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Chapter 5: Dust variability over northern Africa

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5.1. Introduction

The purpose of the analyses presented in this chapter is to describe the variability of

atmospheric dust loadings over Africa north of the Equator and to generate hypotheses

concerning relationships between dust loadings, rainfall in the Sahel and elements of the

regional circulation. This chapter and Chapter 6 both consider processes of dust generation

and the influence of rainfall on dust production. The Infra-red Difference Dust Index (IDDI)

is used to infer information concerning the spatial and temporal distributions of atmospheric

dust. Various dust-producing regions are identified and compared with the accepted sources

described in the literature. The seasonal variations in the activity of these source regions are

described.

Dust indices, consisting of spatially averaged IDDI values over a variety of regions and

representing a number of periods from one to twelve months, are calculated, and these

indices are used to compare mean atmospheric dust concentrations and dust variability over

different latitudinal bands of the Sahel-Sahara zone. Spatial and temporal relationships

between IDDI values in different regions are used to infer information concerning possible

mechanisms of large-scale dust production within the context of the broader body of

meteorological knowledge.

It has been claimed that the Sahel has become the most important source of wind-borne dust

in northern Africa (N’Tchayi et al., 1997). It has also been claimed that such a shift in the

maximum of dust production is due to changes in the Sahelian land surface resulting from

reduced rainfall and excessive land use (Tegen and Fung, 1995; Tegen et al., 1996). The

IDDI data offer an opportunity to examine these hypotheses, at least in part. Therefore an

important element of the work presented in this chapter is an investigation of the relative

importance of the Sahelian and Saharan regions as sources of airborne mineral dust, and of

relationships between dust production in these regions.

5.2. Scales of analysis

Ultimately it is hoped that the impact of dust on the climate of the northern African

subcontinent, and particularly on the climate of the Sahel, may be understood. The impact of

dust on the thermal structure and vertical and horizontal motion of the atmosphere is


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addressed in Chapter 7. However, it is pertinent at this stage to consider the temporal and

spatial scales on which dust is most likely to interact with the processes that determine the

regional climate, in order to identify the regions and periods over which dust activity should

be assessed.

The geographical regions most likely to be important for Sahelian climate modification by

dust on a seasonal timescale are those that experience the greatest spring and summer

insolation. The intense heating of these regions contributes to the formation of the West

African Monsoon (WAM) (Barry and Chorley, 1995). These regions comprise the semi-arid,

arid and hyper-arid plateaux that stretch from the southern Sahel in the south to the central

Sahara in the north. It is postulated that large dust loadings over widespread areas in this

zone might reduce surface heating sufficiently to affect the dynamics of the WAM. Dust

events last for periods ranging from hours to days, and a single dust event is likely to have a

localised impact on the thermal structure of the atmosphere and possibly on the local

circulation. Any prolonged impact of atmospheric dust on the large-scale regional

circulation would arise from generally elevated dust levels over periods longer than those

associated with individual events, caused by a larger than usual number of events in a

particular period and/or a weakening of the processes which remove dust from the

atmosphere. It is therefore pertinent to examine variations in dust loadings over monthly and

seasonal periods, where the latter represent parts of the year characterised by broadly similar

climatic conditions. Annual variations in dust loadings over these periods should be

examined in order to investigate the relationships between dust production, rainfall and

other aspects of the regional climate. Seasonally averaged indices of dust loadings are

particularly useful in assessing the impact of cumulative rainfall amounts on subsequent

dust production (Section 5.7 and Chapter 6).

Single dust events can cover very large areas, and coherent dust signals in the IDDI data

may extend from the Sahel to the coastal regions bordering the Mediterranean (Figure 5.1).

Large-scale configurations of the atmospheric circulation which trigger dust events may

extend far outside the dust source regions (Kalu, 1979; Hastenrath, 1991). Dust that is

transported large distances may have a climatic impact far from its source (Li et al., 1996;

Alpert et al. 1998; Schollaert et al, 1998). Large dust loadings over given regions may

perturb the regional circulation, forming teleconnections with other regions. In this fashion

dust loadings over the Sahara may exert an influence on Sahelian climate. More directly,

dust which originates in the Sahara is transported over the Sahel by the prevailing trade

winds. In winter this circulation extends over the Sahara and Sahel down to the surface in

the form of the Harmattan; at Sahelian latitudes in summer, this transport is confined above


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the oceanic monsoonal air layer in the form of the Saharan Air Layer (SAL). It is therefore

pertinent to examine variations in dust loadings throughout the Sahel-Sahara region, even if

the region of greatest interest is confined to the Sahel. Different regions act as dust sources

during different times of year, so it is also desirable to divide the Sahel-Sahara region into

smaller zones, and examine the variability of dust production in these zones individually.

Figure 5.1: Examples of IDDI signals covering very large areas. Left: Daily field for 18February 1989, illustrating a widespread and intense dust event. Right: Monthly meanIDDI field for January 1990, exhibiting elevated IDDI values extending from northernAlgeria to the northern Sahel. High IDDI values represent large dust loadings. Cloudyregions are masked (white). Scale in Kelvin

Dust over the oceans, specifically over the eastern tropical Atlantic, may have similar

remote impacts via the regional circulation (Schollaert et al, 1998). However, this analysis is

confined to an investigation of dust over land. Large dust loadings over land areas near to

the coast will reflect elevated dust levels over the adjacent ocean regions. Dust levels

generally will also be higher over land than over the oceans, due to the proximity of the

former to the sources of dust. It is expected that no great disadvantage results from the

consideration of mineral dust levels over land only.

The most significant effects of dust on shorter timescales will be those which influence the

dominant rain-producing processes, and are therefore likely to be manifest on timescales

comparable to the lifetimes of the convective disturbances (squall lines or disturbances line)

that bring the majority of the spring and summer rainfall to the Sahel (Tetzlaff and Peters,

1988; Rowell and Milford, 1993). It is plausible that on such short timescales (of the order

of hours – Rowell and Milford, 1993) and relatively small spatial scales (tens to hundreds of

kilometres) dust interferes with the dynamics of the convective cells that make up the

disturbance lines (DLs). Such processes would be most important in the relatively narrow

band of the Sahel, where DL formation is encouraged by surface moisture and the structure


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of the monsoonal air layer (Tetzlaff and Peters, 1988). (DLs may extend over the Sahara, but

can only produce rainfall if they are embedded in the moist monsoonal air layer. Dust may

therefore modify the Saharan sections of DLs considerably, but such modifications will have

little or no hydrological impact unless their effects are transmitted to the more southerly

Sahelian cells of the DLs).

An analysis of the short-timescale interactions between atmospheric dust and DL generation

and evolution would require a modelling approach, which is outside the scope of this thesis.

It should also be noted that the IDDI dataset cannot detect dust in the presence of cloud. DLs

are associated with, and often identified by, widespread cloud cover, so it is impossible to

infer the degree of dust loading in the immediate vicinity of these phenomena. Means of

identifying and/or classifying DLs have been described by Hodges and Thorncroft (1997),

Lamb et al. (1998) and Diedhiou et al. (1998b). This study is a broad investigation of the

role of dust in the climate of Africa north of the equator.

Throughout this study, relationships between atmospheric dust and climate are inferred from

associations between indices representing dust loadings and a number of climatic variables.

These indices are created for given periods and geographical regions. Analyses range from

visual comparisons to studies of statistical relationships between IDDI series and

climatological series. The purpose of this chapter is to describe the variability of dust

production on monthly and seasonal timescales, in order to provide a context within which

to carry out the studies described in Chapters 6 and 7.

5.3. Study areas

For the reasons outlined in the previous section it is desirable to consider dust generation

and dust loadings over a very wide area covering most of Africa north of the equator. The

term “North Africa” is often used to describe the African countries bordering the

Mediterranean, whereas “West Africa” usually refers to the countries of the Sahel-Sudan

zone. The description “northern Africa” is therefore used here to describe the wider study

area, comprising all of Africa north of the equator. This study area is subdivided into

different zones in order to examine relationships between Sahelian and Saharan regions. A

“Sahara” zone is defined as the band between 20° and 30° N, and a “Sahel” zone between

10° and 20° N. (Figure 5.2).

Narrower latitude zones are also defined within the Sahel and Sahara zones (see Section

5.5). All the zones are defined to extend from the West African coast to 30° E. (They are not


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defined over ocean regions). Although the choice of this eastern limit is fairly arbitrary, it is

informed by several factors. East of 30° N, dust loadings are unlikely to exert much of an

influence on the large-scale monsoon dynamics. The WAM is driven to a large extent by the

differential heating of the ocean and land, which will be dominant west of 10° E where the

east-west oriented Guinea Coast region ends. Some distance to the east of the 30° E

meridian, orography results in a climate different to that prevailing over the Saharan and

Sahelian regions, albeit subject to some of the same influences. Interaction between land and

ocean areas in these eastern regions will be dominated by the influence of the Indian Ocean

rather than that of the Atlantic (e.g. Camberlin, 1997). DL generation appears to be

infrequent east of 30° E. (Desbois et al., 1988).

Figure 5.2: The location of the “Sahara” and “Sahel” bands within the wider northernAfrican study area. The northern, western and eastern limits of the map are the limitsof the IDDI data. The western limit is defined by the West African coast.

5.4. The issue of land degradation

Certain studies (e.g. N’Tchayi et al., 1994, 1997) have provided evidence for an increase in

dust production in Sahelian regions over recent years. Other authors have modelled the

global dust cycle and have concluded that “…50 ± 20% of the total atmospheric dust

originates from disturbed soils” (Tegen and Fung, 1995). For the Sahel, the percentage

contribution of disturbed soils to the regional dust budget has not been quantified, and there

are insufficient observational data to verify model estimates. While deforestation and soil

erosion are undoubtedly characteristic of some Sahelian regions, their large-scale impact on

dust production, and particularly on the quantity of dust aerosols reaching high altitudes and

transported large distances, is very poorly understood. The causal relationships linking

changes in Sahelian soil properties with changes in the amount of dust exported from Africa

are therefore not well established. Mineralogical analyses of aerosol particles transported


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over the Atlantic have identified Sahelian sources, characterised by a high clay content

when compared with Saharan sources (Bergametti et al., 1989). However, there is no

evidence that such particles have arisen from soils degraded by climatic desiccation or

human activity (Prospero et al, 1981; Ellis et al., 1993; Chiapello et al., 1997).

