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    (a),(b) Illustration of the AEW phase bins. Amplitudes below 1.5σ are excluded from the composites. In (a) phase numbers follow the same convention as in Reed et al. (1977). In (b) only four phases are shown; this phase space is used for some analyses involving TRMM PR data.

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    Standard deviation of TD-filtered 700-hPa relative vorticity with TCs removed (×10−5 s−1) during JAS 1998–2012. Black boxes show the four regional domains: east Atlantic (ATL), central West Africa (CWA), south West Africa (SWA), and East Africa (EAF).

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    (a) Unfiltered TRMM 3B42 rain rate (mm h−1, shaded), (b) unfiltered ERA-Interim 700-hPa relative vorticity (×10−5 s−1, shaded), (c) AEW phase (shaded) with amplitudes less than 1σ excluded, and (d) AEW amplitude (σ, shaded). AEW amplitude in (c) and (d) is defined as the distance from the origin in Fig. 1. In each panel, AEW-filtered relative vorticity is superimposed (contoured every 1σ); TCs have been removed from this field and all fields in the bottom two panels. All fields are averaged from 5° to 15°N. A TC symbol marks the genesis of Hurricane Helene.

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    Phase–latitude composites of total relative vorticity (×10−5 s−1, shaded) and wind (m s−1, vectors) at (a),(c),(e) 700 and (b),(d),(f) 925 hPa for (a),(b) East Africa (10°–30°E); (c),(d) West Africa (10°W–10°E); and (e),(f) the east Atlantic (40°–20°W).

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    (a),(c),(e) AEW phase with the greatest unconditional rain rate based on a single harmonic fit of the (a) TRMM 3B42, (c) TRMM PR, and (e) ERA-Interim forecast rain rate. (b),(d),(f) Harmonic amplitude (mm h−1) of the (b) TRMM 3B42, (d) TRMM PR, and (f) ERA-Interim forecast rain rate. The PR data were rebinned to 5.0° × 5.0° prior to computing the phase and amplitude. Regions where the first harmonic explains <50% of the variance are shaded gray.

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    Phase–latitude composites of unconditional rain rate anomalies (relative to JAS 1998–2012) from the (a),(d),(g) TRMM 3B42; (b),(e),(h) TRMM PR; and (c),(f),(i) ERA-Interim forecast rain rate (mm h−1, shaded) for (a)–(c) East Africa (10°–30°E); (d)–(f) West Africa (10°W–10°E); and (g)–(i) the east Atlantic (20°–40°W).

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    Unconditional rain rate (% difference from climatology) for each AEW phase: northerlies (N), trough (T), southerlies (S), ridge (R), and no AEW (NO). Rain types shown are total (T), stratiform (S), shallow convective (SC), and deep convective (DC). Climatological rain rates for each rain type are shown in the key. Error bars show the 95% uncertainty due to sampling error from the bootstrap analysis. Shallow convective rain is very rare in the EAF and CWA domains and is excluded.

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    As in Fig. 7, but for the fractional rain contribution (%) from stratiform (S), deep convective (DC), and shallow convective (SC) rain. Stratiform and deep convective rain fractions are indicated by the left y axis and shallow convective rain fractions are indicated by the right y axis.

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    As in Fig. 7, but for the fractional rain coverage (% difference from climatology).

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    As in Fig. 7, but for conditional rain rates (% difference from climatology).

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    FADs showing the climatological frequency of echoes (contoured every 0.5%) and deviations from climatology for each AEW phase (%, shaded) for (a)–(d) deep convection (DC) and (e)–(h) stratiform (S) in the ATL domain. For reference the top right of each panel shows the conditional rain rate in each AEW phase (mm h−1) and the deviation from climatology (%) (also in Fig. 10).

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    As in Fig. 11, but for the CWA domain.

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    The PF attribute value at which 50% of the rainfall comes from PF attribute values larger and smaller than those displayed for all times or climatology (C), northerlies (N), trough (T), southerlies (S), ridge (R), and no AEW (NO). The PF attributes shown are the (a) effective diameter (km), (b) volumetric rain rate (×104 km2 mm h−1), (c) 18-dBZ maximum echo-top height (km), (d) 40-dBZ maximum echo-top height, (e) 85-GHz minimum brightness temperature (BT), and (f) 37-GHz minimum BT. The four domains are indicated by black (EAF), red (CWA), green (SWA), and blue (ATL) lines.

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    (a)–(d) Difference from climatology (%) for the rain rate from each PF size class within each AEW phase and domain. (e)–(h) Fractional contribution (%) of the rainfall from each size class within each AEW phase. The PF sizes are small (S) (effective diameter D ≤ 74 km), medium (M) (D = 75–181 km), and large (L) (D ≥ 182 km). Climatological values are shown in the key of each panel.

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    As in Fig. 14, but for the 40-dBZ maximum echo-top categories: low top (L) (no 40-dBZ echoes and tops ≤ 5 km), medium top (M) (tops 5.25–6.5 km), and high top (H) (tops ≥ 6.75 km).

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    Phase–latitude composites of anomalies of (a)–(c) Q vectors (×10−13 m Pa−1 s−3, vectors), Q-vector convergence (×10−18 Pa−1 s−3, shaded), and pressure vertical velocity (contoured every 1 hPa h−1) at 850 hPa; (d)–(f) column relative humidity (CRH) (%, shaded); and (g)–(i) 925–600-hPa shear magnitude (contoured every 1 m s−1) and vectors and CAPE (J kg−1, shaded) for (a),(d),(g) the east Atlantic (20°–40°W); (b),(e),(h) West Africa (10°W–10°E); and (c),(f),(i) East Africa (10°–30°E). In (a)–(c) the total vertical velocity not the vertical velocity predicted by the Q-vector equation is shown.

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    Schematic of the AEW–convection relationship over (a) central West Africa (CWA) and (b) the east Atlantic (ATL). This schematic presents an exaggerated view of the amount and type of convection in each phase. Green (brown) circles indicate positive (negative) moisture anomalies. Red (blue) circles indicate regions of warm (cool) low-level temperatures and increased (reduced) CAPE. Arrows indicate the adiabatic forcing for ascent or descent.

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The Influence of African Easterly Waves on Convection over Tropical Africa and the East Atlantic

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  • 1 Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida
  • | 2 University at Albany, State University of New York, Albany, New York
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Abstract

Using data from the Tropical Rainfall Measuring Mission (TRMM), the modulation of convection by African easterly waves (AEWs) is investigated over regions of the east Atlantic and tropical Africa. To explain the modulation of convection, the large-scale environment (lift, moisture, conditional instability, and shear) is also examined as a function of AEW phase in each region.

Over semiarid portions of tropical Africa, unconditional rain rates are greatest in the northerly phase of AEWs due to the strong adiabatic forcing for ascent. Along the Guinea Coast, the western coast of Africa, and over the east Atlantic—where forcing for ascent is weaker—rainfall is shifted toward the trough where the air is moist. Significant contrasts in the characteristics of convection as a function of AEW phase—comparable in magnitude to regional contrasts—are also observed. In all regions, large and high echo-top convective systems are more sensitive to AEW phase than small and low echo-top systems. In semiarid regions, deep convection and large high echo-top convective systems account for a large fraction of the rainfall in the ridge and northerlies. Stratiform and small low echo-top convective systems dominate in the trough and southerlies. Convective system height and conditional rain rates increase with conditional instability and system sizes may increase with shear. Over the east Atlantic, stratiform fractions and convective system sizes and echo-top heights are greatest in the trough while the ridge is dominated by shallow convection. This is primarily related to the presence of moist air in the trough and dry air in the ridge.

