# The diurnal cycle of lower boundary-layer wind in the West African monsoon

A. Kassimou, D.J Parker, B. Brooks, N. Kalthoff, Thierry Lebel

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A. Kassimou, D.J Parker, B. Brooks, N. Kalthoff, Thierry Lebel. The diurnal cycle of lower boundary-layer wind in the West African monsoon. Quarterly Journal of the Royal Meteorological Society, 2009, 136 (S1), pp.66-76. 10.1002/qj.536 . insu-00412615

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# The diurnal cycle of lower boundary-layer wind in the West African monsoon

Kassimou Abdou,<sup>a</sup> Douglas J. Parker,<sup>b*</sup> Barbara Brooks,<sup>b</sup> Norbert Kalthoff<sup>c</sup> and Thierry Lebel<sup>d</sup>

**ABSTRACT:** Measurements of lower boundary-layer winds collected from four Sonic Detection And Ranging (SODAR) systems during the African Monsoon Multidisciplinary Analysis (AMMA) are presented. The SODARs were located in a mesoscale network in the vicinity of Niamey, Niger, in the period 31 May to 17 August 2006; from this network 41 days of good measurements have been obtained from at least one of the SODARs, while there are several days in which two or more SODARs produced good simultaneous data. The average variation of the winds in the lower boundary layer is here presented, as a function of height and of time of day. The results confirm previous studies of the diurnal cycle of winds, and quantify the variation of this diurnal cycle with height at low altitudes. On many nights, a distinct nocturnal low-level jet was observed, at 200–400 m altitude. In profiles averaged over all of the sample days, the peak wind shear was in the layer below 300 m, with the strongest wind shear from 0000 to 0600 UTC. In particular, the magnitude of low-level wind shear, which is a significant hazard for aviation, is shown to be strongly dependent on time of day. Strong low-level wind shear (more than 4 m s⁻¹ per 100 m), was observed on more than 35% of days in the 0000–0300 UTC period. Copyright © 2009 Royal Meteorological Society

**KEY WORDS** nocturnal jet; wind shear; aircraft

Received 14 January 2009; Revised 16 September 2009; Accepted 7 October 2009

## 1. Introduction

Significant numbers of people live in the semi-arid geographical region of West Africa. Their livelihood is based on subsistence farming which is sensitively dependent on the rainfall. Any pragmatic agricultural planning for this region needs a thorough understanding of the climate and, in particular, the West African monsoon (WAM), which brings humid air inland in the summer months and feeds the annual rainfall. The dynamical processes involved in the WAM also control the individual rainfall events which make up the local climate: wind shear associated with the African easterly jet (AEJ), combined with a dry mid-level ‘Saharan air layer’ (SAL) allows intense, long-lived and fast-propagating squall lines to develop (e.g. Barnes and Sieckman, 1984; Parker et al., 2005a).

The diurnal cycle of lower boundary-layer winds is recognized to be a key factor in the dynamics of the WAM (Parker et al., 2005b), in common with other semi-arid regions such as Australia (Rácz and Smith, 1999). The basic diurnal cycle can be briefly summarized in the following:

* During the daytime the heat-low intensifies over the Sahara with a pressure minimum in the afternoon; in late afternoon the pressure gradient force directed into the heat-low reaches its diurnal peak. However, despite the strong pressure gradient, there are only relatively weak winds in the daytime convective boundary layer (CBL) due to turbulent mixing of the atmosphere, which balances the Coriolis force on the ageostrophic component of the wind.

* Turbulence drops rapidly when sensible heating reduces in the late afternoon, and the flow is able subsequently to respond to the heat-low pressure gradient force. With the mean pressure gradient directed northwards towards the Saharan heat-low, the low-level southerly flow intensifies overnight, and a nocturnal jet (Blackadar, 1957) may occur. The peak nocturnal jet veers (in the Southern Hemisphere it would back) due to the effect of the Coriolis force on the increasingly strong winds, in an ‘inertial oscillation’. The strength of this inertial oscillation depends on the degree of departure from ageostrophic balance around sunset; in practice this is close to the surface, where the daytime winds are very low. Therefore, the peak winds in the low-level nocturnal jet are in the lowest hundreds of metres above the ground (as observed by Lothon et al., 2008). A region of strong wind shear and stable stratification occurs below the

<footnote><sup>a</sup>Direction de la Météorologie Nationale, Niamey, Niger</footnote>

<footnote><sup>b</sup>Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds, UK</footnote>

<footnote><sup>c</sup>Institut für Meteorologie und Klimaforschung, Forschungszentrum Karlsruhe/Universität Karlsruhe, Germany</footnote>

<footnote><sup>d</sup>LTHE - IRD, Grenoble, France</footnote>

<footnote>*Correspondence to: Douglas J. Parker, Institute of Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, UK.
E-mail: d.j.parker@see.leeds.ac.uk</footnote>
nocturnal jet, meaning that there can often be no signal of the nocturnal jet in the surface wind data (although surface turbulence measurements may reveal the nocturnal jet: Lothon *et al.*, 2008). Overnight, the zone of peak low-level winds moves northward (Parker *et al.*, 2005b), associated with the northward advection of the thermodynamic gradient which drives this circulation. The peak winds in the inertial oscillation, in the Sahel, will be in the hours around sunrise, meaning that the peak of the low-level winds is out of phase (in terms of the diurnal cycle) with the pressure gradient which drives them.

