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    Initial state and domain configuration used in the 2D model.

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    Some key initial surface parameters used in the 2D model: (a) visible albedo, (b) emissivity, (c) leaf area index (LAI), and (d) SSTs prescribed in the 2D model. In (a)–(c), the dashed lines represent the idealized profiles, and the solid lines the ECOCLIMAP profiles.

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    Time–latitude diagrams during (a) the first 15 days for θe and the last 15-day period for (b) θe, (c) meridional wind, (d) zonal wind, (e) instantaneous precipitation, and (f) θ. The dashed lines indicate the continental boundaries.

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    Mean fields over the last 15-day period for the REF simulation: (a) zonal wind (m s−1), isoline every 2.5 m s−1; (b) meridional wind, isoline every m s−1; (c) vertical velocity, isoline every 0.5 × 10−2 m s−1; (d) potential temperature, isoline every 5 K; (f) water vapor mixing ratio, isoline every g kg−1, and (g) potential vorticy isoline every 0.05 PVU [where 1 PV unit (PVU) = 10−6 m2 s−1 K kg−1]. The symbols in the figure are explained in the text.

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    As in Fig. 4 except from the mean July 2000–01 ERA-40 data.

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    Latitudinal variation of model mean (days 15–30) fields (bold lines) compared to the ERA-40 July 2000–01 mean fields (thin), except for rainfall, which is compared to the July GPCP data: (a) θ (dashed line), θe, and rainfall. GPCP July and August values are represented by dashed and dotted line, respectively. (b) Zonal (solid line) and meridional (dashed line) wind profile from model results (bold lines) and from ERA-40 July 2000–01 data (thin line).

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    Latitudinal variation of the surface sensible and latent heat fluxes during the last 15 days of the REF simulation.

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    Latitudinal variation of the soil moisture at the beginning(day 0) and at the end (day 30) of the REF simulation.

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    Parameterized eddy fluxes of (a) zonal momentum and (b) heat during the last 15 days of the REF simulation: isoline every 2.5 m2 s−2 in (a) and every 2 K m s−1 in (b).

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    The θe, θ, and rainfall latitudinal profiles for the REF (bold) and Run_15April (dashed) experiments.

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    As in Fig. 10 but for the REF (bold), Run_Plateau (thin), and Run_Lower_Albedo (dashed) experiments.

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    As in Fig. 10 but for the REF (bold), GG_June (thin), and GG_May (dashed) experiments.

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    Latitudinal profiles of (a) θe, θ, and rainfall and (b) meridional wind for the REF (bold), MS_June (thin), and MS_May (dashed) experiments.

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    The θe, θ, and rainfall latitudinal profiles for the REF (bold), coast 35°N (thin), and No_MS (dashed) experiments.

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    Schematic diagram of the mechanisms that affect the northward penetration of rainfall over West Africa. The arrows indicate the rainfall displacement induced by each mechanism. Their widths are proportional to the intensity of the rainfall shift. See text for details.

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An Idealized Two-Dimensional Framework to Study the West African Monsoon. Part I: Validation and Key Controlling Factors

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  • 1 Centre National de Recherches Météorologiques, Météo-France, and Centre National de Recherches Scientifiques, Toulouse, France
  • | 2 Centre National de Recherches Météorologiques, Météo-France, and Centre National de Recherches Scientifiques, Toulouse, France
  • | 3 Centre National de Recherches Météorologiques, Météo-France, and Centre National de Recherches Scientifiques, Toulouse, France
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Abstract

An idealized vertical–meridional zonally symmetric model is developed in order to recover a July typical monsoon regime over West Africa in response to surface conditions. The model includes a parameterization to account for heat and momentum fluxes associated with eddies. The sensitivity of the simulated West African monsoon equilibrium regime to some major processes is explored. It allows confirmation of the important role played by the sun’s latitudinal position, the aerosols, the albedo, and the SST’s magnitude in the Gulf of Guinea and in the Mediterranean Sea.

The important role of aerosols in warming the Saharan lower layers and their effect on the whole monsoon is underlined. Model results also stress the importance of the Mediterranean Sea, which is needed to obtain the extreme dryness of the Sahara. The use of this idealized model is finally discussed for studying the scale interactions and coupling involved in the West African monsoon as explored in a companion paper.

Corresponding author address: P. Peyrillé, CNRM/GMME/Météo-France, 42 Ave. G. Coriolis, 31057 Toulouse, France. Email: philippe.peyrille@meteo.fr

Abstract

An idealized vertical–meridional zonally symmetric model is developed in order to recover a July typical monsoon regime over West Africa in response to surface conditions. The model includes a parameterization to account for heat and momentum fluxes associated with eddies. The sensitivity of the simulated West African monsoon equilibrium regime to some major processes is explored. It allows confirmation of the important role played by the sun’s latitudinal position, the aerosols, the albedo, and the SST’s magnitude in the Gulf of Guinea and in the Mediterranean Sea.

The important role of aerosols in warming the Saharan lower layers and their effect on the whole monsoon is underlined. Model results also stress the importance of the Mediterranean Sea, which is needed to obtain the extreme dryness of the Sahara. The use of this idealized model is finally discussed for studying the scale interactions and coupling involved in the West African monsoon as explored in a companion paper.

Corresponding author address: P. Peyrillé, CNRM/GMME/Météo-France, 42 Ave. G. Coriolis, 31057 Toulouse, France. Email: philippe.peyrille@meteo.fr

1. Introduction

The West African monsoon (WAM) has a significant impact on the regional climate and also plays an important role in the global climate. As an example, during the last few decades there has been a significant drought over West Africa that was associated with a drastic reduction of the monsoonal rainfall [see Hulme (1994) for a climatology]. The causes of that event are still not well understood and the question of what factors control the rainfall spatial distribution and its intensity remains fully open. One of the main difficulties in trying to understand the WAM variability comes from the important ocean–atmosphere–land coupling, which is a major characteristic of the system (Giannini et al. 2003; Zeng et al. 1999; Rowell et al. 1995).