The northern limit of the Sahel is often placed approximately at the latitude of the 200 mm

or 250 mm isohyet (e.g. Glantz 1994). Such a definition is usually employed when the Sahel

is defined as the semi-arid region capable of supporting rain-fed agriculture (e.g. Mortimore,

1998). Thus it may be assumed that the northern limit of agriculture is approximately

coincident with the 200 mm isohyet, which ranges from some 17° N near the West African

coast to around 14° N in the region of Lake Chad for the period 1984-1993 (Figure 5.3).

Maps of soil degradation show degraded areas extending to around 17° N in Africa,

particularly west of about 10° E (UNEP, 1992, reproduced in Williams and Balling, 1996).

UNEP (1992) attribute the majority of soil degradation in Africa to overgrazing. The zone of

degradation terminates just north of the Niger Bend in Mali, representing the approximate

northernmost limit of degradation in the Sahel. The extent of such degradation may have

been overestimated due to the degree of interpolation employed (Williams and Balling,

1996); certainly such estimates should be treated with caution. Nonetheless, such studies

suggest that dust production north of 17° N in the Sahel-Sahara region is unlikely to be the

result of human-induced soil degradation. It should be noted that the limit of 17° N for soil

degradation coincides with the rough definition of the northern limit of agriculture as being

equivalent to the 200 mm isohyet. The density of livestock associated with pastoral or other

human activity is very low in regions where annual rainfall is below about 250 mm, again

suggesting minimal human impact beyond 17° N. Indeed, the distribution of livestock

appears to be determined by the distribution of permanent human settlement, rather than the

extent of rangeland (Wint and Bourn, 1994), calling into question the notion that Sahelian

rangelands have been widely degraded by agricultural and pastoral activity. These issues

will be discussed further in Chapter 6.


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Figure 5.3: Percentage reduction in rainfall between the wet period of 1950-1965 andthe period under investigation (1984-1993). Dashed contours are isohyets (in mm) forthe former period, solid contours are isohyets for the latter period. Based on the CRUgridded 1°°°°x1°°°° rainfall dataset (New et al., 1999).

It is plausible that degradation north of the limit of widespread human activity has resulted

from climatic desiccation. The isohyets in Figure 5.3 exhibit a southward shift by the order

of a degree latitude between 1950-65 and 1984-93. Such changes in rainfall may well lead to

changes in vegetation cover and hence land surface properties. However, the impacts of such

changes in land cover resulting from shifts in rainfall bands on dust production are

speculative. Nicholson and Tucker (1998) state that there is no evidence for widespread land

degradation on a regional scale in the Sahel, and earlier studies by Tucker et al. (1991,

1994) indicate that vegetation quickly recolonises desiccated areas in favourable rainfall

years (c.f. Chapter 2). It is reasonable under the circumstances to use the liberal UNEP

(1992) estimate of the extent of land degradation as a working value of the latitude beyond

which the degree of land degradation is negligible. The relationship between dust loadings

either side of this hypothetical northern limit of land degradation will be investigated in

Section 5.6.

5.5. Identification of dust source regions

The IDDI data are representative of aerosol loadings (Chapter 3), and over the arid and

semi-arid regions of northern Africa the dominant aerosols are mineral dust particles

mobilised from desert and dryland surfaces. Therefore, it may be assumed that high IDDI

values over the Sahel and Sahara are generally representative of high atmospheric dust

concentrations. Outside these regions, other aerosols, such as biomass burning products, will


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also be important. The role of these particles is addressed where appropriate below, in the

discussions of particular geographical regions.

Concentrations of aerosols in the atmosphere will generally be greatest nearest to their

regions of origin, particularly if concentrations averaged over time are considered. Airborne

dust is likely to have the greatest impact on the radiative and optical properties of the

atmosphere near its source, where mean particle size and particle density are greatest.

Advection of dust will result in IDDI signals away from the major sources, but a judicious

and flexible use of scale and threshold values enables detailed regions of IDDI maxima to be

distinguished. These regions are interpreted as being broadly coincident with sources of dust

aerosols. The terms “IDDI values”, “dust loadings” and “dust production” are therefore

equivalent within the context of the following discussion, which identifies the major sources

of mineral dust in Africa from fields of IDDI data.

Various mean IDDI fields were created in order to examine dust variability over Africa.

Monthly means were created from the daily data. For each grid-cell, a monthly value was

calculated only if no more than 80 per cent of the daily values for that month were missing.

In other words, 6 daily values (or 5 values in the case of February) were required to

calculate a monthly mean value. Daily IDDI values greater than 50 Kelvin were treated as

missing data in order that any cloud values that had been misinterpreted as dust were not

used. The highest IDDI values that have been associated with dust outbreaks are in the range

40-45 Kelvin (Legrand, personal communication). Annual means were created from the

mean monthly values for cells where more than three months contained data. Seasonal

means were created provided one of the months contained data. Ten-year mean monthly and

annual fields were created, with missing data values returned to cells where fewer than four

years were represented. The percentages of data required to create the mean values were

chosen in order to strike a balance between the need for as wide a geographical coverage as

possible, and continuity in the resulting mean fields.

Figure 5.4 shows the mean annual field of IDDI values for 1984-1993. IDDI values greater

than 5K tend to delineate fairly distinct regions. The IDDI value of 5 K corresponds to dusty

conditions characterised by visibilities near the ground of less than 10 km, and is

approximately equivalent to aerosol optical depth (AOD) of 0.3-0.5 (Legrand, 1994, c.f.

Chapter 3). In Chapter 2 it was seen that an increase in AOD of 0.1 could correspond to a

forcing of several Wm-2, of the same order as the globally averaged enhanced greenhouse

gas forcing, albeit on a local or regional scale (Lacis and Mischenko, 1995). A mean IDDI

value of 5 K therefore represents a considerable time-averaged forcing of the local or


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regional climate. Within these regions finer detail is apparent in the form of areas with IDDI

values in excess of 5.5 K. These thresholds are interpreted as indicating broad regions of

dust activity and major source regions respectively. The choice of thresholds is arbitrary

insofar as there is no physical basis for the identification of source regions with IDDI data

above a certain value. However, these IDDI values do reveal a good deal of fine structure in

the annual field, and define regions that broadly coincide with accepted regions in which

mineral dust is mobilised. Three major regions of high dust activity are apparent in the

Sahel-Sahara region; these are discussed below.

Figure 5.4: Annual average dust production over Africa, as indicated by time-averagedIDDI values. IDDI values were averaged for each annual twelve-month period(January-December), and the resulting fields averaged over the period 1984-1993.Large IDDI values indicate high dust loadings. Scale in Kelvin.


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Figures 5.5 and 5.6 illustrate mean seasonal and mean monthly IDDI fields respectively.

These fields yield information concerning the seasonal variations in activity of the aerosol

source regions. A similar approach to that outlined above for the mean annual field is

adopted to identify source regions. For both mean monthly and mean seasonal fields the

threshold of 6 K delineates distinct and detailed regions of high IDDI values. This threshold

is interpreted as loosely defining dust sources. Where appropriate, the seasonality of

particular source regions is discussed in the short sections below which describe the

particular source regions. General patterns of seasonality are discussed at the end of this

section.

Figure 5.5: Mean seasonal IDDI fields over Africa in Kelvin, for the period 1984-1993.


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Figure 5.6: Mean monthly fields of IDDI over Africa north of the Equator in Kelvinover the period 1984-1993. Scale in Kelvin.


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5.5.1. The north-central Sahel

A region extending from about 5° to 20° E, and 13° to 18° N is apparent, with a peak IDDI

value at approximately 16° E, 17° N (Figure 5.4). A lower magnitude maximum in this

region is roughly centred on 9° E, 15° N. The region can thus be divided into two distinct

source areas. The eastern source represents the southern and eastern parts of the Erg of

Bilma, which straddle the border between Niger and Chad, and the alluvial plain to the

north-west of the town of Largeau in northern Chad. This region has been identified as an

important source of dust aerosols which are transported by the Harmattan winds (McTainsh,

1980; Drees et al., 1993). Dust storms in this region occur when intensification of

anticyclonic conditions over the northwestern and central Sahara lead to low-level pressure

surges (Kalu, 1979). The western source lies over central southern Niger, to the south of the

Aïr Massif. It is noted that the western sources are located in the vicinity of an area of

enhanced DL generation just west of the Aïr Mountains (Rowell and Milford, 1993). Both

eastern and western source regions lie within the central to northern Sahelian latitudes.

Mean monthly IDDI fields (Figure 5.6) indicate that the central Sahelian sources become

active in December, with maximum activity in January. Activity is still high in February,

particularly for the eastern source region, and dies down in March, becoming low in April.

The sources are reactivated in May, but activity is lower than in January and February. In

June the western sources merge with a zone of activity stretching westwards from 5° E and

associated with the northern limit of the ITCZ. A signal from the eastern sources is still

apparent, dying away in July.

5.5.2. The west Sahara and western Sahel

A large source region is apparent in the west of the Sahara, with maximum IDDI values

between about 7° - 0° W and 20° - 25° N. This coincides with the Erg Chech of northern

Mali and Mauritania and south-western Algeria, and a region characterised by smaller ergs

in northern Mali1. A secondary maximum is centred on a region of seasonal water courses

near to the coast located around the border between Western Sahara and Morocco, to the

south-west of the Tindouf and Draa hammadas. These regions coincide with the northern-

most extents of dust haze events as reported by Westphal et al. (1988). Coudé-Gaussen et al.

(1987) report a southern Moroccan origin for dust transported over the Canary Islands. A

dust plume reaching northwestern Europe in April 1983 contained particles originating in

1 Geographical data are taken from the VWK Africa North and West road map, 1: 4,000,000, P.O.Box 2105, Obertshausen 2, Germany.


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Mauritania as well as in the southern Sahara/Sahel (Reiff et al., 1986). Chiapello et al.

(1997) found that dust transported over Sal, on the Cape Verde Islands, most frequently

originated in the north and west Sahara; the west Sahara region described here corresponds

to a broad source region characterised by a particular set of transport trajectories (sector 3 in

their description).

