Tropical Easterly Waves in the Tropical North Atlantic Basin

ABSTRACT

Tropical easterly waves (TEWs) serve as precursors to most Atlantic tropical cyclones and strongly modulate the hydrological cycle over West Africa, the tropical Atlantic, and the Caribbean region. Despite significant advances, uncertainties remain regarding the processes governing TEW maintenance and intensification, the relationship with tropical cyclogenesis, and future projections of TEW activity under global warming. Progress on these fronts is constrained by persistent disparities in tracking methodologies, limited observational understanding of moisture–convection feedbacks across scales, and the inability of global climate models to resolve small‐scale processes. This review synthesizes the current state of TEW research, from genesis and tracking methodologies to the multiscale impacts of TEWs on tropical cyclogenesis and regional precipitation, and accounts for the modulation of climate variability modes and future behavior under global warming. We also propose a coordinated research roadmap, including a community‐driven intercomparison initiative analogous to those successfully implemented for other complex atmospheric phenomena to reconcile uncertainties in tracking methodologies. In addition, we stress the need for intensive field campaigns to validate high‐resolution convection‐permitting modeling and train artificial intelligence–driven algorithms. Taken together, these initiatives provide a pathway to resolve outstanding uncertainties and improve the reliability of future TEW projections under global warming.

Tropical easterly waves (TEWs) serve as precursors to North Atlantic tropical cyclones and act as key modulators of regional rainfall. This review synthesizes current TEW research on genesis mechanisms, tracking methodologies, the influence of climate variability modes, and uncertainties in future projections. It also proposes a research roadmap that integrates standardized tracking methodologies, advanced modeling, and artificial intelligence algorithms to reduce uncertainty about future wave activity under global warming.

1. Introduction

Tropical easterly waves (TEWs) are synoptic‐scale weather systems that propagate westward across tropical regions with characteristic periods of 2–7 days, horizontal wavelengths of approximately 3000 km, and phase speeds of 7–8 m/s [1−6]. Those originating over Africa, commonly termed African Easterly Waves (AEWs; hereafter referred to as African‐origin TEWs), are the most extensively documented subset of TEWs and form primarily through the mixed baroclinic and barotropic instabilities of the African Easterly Jet (AEJ), driven by meridional moisture and temperature gradients across the Sahel and Sahara [2, 4, 7].

Research on African‐origin TEWs has evolved considerably since the first descriptions of African disturbances in the 1930s [8] and the seminal identification of the inverted trough structure [9]. Simpson et al. [10] used satellite and surface data to establish the characteristic 3–5 day periodicity and spatial scales of African‐origin TEWs, while Burpee [1] provided the foundational theory linking wave genesis to barotropic–baroclinic instabilities of the AEJ. Meanwhile, Carlson [11] noted the role of the East African topography in enhancing convection and fostering African‐origin TEWs development. The Global Atmospheric Research Programme Atlantic Tropical Experiment (GATE) field campaign in 1974 offered the first comprehensive observational view of African‐origin TEWs structure and convection–wave interactions [3, 12], with later campaigns, such as NASA's African Monsoon Multidisciplinary Analyses (NAMMA) and the African Monsoon Multidisciplinary Analyses (AMMA) in 2006, further advancing understanding of wave activity [13, 14]. The idea of an unstable jet was questioned by Hall et al. [15] and Thorncroft et al. [7], showing that the AEJ is marginally unstable and that its presence is not a necessary condition for African‐origin TEW formation. Meanwhile, Berry and Thorncroft [16] and Mekonnen et al. [17] showed the importance of active convection in African‐origin TEWs genesis. A comprehensive historical overview of African‐origin TEWs research can be found in Núñez‐Ocasio et al. [18].

The significance of TEWs is twofold: they act as drivers of regional hydroclimatology and serve as precursors of tropical cyclones (TCs). Over West Africa (WA), African‐origin TEWs strongly modulate rainfall and organize convection through their interaction with squall lines and mesoscale convective systems (MCSs), with distinct rainfall responses associated with the 3–5‐day and 6–9‐day wave regimes [19−21]. Farther west, TEWs also contribute to seasonal precipitation across the Caribbean and Central America [22, 23]. In addition, African‐origin TEWs serve as precursors to approximately 60% of Atlantic TCs and more than 80% of major hurricanes [24−26]. Recent studies have extended this established relationship by examining the influence of African‐origin TEWs on Atlantic TC tracks and landfall in large modeling ensembles [27, 28].

Previous studies have pointed out that TEW behavior emerges from interactions across multiple spatial and temporal scales, including wave–convection coupling, mesoscale convective organization, monsoon variability, and large‐scale climate modes. However, these processes have often been examined separately or within specific regional and disciplinary contexts. A more integrated framework is, therefore, needed to connect micro‐ and mesoscale convective processes with synoptic TEW dynamics and planetary‐scale climate variability throughout the complete wave lifecycle. Furthermore, as the community grapples with a lack of long‐term observational datasets and conflicting model projections of future wave activity [29−32], there is a pressing need to deepen our understanding of wave behavior and its underlying mechanisms across scales.

While African‐origin TEWs constitute the dominant source of disturbances entering the tropical North Atlantic (NATL) from the east, wave activity in this basin is not exclusively African in origin. Climatological and modeling studies indicate that TEWs can also develop in situ over the tropical NATL, the Caribbean and the Intra‐Americas Seas, where regional topography, jet structures, and thermodynamic gradients provide favorable conditions for local genesis [33−36]. Accordingly, this review adopts a broad definition of the tropical NATL TEW system, encompassing both African‐origin disturbances and regionally generated waves (referred to as regional TEWs). We maintain this terminological distinction consistently throughout the manuscript to differentiate between the genesis mechanisms and structural characteristics, while recognizing that both contribute to the synoptic‐scale variability that modulates regional hydroclimatology across the basin.

Recently, Núñez‐Ocasio et al. [18] developed a comprehensive review focused on African‐origin TEWs, synthesizing advances in their formation, dynamical structure, energetics, and tracking methodologies. While that work provides an essential, in‐depth analysis of the African‐origin TEW lifecycle over Africa, this review integrates the existing literature on TEW‐driven precipitation, tropical cyclogenesis, interannual climate variability, and future projections to present an up‐to‐date, comprehensive synthesis of TEWs activity in the tropical NATL, including both African‐origin and regional systems. We systematically evaluate the current state of knowledge through the following thematic lenses: (i) TEW genesis mechanisms; (ii) advances in TEW tracking methodologies; (iii) the influence of climate variability modes on wave activity; (iv) the role of TEWs in tropical cyclogenesis; (v) the relationship between TEWs and regional precipitation; and (vi) future projections of TEWs behavior under global warming. By analyzing the multiscale atmospheric interactions that define the complete TEW lifecycle, this work synthesizes state‐of‐the‐art to provide a cohesive research roadmap.