Current affilation: Marine Meteorology Division, Naval Research Laboratory, Monterey, California, and University Corporation for Atmospheric Research, Boulder, Colorado.

Corresponding author address: Matthew A. Janiga, Naval Research Laboratory, 7 Grace Hopper Ave., Monterey, CA 93943. E-mail: matthew.janiga.ctr@nrlmry.navy.mil

Abstract

Using data from the Tropical Rainfall Measuring Mission (TRMM), the modulation of convection by African easterly waves (AEWs) is investigated over regions of the east Atlantic and tropical Africa. To explain the modulation of convection, the large-scale environment (lift, moisture, conditional instability, and shear) is also examined as a function of AEW phase in each region.

Over semiarid portions of tropical Africa, unconditional rain rates are greatest in the northerly phase of AEWs due to the strong adiabatic forcing for ascent. Along the Guinea Coast, the western coast of Africa, and over the east Atlantic—where forcing for ascent is weaker—rainfall is shifted toward the trough where the air is moist. Significant contrasts in the characteristics of convection as a function of AEW phase—comparable in magnitude to regional contrasts—are also observed. In all regions, large and high echo-top convective systems are more sensitive to AEW phase than small and low echo-top systems. In semiarid regions, deep convection and large high echo-top convective systems account for a large fraction of the rainfall in the ridge and northerlies. Stratiform and small low echo-top convective systems dominate in the trough and southerlies. Convective system height and conditional rain rates increase with conditional instability and system sizes may increase with shear. Over the east Atlantic, stratiform fractions and convective system sizes and echo-top heights are greatest in the trough while the ridge is dominated by shallow convection. This is primarily related to the presence of moist air in the trough and dry air in the ridge.

Current affilation: Marine Meteorology Division, Naval Research Laboratory, Monterey, California, and University Corporation for Atmospheric Research, Boulder, Colorado.

Corresponding author address: Matthew A. Janiga, Naval Research Laboratory, 7 Grace Hopper Ave., Monterey, CA 93943. E-mail: matthew.janiga.ctr@nrlmry.navy.mil

1. Introduction

African easterly waves (AEWs) are westward-propagating synoptic-scale disturbances that develop over Africa during the West African monsoon and modulate convection. They are also precursors to the development of most tropical cyclones in the Atlantic and have received considerable attention in this regard (e.g., Avila and Pasch 1992; Thorncroft and Hodges 2001; Hopsch et al. 2007, 2010). The observed spatiotemporal relationship between AEWs and rainfall or cloud coverage is well documented (e.g., Carlson 1969a,b; Reed et al. 1977; Fink and Reiner 2003; Berry and Thorncroft 2005; Kiladis et al. 2006). However, simulating this relationship in numerical models remains a challenge (e.g., Ruti and Dell’Aquila 2010; Beucher et al. 2014; Janiga and Thorncroft 2013; Skinner and Diffenbaugh 2013; Crétat et al. 2015). Moreover, relatively little is known about the relationship between AEWs and the properties of convection (e.g., cloud type, rain intensity, and convective system size and vertical development), although this is now receiving attention (Nicholls and Mohr 2010; Guy and Rutledge 2012; Guy et al. 2011). Accurately simulating both the amount and properties of convection as a function of AEW phase is critical since latent heating is so important to their growth and properties (e.g., Hall et al. 2006; Hsieh and Cook 2008; Thorncroft et al. 2008; Berry and Thorncroft 2012).

Janiga and Thorncroft (2014, hereafter JT14) used observations from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) (Kummerow et al. 1998) to examine contrasts in the properties of convection between the east Atlantic and coastal, continental humid, and continental semiarid regions of tropical Africa. In this study, we examine the properties of convection as a function of AEW phase in these same regions to determine how AEWs modulate both the amount and properties of convection. This is then related to differences in the large-scale environment as a function of wave phase.

The semiarid regions of West Africa are acutely dependent on the rainfall from intense mesoscale convective systems (e.g., Mathon et al. 2002; JT14), which propagate westward at speeds of 12–20 m s−1 (Laing et al. 2008), and are often referred to as squall lines. In this region, convective systems typically form ahead of the AEW trough and can propagate into the ridge before dissipating (Payne and McGarry 1977; Fink and Reiner 2003). However, most of the rainfall occurs in the northerly phase of the waves (e.g., Duvel 1990; Gu et al. 2004; Kiladis et al. 2006). Over the east Atlantic, convection is characterized by lower echo tops and higher stratiform fractions (e.g., Schumacher and Houze 2006; Liu et al. 2007; JT14) and rainfall is greatest within the trough (e.g., Thompson et al. 1979; Kiladis et al. 2006).

Over West Africa, the dry adiabatic forcing for ascent associated with AEWs produces low-level ascent ahead of the trough and descent behind it (Thorncroft and Hoskins 1994; Kiladis et al. 2006). This forcing for ascent arises from the interaction of the AEW vortex with the shear of the African easterly jet (AEJ) and the low-level baroclinicity and may explain the preference for rainfall in this phase. The troughs of AEWs also tend to be more moist then the ridge (Kiladis et al. 2006). Numerous studies (e.g., Bretherton et al. 2004; JT14) have found a strong relationship between column relative humidity (CRH) and rainfall. Increased CRH reduces entrainment aiding the development of deep convective clouds (Holloway and Neelin 2009) and reduces low-level evaporation (JT14). The shift of rainfall from the northerlies over land to the trough over the ocean may be due to the effects of moisture dominating over the ocean in the absence of strong forcing for ascent.

JT14 found that conditional instability did not have a strong influence on the total rainfall but did influence convective system intensity and therefore may influence the properties of convection as a function of AEW phase. In addition, Barnes and Sieckman (1984) examined the environment of slow- and fast-moving MCSs over the Sahel. They found that the fast- (slow) moving systems tended to occur in an environment with higher (lower) shear and were more often found in the northerly (southerly) phase of the waves. This is consistent with JT14 who found significant relationships between shear and rainfall intensity as well as convective system size and echo-top height over the southern Sahel. Over the northern Sahel, convection is very limited by moisture (JT14) and, therefore, coincides with the surges of southerly flow and moist monsoon air produced by the northern low-level vortex of AEWs in this region (Cuesta et al. 2010).

The aim of this study is to determine how differences in the amount and properties of convection as a function of AEW phase in several regions—primarily diagnosed using the TRMM PR—can be explained by differences in the large-scale environment (lift, moisture, conditional instability, and shear). Section 2 describes the data sources and methodology, including the procedure for identifying AEW phase and amplitude. Section 3 presents composites of the properties of convection (rain type, rain intensity, and convective system size and vertical development) as a function of AEW phase for four regions that are influenced by AEWs and have distinct large-scale environments and convective properties. The variability of large-scale thermodynamic and dynamic fields as a function of AEW phase and geography is also examined and used to explain the contrasts in convective properties. Section 4 summarizes the results and offers some conclusions.

2. Data and methodology

As in the companion paper JT14, this study uses data from TRMM and the ERA-Interim reanalysis from the period June–September (JAS) 1998–2012. TRMM PR–based precipitation features (PFs), defined as contiguous areas of near-surface rain rate, with attributes related to system size and intensity follow JT14 and references therein. A bootstrap analysis used to identify the sampling uncertainty in TRMM statistics also follows JT14. A summary of the datasets and methodologies described in JT14 is reproduced here for convenience.

a. Data

1) TRMM products and precipitation features

As in JT14, the properties of convection are primarily assessed using the TRMM PR (Kummerow et al. 1998). TRMM data are from the version 7 release (TRMM Precipitation Radar Team 2011). The PR is a KU band (2.17 cm) radar that can reliably detect echoes of 18 dBZ, which is equivalent to a rain rate of ~0.5 mm h−1. In August 2001 the satellite was boosted to a higher orbit to conserve fuel, which slightly reduced the sensitivity of the PR (Shimizu et al. 2009). The PR has a swath width of 245 km (215 km preboost) and a resolution of 5 km (4.3 km preboost). The PR samples the same location approximately once every 3 days and uniformly samples the diurnal cycle. Reflectivity profiles have a vertical resolution of 250 m and are available from just above the surface to 19.75 km.

