 10–100-day westward wavenumber 1–8 filtered fields are also analyzed, and we obtain similar results except that the amplitudes of convection are larger in some regions and the signals are somewhat noisier (not shown). First, a weak convective anomaly appears in the eastern equatorial Atlantic basin (day −15). In the following days, convection enhances while it propagates westward along the equator, reaches its maximum strength in the western Atlantic region by day 0, and further progresses westward on day 6, affecting the Caribbean Sea and Central America. The westward propagation of a negative OLR signal is seen in the unfiltered field (Fig. 8b, right panels), suggesting that Rossby waves dominate intraseasonal convection over the tropical Atlantic Ocean for these events.
The Rossby wave–dominated events in the central Atlantic are quite similar, except that convective anomaly is first initiated over the African continent, subsequently enhances in the eastern and central equatorial Atlantic basin, and then weakens in the western basin. These results suggest that Rossby waves can be generated in the eastern equatorial Atlantic and intensify as they propagate westward (Fig. 8b; left panels), or they can be generated over the African continent and subsequently strengthen over the equatorial Atlantic Ocean (Fig. 9, right panels). These evolution processes are more clearly seen in Fig. 11 (right panels), in which the impact of Rossby waves as indicated by negative OLR anomalies can extend to 70°W. The reason for their intensification over the Atlantic Ocean needs further investigation.
In contrast, for the Rossby wave–dominated convective events in the West African monsoon region, their influences on surface wind and convection in the Atlantic Ocean are due to westward-propagating Rossby waves generated in the monsoon area. Convection anomalies weaken, rather than enhance, as they propagate westward to the central and western Atlantic basin. The maximum westerly wind anomalies to the west of the convective maxima exhibit westward propagation together with the negative OLR maxima (Fig. 10b; day 0 to day 6). Consistent with the filtered fields, apparent westward propagation of negative OLR signals is also seen in the unfiltered total field for the central and eastern Atlantic cases (not shown).
To further demonstrate that the westward-propagating signals have Rossby wave structure, we compare the 850-mb winds and OLR from the 20–100-day westward wavenumber 1–6 filtered fields, which isolate the equatorial Rossby waves, 20–100-day filtered without wavenumber filtering, and the unfiltered fields based on the convective index in the central Atlantic (Fig. 12). Evidently, the winds and OLR associated with the Rossby waves (Fig. 12, left column) show symmetric properties about the ITCZ, which serves as the dynamic equator. Their structures exhibit the characteristics of the first meridional mode equatorial Rossby waves (Kiladis and Wheeler 1995; Molinari et al. 2007), which are also seen in the 20–100-day filtered fields without zonal wavenumber filtering (middle column) and are discernible in the unfiltered fields (right column). Similar results are also observed in Rossby wave–dominated western Atlantic and African monsoon cases (not shown). These results demonstrate that Rossby waves are one of the mechanisms that organize intraseasonal variability of convection and surface winds over the tropical Atlantic Ocean.
In addition, we investigated the relationship between the MJO-dominated convective events and the phase of the Rossby waves. About 82% of the MJO-dominated convective events interfere constructively with the Rossby waves in the western Atlantic, and 94% in both the central Atlantic and West African monsoon regions. This suggests that the MJO and Rossby waves together can amplify their effects on convection and surface winds over the tropical Atlantic Ocean and African monsoon region. The convective signals of the MJO and Rossby waves, however, are not significantly correlated. The correlation coefficients between the MJO and Rossby wave convections are −0.02 in the western Atlantic, 0.0012 in the central Atlantic, and 0.218 in the African monsoon region. The −10- to +10-day lagged correlations are also weak.
Previous studies have shown different mechanisms of the Rossby waves generated in the African monsoon region (Gu and Adler 2004; Gu 2009; Janicot et al. 2011; Taylor 2008; Taylor et al. 2011). Figure 10b is similar to the observation of Sultan and Janicot (2003b) for the 25–60-day westward intraseasonal signals. Here it shows the dissipated Rossby waves from African monsoon region. We also checked the evolution of individual selected Rossby wave events for different regions. The strength variations of the convective signals from individual events are consistent with the composite maps (not shown). However the cases that the Rossby waves strengthen or even originate over the Atlantic Ocean (Figs. 8b and 9b) have not been addressed before.