The Atlantic Ocean, through sea surface temperature variations, is known as one of the major controlling factors of the WAM activity (Lamb 1978; Hastenrath 1984; Janicot 1992; Eltahir and Gong 1996; Zheng et al. 1999; Vizy and Cook 2002). Ward (1998) showed in particular that the north–south SST gradient is well correlated with the intensity of Sahelian precipitation. Recently, Rowell (2003) and Raicich et al. (2003) showed that Eastern Mediterranean SST anomalies are positively correlated with rainfall over the Sahel. Rowell explained it within the context of a numerical study as being caused by an increased evaporation for a warm sea, which sustains vapor transport into the continent.

The continental processes can play a key role through soil moisture (Clark and Taylor 2004; Taylor et al. 2003; Chou et al. 2001; Douville et al. 2001), vegetation cover (Kutzbach et al. 1996; Zheng and Eltahir 1998; Claussen et al. 1999; Zeng et al. 1999), and surface albedo (Charney 1975; Bonfils et al. 2001; Chou and Neelin 2003). Koster et al. (2004) also showed that West Africa is a region of the world where the soil–atmosphere coupling is the most important for local climate. Despite weak terrain elevation compared to other monsoon regions (400 m on zonal average except for a few mountains like the Aïr, Hoggar, and Fouta Jallon) orography can still have an impact on the regional circulation as shown by Semazzi and Sun (1997) and Drobinski et al. (2005).

The interactions of the WAM with the surface (continent and ocean) can be summarized by the results of Eltahir and Gong (1996) who showed that the WAM circulation intensity is well correlated with the meridional gradient of moist static energy (MSE) in the planetary boundary layer. A strong (weak) MSE gradient is diagnosed to be associated with a strong (weak) monsoon circulation and a more northerly (southerly) placement of the intertropical convergence zone and hence a wet year over the Sahel.

The internal dynamics of the atmosphere also comprises important factors that affect the WAM. Chou et al. (2001) have illustrated that the horizontal advection of humidity and temperature (ventilation) can disfavor moist convection over land. However, the albedo effect seems to be more important than ventilation over West Africa (Chou and Neelin 2003). Convective activity over West Africa can be modulated by waves such as equatorially trapped waves originating from the Pacific (Matthews 2004) or by Rossby waves generated by deep convective areas to the east of the WAM region (Rodwell and Hoskins 1996; Chou et al. 2001; Chou and Neelin 2003). Moreover, Roca et al. (2005) showed that midlatitude dynamics and the African monsoon are linked through dry air intrusions that can favor the formation of long-lived mesoscale convective systems. Also, strong interactions are known between the convective and synoptic scales (Redelsperger et al. 2002; Diongue et al. 2002), for which the magnitudes depend on the year considered (wet or dry) as shown by Grist and Nicholson (2001) for the synoptic weather systems and Grist et al. (2002) for easterly wave activity.

This terse review of the WAM dynamics aims at showing the numerous processes and interactions involved in the WAM, which present a major problem for a better understanding of its variability. Global circulation models (GCMs), in which the full system is supposed to be treated, do not fully succeed in representing a realistic monsoon in terms of the ITCZ location and its interannual variability [see the Atmospheric Model Intercomparison Project (AMIP) results, e.g., in Sperber and Palmer (1996)]. It thus implies that some of the fundamental process or interactions are not well represented, and moreover the complexity of the GCMs does not allow identifying them clearly.

A complementary approach is to use a simpler numerical framework where the degrees of freedom are limited and therefore the key mechanisms can be identified and studied more easily than in a GCM. This methodology has been successfully used in the past (e.g., Chou et al. 2001; Zheng et al. 1999; Rodwell and Hoskins 1996; Webster 1983), but, as of yet, not to treat the interactions over a wide range of scales.

In this series of two papers, a zonally symmetric numerical model is introduced to study West African monsoon dynamics using an idealized modeling approach. The goal here is not to simulate real cases, but to define idealized cases that contain the basic ingredients of reality. The host model provides a complete set of physical parameterizations and affords the possibility to explicitly resolve convection (high resolution) owing to the use of a two-way interactive grid-nesting technique. The framework has therefore been developed to investigate many of the phenomena and couplings outlined above and to treat the scale interactions ranging from diurnal up to the seasonal time scale. Nonetheless, in this series of papers only the low-resolution version of the model is used to assess the model possibilities. This study also aims at preparing the African Monsoon Multidisciplinary Analysis (AMMA) international program and its observation field campaign component that took place in 2006.

The goal of this first paper is to present and evaluate the idealized model. We then identify the WAM key controlling factors and address their relative importance within this unified framework. Section 2 presents the idealized model and the initial atmospheric and surface conditions. Section 3 evaluates the skill of the model in terms of retrieving the WAM summer regime as compared with climatology. Then the idealized model is used in section 4 to explore the WAM response to some processes known as playing a major role on the WAM equilibrium. Finally, those results are discussed in section 5. A companion paper (Peyrillé and Lafore 2006, manuscript submitted to J. Atmos. Sci., hereafter Part II), analyzes how the temperature and humidity advections can modulate the WAM activity and studies the diurnal cycle of the system using budget calculations.

2. The model configuration for the WAM

A quick glance at a map of West Africa is sufficient to reveal that this region exhibits unique characteristics. It is the largest region of the world (∼5000 km × 2000 km) with a high albedo corresponding to the Saharan desert. The quasi-zonal distribution of continental surface properties such as albedo and vegetation is the second striking feature. It is reflected in the quasi-zonal distribution of precipitation as depicted by climatologies (see, e.g., Hulme 1994), which can be explained by the east–west orientation of the Guinea coast along 5°N. The absence of major mountains also contributes to the zonal symmetry of this region. It should be noted that the only moderate mountains (in terms of elevation and expanse) of Cameroon and of Fouta Djalon coincide with two local maxima of precipitation that alter the zonal symmetry of the region. Australia exhibits similar idealized characteristics (Dickinson and Molinari 2000) but over a much smaller area (∼2000 km in longitude).

