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Using three daily measurements of wind speed and direction from synoptic weather station data in SE Niger, we examined the diurnal, seasonal and interannual time-scale of Sahel climate variability between 1950 and 1992. The seasonal wind patterns are closely related to the temperatures and West African monsoon dynamics. The transitions between the two seasons are marked by an important increase in calms (wind speed <0.5 m.s-16 ). Such variations are related to meridional shifts of the Inter Tropical Discontinuity (ITD) and Inter Tropical Convergence Zone (ITCZ). Interannual fluctuations of annual wind speeds are consistent with Sahel rainfall variability. Dry years, such as in 1969-1973 and 1983-1986 periods, are associated with negative anomalies in wind speeds mainly due to an increase in calms and dry conditions. Nevertheless, we note several differences: the first period is associated with a yearly increase in the annual mean speed, while the second is associated with a decrease. Differences could be related to changes in atmospheric circulation, especially regarding the strength and latitudinal position of Tropical and African Easterly jets.
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Can daily meteorological measurement of near-surface wind detect
climate changes in the Sahel (SE Niger, 1950e1992)?
Bouba Hassane
, Alain Durand
, Zibo Garba
, Bastien Dieppois
, David Sebag
Jean-Louis Rajot
, Arona Diedhiou
, Benjamin Ngounou Ngatcha
, Abdoulkarim Traore
Dpt. de G
eologie, Universit
e Abdou Moumouni, BP 10662, Niamey, Niger
Laboratoire Morphodynamique Continentale et C^
ere (M2C), UMR CNRS 6143, Universit
e de Rouen, 76821, Mont Saint Aignan Cedex, France
Laboratoire HydroSciences Montpellier (HSM), Universit
e de Montpellier 2, IRD, France
Laboratoire BIOEMCO, UMR-IRD 211 &LISA, UMR CNRS 7583, Universit
e de Paris-Est Cr
eteil, 94010, Cr
eteil, France
LTHE/IRD, Universit
e de Grenoble, BP 53, 38041, Grenoble Cedex 9, France
Dpt. des Sciences de la Terre, Universit
e de Ngaound
e, BP 454, Ngaound
e, Cameroun
Direction de la M
eorologie Nationale (DMN), BP 218, Niamey, Niger
article info
Article history:
Received 23 November 2013
Received in revised form
25 May 2015
Accepted 27 July 2015
Available online xxx
Central Sahel
Climate variability
Wind speed and direction
Using three daily measurements of wind speed and direction from synoptic weather station data in SE
Niger, we examined the diurnal, seasonal and interannual time-scale of Sahel climate variability between
1950 and 1992. The seasonal wind patterns are closely related to the temperatures and West African
monsoon dynamics. The transitions between the two seasons are marked by an important increase in
calms (wind speed <0.5 m s
). Such variations are related to meridional shifts of the Inter Tropical
Discontinuity (ITD) and Inter Tropical Convergence Zone (ITCZ). Interannual uctuations of annual wind
speeds are consistent with Sahel rainfall variability. Dry years, such as in 1969e1973 and 1983e1986
periods, are associated with negative anomalies in wind speeds mainly due to an increase in calms and
dry conditions. Nevertheless, we note several differences: the rst period is associated with a yearly
increase in the annual mean speed, while the second is associated with a decrease. Differences could be
related to changes in atmospheric circulation, especially regarding the strength and latitudinal position
of Tropical and African Easterly jets.
©2015 Published by Elsevier Ltd.
1. Introduction
During the 20th century, studies on climate variability in the
Sahel are most often based on interannual or decadal uctuations
of rainfall, which are the most important from both an economic
and social point of view. All studies have indicated that this region
experienced a dramatic change a series of unprecedented droughts
since the end of the 1960s (e.g., Janicot and Fontaine, 1993;
Nicholson, 2001; L'Hote et al., 2002). These droughts led to a
disruption in balance of the fragile Sahelian ecosystem (UNEP,
1992). In particular, we have witnessed a remobilization of dunes
(e.g., Courrel and Chamard, 1987; Tidjani, 2008) and an increase in
dust suspension in the atmosphere (Middleton, 1985), which
reduced horizontal visibility at the local level (e.g., Ozer, 2000;
Anuforom, 2007).
Rainfall over this region appears to be linked to the timing and
amplitude of the Inter-Tropical Convergence Zone (ITCZ) shifting, as
well as the intensity of the atmospheric ows (e.g., Nicholson,
2008); however, rainfall is not representative of the permanent
local conditions because it is only observed for a few days during
the rainy season (i.e., when the ITCZ is in its northernmost posi-
tion). In contrast, windless days are unusual (Leroux, 1983). Near-
surface wind speeds and directions recorded by meteorological
stations are likely to describe the circulation patterns of the air
masses throughout the year. Therefore, the question arises as to
whether it is possible to understand climate variability from wind
dynamics in semi-arid areas.
The objective is to examine, on a local scale, the uctuations of
wind dynamics and compare them to observed changes in rainfall
between 1950 and 1992. The spatial resolution of these observa-
tions is considerably lower than that offered by reanalysis elds
*Corresponding author. Dpt. de G
eologie, Universit
e Abdou Moumouni, BP
10662, Niamey, Niger.
E-mail address: (B. Hassane).
Contents lists available at ScienceDirect
Journal of Arid Environments
journal homepage:
0140-1963/©2015 Published by Elsevier Ltd.
Journal of Arid Environments 124 (2016) 91e101
(NCEP/NCAR-1 [NNR-1], 20th century reanalysis [20CR], 2
which are only representative of the regional scale. This local
approach to wind dynamics is the rst step to improve our un-
derstanding of soil erosion and dust transport in relation to envi-
ronmental changes following dry years. Three daily measurements
of wind (direction and speed at 6:00 am, 12:00 noon and 6:00 pm)
from two synoptic stations in SE Niger were used: Maïn
(sahelian zone) and Nguigmi (northern sahelian zone, near the
Sahara boundary).
After a discussion of the study area and its climatic setting in
Section 2, we present the data and methods in Section 3. Next, we
examine the local rainfall variability in Section 4, prior to an anal-
ysis of uctuations in wind speed and direction in Section 5. Finally,
the characteristics of wind patterns during droughts are described
in Section 6.