The West Sahara sources are most active in March. (Some low-level activity is also apparent

in February). The region of maximum IDDI values within the zone shifts from the east in

March to the west (southern Morocco/northern Western Sahara) in April and May. At this

time of year Saharan thermal lows develop south of the Atlas Mountains, influenced by the

strong east-west thermal contrast between the continental and oceanic regions (Moulin et

al., 1998a). These cyclones are responsible for transporting large amounts of dust to the

eastern Mediterranean. April coincides with the end of the Moroccan wet season, and the

consequent reduction in wet deposition will also act to enhance dust concentrations.

Activity reduces and shifts inland over western Algeria in June. A contribution to the annual

IDDI signal for this region arises from a zone of intense activity in the northern Sahel and

southern Sahara in June, July and August. This zone moves northwards over these months,

its central latitudes being approximately coincident with the expected position of the surface

discontinuity between the monsoon and Saharan air masses (Hastenrath, 1991). It is at these

locations that the signals are strongest, indicating dust production in the Saharan air mass,

and production in the Sahelian monsoonal air wedge, or advection from the Sahara, where

the monsoon layer is too shallow to allow significant rainfall to occur. A strong relationship

between the location of the transition zone from convective rainfall to a shallow monsoon

layer and the latitude of the maximum number of dusty days is reported by Alpert et al.

(1998).

In the summer, there will be a strong differential heating between the southern Sahara and

the waters off West Africa, resulting in the generation of cyclones which will interact with

the low-pressure zone associated with the ITCZ. Cyclogenesis may also be assisted by the

dynamics of the discontinuity region, as the Saharan air rises over the cooler monsoon air.

Dust may also enhance dry convection by heating the local atmosphere, resulting in a

positive feedback in the dust cycle (e.g. Chen et al., 1995). By September, dust production

has declined dramatically, although some residual activity is apparent over central

Mauritania and Mali.


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5.5.3. The east Sahel-Sahara

The third major source region is approximately oriented in a north-south direction along the

30° longitude meridian, stretching from some 13° N in northern Sudan to around 25° N in

southern Egypt, terminating to the south of the oases of Dakhla and Kharga. Dust from the

northeastern Sudan has been transported to the eastern Mediterranean (Middleton, 1986).

Activity in this region commences in the south in December, increasing in strength until

March and persisting until June.

5.5.4. Other Sahelo-Saharan sources

A minor region of activity is apparent at and to the north-east of a location centred on 14° E,

22.5° N. This area lies between the Plateau de Djado in northern Niger and the Idhan

Murzuq erg in south-western Libya, and is characterised by ephemeral watercourses and

elevations reaching some thousand metres. This region becomes active in December,

remaining a weak source until February, when activity is most intense. Notable activity is

also apparent in March and April, with the source switching off by May.

5.5.5. Seasonal patterns of dust production and non Sahelo-Saharan sources

The mean seasonally averaged fields of IDDI (Figure 5.5) illustrate broad patterns of dust

production throughout northern Africa. The most notable characteristic of the first six

months of the year is the switch of production from the eastern half of continental North

Africa in JFM to the west in AMJ. This is a broad general pattern: the East Sahel-Sahara

region remains active in AMJ, and the West Sahara region becomes active in March. Indeed,

March is the most active month as far as the West Sahara is concerned. However, within the

West Sahara region, maximum activity shifts from the east in March to the west in April and

May, reflecting the general seasonal pattern.

Within the Sahel-Sahara zone, activity remains concentrated almost exclusively west of 10°

E throughout JAS, and appears to be closely associated with the position of the ITCZ. For

example, the June source region lies to the north of the zone in which more than 40% of the

days in June are characterised as cloudy (Figure 5.7). The southernmost limit of the zone of

June high IDDI values (as defined as IDDI values greater than 6K) varies from about 12º to

15º N. These latitudes are approximately coincident with, or to the north of, the surface

discontinuity associated with the ITCZ (Hastenrath, 1991). As the ITCZ moves north in

July, the zone of dust production shifts to the north-west, to about 18º - 24º N and 13º W - 7º


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E. The longitudinal extent of this region of activity shrinks in August to approximately

12ºW - 2º E, while its latitudinal extent is similar to that of June. The southern limit of the

region of high JAS IDDI values lies immediately to the north of the Niger Bend, and

contains the plains between 5° and 10° W which have been identified by Rowell and

Milford (1993) as areas of enhanced DL generation. (They also identify frequent DL events

over the most northerly regions of the Niger River).

OND is characterised by low IDDI values throughout continental North Africa. The

December activation of relatively small source regions in the central/northern Sahel and the

central Sahara results in a weak signal in these areas. October and November exhibit the

lowest IDDI values, representing an annual minimum in the seasonal dust cycle.

Figure 5.7: Mean June IDDI field (left), compared with mean June cloud frequencyfield (per cent of cloudy days in June – right). The scales are inverted with respect toone another so that yellow/red represents high dust loadings and low cloud frequency(i.e. aridity). Blue represents low dust levels and wet conditions in the IDDI and cloudfields respectively.

The Guinea Coast

Also notable in JAS is a zone of relatively high IDDI values along the Guinea Coast region,

extending in places to some 12° N and exhibiting a maximum in the east over Nigeria

(Figure 5.5). The period JAS corresponds to the “Little Dry Season” (Barry and Chorley,

1995) in this region and it might therefore be expected that widespread biomass burning

would be prevalent. Monthly maps of fire distribution are available for some years from the

World Fire Atlas, compiled by the European Space Agency and the European Space

Research Institute (ESA/ESRIN) as part of the Ionia programme

(http://shark1.esrin.esa.it/home.html; Arino and Melinotte, 1995; Arino et al., 1997).

These maps have been produced from AVHRR and ATSR satellite data. A visual

http://shark1.esrin.esa.it/home.html;


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comparison of the monthly IDDI fields with monthly fire maps for 1993 suggests that the

JAS high IDDI values over the Guinea Coast are not due to combustion products, as fires are

almost entirely absent from this region in this period according to the fire maps. At this time

of year detectable fires are concentrated between the Equator and 20°S, where IDDI values

are low. Strong fire signals in the ESA/ESRIN data occur over and to the east of the Guinea

Coast throughout the winter, with fires being most widespread in January. Again, the

regions of high IDDI values do not correspond to those characterised by fires; the January

1993 IDDI field exhibits low values over the Guinea Coast. However, the relationship

between the distribution of fires as detected by satellite remote sensing methods, and high

concentrations of biomass burning aerosol products is not necessarily straightforward.

The effect of smoke aerosols will be similar to that of sub-micron dust particles, resulting in

a cooling of the land surface due to a reduction in solar insolation. Both smoke and fine dust

are transparent in the infra-red part of the electromagnetic spectrum, and will not reduce the

OLR. Any IDDI signal resulting from the presence of these materials will therefore be solely

due to the cooling of the land surface, and is likely to be significant only when they are

present in large quantities. Dense clouds of smoke will obscure the ground from satellite

detectors operating in the visible part of the electromagnetic spectrum, hindering the

detection of the fires which produce them. It is therefore highly likely that fires resulting in

large quantities of smoke aerosols will not be represented in fire maps, explaining the

presence of strong localised IDDI signals which do not correspond to detected fires. It is

plausible that material from such fires is responsible for some of the high IDDI signals

apparent in Figures 5.4 to 5.6, providing at least a partial explanation for the summer Guinea

Coast signal.

Another plausible explanation for the high IDDI values over the Guinea Coast in summer is

that dust is transported from the Sahel-Sahara to a region of relatively stagnant air over this

region, where it remains in the atmosphere for some time. Between the Guinea Coast and the

Sahel-Sahara transition zone, dust will be removed from the atmosphere by rainfall,

resulting in short residence times, low aerosol concentrations and hence low IDDI values.

West central Africa

Large quantities of combustion aerosols also provide a plausible explanation for high IDDI

values over regions where dust is unlikely to be a major feature of the atmosphere. Such

values are seen over west central Africa (stretching from Gabon to the Democratic Republic

of Congo and southwards over Angola) in all the fields, and are largest in OND and JFM.


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Some biomass burning occurs in this region in these periods, particularly in October (based

on 1993 data from ESA/ESRIN). However, the frequency and density of fires during the

periods in question is far greater between 0° and 15° N, where IDDI values remain low.

Again, these discrepancies between the IDDI and fire data may be due to the complex

relationship between fire and smoke aerosol distributions.

The west-central African region is adjacent to an area of frequent cloud cover in JFM and

OND (i.e. southern hemisphere spring and summer), when the IDDI values are highest. It is

possible that some “cloud contamination,” i.e. misinterpretation of cloud values as IDDI

values occurs in these periods. This is most likely to occur when cloud is present throughout

the entire 15-day reference period used to produce a given set of IDDI values. When this

occurs, a cloud signal will be incorporated into the radiometric count values comprising the

“clear sky” field, resulting in erroneous reference values. While this will tend to reduce the

calculated IDDI values, it may also cause the cloud identification algorithm to fail, resulting

in cloud being misidentified as aerosol. It is possible that cloud contamination is also

responsible for some of the high values over the Guinea Coast.

Eastern Africa

Similar features occur over many of the eastern coastal regions of Africa south of 10º N,

particularly in AMJ and JAS. These regions contain no extensive deserts, but do include

semi-arid and dry sub-humid zones. The boreal summer high IDDI signal occurs during the

dry season in East Africa. It is possible that dust mobilisation occurs from disturbed soils in

these regions, although a complex biomass burning aerosol signal is again likely.

A prominent feature of the seasonal IDDI maps is the region of very high IDDI values over

the Horn of Africa in JAS. This signal in the IDDI data coincides with very high equivalent

aerosol optical thickness (EAOT) measurements over the Arabian Sea (Husar et al., 1997 –

based on data from July 1989 to June 1991, c.f. Chapter 2, Figure 2.5). The parts of Arabia

visible in the IDDI fields exhibit low IDDI values, suggesting that the material transported

over the Arabian Sea originates predominantly in the Horn of Africa. Mobilisation and

transport of dust is aided by the East African (or Somali) low-level jet, which is active at

this time of year as part of the summer monsoonal circulation (Hastenrath, 1991, Husar et

al., 1997). Transport of dust over large distances occurs above the monsoon inversion, in a

fashion analogous to the transport of Saharan dust above the trade wind inversion in the

Saharan air layer (Kalu, 1979; Sirocko et al., 1991).


