ATMOSPHERIC SCIENCE LETTERS
Atmos. Sci. Let. 13: 103–107 (2012)
Published online 23 December 2011 in Wiley Online Library(wileyonlinelibrary.com) DOI: 10.1002/asl.367

The onset of the West African monsoon simulated in ahigh-resolution atmospheric general circulation modelwith reanalyzed soil moisture fields
T. J. Yamada,1 * S. Kanae,2 T. Oki3 and Y. Hirabayashi4
1 Faculty of Engineering, Hokkaido University, Kita 13, Nishi 8, Kita-ku, Sapporo 060-8628, Japan
2 Department of Mechanical and Environmental Informatics, Tokyo Institute of Technology, 2-12-1 O-okayama, Meguro-ku, Tokyo 152-8522, Japan
3 Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8595, Japan
4 Institute of Engineering Innovation, School of Engineering, The University of Tokyo, 2-11-16 Bunkyo-ku, Tokyo 113-8656, Japan*Correspondence to:T. J. Yamada, Faculty ofEngineering, Hokkaido University,
Kita 13, Nishi 8, Kita-ku,Sapporo 060-8628, Japan.
E-mail:tomohito@eng.hokudai.ac.jp
Received: 25 June 2011
Revised: 15 September 2011
Accepted: 22 November 2011

Abstract
The simulation of the onset of the West African monsoon (WAM), associated with thenorthward shift of the Intertropical Convergence Zone (ITCZ) occurring in May, June, andJuly, is a challenging task for atmospheric general circulation models (AGCMs), becauseof complex water and energy balance through the land-atmosphere interaction as well as
atmospheric processes. We provide evidence that a combination of state-of-the-art global
fields of reanalyzed soil moisture anomalies and a sufficiently high-resolution (∼50 km)
AGCM produces a successful simulation of the northward shift of the ITCZ and thefollowing onset of the WAM in July. Copyright  2011 Royal Meteorological Society
Keywords:

West African monsoon; soil moisture; African Easterly Jet; AGCM

1. Introduction
The Sahel is one of the most densely populated
regions of the African continent and is characterized meteorologically as a monsoon region. The
management of water resources across the Sahelin the monsoon season is important for agriculture
and other human activities. The Intertropical Convergence Zone (ITCZ) shifts abruptly northward from aquasi-stationary location at 5◦ N (Gulf of Guinea) in
May–June (MJ) to another quasi-stationary location at10◦ N in July–August (JA; Sultan and Janicot, 2000,2003), bringing about the onset of the monsoon overthe Sahel. The monsoon onset is routinely captured inregional model simulations (Gallée et al., 2004; Hagosand Cook, 2007) by realistic lateral boundary conditions of the atmosphere. On the other hand, manyGCMs, despite good simulations of the mature West
African monsoon (WAM) in August, have failed toaccurately simulate the ITCZ rapid northward transition from the Gulf of Guinea (d’Orgeval et al., 2006).
This article shows a successful example of the onset
simulation in a high-resolution atmospheric generalcirculation model (AGCM) that is not forced withrealistic lateral boundary conditions and atmosphericinitial conditions.

2. The model and experimental design
Our study involves two sets of eight AGCM simulations in 1998, using the AGCM designed for the Earth
Simulator (AFES; Ohfuchi et al., 2004). The AFES
Copyright  2011 Royal Meteorological Society

initially adopted physical and dynamical cores fromthe Center for Climate System Research (The University of Tokyo)/National Institute for Environmental Studies (CCSR/NIES) AGCM (Numaguti et al.,1997), which were then modified and developed independently at the Earth Simulator Center.
The eight AGCM simulations started at 00Z on
24–31 March using the European Centre for MediumRange Weather Forecasts (ECMWF) Reanalysis 40(ERA40) dataset as an atmospheric initial condition.
We used a T239 (∼50 km) triangular truncation, which
is approximately one fifth smaller than the resolutions (250–300 km) used in previous studies (Kanaeet al., 2006; Douville et al., 2007). We used thepentad Atmospheric Model Intercomparison Project(AMIP) optimally interpolated Sea Surface Temperature (OISST) data of 1998 as the boundary condition.
Hereafter, we refer to the set of basic model simulations as the control run (hereafter CTRL-T239), in
which the AMIP OISST data were prescribed at eachtime step. The eight simulations differed only in theirinitial atmospheric conditions.
The ensemble mean of the eight simulations isanalyzed below. Another set of eight simulations
called SOIL-T239 differed from CTRL-T239 only inthe treatment of subsurface soil moisture. In CTRLT239, subsurface soil moisture was computed by modeled precipitation and atmospheric conditions withland–atmosphere interactions, as in the standard in
AGCM simulations. Global fields of observationbased soil moisture are not available yet; therefore,in SOIL-T239, a simulated global field of reanalyzed
subsurface soil moisture was prescribed at each time

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step; this field was produced by an off-line land
surface model using ground and satellite-based precipitation observations (Global Precipitation Climatology Project, GPCP) (Huffman et al., 2001) and reanalyzed atmospheric forcing data (Hirabayashi et al.,2005). The design of SOIL-T239 is analogous tothose AGCM simulations using observed global SSTs
as a boundary condition, such as in studies of theimpact of El Niño. We defined subsurface soil moisture as that 5 cm below the land surface. Therefore,
the surface soil layer (0–5 cm) freely evolves throughland–atmosphere interactions.