* After sunrise, a CBL grows through the nocturnal inversion and can mix momentum from the nocturnal jet down to the ground, leading to a diurnal peak in the surface winds. This process has been observed by May (1995), Parker *et al.* (2005b) and Washington *et al.* (2006). By day the low-level humidity falls, as dry air from the SAL above is mixed down in the developing convective boundary layer (Hamilton *et al.*, 1945; Parker *et al.*, 2005b; Lothon *et al.*, 2008; Pospichal *et al.*, 2009).

The nocturnal meridional flow brings moist air northward, and is the main source of moisture during the pre-onset period, when convective systems and squall lines are still scarce (Lothon *et al.*, 2008). Couvreux *et al.* (2009) have shown that later, during the monsoon season, there may still be periodic northward excursions of the monsoon flux into the Sahara, driven by variability in the Saharan heat-low, and with a strong nocturnal flow. At higher levels, around 700 hPa, there is a dry return flow from the Sahara.

The leading edge of the low-level monsoon flow is known as the intertropical front (ITF; sometimes also known as the intertropical discontinuity or ITD), and this feature also shows a marked diurnal cycle (Hamilton *et al.*, 1945). Flamant *et al.* (2007), Pospichal and Crewell (2007), Lothon *et al.* (2008), Bou Karam *et al.* (2008) and Pospichal *et al.* (2009) have presented observations of the winds in the ITF region at different latitudes and times of day. Bou Karam *et al.* (2008) showed how the nocturnal flow just behind (to the south of) the ITF has the dynamics of a gravity current, and through strong turbulent mixing can bring high winds down to surface levels, with high surface wind shear and a strong potential to lift mineral dust. This contrasts with the nocturnal jet further south of the ITF, which is decoupled from the surface flow by stability, and therefore has less potential to lift dust.

Parker *et al.* (2005b) also considered the seasonal cycle of the lower boundary layer winds in the Sahel, noting that the coherence of the diurnal cycle becomes weaker during the rainy monsoon season, from late June approximately to September. It is likely that the high winds induced by intermittent convective storms, and the local circulations induced by soil moisture (Taylor *et al.*, 2007) add a significant ‘noise’ to the simple diurnal cycle outlined above.

A number of dynamical aspects of the WAM are critical to aviation in the Sahel. Apart from the intense winds due to squall lines, the occurrence of a nocturnal low-level jet can lead to significant wind shear. There seems to be some divergence of methods for quantifying and analysing the low-level wind-shear hazard for aircraft, probably due to the different meteorological conditions which can generate this phenomenon around the world (for instance intense synoptic storms, nocturnal jets, or convective squalls). The Met Office Forecasters’ Reference Book (Meteorological Office, 1993) provides examples of a number of datasets showing observed wind shears, and their climatological frequencies, under different stability conditions, and typically quotes the wind shear as a ratio $V_h/V_0$, of the wind speed at height $h$ to the wind speed at the ground ($V_0$). This ratio is probably more usefully applied to cases of wind shear due to high geostrophic wind occurring in midlatitudes, and we might expect the ratio to be less helpful in nocturnal jet examples, where the low-level wind speed can be very low and dynamically decoupled from the nocturnal jet itself.

In practice, forecasters in Niamey (close to the SODAR sites) provide to pilots a warning of wind shear if the 600 m winds (from the local observational balloon sounding) exceed 30 knots (around $15 \text{ m s}^{-1}$). If, from the profiles shown subsequently, we assume that most of this wind shear will be in the lowest 300 m, this criterion corresponds to a mean wind shear of around $5 \text{ m s}^{-1}(100 \text{ m})^{-1}$ (or $5 \times 10^{-2} \text{ s}^{-1}$) over the lowest 300 m (or a weaker mean wind shear over the full 600 m). The Forecasters’ Reference Book (page 29) also discusses the nocturnal jet and cites an example of wind speeds of 50 knots at 1300–1600 ft (approximately $25 \text{ m s}^{-1}$ at 400–490 m) as representing ‘very strong low-level shear, which presents a hazard to aircraft on the final stages of an approach to landing’. This example also corresponds to a mean wind shear of around $5–6 \text{ m s}^{-1}(100 \text{ m})^{-1}$, assuming low surface wind speed. Similarly, in five case-studies from Dallas-Fort Worth International Airport, Kaplan *et al.* (2000) showed that the average peak wind shear below the nocturnal jet was $2.9 \text{ m s}^{-1}(100 \text{ m})^{-1}$.

Strong low-level winds can lift significant amounts of dust and reduce visibility; this process seems to be particularly significant in the first hours after sunrise (Washington *et al.*, 2006), when the momentum associated with such a jet can be mixed down to the surface by a growing CBL. The reduction in visibility is another important hazard for aviation. The lifting of dust is also an important process in the export of dust aerosols from West Africa into the global climate system, and the representation of this lifting in models requires suitable boundary layer schemes, with careful attention to resolution (Todd *et al.*, 2008).