2. Genesis of TEWs

The genesis of African‐origin TEWs has traditionally been interpreted within the framework of mixed barotropic–baroclinic instability of the AEJ. Reversals in the meridional potential‐vorticity (PV) gradient, together with the horizontal and vertical wind shear associated with the summer AEJ, provide an environment favorable for the growth and amplification of synoptic‐scale disturbances over WA and the eastern Atlantic [1, 37−41]. However, the finite zonal extent of the AEJ raises questions about whether spontaneous modal instability alone can explain the initiation of observed African‐origin TEWs [7, 15]. Observational and modeling studies [7, 16, 17, 42, 43] also indicate that the AEJ may act as a favorable waveguide and energy source, while finite‐amplitude disturbances generated by organized convection, diabatic heating, topography, and other tropical perturbations provide the initial forcing required for wave development (Figure 1). In this coupled dynamical–convective framework, convection is not merely a response to a pre‐existing wave; the associated diabatic heating can generate or reinforce vorticity and PV anomalies, thereby contributing to the initiation, amplification, and maintenance of the disturbance [44, 45]. This coupled evolution may also be influenced by interactions with other tropical disturbances. In particular, convectively coupled Kelvin waves can enhance convection over eastern Africa and, through their interaction with regional topography and organized convective systems, contribute to the initiation or amplification of low‐level African‐origin TEWs [46, 47]. This relationship is, therefore, bidirectional: tropical waves modulate the timing and organization of convection, while diabatic heating associated with organized convection can reinforce vorticity and promote subsequent wave development.

FIGURE 1.

Schematic representation of the formation and initialization mechanisms of tropical easterly waves (TEWs) over Africa. The African Easterly Jet (AEJ; gray arrow) is depicted at 600–700 hPa pressure levels. The sharp meridional thermal and moisture gradients between the warm, dry Saharan air mass to the north and the cooler, moist flow from the Gulf of Guinea to the south generate baroclinic and barotropic instabilities, which serve as the primary energy sources for synoptic‐scale perturbations. Initial wave disturbances (red dashed line) are also influenced by the orographic Ethiopian Highlands and propagate westward across the continent, further modulated by the Guinea Highlands before crossing the coast toward the tropical Atlantic.

In addition to dynamical and convective processes, the West African Monsoon (WAM) also plays a central role in the initiation and early development of African‐origin TEWs from June to September, coinciding with the peak season of TEWs activity [5, 6]. The seasonal evolution of the monsoon circulation and associated cloud–radiative effects can modify the thermodynamic and dynamical environment in which these waves develop [48, 49]. Topography adds a further layer of complexity; modeling studies indicate that African highlands can modify the structure of the AEJ and influence wave energetics and regional development (Figure 1), partly through their effects on background baroclinicity and the spatial organization of convection [50]. In particular, the Ethiopian Highlands and the Guinea Highlands appear to be especially important regional features affecting rainfall and wave characteristics and, in turn, influencing where disturbances are initiated and how they evolve downstream [50, 51].

Recent studies further suggest that air moisture plays an important role in the TEWs development over WA. Modeling studies have shown that growth and propagation of waves embedded within the WAM depend strongly on the surrounding moisture field, highlighting the active role of moisture in wave amplification and convective coupling [52]. These studies suggest that the growth and propagation of disturbances embedded within the WAM are strongly controlled by the surrounding moisture field [52], and earlier work likewise indicates that moist processes can substantially modify the AEJ wave system and the organization of convection associated with these disturbances [17, 53, 54]. In addition, upstream disturbances and multiscale interactions, rather than local instability alone, can also act as a trigger for wave development [55], suggesting that finite‐amplitude precursors may play an important role in initiating TEWs across WA. Related studies have further shown that other tropical disturbances, including convectively coupled Kelvin waves and intraseasonal variability associated with the Madden−Julian Oscillation (MJO), can modify the environment in which these waves emerge, thereby influencing their timing, structure, and subsequent growth [47, 56, 57].

A complementary perspective on African‐origin TEW genesis and evolution is provided by PV analysis. Berry and Thorncroft [16] applied a PV–potential temperature framework to the lifecycle of an intense African‐origin TEW and proposed a three‐stage conceptual model involving convectively forced initiation, baroclinic growth through the interaction of low‐level thermal anomalies with the mid‐tropospheric PV strip, and downstream amplification through the generation and merger of convectively produced PV anomalies. Subsequent studies further showed that African‐origin TEWs are characterized by coherent vorticity and PV anomalies that tilt eastward below the AEJ and westward above it, a configuration consistent with baroclinic growth and convective amplification [45, 58]. This framework connects the classical instability interpretation with the active roles of moist convection, diabatic PV generation, and environmental moisture. More recently, Fischer et al. [59] demonstrated that the three‐dimensional PV structures associated with African‐origin TEWs can be objectively identified and tracked within a climatological framework. Overall, the PV perspective supports an interpretation of African‐origin TEW genesis and evolution as the combined result of dynamical instability, diabatic forcing, and convective feedbacks [45, 60].

Although most TEWs crossing the tropical NATL originate over Africa, the origin of disturbances observed farther west is not always unambiguous. Kiladis et al. [61] documented the structural evolution of African‐origin TEWs from WA into the adjacent tropical NATL, and some of these disturbances remain coherent as they propagate farther west. Serra et al. [34] found that some wave signatures can be traced continuously from the Atlantic into the Caribbean, with particularly strong coherence across Costa Rica and Panama. However, their analysis also identified regional genesis and amplification maxima over the western Caribbean, where the Caribbean low‐level jet (CLLJ) can provide a local source of wave energy. Thus, TEWs observed west of 40°W may include both downstream extensions of African‐origin disturbances and waves that develop or reintensify regionally within the Intra‐Americas Seas. Climatologically, approximately 50–60 TEWs form over Africa during a typical boreal summer and hurricane season. Enyew and Mekonnen [62] identified an average of approximately 38 mature African‐origin TEWs per year crossing the WA coast during July–October, with substantial interannual variability. These estimates refer to waves reaching the African coast and should not be interpreted as the number that remain coherent as far west as the Caribbean region.

TEWs formed over the Intra‐Americas Seas evolve within a large‐scale environment that differs markedly from the WAM waveguide. Over the Intra‐Americas Seas, the background state is shaped by complex topography, the Western Hemisphere Warm Pool, the Intertropical Convergence Zone (ITCZ), persistent deep convection over the Panama Bight, and regional jet structures, all of which favor regional wave development. Idealized and case‐based modeling studies have accordingly shown that some easterly waves in this sector can undergo in situ genesis [35, 36]. Over the Caribbean, wave activity remains dynamically connected to African‐origin disturbances, but not all such waves reach the basin, and those that do may weaken, reorganize, or intensify depending on the local moisture field, convective coupling, and interaction with the CLLJ [63]. Recent studies further indicate that Caribbean TEWs exhibit structural and thermodynamic characteristics consistent with moisture‐modulated growth, including behavior compatible with moisture–vortex instability, underscoring the importance of regional thermodynamic structure in addition to upstream forcing [64, 65].

From this perspective, TEWs over the tropical NATL are best viewed as the outcome of a dynamically connected tropical system in which African precursor disturbances, regional jet instability, moist convection, latent heating, environmental humidity, topography and, at times, remote wave forcing can all contribute to wave initiation, maintenance, and amplification. This multiscale framework is especially relevant for the tropical NATL because it links the continental origin of many TEWs to their subsequent evolution across the Atlantic and Caribbean, while also recognizing that regional environments may support the development or reintensification of waves away from their source region.

3. TEW Tracking

Unlike TCs [66, 67], TEWs lack a continuous observational record, presenting a critical challenge for researchers. Consequently, the community depends on tracking algorithms to extract their climatological activity and structure from reanalysis or satellite data [33]. This reliance on proxy identification, however, has sometimes led to contradictory sets of climatologies, as there is no universally accepted tracking method [5, 33, 59]. In this context, the same TEW can be characterized differently depending on the chosen variable (e.g., meridional wind at 850 hPa vs. relative vorticity at 700 hPa) and tracking approach [68, 69]. Additionally, these heterogeneous climatologies further undermine the comparison of long‐term trends and the validation of global climate models, as wave counts vary significantly across different approaches [70].