2. Study area
2.1. Geographical, geomorphologic and climatic settings
The Maïn
e-Soroa and Nguigmi weather stations are located in
the Sahel, to the west of Lake Chad in the administrative region of
Diffa (Eastern Niger, Fig. 1). This region consists of at areas with
altitudes ranging from 400 m in the NW to 280 m in the SE. No
topographic obstacles opposed the dominant NEeSW winds that
have shaped the landscape of the Chad Basin during the Upper
Quaternary (Mainguet, 1984; Durand, 1995).
The Sahel region is a semi-arid area lying just to the south of the
Sahara desert. It is characterized by acacia savannas in which
grasses and shrubs are prominent. This term is often applied to the
general region extending some 5000 km across the eastewest
extent of Africa and from the Sahara to the humid savanna at
approximately 10
N. Mean annual rainfall is on the order of
100e200 mm year
in the north (sahelo-saharan zone), where the
Sahel gives way to desert, and 500e700 mm year
at its southern
limit (sudano-sahelian zone) (Toupet, 1992). Throughout the region
rainfall is generally limited to the boreal summer-months, with a
maximum occurring in August. In the Sahel, the length of the rainy
season ranges from one to two months in the north to four to ve
months in the south. Climatologically, this is due to seasonal shifts
in the pressure over the Sahara and the location of the Inter-
Tropical Convergence Zone (ITCZ; Janicot and Fontaine, 1993;
Nicholson, 2011). During the boreal summer, the low pressure
over the Sahara lies between the NE trades, or Harmattan, and the
humid SW Monsoon ow. The surface position of the ITCZ, i.e., the
Inter-Tropical Discontinuity (ITD), which can reach 20
N, separates
these two wind patterns. During the boreal winter, such a pattern is
reversed due to high pressure anomalies over the Sahara. The ITCZ
as well as the ITD move southward and penetrate into the southern
The upper air patterns also shift seasonally and thus contribute
to Sahelian climate variability (e.g., Newell and Kidson, 1984;
Janicot and Fontaine, 1993; Grist and Nicholson, 2001; Nicholson
and Webster, 2007). In summer, the upper-level ow is easterly
over most of the continent. Imbedded in the easterlies are two jet
streams (Nicholson, 2013): the Tropical Easterly Jet (TEJ), at 200 hPa
with a mean speed of 16e20 m s
, closely related to the deep wet
convection; and the African Easterly Jet (AEJ), at 600 hPa with a
mean speed of 8e10 m s
, which provides the instability for the
growth of African easterly waves (Burpee, 1972) and of rain bearing
disturbances (Mathon et al., 2002).
2.2. Interannual sahelian rainfall variability
The observed change between the late 1960s and the 1990s
corresponds to a decrease of rainfall in the Sahel, which is reected
in a general shifting of the isohyets in Niger from 75 to 150 km to
the south (Ozer and Erpicum, 1995)(Fig. 2). This rainfall decit was
characterized by a decrease of rainy days (Le Barb
e and Lebel, 1997).
On a wider scale, these observed changes in rainfall can be
described through two spatial patterns determined by West African
Monsoon variability. The most common is a dipole (þ/type) in
which drought occurs in the Sahel while wet conditions are
observed over the Guinean zone (e.g., Nicholson, 1980; Janicot,
1992a; Moron, 1994; Fontaine and Janicot, 1995). This is due to a
strengthening and southwards shift of the AEJ blocking the
northwards shift of the ITCZ and then the position of the tropical
rain belt (Grist and Nicholson, 2001; Nicholson and Webster, 2007;
Nicholson, 2008). The second pattern is characterized by negative
rainfall anomalies in the whole of West Africa. In this case (/
type), the ITCZ has a northern normalposition. However, an in-
crease in air sinking motions resulting from a shift of the Atlantic
subsiding branch of the Walker (zonal) circulation and a weakening
of the TEJ speed (up to 10 m s
) are likely to reduce convection and
then rainfall over West Africa (e.g., Janicot, 1992b; Grist and
Nicholson, 2001; Nicholson and Webster, 2007).
3. Data and methods
Two weather stations located in the Central Sahel were selected
(Fig. 2): Maïn
e-Soroa (13
N, 11
E) at a 338 m
elevation and Nguigmi (14
N, 13
E; located near the
boundary of the Sahara) at a 287 m elevation. These stations were
established in 1936 (Maïn
e Soroa) and 1921 (Nguigmi). Since 1961,
these stations have been used for the synoptic meteorological
observation network.
Data from 1950 to 1992 were collected from the Niger Republic
National Direction of Meteorology (NDM) for 1950e1992. We used
Tal Desert
Yobe river
030 km
Fig. 1. Geomorphologic al setting of the Southern Diffa administrative region, south-
eastern Niger according to Durand (1995). The Kadzell is the alluvial plain of the Yobe
River in Niger, which is equivalent to Bornu in Nigeria. Quaternary meanders of the
Yobe have smoothed the surface of Kadzell and Bornu mixing ancient eolian sands
with uvial silty clay contributions. The Lacustrine area of Lake Chad appeared here at
approximately 280 m. The lake, is now almost driedup in Niger. It covered a former erg
with the tops emerged from the dunes forming an archipelago landscape. The wind
eld of the former erg Manga (>15,000 years), which was attened during the Holo-
cene by alternating wet periods (runoff) and dry periods (wind erosion). The Manga
plateau is dotted with basins (interdunes relics) of which the most southern are
seasonally inundated during the wet periods. The Tal desert, located on the edge of the
Manga plateau (310e330 m), consists of unconsolidated sand accumulated by wind
erosion. It has a NEeSW orientation, which is the prevailing wind direction. Recent
droughts have led to a new generation of sand dunes in many parts of the Manga and
Kadzell areas.
B. Hassane et al. / Journal of Arid Environments 124 (2016) 91e10192
the monthly precipitation amounts and the daily wind measure-
ments (direction and speed) at 6:00 am, 12:00 noon and 6:00 pm.
The wind data were collected from the original manuscripts
archived at the NDM in Niamey. At the weather stations, these data
were obtained in conformity with the Weather Meteorological
Organization (WMO) directives for instruments and measure-
ments. Wind speed and direction were measured with two Jules
Richard Instruments located at a height of 10 m: a weathercock and
an anemometer. Registered values represent the mean of obser-
vation for 10 min. The wind directions were noted in two columns
of the archives: rst as numerical values (in tenths of degrees: 0
) and then grouped into sectors of 22.5
(e.g., N,
NNE, NE). The wind speeds were expressed as whole values (e.g.,1,
2, 3 m s
) to account for oscillations during the measurements. For
example, a value of 2 includes observations between 1.5 and
2.5 m s
during 10 min. Values less than 0.5 m s
were counted as
0 and considered as calm(the opposite of wind). In this case the
wind direction was not recorded. The time series studied here is
limited to the period between 1950 and 1992. Since 1993,
numerous gaps of various extents (days, months and as much as a
year) occurred due to instrument failure. Since 2000, human ob-
servations replaced measurements by instruments. The wind di-
rection is estimated with a simplied compass card of 8 directions
(N, NE, E, SE, S, SW, W, NW, N) and the wind speed is estimated with
the empirical Beaufort scale.