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Southern Africa

Finally it is worth mentioning the southern hemisphere African deserts in terms of dust

sources as defined by the IDDI data. These regions do not stand out in the seasonal or

annual fields, although elevated IDDI values are apparent over the Kalahari in JFM. It is

striking that the Namib Desert does not appear to be a significant source of dust. The cold

Benguela Current to the immediate west of the desert results in a highly stable atmosphere

which is not conducive to the generation of the large convective events responsible for dust

mobilisation and transport elsewhere. While dust storms do occur over the sandy desert in

the Namibian interior, it appears that the spatial and time scales associated with these events

are such that they do not produce a major signal in the mean IDDI fields. The coastal

atmosphere is very different from that over West Africa, and it is likely that the atmospheric

environment over the Namib desert is such that dust aerosols are not carried to the

elevations necessary for long-range transport. Middleton (1997) states that dust mobilisation

and transport from the southern African deserts is poorly understood, but suggests that the

scale of such phenomena is not comparable with that which characterises the northern

African regions.

Summary

The above discussion illustrates some of the caveats to be considered when interpreting the

IDDI data. The question of whether the IDDI is a reliable means of detecting combustion

aerosols remains open, and will only be resolved when the relationship between detected

fires and the nature and distribution in the atmosphere of their products is better understood.

The physics of the interactions between IR radiation and such products should also be

investigated further.

It also appears that the IDDI is less reliable under persistently cloudy conditions. High IDDI

values which cannot be associated with dust or other aerosols are likely to be the result of

cloud contamination, where the IDDI method is not reliable due to high levels of cloud

throughout the period used to produce the reference images. Cloud contamination is most

likely to occur in humid regions, as suggested by the occurrence of very localised high IDDI

values at the edge of regions of high cloud frequency. Over the main regions of interest,

which are the semi-arid and arid zones of the Sahel and Sahara, such effects are likely to be

minimal. Indeed, the mean IDDI values over the Sahel and Sahara generally do not exhibit

the large-magnitude localised signals (often confined to a single 1° latitude x 1° longitude

grid-cell) seen near the edge of cloud fields in the equatorial regions. In the Sahel-Sahara


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zone, the dominant aerosols are dust particles. These will be preferentially detected

compared with other aerosol types due to the episodic nature of their production and

transport (resulting in a strong contrast with the background signal incorporated in the

reference field). The IDDI is therefore particularly suited to investigations of large dust

events; the strongest IDDI signals will result when such events contain a high proportion of

large dust particles, resulting in a reduction in both surface insolation and OLR.

Further work is required to decouple the effects of biomass burning products and cloud

contamination from the impacts of dust on the IDDI signal. However, over the Sahel and

Sahara, the IDDI appears to perform well, and detects large dust events and the major

sources of dust aerosols. It may therefore be used with confidence in studies of Saharan and

Sahelian aerosols and their relationships with the regional climate. Seasonal and

geographical variations in the IDDI data may also be used to infer information concerning

the nature of the major aerosol sources in northern Africa.

5.5.6. Character of the source regions

The dust sources in the northern central Sahel, the west Sahara, east Sahel-Sahara and the

Niger-Libya border region all lie in areas that are characterised by sandy desert (erg) and/or

ephemeral watercourses (or wadi systems). These regions constitute the most significant

dust sources in Africa. The area to the south of the Aïr Massif, in the western part of the

northern Central Sahel source region, is characterised predominantly by temporary

watercourse, although it includes the westernmost part of the Erg du Teneré. It also includes

the northernmost limits of the zone of settlement, and therefore of agriculture. It is therefore

the most likely candidate, out of all the Saharan and Sahelian sources, for a region

containing anthropogenic sources. However, significant settlements are absent from much of

the zone, and the density of wadi systems and proximity to the Aïr highlands suggests that

erodible material is likely to be supplied in large part by hydrological action.

The distribution of dust signals in the IDDI fields suggests that large-scale dust production

occurs predominantly in response to the prevailing climatological conditions and, outside of

eastern Africa, in regions where human activity is limited or negligible. It is possible,

however, that material from anthropogenically degraded soils does not produce a strong

signal in the IDDI data, resulting in an underestimation of the extent of the major source

regions. Aerosols from degraded soils are likely to be very different in nature from those

deflated from arid to hyper-arid desert regions. Dust consisting of such aerosols will contain

more organic material and have a higher clay content, resulting in a high proportion of small


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( < 2 µm) aerosol particles (McTainsh and Walker, 1982). Organic material has been

detected in dust deposited in Niger (Drees et al., 1993) and northern Nigeria (McTainsh and

Walker, 1982). However, it is not clear whether the organic input is due to desiccation of

vegetated areas or if it is a long-term feature of the soil-dust cycle.

Small aerosol particles from clay-rich soils will have a weak attenuating effect on the

outgoing longwave radiation (OLR). Thus the IDDI signal from such material will be

predominantly the result of surface cooling. McTainsh and Walker (1982) report a tendency

for lower visibility and reduced solar radiation to be associated with finer mean particle

sizes. The correlation of IDDI values with measured visibilities (Legrand et al., 1994; c.f.

Chapter 3) suggests that the IDDI are capable of detecting such fine material. Recent

modelling studies indicate no difference in the temperature and IR radiance at the top of the

atmosphere (TOA) between fine dust in a elevated layer and fine dust extending from the

ground to 1.5 km (Legrand, personal communication.). A lack of layering of locally

produced fine aerosol particles over the Sahel is therefore unlikely to lead to poor detection

of such material. It is plausible that fine particles from degraded Sahelian soils remain near

the surface, and have a small effect on the net IR radiance at the TOA. However, this is

speculative, and aerosols which remained at low levels would not contribute to the budget of

aerosols exported from Africa, as this transport occurs above about 1.5 km (Alpert et al.,

1998). The IDDI data therefore call into question the assumption that aerosols from

degraded soils contribute significantly to the budget of material exported from northern

Africa.

5.6. Sahel and Sahara IDDI indices: a comparison

Sahelian and Saharan zones are defined in order to compare dust production in the two

regions. The Sahel is defined as the latitudinal band lying between 10º and 20º N, between

the West Africa coast and 30° E. The Sahara is defined as the band lying between 20º and

30º N within the same longitudinal band as the Sahel. The large longitudinal range is

justified, as the primary purpose of this section is to examine changes in the nature of dust

production with latitude, i.e. as the inhabited Sahel gives way to the effectively uninhabited

Sahara. Nonetheless, the definitions of the “Sahel” and “Sahara” are arbitrary, and the

“Sahel” region extends into the zone in which agriculture and human impact on the land

surface are minimal or non-existent (Section 5.3). For these reasons the bands were further

divided (Figure 5.8) into the South Sahel (10°-15° N.), North Sahel (15°-20° N; effectively

the Sahel-Sahara transition zone), South Sahara (20°-25° N.) and North Sahara (25°-30°N.)


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IDDI indices were created for these regions for monthly, “seasonal” and annual periods.

Seasonal periods were chosen to represent different prevailing meteorological conditions

and different dominant patterns of dust distributions. The “wet season” was liberally defined

as May to October and the “dry season” as November to April. The dry season was divided

into the “early dry season” (November and December), and the “late dry season” (January to

April). The annual period used here is the twelve-month period from the beginning of

October to the end of September. In order to create a period which, cumulative effects aside,

will be affected by only one wet season, an index from the beginning of October to the end

of April (before the onset of the next year’s rains) was also created. (This period is very

similar to the dry season period, and allows the impact of including October into the period

between wet seasons to be assessed).

Figure 5.8: Bands for which IDDI values were zonally average to create IDDI indices.

The indices were constructed by averaging monthly fields of IDDI data over the periods, or

“seasons”, in question. These temporally averaged fields were then spatially averaged over

the regions of interest. The spatial averaging process was also carried out for individual

months. The resulting timeseries are ten years in length, or nine years in the case of periods

that span two years, such as October-September.


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5.6.1. Mean zonal variations of IDDI

Mean monthly, seasonal and annual IDDI values were created by averaging the yearly

values that constitute the IDDI-index timeseries described above. The resulting mean

monthly values are plotted against month for the various zones defined above, in Figure 5.9.

The numerical values of the means for the periods comprising more than one month are

given in Table 5.1.

Figure 5.9: Mean spatially averaged IDDI values, in hundredths of a degree Kelvin,over various latitudinal bands (see text for definitions), for individual months.

Figure 5.9 effectively shows the mean seasonal variation in dust production for the different

zones. The seasonal behaviour of the Sahel and Sahara zones is broadly similar, although

some striking differences are apparent. Saharan IDDI values, and by inference dust

production, peak during the period February-May, with the highest values apparent in April.

During this period they exceed the Sahel IDDI values, which peak in May and June. A

comparable Sahel maximum is also apparent in March. From June to September there is a

downward trend in IDDI for both regions, with the Sahel values exceeding the Sahara

values. Sahelian IDDI values fall dramatically below those of the Sahara in November, most

likely in response to the previous wet season’s rainfall, via the effects of moisture and/or

vegetation on soil cohesion and vulnerability to deflation.

These seasonal variations in IDDI values, and by inference in dust production, are reflected

to varying degrees over the narrower zonal bands. The largest IDDI values are located over

the South and North Sahara in March and April respectively. These values represent both

geographical and seasonal maxima in dust loadings. IDDI values over the Saharan regions

also exceed values over the Sahelian regions in November. The November Saharan values

reflect the largest dust loadings at a time when dust production is at a minimum, whereas the


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March/April values reflect maxima during a high-activity season. Minima in the North

Sahara series which are not reflected in the South Sahara series occur in February and

August, and represent a decoupling of dust production in these two zones. During February

such a decoupling is likely to be the result of mobilisation mechanisms connected with

Atlantic and Mediterranean cyclones extending over North Africa.