The African Monsoon Multidisciplinary Analysis (AMMA) has been launched to get a deeper insight into the many coupled physical and environmental systems which determine the WAM. A major aspect of AMMA has been to combine a huge number of ground-based, maritime, airborne and satellite measurements
(Redelsperger *et al.*, 2006; Lebel *et al.*, 2009). As part of this observational programme, four SODAR (Sonic Detection And Ranging) systems were deployed in the Niamey region, in a small network. This paper describes the average wind patterns and their diurnal cycle, as observed by this network of SODARs. Very few measurements of this diurnal cycle have ever been made in this climatic zone and the results will be important for aviation and for the evaluation of weather and climate models.

## 2. Site description, measurement overview and data acquisition

The four sites used in this study are all within the Niamey area, within a radius of around 50 km, forming part of the AMMA mesoscale site around Niamey (Figure 1 and Table I; see also Lebel *et al.* (2009)). The sites lie in a tropical climate with a dry season between October and April and a wet season between May and September. Air temperatures rarely drop below 20°C; the extreme temperature range is 15 to 45°C. The measurement site of Alkama is surrounded by millet fields, the site of Gourou Goussa is rocky fields, while the ground at Koure and Banizoumbou is largely sandy. The topography of the area is very gentle, with no major hills in the vicinity of the SODAR network – SODAR site elevations are given in Table I. The instruments were deployed from 31 May to 17 August 2006. Note that all times are quoted as UTC: at longitudes of less than 2°W there is only a difference of a few minutes between UTC and local solar time. Extreme operating conditions imposed

by the deployment on the SODAR systems caused a wide variety of technical problems with the result that the network was never fully operational with all four stations running simultaneously (see Table II). Despite these problems, this network produced 41 days of good measurements from at least one of the SODARs, and there are several days in which two or more SODARs operated simultaneously.

The days of effective observations with the SODARs were split into two groups: a period of 7 days of good measurements in the period 31 May to 7 June 2006, prior to the official monsoon onset date for 2006 (Janicot *et al.*, 2008), and a period of 34 days of good measurements in the period 8 July to 16 August 2006, when the monsoon circulation was well-established (Table II). In each of these periods, the ITF lay to the north of the SODAR sites (Figure 1), and the monsoon flow was measured throughout. There was no evidence, in the early period, when the ITF was only 100–200 km north of the SODARs, of the ITF dynamics directly causing strong surface winds through gravity current processes, as described by Bou Karam *et al.* (2008).

SODAR systems are capable of measuring the wind speed profile and turbulence characteristics (standard deviation of the vertical wind speed, $\sigma_w$, and backscatter intensity) in the lower atmosphere. The turbulence data can be used to detect the boundary-layer height (Beyrich, 1997; Seibert *et al.*, 2000); however, analysis and presentation of the boundary-layer turbulence structure is outside the remit of this particular paper and will be reserved for future work. The SODARs deployed were Scintec MFAS64. This phased array system consists of 64 transducers and 64 receiver antennae in a monostatic configuration, that is, the same antenna is used for emission and reception of sound. The MFAS64 generates different beam angles during emission and reception by phase-delayed driving and sensing, respectively, of the rows or columns of an array of acoustic transducers. With the SODAR, the spectra are determined by applying a Fast Fourier Transform to the acoustic signals received from the different directions. The systems were operated in a multi-frequency mode. In this mode, sequences composed of pulses of ten frequencies in the range from 1650 to 2750 Hz are emitted and the backscattered waves of all frequencies are received simultaneously. Multi-frequency operation significantly increases the signal-to-noise ratio, since more acoustic power can be emitted into the atmosphere without increasing the pulse length per frequency, i.e. without reducing the vertical resolution. This procedure is repeated in the vertical and at an angle of 29° to the north, east, south and west. Within a single emitted sequence, pulses of different frequencies or direction have different lengths. The shortest possible pulse length corresponds to a layer thickness of 10 m during data evaluation. The operating parameters used during the deployment were set by the manufacturer for optimum range of retrieval.

The SODARs were powered by solar panels, recharging a battery pack. As the batteries aged during the measuring period, they held less charge and often would not

<figure><img src="image_3.png" /><figcaption>Figure 1. Plots of the mean 925 hPa, 0000 UTC winds from the UK Met Office Africa-LAM analyses, averaged over the periods (a) 5–8 June and (b) 8 July–16 August 2006, during which the SODARs were operating. The SODAR sites are indicated by triangles. The location of Niamey (at which the UHF wind profiler and radiosonde data analysed by Lothon *et al.* (2008) were collected) is shown by a square. In each panel, the intertropical front (ITF) would be identified as the zone of confluence of the southwesterly and northerly winds.</figcaption></figure>
<table><caption>Table I. SODAR location details from GPS.</caption><thead><tr><th>Site</th><th>Latitude N in degrees</th><th>Longitude E in degrees</th><th>Elevation (m)</th></tr></thead><tbody><tr><td>Al Kama (Al-K)</td><td>13.8208</td><td>2.9546</td><td>206</td></tr><tr><td>Banizoumbou (B)</td><td>13.5232</td><td>2.6289</td><td>232</td></tr><tr><td>Gourou Goussa (G-G)</td><td>13.8361</td><td>2.0379</td><td>237</td></tr><tr><td>Koure Sud (K-S)</td><td>13.2040</td><td>2.6151</td><td>235</td></tr></tbody></table>