For wind speeds and directions, we initially studied the seasonal
uctuations using monthly averages for the period of 1950e1992.
We then compared the long-term wind parameter evolution (speed
and direction) with that of the rainfall. To accomplish this, we used
several analysis methods. First, we used the LOESS method (LOcal
regrESSion, Cleveland and Devlin, 1988), which is a non-parametric
polynomial regression and smoothing function with 0 mean and
. It combines a linear regression technique and has non-
linear regression exibility. It is based on the principle of sliding
windowsthat are dened from the neighboring points. The LOESS
is superior to the moving mean because it retains a much better
variance. Thus, according to the window size used, this method
assesses decadal variations (~10 years) and trends (~40 years).
Additionally, trends in annual time series and their statistical sig-
nicance were assessed using ManneKendall trend test (Mann,
1945; Kendall, 1948). To detect breaks or sudden changes in mean
in the time series, statistical segmentation was then applied (e.g.,
Hubert et al., 1989; Gedikli et al., 2007). This method helped us
identify multiple changes in mean of a time series. Using the least
squares algorithm, the segmentation method detects optimal
breaks between adjacent segments with means that are signi-
cantly different from the Scheffe contrast test at 95%.
4. Local rainfall variability
4.1. Seasonal variations
Rainy season occurs from May to October with a peak in August
(Fig. 3A1 and B1). The seasonal total precipitation distributions
differ between the two stations because of their latitudinal loca-
tions (cf sect. 2). At the Maïn
e-Soroa station (Fig. 3B1), where the
rainy season lasts longer, rainfall amounts exceed 20 mm month
during the transition periods between the dry and wet seasons (i.e.,
June and September). Monthly rainfall amounts are much less in
Nguigmi (Fig. 3B1). After the 1960s, these seasonal uctuations
underwent changes (Fig. 3A1-B1): the August rainfall amounts
were highly reduced, while the July rainfall amounts increased. As
proposed by Chaouche (1988), these observations could indicate a
shift of the rainy season during dry years.
4.2. Interannual rainfall anomalies
Annual rainfall amounts at Maïn
e-Soroa and Nguigmi stations
(Fig. 3A2-3, B2-3) exhibited a signicant negative trend between
1950 and 1970 (wet) and 1971e1992 (dry) (ManneKendall trend
test: tau ¼0.45 and 0.27, p-value ¼0.00002 and 0.01, respec-
tively). In Maïn
e-Soroa, the trend revealed a wet period during
1950e1970 (432 mm over 42 rainy days) and a dry period from
1971 to 1992 (299 mm over 35 rainy days). In Nguigmi, the dry
years began earlier: the wet years occurred during 1950e1965
(255 mm over 22 rainy days) and the dry years occurred from 1966
to 1992 (172 mm over 23 rainy days). Next, we analyzed the annual
rainfall amounts and the quasi-decadal smoothing of the two se-
ries. As described by d'Amato and Lebel (1998), the Sahel drought
seems to have developed in two phases: from 1968 to 1975 and
during the 1980s. In Maïn
e-Soroa, the second period was much
drier than the rst one and had the lowest rainfall amounts
(Fig. 3A2: 197.6 mm in 1984 and 164.9 mm in 1987). In Nguigmi,
where the dry anomalies occurred earlier (likely due to its
0300 km
19 50 - 1 96 7
196 8 - 1 985
Fig. 2. A comparison of rainfall in Niger between 1950e1967 and 1968e1985 (according to Ozer and Erpicum, 1995). Between 1956 and 1969, the Maiduguri station in Nigeria
(11510N) received an average of 580 mm year
over 53 rainy days and the Tanout station in Niger (14590N) received an average of 350 mm year
over 26 days (Mugnier, 1995).
Northernmost in Niger, between 1950 and 1969, Agadez (16580N) received an average of 178 mm year
over 29.3 days and Bilma (18400N) received an average of
18.6 mm year
over 8.5 days (Giazzi, 1996). The rainfall decits between 1956e1969 and 1970e1991 are expressed as 90 mm year
(13 days) for the Maiduguri station in
Nigeria and 140 mm year
(4 days) for the Tanout station in Niger (Mugnier, 1995). Further north in Niger, between 1950e1969 and 1970e1991, the decit is expressed
as 86 mm year
(8.4 days) in Agadez and 7.8 mm year
(5.4 days) in Bilma (Giazzi, 1996).
B. Hassane et al. / Journal of Arid Environments 124 (2016) 91e101 93
northernmost position), the driest years were observed during
1965e1976 ( Fig. 3B2: 68.5 mm in 1972 and 80.9 mm in 1976).
Moreover, between the dry periods (i.e., in the late 1970s), the two
rainfall stations recorded a brief wet anomaly, as described by
Dieppois et al. (2015).
5. Wind speed and direction
5.1. Seasonal variations
Forty-three years of three daily measurements of wind speed
and direction were analyzed (6:00 am, 12:00 noon and 6:00 pm)
(Fig. 4 and Table 1). Of the 47,118 observations per station, 82.7%
and 73.7% showed a signicant wind (speed 0.5 m s
) at the
e-Soroa (Fig. 4A1) and the Nguigmi weather stations
(Fig. 4B1), respectively. Winds were most frequent at 12:00 noon at
both stations: 31.9% of the 15,030 observations (27% at 6:00 am and
23.8% at 6:00 pm) occurred at Maïn
e-Soroa and 31% of the 14,732
observations (22.9% at 6:00 am and 19.8% at 6:00 pm) occurred at
The main wind directions observed in Maïn
e-Soroa were NE
(20.9%), N (12.1%), SW (10.3%), E (8.5%), W (8.5%) and S (6.9%)
(Fig. 4A1-B1 and Table 1). In Nguigmi, the main wind directions
were NE (14.8%), E (13%), W (8.7%), N (6.6%), S (5.7%) and SW (4.6%)
(Fig. 4A2-B2 and Table 1). The N, NE and E wind directions were
observed throughout the year, though were very weak in the
summer, whereas the S, SW and W winds were sporadic from
November to February (Fig. 5). These latter wind directions became
prominent in July and August (Fig. 5). Throughout the year, the SE
and NW directions were infrequent (<10% both). The seasonal
changes in wind direction are a function of the alternating
monsoon and Harmattan wind regimes, as observed in the regional
seasonal cycle (cf. Section 2). The NE, N and E wind directions
associated with the dry Harmattan dominated from October to
April (dry season), and the SW, W and S directions associated with
the monsoon dominated from May to September (rainy season)
(Fig. 5). Both weather stations showed that the transitions between
the seasons were characterized by an important increase in calms
(Fig. 5). In Maïn
e-Soroa (Nguigmi), the highest records of calms
were observed in April (May) and September (September) (Fig. 5).