The Rossby waves developed in the Atlantic can have significant effects on intraseasonal variability of convection and surface winds in the western Atlantic, Caribbean Sea, and Central America. The Rossby wave–dominated convective events, which reach a maximum in the African monsoon region, show less impact on the western Atlantic due to the reduced strength during their westward propagation. The evolution of tropical and subtropical convective activities shown by the OLR data above are further confirmed by using GPCP data with 1° × 1° resolution (Yu et al. 2011; not shown here). The related large-scale circulations and SST impacts on the maintenance, development, and propagation of the intraseasonal signals over Atlantic remain unclear, and will be explored in our future research.
4. Summary and conclusions
Intraseasonal variability (10–100-day periods) of convection and surface wind in the tropical Atlantic is analyzed using satellite wind, outgoing longwave radiation (OLR), precipitation, and ERA-Interim products for the period of 2000–08. Both westward- and eastward-propagating intraseasonal signals are observed from surface winds, OLR, and precipitation fields. The MJO dominates the 20–100-day eastward-propagating signals, and Rossby waves dominate the 10–100-day and 20–100-day westward-propagating signals (Fig. 1).
Generally, the MJO generated in the Indo-Pacific Ocean (Fig. 3 and left panels of Figs. 8–11) can propagate across the equatorial Atlantic to affect the African monsoon. On the other hand, Rossby waves can also be generated in the eastern equatorial Atlantic Ocean, in addition to the African monsoon region shown by previous studies. The Rossby waves propagate westward (Figs. 5 and 8b and right panels of Figs. 9–11), affecting the entire tropical Atlantic basin and even the Caribbean Sea and Central America. Of particular interest is that the MJO can be enhanced over the tropical Atlantic Ocean while they propagate eastward, amplifying their influence on intraseasonal variability of convection in the African monsoon (Figs. 9a and 10a); some Rossby waves can strengthen while they propagate westward across the tropical Atlantic, dominating the intraseasonal variability of convection and surface winds in the west (Figs. 8b and 9b).
The relative contributions from westward and eastward signals related to different atmospheric processes vary in different regions. At 20–100-day periods, the MJO has a larger contribution to convection and more frequently dominates the observed strong convective events in the African monsoon region than Rossby waves, with an STD of OLR variability of 6.6 versus 4.0 W m−2 (Table 1; Fig. 7). Rossby waves are more important in the western Atlantic Ocean than the MJO, with an STD of 5.2 versus 4.3 W m−2 (Table 1; Fig. 7). Both the MJO and Rossby waves contribute approximately equally in the central Atlantic basin.
The impacts of intraseasonal variability have significant seasonality. While the MJO is more intense during November–April than during May–October in all three regions defined in Fig. 6, the intraseasonal Rossby waves are stronger during November–April only in the African monsoon region, and they are comparable for the two seasons in the western and central Atlantic basins (Fig. 7). Indeed, there are more Rossby wave–dominated convective events during May–October in the western and central Atlantic (Fig. 7), which account for the observed westward-propagating signals of the 20–100-day OLR for this season (Fig. 2).
Results presented here support the notion that the MJO can propagate eastward, affecting the African monsoon precipitation system. The results also support previous studies that Rossby waves from African monsoon precipitation can propagate westward to affect the tropical Atlantic Ocean. In addition, this study presents a few new findings. First, the relative importance of MJO and Rossby waves in causing intraseasonal variability of convection and surface wind is quantitatively assessed in the tropical Atlantic Ocean and African monsoon region. Second, some strong convective events associated with the MJO and Rossby waves can be enhanced while they propagate eastward (westward) across the Atlantic Ocean. Finally, Rossby waves can also be generated in the eastern equatorial Atlantic Ocean, not only in the African monsoon region. Under what conditions do the MJO and Rossby wave strengthen, and what are the roles played by air–sea interaction over the Atlantic Ocean? What are the generating mechanisms for the Rossby waves from the eastern equatorial Atlantic basin? These questions remain to be answered in our future research.
Acknowledgments
We thank ECMWF and NCAR for the ERA-40 and ERA-Interim fields. The daily OLR data were provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their web site at http://www.cdc.noaa.gov/. The QuikSCAT winds were produced by Remote Sensing Systems sponsored by the NASA Ocean Vector Winds Science Team (OVWST; http://winds.jpl.nasa.gov/people/scientists.cfm). Weiqing Han is supported by NOAA NA11OAR4310100 and NASA Ocean Surface Topography Science Team award NNX08AR62G.