<table><caption>Table II. Data availability from the four SODAR sites.</caption><thead><tr><th></th><th>B</th><th>G-G</th><th>Al-K</th><th>K-S</th></tr></thead><tbody><tr><td>27-May-06</td><td>1</td><td></td><td></td><td></td></tr><tr><td>28-May-06</td><td>1</td><td></td><td></td><td></td></tr><tr><td>29-May-06</td><td></td><td></td><td></td><td></td></tr><tr><td>30-May-06</td><td></td><td></td><td></td><td></td></tr><tr><td>31-May-06</td><td></td><td></td><td>3</td><td></td></tr><tr><td>01-Jun-06</td><td></td><td>1</td><td>3</td><td></td></tr><tr><td>02-Jun-06</td><td>1</td><td>3</td><td>1</td><td></td></tr><tr><td>03-Jun-06</td><td></td><td>3</td><td></td><td></td></tr><tr><td>04-Jun-06</td><td></td><td>2</td><td></td><td></td></tr><tr><td>05-Jun-06</td><td></td><td></td><td></td><td></td></tr><tr><td>06-Jun-06</td><td></td><td>2</td><td></td><td></td></tr><tr><td>07-Jun-06</td><td></td><td>1</td><td>3</td><td></td></tr><tr><td>08-Jun-06</td><td></td><td></td><td></td><td></td></tr><tr><td>07-Jul-06</td><td></td><td></td><td></td><td></td></tr><tr><td>08-Jul-06</td><td>2</td><td></td><td></td><td></td></tr><tr><td>09-Jul-06</td><td></td><td></td><td></td><td></td></tr><tr><td>10-Jul-06</td><td>3</td><td></td><td>2</td><td></td></tr><tr><td>11-Jul-06</td><td>3</td><td></td><td>3</td><td></td></tr><tr><td>12-Jul-06</td><td>3</td><td></td><td>3</td><td></td></tr><tr><td>13-Jul-06</td><td>2</td><td></td><td>3</td><td>3</td></tr><tr><td>14-Jul-06</td><td>2</td><td></td><td>1</td><td>3</td></tr><tr><td>15-Jul-06</td><td>2</td><td></td><td></td><td>3</td></tr><tr><td>16-Jul-06</td><td></td><td></td><td></td><td>3</td></tr><tr><td>17-Jul-06</td><td>2</td><td></td><td></td><td>3</td></tr><tr><td>18-Jul-06</td><td>2</td><td></td><td></td><td>3</td></tr><tr><td>19-Jul-06</td><td>2</td><td></td><td></td><td>2*</td></tr><tr><td>20-Jul-06</td><td>2</td><td></td><td></td><td>2*</td></tr><tr><td>21-Jul-06</td><td>2</td><td></td><td></td><td>3</td></tr><tr><td>22-Jul-06</td><td>2</td><td></td><td></td><td>2*</td></tr><tr><td>23-Jul-06</td><td>2</td><td></td><td></td><td>2*</td></tr><tr><td>24-Jul-06</td><td>2</td><td></td><td></td><td>3</td></tr><tr><td>25-Jul-06</td><td>2</td><td></td><td></td><td>3</td></tr><tr><td>26-Jul-06</td><td>2</td><td></td><td></td><td>2</td></tr><tr><td>27-Jul-06</td><td>2</td><td></td><td></td><td></td></tr><tr><td>28-Jul-06</td><td>2</td><td></td><td></td><td></td></tr><tr><td>29-Jul-06</td><td>2</td><td></td><td></td><td></td></tr><tr><td>30-Jul-06</td><td>2</td><td></td><td></td><td></td></tr><tr><td>31-Jul-06</td><td>1</td><td></td><td></td><td></td></tr><tr><td>01-Aug-06</td><td>2</td><td></td><td></td><td></td></tr><tr><td>02-Aug-06</td><td></td><td></td><td></td><td></td></tr><tr><td>03-Aug-06</td><td>2</td><td></td><td></td><td></td></tr><tr><td>04-Aug-06</td><td>2</td><td></td><td></td><td></td></tr><tr><td>05-Aug-06</td><td>2</td><td></td><td></td><td></td></tr><tr><td>06-Aug-06</td><td>2</td><td></td><td></td><td></td></tr></tbody></table>