As a result, the gradients of surface properties are mainly meridional. Vegetation penetrates northward up to 15°N. The narrow Sahel zonal band (∼500 km) is a region with a strong meridional precipitation gradient corresponding to the sharp southern flank of the Sahara. The induced gradient of soil moisture generates strong low-level baroclinicity, responsible for the formation of the African easterly jet (AEJ) around 600 hPa and along 15°N during the Northern Hemisphere summer (Thorncroft and Blackburn 1999; Cook 1999; Parker et al. 2005).

a. The host atmospheric model

The aforementioned arguments aim at suggesting that, contrary to other monsoons, a two-dimensional framework can be used to explore the basic physics and couplings involved in the WAM, as already performed by Eltahir and his colleagues. This idea will be pursued in this series of papers by first developing an idealized two-dimensional model on a vertical–meridional domain. The goal is not to represent the whole complexity of the WAM system, but to isolate and understand its fundamental process and interactions.

The host model is the French community atmospheric simulation system Méso-NH (Lafore et al. 1998), which has been jointly developed by the Centre National de Recherches Météorologiques [Météo-France and the Centre National de la Recherche Scientifique (CNRS)] and the Laboratoire d’Aérologie (CNRS). This limited-area research model is based on the Durran (1989) modified anelastic system. It offers a complete physical package, including a fully interactive biosphere model, that is capable of doing simulations over a wide range of resolutions (100 km to 1 m) for both real and idealized cases. It also provides powerful diagnostics (tracers, in-line budgets, etc.) to analyze model results in details.

For the present study, the following physical parameterizations have been activated: (i) the one-dimensional version of a turbulent scheme (Cuxart et al. 2000) based on diagnostic second-order moments and a turbulent kinetic energy equation and the mixing length of Bougeault and Lacarrère (1989); (ii) a bulk microphysics scheme combining a three-class ice parameterization with Kessler’s scheme for warm processes (Pinty and Jabouille 1998; Caniaux et al. 1994); (iii) a convective scheme (Bechtold et al. 2001) adapted from Kain and Fritsch (1990); (iv) the European Centre for Medium-Range Weather Forecasts (ECMWF) operational radiation (Morcrette 1991); and (v) the Interactions between the Surface–Biosphere–Atmosphere (ISBA) surface scheme of Mahfouf and Noilhan (1996) implemented by Belair et al. (1998). To improve the surface flux parameterization over the ocean for weak wind regimes, the scheme proposed by Mondon and Redelsperger (1998) has been activated.

b. Model configuration and initial conditions

Figure 1 summarizes the model configuration and atmospheric initial conditions. A two-dimensional vertical–meridional domain is used, extending from 30°S to 40°N with a 70-km horizontal resolution. In the vertical, the domain reaches a height of 30 km, using a stretched mesh from 30 m near the surface to 1 km in the upper troposphere and a sponge layer above 20 km to avoid wave reflection at the rigid upper boundary. A Lambert projection has been chosen as Méso-NH allows a 2D east–west domain to be projected in the north–south direction by using a suitable choice of conicity and reference latitude parameters. Wall lateral boundary conditions have been employed, so interactions with midlatitudes are not considered in the present work to better control and understand the WAM system by itself. This external forcing may be considered later by simply adding a relaxation toward the climatology. The West African continent is approximated by a continental band between 5° and 30°N with the western Atlantic (Gulf of Guinea) and Mediterranean Sea to the south and north, respectively. An idealized profile of topography can be imposed; nevertheless it has been set to zero in this paper for most experiments.

The atmospheric initial conditions are horizontally homogeneous and at rest. This corresponds to an idealized potential temperature profile, depicted in Fig. 1, characteristic of the summer mean state of the tropical atmosphere over West Africa (between 10°W and 10°E). For this idealized approach, the relative humidity is simply set to 10% in order to reduce the surface–atmosphere coupling during the spin up of the model. Whereas the equilibrium reached by the WAM system is weakly sensible to the above initial conditions, the specification of aerosols is more important. They are prescribed from monthly climatology (Tegen et al. 1997).

The initial oceanic conditions are derived from the Reynolds SST estimates (Reynolds et al. 2002) provided by the Climate Diagnostics Center (more information available online at http://www.cdc.noaa.gov/cdc/data.noaa.oisst.v2.html) over the 1982–2003 period, and they are monthly and zonally averaged between 10°W and 10°E (Fig. 2d). The most salient characteristic of the seasonal evolution of the SST latitudinal distribution is a cooling in the Gulf of Guinea [∼−4°C (3 months)−1] and a warming of the Mediterranean Sea [∼+7.5°C (3 months)−1]. The importance of this reversal of the SST pattern surrounding West Africa on the WAM activity will be stressed in subsequent sections of this paper. The equatorial cold tongue development due to the upwelling establishment in spring in the Gulf of Guinea (see box in Fig. 2d) should also be noted.

The initialization of continental surface conditions is more complex as more than 20 surface and subsurface properties need to be prescribed within the surface biosphere scheme. The degree of complexity of this scheme is justified by the objective to study the surface–atmosphere coupling in a further paper. For that initialization purpose the ECOCLIMAP high-resolution land surface parameter database (Masson et al. 2003) is used, which is designed to initialize meteorological and climate models. For each surface property, the land use data are zonally averaged in the (10°W, 10°E) band in order to obtain its mean meridional distribution for the considered month. Finally, an idealized profile is prescribed from this distribution. Figures 2a–c show some of such meridional profiles for the surface albedo in the visible wavelengths, the emissivity, and the leaf area index (LAI), respectively, which are crucial parameters for the WAM. Schematically, three bands can be considered to obtain the idealized profiles. From the Guinea coast to ∼12°N the albedo is low and the emissivity is high, whereas the vegetation is maximum. On the contrary, over the Sahara (∼17°–30°N) there is high albedo, low emissivity, and no vegetation. In between, the Sahel band is a region of strong gradients of these surface parameters. For the visible albedo, higher values (0.35) than those proposed by ECOCLIMAP are used herein in order to better fit with values proposed by Knorr and Schnitzler (2001). The above parameters are all prescribed during the simulations, whereas the prognostic variables of the ISBA model are only initialized. In particular, the soil moisture is initialized at the wilting point value (corresponding to values comparable with Walker and Rowntree 1977), so that, during the model spinup, the atmosphere will be fed by moisture mainly from the ocean fluxes. This setup procedure has been found to be the most efficient to reduce the sensitivity of the equilibrium state to the initial moisture conditions, due to the soil memory.