Fig. 3. The rainfall variability in Maïn
e-Soroa (A1; A2 and A3) and Nguigmi (B1; B2 and B3). 1 (A1 and B1). Monthly rainfall amounts. The thin lines represent the monthly amounts
for each of the 43 years. The older years are gray, the latest years are black and the black bold line represents the mean value. 2 (A2 and B2). The annual rainfall amounts. 3 (A3 and
B3). The annual standardized anomalies: decadal variability (dashed lines) and trend (solid lines) of rainfall amounts. Decadal variability (~10 years) and trend are extracted using
the LOESS smoothing procedure. P1 to P4 indicate the periods of 4 years used in the rainfall and wind comparisons (Sect. 5.3 and 6).
B. Hassane et al. / Journal of Arid Environments 124 (2016) 91e10194
These high records of calms would thus be related to crossing of the
ITD during its northward and southward displacements.
The mean wind speeds measured at 6:00 am, 12:00 noon and
6:00 pm also show a high variability. Because of thermal turbulence
in arid areas (Nicholson, 2011), the wind frequency and speed in-
crease substantially between 6:00 am (sunrise) and 12:00 (midday
sun) before declining to 6:00 pm (sunset) (Le Vourc'h et al., 2002).
Differences occur in the seasonal variations of wind speed
depending on the measurement times. At 6:00 am (Fig. 6A1 and
B1), low mean speeds were observed in April and October with a
high in June in Maïn
e-Soroa; in Nguigmi, low mean speeds were
observed in May and September with a high in July. However, at
Fig. 4. The compass cards of wind directions in Maïn
e-Soroa (A1 and A2) and Nguigmi (B1 and B2) for the period 1950e1992. The compass cards take into account all of the
signicant measurements at 6:00 am, 12:00 noon and 6:00 pm (wind speeds >0.5 m s
). Compass cards A1 and B1 are roses of 36 considering the directions every 10(recorded as
numerical values in the notebooks) and A2 and B2 are roses of 16, considering the directions grouped into sectors of 22.5(collected by letters in the notebooks: N, NNE, NE, ENE, E,
etc.). For the registered directions, each month is represented by a band starting with January in the center of the compass cards. The gray bands correspond to the rainy months
from May to October.
Table 1
The percentages of the main directions of winds and observations of calms at 6:00 am, 12:00 noon and 6:00 pm between 1950 and 1992 at the Maïn
e-Soroa and Nguigmi
weather stations.
Directions Maine-Soroa Nguigmi
6h 12h 18h 6h 12h 18h
N 16.2 8.9 11.3 10.0 4.2 5.6
NNE 2.7 1.9 1.9 2.7 2.4 1.5
NE 18.5 23.6 20.6 15.5 16.0 12.8
ENE 0.8 4.5 1.3 2.5 4.8 2.6
E 3.0 14.2 8.3 7.5 21.4 10.2
ESE 0.2 1.0 0.4 0.3 4.5 1.0
SE 2.4 4.2 2.8 0.8 7.7 3.6
SSE 0.6 0.6 0.5 0.6 2.4 1.4
S 7.7 5.9 7.0 2.8 7.0 7.4
SSW 1.5 1.3 1.0 1.0 1.3 1.0
SW 13.7 10.8 6.4 5.3 5.4 3.2
WSW 1.0 1.2 0.4 2.1 1.8 1.1
W 8.5 11.7 5.3 11.4 10.0 4.6
WNW 0.5 0.6 0.5 1.1 1.4 0.6
NW 3.1 4.7 3.0 3.0 3.1 1.6
NNW 0.8 0.7 0.6 2.1 0.6 1.1
Calms 18.9 4.3 28.7 31.4 6.2 40.5
B. Hassane et al. / Journal of Arid Environments 124 (2016) 91e101 95
Fig. 5. The monthly proportion of predominate wind directions observed at 6:00 am, 12:00 noon and 6:00 pm and the calms observed (curve) in Maïn
e-Soroa (A) and Nguigmi (B)
from 1950 to 1992.
Fig. 6. The monthly wind speed cycle at 6:00 am (1-A1 and B1) and 12:00 noon (2- A2 and B2) at the Maïn
e-Soroa (A1 and A2) and Nguigmi (B1 and B2) weather stations between
1950 and 1992. The gray curves represent the monthly mean speeds for each year, and the black curve corresponds to the mean of these monthly speeds. Counting for 0 m s
records of calms, the mean speeds are 2.05 m s
(sd ¼0.67) at 6:00 pm, 2.33 m s
(sd ¼1.58) at 6:00 am and 4.00 m s
(sd ¼1.97) at 12:00 noon at Maïn
e-Soroa. At Nguigmi, the
means are less important: 1.63 m s
(sd ¼0.66); 1.87 m s
(sd ¼1.51) and 3.63 m s
(sd ¼1.68), respectively.
B. Hassane et al. / Journal of Arid Environments 124 (2016) 91e10196
12:00 noon (Fig. 6A2 and B2), low mean speeds were observed in
May and September with a high in July in Maïn
e-Soroa; in Nguigmi,
low mean speeds were observed in June and September with a high
in July. At 12:00 noon, the highest speeds were observed during the
dry season with a maximum in February at both stations (Fig. 6A2
and B2).
Once more a correlation can be made between the seasonal
wind evolution and the ITCZ and ITD shifts (Sultan and Janicot,
2000). Between April and June (pre-monsoon phase), the ITCZ
progressively shifts from 2 to 5
N, whereas the ITD moves from 9 to
N. At the end of June, the ITCZ shows an abrupt shift up to 10
which is the beginning of the monsoon phase (Sultan and Janicot,
2000; Thorncroft et al., 2011). From the end of August to the
beginning of September, the withdrawal phase of the ITCZ and the
ITD begins. Indeed, when the ITD is located near the weather sta-
tions, low wind speeds were detected. Thus, wind speeds can help
describe and explain the limits of the rainy season in the Sahel
(Fig. 3A1 and B1).