Geographical region

Period Sahel Sahara South

Sahel

North

Sahel

South

Sahara

North

Sahara

JFM 510 534 478 541 539 429

AMJ 520 527 493 545 516 539

JAS 485 461 463 505 482 438

OND 410 438 396 424 438 438

Wet 487 471 467 506 476 464

Dry 475 510 447 502 512 507

Early Dry 412 446 391 433 451 440

Late Dry 506 541 476 536 542 541

Oct-Sep 482 491 458 505 495 486

Oct-Apr 466 498 457 489 499 497

Table 5.1: Mean IDDI values, in hundredths of a degree Kelvin over various latitudinalbands (see text for definitions), for different periods. Values representing meridionalmaxima in dust production are shown in bold.

The maximum value in the North Sahel series occurs in June and is comparable with those

in the Saharan series in March and April. From June to September, and during December

and January, the North Sahel exhibits the highest values of all the zones, indicating a

meridional maximum in dust production between 15° and 20° N. These wet season dust

maxima are consistent with the observations of N’Tchayi et al. (1997, c.f. Chapter 2). The

lowest values of all the series occur over the North and South Sahel in November, with the


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latter zone exhibiting lower values than the former. It is expected that the impact of rainfall

on vegetative cover will be greater in the South Sahel than in the North Sahel. Soil moisture

and vegetation take longer to return to their pre-wet season states further south (Hess et al.,

1996), as the role of vegetation becomes more important and soil moisture contents rise.

Rainfall impacts on vegetation will be most manifest over regions and periods usually

characterised by widespread vegetative cover. Therefore the larger these regions and the

longer the periods, the greater is the potential for changes in rainfall to alter land-

atmosphere interaction by perturbing the system from its normal state.

The mean seasonal and annual IDDI values (Table 5.1) yield information concerning the

most active dust-producing zones on longer timescales. Most importantly from the

perspective of the debate concerning whether the region of maximum dust production has

moved from the Sahara to the Sahel in recent years, the largest value for the annual

(October–September) period occurs over the North Sahel. This situation is reflected during

the wet season, JFM, AMJ and JAS, while the zone of maximum production shifts

northwards to the Sahara in OND. In AMJ, IDDI values fall over the South Sahara and rise

to a value comparable with that for the North Sahel over the North Sahara. Thus in AMJ,

there are two meridional maxima in dust production, suggesting two independent and

geographically distinct sets of deflationary processes. April is characterised by the passage

of Atlantic cyclones over the west Sahara at the end of the Moroccan wet season (Moulin et

al., 1998), which explain the high IDDI values over the North Sahara. In the North Sahel,

AMJ includes the historical period of maximum dust-event frequency (April), as well as the

period to which the annual dust maximum has shifted in some regions (June) (N’Tchayi et

al, 1997).

When the wet season is removed from the annual period to leave the October–April period,

the South Saharan signal is dominant, although the difference in IDDI values between the

South Sahara and the North Sahel is not large (0.1 K or 2%). The dry season, when analysed

as a whole, or as the early and late dry season, also yields maxima over the South Sahara.

The shift from dry season maximum over the South Sahara to wet season maximum over the

North Sahel suggests that changes in climate or land-surface associated with a general

increase in Sahelian dust production are likely to be associated with spring and summer

deflation as much as with dry season dust mobilisation. The largest percentage difference

between South Sahara and North Sahel IDDI values occurs in the wet-season (6 %), further

supporting the notion that wet-season processes contribute to the enhanced annual Sahelian

dust signal. The nature of these processes will be discussed in the following section.


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5.6.2. Locating the meridional maximum of dust production

IDDI values for the South Sahel do not exceed those of the North Sahel in any month

(Figure 5.9), suggesting that, within the 10°-20° N. band, dust production is maximum north

of 15° N throughout the year. The North Sahel band contains the northern limit of the zones

of rainfed agriculture and potential land degradation, the northernmost extent of which has

been tentatively placed at around 17° N. (see Section 5.3). It is therefore instructive to

examine IDDI values to the north and south of this limit within the North Sahel zone.

In order to locate the meridional maximum of dust production within the Sahel more

precisely, the distribution of sources between the northern and southern sections of the 15°-

20° N band was examined. Zonal averages were created for a southern band between 15° N

and 17° N. This band will contain the regions where any land degradation is prevalent. As

the limit of land degradation will vary with longitude, possibly extending north of 17° N in

places, the northernmost band was defined as the region from 18° N to 20° N, leaving a gap

of 1° between the zones. The zonally averaged IDDI values for these regions are plotted in

Figure 5.10. It is assumed that any maxima in the spatially averaged IDDI representing these

2° latitude bands which are coincident with maxima in the North Sahel for the 5° bands

represent the latitudes of maximum dust production within the latitudinal range 10°-30° N.

It may be argued that, at a 2° latitude resolution, localised zones of higher values may exist

at other latitudes, the signals of which have been lost due to the zonal averaging process. For

this to be the case these other zones would have to be sharply defined, narrow in zonal

extent and surrounded by low IDDI values. The distribution of high-value regions in the

IDDI fields suggests that this is not the case.

Figure 5.10: Mean spatially averaged IDDI values over the northern and southernextremities of the North Sahel zone. Units in hundredths of a degree Kelvin.


163

The 18°-20° N band exhibits higher IDDI values than the 15º-17º N band in July and

August. Values in the two bands are very similar in April, September and November (with

differences of less than 1 %). Throughout most of the year (January-March, May-June,

October and December) values are greater over the 15°-17° N band, indicating higher dust

loadings over the latitudes containing potentially degraded areas. In order to examine

whether these maxima within the North Sahel represent meridional maxima in dust

production over all the zones discussed, the periods in which the North Sahel exhibits the

highest IDDI values of all the 5° bands are recalled. These are June-September and

December-January. Therefore, in June, December and January, the higher values over the

15°-17° N band indicate a meridional maximum in dust production within the zone that is

potentially subject to degradation, albeit at the edge of this zone where the extent of

degradation is unclear. The groups of months exhibiting similar distributions of meridional

IDDI maxima are discussed in turn below.

At this point it is appropriate to address the implications of choosing the above two 2º

bands, rather than other such domains within the North Sahel. IDDI values over the chosen

regions were compared with those over other zones in order to test the assumption that

maximum values associated with either of these bands represent meridional maxima. IDDI

values for the 16°-18° N and 17°-19° N zones (not shown) lie between those for the 15°-17°

N and 18°-20° N zones or exhibit negligible deviations from them. Thus, considering these

other possible bands, it can still be said that the high IDDI values over the bands at the

extremities of the North Sahel zone represent meridional maxima at a 2° latitude resolution.

July and August: 18º-20º N maximum

July and August represent the peak of the wet season, when the organised lines of westward-

travelling convective disturbances (DLs) crossing the Sahel are most frequent and intense.

DLs play a major role in rainfall generation and are known to mobilise dust (Kalu, 1979).

Rowell and Milford (1993) identified DLs in August 1985 which were generated as far

north as 20° N. They found regions of enhanced DL generation just west of the Aïr

Mountains between 16° and 19° N and also around the northernmost part of the river Niger.

They state that DLs from the former region were short lived, and that DLs generated north

of about 14° N generally do not exist for more than a few hours.

The greater the convective activity of the DLs, the more likely the convective cells which

comprise them will be to transport dust to high altitudes, where it will produce a large IDDI

signal. However, the more intense the convection, the more likely the cells are to produce


164

rainfall which will remove the dust from the atmosphere. Therefore dust will be quickly

removed where the unstable monsoon layer is thick enough to allow convection to high

altitudes, and where the surface is moist enough from past rainfall to provide a moisture

supply to the convective cells. The opposing processes of convective dust generation and

rainfall washout mean that the zone of maximum IDDI will occur close to the edge of the

rainfall zone, where convection is as intense as is possible without being strong enough to

produce large amounts of rainfall. This is likely to be the case within a few hundred

kilometres of the surface discontinuity between the Saharan and the monsoon air masses,

which is located near 20° N during August (Hastenrath, 1991). Dust mobilised by the DLs in

this region may reach relatively high altitudes without being removed from the air by

rainfall, so will remain in the atmosphere for some time, resulting in a strong signal in the

mean IDDI fields. A southerly shift in the isohyets, as has been apparent in the Sahel since

the onset of dry conditions in the late 1960s (Figure 5.3), will also entail southward

displacement of the zone in which the relationship between dust mobilisation and rainfall

removal of dust particles shifts to favour high atmospheric dust concentrations.

The above conceptual model is supported by the fact that the zone of maximum IDDI values

in August (Figure 5.6) lies immediately to the north of the regions of enhanced DL

generation described by Rowell and Milford (1993). The southernmost limit of the distinct

zone where IDDI values are greater than 5 K is located at around 18° N., and the entire high-

IDDI zone is confined to the west of the Air Mountains. The shift in maximum IDDI values

from the 15°-17° N band in May and June to the 18°-20° N band in July and August is also

compatible with this model, as the zone of maximum wet-season dust loadings will migrate

with the surface discontinuity.

The reasons for the large northwards extent of the summer zone of high-IDDI values (to

some 26° N in July and August, see Figure 5.6) are not clear. DL activity is unlikely to

extend far enough north to explain the dust signals much beyond the surface discontinuity. It

is possible that advection transports dust northwards, although this would require that large

amounts of dust are transferred across the boundary between the monsoonal and Saharan air

masses, and then transported further north within the Saharan air mass. This seems unlikely,

as the prevailing motion within this air mass is towards the southwest. The DLs that bring

rainfall to the Sahel require a surface moisture source to develop fully, and are reinforced by

the dynamics of the moist air layer and northward surges of monsoonal air. However, these

DLs are triggered by African easterly waves, which may extend for some thousands of

kilometres in a north-south direction (Hastenrath, 1992; Rowell and Milford, 1993). It is


165

plausible, although speculative, that instabilities in the easterly waves give rise to DL-like

activity within the Saharan air mass, which results in meteorological conditions capable of

mobilising dust. An alternative explanation is that the northeasterly surface winds in the

Sahara are stronger in the vicinity of the surface discontinuity. Dust transport near the

discontinuity may be assisted by the enhanced vertical motion resulting from the rising of

the Saharan air above the monsoon air.