Starting from the above initial conditions, the model is integrated for 30 days, with solar conditions corresponding to a permanent day (15 July) in order to study the equilibrium reached after a spinup period of about 15 days. The seasonal cycle is therefore not considered in this first paper.

c. Parameterization of heat and momentum meridional transfers

A 2D framework cannot explicitly resolve meridional transports of heat and momentum associated with eddies that develop in response to baroclinic and barotropic instabilities. These adjustment processes play an important role in avoiding symmetric instability and in determining the horizontal temperature profile and jet locations and magnitudes (Stone and Yao 1987, 1990). However, they do not alter the basic structure of the zonal mean meridional circulation of monsoon (Privé and Plumb 2007). Thus, a parameterization of these meridional fluxes has been implemented in the 2D WAM model in order to perform a long-term simulation later.

1) Eddy heat fluxes

The parameterization of eddy heat fluxes is taken from schemes available in the literature. To represent the meridional eddy heat flux, the simplest downgradient formulation of Zou and Gal-Chen (1999) is used [see their Eq. (4) ]. It is assumed to only depend on the horizontal mean gradient of the potential temperature:
i1520-0469-64-8-2765-e1
where the overbar denotes a zonal mean between 10°W and 10°E, the prime indicates the eddy component, and y is the local coordinate along the latitudinal direction. Similarly to Branscome (1983), the coefficient Kθ depends on the strength and on the depth of the baroclinic instability, the vertical stability, and the Coriolis parameter. The vertical eddy heat flux is also parameterized using the formulation given in Stone and Yao (1990). It is proportional to the horizontal eddy flux of heat as a function of the slope of isentropes [Eq. (25) of Zou and Gal-Chen 1999].

2) Eddy momentum fluxes

For momentum fluxes, an original parameterization largely inspired by Luz et al. (2003) is adopted. For the low latitudes considered here, it is assumed that eddies due to the barotropic adjustment are the main contributors to the meridional transport of the zonal momentum. The conservation of the absolute angular momentum M = (Ωa cosφ + u)a cosφ (with Ω representing the earth rotation, a is the earth radius, and φ is the latitude) is used to derive the eddy momentum fluxes, by stating a downgradient formulation for the meridional flux of M such that
i1520-0469-64-8-2765-e2
This formulation is applied at each model level within and around barotropically unstable regions. As in Luz et al. (2003), they are first defined as regions where the gradient of absolute vorticity (η) is negative (positive) in the Northern (Southern) Hemisphere. The boundaries (y1 and y2) of each unstable region and their center y0 = (y1 + y2)/2 are then detected. Finally the diffusion coefficient Ku is defined as
i1520-0469-64-8-2765-e3
where S(y) = (η(y2) − η(y1))/(y2y1) and Γ = (y2y1)/2.

Here Γ is the half-width of the unstable zone, S is the instability magnitude taken as the difference of η over its width, and Cu is a constant (Cu = 3 × 1014 m3) fixed to get momentum flux magnitudes similar to those estimated from 40-yr ECMWF Re-Analysis (ERA-40) (Simmons and Gibson 2000). The exponential function aims at diffusing the flux throughout the unstable zone. The final value of the coefficient is the sum of the contribution of each unstable region (if there are several).

d. Set of simulations

Table 1 provides the main characteristics of the reference simulation (hereafter REF) and of the 10 sensitivity experiments that will be presented and discussed in the present paper. It should be noted that the May SST has been prescribed for the Mediterranean Sea in the REF simulation aimed at simulating a typical July WAM regime. The main reasons for using such a cold Mediterranean SST are discussed in section 4d. The sensitivity experiments have been selected to illustrate the sensitivity of the 2D model to some parameterizations introduced for this study (eddy fluxes) and to explore the major features that act on the WAM equilibrium: the Gulf of Guinea and Mediterranean SSTs, albedo, mineral aerosols, the position of the sun (date), and the mean altitude of West Africa.

3. Overview of the reference simulation and sensitivity study

a. Reference simulation outline

Figure 3 shows the time–latitude diagram for the entire 30-day period of the reference simulation for several variables close to the surface. Starting from a dry mean tropical atmosphere at rest, the WAM model builds an atmospheric circulation in response to the oceanic and continental surface conditions. It thus takes only 10–15 days to reach a typical monsoon regime. Close to the surface, it is characterized by a southwesterly monsoon flow over the continent and the northeasterly Harmattan flow to the north (Figs. 3c,d). Their convergence occurs around 20°N and corresponds to the intertropical discontinuity (ITD). The equivalent potential temperature (θe) is maximum in the monsoon flux over the continent (Figs. 3a,b), whereas the temperature maximum is reached in the 20°–30°N band (Fig. 3f) corresponding to the Saharan heat low (SHL). The permanent state reached after about 15 days is not steady. First, the diurnal cycle is intense and maximum for θe and θ in the monsoon and in the SHL, respectively. Second, a slower variability with a northward drift of the monsoon is noted, especially during the last 10 days as seen from all variables. In particular, precipitation, which initially spreads between the coast (5°N) and 15°N, drifts northward after day 20 to establish a dry regime along the coast (Fig. 3e).

b. Comparison with ERA-40 and the Global Precipitation Climatology Project (GPCP) fields

The mean vertical cross section over the last 15 days of simulation REF is depicted by Fig. 4 and compared with the ERA-40 reanalysis fields (Fig. 5). The ERA-40 reanalysis data are taken on T159 spectral resolution with 60 model levels. The data have been averaged for the July 2000 and 2001 months between 10°W and 10°E. It can also been compared to similar mean vertical slabs that have been shown by Grist and Nicholson (2003). The simple 2D WAM model succeeds in reproducing the basic ingredients of the WAM in July (i.e., the low-level moist monsoon and dry Harmattan flows, the ITD at 20°N, the midlevel AEJ around 15°N, the ITCZ around 10°N, the upper level tropical easterly jet (TEJ), and subtropical jet (STJ) to the south and north of the ITCZ, respectively, and the SHL. Many differences in terms of intensity and position of those structures can be noted.