TRMM PR rain types and PF attribute categories describing system size and intensity follow JT14 (see their Tables 1 and 2). The PF boundaries are determined by contiguous areas of PR near-surface rain rate. Three PF size and maximum 40-dBZ echo-top categories are defined following JT14 such that each category accounts for one-third of the rainfall over the east Atlantic and tropical Africa. Further details on these PF categories and their climatological properties during the monsoon season are provided in section 4 of JT14.

The TRMM 3B42 precipitation rate (Huffman et al. 2007) is primarily based on microwave and infrared (IR) measurements with PR and rain gauge data used for calibration. This product is available every 3 h at 0.25° × 0.25°. To facilitate comparisons with the PR, the 3B42 precipitation rate was degraded to 1.0° × 1.0°, which is the resolution the PR was binned to as well.

2) Reanalysis data sources

The European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim reanalysis (Dee et al. 2011) is used to characterize the large-scale environment of the AEWs. This reanalysis has a horizontal grid spacing of approximately 0.7° × 0.7° and 27 vertical levels spanning 1000 to 100 hPa. It is important to note that reanalyses can have substantial biases over tropical Africa and the east Atlantic due to the lack of observations and influence of convective parameterization. This results in substantial differences in the structure of AEWs between different reanalyses (Janiga and Thorncroft 2013). Nevertheless, previous studies suggest that reanalyses are adequate for drawing qualitative conclusions regarding the relationship between convective systems and their environment in this region. For example, Nicholls and Mohr (2010) examined the environments of convective systems of different intensities in the region using ECMWF analyses and radiosondes and found that both datasets yielded similar conclusions.

b. Methodology

1) AEW phase identification

The approach used to determine AEW phase and amplitude is similar to that used by Riley et al. (2011) to determine the phase and amplitude of the Madden–Julian oscillation and by Yasunaga and Mapes (2012) to determine the phase and amplitude of a variety of equatorial waves. For consistency with previous studies (e.g., Reed et al. 1977) this study uses a dynamical field, 700-hPa relative vorticity anomalies, to determine the phase and amplitude of AEWs. Here, anomalies are defined with respect to the first four harmonics of the annual cycle. However, an earlier version of this work used TRMM 3B42 rain-rate anomalies to identify wave phase and amplitude and yielded equivalent composites of wave structure and convective properties, lending confidence to the robustness of the results.

Because tropical cyclones (TCs) move westward at speeds similar to AEWs, they project onto the same portions of the wavenumber–frequency spectrum. To clarify the composites over the east Atlantic, TCs are excluded from the AEW composites following Aiyyer et al. (2012). The relative vorticity anomalies associated with TCs were relaxed to zero by multiplying the anomalies by a Gaussian weighting function. The Gaussian weighting function w is
e1
Here, R = 750 km is used to specify the length scale of the weighting function and r(x, y) is the distance between each grid point and the TCs. The TC positions are taken from the International Best Track Archive for Climate Stewardship (IBTrACS) dataset (version 3, release 5) (Knapp et al. 2010).

To isolate the signals associated with AEWs, relative vorticity anomalies with TCs removed were filtered for westward-propagating synoptic spatiotemporal-scale signals. First, the linear temporal trend was removed and 75 days on each end were tapered to zero using a split-cosine-bell taper. Next, the circum-global data were decomposed using a two-dimensional Fourier transform and periods of 2–10 days and wavenumbers from −25 to −4 (1600–10 000 km) were retained.

Figure 1 shows two phase spaces defined using AEW-filtered relative vorticity (x axis) and its time derivative (y axis). The AEW-filtered relative vorticity is used to identify troughs and ridges and the time derivative of the AEW-filtered relative vorticity is used to identify northerlies and southerlies. The phase spaces use normalized AEW-filtered relative vorticity and its normalized time derivative to determine phase and amplitude. The normalization is applied at each grid point by dividing both fields by their standard deviation during JAS 1998–2012. AEW amplitude is defined based on the distance from the origin of the phase space (Fig. 1). When compositing data for each AEW phase, times and locations with an AEW amplitude less than 1.5 are excluded. For reanalysis data and total rain rates, eight phases were used (Fig. 1a). For TRMM PR rain type and PF statistics, four phases were used to increase the statistical robustness of the results (Fig. 1b). When compositing reanalysis data as a function of AEW phase, reanalysis fields were binned by phase using phases identified on a 0.7° × 0.7° grid at each 6-hourly time. When compositing TRMM PR data, the matching is done on a 1.0° × 1.0° grid using data within 3 h of each 6-hourly time.

Fig. 1.
Fig. 1.

(a),(b) Illustration of the AEW phase bins. Amplitudes below 1.5σ are excluded from the composites. In (a) phase numbers follow the same convention as in Reed et al. (1977). In (b) only four phases are shown; this phase space is used for some analyses involving TRMM PR data.

Citation: Monthly Weather Review 144, 1; 10.1175/MWR-D-14-00419.1

Standardized fields were used to define the phase space so that regional differences in the intensity of the AEWs would be reflected in the composites. The standard deviation of AEW-filtered relative vorticity with TCs removed (x axes in Fig. 1) is shown in Fig. 2. There is a general westward increase in the magnitude of AEW activity between 35°E and 20°W. The spatial structure of the standard deviation of the time derivative of the AEW-filtered relative vorticity is similar (not shown). To examine north–south and east–west contrasts in the relationship between AEWs and convection, four domains were selected: east Atlantic (ATL, 5°–10°N, 40°–20°W), southern West Africa (SWA, 5°–10°N, 10°W–10°E), central West Africa (CWA, 10°–15°N, 10°W–10°E), and East Africa (EAF, 5°–10°N, 10°–30°E). The climatological properties of convection within these domains are examined in JT14.

Fig. 2.
Fig. 2.

Standard deviation of TD-filtered 700-hPa relative vorticity with TCs removed (×10−5 s−1) during JAS 1998–2012. Black boxes show the four regional domains: east Atlantic (ATL), central West Africa (CWA), south West Africa (SWA), and East Africa (EAF).

Citation: Monthly Weather Review 144, 1; 10.1175/MWR-D-14-00419.1

Figure 3 illustrates the identification of AEW phase for an intense AEW in 2006, which was the precursor to Hurricane Helene (Schwendike and Jones 2010). In this figure, unfiltered fields include TCs while filtered fields exclude TCs. Figures 3a and 3b show the unfiltered TRMM 3B42 rain rate and ERA-Interim 700-hPa relative vorticity averaged between 5° and 15°N. In addition, AEW-filtered relative vorticity (x axes in Fig. 1) is contoured every 1σ in each panel to highlight the troughs and ridges. The phase and amplitude of the AEWs was determined using data that were first averaged from 5° to 15°N. This is purely for illustrative purpose, the composites presented in section 3 match fields with their phase and amplitude on a latitude–longitude grid. The phase is not displayed for points where the amplitude (distance from origin of phase space) averaged between 5° and 15°N is less than 1.

Fig. 3.
Fig. 3.