December, January and June: 15º-17º N maximum

The monthly IDDI fields (Figure 5.6) indicate that the 15º-17º N band contains the southern

regions of the Bilma-Faya-Largeau source region and the sources to the south of the Aïr

Mountains. These sources are most active from December to February. As discussed earlier

in this chapter, the former area is a well-known dust source, and the latter sources are likely

to be the consequence of pluvial processes in highland regions. At these latitudes, intense

rainfall events are characteristic of the summer months, but annual rainfall amounts are

relatively low. A possible explanation for the maximum in dust production in some months

in this zone is that the balance between rainfall erosion and vegetation cover is such that

summer production of erodible material by fluvial processes is at a maximum in this zone.

While an anthropogenic influence cannot be discounted, the mean relationship between

rainfall and land cover may therefore be sufficient explanation for the maximum in dust

production in this band. Dust concentrations will be kept low during the summer months by

wet deposition, and the erodible material will undergo the most significant transport as a

result of winter mechanisms operating in a dry atmosphere. In June, a combination of

intense mobilisation events related to convective activity (DLs) and relatively bare soils

(before the summer vegetation becomes established) is likely to be behind the meridional

maximum in dust concentrations.

February, March, May and October: Local maximum at 15º-17º N

In February, North Sahel IDDI values are similar to those for the South Sahara, which

represent a meridional maximum in dust concentrations at a 5º-latitude resolution. A similar

situation exists in March, although the differences between the North Sahel and the South

Sahara are somewhat greater, and the North Sahara values are much greater than in

February. In October, dust concentrations are greatest over the Saharan regions, with very

similar values for the North and South Sahel. Thus, in these three months, the general trend

is for dust concentrations to decline from the South Sahara to the South Sahel. However,

superimposed on this general decline is an increase in dust concentrations over the band


166

from 15º-17º N. This is indicative of a zone of increased dust production, the signal from

which is superimposed on the regional trend of decreasing dust concentrations away from

the southern and central Saharan regions, from which dust is advected by the Harmattan.

The monthly fields indicate strong Saharan sources in February and March, with high

activity also occurring in the Bilma-Faya-Largeau region. The reasons for the local

meridional dust maximum are therefore similar to those behind the regional maximum in

December and January. High activity is also apparent in the eastern Sahel-Sahara sources,

which extend to the 15º-17º N zone. A reactivation of the Bilma-Faya-Largeau sources is

apparent in May, with maximum activity between about 14º and 17º N. Although the IDDI

signal in this region is weaker than in December and January, the central Saharan sources

are relatively inactive in May. The pattern of source activity in October is similar to that in

January and February, albeit on a much reduced scale in terms of intensity and geographical

extent of dust production.

Summary

In January, May and June, the meridional maximum in dust production appears to lie within

the zone that may be characterised by some degree of land degradation. It is possible that the

volumes of airborne dust originating in the 15°-17° N are augmented by deflation from

degraded soils. It is also possible that material from degraded soils makes a large enough

contribution to the dust budget of the region to cause the meridional maximum in dust

production. Degraded soils may be more susceptible to deflation in May and June than in

most other months because of the prevalence of deflationary meteorological processes

associated with early DLs. This susceptibility will continue into the JAS period, when these

processes will be more effective, but when levels of dust will be kept low by increased

rainfall washout. Increases in vegetation cover as the summer progresses are likely to reduce

dust mobilisation. During July and August the meridional maximum of dust production is

located between 18° and 20° N. As this band lies outside the zone of potential degradation it

is concluded that dust mobilisation here is a response to the level and nature of the DL

activity.

This interpretation suggests that caution should be applied before attributing the May/June

meridional maximum in the 15°-17° N zone to soil degradation, as the deflationary

processes (related to DL activity) will be of maximum efficacy in this zone in these months.

However, the state of the soil will affect the response of the land to such processes. The fact

that higher IDDI levels are observed over the 15°-17° N zone for eight out of twelve months,

regardless of the location of the meridional IDDI maximum, implies that dust concentrations


167

are higher in the marginal zone characterised by some human impact on the land surface

than in the unutilised zone representing the Sahel-Sahara transition zone. Several possible

factors that might be responsible for this phenomenon are postulated:

i. Removal of vegetation and disturbance of topsoil by human activity may reduce the

cohesion of the soil and increase its vulnerability to deflation.

ii. Dying off of vegetation in response to dry conditions may have a similar, although less

dramatic, effect to human activity.

iii. Higher rainfall levels than in the more northerly zone may cause increased water

erosion, ensuring a constant supply of erodible material. This process may act on

undisturbed soils, particularly after one or more drought years when vegetation cover

has been reduced and the organic content of the soil diminished. Rainfall on loose, dry

soils will enhance their erodibility still further. The impact of such water erosion is

likely to depend on the soil state, the intensity of the rain (i.e. droplet size) and the

timing of the rainfall. Rainfall that is sustained over a period of weeks or months will

initially enhance erosion, but will ultimately stabilise the land surface by encouraging

vegetation cover. Isolated rainstorms will cause significant erosion without otherwise

altering the land surface. Rainfall events, flash floods and ephemeral river flow are

important mechanisms of sediment mobilisation in drylands (Baird, 1997; Reid and

Frostick, 1997).

Although the processes described in point (iii) above will have a greater impact on degraded

or desiccated soils, they will also be a naturally occurring feature of the climatically

marginal extremities of a monsoonal regime such as that characterising West Africa. The

southward shift in the isohyets over the course of the late twentieth century desiccation is

likely to be associated with a southward movement of this marginal zone, which will entail a

similar shift in the zone in which pluvial and geomorphological processes are associated

with significant dust production throughout most of the year, and with elevated dust

concentrations in the wet season.

5.6.3. Commonality of Sahelian and Saharan dust loadings

The above results are not incompatible with the notion that at least some of the dust

produced in the Sahel zone is the result of soil degradation. However, the seasonal

variations in dust levels appear to reflect the migration of meteorological conditions, most

notably the surface discontinuity associated with the movement of the ITCZ. For six months


168

of the year dust loadings are greatest south of 20° N. During four of these six months the

meridional maximum of dust production is located in the zone from 15° to 17° N, while for

the remaining two months this maximum lies between 18° and 20° N. Thus it appears that

much of the annual dust production in northern Africa occurs in the zone including the

northern limits of human activity and the transition zone between the Sahel and the Sahara,

but south of the hyper-arid desert regions. It is uncertain to what extent dust from this region

is mobilised from soils that have been degraded through human activity (such as

overgrazing), past agricultural activity or climate-induced desiccation, although the role of

the last of these processes is likely to be significant. In order to ascertain the degree to which

soil degradation has affected dust production in this and more southerly regions, field

studies would be required. However, the IDDI data allow us to examine the extent to which

variations in dust production in these marginal regions reflect those in regions where soil

degradation is unlikely to be an important factor in deflation. These latter regions are those

in the interior of the Sahara, where rainfall and human/animal impacts are negligible.

In order to achieve a comparison of dust variability over different latitudinal zones, time

series of IDDI values averaged over the different zones described in the previous section

were correlated with each other. Each correlation was between a pair of series representing

the same period or month. In order to minimise the likelihood of high correlations resulting

from single, spatially continuous source regions straddling the boundaries between zones,

indices representing adjacent zones were not correlated. The statistical significance of the

correlations was tested using the method of Ebisuzaki (1997), which accounts for

autocorrelation in the timeseries (see Chapter 3). The resulting correlations are presented

below in Tables 5.2 and 5.3.

When IDDI indices representing periods longer than one month are correlated between the

various zones, statistically significant results are particularly notable in AMJ (Table 5.2).

Relationships in this period are also likely to be responsible for part of the signal

represented by the significant results for the wet season (May-October) and for the annual

period January-December. An April signal may also be reflected in some of the late dry

season (January-April) results. The lack of significant correlations in the dry (November-

April), early dry (November-December) and OND periods may reflect a decoupling between

the Sahelian and Saharan regions due to the fact that, in the period immediately following

the wet season, Sahel dust production is significantly influenced by the soil state as

determined by rainfall. This influence could be in the form of soil moisture content and/or

vegetation coverage and state, and could include an anthropogenic component.


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Regions for which correlations were calculated

Period S. Sahel -

S. Sahara

S. Sahel -

N. Sahara

N. Sahel -

N. Sahara

15-17°°°°N -

S. Sahara

15-17°°°°N -

N. Sahara

18-20°°°°N -

N. Sahara

JFM 0.43 0.24 0.21 0.16 -0.04 0.48

AMJ 0.90* 0.58* 0.58 0.95* 0.64* 0.50

JAS 0.50 0.41 0.62 0.02 0.06 0.80

OND 0.62 0.11 0.00 0.62 -0.14 0.14

Wet 0.63* 0.64* 0.68 0.87* 0.63 0.66

Dry 0.60 0.40 0.03 0.29 -0.04 0.12

Early Dry 0.36 0.24 0.18 0.56 0.02 0.30

Late Dry 0.56* 0.54* 0.62 0.29 0.35 0.83*

Oct-Apr 0.76 0.44 0.17 0.45 0.06 0.28

Oct-Sep 0.86* 0.63 0.38 0.57 0.18 0.48

May-Apr 0.72 0.63 0.50 0.58 0.34 0.62*

Jan-Dec 0.69* 0.56* 0.45 0.32 0.14 0.67

Table 5.2: Correlations between series of yearly IDDI indices, representing variousperiods, over different latitudinal zones, for 1984-1993. Correlations significant at the5% significance level are shown in bold; those significant at the 1% level are markedwith an asterisk.

The monthly-index correlations show a less coherent pattern than the aggregated period

results (Table 5.3). The largest number of significant results occurs in May, and there is,

arguably, a clustering of significant correlations around the March-May period. The

relationship between the North Sahel and the North Sahara in July and September is

plausibly due to African easterly waves which will be manifest as DL activity within the

monsoonal air mass. The correlation between the South Sahel and South Sahara in August is

also likely to be due to DL activity; both these regions will be characterised by the edges of

the zone in which DLs are generated (Rowell and Milford, 1993).