While early studies relied on manual tracking (e.g., see Refs. [1, 71, 72]), current methodologies broadly utilize objective techniques centered on specific atmospheric variables (Figure 2 and Table S1). Because TEWs are complex systems comprising coupled kinematic and convective structures, the choice of tracking variable fundamentally dictates the resulting climatology. For instance, algorithms utilizing satellite‐derived outgoing longwave radiation (OLR) delineate the wave's convective envelope and associated cloud shielding [61, 73]. However, because deep convection is frequently decoupled from the dynamic wave center, OLR‐based identification often yields discontinuous and structurally ambiguous trajectories. In addition, these algorithms tend to capture longer wavelengths representative of upper‐tropospheric mixed Rossby‐gravity waves, resulting in different frequency and wavelength statistics compared to low‐level vorticity tracking [74]. Consequently, OLR‐based climatologies tend to underrepresent waves with weak or intermittent convection, skewing the detected population toward strongly convective systems. To develop robust, large‐scale climatologies, objective tracking typically identifies extrema in dynamical fields, such as meridional wind via Hovmöller diagrams (e.g., see Refs. [63, 75−77]), relative vorticity [68, 78−80], or relative vorticity combined with satellite brightness temperature [81]. Following Núñez‐Ocasio et al. [18], these objective tracking methods can be grouped into three families: (i) the TH01 family [5, 34, 74, 78, 79], which is based on the application of the TRACK algorithm developed by Hodges [82−84] detecting vorticity maxima and linking them via cost‐function minimization; (ii) the curvature vorticity (CV) Hovmöller family [31, 47, 68, 69, 85−87], which tracks CV features through Hovmöller analysis; and (iii) the trough line family [33, 59, 88], which stitches trough axes in time. For a comprehensive discussion of these tracking method families, see Núñez‐Ocasio et al. [18]. Regarding the tracking variable, utilizing relative vorticity introduces distinct analytical challenges, as this field is inherently noisy, sensitive to model grid resolution, and heavily influenced by background horizontal wind shear. To address these limitations, a growing number of studies (e.g., see Refs. [5, 6, 27, 33, 47, 89, 90, 91]; see Figure 2 and Table S1) have used CV for wave detection. By minimizing the influence of background shear, CV removes biases associated with the strength of the AEJ and provides a more accurate proxy for wave strength and coherence [69, 88, 91]. Recently, Fischer et al. [59] proposed an objective tracking using CV and Hilbert transform to effectively identify and collect 3D PV structures associated with specific waves. Table S1 summarizes the 36 studies considered in this review and corresponding tracking methodologies. Crucially, these methodological choices are not neutral with respect to the resulting climatology. Each tracking approach captures distinct features of the wave system, and the limitations inherent to the tracking method propagate directly into the climatology. Belanger et al. [33] demonstrated that when identical objective tracking criteria are applied across different datasets, seasonal cycles and broad spatial patterns are robust, but absolute wave counts, track densities, and intensity metrics differ substantially, particularly for weaker systems, indicating that discrepancies in climatologies arise not only from tracking methods but also from the underlying dataset used, likely linked to differences in subgrid‐scale parameterizations and resolution [5, 6, 33]. This behavior is not unique to TEW tracking, having been observed in tracking other weather systems, including extratropical cyclones [92], TCs [93], and atmospheric rivers [94]. Consequently, comparing across studies that employ different tracking methods, datasets, or both remains challenging.

FIGURE 2.

Summary of the variables used in the 36 studies found in the literature for tracking tropical easterly waves (TEWs). Proportions are based on the primary variable used in the tracking algorithm. For a comprehensive list of the specific references and methodology associated with each category, see Table S1.

The performance of any tracking algorithm is constrained by the interplay between the chosen variable, the tracking level, and the thresholds applied. Regardless of the chosen variable, tracking is usually performed at specific pressure levels (most commonly 850, 700, and 600 hPa; see Table S1) and relies on strict post‐processing thresholds, such as a minimum lifespan of 2 days, westward propagation constraints, and minimum travel distances, to filter out transient mesoscale noise [81]. On this basis, these tracking methodologies possess inherent limitations that can skew analysis. For example, tracking based on relative vorticity or relative vorticity anomalies (e.g., see Ref. [68]) struggles in highly sheared environments (e.g., the southern Caribbean). Meanwhile, temporal bandpass filtering requires a long time series that restricts its use for real‐time forecasting [33]. A significant limitation of many conventional tracking frameworks (e.g., see Refs. [68, 75]) is their inherent spatial bias. Most algorithms are designed to capture systems propagating from Africa into the tropical Atlantic, thereby systematically overlooking disturbances that initiate in situ over the Atlantic and Caribbean region, as well as short‐lived waves that both develop and dissipate entirely over the African continent [33]. Furthermore, automated trackers depend on user‐defined thresholds (e.g., vorticity maxima) that inadvertently filter out weak or nascent waves during the early stages of their life cycle or fail to continuously track a wave once it has weakened below the tracking threshold but later strengthens [69, 78]. Therefore, threshold‐dependent detection introduces a systematic intensity bias into the climatological record, favoring mature waves over weak systems and potentially misrepresenting trends in wave genesis or dissipation. In addition, studies relying on a single tracking level also fail to capture the full spectrum of TEWs. For example, Hollis et al. [5] tracked TEWs at both 850 and 700 hPa. Northern Hemisphere TEWs were well defined at both levels, although the study showed level‐dependent differences in annual wave frequency across basins and in their spatial distribution over Africa. Substantially fewer TEWs were identified at 850 hPa than at 700 hPa, showing that estimated wave counts depend strongly on the selected tracking level. Over Africa, however, detections at these two levels should not necessarily be interpreted as independent wave populations. Classical observational and tracking studies describe a vertically and meridionally tilted African‐origin TEW structure, with low‐level cyclonic activity generally located farther north and mid‐tropospheric activity displaced equatorward toward regions of deeper convection [78, 79, 95, 96]. These low‐ and mid‐level structures may become more vertically aligned as some waves approach the WA coast and propagate over the tropical Atlantic. Hollis et al. [97] further found that vertically collocated 700‐ and 850‐hPa waves were associated with stronger and more organized precipitation than noncollocated waves. Among noncollocated detections, 850‐hPa waves exhibited higher rain rates than those tracked only at 700 hPa. Thus, tracking at different pressure levels may sample vertically connected components or different evolutionary stages of the same three‐dimensional disturbance, while also identifying distinct shallow or mid‐level structures, thereby affecting estimated wave frequencies, trajectories, and precipitation characteristics.

Recent advancements have seen the rise of deep learning models that can identify waves by learning the complex spatial patterns of moisture and wind together, rather than relying on a single‐variable threshold [98, 99]. These artificial intelligence (AI)‐driven approaches offer a promising path toward a unified global TEW climatology by identifying the structural integrity of the wave rather than just its intensity at a single point. However, given the lack of long‐term in situ observations, these studies rely on high‐resolution reanalysis products, such as ERA5 [100], or satellite data, together with human‐expert labels that serve as target “ground truth” for the algorithms.