The zonal winds (Figs. 4a and 5a) are stronger than ERA-40, especially the TEJ (30 instead of 20 m s−1) and the STJ (30 versus 20 m s−1). In addition, their positions are shifted by about 10° to the south. At low and midlevels, the winds are closer to the ERA-40 reanalysis with a similar AEJ magnitude (14 versus 12 m s−1) and position (∼15°N). Also, the idealized model rebuilds low-level westerlies along the coast (5°N), whereas in reality they are located near the equator. In general, the simulated structures are stronger than in ERA-40 reanalysis, which is a typical feature of the 2D modeling of monsoons (Privé and Plumb 2007; Stone and Yao 1987). The meridional wind (Figs. 4b and 5b) is quite realistic south of 20°N with an intense northerly branch at upper levels corresponding to the direct Hadley cell. At higher latitudes, the idealized model does not succeed in reproducing the indirect branch with a southerly flow. The vertical motions (Figs. 4c and 5c) are too strong and are located in the ITCZ. Subsiding motions in the free atmosphere are well reproduced overall, but they are too weak above the SHL region. The shallow ascending motions (up to 4–5 km) above the ITD are well reproduced. A band of moderate ascending motion up to 7 km is simulated at 6°S over the ocean on the southern flank of the cold pool. It corresponds to a band of precipitation that is not observed in July. The SHL structure (Figs. 4d and 5d) is well reproduced but is less warm than observed, and the model produced too much baroclinicity at midlevels above the SHL. At upper levels, the tropopause height change between the Tropics and subtropics is well reproduced although it is too sharp and is positioned too far south.

Finally, the vapor mean cross section of the model (Figs. 4e) is well compared to ERA-40 (Fig. 5e) Nevertheless the position of the vapor mixing ratio maximum stays a little too north. The potential vorticity (PV) mean structure exhibits the three main characteristics shown by Thorncroft and Blackburn (1999): that is, the low PV area in the SHL capped by a layer (4–7 km) of moderate PV, the midtropospheric high PV anomaly in the ITCZ, and the signature of the tropopause height change between the Tropics and subtropics. Thus, the PV gradient sign reversal (Dickinson and Molinari 2000) around and to the north of the AEJ is simulated, which is a signature of instabilities responsible for the development of AEWs.

Figure 6 provides a synthetic view of the monsoon regime simulated by the REF simulation as compared with the July mean WAM. Overall the latitudinal distribution of temperature, moist energy (θe), and precipitation exhibit the same patterns as those from ERA-40. As directly observed during the JET2000 experiment (Thorncroft et al. 2003), the salient features are the strong baroclinic zone and the θe gradient reversal in the Sahelian band (12°–18°N). The θ field at low levels confirms that the SHL is about 6 K colder and narrower than in the reanalysis. This may be the impact of a colder Mediterranean SST prescribed in the model for the REF experiment (May instead of July). The θe maximum is less than observed (5 K). The precipitation distribution is compared with the mean value between 10°W and 10°E of GPCP precipitation (more information is available online at http://www.ncdc.noaa.gov/oa/wmo/wdccamet-ncdc.html) product over the 1982–2003 period for July and August. The idealized model produced too much rain (by a factor of about 2), consistent with the stronger simulated ascending motions previously noted in the ITCZ. The rain distribution corresponds to a summer [July–August (JA)] regime. As observed, there is a sharp decrease of precipitation along the northern flank of the monsoon; nevertheless, some weak precipitation is obtained over the Sahara. Another discrepancy is the rainband over the ocean at 6°S as already noted on Fig. 4c. The low-level wind distribution (Fig. 6b) confirms previous conclusions drawn from the vertical cross sections: there is a good agreement for the meridional wind component in the monsoon but a weak overestimation of the Harmattan. In contrast, the zonal component is too strong over the ocean and for the Harmattan.

c. Distribution of surface fluxes and properties

Figure 7 provides the meridional distribution of surface fluxes averaged over the last 15 days of simulation REF. Over the Gulf of Guinea, the latent heat flux is strong (up to 200 W m−2) with a significant decrease (120 W m−2) over colder water within the equatorial upwelling zone that may explain the simulated rainband on its southern flank. Over the continent in the Soudanian band (up to 12°N), the latent heat flux stays significant (130 W m−2). The Sahelian band corresponds to a northward decrease of the latent heat flux whereas the sensible heat flux increases. In the SHL, the Bowen ratio reaches a value of 1 and both mean fluxes reach about 30 W m−2. Such values may be considered weak. Nevertheless, there are mean values over the full day and the diurnal cycle is intense. Also, the albedo is large over the SHL so that the soil receives a weak fraction of the incident solar radiation.

The soil moisture distribution at the end of the REF simulation (Fig. 8) reflects the amount of precipitation accumulated during the simulation minus the surface evaporation. So, starting from a wilting-point surface condition, the model retrieves realistic soil moisture distributions for summer conditions. In return, such moisture conditions can supply latent heat fluxes simulated in the Soudanian region.

In short, the idealized model using drastic assumptions (2D, wall lateral boundaries, no large-scale forcing, etc.) is able to reproduce a typical WAM regime that exhibits many similarities with ERA-40 reanalysis. It also presents some systematic differences (precipitation and upper-level jet magnitude). Keeping in mind these shortcomings, it is estimated that its degree of realism is sufficient to be used to explore the basic features that can control the multiscale and multiprocess WAM system. In a first step, the sensitivity of the model to the initialization procedure and to the parameterizations specifically implemented for this study is assessed. The next section describes the results concerning the parameterization of the meridional transfers.

d. Sensitivity study of the meridional transfers

Experiment No_EddyFluxes (see Table 1) started from the REF experiment at day 15 and was run another 15 days without the meridional transfer parameterization. In that case, TEJ and STJ reach larger magnitudes (40 and 55 m s−1) than for REF (30 and 30 m s−1), which is in agreement with previous studies (Stone and Yao 1987; Privé and Plumb 2007) that showed the weakening of the upper-tropospheric jets by eddies. Performing several month simulations without representing eddy fluxes will thus lead those jets to become unrealistic. Figure 9 shows the heat and momentum fluxes as parameterized in REF and averaged over the 15–30-day period. Heat fluxes are significant for latitudes north of 20°N and exhibit structure and intensity (17 K m s−1) similar those found by Schubert et al. (1990). Momentum fluxes are intense in the vicinity of the AEJ and of the STJ with maxima up to 10 m2 s−2 for the latter, which is still in agreement with Schubert et al. (1990).