(a) Unfiltered TRMM 3B42 rain rate (mm h−1, shaded), (b) unfiltered ERA-Interim 700-hPa relative vorticity (×10−5 s−1, shaded), (c) AEW phase (shaded) with amplitudes less than 1σ excluded, and (d) AEW amplitude (σ, shaded). AEW amplitude in (c) and (d) is defined as the distance from the origin in Fig. 1. In each panel, AEW-filtered relative vorticity is superimposed (contoured every 1σ); TCs have been removed from this field and all fields in the bottom two panels. All fields are averaged from 5° to 15°N. A TC symbol marks the genesis of Hurricane Helene.

Citation: Monthly Weather Review 144, 1; 10.1175/MWR-D-14-00419.1

In Fig. 3, a TC symbol marks the time when TC Helene reached tropical depression status at 1200 UTC 12 September 2006. The AEW trough associated with this TC can be traced back to 6 September in the AEW-filtered relative vorticity. The filter also captures ridges to the east and west of the trough and a weaker and less coherent trough after the Helene wave. The highest rain rates were found in the northerlies of the Helene wave (Fig. 3a), as is typically observed (e.g., Kiladis et al. 2006). From 8 to 11 September, the highest AEW amplitude is aligned with the trough; following this, the highest amplitude shifts into the ridge found to the west of TC Helene (Fig. 3d). This illustrates that the AEW amplitude defined using this method is independent of AEW phase. Figure 3 also illustrates the exclusion of the westward-moving relative vorticity signal associated with TC Helene by the TC removal procedure.

2) Statistical significance

The statistical robustness of the results with respect to sampling errors was assessed using a bootstrap analysis (Iida et al. 2010; Barnes and Houze 2013; JT14). In each of the 1000 bootstrap simulations, TRMM statistics over a given regional domain (EAF, CWA, SWA, and ATL) are recalculated by drawing from daily binned data randomly with replacement using all available days. The number of times daily data is sampled in each simulation is equal to the number of days during JAS 1998–2012. The 95% uncertainty range (±2 standard deviations) was determined for each statistic in each regional domain and AEW phase using these 1000 simulations.

3. Results

a. Overview of AEW structure and rainfall modulation

To demonstrate that the AEW phase identification method is accurately capturing the tilted mixed barotropic–baroclinic structure of the waves presented in previous studies (e.g., Reed et al. 1977; Berry and Thorncroft 2005; Kiladis et al. 2006), Fig. 4 shows phase–latitude composites of the total relative vorticity and wind averaged over East Africa (10°–30°E), West Africa (10°W–10°E), and the east Atlantic (20°–40°W) at 700 and 925 hPa. At 700 hPa, there is elevated vorticity and cyclonic flow within the trough at each longitude (Figs. 4a,c,e). The small change in AEW amplitude at 700 hPa between East Africa and the east Atlantic is consistent with Janiga and Thorncroft (2013) who examined the composite structure of AEWs in three different reanalyses using a vortex-tracking method.

Fig. 4.
Fig. 4.

Phase–latitude composites of total relative vorticity (×10−5 s−1, shaded) and wind (m s−1, vectors) at (a),(c),(e) 700 and (b),(d),(f) 925 hPa for (a),(b) East Africa (10°–30°E); (c),(d) West Africa (10°W–10°E); and (e),(f) the east Atlantic (40°–20°W).

Citation: Monthly Weather Review 144, 1; 10.1175/MWR-D-14-00419.1

At 925 hPa, there are much larger changes in wave structure between East Africa and the east Atlantic (Figs. 4b,d,f). Over East Africa, a 925-hPa vortex is present within the trough at 16°N (Fig. 4b). This vorticity signature also observed by Berry and Thorncroft (2005) weakens with height and is associated with a positive temperature anomaly (not shown) suggesting a warm-core structure. At 10°N, the latitude of the 700-hPa vortex, the 925-hPa vorticity is only slightly elevated in the trough, which is also consistent with the results of Janiga and Thorncroft (2013). Between East Africa and West Africa, the northern vortex at 925 hPa strengthens dramatically and shifts north to 19°N. In addition, the 925-hPa portion of the vorticity anomaly near 10°N intensifies. Over the east Atlantic, the northern vortex at 925 hPa is no longer apparent, consistent with the absence of a baroclinic zone and eddy heat transport (Diedhiou et al. 2002), and the 925-hPa flow is dominated by the low-level portion of the southern convectively active vortex.

Figure 5 shows the geographic variability of the relationship between AEW phase (as defined in Fig. 1a) and the unconditional rain rate. The unconditional rain rate is the average rain rate including pixels with zero rain rate. In contrast, the conditional rain rate excludes zeros from the average and is, therefore, a measure of rain intensity. To construct this figure, rain rates from the TRMM 3B42 product, TRMM PR near-surface rain rate, and ERA-Interim forecast rain rate were binned into eight AEW phases at each point on a 1.0° × 1.0° grid. The TRMM PR rain rate was then rebinned to a 5.0° × 5.0° grid using the 1.0° × 1.0° data to increase the robustness of the results. Next, a single harmonic was fitted to the series of rain rate as a function of AEW phase at each grid point. The phase illustrated is the wettest phase in the harmonic fit and the amplitude is the difference between the rain rate in the wettest and driest phase.

Fig. 5.
Fig. 5.

(a),(c),(e) AEW phase with the greatest unconditional rain rate based on a single harmonic fit of the (a) TRMM 3B42, (c) TRMM PR, and (e) ERA-Interim forecast rain rate. (b),(d),(f) Harmonic amplitude (mm h−1) of the (b) TRMM 3B42, (d) TRMM PR, and (f) ERA-Interim forecast rain rate. The PR data were rebinned to 5.0° × 5.0° prior to computing the phase and amplitude. Regions where the first harmonic explains <50% of the variance are shaded gray.

Citation: Monthly Weather Review 144, 1; 10.1175/MWR-D-14-00419.1

The observed relationship between AEWs and rain rate is weak east of 30°E (Figs. 5b,d). Between 10° and 30°E, it is strongest between 5° and 10°N over the EAF domain (Figs. 5b,d), with rainfall preferred in the northerlies (Figs. 5a,c). Between 10°W and 10°E, the region of greatest amplitude is located between 10° and 12.5°N, with rain still preferred in the northerlies. Along the coast of the Gulf of Guinea, in the southern West Africa (SWA) domain, the modulation of rainfall is still quite strong but the preferred location is within and just ahead of the trough. The rain-rate peak shifts toward the trough along the western coast of Africa and is centered on the trough over the east Atlantic. The amplitude of the rainfall modulation also increases sharply moving from the land to the ocean between 10° and 15°W, which is especially apparent in the TRMM 3B42 rain rate.

The phase relationship between AEWs and rain rate in the ERA-Interim forecasts is quite different from the two TRMM rain rates (Fig. 5). Over East Africa, the relationship between AEWs and rain rate is too strong, is preferred in the trough instead of the northerlies, and displays unrealistic intense local amplitude peaks just south of the Darfur Highlands (10°N, 23°E) and west of the Ethiopian Highlands (11°N, 35°E). Over West Africa, rainfall is again biased toward the trough with two intense peaks in amplitude near the Jos Plateau (10°N, 9°E) and Guinea Highlands (8°N, 13°W). The tendency for rainfall produced by convective parameterizations to be biased toward the trough and have unrealistic amplitudes over Africa has been observed in other reanalyses (Janiga and Thorncroft 2013) as well as climate models (Skinner and Diffenbaugh 2013) and may be due to the absence of propagating convective systems. In addition, rain rates over the east Atlantic are preferred behind the trough in the ERA-Interim forecasts instead of within the trough as in TRMM. These biases may affect the reanalysis depictions of moisture and temperature within the waves (section 3e) and must be kept in mind.