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Regions for which correlations were calculated

Month S. Sahel –

S. Sahara

S. Sahel –

N. Sahara

N. Sahel –

N. Sahara

15-17°N –

S. Sahara

15-17°N –

N. Sahara

18-20°N –

N. Sahara

Jan 0.54 0.18 0.57 0.72* 0.34 0.71*

Feb 0.53 0.45 0.49 0.44 0.49 -0.41

Mar 0.48* 0.22 -0.12 -0.09 -0.14 -0.05

Apr 0.75* 0.35 0.30 0.74* 0.36 0.24

May 0.76* 0.57* 0.53 0.86* 0.46 0.52

Jun 0.68 0.40 0.27 0.62 0.33 0.17

Jul 0.26 0.12 0.89* 0.46 0.78 0.84*

Aug 0.64* 0.44 0.01 0.18 -0.16 0.08

Sep -0.28 0.10 0.93* 0.23 0.57 0.92*

Oct 0.34 0.53 0.25 0.77 0.19 0.30

Nov 0.50 0.19 0.18 0.71* 0.10 0.26

Dec 0.65* 0.53 0.45 0.63 0.30 0.57

Table 5.3: Correlations between series of yearly IDDI indices, representing individualmonths, over different latitudinal zones, for 1984-1993. Key as for Figure 5.2.

Correlations were also calculated between the IDDI-index timeseries calculated over the

10°-19° N. and 21°-30° N zones, which represent the aggregated Sahel and Sahara

respectively. A gap of 2° latitude was left between the zones in order to reduce the effect of

coherent regions of IDDI overlapping the two zones. The resulting correlations are shown in

Table 5.4. As with the narrower latitudinal bands described above, strong correlations are

apparent in the AMJ season, and in the individual months comprising this season. These

relationships are probably largely responsible for the high wet season correlation, and

possibly for the late dry season result. They also offer an explanation as to why the January-

December annual period exhibits a significant result, whereas the May-April annual period

does not. The former period contains the AMJ period whereas the latter period starts a third


171

of the way through it, distributing each coherent, continuous AMJ period of high

correlations between two twelve-month periods. Although the October-September annual

period, which also contains the AMJ season, does not exhibit a significant result, the

correlation is high. It is possible that this high correlation represents a real relationship but

was not classified as significant due to high autocorrelation in the timeseries.

a.

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

0.57 0.56 0.07 0.67* 0.87* 0.89* 0.63 0.41 0.47 0.60 0.48 0.65

b.

JFM AMJ JAS OND Wet Dry EarlyDry

LateDry

Oct-Apr

Oct-Sep

May-Apr

Jan-Dec

0.28 0.92* 0.55 0.35 0.86* 0.40 0.42 0.58* 0.50 0.72 0.63 0.63*

Table 5.4: Correlations between series of yearly IDDI indices representing theaggregated Sahel and Sahara zones, for (a) individual months and (b) periods ofbetween two and twelve months duration. Key as for Figure 5.2.

The frequency of significant correlations between the various zones described here suggests

that the mechanisms of dust production are often large-scale in nature, extending throughout

Sahelian and Saharan latitudes. The fact that the overwhelming majority of correlations are

positive also suggests that there exists a systematic commonality to the data representing

dust levels over the various latitudinal zones. A significant degree of commonality in dust

loadings may be due to advection of mineral aerosols from the Sahara over the Sahel.

However, it is difficult to explain correlations between these two regions in terms of

advection for those periods when the majority of production occurs in the southernmost of

the zones being correlated, as advection is generally towards the south and west. During the

boreal summer, correlations are apparent between regions under the influence of two

different air masses: advection of dust from the northern Saharan airmass into the southern

monsoonal airmass is unlikely, although a Saharan signal may result from dust-laden

Saharan air overlying the monsoonal airmass to the south.

However, the significant correlations between latitudinal zones are not ubiquitous, meaning

that zonal variations in dust production are significant. The decoupling of the Saharan and


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Sahelian dust signals is evident in those periods when significant correlations between

Saharan and Sahelian zones are infrequent or non-existent. Such a period is that immediately

following the Sahel wet season, suggesting that rainfall does have an impact on dust

production. This is in keeping with the findings of other authors who have noted elevated

dust levels in air originating over northern Africa after dry episodes in the Sahel (e.g.

Prospero and Nees, 1986). The decoupling of Saharan and Sahelian dust signals in

individual years is discussed further in the following section.

5.7. Interannual variability of the IDDI

Interannual variability of dust production in zones located in the Sahel-Sahara region was

examined by plotting the timeseries of IDDI indices representing selected yearly or sub-

yearly periods for these zones (Figures 5.12 to 5.15). The timeseries used were those

employed in the correlation analysis described in the previous section. In this section

selected timeseries are plotted in the form of standardised anomalies with respect to the

period 1984-1993 for each series. For each period (e.g. wet season, AMJ), the timeseries

representing mean IDDI over the aggregated Sahel and Sahara zones are presented.

Timeseries for the two narrower zones (e.g. South Sahel, North Sahara) which exhibit the

strongest commonality (see section 5.5), or which might best serve to illuminate the

processes driving the generation of dust, are also plotted in each case. Individual monthly

anomalies for the aggregated Sahel and Sahara only are also presented (Figures 5.16 and

5.17). For each period for which timeseries are plotted, years containing particularly large-

magnitude anomalies are noted. IDDI and climatological data from these anomalous years

will be used to produce composite fields representing high and low dust years in Chapter 6.

As the following sections contain some discussion of the relationships between dust

loadings and rainfall, rainfall anomalies for the period 1983-1993 are plotted in Figure 5.11

(below). 1983 is included because of its potential impact on dust production in the Sahel

during 1984. Both annual and August anomalies are shown: most of the variability in

Sahelian rainfall is due to variations in August-September rainfall totals (Nicholson and

Palao, 1993), and August is the month of maximum rainfall. Discussions of dust-rainfall

relationships based only on short series of anomalies must be fairly speculative. However,

such speculation is employed in order to form hypotheses concerning dust-climate

interactions that will provide a context for the investigations described in the following

chapters.


173

The three driest years in the Sahel between 1984 and 1993 were, in descending order of

aridity, 1984, 1987 and 1990 (Figure 5.11). The three wettest years in the same period were,

in order of decreasing rainfall anomaly magnitude, 1988, 1989 and 1991. Only 1988

exhibited annual rainfall above the twentieth century mean, and the 1988 anomaly was only

marginally greater than zero.

Figure 5.11: Rainfall anomalies for the spatially aggregated Sahel (10°°°°-20°°°° N; WestAfrican coast - 30°°°° E) based on the mean for the period 1983-1993. Units are standarddeviations.

5.7.1. Annual IDDI anomalies

The annual IDDI anomalies were created for the period from October to September. This

period was chosen in order to capture a signal characterising a twelve-month period

beginning at the end of the wet season. Although such a period will capture the effects of

two wet seasons, it will contain a dry season that is subject to the influence of a single year’s

rainfall, if cumulative effects are neglected. Figure 5.12 shows that the Sahelian anomalies

tend reflect the Saharan anomalies from the 1985/86 12-month period onwards. However,

although the correlation between the two timeseries is high (0.72) it is not statistically

significant at the 5% level. The apparent correspondence is particularly strong between the

South Sahel and the South Sahara, and the correlation rises to 0.86 between these two zones,

significant at the 1% level.


174

Figure 5.12: Standardised anomalies of IDDI values averaged over twelve monthperiods from October to the following September, then spatially averaged for specifiedregions (see text for details.) Anomalies are with respect to the 9-year mean of annualaverage IDDI values.

Over the period for which data are available, the largest positive annual IDDI anomaly for

the Sahel occurs in 1984/85, immediately after the very dry year of 1984 (the driest year for

the aggregated Sahel this century). The other two largest positive anomalies occur in

1987/88 and 1990/91, following the two next driest years in the 1984-1993 period. This

pattern is slightly stronger in the South Sahel, where both rainfall and vegetation cover are

greater and therefore likely to play a larger role in determining land-surface properties.

However, the largest magnitude negative IDDI anomalies in the Sahel occur in 1985/86,

1989/90 and 1991/92. The first and last of these periods immediately follow those in which

IDDI is at a maximum following very dry summers. The obvious inference to be drawn from

this is that the intervening wet seasons of 1985 and 1991 have led to a recovery in soil

cohesion and vegetation cover, leading to a land-surface less vulnerable to deflation.

However, both these years are characterised by relatively low rainfall. The deficit in 1985 is

of considerable magnitude, and precedes the least dusty 12-month period in the series. Four

possible interpretations of these anomalies are postulated:

i. Even relatively low rainfall amounts may be sufficient to prompt a recovery in soil

cohesion and protection by vegetation. It is likely that the response of vegetation to

rainfall variations is not linear, and that a rainfall threshold exists, below which soil

becomes particularly vulnerable to deflation. Such a threshold is likely to be

determined by the amount of moisture required for vegetation to exhibit significant

growth during the wet season. It is possible that this minimum-rainfall threshold was

breached in 1984, 1987 and 1990, but not in other years in the 1984-1993 period.


175

These three dry years all exhibit rainfall deficits in excess of 1.8 standard deviations

from the 1901-1996 mean. The next largest deficit occurred in 1985 and had a

magnitude of approximately 1.5 standard deviations. This would suggest that any

hypothetical “vulnerability threshold” would lie between 1.5 and 1.8 standard

deviations if measured in terms of rainfall deficits from the twentieth century mean. Of

course such an approach does not account for spatial variations in rainfall, and it

would be desirable to perform such determinations of vulnerability thresholds on

smaller spatial scales. Such determinations would need to be verified by field

measurements, and would require more years of IDDI data than are available at

present.

ii. The differences in the sign of anomalies in dry years may be the result of different

spatial patterns of drought. If the 1985 and 1991 rainfall deficits are the result of more

localised drought conditions than occurred in 1984 and 1990 it is likely that other

regions experienced enough rainfall for a recovery in the soil and vegetation to occur

which stabilised the soil, reducing deflation. This is especially likely if large-

magnitude rainfall anomalies in 1985 and 1991 occurred in regions away from the

major dust sources.

iii. It is possible that the majority of vulnerable material in Sahelian regions is removed by

deflation in the months following the wet season. If no new erodible material is

created before the following dry season deflation will be minimal, even after a

particularly dry summer. Water is an important agent for the concentration of erodible

material in environments where deflationary processes are prevalent (Middleton,

1997). Hence after two consecutive dry summers dust levels will be low, most of the

erodible material having been removed after the first dry summer. This hypothesis

provides a plausible model for the periods 1984-1986 and 1990-1992, when large

positive IDDI anomalies in one 12-month period are followed by notable negative

anomalies in the next 12-month period.

iv. The relatively high degree of commonality between Sahelian and Saharan IDDI

anomalies suggests that large-scale processes and phenomena connected with the

atmospheric circulation may exert a common influence on both regions. These

processes might dominate over rainfall influences and be responsible for the pattern of

anomalies, with large anomalies after dry summers being coincidental. It is plausible

that at least some of the apparent commonality between the Sahel and Sahara is due to

advection from the latter to the former. Advection is probably responsible for the


176

relatively low background field of non-zero IDDI values which prevails throughout the

year. However, the discrete and pronounced localised regions of high IDDI apparent in

the mean monthly fields are indicative of areas coinciding with or close to sources,

suggesting that the strongest signals are characteristic of recently mobilised dust,

rather than dust which has been advected very large distances. Theoretical and

observational considerations indicate that both particle size and aerosol density will be

greater closer to source regions (e.g. Gillies et al., 1996), producing a large IDDI

signal as the result of both scattering of shortwave radiation (although the mean

particle size will be high, concentrations of sub-micron particles will be high) and

attenuation of longwave radiation. The fact that the highest zonal IDDI values

commonly occur in the northerly Sahelian latitudes also suggest that the zonal IDDI

signals are responses to generation rather than large-scale advection; if dust over the

Sahel originated in the Sahara, we should expect the highest dust loadings over the

latter region, close to the sources.