5.2. Interannual wind speed anomalies
Both weather stations show highly similar wind speed inter-
annual variability. Between 1950 and 1952 the ManneKendall
signicance test indicated a very slight downward trend
(tau ¼0.12 and p-value ¼0.26) at Maïn
e-Soroa and a very slight
upward trend (tau ¼0.05 and p-value ¼0.67) at Nguigmi (Fig. 7,
captions). As determined by the LOESS procedure, decadal varia-
tions showed three important negative anomalies (Fig. 7, dashed
lines). The rst anomaly was stronger and occurred earlier in
Nguigmi (1956e1962) than in Maïn
e-Soroa (1959e1960).
Conversely, the second anomaly was stronger in Maïn
(1967e1971) than in Nguigmi (1966e1969). The third one began in
1984 at Maïn
e-Soroa and in 1987 at Nguigmi. The long-term vari-
ations (Fig. 7, black curves) showed a negative trend since 1979 at
both stations.
Vautard et al. (2010) detected a signicant decrease of wind
speeds since the 1980s in the whole northern hemisphere. Thus,
the sahelian wind speed uctuations appear to be consistent with
observations on a wider scale. In the Sahel, however, such a
decrease in wind speed cannot be the result of an increase in soil
roughness linked to vegetation cover, as proposed by Vautard et al.
The time series segmentation helps to identify periods with
means that were signicantly different. It highlighted a period with
a high wind speed mean delimited by two major breaks at both
stations: i) an increase (þ1.4 4 m s
in Maïn
e-Soroa and
Fig. 7. The annual mean speeds (considering 6:0 0 am, 12:00 noon and 6:00 pm) and trends at the Maïn
e-Soroa (A) and Nguigmi (B) weather stations between 1950 and 1992. The
annual mean speeds (þ) are calculated by assuming the calms are zero. The LOESS method is used to characterize the quasi-decadal variation (dashed line) and long-term variation
(black curve). Hubert segmentation is used with the 95% Scheff
e test, which distinguishes 4 segments at Maïn
e-Soroa (sd ¼0.65) and 5 segments at Nguigmi (sd ¼0.62) cor-
responding to the periodic means. The horizontal line represents the mean speed for 1950e1992. The ManneKendall tests applied are all signicant at Maïn
e-Soroa and Nguigmi:
1950e1992 (tau ¼0.12 and p-value ¼0.26 and tau ¼0.05 and p-value ¼0.67, respectively); 1950e1969 (tau ¼0.06 and p-value ¼0.72 and tau ¼0.12 and p-value ¼0.49,
respectively) and 1970e1992 (tau ¼0.33, p-value ¼0.03 and tau ¼0.53 and p-value ¼0.0006, respectively).
B. Hassane et al. / Journal of Arid Environments 124 (2016) 91e101 97
0.52 m s
in Nguigmi) occurred between 1970 and 1971 in Maïn
Soroa and 1969 and 1970 in Nguigmi and ii) a decrease occurred in
e-Soroa in 1985e1986 (0.95 m s
) and in Nguigmi in
1988e1989 (1.53 m s
). In Maïn
e-Soroa (Fig. 7A), another break
was distinguished between 1967 and 1968 (1.31 m s
). In
Nguigmi (Fig. 7B), two breaks were distinguished, a decrease be-
tween 1956 and 1957 (0.85 m s
) and an increase between 1961
and 1962 (þ0.67 m.s
). The periods of low wind speeds appeared
in the raw data of the two stations (Fig. 7,þ). We note that these
changes are nearly synchronous with the decadal variability of
rainfall (Fig. 3).
5.3. Decadal anomalies in wind directions
Considering the decadal precipitation variability at Maïn
Soroa, the wind direction measurements were sampled for 4 pe-
riods (4 years each) (Fig. 8): 1961e1964 (P1), 1969e1972 (P2),
1976 e1979 (P3) and 1983e1986 (P4). These periods were charac-
terized by positive (P1 and P3) or negative (P2 and P4) rainfall
anomalies (Fig. 3). P1 and P3 were characterized by more wind
records at Maïn
e-Soroa (90 and 96%, respectively; Fig. 8A1 and A3)
than at Nguigmi (66 and 82%, respectively; Fig. 8B1 and B3). For P2
and P4, the proportions of winds decreased at Maïn
(Fig. 8A2 and A4) and, subsequently, were similar compared with
Nguigmi (Fig. 8B2 and B4).
In P1, the predominant directions in the dry season were N
(18.5%), NE (24.8%) and E (8.6%) at Maïn
e-Soroa and NE (10.9%), E
(15.8%) and SSE (10.7%) at Nguigmi. During the rainy season, W
(11.7%) and SW directions (9.1%) were predominant at Maïn
and SE (13.1%) and W (10.5%) were predominant at Nguigmi. During
the P2 period, winds of the rainy season (NW, W, SW and S)
decreased at Maïn
e-Soroa (8.7%) while an increase (þ14%) was
detected at Nguigmi. Comparing P2 to P1, a signicant strength-
ening of the N winds occurred at Nguigmi (þ15.7%) and at Maïn
Soroa (þ1.4%) (Fig. 8A2 and B2). Comparing P3 to P1, a strength-
ening of the NE and E winds was noted during the dry season:,
respectively, þ2.1% and þ11.1% at Maïn
e-Soroa and up to þ20.3%
and þ7.9% at Nguigmi (Fig. 8A3 and B3). In the rainy season, the W
winds were dominant and reinforced during P3 (þ6.8% and þ5.3%
compared to P1, respectively). The P4 period were marked by the
emergence of directions (e.g., SSW, WSW, and SSE) intermediate to
the main wind directions at Maïn
e-Soroa (Fig. 8A4) and a signi-
cant decrease (14%) occurred in the rainy season winds. During
P4, the Nguigmi weather station was marked by the predominance
and strengthening of the NE (þ30.3%) and E (þ10.6%) winds
(Fig. 8B4).