4. Analysis of some of the WAM key forcing

The objective of this section is to explore the response of the idealized model to processes known as playing a role on the WAM mature regime: radiative forcing, aerosols, albedo, continent mean elevation, and oceanic basin SSTs surrounding West Africa (Gulf of Guinea and Mediterranean Sea here). Toward that aim, the diagnostics are the meridional distributions of precipitation, θ, and θe close to the surface averaged during the 20–30-day period of each simulation that provide a synthetic picture of the simulated WAM regime.

a. Radiative forcing and aerosols

Run_15April tests the impact of the radiative forcing (Fig. 10) by taking a permanent day in spring, whereas the solar maximum is closer to the equator (20°N) than in summer (25°N for REF). The WAM system is shifted southward of 2° for all parameters (precipitation, θ, and θe). The suppression of desert aerosol climatology has a similar impact but with a doubling of the southward shift (4°). Also, the SHL is a little colder (−2 K). It thus suggests that the more northerly position of the sun favors the WAM northward penetration. The dust aerosols clearly have the same effect by increasing the warming in the SHL, but with a stronger efficiency than for the sun seasonal displacement.

b. Forcing by the albedo and by the mean altitude of the continent

Since Charney (1975), many works have stressed the importance of the albedo on the northward extent of the WAM (Chou and Neelin 2003). Figure 11 confirms this idea, as a reduction of the albedo (−0.1 for albedo in the visible and infrared wavelengths) results in a northward displacement of the ITCZ rainband and of the θ and θe maxima by 5° and 3°C, respectively.

Whereas the high elevation of the relief plays a major role on the Indian monsoon (e.g., Flohn 1968; Yanai et al. 1992; Wu and Zhang 1998), this is less obvious for the WAM since the average elevation of West Africa is relatively low (∼400 m). The introduction of a plateau of a similar height induces a northward displacement of the monsoon of about 3° (Fig. 11). The impact on precipitation is stronger when rainy conditions prevail over the Sahara.

c. SST forcing by the Gulf of Guinea

The SST in the Gulf of Guinea (GG) is a factor recognized as the most important in controlling the WAM (e.g., Hastenrath 1984; Janicot 1992; Ward 1998; Zheng et al. 1999). The rapid cooling of the GG between May and June (Fig. 2d) can contribute to the WAM onset that occurs on 21 May on average (Sultan and Janicot 2003; Okumura and Xie 2004; Gu and Adler 2004). Figure 12 tests this hypothesis by prescribing different SST meridional distributions in the GG. The idealized model response confirms this link. The warmer SST observed in May increases the moist energy over the GG. Two rainbands are generated around the equator and at 9°N. In June when the SSTs in GG are 2°C less, the monsoon shifts northward by 2° for θ and 4° for θe, its moist energy decreases, and the two rainbands move to the coast and to 11°N. Finally, in July with the coldest GG SSTs, the rainband settles around 13°N. All together, the cooling of the Gulf of Guinea between June and July can alone explain a northward drift of the WAM by about 6° of latitude.

d. SST forcing by the Mediterranean Sea

The role of SSTs in the Mediterranean Sea (MS) on the WAM has already been pointed out (Rowell 2003; Raicich et al. 2003), but to a lesser extent than for the GG. Figure 13a illustrates the response of the model to the SST warming of 5°C observed in the MS between May and July (Fig. 2d). It results in warming and moistening above the MS at low levels. The SHL magnitude (θ) and position are weakly affected. On the contrary, the moisture increases in the SHL with the SST warming. It helps precipitation to develop over the Sahara. It thus suggests that warmer SSTs in the MS favor the northward penetration of the WAM mainly through an increase of the moisture over the Sahara. The change in the distribution of meridional wind (Fig. 13b) gives another insight in the processes involved. Clearly, the magnitude of the Harmattan and its extension decrease with the MS warming. So the Harmattan magnitude and its southward penetration depend on the thermal contrast between the African continent and the MS. To summarize, two mechanisms favoring the northward penetration of the monsoon in summer are identified. First, the Mediterranean Sea warming decreases the thermal contrast with the Saharan heat low, resulting in a decrease of the Harmattan and its blocking effect. Second, the increase of moisture supply by the MS favors the SHL humidification. The above behavior led us to the choice of a REF simulation with a cold MS, thereby avoiding an unrealistic northward shift of the WAM in the idealized model. Possible causes of this drift related to the third dimension are discussed in Part II. For instance, zonal advection from the MS into the north of Africa (25°–35°N, 10°W–0°) act to cool the heat low. This effect is, in fact, represented here with a colder MS.

e. Impact of the latitudinal extent of the Mediterranean Sea

In regards to the MS_June, MS_July experiments, the Mediterranean Sea acts as a potential source of energy, the SST reflecting the intensity of such a source. Also, the position of the Mediterranean coast varies between 30° and 35°N in the eastern and western basins, respectively, which limits the amount of moist static energy available for transport into the Sahel. The impact of the coastal position (30°, 35°, and 40°N) in the idealized model (Fig. 14) has then been tested to understand the importance of the extension of the MS for the WAM. The question addressed here is then twofold: (i) can the position of the north coast explain why the eastern part of Sahel is colder than the western part and (ii) what is the basic role of this energy source? The meridional profiles of continental surface conditions are then extended to 35° and 40°N to reduce the extent of the MS. The last experiment is equivalent to replacing the MS by a continental desert surface. One can note that several experiments have been conducted with different profiles of surface conditions (lower albedo over 35°–40°N, nondesert conditions): all exhibited the same type of response, so they are not presented here for synthetic purpose.