<table><caption>Table II. *continued*</caption><tr><td>07-Aug-06</td><td>2</td></tr><tr><td>08-Aug-06</td><td>2</td></tr><tr><td>09-Aug-06</td><td>2</td></tr><tr><td>10-Aug-06</td><td>2</td></tr><tr><td>11-Aug-06</td><td></td></tr><tr><td>12-Aug-06</td><td>2</td></tr><tr><td>13-Aug-06</td><td>2</td></tr><tr><td>14-Aug-06</td><td>1</td></tr><tr><td>15-Aug-06</td><td>2</td></tr><tr><td>16-Aug-06</td><td>2</td></tr><tr><td>17-Aug-06</td><td>1</td></tr></table>

Coded as: 'Sparse data – less than 12 hours' (1); 'Good data but some gaps (typically missing data from late evening to around 0700 UTC)' (2); and 'Continuous data, near 100% coverage' (3). Those nights where missing data are likely to have a meteorological cause (rainfall) are marked 2*. The site names are abbreviated as in Table I. Shading indicates a period of around 1 month in which no data were collected.

sustain the measurements throughout the night. In such instances, observations would recommence after sunrise. Similarly, cloudy or overcast days, when less charge was fed to the batteries, provoked loss of observations overnight. The SODARs did not work in raining conditions, so no data are available during squall-line events. However, the data will be useful for the study of the typical wind fields immediately preceding a squall line.

The analysis described in this paper is based on the archive of 15-minute averages of the wind fields, at 10 m vertical intervals, with the lowest level at 30 m above the ground and the highest at 600 m. Note that although the manufacturer's upper limit for the MFAS64 is quoted as 1000 m, operationally the upper limit is determined by atmospheric attenuation, boundary-layer height, and background noise pollution. In this deployment the operational upper limit was found to never exceed 600 m. In addition, data loss occurs due to scattering of the signal from hydrometeors and during periods of very strong winds when the signal is transported away from the receiver. SODAR data can be considered to provide better time-sampling than the radiosondes launched at Niamey (6-hourly in 2006, with intensive phases of 3-hourly sondes – see Parker *et al.*, 2008), and give a better vertical resolution than UHF wind-profilers close to the ground (Lothon *et al.*, 2008).

Hourly-averaged data have been computed by averaging over all sites, recognising that each site has many gaps in the record. No attempt has been made to remove
days on which squall lines occurred; it should be remem-
bered that no data are collected during rainfall, when the
most intense winds associated with squall lines occur,
and therefore to some extent squall lines are automati-
cally filtered out. However, the trailing mesoscale region
behind a squall line does influence the winds for many
hours later (e.g. Chalon *et al.*, 1988). The results repre-
sent averages of wind data collected away from periods
of rainfall. In a similar vein, it should be noted that the
diurnal cycle of mean winds is not the same as the diur-
nal cycle of squalls. Squall lines have their own distinct
diurnal cycle of occurrence (e.g. Duvel, 1989). Although
there is some difference in the mean winds between the
two observing periods highlighted in Figure 1, we have
combined these periods for the averaging performed here,
since the earlier period is relatively short.

As an illustration of the data availability and quality,
Figures 2 and 3 show the mean (over the four sites)
derived wind speed and direction in the lower 600 m
of the atmosphere for a period between 10 and 27 July
2006. These profiles give an impression of the level of
variability from day to day in the data, and the general
features are representative of the mean wind profiles
obtained over the entire deployment.

The data from each SODAR consist of sets of 15-
minute averaged winds. Figures 2 and 3, and some
subsequent figures, show mean winds averaged over
the many 15-minute samples obtained from a number
of SODARs, and over a number of days. Day-to-day
variability, and differences between sites, leads to a
distribution of these 15-minute mean winds at each height
and time of day, and this leads to some uncertainty in our
estimate of the average over the sample days. Therefore,
in order to measure the confidence of the graphs, standard
errors were calculated for each time of day and each
level, as σ/√n, where σ is the standard deviation of the
sample of 15-minute mean winds, and n is the size of this
sample. Note that the standard deviation of the turbulent
motions in each 15-minute sample is not used here. For
clarity of presentation the standard errors in the data are
not plotted in the following figures, but typical standard
errors are less than 1 m s⁻¹. Figure 4 also shows the
number of available data-points, n, at each hour of the
day, used to compute the means; recall that these means
represent an average over a number of days and a number
of SODARs operational at that time (never more than
three). Standard errors increase as the data samples get
smaller, at night (due to power loss on some nights) and
at higher altitudes due to signal attenuation; for instance,
at 500 m altitude the standard error on mean wind speeds
is less than 2 m s⁻¹ at night falling to less than 1 m s⁻¹
during the day.