REFERENCES
Alaka, G. J., and E. D. Maloney, 2012: The influence of the MJO on upstream precursors to African easterly waves. J. Climate, 25, 3219–3236.
Arkin, P. A., and P. E. Ardanuy, 1989: Estimating climatic-scale precipitation from space: A review. J. Climate, 2, 1229–1238.
Duchon, C. E., 1979: Lanczos filtering in one and two dimensions. J. Appl. Meteor., 18, 1016–1022.
Foltz, G. R., and M. J. McPhaden, 2004: The 30-70 day oscillations in the tropical Atlantic. Geophys. Res. Lett., 31, L15205, doi:10.1029/2004GL020023.
Grodsky, S. A., and J. A. Carton, 2001: Coupled land/atmosphere interactions in the West African monsoon. Geophys. Res. Lett., 28, 1503–1506.
Gu, G., 2009: Intraseasonal variability in the equatorial Atlantic–West Africa during March–June. Climate Dyn., 32, 457–471.
Gu, G., and R. F. Adler, 2004: Seasonal evolution and variability associated with the West African monsoon system. J. Climate, 17, 3364–3377.
Han, W., P. J. Webster, J.-L. Lin, W. T. Liu, R. Fu, D. Yuan, and A. Hu, 2008: Dynamics of intraseasonal sea level and thermocline variability in the equatorial Atlantic during 2002–2003. J. Phys. Oceanogr., 38, 945–967.
Hendon, H. H., and M. L. Salby, 1994: The life cycle of Madden–Julian oscillation. J. Atmos. Sci., 51, 2225–2237.
Hoskins, B. J., and G.-Y. Yang, 2000: The equatorial response to higher-latitude forcing. J. Atmos. Sci., 57, 1197–1213.
Janicot, S., and B. Sultan, 2001: Intra-seasonal modulation of convection in the West African monsoon. Geophys. Res. Lett., 28, 523–526.
Janicot, S., F. Mounier, N. M. J. Hall, S. Leroux, B. Sultan, and G. N. Kiladis, 2009: Dynamics of the West African monsoon: Part IV: Analysis of 25–90-day variability of convection and the role of the Indian monsoon. J. Climate, 22, 1541–1565.
Janicot, S., and Coauthors, 2011: Intraseasonal variability of the West African monsoon. Atmos. Sci. Lett., 12, 58–66.
Jones, C., M. V. Carvalho, R. W. Higgins, D. E. Waliser, and J. K. E. Schemm, 2004: Climatology of tropical intraseasonal convective anomalies: 1979–2002. J. Climate, 17, 523–539.
Kiladis, G., and M. Wheeler, 1995: Horizontal and vertical structure of observed tropospheric equatorial Rossby waves. J. Geophys. Res., 100 (D11), 22 981–22 997.
Liebmann, B., and C. A. Smith, 1996: Description of a complete (interpolated), outgoing longwave radiation dataset. Bull. Amer. Meteor. Soc., 77, 1275–1277.
Liebmann, B., C. A. Smith, L. M. V. Carvalho, C. Jones, C. S. Vera, I. Bladé, and D. Allured, 2009: Origin of convectively coupled Kelvin waves over South America. J. Climate, 22, 300–315.
Madden, R. A., and P. R. Julian, 1971: Detection of a 40–50 day oscillation in the zonal wind in the tropical Pacific. J. Atmos. Sci., 28, 702–708.
Madden, R. A., and P. R. Julian, 1972: Description of global-scale circulation cells in the tropics with a 40–50 day period. J. Atmos. Sci., 29, 1109–1123.
Madden, R. A., and P. R. Julian, 1994: Observations of the 40–50-day tropical oscillation—A review. Mon. Wea. Rev., 122, 814–837.
Maloney, E. D., and J. Shaman, 2008: Intraseasonal variability of the West African monsoon and Atlantic ITCZ. J. Climate, 21, 2898–2918.
Maloney, E. D., D. B. Chelton, and S. K. Esbensen, 2008: Subseasonal SST variability in the tropical eastern North Pacific during boreal summer. J. Climate, 21, 4149–4167.
Maloney, E. D., A. H. Sobel, and W. M. Hannah, 2010: Intraseasonal variability in an aquaplanet general circulation model. J. Adv. Model. Earth Syst., 2 (5), doi:10.3894/JAMES.2010.2.5.
Matthews, A. J., 2000: Propagation mechanisms for the Madden–Julian oscillation. Quart. J. Roy. Meteor. Soc., 126, 2637–2651.