Overall, we acknowledge that, while this review does not encompass all studies tracking TEW, the selected works (Figure 2 and Table S1) serve as a robust proxy for the broad variability in tracking methodologies. To advance the field, we argue that the community must standardize tracking protocols, moving toward multivariate algorithms that simultaneously account for kinematics and diabatic heating.

4. Influence of Climate Variability Modes on TEWs Activity

The TEWs activity in the northern and southern hemispheres is not stationary over time [5]. Wave activity, particularly those forming in WA, varies substantially across interannual and subseasonal timescales, indicating that wave climatology is strongly modulated by large‐scale climate variability rather than by the mean seasonal state alone [78, 87]. To explain this variability, it is necessary to consider not only the internal dynamics of the TEWs storm track, but also the probable influence of modes of climate variability that modulate the background state in which the waves form, amplify, and propagate across the NATL basin.

At interannual timescales, El Niño–Southern Oscillation (ENSO) is the dominant external modulator of TEWs characteristics over the tropical NATL. Lawton et al. [87] found that African‐origin TEWs are systematically stronger, wetter (moister), and more convectively organized during La Niña years compared to El Niño years. This contrast emerges over the African continent itself, indicating that ENSO acts upstream of the Atlantic by altering the conditions under which waves form and intensify in their source region. Dynamically, La Niña years are associated with a stronger Tropical Easterly Jet (TEJ) that extends farther westward into the Atlantic [101], and Lawton et al. [87] hypothesize that ENSO‐driven changes to the regional circulation over Africa, including the AEJ and WAM, potentially create background conditions that enhance convection near propagating waves and amplify thermodynamic instabilities. The latter is consistent with the coupled dynamical–convective framework, wherein convection does not simply respond to pre‐existing disturbances but actively contributes to wave amplification through diabatic heating and PV generation (e.g., see Refs. [45, 60]). The enhanced moisture content and convective activity of TEWs during La Niña further increase their potential for tropical cyclogenesis as they propagate into the warmer, less‐sheared portion of the main developing region, consistent with early work by Ruti and Dell'Aquila [102]. They also found that warm ENSO events were associated with suppressed wave activity over the Gulf of Guinea coast through an upper‐tropospheric teleconnection bridge, while cold events favored wave enhancement. The ENSO signal in the NATL basin also operates through a well‐established downstream pathway: El Niño is associated with a large increase in vertical wind shear in the Caribbean and western Atlantic [103, 104]. While moderate shear can favor the organization of deep convection and mesoscale systems [42, 105, 106], this anomalously strong shear degrades the environment for sustained convective coupling and tropical cyclogenesis from TEWs. These results describe similar relationship mechanisms between these modes of variability and TCs in the NATL basin [107, 108].

Tropical Atlantic SST anomalies provide a second, independent source of interannual modulation that acts more locally than ENSO and is particularly relevant for the thermodynamic environment in which TEWs form and propagate westward [109]. Atlantic Niño events are characterized by SST increase along the eastern tropical Atlantic Ocean, favoring a strengthening of the Atlantic intertropical convergence zone rainband, enhancing African‐origin TEW activity and low‐level cyclonic vorticity across the deep tropical eastern NATL [110, 111, 112]. Eastern Atlantic Niño events have also been associated with stronger moisture flux convergence and enhanced monsoon rainfall over WA, consistent with a more favorable large‐scale environment for African‐origin TEW activity [113].

The coupled sea‐surface temperature–atmosphere variability in the tropical NATL is commonly described in terms of the Atlantic Meridional Mode (AMM), a climate mode associated with the cross‐equatorial meridional gradient of the sea SST anomalies in the tropical Atlantic [114]. While its influence on African‐origin TEWs activity is less well directly established than that of ENSO, the AMM is better understood as a modulation of the large‐scale tropical Atlantic environment than as a primary direct control on wave generation, since it alters meridional SST gradients, the position of the Atlantic ITCZ, and the moisture and shear conditions through which the waves propagate [115, 116, 117]. At longer timescales, the Atlantic Multidecadal Oscillation (AMO) provides an additional background state for TEWs activity. The position of the Atlantic Jet (AJ) varies with the AMO; it is situated farther north during warm phases. This northward shift correlates with heightened wave activity across WA and extending into the Atlantic, potentially explaining the increased frequency of Atlantic tropical storms observed during the warm AMO phases [118].

At subseasonal timescales (30–90 days), the MJO is the dominant component of the intraseasonal variability in the tropical atmosphere [119], also affecting the TEWs activity in the NATL basin. Over WA, the MJO produces alternating periods of enhanced and suppressed precipitation and easterly‐wave activity, accompanied by marked phase‐dependent variations in African easterly wave perturbation kinetic energy [56, 120]. This subseasonal influence is not confined to WA. MJO‐related convective anomalies may be partly communicated through eastward‐propagating convectively coupled Kelvin waves, which modify convection and the dynamical environment near the AEJ entrance region and thereby influence African‐origin TEW initiation and activity over Africa. These interactions can subsequently affect downstream tropical cyclogenesis over the Atlantic [56, 57, 121].

Overall, TEW activity is modulated by a hierarchy of climate modes acting on different timescales, as summarized in Table 1. ENSO has strong direct support as an interannual control on African‐origin TEW characteristics, tropical Atlantic SST variability provides an oceanic pathway through which the Atlantic ITCZ and the wave environment are altered, and the MJO and Kelvin waves shape the subseasonal intermittency and convective coupling of the disturbances. For a tropical NATL‐focused review, this implies that TEWs variability should be interpreted not only in terms of internal wave dynamics and mean monsoon structure, but also as the outcome of multiscale interactions between synoptic disturbances and larger‐scale climate modes.

TABLE 1.

Summary of the main modes of climate variability that modulate TEWs activity over WA and the tropical NATL, including their characteristic timescales, proposed mechanisms, and observed wave response.

Climate mode	Timescale	Main mechanism affecting TEWs	Observed TEW response	References
ENSO	Interannual	Modifies the large‐scale tropical circulation over WA and the Atlantic, including the strength and zonal extent of the TEJ, the latitude of the AEJ, and vertical wind shear over the tropical NATL.	African‐origin TEWs tend to be stronger, moister, and more convectively organized during La Niña than during El Niño; El Niño also increases downstream Atlantic–Caribbean shear, reducing convective coupling and tropical cyclogenesis potential.	Lawton et al. [87]; Ruti and Dell'Aquila [102]; Shapiro [103]; Aiyyer and Thorncroft [104]
Atlantic Niño/eastern tropical Atlantic SST anomalies	Interannual	Warmer SSTs in the eastern equatorial Atlantic strengthen the Atlantic ITCZ, enhance low‐level moisture convergence and vorticity, and favor a wetter monsoon environment near the West African coast.	Generally associated with enhanced African‐origin TEW activity and a more favorable thermodynamic environment for wave growth and propagation near the eastern NATL.	Patricola et al. [109]; Druyan and Fulakeza [110]; Kim et al. [111]; Wang et al. [112]; Xing et al. [113]
AMM	Interannual	Alters cross‐equatorial SST gradients, ITCZ position, moisture availability, and shear across the tropical Atlantic.	Likely modulates the background environment through which TEWs propagate, rather than acting as a primary direct control on wave generation.	Doi et al. [114]; Chiang and Vimont [115]; Vimont and Kossin [116]; Patricola‐DiRosario et al. [117]
AMO	Multidecadal	Modifies the decadal‐scale Atlantic background state, including the latitudinal position of the Atlantic jet and the broader environment favorable for wave activity.	Warm AMO phases have been linked to a northward‐shifted Atlantic jet and enhanced wave activity over WA and the Atlantic, potentially contributing to greater Atlantic storm activity.	Martin and Thorncroft [118]
MJO	Subseasonal (30–90 days)	Produces phase‐dependent changes in convection, humidity, and large‐scale circulation over WA and the tropical Atlantic.	Leads to alternating periods of enhanced and suppressed TEW activity, with modulation of precipitation and perturbation kinetic energy.	Zhang [119]; Alaka and Maloney [56, 120]; Ventrice et al. [121]