**3. The diurnal cycle of winds**

Figures 2 and 3 have already been used to show the
typical evolution of the mean wind speed and direction
over the four instruments; these data illustrate some of
the features described in section 1, and provide novel

measurements of the near-surface flows. Hereafter, we
refer to a given night by the date on which that night
commenced. The occurrence of a nocturnal low-level
jet maximum can be observed to occur on a number
of occasions between 200 m and 400 m (the nights
beginning 9, 11, 13, 14, 15, 16, 17, 18, 20, 21, 22, 23, 24
July). On other nights, the winds increase monotonically
from the surface up to the upper measurement level
(e.g. nights beginning 10 and 12 July). Close to the
surface, maximum wind speeds often occur between
0700 and 1000 UTC (e.g. 7.4 m s⁻¹ at 0930 UTC at
30 m altitude at the Banizoumbou site on the morning
of 10 July), while afternoon winds are relatively light
(less than 3 m s⁻¹ on the afternoon of 10 July at
30 m at Banizoumbou) and variable, before the low-level
wind speeds begin to increase again after sunset. There
are isolated occasions with significant low-level winds,
greater than 4 m s⁻¹ at 30 m altitude overnight (11,
14, 16, 17, 24 July). Throughout this period, the wind
direction is predominantly westerly (red, orange, yellow
colours in Figure 3). On some nights (e.g. 12, 14, 20 July)
there is evidence for a clockwise rotation of the wind
vector overnight, but this is not seen every night (e.g. 16
July). Occasions of winds with a significant easterly or
northeasterly direction, notably 10, 14, 17, 22, 26 July,
were associated with deep convective events, as observed
in satellite imagery and ground observations (not shown).
In contrast, the easterly winds at 500–600 m altitude on
25 July were associated with the passage of the northerly
sector of a synoptic African Easterly Wave (described by
Cuesta et al., 2009).

Figure 5 shows the variation of (a) horizontal wind speed, (b) direction, (c) zonal, and (d) meridional components with time of day, averaged across all SODAR stations for the entire study period, according to altitude. The graphs show features which result from the differences in heating and turbulence throughout the day.

Heating at the surface during daylight hours increases
boundary-layer turbulence, leading to reduced variations
in the horizontal wind speeds with height, and mean
wind speeds decreasing during the day (Figure 5(a),
1000–1700 UTC). At night, after 1900 UTC, dry convec-
tion and turbulence decrease and the wind speed accel-
erates at all levels (Figure 5(a)). The maximum daily
mean wind speed at all of the levels above 100 m occurs
between 0400 and 0700 UTC. This is consistent with
the UHF wind profiler results of Lothon *et al.* (2008),
obtained less than 60 km from the SODAR sites for
the longer period of April 2006 to January 2007, which
showed the maximum to occur on average at 0500 UTC,
but most commonly around 0600 or 0700 UTC. At the
lowest (30 m) level, the highest mean wind speed occurs
at 1000–1200 UTC, as in the observations described
by May (1995), Parker *et al.* (2005b) and Washington
*et al.* (2006). In particular, the reduction in the vertical
gradient of wind speed, with high-level winds dropping
as low-level winds accelerate between 0700 and 1000
UTC, is consistent with the effects of turbulent mix-
ing of momentum as the boundary layer grows at this
<figure><img src="image_4.png" /><figcaption>Figure 2. Time-height plot of wind speed for the period 10 July to 27 July 2006. Data are averaged over all four sites.</figcaption></figure>

time of day. At 400 m altitude, the mean wind direction turns overnight from south-southwest around 2100 UTC to west-southwest by 0600 UTC (Figure 5(b)). The greatest spread of the wind direction with height occurs overnight, when the stable layers of the lower boundary layer are decoupled. At 0600 UTC the wind veers by nearly 40° over the 30 m to 300 m layer, before backing again by around 15° up to 600 m.

The average zonal component of winds (u) reaches a minimum in late afternoon and early evening at all levels, but remains positive (westerly) on average (Figure 5(c)). Overnight, the zonal component increases markedly, at those levels above 100 m. At 100 m and below, an increase between 2100 UTC and 0300 UTC is followed by a near-constant mean zonal component until sunrise. After 0700 UTC the low-level zonal winds increase and the higher-level (above 100 m) winds decrease rapidly. A peak in low-level zonal winds occurs at 1000 UTC. By 1200 UTC, the zonal wind shear is very low; less than 1 m s⁻¹ over this range of levels.

The average meridional (v) component of the winds indicates a minimum in the mid-afternoon at upper levels

(above 100 m) and increases again towards the night (Figure 5(d)), while at lower levels the v-component reveals only a weaker diurnal variation. At all levels the meridional component increases significantly between 1900 and 2200 UTC, but decreases again before sunrise at around 0600 UTC. Comparing Figures 5(c) and (d), the meridional component of the average wind begins to increase after around 1400 UTC, and certainly by 1800 UTC, reaching a maximum around 2200–0300 UTC (Figure 5(c)), while the average zonal component begins to increase later in the day, after 1900–2000 UTC, reaching a maximum around sunrise (Figure 5(c)). This shift in the timing of the acceleration of the two components of the low-level winds is consistent with an initial northward acceleration down the large-scale pressure gradient followed by clockwise turning of the wind vector overnight by the Coriolis force, associated with the behaviour of the nocturnal jet (Blackadar, 1957), and previously identified by Parker *et al.* (2005b) in surface data from the Niamey region.