Matthews, A. J., 2004: Intraseasonal variability over tropical Africa during northern summer. J. Climate, 17, 2427–2440.
Milliff, R. F., and R. A. Madden, 1996: The existence and vertical structure of fast, eastward-moving disturbances in the equatorial troposphere. J. Atmos. Sci., 53, 586–597.
Molinari, J., K. Lombardo, and D. Vollaro, 2007: Tropical cyclogenesis within an equatorial Rossby wave packet. J. Atmos. Sci., 64, 1301–1317.
Mounier, F., S. Janicot, and G. N. Kiladis, 2008: The West African monsoon dynamics. Part III: The quasi-biweekly zonal dipole. J. Climate, 21, 1911–1928.
Nicholson, S. E., and J. P. Grist, 2003: The seasonal evolution of the atmospheric circulation over West Africa and equatorial Africa. J. Climate, 16, 1013–1030.
Pan, L.-L. and T. Li, 2008: Interactions between the tropical ISO and midlatitude low-frequency flow. Climate Dyn., 31, 375–388.
Park, C.-K., and S. D. Schubert, 1993: Remotely forced intraseasonal oscillations over the tropical Atlantic. J. Atmos. Sci., 50, 89–103.
Redelsperger, J.-L., A. Diongue, A. Diedhiou, J. P. Ceron, M. Diop, J. F. Gueremy, and J. P. Lafore, 2002: Multi-scale description of a Sahelian synoptic weather system representative of the West African monsoon. Quart. J. Roy. Meteor. Soc., 128, 1229–1257.
Redelsperger, J.-L., C. D. Thorncroft, A. Diedhiou, T. Lebel, D. J. Parker, and J. Polcher, 2006: African Monsoon Multidisciplinary Analysis: An international research project and field campaign. Bull. Amer. Meteor. Soc., 87, 1739–1746.
Shapiro, L. J., and S. B. Goldenberg, 1993: Intraseasonal oscillations over the Atlantic. J. Climate, 6, 677–699.
Simmons, A., S. Uppala, D. Dee, and S. Kobayashi, 2007: ERA-Interim: New ECMWF reanalysis products from 1989 onwards. ECMWF Newsletter, No. 110, ECMWF, Reading, United Kingdom, 25–35.
Sultan, B., and S. Janicot, 2003a: The West African monsoon dynamics. Part I: Documentation of intraseasonal variability. J. Climate, 16, 3389–3406.
Sultan, B., and S. Janicot, 2003b: The West African monsoon dynamics. Part II: The “preonset” and “onset” of the summer monsoon. J. Climate, 16, 3407–3427.
Taylor, C. M., 2008: Intraseasonal land–atmosphere coupling in the West African monsoon. J. Climate, 21, 6636–6648.
Taylor, C. M., and Coauthors, 2011: New perspectives on land–atmosphere feedbacks from the African Monsoon Multidisciplinary Analysis. Atmos. Sci. Lett., 12, 38–44, doi:10.1002/asl.336.
Thorncroft, C. D., and Coauthors, 2003: The JET2000 project: Aircraft observations of the African easterly jet and African easterly waves. Bull. Amer. Meteor. Soc., 84, 337–351.
Ventrice, M. J., C. D. Thorncroft, and P. E. Roundy, 2011: The Madden–Julian oscillation’s influence on African easterly waves and downstream tropical cyclogenesis. Mon. Wea. Rev., 139, 2704–2722.
Waliser, D., and Coauthors, 2009: MJO simulation diagnostics. J. Climate, 22, 3006–3030.
Wheeler, M. C., and G. N. Kiladis, 1999: Convectively coupled equatorial waves: Analysis of clouds and temperature in the wavenumber–frequency domain. J. Atmos. Sci., 56, 374–399.
Wheeler, M. C., and H. H. Hendon, 2004: An all-season real-time multivariate MJO index: Development of an index for monitoring and prediction. Mon. Wea. Rev., 132, 1917–1932.
Xie, P., and P. A. Arkin, 1996: Analyses of global monthly precipitation using gauge observations, satellite estimates, and numerical model predictions. J. Climate, 9, 840–858.
Yu, W., W. Han, E. D. Maloney, D. Gochis, and S. Xie, 2011: Observations of eastward propagation of atmospheric intraseasonal oscillations from the Pacific to the Atlantic. J. Geophys. Res., 116, D02101, doi:10.1029/2010JD014336.