By restricting the observations to July and August, when most of
the precipitation occurs, we note that the two wet periods
(1961e64 and 1976e79) were very similar in terms of the pre-
dominance of W and SW winds (Fig. 8A1, B1, A3 and B3). However,
the two arid periods (1969e72 and 1983e86) differed signicantly
at Maïn
e-Soroa and between Maïn
e-Soroa and Nguigmi (Fig. 8A2,
B2, A4 and B4). The compass card for JulyeAugust at Maïn
between 1983 and 1986 (Fig. 8A4) was similar to that observed at
Nguigmi between 1969 and 1972 with many secondary directions
(Fig. 8B2).
The driest periods were characterized by a particularly signi-
cant W wind reduction and a drop in the wind records at Maïn
Soroa (Fig. 8). We noted especially the similitude between the
annual mean of wind speed (Fig. 7) and the proportions of calms
(Fig. 9). Thus, decreases in annual mean of the wind speed can be
related rst to an increase in calms. Moreover, the two driest pe-
riods can be distinguished. Between 1969 and 1972, the annual
mean of wind speed increased every year (Fig. 7), while the number
of calms decreased (Fig. 9) at both stations. On the contrary, be-
tween 1983 and 1986, the annual mean of wind speed decreased
every year (Fig. 7), while the number of calms increased (Fig. 9)at
both weather stations.
Fig. 8. Compass cards of the P1eP4 4-year periods in Maïn
e-Soroa (A1 ¼1961 e196 4; A2 ¼1969e1972; A3 ¼1976 e1979; A4 ¼1983e1986) and Nguigmi (B1 ¼19 61e1964 ; B2 ¼
1969e1972; B3 ¼19 76e1979; B4 ¼1983e1986) for the total observations at 6:00 am, 12:00 noon and 6:00 pm. The percentages correspond to the proportions of the signicant
winds (with speeds 0.5 m s
). On the arrows, the lines that delimit the bands set the limits of the months, starting with January (at the center of the compass card). The gray
bands correspond to May through October. These 4 periods were dened in terms of decreasing and increasing precipitation (quasi-decadal variability) at Maïn
e-Soroa (cf. Fig. 3).
B. Hassane et al. / Journal of Arid Environments 124 (2016) 91e10198
6. Wind vs droughts
At Maïn
e-Soroa, the dry periods were concomitant with an
increasing number of calms (Figs. 8 and 9). Furthermore,
throughout the period of 1950e1992, the number of calms was
more important at Nguigmi (26.3%) than at Maïn
e-Soroa (17.3%).
Climatologically, the Nguigmi weather station was however, much
dryer compared to Maïn
e-Soroa (Fig. 3); which thus raises the
question of a possible relationship between the number of calms
and dry conditions.
The time-evolution of the monthly percentage of calms was
therefore examined during the P1 to P4 periods (Figs. 3 and 10). At
e-Soroa, the minimum calms, which occur during the rainy
season, was observed in June during wet periods (P1: 1961e19 64
and P3: 1976e1979) and in July during the dry periods (P2:
1969e1972 and P4: 1983e1986) (Fig.10). The amplitude of seasonal
uctuations in the percentage of calms (differences between
maxima and minima) was more important during the dry periods.
Thus, the observed uctuations at Maïn
e-Soroa during the dry
periods were similar to that observed in Nguigmi for all periods
(Fig. 10).
At Nguigmi, the P1 period was different than the P2, P3, P4
periods: i) the percentage of calms were above the mean for the
period of 1950e1992; and ii) a minimum occurred in June instead
of July (Fig. 10). Moreover, at Maïn
e-Soroa, during the rst dry
period (P2), more calms were observed during the half-year dry
period (November to April) and, conversely for the second period
(P4), more calms during the half-year wet period (May to October);
at Nguigmi, since 1967, the calms were more important during the
half-year wet period (Fig. 9). In other words, while the P3 period is
similar to the P1 period at Maïn
e-Soroa, the observed change
observed at Nguigmi was irreversible since the P2 period (Fig. 10).
At Maïn
e-Soroa, during the dry periods P2 and P4 the signicant
decrease of winds affected the rainy months (July and August) more
than other months, and it mainly concerned W (P2 and P4) and SW
and S (P4) winds (Fig. 8A2 and A4). This was consistent with a
decrease in the monsoon ux. Nevertheless, the second dry period
(P4) differed from the rst (P2): the W wind disappeared and the
SSE, SSW, WSW directions emerged. At Nguigmi, meanwhile the
percentage of calms decreased, an increase of Harmattan wind was
observed (Fig. 8B): N (P2), NE et E (P3), NE (P4); this increase was
observed even during the half-year wet period (P3 and P4). Thus,
when the monsoon ow decreased at the Maïn
e-Soroa weather
station, the Harmattan ow increased at Nguigmi.
The dry period P4 (1983e1986) was solely determined from the
decadal evolution of rainfall (Fig. 3A3 and B3), but the period was
not homogeneous and exhibited a range of atmospheric processes.
According to Fontaine et al. (1995), the year 1984 was characteristic
of theþ/- type (wet conditions over the Guinean zone and dry
conditions over the sahelian zone), whereas the year 1986 was of
the /type (dry conditions over both regions). Differences also
appeared in observations of the wind directions for each year. At
e-Soroa, 1983 (Fig. 11A1), the driest year in the P4 period, was
marked by the predominance of NE and N winds; weakness of SW
and S winds suggested a southernmost location of the ITD. During
1984 and 1985 (Fig. 11A2 and A3), N and NW winds were dominant;
in 1986, the prevailing winds were from the NE and SW (Fig. 11A4)
as during the mean year (Fig. 4A2). When considering only July and
August, these differences were still evident: the (þ/) rainfall
anomaly was marked at Maïn
e-Soroa by a predominance of S and
SE winds in 1984, whereas the (/) rainfall anomaly corre-
sponded with the regional mean wind dynamics and was
Fig. 9. Evolution of the percentage of annual calm records between 1950 and 1992. For
total measurements at 6:00 am, 12:00 noon and 6:00 pm at Maïn
e-Soroa (A) and
Nguigmi (B). (
)¼January to December, (þ)¼November to April and (B)¼May to
Fig. 10. Monthly percentages of calm records at Maïn
e-Soroa (A) and Nguigmi (B) weather stations. Monthly means for the P1eP4 periods and for the whole 1950e1992 period.