Figure 6(a) and (b) show the average vertical profile of the wind speed and direction at the main synoptic
<figure><img src="image_5.png" /><figcaption>Figure 3. Time-height plot of wind direction for the same period as Figure 2. Data are averaged over all four sites.</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>Figure 4. The number of data-points used to compute averages from the SODAR data. The diurnal signal is due to loss of power overnight on some occasions.</figcaption></figure>

hours. Consistent with Figure 5(a), at 1200 UTC there
are the strongest 30 m average wind speeds, but the

weakest wind shear over the 30 m to 600 m layer. The
weakest average winds occur at 1800 UTC at all levels
below 480 m. By 0000 UTC a strong vertical gradient
in wind speed has developed between 30 m and 300 m,
with a small peak in mean wind speed at this level. The
highest mean wind speeds at all levels were measured at
0600 UTC; the low-level gradient in wind speed, below
300 m, appears to be equally strong at 0000 UTC and
0600 UTC, but the later maximum in wind speed is
more than 10 m s⁻¹ at 350 m, and has veered some 13°
(Figure 6(b)). Other observations have shown that the
peak nocturnal low-level jet was most commonly found
at 350–450 m altitude (Lothon *et al.*, 2008, from a longer
time-period including the dry-season months) or even at
600–700 m altitude (Kohler *et al.*, 2009). Here the peak is
much less distinct than that found by Lothon *et al.* (2008)
and Kohler *et al.* (2009) in radiosonde and UHF wind
profiler data. It should be noted that the minimum in wind
speed observed by Lothon *et al.* (2008) was typically at
an altitude higher than the 600 m limit of the SODAR
data, typically 1.7 km in their Fig. 6 (mean June 2006
radiosonde profiles) and 1.2–1.6 km in their Fig. 10
<figure><img src="image_7.png" /><figcaption>Figure 5. The mean (a) speed (m s⁻¹), (b) direction (°), (c) zonal component and (d) meridional component of the wind (m s⁻¹), as a function of time of day (UTC; plotted at the end time of each hour of averaging), for different heights as labelled. Data are averaged over all days and all sites. Note that different wind scales are used in (a), (c) and (d).</figcaption></figure>

(April 2006 to January 2007 UHF data), and consistent with the upper limit of monsoonal flow observed just after sunrise by Bou Karam *et al.* (2008), so the lack of a very distinct peak in the 0000 and 0600 UTC data presented in Figure 6(a) is not inconsistent with these previous studies. The peak in mean wind speed around 300–350 m seen in Figure 6(a) is generated from the averaging of a number of days with a more distinct maximum around this level, and a number of days where the winds increase monotonically with height, as seen in Figure 2.

Figure 6(b) confirms the rotation of the wind vector during the diurnal cycle. At 1800 UTC, the wind direction is almost constant with height, around 212°, from 100 m to 600 m. Overnight, the wind direction is altered by the Coriolis force causing a veering of the winds. The profile of mean zonal wind component (Figure 6(c)) is approximately monotonically increasing with height up to 300 m, and reasonably constant above there at all times, with maximum mean shear at 0000 and 0600 UTC in the 30–200 m layer. The meridional component (Figure 6(d)) shows a more complex profile with a distinct maximum around 180–300 m at 0000 UTC and 200–360 m at 0600

UTC. The meridional component diminishes in strength between 0000 UTC and 0600 UTC, consistent with the turning of the nocturnal winds by the Coriolis effect. This effect is also seen in the hodograph of Figure 7 which describes the veering of the winds with time at 100 m and 600 m. Due to the larger values of the wind speed at 600 m, and the decoupling of this higher level from the stable surface layer at night, the veering is more marked there.

4. Statistics of wind shear

In addition to the mean diurnal cycle and profiles described in section 3, it is informative to inspect the wind shear in more detail, and its variability from day to day. As noted in section 1, the wind shear in the lowest hundreds of metres represents a significant hazard for aircraft at take-off and landing, and can be difficult to observe and predict.

Wind shear has been evaluated as the magnitude of the vector change in the 15-minute winds between two selected levels. For each 6-hour period during the
<figure><img src="image_8.png" /><figcaption>Figure 6. Mean (a) speed (m s⁻¹), (b) direction (°), (c) zonal component and (d) meridional component of winds (m s⁻¹) as a function of height at each main synoptic hour, averaged over all sites and all available days. Note that different wind scales are used in (a), (c) and (d).</figcaption></figure>

<figure><img src="image_9.png" /><figcaption>Figure 7. Hodograph of mean winds at altitudes of 100 m (dotted line and diamonds) and 600 m (solid line and triangles), averaged over all sites at times 0000, 0600, 1200 and 1800 UTC (labelled).</figcaption></figure>

observational programme, the maximum 15-minute mean wind shear of all the available SODARs has been

computed. The results for wind shear between 30 m and 300 m (with these levels chosen by reference to Figure 6(a)–(d)) are shown in Figure 8 in terms of frequency of occurrence during the study period.