The SHL drastically increases in magnitude and size when the coast is displaced to the north. Clearly, the northern flank of the SHL is influenced by the coast position so that, without the MS, the SHL reaches the northern boundary of the model. The precipitation distribution also changes in response to the displacement of the coast position. The rainband around 13°N decreases in magnitude but stays at the same location, whereas weak precipitation develops over the Sahara. This suggests that the MS existence may, in part, explain the extreme dryness of the western Sahara whereas the eastern Sahara experiences less warm/dry conditions. The effect of orography is not considered here and might also play a role in this asymmetry (Semazzi and Sun 1997).

5. Discussion and conclusions

Following the approach initiated by Eltahir and his colleagues, an idealized 2D model is developed that is used to recover the monsoon regime over West Africa in response to different meridional profiles of surface conditions. The main assumptions imposed on the model are the 2D framework and wall boundary conditions at the southern and northern model boundaries (30°S and 40°N), respectively. An interactive surface scheme is activated to treat the atmosphere–continental surface coupling, which plays a major role on the WAM regime. A parameterization of meridional eddy fluxes of heat and zonal momentum has been added in order to allow simulations over long periods, such as a full season.

Starting from a dry mean tropical atmosphere at rest and prescribing idealized surface conditions over the continent and SSTs over the Gulf of Guinea and Mediterranean Sea, after a 10–15-day transition this idealized model reaches a monsoon regime that can be compared with the mean state provided by the ERA-40 reanalysis and climatologies. Despite some differences (jets too strong, heat low too cold), the idealized model is able to reproduce the basic ingredients of the WAM. It thus suggests that the West African monsoon is basically a 2D system and that to a first order; thus, it can be simply considered to be the atmospheric response to oceanic and continental surface conditions.

The model reveals that the characteristic time scale of this response is about 10 days. It can simply be interpreted as the time needed to moisten the tropical atmosphere by surface latent heat fluxes (10 days at 150 W m−2). Nevertheless it is more complex and fundamental as it is also the time to retrieve the WAM dynamics. This may have important consequences for understanding the strong intraseasonal variability of the WAM. For instance, many studies (Kiladis and Weickmann 1997; Sultan et al. 2003) note peaks of variability in the 10–14-day range [e.g., up to 40–60 days for the dry spells: (Sultan and Janicot 2000; Grodsky and Carton 2001)]. Until now, an effort has been made to find atmospheric dynamics explanations for this intraseasonal variability, but the question remains unanswered. Here, it is suggested that the coupling between the surface and the atmosphere may be another source for the WAM variability observed between 10 and 40 days.

A large set of sensitivity experiments was performed in order to explore the response of the idealized model to some processes known to play a major role on the WAM mature regime. The schematic shown in Fig. 15 summarizes the relative impact of the above processes on the monsoon northward penetration.

  • The northward displacement of the sun from spring to the summer favors the northward extent of the WAM.
  • The dust aerosols have the same effect but with a stronger efficiency. As no coupling between aerosols and atmospheric dynamics is allowed in the model, only the radiative effect of aerosols is exhibited here. The greater warming of the SHL in the REF experiment can be associated with the absorption of solar radiation by dust aerosols, which causes a local warming of the lower Saharan layers (Myhre et al. 2004; Grini et al. 2006). This effect of strengthening of the heat low by the aerosols was already pointed by Mohalfi et al. (1998) but for the case of the Arabian heat low and without considering their effect on the WAM.
  • The West Africa mean elevation (∼400 m) also contributes to the northward displacement of the WAM. In further work it would be interesting to use this model to explore the impact of the local topography (Fouta Djalon, Jos Plateau, Aïr, and Cameroon Mountains) on the convection onset and on the precipitation spatial distribution. Nevertheless, other orographic effects, as studied by Drobinski et al. (2005) for the impact of the Saharan orography at the monsoon onset, are fully 3D and cannot be analyzed by the model.
  • The negative impact of an albedo increase (Charney 1975; Chou and Neelin 2003) is confirmed. This is not here the leading effect maybe because of the short time scale considered.

The maximum impacts are obtained when changing the SSTs of oceans surrounding West Africa:

  • A warm Gulf of Guinea has a negative impact on the WAM northward extent by reducing the meridional temperature gradient (Ward 1998). Thus, the rapid cooling of the Gulf of Guinea between April and June can contribute to the monsoon onset (characterized by an abrupt northward shift of the ITCZ).
  • In contrast, a warm Mediterranean Sea, as observed in July and August, favors the WAM penetration and precipitation over the Sahel, mainly through moisture advection and the decrease of the Harmattan blocking effect. The impact of the Mediterranean Sea is less well known than that of the Gulf of Guinea. Further studies are needed based on simulations and observational analysis.
  • The position of the Mediterranean Sea coast has been shown to have a positive impact on the WAM. This suggests that the northern limit of the Sahel precipitation band is shaped by the latitudinal extent of the Mediterranean Sea so that the penetration is less in central and eastern Africa in relation with the more southerly position of the coast in the Eastern Mediterranean (Leventine) basin. The position of the coast thus favors a wetter east Sahara. Also the suppression of the Mediterranean Sea influence results in a moister Sahara, so it is suggested that the existence of the basin contributes to the extreme dryness of the Sahara. This series of experiments (aerosols, Mediterranean Sea, etc.) also highlights that the meridional gradient of θe and θ are important not only south of the ITD (Eltahir and Gong 1996; Emanuel 1995) but also north of it.

Globally, the idealized model tends to shift the WAM too far northward. It is the main reason why a cold Mediterranean Sea was prescribed, which limited this drift in the REF simulation. Some drastic assumptions may explain this behavior (2D framework, wall boundaries, etc.). In the companion paper (Part II), the idea is developed that there is the need to add an external forcing to represent the terms (zonal advection, transport by eddies, etc.) that are neglected in a 2D framework. This partly corresponds to the ventilation term introduced by Chou et al. (2001), and it is shown to impact the penetration of monsoon over the continent. Another salient feature of the present simulations is the intense diurnal cycle, especially for the Sahel and Sahara latitudes, as noted by Parker et al. (2005). Part II will also develop this aspect.