B. Hassane et al. / Journal of Arid Environments 124 (2016) 91e101 99
characterized by a predominance of SW wind in 1986 (Fig. 11B2 and
B4). The most striking feature of the period (P4) at Maïn
e-Soroa was
the importance of the NW wind. Specically, the NW wind was
highest between October 1983 and April 1984 and between
September 1984 and May 1985. The wind's frequency was 6.2% in
1983,19% in 1984 and 11.7% in 1985 compared to an average of 4.4%
for the 1950e1992 period. In terms of the NW wind speed, these
years are almost prominent (Fig. 12). This exceptional NW wind
anomaly might be related to the changes induced by the excep-
tional 1982e1983 El Ni~
no anomaly. Giannini et al. (2000, 2001) and
Alexander and Scott (2002) noted a weakening of the Azores an-
ticyclone and a strengthening with a slight southward shift of the
Subtropical Westerly Jet. In this context, a strengthening of the W
winds occurs in the Tropical Northern Atlantic, which could explain
the replacement of the NE winds with the NW winds in the Central
Sahel. Thus, the analysis of the meteorological surface winds offers
more information than rainfall. The winds help link drought to the
various atmospheric circulation types.
7. Conclusions
At daily and seasonal scales, the observations are good illus-
trations of the current knowledge regarding tropical meteorology.
At the daily scale, the average wind speeds emphasize the role of
thermal turbulence (i.e., greater speeds at 12:00 pm than at 6:00
am and 6:00 pm). At the intra-annual scale, through wind direction
and speed, it is possible to dene the seasons that are closely
related to rainfall. Thus, the dry season is characterized by the
predominance of the NE, E and N wind directions (Harmattan
winds) from October to April, whereas the rainy season is charac-
terized by SW, W and S directions (monsoon winds) from May to
September. The transitions between the dry and the rainy seasons
are marked by an increase of calms (wind speed <0.5 m s
) which
seems to follow closely the displacements of the ITD. The differ-
ences between Maïn
e-Soroa and Nguigmi are rst linked to the
most northerly position of Nguigmi; therefore, the station experi-
ences a shorter rainy season.
At the interannual scale, as expected, during dry periods the
monsoon winds decrease at the Maïn
e-Soroa weather station while
the Harmattan winds increase at Nguigmi. However, other obser-
vations are unexpected. The annual mean of wind speed variations
reect the chronology of rainfall evolution. Moreover, the driest
periods are characterized by: i) a low mean wind speed linked rst
to high records of calms; ii) a more important amplitude of seasonal
uctuations in the percentage of calms (differences between
maxima and minima) and iii) a shift from June to July of the min-
imum of calms which occurs during the rainy season. This raises the
question of a possible use of calm observations as seasonal pre-
dictor of the Sahel rainy season. Such hypothesis must be tested
using several weather stations throughout the Sahel region.
The two arid periods nevertheless present important differ-
ences, which the rainfall did not indicate: the rst period corre-
sponds to an increase from year to year in the annual mean speed
Fig. 11. Annual compass cards in Maïn
e-Soroa (A: A1 ¼1983; A2 ¼1984; A3 ¼1985; A4 ¼1986) and JulyeAugust compass cards (B: B1 ¼1983; B2 ¼1984; B3 ¼1985; B4 ¼1986)
for the 6:00 am, 12:00 noon and 6:00 pm observations during the P4 period (1983e1986). The percentages correspond to the proportions of signicant winds (with
speeds 0.5 m s
Fig. 12. The variations in the daily wind speeds (gray line) and monthly averages
(black curve) in Maïn
e-Soroa for all 6 am, 12 noon and 6 pm observations on the NW/
SE axis. NW and SE represent positive and negative values, respectively.
B. Hassane et al. / Journal of Arid Environments 124 (2016) 91e101100
and the second to a decrease. Moreover, these two periods dis-
played different dominant wind directions. Between 1969 and 1973
a decrease of wind frequency on the SW/NE and W/E axes was
identied in Maïn
e-Soroa at 6:00 am; in Nguigmi these changes
were detected in NE, E and N wind directions. Between 1983 and
1986 the wind decreases on each axis, except for the NW winds in
e-Soroa and the NE and E winds in Nguigmi. These differences
could be related to changes in the atmospheric circulations, espe-
cially the strength and latitudinal position of Tropical and African
Easterly Jets.
Furthermore, the coherence of the wind and rainfall uctuations
allowed us to favorably consider the validity of wind measurements
from the synoptic stations. It would be particularly interesting to
compare them with the reanalysis data (e.g., NNR-1, 20CR) in this
region, where only few observation data are assimilated. Most
importantly, we intend to contribute to the analysis of Sahelian
environmental changes, where rainfall and wind interact through
vegetation and soil erosion to the dust transport.
This study was supported by the AIRD (Agence Inter-
etablissements de Recherche pour le D
eveloppement) through the
CORUS2 project, titled Impact de la pression anthropique et du
Changement Global sur les ux s
edimentaires en zone sah
(grant no. 6116).It is also a contribution to the AMEDE action
(Analyse Multi-Echelle de la Dynamique Eolienne au Sahel), which
is funded by the FED 4116 SCALE (ESTER project) with support from
the Institut de Recherche pour le D
eveloppement (IRD) and the
egion Haute-Normandie (France). The authors are grateful to the
Direction de la M
eorologie Nationale of Niger for providing most
of the data.
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The utilization of wind energy has been well known for centuries, mainly for irrigation purposes. It is also known that wind energy can be converted to electrical energy using a wind-turbine generator especially in remote areas wind energy generation such as that produced by small-scale wind turbines installed in remote areas can be defined as micro-generation. There is a growing interest in the use of wind power in remote areas for distributed generation. Since the generated power is a function of the wind turbine blades and the wind speed, while a small increase in the wind speed leads to a large difference in wind power generation. For installation, an easy fabrication with low cost was the most important challenge. Therefore, it is in our interest to assess properly the wind turbine blades and suitability of these blades at remote areas and attempt to enhance them by using various proposed models investigated aerodynamics by Computational Fluid Dynamics (CFD). Half circle, carved airfoil and semi carved airfoil proposed models are tested. The first model offers a high force compared with others at the same wind velocity. This paper also highlights the potential to increase such systems' economic attractiveness and their acceptance by the user with simple design. © 2021 Zibeline International Publishing Sdn. Bhd.. All rights reserved.
... La croissance démographique significative et l'évolution des modes de consommation accentuent la pression sur les ressources en eau. Aussi, cette situation est accentuée par les effets négatifs des changements climatiques dont les manifestations sont de plus en plus visibles(Hassane et al., 2016 ; Metz et al., 2011).Ces pressions imposent donc aux entreprises sahéliennes d'optimiser leurs consommations et de trouver des solutions de recyclage ou de réutilisation de leurs eaux usées in situ. Les eaux usées industrielles doivent donc être recyclées sur site pour un nouvel usage, puis le traitement à la sortie de l'usine doit permettre d'extraire une eau de qualité qui correspond aux usages. ...