5. Role of TEWs in Tropical Cyclogenesis

TEWs are critical synoptic‐scale precursors for tropical cyclogenesis in the NATL basin [27, 28, 77, 122−127]. TEWs act as the primary seedlings for the hurricane season and account for around 60% of seasonal TCs, including almost all (∼85%) of major hurricanes [24, 25, 26, 27, 128, 129]. Approximately 38 mature African‐origin TEWs cross the WA coastline during the July–October period [62]. While this value is sensitive to the specific study period, dataset, and tracking algorithm employed (e.g., see Refs. [5, 6, 33]), it should be noted that only a relatively small fraction of these disturbances ultimately develop into a TC, with previous estimates ranging from approximately 14% to 20% of coast‐crossing African‐origin TEWs [62, 68]. The spatial distribution of the resulting cyclones is heavily dependent on whether the African‐origin TEWs follow a northern or southern propagation track upon exiting the African continent [96, 130, 131]. As the deep tropical Atlantic provides a more favorable background environment, African‐origin southern‐tracking systems frequently initiate cyclogenesis much farther east. In contrast, northern‐tracking waves generally require longer over‐water transit times, frequently deferring cyclogenesis over the Caribbean Sea or the Gulf of Mexico [122]. On this basis, TCs associated with southern‐track waves are approximately 1.7 times more frequent than those linked to northern‐track waves [85, 122, 126, 131]. Meanwhile, the merging of African‐origin northern‐ and southern‐track waves was found to be a precursor for one‐quarter of tropical cyclogenesis events in the eastern tropical Atlantic (east of 40°W) [132].

The transition from a synoptic‐scale TEW to a TC can be explained by the “marsupial paradigm” [77], a Lagrangian framework positing that the wave's critical layer, defined by a comoving region of closed streamline circulation, serves as the primary incubator for an incipient TC or tropical depression. Within this enclosed “marsupial pouch,” the wave's kinematic structure acts as a dynamical buffer, isolating the incipient vortex from hostile environmental factors (Figure 3), such as dry air intrusion and shear/strain deformation [77, 133]. Concurrently, this trapped environment facilitates the moisture−convection feedback loop necessary for the organization of mesoscale convective vortices into a coherent, self‐sustaining TC [134−138]. Supporting the marsupial paradigm, Asaadi et al. [139] found that all developing waves were associated with a wave pouch, whereas only 10% of nondeveloping TEWs exhibited this feature. A critical requirement for this paradigm is the four‐dimensional coherence of the pouch. The recirculation mechanism is only effective if the region maintains both temporal stability and vertical alignment [140, 141]. Fluctuations in the background environment, variations in the wave's phase velocity, or excessive vertical motion through the critical layer can disrupt this structure, thereby compromising the protection and moisture‐trapping benefits essential for cyclogenesis [85].

FIGURE 3.

Schematic representation of tropical cyclogenesis within a “marsupial” wave pouch. Dashed light blue streamlines illustrate the typical inverted‐V flow pattern observed in a stationary (ground‐based) frame of reference. The solid blue streamline delineates the wave pouch as viewed in the frame of reference moving at the same speed as the wave. This closed circulation serves as a protective container for mesoscale vortices, insulating deep convection (shaded gray) from detrimental environmental factors like the dry Saharan Air Layer. Convergent flow allows for the entrainment of environmental vorticity and air through a lateral opening. The core of the pouch—the optimal site for storm development—is defined by the intersection of the trough axis (solid brown line) and the critical latitude (solid purple line) relative to the easterly jet (solid gray line). Adapted from Wang et al. [134].

Understanding why some TEWs develop into TCs while others decay requires distinguishing between the broader population of seed disturbances and the subset of TEW‐associated TCs. Although TEWs supply the majority of Atlantic TCs, most disturbances within this wave population never undergo cyclogenesis. The marsupial paradigm [77] provides a mechanistic framework for this selection process: developing waves are characterized by a coherent, vertically aligned wave pouch that isolates incipient convection from dry‐air intrusion and disruptive shear. However, pouch formation alone is insufficient. Key discriminating factors between developing and nondeveloping TEWs include: (i) thermodynamic preconditioning where developing TEWs exhibit higher integrated water vapor, deeper moist layers, and stronger low‐level moisture flux convergence as they exit the African coast [128, 142, 143]; (ii) convective organization where developing systems are associated with more vigorous, organized MCSs [45, 124, 125]; (iii) environmental favorability, low vertical wind shear, high SSTs, and enhanced mid‐tropospheric humidity are necessary but not individually sufficient [144]; and (iv) wave amplitude, larger‐amplitude waves with stronger low‐level vorticity are more likely to undergo cyclogenesis [62, 68, 145]. The interaction of these factors is nonlinear. Thus, while a wave may exhibit a favorable pouch structure but fail to develop if it encounters dry air or excessive shear, another wave with moderate amplitude may develop if embedded in a highly favorable large‐scale environment. This inherent conditional dependence explains why the same wave population that seeds a large fraction of Atlantic TCs also includes many disturbances that never undergo cyclogenesis.

Beyond these primary discriminating factors, developing disturbances also manifest stronger radiative heating and enhanced horizontal moist static energy advection [68, 128, 142, 143]. These kinematic and thermodynamic signals have proven reliable even within forecast ensemble members, where developing members were more convectively active when crossing the African coast than the nondeveloping counterparts [146]. Furthermore, the WAM influences Atlantic tropical cyclogenesis across both seasonal and synoptic timescales. At the seasonal scale, wetter western Sahel monsoon seasons have historically been associated with enhanced major‐hurricane activity over the Atlantic, partly through related changes in the large‐scale circulation and vertical wind shear [147, 148]. At the synoptic scale, developing African‐origin TEWs tend to be associated with widespread deep convection and moist conditions around and ahead of the wave trough [62, 142]. It should be noted that convection‐permitting sensitivity experiments for an individual African‐origin TEW indicate that a more intense monsoonal flow in a moister environment can slow the westward translation of the wave and promote the decoupling of convection from the wave trough, partly because convection becomes phase‐locked with the Guinea Highlands rather than with the propagating disturbance [52]. Consequently, the thermodynamic evolution of the wave's boundary layer is a critical determinant of cyclogenesis. Recent diagnostics highlight that a net inward moisture flux toward the wave's kinematic center is a vital prerequisite for vortex intensification [149]. This convective dependence is further reflected in the marked difference in cyclogenesis rates between propagation corridors; African‐origin waves following the southern track, characterized by higher environmental moisture content, exhibit significantly higher conversion rates into TCs compared to those moving in the drier northern Sahelian pathway [122, 125].