3. Results
Upper panels of Figure 1 show the simulated andobserved geographical distributions of MJ mean precipitation and horizontal wind vectors at a lower height(925 hPa). The observation (Figure 1(a)) clearly shows
the ITCZ over the Gulf of Guinea (2–6◦ N, 10 ◦ W–
5 ◦ E). On the other hand, CTRL-T239 does not simulate the ITCZ (Figure 1(b)). The precipitation of
CTRL-T239 is approximately 3.3 mm/day, as opposedto the observed 7.6 mm/day, with unrealistic southerly
flow affecting the Sahel. In contrast, SOIL-T239 successfully simulates the geographical distribution of
precipitation (∼6.1 mm/day) over the Gulf of Guinea
and weakened horizontal wind vectors at 925 hPa overthe southern vicinity of the Sahel in MJ (Figure 1(c)).
Our results indicate that the geographical pattern andstrength of the oceanic ITCZ in the vicinity of thecoastline can potentially be improved by incorporating
reanalyzed soil moisture anomalies in high-resolution
AGCMs through the stationary unstable lower atmosphere during the 2 months.
Lower panels of Figure 1 show the results for July.
The ITCZ reaches to the Sahel, making the onsetof the WAM (Figure 1(d)). CTRL-T239 (Figure 1(e))

T. J. Yamada et al.

does not have enough precipitation contrary to theobservation. SOIL-T239 simulates well the geographical distribution of precipitation in July over many
parts of Sahelian countries (Figure1(f)). In the firsthalf of July, the area of large observed precipitation
abruptly shifts northward to 10◦ N (Figure 2(a)). The
poor simulation of CTRL-T239 in July could be a consequence of the ITCZ activity in MJ (Figure 2(b)).
Similarly, SOIL-T239 simulates clearly the northward
shift of the ITCZ to the Sahel (Figure 2(c)) with sufficient precipitation contrary to CTRL-T239. Comparing the observation (Figure 2(a)) and SOIL-T239(Figure 2(c)), SOIL-T239 exhibits smoother latitudinal shifts than the observed data due to averaging theresults of the eight ensembles. Each ensemble member
also represents the abrupt northward shift of the ITCZ.
The main driving forces of the ITCZ propagation northward to the Sahel are the low-level meridional flow (between the surface and 800 hPa) and theAfrican Easterly Jet (AEJ) at 600–700-hPa height inassociation with the intense solar heating over theSahara (Druyan and Hall, 1994; Cook, 1999; Sultanand Janicot, 2003). Observations indicate a strong convergence region at 925 hPa over 2–6◦ N in MJ, whichshifts northward to 8–12◦ N in the first half of July
(Figure 2(d)). The observed 700-hPa cyclonic vorticity
also shifts between MJ (over the Gulf of Guinea) andJuly (over the Sahel, Figure 2(g)). Relative vorticity
is an indication of the potential to develop barotropic
instability, which grows by converting potential energy
associated with the mean horizontal temperature gradient, as especially seen in the unstable flank of theAEJ, where the African Easterly Waves (AEWs) can
develop (Burpee, 1972; Norquist et al., 1997). Thefigures show clear northward displacement of the lowlevel convergence and the cyclonic vorticity, followed
by a northward shift of the ITCZ. Low-level convergence in CTRL-T239 differs from the observation,

Figure 1. Geographical distributions of precipitation and wind vector at 925 hPa height for GPCP, CTRL-T239, and SOIL-T239.
Upper figures are for May and June (MJ) and lower figures are for July. Wind vectors in (a) and (d) were plotted by the European
Centre for Medium-Range Weather Forecast (ECMWF) Reanalysis 40 (ERA40) dataset. The difference between the mean MJ daily
precipitation between SOIL-T239 (c) and CTRL-T239 (b) satisfied the 99% statistical significance level by Student’s t-test in andaround the Gulf of Guinea. Quadrilateral green (pink) lines indicate the targeted the Gulf of Guinea (the Western Sahel).
Copyright  2011 Royal Meteorological Society

Atmos. Sci. Let. 13: 103–107 (2012)

The onset of the West African monsoon

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Figure 2. Latitudinal diagrams of 10-day mean precipitation (mm/day) (upper panels), horizontal wind convergence (1/s) at 925 hPaheight (middle figures), and relative vorticity (1/s) at 700 hPa height (lower panels) averaged between 10 ◦ W and 5 ◦ E for GPCP,ERA40, CTRL-T239, and SOIL-T239. The left panels are for GPCP and ERA40; the middle panels are for CTRL-T239; and theright panels are for SOIL-T239. In the middle panels, values are multiplied by 106 . Warmer (cooler) colors indicate convergences(divergences). In the lower panels, values are multiplied by 105 . Cooler (warmer) colors indicate cyclonic (anticyclonic) disturbance.