This study shows that the WAM is a complex multiscale, multiprocess system. Its equilibrium depends on a lot of interacting processes that can be explored with the model. Here, the study was limited to the atmospheric response for a permanent 15 July day. The coupling with the surface has not been analyzed to focus first on the main processes acting on the WAM (mainly SST forcing). The simulations of the full seasonal cycle, which involve coupling with the surface have already been performed and will be presented in a future paper.

Finally it must be noted that the model used here allows for the explicit resolution of finescale processes such as convection using the grid-nesting technique (Clark and Farley 1984; Stein et al. 2000). Above facilities have led us to choose this host model to perform high-resolution simulations in further studies.

Acknowledgments

The authors thank P. Mascart and C. Piriou for their suggestions. We are also grateful to S. Wright for the early development of the framework, P. Jabouille and the Meso-Nh support team for their numerous suggestions concerning the host model, and A. Boone for the first review of the paper. We also appreciate the work done by G. Castella and S. Faroux in exploring the monsoon dynamics using the idealized model.

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Fig. 1.
Fig. 1.

Initial state and domain configuration used in the 2D model.

Citation: Journal of the Atmospheric Sciences 64, 8; 10.1175/JAS3919.1

Fig. 2.
Fig. 2.

Some key initial surface parameters used in the 2D model: (a) visible albedo, (b) emissivity, (c) leaf area index (LAI), and (d) SSTs prescribed in the 2D model. In (a)–(c), the dashed lines represent the idealized profiles, and the solid lines the ECOCLIMAP profiles.

Citation: Journal of the Atmospheric Sciences 64, 8; 10.1175/JAS3919.1

Fig. 3.
Fig. 3.

Time–latitude diagrams during (a) the first 15 days for θe and the last 15-day period for (b) θe, (c) meridional wind, (d) zonal wind, (e) instantaneous precipitation, and (f) θ. The dashed lines indicate the continental boundaries.

Citation: Journal of the Atmospheric Sciences 64, 8; 10.1175/JAS3919.1

Fig. 4.
Fig. 4.

Mean fields over the last 15-day period for the REF simulation: (a) zonal wind (m s−1), isoline every 2.5 m s−1; (b) meridional wind, isoline every m s−1; (c) vertical velocity, isoline every 0.5 × 10−2 m s−1; (d) potential temperature, isoline every 5 K; (f) water vapor mixing ratio, isoline every g kg−1, and (g) potential vorticy isoline every 0.05 PVU [where 1 PV unit (PVU) = 10−6 m2 s−1 K kg−1]. The symbols in the figure are explained in the text.

Citation: Journal of the Atmospheric Sciences 64, 8; 10.1175/JAS3919.1

Fig. 5.
Fig. 5.

As in Fig. 4 except from the mean July 2000–01 ERA-40 data.

Citation: Journal of the Atmospheric Sciences 64, 8; 10.1175/JAS3919.1

Fig. 6.
Fig. 6.

Latitudinal variation of model mean (days 15–30) fields (bold lines) compared to the ERA-40 July 2000–01 mean fields (thin), except for rainfall, which is compared to the July GPCP data: (a) θ (dashed line), θe, and rainfall. GPCP July and August values are represented by dashed and dotted line, respectively. (b) Zonal (solid line) and meridional (dashed line) wind profile from model results (bold lines) and from ERA-40 July 2000–01 data (thin line).

Citation: Journal of the Atmospheric Sciences 64, 8; 10.1175/JAS3919.1

Fig. 7.
Fig. 7.

Latitudinal variation of the surface sensible and latent heat fluxes during the last 15 days of the REF simulation.

Citation: Journal of the Atmospheric Sciences 64, 8; 10.1175/JAS3919.1

Fig. 8.
Fig. 8.

Latitudinal variation of the soil moisture at the beginning(day 0) and at the end (day 30) of the REF simulation.

Citation: Journal of the Atmospheric Sciences 64, 8; 10.1175/JAS3919.1

Fig. 9.
Fig. 9.

Parameterized eddy fluxes of (a) zonal momentum and (b) heat during the last 15 days of the REF simulation: isoline every 2.5 m2 s−2 in (a) and every 2 K m s−1 in (b).

Citation: Journal of the Atmospheric Sciences 64, 8; 10.1175/JAS3919.1

Fig. 10.
Fig. 10.

The θe, θ, and rainfall latitudinal profiles for the REF (bold) and Run_15April (dashed) experiments.

Citation: Journal of the Atmospheric Sciences 64, 8; 10.1175/JAS3919.1

Fig. 11.
Fig. 11.

As in Fig. 10 but for the REF (bold), Run_Plateau (thin), and Run_Lower_Albedo (dashed) experiments.

Citation: Journal of the Atmospheric Sciences 64, 8; 10.1175/JAS3919.1

Fig. 12.
Fig. 12.

As in Fig. 10 but for the REF (bold), GG_June (thin), and GG_May (dashed) experiments.

Citation: Journal of the Atmospheric Sciences 64, 8; 10.1175/JAS3919.1

Fig. 13.
Fig. 13.

Latitudinal profiles of (a) θe, θ, and rainfall and (b) meridional wind for the REF (bold), MS_June (thin), and MS_May (dashed) experiments.

Citation: Journal of the Atmospheric Sciences 64, 8; 10.1175/JAS3919.1

Fig. 14.
Fig. 14.

The θe, θ, and rainfall latitudinal profiles for the REF (bold), coast 35°N (thin), and No_MS (dashed) experiments.

Citation: Journal of the Atmospheric Sciences 64, 8; 10.1175/JAS3919.1

Fig. 15.
Fig. 15.

Schematic diagram of the mechanisms that affect the northward penetration of rainfall over West Africa. The arrows indicate the rainfall displacement induced by each mechanism. Their widths are proportional to the intensity of the rainfall shift. See text for details.

Citation: Journal of the Atmospheric Sciences 64, 8; 10.1175/JAS3919.1

Table 1.

Set of simulations with their main characteristics.

Table 1.
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