However, it is still debated if the presence of a TEW is a necessary condition for TC development [109, 144, 145, 150−152]. Recent studies have noted that environmental conditions play a larger role than TEW strength in driving TC formation (e.g., see Refs. [144, 150, 153, 154]). Bercos‐Hickey and Patricola [155] found that suppressing the African‐origin southern and northern TEW tracks led to an unexpected increase in seasonal TC activity. This surge in cyclogenesis was linked to a more favorable Atlantic environment, with reduced wind shear and enhanced convective activity [145]. Meanwhile, Danso et al. [151], using convection‐permitting simulations, found that TC forms farther west in response to suppression of TEW activity, with implications for TC tracks and landfall probabilities. Similar results were also found by Kouski et al. [28] using TC‐permitting regional model simulations. Furthermore, Bercos‐Hickey et al. [145] cautioned against using projected changes in African‐origin TEWs frequency to predict future Atlantic TC activity. They noted that climate models frequently show conflicting responses, with projected shifts in storm frequency often appearing uncorrelated or even inversely related to changes in wave count.

These studies emphasize that TEWs function as critical synoptic‐scale precursors for tropical cyclogenesis, representing a component of a complex, multiscale convective architecture rather than an isolated catalyst. Although the observational record identifies these waves as the primary seedling mechanism for North Atlantic cyclogenesis, recent evidence suggests that their presence is not a strict requirement for storm formation. Ultimately, the transition from a seedling disturbance to a self‐sustaining vortex is governed by a synergistic interplay between the wave's vertical tilt, tropospheric moisture flux, wave amplitude, and background environmental conditions. Given the complex relationship between TEWs, the environment, and tropical cyclogenesis, further studies are required to resolve lingering uncertainties in both operational TC genesis forecasting and long‐term climate projections.

6. Relationship Between TEWs and Regional Precipitation

TEWs are an important source of synoptic‐scale precipitation variability across the tropical belt [97]. Globally, they can account locally for up to 20%–30% of annual mean precipitation in regions of frequent wave activity, although their contribution is much smaller across large parts of the tropics [97]. In the tropical NATL, they modulate seasonal rainfall and help organize regional convective activity [6, 97]. However, their basin‐wide annual rainfall contribution is more modest, ranging from about 1% to 7%, with regional maxima aligned with the main wave corridor and peak activity during boreal summer [6]. At regional and seasonal scales, however, their influence can be much stronger, particularly over parts of the tropical Americas during the May–November rainy season [22]. Similar regional and seasonal relationships have also been documented for the WAM, the North American monsoon, and the Intra‐Americas Seas summer rainy season [63, 156, 157].

Although TEWs occur across several tropical basins, the African‐origin branch has received the greatest attention because of its well‐established links to WAM rainfall and Atlantic tropical cyclogenesis [26, 37]. Their influence on precipitation arises from a combination of dynamical and thermodynamic processes, including the organization of deep convection, the enhancement of low‐level moisture convergence, and the triggering and maintenance of MCSs [22, 124, 158]. In this sense, TEWs are not simply transient rain‐bearing disturbances, but synoptic‐scale organizers of convective environments whose rainfall effects depend on how wave dynamics interact with environmental moisture and regional boundary conditions.

Over WA and the eastern tropical Atlantic, the relationship between African‐origin TEWs and precipitation is well established, but dynamically heterogeneous. The wave circulation promotes lower‐tropospheric moisture convergence and ascent, creating favorable conditions for the development and organization of deep convection [44, 159]. In turn, latent heating associated with organized convection can reinforce the vorticity and PV structure of the wave, thereby contributing to its maintenance or amplification [44, 45]. These waves are closely associated with rainfall over WA, yet the location of the peak precipitation relative to the wave depends on the phase relationship between circulation, moisture transport, and convection [160]. This behavior is linked to the two well‐known wave regimes associated with the AEJ, which differ in timescale, latitude, and convective coupling [19, 20]. Janiga and Thorncroft [159] further showed that African‐origin TEWs strongly modulate convection over tropical Africa and the eastern Atlantic, thereby helping to organize rainfall on synoptic timescales. At daily timescales, these waves also favor intense rainfall events over WA, especially within the 3–5‐day band, which appears more tightly linked to rainfall variability than longer‐period disturbances [161].

This close wave–rainfall linkage is also evident in modeling studies. Skinner and Diffenbaugh [156] showed that African‐origin TEWs account for an important fraction of the WAM precipitation, implying that biases in wave representation can translate directly into rainfall biases. Consistent with this, later modeling studies have shown that changes or biases in the wave activity are closely linked to variations in the position, intensity, and variability of West African monsoon rainfall [30, 70]. These links arise partly through the wave–convection coupling described above: when models misrepresent African‐origin TEW structure or the moisture budget of propagating disturbances, the resulting errors in convective organization cascade into systematic rainfall biases [53, 70].

Farther downstream, over the tropical Americas, TEWs remain an important regional contributor to seasonal rainfall, particularly over northern South America, the Caribbean, and Central America [22, 23, 63, 162]. TEWs can account for up to 50% of seasonal rainfall over northern South America, with contributions of 30%–50% across parts of northern South America and similarly large values over Central America and adjacent regions [22]. Over northern South America and the Caribbean, however, the TEWs–precipitation relationship becomes more heterogeneous because it is strongly modulated by air–sea coupling, topography, low‐level jets, and the large‐scale intraseasonal background [23, 34, 163, 164]. Indeed, nearly half of the TEWs affecting the region during boreal summer are associated with suppressed precipitation and clearer skies rather than with convective enhancement [23]. The comparison between convective and dry waves revealed contrasting patterns of lower‐ and upper‐tropospheric divergence and vertical motion. The results further suggest that the MJO modulates the effects of TEWs on regional convection and precipitation and may also influence their subsequent westward propagation. Consequently, TEW passage over the western tropical Atlantic may be accompanied by either enhanced or suppressed precipitation, depending partly on the prevailing intraseasonal conditions.

Over the Intra‐Americas Seas, the wave‐related rainfall is strongly modulated by topography, moisture availability, mesoscale convective organization, and regional air–sea interaction [165]. As TEWs propagate across the Caribbean, enhanced vertically integrated moisture flux convergence and precipitable water frequently lead to intense precipitation events, although stronger‐than‐normal CLLJ conditions tend to suppress easterly wave activity through reduced precipitable water, cooler Caribbean SSTs, and stronger vertical wind shear, leading to below‐normal summer rainfall over much of the Intra‐Americas Seas and southern Mexico [63]. This interpretation is physically consistent with broader climatological analyses of the CLLJ, which show that its summer intensification is linked to increased moisture flux divergence and reduced Caribbean precipitation [63, 163]. In addition, TEW‐related precipitation over the NATL basin depends on the moisture sustained by distinct moisture‐source regimes, with a progressive westward shift in moisture uptake as the waves propagate from the eastern Atlantic toward the Caribbean [6]. When TEWs reach land, induced moisture convergence can interact constructively with mountain ranges, coastal circulations, and the diurnal cycle, particularly over Central America and the Caribbean islands, where convection is highly sensitive to terrain and low‐level flow.