Low wind shear, with no 15-minute mean value greater than 0–2 m s⁻¹ per 100 m, occurs quite commonly during the day (on more than 50% of days during 0900–1800 UTC, the wind shear is in this category) but occurs quite rarely overnight. Higher wind shear, greater than 4 m s⁻¹ per 100 m, is most common in the period 1800 to 0900 UTC (with a peak of more than 35% of occasions in the 0000–0300 UTC period), and least common in the afternoon, 1200–1500 UTC. Following the discussion in section 1, these higher wind shears of more than 4 m s⁻¹ per 100 m are of concern to aviation, and would normally lead to the issue of a warning to pilots. The highest wind shears observed here, greater than 6 m s⁻¹ per 100 m, represent a small sample of events (one or two events in each time category) and therefore lack statistical significance. The highest wind shear, of 8.5 m s⁻¹ per 100 m (23 m s⁻¹ across the 30–300 m layer) occurred
<figure><img src="image_10.png" /><figcaption>Figure 8. Frequency distribution of wind shear as a function of time of day, for the study period. The central category, of 4–6 m s⁻¹(100 m)⁻¹, is the one which would normally require the issue of a warning of high wind shear to pilots (see text in section 1).</figcaption></figure>

from 0900 to 0915 UTC on 1 June 2006, and, from inspection of satellite imagery and surface observations, does not seem to have been associated with a major cumulonimbus system.

**5. Conclusion and outlook**

This paper has described the diurnal cycle of lower boundary-layer winds in the Sahel, as measured in the Niamey region during the summer monsoon period of 2006. These low-level winds are very important in the transport of water vapour through the monsoon system, in the lifting of mineral dust and in the occurrence of wind shear, which is hazardous for aircraft. Despite their significance, measurements of winds at low altitudes (from 30 m above the ground) have been rare in this part of the world and particularly in the night-time hours.

The results qualitatively agree with other studies of the diurnal cycle in this region (e.g. Parker *et al.*, 2005b; Washington *et al.*, 2006; Pospichal *et al.*, 2007; Lothon *et al.*, 2008) and elsewhere (e.g. May, 1995). Here we have quantified the amplitude of the diurnal cycle of winds in this part of the world, and provide unique measurements at low altitudes, down to 30 m. On many nights, a distinct nocturnal low-level jet was observed, at 200–400 m altitude. In the averaged profiles, the peak wind shear was in the layer below 300 m, with the strongest wind shear from 0000 to 0600 UTC.

One of the important effects of the diurnal cycle in low-level winds described here is to modulate the lifting of mineral dust. Under given large-scale synoptic conditions, the low-level winds have a strong diurnal cycle which implies a similar diurnal cycle in dust emission from the surface. Typically, dust lifting is parametrized as a function of 10 m winds, and the low-level (30 m) data available from the SODARs is potentially an excellent surrogate for this field. At the same time, dust may be advected in from long distances upstream, so the local

diurnal cycle of winds is only one factor controlling dust loadings at a given location. It will be very interesting to use the SODAR data in future studies of dust uplift, in relation to measures of dust loadings, and to make use of the turbulence diagnostics from the SODARs and other instruments such as the UHF radar.

The data shown in Figure 2 illustrate the coherence of the diurnal cycle of winds in this region, but also show the interesting fine structure of the winds, in time and height. For example, there are times when we see short-lived events of separate jet maxima at night, for instance around on the night of 11 July. Further investigation of such fine structure, for example on a case-study basis, would be very interesting.

The frequency of strong wind shear, of concern to aircraft taking off and landing, has been shown in Figure 8. A diurnal cycle in frequency of intense wind shear (more than 4 m s⁻¹ per 100 m), has been observed, with such intense wind shear being recorded on more than 35% of days in the 0000–0300 UTC period. Sophisticated predictive models of the aviation hazard resulting from low-level jets are being developed on the basis of numerical weather prediction models, making use of the model wind shear as well as the model turbulence (for instance turbulent kinetic energy and eddy dispersion rate: Kaplan *et al.*, 2000). It would be interesting in future to explore the turbulence estimates which could be obtained from the SODAR data, in the context of aviation security, and to evaluate models against the SODAR data in this context.

The data presented here should be of interest to many groups studying the West African monsoon, including aviation forecasters, modellers wishing to correctly represent lower boundary-layer winds, and those for whom wind fields are a key input (for instance in the hydrological cycle, or in the lifting of mineral dust). There are many possible further uses of the data from these SODARs, notably to analyse the variations between sites
on the network, to examine specific events such as squall lines, and to more closely inspect the patterns of temporal variability. Further work is currently detailing the turbulence and boundary-layer structures by making use of the backscatter signal properties in the SODAR data.

## Acknowledgements

We wish to thank the DMN of Niger, in particular Mr Katiellou, and the IRD in Niamey, notably Luc Desbois, for their assistance and support. This work was funded in the United Kingdom by NERC (NE/B505538/1). Kassimou Abdou also received assistance from the University of Leeds for a study visit in 2007. Thanks to Sean Milton (of the Met Office) and Nick Dixon for the data and plotting in Figure 1. We thank the two reviewers, Frederique Saïd and Diana Bou Karam, for their thorough and perceptive comments which have greatly improved the paper. Based on a French initiative, AMMA was built by an international scientific group and is currently funded by a large number of agencies, especially from France, United Kingdom, USA and Africa. It has been the beneficiary of a major financial contribution from the European Community's Sixth Framework Research Programme. Detailed information on scientific coordination and funding is available on the AMMA International web site, http://www.amma-international.org/.

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