and the cyclonic vorticity is not active until midJuly (Figure 2(h)) in the ensemble mean, even thougha few of the members intermittently show weaker
cyclonic vorticities over the Gulf of Guinea. In contrast, SOIL-T239 simulates both the low-level convergence (Figure 2(f)) and the cyclonic vorticity over theGulf of Guinea in MJ (Figure 2(i)). Furthermore, anorthward shift of these two prominent features fromthe Gulf of Guinea to the Sahel is simulated in thefirst half of July (Figure 2(i)). Thus, the combined
good simulation of the low-level convergence and thecyclonic vorticity led to the appropriate representationof the onset of the WAM.
To understand why SOIL-T239 reproduces thecyclonically sheared side of the AEJ better thanCTRL-T239, we examine the vertical profiles of MJ
mean zonal wind velocities averaged between 10 ◦ W
and 5 ◦ E (Figure 3(a)–(c)). Warmer colors in the middle troposphere indicate the AEJ. The meridional location of the AEJ simulated by SOIL-T239 agrees withthe observations. In CTRL-T239, strong easterly winds
extend to 2 ◦ S, and the AEJ formed farther southward compared to the observations. The surface andlower tropospheric warm temperature anomaly, particularly over the Sahel and the Sahara, is caused by
reduced release of latent heat and may be one reason in CTRL-T239 for the incorrect location of theAEJ (Figure 3(d)). The reason for the dry bias inCTRL-T239 over the regions could not be assessed
Copyright  2011 Royal Meteorological Society

without performing SOIL-T239, because of limited
observation. Finally, the same types of experiments
have been performed also at lower resolution (T39,∼300 km): SOIL-T39 and CTRL-T39, to discuss thehorizontal dependency of the onset of the WAM. The
prominent feature of the lower resolutions (Figure 4(a)and (b)) is too much precipitation over the Sahel in
MJ contrary to observation (Figure 2(a)). As clearlyshown in Figure 4(c)–(f), the low-level convergenceand the cyclonic vorticity at 700 hPa over the Gulf ofGuinea are also not produced with the lower resolution, despite the realistic soil moisture fields over land.
Therefore, such a low resolution is not be sufficient torepresent the meridional characteristics of atmosphericcirculations for the WAM onset.

4. Discussion
Previous studies have mainly discussed how soil moisture anomalies affect the variability in local precipitation predominantly through a one-dimensionalland–atmosphere process (Koster et al., 2004). Our
study demonstrates that realistic soil moisture states
influence precipitation nonlocally by controlling the
low-level convergence and conditions for AEWs
through the determination of heat low and geostrophic
circulation as well as surface hydro-meteorologicalconditions such as pressure field, the Bowen ratio
Atmos. Sci. Let. 13: 103–107 (2012)

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T. J. Yamada et al.

Figure 4. Latitudinal diagrams of 10-day mean precipitation(mm/day), horizontal wind convergence (1/s) at 925 hPa height(upper panels), and relative vorticity (1/s) at 700 hPa height(lower panels) averaged between 10 ◦ W and 5 ◦ E for CTRL-T39
and SOIL-T39. Details are provided in Figure 2.

Figure 3. Vertical and meridional distributions of mean Mayand June (MJ) zonal wind velocity for ERA40 (a), CTRL-T239(b) and SOIL-T239 (c). (d) Mean MJ air temperature differences
between SOIL-T239 and CTRL-T239.

and surface temperature gradient. Cook (1999) demonstrated the connection between soil moisture distributions and the AEJ and the thermal wind relationship during the monsoon’s mature stage. Both thestrength and the meridional location of the AEJ, whichforms the AEWs, were simulated well in SOIL-T239.
Our result suggests that this relationship may also be
important to simulate the onset. The difference of theinitial stage of the WAM between CTRL-T239 andSOIL-T239 further affects the prediction of Atlantic
hurricane activity (not shown). One limitation of ourstudy is that computational costs do not allow performing multiyear simulations at this time, which would
increase the confidence in the results. This will be thesubject of a future article.
From the viewpoint of climate change, the fourth
assessment report of the Intergovernmental Panel on
Climate Change (IPCC) noted that the Sahel could
become marginally more dry based on multi-model
assessment (Cook and Vizy, 2006), whereas someCopyright  2011 Royal Meteorological Society

individual models have projected an increase in rainfall across the Sahel (Liu et al., 2002). This work
implies that the spatial resolution and the degree ofland–atmosphere coupling may strongly affect the prediction of the WAM under climate change.

Acknowledgements
The authors wish to express their gratitude to Oreste Reale,
Wataru Ohfuchi, Takeshi Enomoto, Akira Kuwano-Yoshida,
and Nobumasa Komori for helpful comments and suggestions.
All computational resources were provided by the Earth Simulator Center in Japan Agency for Marine-Earth Science andTechnology. This work was supported by Core Research for
Evolutional Science and Technology, Japan Science and Technology Agency (CREST/JST).

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