The influence of TEWs on rainfall over northern South America is particularly complex, as it interacts with major regional moisture‐transport systems (e.g., CLLJ) and the latitudinal position of the ITCZ. The seasonal migration of the ITCZ modulates where and when TEWs trigger deep convection over the region, with waves propagating beneath or near the ITCZ benefiting from enhanced low‐level moisture and reduced convective inhibition [166]. More broadly, this suggests that TEW‐related precipitation does not arise from a fixed moisture reservoir, but evolves along the wave life cycle as the disturbances interact with changing thermodynamic environments across the basin. In this context, approximately 86% of TEWs passing over northern South America enhance convective activity, favoring precipitation from 4 days before the waves reach northern South American territory [167]. These studies illustrate that TEWs are among the main synoptic systems supporting regional precipitation across the tropical Atlantic and adjacent continental regions. Therefore, TEWs are best understood as multiscale hydroclimatic organizers, with rainfall impacts emerging from the interaction of wave dynamics, convective coupling, environmental moisture, and regional boundary conditions.

7. Future Projections of TEW Activity Under Global Warming

Future projections of TEW activity remain characterized by significant intermodel inconsistencies. Since the early assessment of African‐origin TEW responses to greenhouse forcing by Skinner and Diffenbaugh [168], subsequent studies have reported contrasting changes in wave frequency, intensity, and track, reflecting differences in model physics, spatial resolution, tracking methods (Table S1), and climate scenarios [32, 145]. Projections using the Coupled Model Intercomparison Project Phase 5 (CMIP5) indicate a reduction in African‐origin wave activity during late spring and early summer, followed by a marked intensification between July and October [70], a pattern physically consistent with projected precipitation changes in the Sahel region [169]. More recent CMIP6 simulations indicate a robust increase in wave activity over the Sahel–Sahara region by the end of the 21st century [32]. However, the spatial response differs between the two primary wave tracks. The drier African‐origin northern‐track corridor is projected to experience an increase in wave frequency, particularly regarding the most intense systems, due to enhanced baroclinicity [29, 30, 89, 168]. Conversely, projections for the southern track lack robust consensus; simulations offer ambiguous results concerning future changes in frequency and magnitude [70, 168]. In particular, a decrease in southern track frequency has been attributed to weakened temperature gradients and increased static stability associated with weak temperature gradient balance [29]. Disparities in wave propagation toward the Atlantic have also been linked to the inadequate representation of the Guinea Highlands in low‐resolution models [70]. The importance of accurately representing this region is supported by the earlier process‐based analysis of Berry and Thorncroft [16], who showed that convectively generated PV anomalies over the Guinea Highlands interacted and merged with mid‐tropospheric PV structures embedded within an approaching African‐origin TEW, contributing to the development of a strong vortex near the WA coast. Furthermore, studies using regional climate models have reported a region‐wide reduction in wave activity due to decreased barotropic and baroclinic instability [30, 170]. In contrast, Bercos‐Hickey and Patricola [31] found an increase in wave frequency and intensity, while Córdova‐García et al. [171], using downscaled CMIP6 simulations [172], projected a statistically nonsignificant decrease in annual frequency but a robust increase in TEW intensity during July–September. Domínguez et al. [173] projected slight positive changes in TEW track density south of 10°N over the Atlantic Ocean.

In addition, multimodel ensembles from the High‐Resolution Model Intercomparison Project (HighResMIP) [174] corroborate intensification through substantial increases in eddy kinetic energy (EKE), a metric of wave strength [145]. These ensembles suggest that TEWs will intensify even when the southern African‐origin TEW track shows little change, indicating that wave intensification does not necessarily require a geographical migration of established wave corridors. Complementing these broad‐scale projections, new evidence from convection‐permitting simulations [175, 176] provides a higher‐resolution perspective, consistently showing an intensification of the meridional temperature gradient associated with stronger African‐origin TEWs. This finding aligns with several earlier studies (e.g., see Refs. [29, 31, 89]) and highlights that physical mechanisms for wave intensification are robust across scales. However, discrepancies between future coupled and uncoupled simulations were further elucidated by Bercos‐Hickey et al. [145], who noted a reduction in EKE within the northern track under coupled configurations. These variations are primarily attributed to distinct precipitation patterns. Specifically, coupled models exhibit enhanced rainfall near the African coast between 5°N and 15°N, but a corresponding deficit in the 15°–25°N latitudinal band compared to uncoupled simulations. Because wave intensity is intrinsically linked to convective activity [128], the projected decrease in precipitation likely suppresses EKE in the northern track. Furthermore, inherent differences in large‐scale circulation between simulations likely alter the structure of the AEJ, subsequently modifying energy exchanges between the mean flow and transient waves. Observational trends indicate an increase in African‐origin TEW strength as well as a poleward shift of the African‐origin TEWs [87, 91, 177], lending observational support to the projected intensification signal.

Interestingly, high‐resolution simulations suggest that TEW tracks do not necessarily shift in tandem with the strengthening or northward displacement of the AEJ [175, 176]. This spatial distribution implies complex dynamical forcing where intensified moisture−convection coupling fuels more precipitating events within future disturbances, despite the lack of significant migration of wave tracks. Downstream of these dynamical shifts, waves are projected to become wetter, with significantly higher column‐integrated water vapor, attributed to an intensified WAM and stronger waves [176]. It should be noted that these authors used a wave tracker biased toward southern‐track African‐origin waves. Nonetheless, consistent with these previous findings, Córdova‐García et al. [171] projected a significant increase in moisture uptake and precipitation for wet waves across the tropical Atlantic, including the WA coast and the Caribbean region (Figure 4), reaching scaling rates of ∼8.5%/°C and ∼4.0%/°C, respectively, by the end of the century under the SSP5‐8.5 scenario. In contrast, Domínguez et al. [173], using a regional climate model, found that TEW‐driven precipitation could decline by about 60% over the Caribbean, Gulf of Mexico, and central‐southern regions of Mexico. Over the Sahelian region, the intensification of TEWs suggests a heightened risk of extreme weather. Given the established linkage between TEWs and the MCSs [54, 124, 178] that modulate regional rainfall, their increased strength or frequency implies a greater potential for extreme flooding events.

FIGURE 4.

Projected changes in the annual 6‐h area‐averaged (A) moisture uptake and (B) Lagrangian precipitation for wet tropical easterly waves relative to the historical period (HIST) under future scenarios (SSP2‐4.5 and SSP5‐8.5 at MID‐ [2041−2070] and END‐of‐century [2071−2100]). (C) Cluster 1 (C1) spans from Africa to approximately 40°W, centered near the Cape Verde islands; Cluster 2 (C2) comprises the area from 40°W to the Lesser Antilles Arc, centered near 17°N and 50°W; Cluster 3 (C3) extends from the Lesser Antilles Arc toward the Caribbean Sea and Gulf of Mexico, centered north of La Hispaniola. For all panels, the central line within each box represents the median, box edges indicate the interquartile range (IQR), and whiskers extend to 1.5 times the IQR. Percentage values shown above each future scenario box represent the percentage change in the median relative to the corresponding historical median. Changes shown in red indicate a statistically significant difference from the historical period based on a Mann−Whitney U test (p < 0.05). The analysis was performed by applying a Lagrangian moisture tracking approach [179] to a downscaled bias‐corrected CMIP6 dataset [172]. Adapted from Córdova‐García et al. [171].