Figure 6 shows phase–latitude composites of the unconditional rain rate from the same three datasets for East Africa, West Africa, and the east Atlantic. Similar to Fig. 5, these composites illustrate the following characteristics: 1) an increase in the absolute magnitude of the rain-rate anomalies between East Africa and the east Atlantic in the TRMM datasets, 2) the shift in rain rate toward the trough moving southward from the Sahel to the Guinea Coast over West Africa in the TRMM datasets, 3) a shift in rain rate toward the trough in the TRMM datasets moving from West Africa to the east Atlantic, and 4) the overestimation of rain rate within the trough over East and West Africa in the ERA-Interim forecasts.

Fig. 6.
Fig. 6.

Phase–latitude composites of unconditional rain rate anomalies (relative to JAS 1998–2012) from the (a),(d),(g) TRMM 3B42; (b),(e),(h) TRMM PR; and (c),(f),(i) ERA-Interim forecast rain rate (mm h−1, shaded) for (a)–(c) East Africa (10°–30°E); (d)–(f) West Africa (10°W–10°E); and (g)–(i) the east Atlantic (20°–40°W).

Citation: Monthly Weather Review 144, 1; 10.1175/MWR-D-14-00419.1

b. Rain types

Rain observed by the TRMM PR was divided into several categories: stratiform, convective, shallow convective, and deep convective using the same rain-type flags as JT14 (see their Table 1). Figure 7 shows the percent difference between the unconditional rain rate in each AEW phase, including times when no AEW was present, and the climatological rain rate for each rain type within each domain. For reference, the climatological rain rates are shown in the keys.

Fig. 7.
Fig. 7.

Unconditional rain rate (% difference from climatology) for each AEW phase: northerlies (N), trough (T), southerlies (S), ridge (R), and no AEW (NO). Rain types shown are total (T), stratiform (S), shallow convective (SC), and deep convective (DC). Climatological rain rates for each rain type are shown in the key. Error bars show the 95% uncertainty due to sampling error from the bootstrap analysis. Shallow convective rain is very rare in the EAF and CWA domains and is excluded.

Citation: Monthly Weather Review 144, 1; 10.1175/MWR-D-14-00419.1

In the EAF domain, the enhancement of rain in the northerlies and suppression of rain in the southerlies is statistically significant for the total rain rate as well as the stratiform and deep convective rain rate (Fig. 7a). The phase of the relationship between rain rates and AEWs is similar in the CWA domain but the amplitude of the departures from climatology is larger (Fig. 7b). Similar to Figs. 5 and 6, Fig. 7c shows that, relative to the CWA domain, rain is shifted toward the trough in the SWA domain. In contrast, shallow convection is enhanced in the southerlies and suppressed in the northerlies (Fig. 7c). However, the enhancement of shallow convection in the southerlies is weaker than the enhancement of other rain types in the trough.

In the ATL domain, the total, deep convective, and stratiform rain rates are significantly enhanced in the trough and suppressed in the ridge (Fig. 7d). However, shallow convection is much less sensitive to AEW phase than deep convection and stratiform. This is similar to JT14 who showed that while the dry and humid days over the east Atlantic have large differences in deep convective and stratiform rain rates, the shallow convective rain rates are similar (see their Fig. 11a).

Figure 8 shows the stratiform, deep convective, and shallow convective rain fractions for each phase and domain. In both the EAF and CWA domains, the stratiform fraction is highest in the trough and lowest in the ridge while the deep convective rain fraction is highest in the ridge and lowest in the trough (Figs. 8a,b). However, these differences are more robust in the CWA domain where the waves have a stronger influence on rain rates. In the SWA domain, the stratiform fraction is lowest in the northerlies and highest in the trough while the deep convective fraction is highest in the northerlies and lowest in the southerlies (Fig. 8c). In the ATL domain, stratiform fractions are highest in the trough and southerlies and lowest in the ridge and northerlies (Fig. 8d). In contrast, the deep convective fraction is highest in the ridge and northerlies and lowest in the trough and southerlies. The shallow convective fraction is significantly higher in the ridge than the other phases in the ATL domain.

Fig. 8.
Fig. 8.

As in Fig. 7, but for the fractional rain contribution (%) from stratiform (S), deep convective (DC), and shallow convective (SC) rain. Stratiform and deep convective rain fractions are indicated by the left y axis and shallow convective rain fractions are indicated by the right y axis.

Citation: Monthly Weather Review 144, 1; 10.1175/MWR-D-14-00419.1

In the ATL domain, as convection transitions from suppressed to enhanced and back, certain rain types are preferred relative to climatology: shallow convection in the ridge during convectively suppressed periods, deep convection in the northerlies and trough during developing periods, and stratiform in the trough and southerlies during dissipating periods. This is similar to the evolution of rain types described by Mapes et al. (2006) for a variety of equatorial disturbances. The shallow convection may play some role in preconditioning the environment for deep convection by moistening it (e.g., Waite and Khouider 2010). Over the continent, high deep convective fractions precede the highest rain rates while stratiform lags behind and has high fractions in the postconvective AEW phase. This suggests an abrupt transition to deep convection, perhaps related to the prevalence of high conditional instability and the strong diurnal cycle.

The modulation of the unconditional rain rate (Fig. 7) and rain fractions (Fig. 8) can be explained by two factors: the rain frequency (Fig. 9) and the rain intensity or conditional rain rate (Fig. 10). The magnitude and phase of the variability of rain frequency is similar to the variability of the unconditional rain rate (Fig. 7). In contrast, changes in the conditional rain rate due to AEWs are only on the order of 10% of the climatological values. In addition, the phase with the highest conditional rain rates does not always have the highest unconditional rain rate or rain frequency. This behavior also occurs climatologically. Rain in the Sahel is rare but quite intense when it does occur (JT14).

Fig. 9.
Fig. 9.

As in Fig. 7, but for the fractional rain coverage (% difference from climatology).

Citation: Monthly Weather Review 144, 1; 10.1175/MWR-D-14-00419.1

Fig. 10.
Fig. 10.

As in Fig. 7, but for conditional rain rates (% difference from climatology).

Citation: Monthly Weather Review 144, 1; 10.1175/MWR-D-14-00419.1

Over land, there is a tendency for intense conditional rain rates to occur immediately preceding and during the periods of highest rain coverage while the weakest conditional rain rates occur during the suppressed and dissipating periods. For example, in the CWA domain (Fig. 10b), deep convective conditional rain rates in the northerlies and ridge are similar despite large differences in unconditional rain rates and rain coverage (Figs. 7b and 9b). In the ATL domain, rain intensity tends to be in phase with the rain coverage (Figs. 9d and 10d). The highest conditional rain rates occur in the trough and the lowest conditional rain rates occur in the ridge. These results suggest that over land rain coverage and rain intensity are controlled by different environmental factors while over the ocean the same factor controls both.

c. Reflectivity

Figures 11 and 12 show the climatological frequency of reflectivity values at each altitude (contours) and the deviations from this climatological frequency (shaded) for deep convective and stratiform rain in each AEW phase in the ATL and CWA domains, respectively. Here frequency refers to the fraction of time (%) that echoes of a given reflectivity are present. These domains are representative of the behaviors in the oceanic and continental environments. The TRMM PR near-surface rain rates are sensitive to drop size distribution (DSD) assumptions in the Z–R relationship (Iguchi et al. 2000, 2009; Kozu et al. 2009). In addition, the PR near-surface rain rate estimate tends to systematically underestimate the rate rate from intense convection over land (Rasmussen et al. 2013). Overall, the phases with elevated (reduced) conditional rain rates (top-right corner of panels in Figs. 11 and 12) also have elevated (reduced) near-surface reflectivity. This suggests that variations in the conditional rain rates are not dominated by changes in the Z–R relationship used to calculate the near-surface rain rate.

Fig. 11.
Fig. 11.