Les industries de production de boissons génèrent quotidiennement des volumes importants d’eaux usées. Du fait des résidus de production et des produits de lavage et de désinfection, ces rejets industriels, en plus d’être chargés en matière organique, contiennent des polluants minéraux comme le sodium. L’osmose inverse (OI), l’électrodyalyse (ED) et la nanofiltration (NF) sont des procédés performants pour l’élimination des polluants minéraux dissouts et le bioréacteur réacteur à membrane (BàM) pour la dégradation de la pollution organique. 4 pilotes de BàM, 2 de NF et 1 d’ED ont été utilisées pour étudier le traitement d’effluents d’industrie de production de bières et de boissons gazeuses par des technologies membranaires dans le contexte climatique sahélien. L’évolution de la biomasse dans le réacteur biologique et les performances épuratoires des systèmes ont été suivies. L’influence des conditions opératoires sur le fonctionnement des installations a également été évaluée. Les résultats obtenus montrent que les caractéristiques des eaux usées industrielles étudiées connaissent des variations importantes avec des teneurs moyennes de demande chimique en oxygène (DCO) de 5 gO2/L, de sodium de 0,5 mg/L et de pH de 11. L’évolution des microorganismes dans le réacteur biologique est influencée par les conditions opératoires notamment le pH, la température, la charge organique de l’alimentation, le temps de séjour des boues et les performances mécaniques du système. L’élimination de la pollution organique a été influencée par l’acclimatation de la biomasse et par la charge massique dans le réacteur. Des rendements d’élimination de la DCO compris entre 93 et 96 % ont été obtenus aussi bien en conditions aérobie qu’anaérobie. Le sodium a été très peu retenu par le traitement au BàM avec des rendements d’élimination faibles. Le rendement moyen de production de biogaz avec le BàM anaérobie est estimé à 0,21±0,03 L biogaz/gDCO éliminé pour un débit moyen de 89±40 L/j. L’application de la NF au perméat du BàM a conduit à des effluents de meilleure qualité avec une élimination aussi bien de la matière organique dissoute que des ions. L’ED a conduit à une meilleure élimination de la salinité à la suite du BàM mais moins de la matière organique dissoute. Les concentrations de sodium dans les produits finaux de traitement avec la NF et l’ED sont inférieures à 150 mg/L autorisant ainsi une possible réutilisation des eaux traitées pour l’irrigation et un déversement sans risque dans l’environnement. Tenant compte des différentes activités, le cout d’exploitation de la station de prétraitement actuelle de la Brakina est évaluée à 140 FCFA/m3 d’eau traitée (0,213 euros) dont environ 70% consacré à la neutralisation des eaux usées par l’addition d’acide concentré. L’amélioration du traitement avec un couplage BàM-NF fait ressortir un investissement estimé à 3,8 milliards de FCFA (5,7 millions d’euros). Les charges d’exploitation sont pour leur part évaluées à 322 FCFA/m3 d’eau traitée (0,49 euros/m3 d’eau traitée) pour un BàM aéré contre 227 FCFA/m3 d’eau traitée (0,34 euro/m3 d’eau traitée) pour un BàM anaérobie soit une baisse de 30%. La construction d’un tel système pourrait occasionner la pérennisation de la maraîcheculture en aval de la station de traitement de Kossodo et générer des centaines d’emplois permanents avec des revenus nets supérieurs à 12 millions FCFA/mois (18 675 euros). Aussi, cela pourrait constituer une vitrine pour la politique sociale et environnementale de la Brakina. Toutefois, les investissements importants, la disponibilité spatiale et l’absence de compétence technique pour la maintenance curative du système pourraient être les principales contraintes à la mise en œuvre de ce projet.Mots clés : bioréacteur à membrane, eaux usées industrielles, électrodyalyse, industrie de production de boissons, nanofiltration
... The latter coincide with the high-temperature and low precipitation of this first regional drought period and could therefore be another feature of this very strong climatic anomaly. A similar pattern can be seen in recently published data for a station ∼1000 km east of Niamey (Hassane et al., 2016), strengthening the significance of this observation. Annual LW down was strongly correlated to Ta (correlation: ...
The Sahel has experienced strong climate variability in the past decades. Understanding its implications for natural and cultivated ecosystems is pivotal in a context of high population growth and mainly agriculture‐based livelihoods. However, efforts to model processes at the land–atmosphere interface are hindered, particularly when the multi‐decadal timescale is targeted, as climatic data are scarce, largely incomplete and often unreliable. This study presents the generation of a long‐term, high‐temporal resolution, multivariate local climatic data set for Niamey, Central Sahel. The continuous series spans the period 1950–2009 at a 30‐min timescale and includes ground station‐based meteorological variables (precipitation, air temperature, relative and specific humidity, air pressure, wind speed, downwelling long‐ and short‐wave radiation) as well as process‐modelled surface fluxes (upwelling long‐ and short‐wave radiation, latent, sensible and soil heat fluxes and surface temperature). A combination of complementary techniques (linear/spline regressions, a multivariate analogue method, artificial neural networks and recursive gap filling) was used to reconstruct missing meteorological data. The complete surface energy budget was then obtained for two dominant land cover types, fallow bush and millet, by applying the meteorological forcing data set to a finely field‐calibrated land surface model. Uncertainty in reconstructed data was expressed by means of a stochastic ensemble of plausible historical time series. Climatological statistics were computed at sub‐daily to decadal timescales and compared with local, regional and global data sets such as CRU and ERA ‐Interim. The reconstructed precipitation statistics, ∼1 °C increase in mean annual temperature from 1950 to 2009, and mean diurnal and annual cycles for all variables were in good agreement with previous studies. The new data set, denoted NAD (Niamey Airport‐derived set) and publicly available, can be used to investigate the water and energy cycles in Central Sahel, while the methodology can be applied to reconstruct series at other stations.
With images provided by satellites, a new analytical tool for observing the landscape of a region is now at our disposal. In the field of aeolian dynamics, satellite data have provided a new means for the study of sand seas and the interpretation of the direction of sand transport. These newly perceived relation-ships between the Sahara and surrounding climatic zones and the dynamics between the Sahara and its semi-arid margins are discussed in this chapter.