Furthermore, observational evidence indicates that the increasing trend in Atlantic TC frequency since 1980 has been driven primarily by TCs with TEW origins, whereas non‐TEW TCs show no significant trend [91, 180]. However, future changes in TEW frequency are not necessarily a good indicator of future TC activity [145]. Regional modeling studies in which TEWs were suppressed through lateral boundary conditions found no reduction in seasonal Atlantic TC numbers [109, 151]. In contrast, several experiments report an increase in TC frequency and intensity when African‐origin TEWs are filtered, particularly when the southern track or the 2–6‐day periodicity band is suppressed [145, 151, 181]. This counterintuitive response arises because wave suppression enhances the large‐scale environment favorable for TC genesis [145, 151, 181]. Despite this decoupling between TEW counts and TC genesis, projected changes in TEW activity are expected to significantly reshape the broader climatic landscape of WA and the tropical Atlantic [32]. The spatial overlap between the projected intensification of African‐origin northern‐track waves and the prolific dust sources of the western Sahara suggests a likely increase in the trans‐Atlantic transport of Saharan mineral aerosols [182]. This dynamic has critical implications for tropical cyclogenesis; stronger northern‐track African‐origin TEWs facilitate the transport of dry, dusty air, which can inhibit or delay the development of TCs until the waves migrate to more favorable conditions farther west in the Atlantic basin [183]. However, it should be noted that northern‐track TEWs are more strongly affected by changes in dust [184]. On this basis, the net effect on future Atlantic TC activity remains uncertain.

In summary, while model projections exhibit disparities regarding the future frequency of TEWs, there is a growing consensus that enhanced moisture−convection coupling will drive more intense and wetter disturbances. Understanding uncertainties in future projections is crucial, as the thermodynamic and dynamical evolution of TEWs will fundamentally reshape hydrological and storm‐related climate risks across WA and the broader tropical Atlantic basin, including the Caribbean region, under continued global warming.

8. Final Remarks and Research Roadmap

A compounding challenge in TEW research is the persistent scarcity of in situ observations across the African continent and the tropical Atlantic. This lack of observations introduces significant uncertainty regarding whether reanalysis and model outputs accurately represent the true physical evolution of wave events. Beyond data reliability, the automated detection of TEWs within standard meteorological fields presents distinct algorithmic hurdles. While there is an overall agreement in seasonal cycles and spatial distribution [5, 6, 33], objective tracking frameworks frequently fail to capture weaker systems and are susceptible to artificially double‐counting a single wave if it undergoes cycles of decay and subsequent reintensification. In this context, standardizing tracking algorithms is essential for reducing the uncertainty in TEW climatologies and climate model projections. In particular, we stress the need for a coordinated, community‐driven intercomparison initiative analogous to those successfully implemented for other complex atmospheric phenomena. Collaborative frameworks, such as the Intercomparison of Mid Latitude Storm Diagnostics (IMILAST) for extratropical cyclones [92], the Atmospheric River Tracking Method Intercomparison Project (ARTMIP) [185], the Identification of Sources of Precipitation through an International Research Effort (INSPIRE) [186], Water Isotope Model Intercomparison Project (WisoMIP) [187], and similar systematic evaluations for Mediterranean cyclones [188], have proven highly effective in establishing robust community benchmarks. An equivalent intercomparison project for TEWs, wherein diverse objective tracking schemes are rigorously evaluated against a common set of reanalysis fields and observational protocols, would be transformative. Such an initiative would systematically quantify algorithmic spread, allowing researchers to confidently disentangle true physical wave variability from methodological artifacts. Moreover, a multialgorithm evaluation would clarify which tracking techniques are optimally suited for specific research objectives, such as isolating cyclogenesis precursors versus mapping rainfall modulation. Ultimately, building this methodological consensus is paramount to creating a unified baseline, which is urgently needed to robustly validate global climate models and assess future changes in TEW activity.

In this context, significant uncertainty remains regarding the future behavior of TEWs. This ambiguity arises not only from inconsistencies in tracking methodologies and spatial resolution but also from the inherent limitations of global climate models and regional models employing convective parameterizations, which often fail to resolve the complex moisture−convective feedbacks and multiscale atmospheric processes critical to the West African weather‐climate system [44, 53, 125, 189]. Given the critical role of these unresolved small‐scale thermodynamic processes in driving wave track and intensification, the adoption of convection‐permitting simulations is increasingly essential. Nonetheless, representing multiscale feedback loops in these models remains a substantial challenge. Even within convection‐permitting simulations, the representation of the Saharan Air Layer and associated dust−radiation feedbacks is frequently simplified, leaving the competitive balance between aerosol‐loading and thermodynamic moistening poorly constrained [190−192]. Furthermore, the accuracy of convection‐permitting simulations remains sensitive to the representation of land‐surface processes and the quality of lateral boundary forcing [193, 194]. Finally, while pseudo‐global warming approaches are computationally efficient, they inherently assume a stationary background state, thereby failing to capture potential nonlinear shifts in large‐scale climate modes (e.g., ENSO) that fundamentally alter the environments through which TEWs propagate [195]. Addressing these multiscale modeling limitations is critical to reconciling current uncertainties and improving the reliability of future climate projections for TEW activity.

Building upon these systematic intercomparisons and modeling projections, the integration of AI‐driven architectures represents a critical frontier in the TEW research roadmap [98, 196]. While traditional objective trackers often struggle with the structural complexity of waves interacting with the ITCZ or the monsoon trough, deep learning frameworks can synthesize high‐dimensional datasets to identify waves through multivariate pattern recognition rather than isolated variable thresholds. By simultaneously accounting for kinematic signatures and diabatic heating patterns, these models may offer a more nuanced lens into the wave lifecycle. Furthermore, AI provides the computational efficiency required to automate the detection of multiscale interactions that remain elusive to conventional diagnostics. Incorporating these machine learning techniques is, therefore, not merely a technical enhancement, but an essential step toward a more objective, physics‐informed understanding of wave behavior that can help in reconciling existing modeling disparities.

Finally, the lack of in situ observations remains a significant challenge in TEW analysis and model validation. Observational campaigns such as GATE, AMMA, and NAMMA have been pivotal in advancing understanding of African‐origin TEW structure, convective coupling, African MCSs, and the WAM [3, 12, 13, 14, 18, 197]. However, they were limited in both duration and spatial coverage. On this basis, future research efforts should focus on the execution of intensive field campaigns across continental Africa and the tropical Atlantic, including the Caribbean region. These observations are critical for providing the high‐fidelity ground truth required to validate multiscale convective feedbacks in climate and regional models, including convection‐permitting models, and to train and validate AI‐driven algorithms. Together, this multipronged approach (Figure 5), integrating standardization, advanced modeling, AI diagnostics, and observations, will be paramount to deepening our understanding of TEW activity and reducing uncertainty in future projections.

FIGURE 5.

Proposed research roadmap for future tropical easterly wave (TEW) studies, integrating standardized tracking algorithms, advanced simulations, and artificial intelligence (AI) with ground‐truth observations to deepen the understanding of TEW activity.

Author Contributions

Orlando L. Córdova‐García: Writing – review and editing, Writing – original draft, visualization, investigation, conceptualization. Ricardo M. Trigo: Writing – review and editing, investigation, conceptualization. Raquel Nieto: Writing – review and editing, investigation, conceptualization. Luis Gimeno: Writing – review and editing, investigation, conceptualization. Rogert Sorí: Writing – review and editing, supervision, methodology, conceptualization. Milica Stojanovic: Writing – review and editing, visualization, supervision, investigation, conceptualization. Albenis Pérez‐Alarcón: Writing – review and editing, visualization, supervision, investigation, conceptualization.

Conflicts of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Supporting information

Table S1: nyas70415‐sup‐0001‐TableS1.pdf