FADs showing the climatological frequency of echoes (contoured every 0.5%) and deviations from climatology for each AEW phase (%, shaded) for (a)–(d) deep convection (DC) and (e)–(h) stratiform (S) in the ATL domain. For reference the top right of each panel shows the conditional rain rate in each AEW phase (mm h−1) and the deviation from climatology (%) (also in Fig. 10).

Citation: Monthly Weather Review 144, 1; 10.1175/MWR-D-14-00419.1

Fig. 12.
Fig. 12.

As in Fig. 11, but for the CWA domain.

Citation: Monthly Weather Review 144, 1; 10.1175/MWR-D-14-00419.1

In the ATL domain, both deep convection and stratiform are characterized by a shift toward more frequent high-reflectivity values at all levels in the trough and a shift toward less frequent high-reflectivity levels at all levels in the ridge (Fig. 11). The increase in reflectivity, echo-top height, and conditional rain rates observed in the trough closely resembles those days in the ATL domain with high CRH (Figs. 16a,c in JT14) while the conditions in the ridge resemble the low CRH days (Figs. 16b,d in JT14).

In the CWA domain, the deep convective regions are characterized by more frequent high reflectivity in the ridge and less frequent high-reflectivity echoes in the trough and southerlies (Fig. 12). The upper-level stratiform reflectivity changes are consistent with those in the deep convection for each phase. This suggests that when deep convection produces large amounts of ice, it is transported to the upper-levels of neighboring stratiform regions. However, the response at low levels in the stratiform region can be weaker or of opposite sign. When stratiform is present in the ridge, the increase in the frequency of high reflectivity at upper levels greatly exceeds that at lower levels (Fig. 12h). Climatologically, stratiform reflectivity values are 3.1 dBZ greater at 4 km than at 1.5 km in the CWA domain, consistent with stratiform evaporation. In the ridge, this difference increases to 3.7 dBZ suggesting increased low-level evaporation that cancels out the effect of greater ice content aloft. In the northerlies, there is a shift toward more frequent high reflectivity at low levels despite near climatological reflectivity values aloft (Fig. 12e). Here the mean reflectivity at 4 km is only 2.4 dBZ greater than that at 1.5 km, indicating reduced low-level evaporation. The behavior observed by JT14 for low and high CRH days in the CWA domain resembles conditions in the ridge and northerlies, respectively (see their Fig. 17).

d. Precipitation features

Figure 13 shows, for each domain and phase, the PF size or intensity where 50% of the rainfall comes from PFs with attribute values both larger and smaller than the values displayed (Fig. 13a). These diagnostics summarize changes in the size or intensity of the dominant rainfall producing convective systems and were also calculated by Liu (2011) and JT14.

Fig. 13.
Fig. 13.

The PF attribute value at which 50% of the rainfall comes from PF attribute values larger and smaller than those displayed for all times or climatology (C), northerlies (N), trough (T), southerlies (S), ridge (R), and no AEW (NO). The PF attributes shown are the (a) effective diameter (km), (b) volumetric rain rate (×104 km2 mm h−1), (c) 18-dBZ maximum echo-top height (km), (d) 40-dBZ maximum echo-top height, (e) 85-GHz minimum brightness temperature (BT), and (f) 37-GHz minimum BT. The four domains are indicated by black (EAF), red (CWA), green (SWA), and blue (ATL) lines.

Citation: Monthly Weather Review 144, 1; 10.1175/MWR-D-14-00419.1

Similar to JT14, the variations in PF size and volumetric rain rate are closely related (Figs. 13a,b). In the EAF and CWA domains, the northerlies and ridge receive their rainfall from larger PFs with higher volumetric rain rates than the trough and southerlies. However, climatologically, the CWA domain is characterized by larger PFs with higher volumetric rain rates than the EAF domain and this is reflected in the individual phases. Large PFs also account for an anomalously high fraction of the rainfall in the northerlies in the SWA and ATL domains. However, in these domains the ridge is characterized by the smallest PFs.

Figures 13c–f show different metrics of PF intensity. High echo tops, especially at the 40-dBZ threshold, are consistent with strong updrafts while low microwave brightness temperatures are associated with large ice water paths (e.g., Zipser et al. 2006; Liu et al. 2007; Nicholls and Mohr 2010; Guy and Rutledge 2012; JT14). Overall, Figs. 13c–f are consistent with the conditional rain rate (Fig. 10) and frequency altitude diagrams (FADs) (Figs. 11 and 12) and indicate that, over the continent, intense systems dominate in the northerlies and ridge while weak systems are important in the trough and southerlies. In the ATL domain, system intensity is greatest in the northerlies and trough and lowest in the ridge.

Figures 14 and 15 illustrate how the rain rate from the three size and maximum 40-dBZ echo-top categories examined by JT14 are modulated by AEW phase in each region. Each category accounts for one-third of the rainfall over the east Atlantic and tropical Africa (Fig. 6 in JT14). The three size categories are roughly associated with isolated convection, multicellular clusters and small MCSs, and large MCSs or mesoscale convective complexes (MCCs), respectively.

Fig. 14.
Fig. 14.

(a)–(d) Difference from climatology (%) for the rain rate from each PF size class within each AEW phase and domain. (e)–(h) Fractional contribution (%) of the rainfall from each size class within each AEW phase. The PF sizes are small (S) (effective diameter D ≤ 74 km), medium (M) (D = 75–181 km), and large (L) (D ≥ 182 km). Climatological values are shown in the key of each panel.

Citation: Monthly Weather Review 144, 1; 10.1175/MWR-D-14-00419.1

Fig. 15.
Fig. 15.

As in Fig. 14, but for the 40-dBZ maximum echo-top categories: low top (L) (no 40-dBZ echoes and tops ≤ 5 km), medium top (M) (tops 5.25–6.5 km), and high top (H) (tops ≥ 6.75 km).

Citation: Monthly Weather Review 144, 1; 10.1175/MWR-D-14-00419.1

Figures 14a–d show the modulation of the rain rate from each PF size as a function of AEW phase for each region. As in Fig. 7, the climatological rain rate for each PF category is shown in the key. In the EAF domain, the rain rate from large PFs is significantly enhanced in the northerlies and reduced in the southerlies (Fig. 14a). The changes in the rain rate from small and medium PFs are much smaller and generally not statistically significant. This behavior is dramatically exaggerated in the CWA domain (Fig. 14b). In this region, even the rain rate from small PFs is significantly enhanced in the northerlies and suppressed in the southerlies but the degree of enhancement or suppression is much smaller than for the large PFs. In the SWA and ATL domains, the large PFs again have the strongest response to AEW phase (Figs. 14c,d) and are enhanced in the wet phases and suppressed in the dry phases (Fig. 7). Figures 14e and 14f show the changes in the rain fraction from each PF size in each domain. In the CWA domain, large PFs account for approximately 4 times as much rain as small PFs in the northerlies while they are less important than small PFs in the suppressed environment of the southerlies (Fig. 14f).

Figures 15a–d show how AEWs modulate the rainfall from the three PF echo-top categories. In the continental regions, high echo-top PFs are more sensitive to AEW phase than the low echo-top PFs (Figs. 15a–c) and in the ATL domain, medium echo-top PFs are more sensitive to AEW phase than the low top PFs (Fig. 15d) (high echo-top PFs are negligible in the ATL domain and excluded). The contribution of each PF type to the total rain rate in each AEW phase and domain is shown in Figs. 15e and 15f. In the CWA domain, both the northerlies and ridge have anomalously large contributions from high echo-top PFs and low contributions from the low echo-top PFs while the opposite is observed in the trough and southerlies (Fig. 15f). This occurs despite the fact that rain rates are suppressed in the ridge and enhanced in the northerlies (Figs. 7b and 15b). Over the east Atlantic, those phases with the most intense convection (Fig. 15h) are also those with the highest unconditional rain rate (Fig. 7d).

In summary, over the continent, those phases dominated by large and intense convective systems tend to be collocated or slightly ahead of the phase with the highest rain rate. In contrast, the phases characterized by weaker convective systems tend to follow the wettest phase. This would be consistent with a conditionally unstable environment with high convective inhibition before the development of widespread convection and a stable environment afterward due to widespread convective downdrafts. The greater sensitivity of the large PF rain rate to AEW phase indicates that AEWs primarily modulate rainfall by changing the frequency of large MCSs. Isolated convection is only weakly influenced by AEWs which suggests that it can be triggered by other processes such as cold pools and topographic features. In contrast, large MCSs appear to respond strongly to the enhancement or suppression from the large-scale environment associated with the AEW.

The size and intensity of the convection in the ATL domain is generally correlated with the unconditional rain rate. In oceanic environments, there is a strong relationship between CRH and the size and vertical development of convective systems (Brown and Zhang 1997; Zhou et al. 2013; JT14) as well as the total rain rate (Bretherton et al. 2004) and variations in conditional stability are weak. Based on this, one might expect variations in humidity associated with the AEWs to be the most important factor over the east Atlantic. The modulation of the large-scale environment by AEWs will be investigated in the following section to examine these possibilities.

e. Modulation of the convective environment

To investigate the causes of the observed variation in TRMM statistics, Fig. 16 shows composites of the large-scale environment within AEWs. As mentioned earlier, these results may be influenced by the physical parameterizations used in generating the reanalysis and should be viewed qualitatively.

Fig. 16.
Fig. 16.

Phase–latitude composites of anomalies of (a)–(c) Q vectors (×10−13 m Pa−1 s−3, vectors), Q-vector convergence (×10−18 Pa−1 s−3, shaded), and pressure vertical velocity (contoured every 1 hPa h−1) at 850 hPa; (d)–(f) column relative humidity (CRH) (%, shaded); and (g)–(i) 925–600-hPa shear magnitude (contoured every 1 m s−1) and vectors and CAPE (J kg−1, shaded) for (a),(d),(g) the east Atlantic (20°–40°W); (b),(e),(h) West Africa (10°W–10°E); and (c),(f),(i) East Africa (10°–30°E). In (a)–(c) the total vertical velocity not the vertical velocity predicted by the Q-vector equation is shown.

Citation: Monthly Weather Review 144, 1; 10.1175/MWR-D-14-00419.1

Figures 16a–c show anomalies of Q vectors, Q-vector convergence, and vertical velocity at 850 hPa, the level of maximum Q-vector convergence. The dry idealized simulations of Thorncroft and Hoskins (1994) produced ascent ahead of the trough and descent behind it at this level associated with the interaction between the AEW vortex and easterly shear below the AEJ. Following Kiladis et al. (2006), Q vectors were calculated using the nondivergent wind instead of the geostrophic wind [see their Eqs. (A1) and (A2)]; this provides a qualitative depiction of the adiabatic forcing for ascent. It is important to note that 850 hPa is within the well-mixed boundary layer and flow at this level and is strongly modulated by the diurnal cycle (Parker et al. 2005). However, compositing nondivergent and divergent flow anomalies as a function of AEW phase for each 6-hourly UTC time (not shown), reveals that the waves themselves are dominated by the rotational flow throughout the diurnal cycle. Therefore, although other factors may be involved in the triggering of convection, the adiabatic forcing for ascent associated with the waves is worth examining.

Over East Africa, areas of anomalous 850-hPa Q-vector convergence and ascent are observed on the west side of the northern vortex while Q-vector divergence and descent are observed to the east (Fig. 16c). A similar but amplified pattern of Q-vector convergence and vertical velocity is observed over West Africa (Fig. 16b). The strong correspondence between Q-vector convergence and ascent in a region devoid of moist convection suggests that adiabatic forcing is responsible for the ascent. The dramatic intensification of the northern vortex between East Africa and West Africa and the associated increase in adiabatic forcing may explain the onset of convection within the AEWs between 10° and 15°N that begins over West Africa (Fig. 5). South of 10°N, over West Africa and the east Atlantic, convection is centered in the trough. In these locations, the forcing for ascent is weak and other factors such as moisture may become more important.

Figures 16d–f show how AEWs modulate the CRH. In each region, CRH is enhanced within the trough and suppressed in the ridge. The enhancement of CRH within the trough may be due to the rotation within that feature trapping the moisture produced by convection (e.g., Dunkerton et al. 2009). Numerous studies have found a strong relationship between rain rate and CRH in the tropics (e.g., Bretherton et al. 2004; Holloway and Neelin 2009), including the regions of tropical Africa examined in this study (JT14). Over the SWA and ATL domains, the highest rain rates are located in the trough (Figs. 57). Since the adiabatic forcing for ascent in the northerlies is weak in these regions (Figs. 16a,b), reduced entrainment due to the enhanced CRH may be an important factor in determining the phase relationship between AEWs and rainfall.

Figures 16g–i show the modulation of CAPE and 925–600-hPa shear by AEWs. Over the continent, between 5° and 15°N, CAPE is slightly enhanced in the northerlies and strongly reduced between the trough and southerlies. The reduced CAPE between the trough and southerlies is likely associated with the transport of low midlevel equivalent potential temperature θe air downward and evaporative cooling within convective downdrafts combined with cold air advection from the south. The increased CAPE in the northerlies may be due to low-level advection as suggested by Berry and Thorncroft (2005); it may also be associated with a recovery of the boundary layer due to increased insolation following a period of suppressed cloud cover. JT14 examined the relationship between several environmental variables and both rain rate and PF characteristics. Over the CWA and EAF domains, CAPE did not have a significant relationship with rain rate. However, enhanced CAPE was associated with a significant increase in the fraction of the rainfall from high echo-top convection. Both the EAF and CWA domains showed a significant shift toward larger contributions from high echo-top systems in the ridge and northerlies and low echo-top systems in the trough and southerlies (Fig. 15). It is possible that this is due to the enhanced CAPE in the ridge and northerlies and reduced CAPE in the trough and southerlies.

Over the continent, the 925–600-hPa shear is enhanced between the ridge and northerlies and reduced between the trough and southerlies. Over West Africa, the shear between these two levels is associated with the low-level westerly monsoon flow and midlevel easterlies of the AEJ. The changes in shear appear to be primarily controlled by the northern vortex, which enhances the monsoon westerly flow between the ridge and northerlies and induces southerly flow between the trough and ridge (Fig. 4d). Over the CWA domain there is a clear shift toward large systems in the northerlies and smaller systems in the southerlies (Fig. 14f). Barnes and Sieckman (1984) found that fast-moving linear MCSs or squall lines tend to be located in the northerlies and ridge while slow-moving less organized convective systems are found in the southerlies. The large PFs include both linear MCSs and large but unorganized areas of convection. While we have not examined the organizational mode of the convection this is something that could be done in future work (e.g., Liu and Zipser 2013).

4. Summary and conclusions

In this study, the relationship between AEWs and the properties of convection and convective systems, diagnosed using the TRMM Precipitation Radar (PR), was examined. Rainfall intensity, rain type, the vertical structure of reflectivity, and the size and maximum echo top of contiguous precipitation features (PFs) as a function of AEW phase in several regions was interpreted using AEW composites of the large-scale environment (lift, moisture, conditional instability, and shear) based on the ERA-Interim reanalysis. This expands on previous studies of AEWs and convection that had primarily focused on cloud cover or rain rate.

Figure 17a summarizes the relationship between AEWs and convection over the Sahel or central West Africa (CWA) domain. Consistent with previous studies (e.g., Reed et al. 1977; Duvel 1990; Fink and Reiner 2003; Kiladis et al. 2006), the highest unconditional rates are located in the northerlies and the lowest in the southerlies. In this region, the northerlies are characterized by enhanced adiabatic forcing for ascent while the southerlies are characterized by forcing for descent. Adiabatic forcing for ascent appears to be a key factor in explaining the relationship between the unconditional rain rate and AEW phase.

Fig. 17.
Fig. 17.

Schematic of the AEW–convection relationship over (a) central West Africa (CWA) and (b) the east Atlantic (ATL). This schematic presents an exaggerated view of the amount and type of convection in each phase. Green (brown) circles indicate positive (negative) moisture anomalies. Red (blue) circles indicate regions of warm (cool) low-level temperatures and increased (reduced) CAPE. Arrows indicate the adiabatic forcing for ascent or descent.

Citation: Monthly Weather Review 144, 1; 10.1175/MWR-D-14-00419.1

In the East Africa (EAF) domain, the modulation of the unconditional rain rate by AEWs is weaker. While AEWs have similar intensities at 700 hPa in both the CWA and EAF domain, the northern vortices of AEWs over East Africa are much weaker than those over West Africa. Differences in the strength of the northern vortex appear to be connected to the strength of the adiabatic forcing for ascent. We also examined the relationship between rainfall and AEWs along the Guinea Coast in southern West Africa (SWA), a region that has received much less attention, and found that the rainfall tends to be located within the trough. Adiabatic forcing for ascent is weak this far from the baroclinic zone; therefore, the high rain rates in the trough may be associated with the enhanced column relative humidity (CRH) in that AEW phase.

The importance of different rain types is also dependent on AEW phase in the CWA domain. The ridge and trough are characterized by high fractions of deep convective and stratiform rain, respectively (Fig. 17a). However, this does not imply that either phase has the largest amount of rain from each rain type. Both the deep convective and stratiform rain rates are highest in the northerlies, which has a higher rain rate than any other phase. JT14 found that stratiform fractions tend to increase with CRH, which is higher in the trough than the ridge. The increase in stratiform rain rate with CRH may be due to factors such increased ice production aloft (Del Genio et al. 2012) and reduced low-level evaporation (Geerts and Dejene 2005; Fuentes et al. 2008).

As AEWs move from West Africa to the east Atlantic, the rainfall shifts from the northerlies to the trough (Fig. 17b), consistent with previous studies (e.g., Thompson et al. 1979). Laing et al. (2008) estimated the average phase speed of westward-propagating convective events and AEWs to be 12 and 7.7 m s−1, respectively, with convective events lasting 17.3 h on average. Therefore, the average convective event only gains 268 km relative to the AEW during its lifetime. Combined with increased local triggering of convection as one approaches the western coast of Africa, this explains why the mean rain rate does not shift toward the ridge. While the adiabatic forcing for ascent within AEWs is weak over the east Atlantic, the CRH is especially enhanced within the trough and reduced in the ridge and therefore likely plays a major role in the modulation of rain rate. The importance of different rain types is also modulated by the AEWs in the ATL domain. Stratiform fractions are especially high within the trough and southerlies, while shallow convective fractions are greatest within the ridge. However, the shallow convective rain rate is similar in each AEW phase. The variability of the deep convective and stratiform rain rate is what determines the changes in rain fraction.

AEWs also modulate the size and vertical development of convection. Both frequency altitude diagrams (FADs) of reflectivity and analyses of PFs were used to show that the ridge and northerlies are dominated by large and intense convective systems in the CWA domain (Fig. 17a). Smaller and weaker systems accounted for a larger fraction of the rainfall in the trough and southerlies. However, the number of large and intense systems was much greater in the northerlies than in the ridge and the number of small and weak systems in the trough was much greater than in the southerlies, explaining variations in the unconditional rain rate. We also found that CAPE and 925–600-hPa shear are greater in the northerlies and ridge than in the trough and southerlies. The reduction of CAPE in the trough and southerlies, where convective downdrafts produce a low-level stable layer, is much greater than the enhancement of CAPE in the ridge and northerlies. Variations in shear appear to be due to the low-level warm-core northern vortex found near 20°N. In the northerlies this feature enhances the low-level westerly flow, while in the southerlies it reduces it. This modulates the magnitude of the shear between the low-level westerlies and the midlevel AEJ. Variations in shear as a function of AEW phase may be linked to the size of the convective systems as suggested earlier by Barnes and Sieckman (1984). However, in the CWA domain, CAPE and shear appear to primarily control the characteristics of convective systems not their absolute number. The number of convective systems and the unconditional rain rate instead appear to be modulated by the adiabatic forcing for ascent.

In the ATL domain, CRH is the environmental factor that is most modulated by AEW phase (Fig. 17b). The AEW phases with larger and more vertically developed convection also have higher CRH and unconditional rain rates. This finding is similar to that in JT14 who examined how the properties of convection differ on days with high and low CRH in the region.

Guy and Rutledge (2012) also used the TRMM PR to examine how AEWs modulate rain type and the characteristics of PFs. However, they concluded that the contrasts in the properties of convection as a function of AEW phase are small when compared to the regional contrasts. Our results challenge this conclusion since we found that these contrasts are comparable in many cases. For example, the stratiform rain fraction varies from 51.0% in the ATL domain to 40.6% in the CWA domain. This is comparable to the contrast in the stratiform fraction between the trough (47.0%) and ridge (35%) within the CWA domain. Similarly, within the trough and ridge of AEWs, respectively, 65% and 20% of the rainfall comes from large PFs. This is much larger than the climatological regional contrasts between the four domains examined in this study. The regional variability in the fraction of the rainfall coming from PFs with different 40-dBZ echo tops is generally larger than the variability due to AEW phase. Nevertheless, statistically significant contrasts in the fraction of the rainfall from the different PF intensity categories were observed.

Presently, models with parameterized convection have considerable difficulty simply simulating rain rate as a function of AEW phase over land. They tend to underestimate the rain rate in the northerlies and overestimate the rain rate in the trough and southerlies (e.g., Skinner and Diffenbaugh 2013; Crétat et al. 2015). This bias is clearly present in the ERA-Interim forecasts (Figs. 5 and 6). Moreover, this problem also occurs in models with superparameterized convection (McCrary et al. 2014). Large westward-propagating MCSs, which are modulated by the diurnal cycle, are responsible for much of the rainfall in this region (e.g., Laing et al. 2008; JT14). This is why simulations with explicit convection, which are able to capture these MCS, are much better at simulating the diurnal cycle in the region (Pearson et al. 2014). Explicit convection may be required to correctly represent the phase relationship between AEWs and rainfall over land. Furthermore, simulations with explicit convection may be more easily compared to the satellite-based radar statistics of convective properties shown in this study. Detailed comparisons of observed and simulated convective properties may help identify issues with the simulated microphysical processes and cloud dynamics, which are themselves often related (e.g., Varble et al. 2014), and may feed back onto larger scales. For example, stratiform cloud is characterized by top-heavy heating profiles and increased midlevel potential vorticity production. As a result, the elevated stratiform fractions in the trough of AEWs in the CWA domain may contribute to the development of the cyclonic circulation within that phase.

Acknowledgments

We thank the three anonymous reviewers who provided insightful comments on this manuscript. TRMM data used in this study were acquired as part of the NASA’s Earth–Sun System Division and archived and distributed by the Goddard Earth Sciences (GES) Data and Information Services Center (DISC). The ECMWF reanalysis data were obtained from the Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. This research was supported by National Science Foundation Grants ATM-0732255 and AGS-1321568.

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