5.7.2. Wet season IDDI anomalies

Figure 5.13: Standardised anomalies of IDDI values averaged over a liberally definedwet-season from May to October, then spatially averaged for specified regions (see textfor details.) Anomalies are with respect to the 10-year mean of seasonal average IDDIvalues.

Wet season (May-October) IDDI anomalies are presented in Figure 5.13 for the aggregated

Sahel and Sahara, and also for the South Sahel and North Sahara. The latter two regions are

chosen due to the fact that their IDDI indices are significantly correlated (see Table 5.2), and

the fact that they are separated by some 10° latitude. The higher correlation between IDDI

indices for the 15°-17° N and South Sahara zones may be explained by the fact that both


177

these zones are characterised by the mobile band of high IDDI values around and to the

north of the surface discontinuity associated with the summer position of the ITCZ. The

correlation between the South Sahel and South Sahara may also be explained in this manner,

although any teleconnections that exist between the Sahel and Sahara may also contribute to

the apparent relationship.

The large separation of the South Sahel and North Sahara further precludes advection as a

linking factor (especially since the relationship of each region’s zonal IDDI with that of the

closer non-adjacent region is weaker). This suggests a possible atmospheric teleconnection

between the two zones, resulting from the regional circulation, provided the validity of such

a statistical comparison of two such short timeseries is accepted.

The most notable anomaly in the Sahel (aggregated and South) is the large positive anomaly

of 1991. Although characterised by a rainfall deficit relative to the twentieth century mean,

1991 was the third wettest year in the 1984-1993 period for which IDDI data are available.

Only 1988 and 1989 were wetter, with 1988 being the wettest. These are the only other

years to exhibit positive IDDI anomalies in the South Sahel. Anomalies are also positive,

although small, in the aggregated Sahel. In this region the anomalies for 1987 and 1988 are

similar, despite the fact that 1987 was very dry and 1988 relatively wet. In the South Sahel,

1987 exhibits a small negative anomaly. Positive Saharan anomalies are greatest in 1988 and

1991.

The largest magnitude negative anomalies in all four regions occur in 1985 and 1990, years

characterised by large rainfall deficits which follow a very dry year and a relatively wet year

respectively. The wet-season IDDI anomaly for 1984, the driest year this century in the

Sahel, is negative and small in the South Sahara and positive but near-zero for the other

regions.

The pattern of wet season IDDI anomalies suggests that dust production is not a simple

function of rainfall. If any pattern is evident from this short timeseries of anomalies, it is that

there is a tendency for wet years to be characterised by dusty summers, and dry years to

exhibit low summer dust loadings. These findings are consistent with the argument that

summer dust production is largely due to activity related to African Easterly Waves,

particularly to DL activity in the Sahelian, and possibly southern Saharan, regions. The

interpretation that summer dust production is controlled by such large-scale phenomena that

may span many degrees of longitude and latitude is supported by the fact that there are

striking similarities between the Sahelian and Saharan wet-season IDDI anomaly series.


178

Note the statistically significant correlation of 0.86 between the wet season IDDI indices for

the aggregated Sahel and Sahara zones.

For dust levels to be positively related to DL activity, the dust-raising activity of the DLs

must dominate over the removal of dust by rainfall, the amount of which is related to the

frequency of DLs of intermediate to high intensity (Lamb et al., 1998). Therefore a

theoretical rainfall threshold may be postulated, above which the washout of dust by DL-

induced rainfall dominates over vertical dust transport by DL-related convective

disturbances. This suggests that the nature of the relationship between summer dust loadings

and DL activity will depend on the aridity of the region in question, or the amount of rainfall

that the DLs generate. Lamb et al. (1998) present evidence that the decline in rainfall over

the Sahel since the l950s has coincided with a general decrease in the frequency of large and

well organised (and intense) DLs, and an increase in the frequency of small and

disorganised (and weak) DLs. It may be speculated that at least part of the increase in dust

production over the past few decades is due to a change in the ratio of mobilisation to

washout, which is a result of the changes in the nature of the DLs. Lamb et al. (1998) also

report an increase in the post-1965 frequency of DL absence. Periods characterised by

weaker DLs may be characterised by lower rainfall and elevated dust levels for the reasons

outlined above, provided the DLs are still strong enough to result in deflation. Periods of DL

absence are likely to be marked by reductions in both rainfall and atmospheric dust loadings

for similar reasons.

This conceptual model would be consistent with increased dust aerosol levels over the

Sahel, where the decline in rainfall effects the deflation/washout ratio, and also with

unchanged or reduced levels of dust over the Sahara. As rainfall over the Sahara is

negligible, the deflation/washout ratio will be unaffected. However, the occurrence of fewer

(or of generally weaker) DLs may lead to a reduction in dust generation over the Sahara,

without these changes being offset by reduced washout. This model is consistent with the

observations of N’Tchayi et al. (1997), who have observed a decrease in the frequency of

dust events at some Saharan sites (c.f. Chapter 2). Although a detailed analysis of the

frequency, distribution and intensity of DLs is outside the scope of this thesis, the

relationship between easterly wave activity and dust production will be assessed in a more

quantitative fashion in Chapter 6.


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5.7.3. Early dry season (November-December) IDDI anomalies

IDDI values for the Sahel over the November-December period should be more highly

dependent on rainfall in the previous wet season than IDDI values in other periods, as

vegetation and soil moisture content (both determined by the amount of rainfall in the

previous few months) will not have reached their minimum extent and level respectively.

Land surface properties will therefore retain a wet season “signature”. None of the Sahara-

Sahel pairs of zonally averaged anomalies are significantly correlated, suggesting that the

preferential impact of rainfall on the Sahelian soils acts to decouple dust production in this

region from that in the Sahara. The lack of commonality is reflected in the series of yearly

anomalies, although some similarities between the Sahel and Sahara are apparent (Figure

5.14). The impact of the 1984 drought in the Sahel is evident from the large positive

anomaly apparent for this year in the Sahel IDDI series, contrasting with a negative anomaly

in the Sahara series. The South Sahel and South Sahara series are also presented in order to

provide a comparison between a rainfall dominated region and an arid region.

Figure 5.14: Standardised anomalies of IDDI values averaged over the early dry season(November-December) which immediately succeeds the wet-season, then spatiallyaveraged for specified regions (see text for details.) Anomalies are with respect to the10-year mean of the bi-monthly average IDDI values.

The most striking aspect of the Sahel series is that anomalies are consistently positive from

1984 to 1988, after which they are negative or (in the case of the aggregated Sahel in 1992)

barely exceed zero. Analysis of individual monthly IDDI anomalies (Figure 5.17)

demonstrates that this change in the IDDI series is due to an even more pronounced change

in the December values. The short length of the series means that caution is required in

assigning any significance to these results. However, a tentative interpretation is that soil


180

cohesion underwent a recovery as a result of the cumulative effects of the relatively wet

summers of 1988 and 1989. Although the 1989 rainfall anomaly was negative, the deficit

was small, and it is plausible that there was enough rain to reinforce a recovery prompted by

the positive rainfall anomaly of 1988. The fact that the November-December IDDI anomaly

in 1988 was positive suggests that this single wet year was insufficient to cause a recovery

in soil structure. An alternative, and not incompatible, interpretation is that relatively

vigorous rainfall acting on degraded soils produced a large amount of deflatable material

which was removed in the subsequent dry season, causing relatively high dust loadings over

the Sahel in late 1988. However, before the negative IDDI anomaly of 1989 is ascribed

wholly to a rainfall-induced recovery of degraded soils, it should be noted that large

negative anomalies are also evident in the Sahara in 1989, suggesting a possible explanation

involving large-sale aspects of the region atmospheric circulation. This interpretation is

strengthened by the fact that the large negative anomaly over the Sahara occurs within a

series of consecutive positive anomalies, from which it represents a significant departure.

Such large-scale processes are probably confined to 1989, as suggested by the return of the

Sahara to positive anomalies in 1990, and by the contrary nature of the Saharan and Sahelian

signals in 1990 and 1991.

5.7.4. Late dry season (January-April) IDDI anomalies

Figure 5.15: Standardised anomalies of IDDI values averaged the late dry season(January-April), then spatially averaged for specified regions (see text for details.)Anomalies are with respect to the 10-year mean of January-April average IDDI values.

The impact of one summer’s rainfall on the following late dry season dust production is

uncertain, and likely to be complex. Around the beginning of the calendar year the moisture


181

content of the soil will have diminished to the point at which it plays a negligible role in

determining the cohesive properties of the soil. It is possible that the previous year’s rainfall

has an indirect effect on soil cohesion via the amount of organic debris resulting from the

decay of vegetation. This notion is supported by the existence of a dramatic peak in the

IDDI anomaly series in this period for 1985 (Figure 5.15), after the severe drought of 1984.

However, this phenomenon is not apparent after other very dry years, suggesting that the

effects of drought on dust production in this period may be cumulative. In other words the

dust production cycle is likely to be quite robust during the first few months of the year,

with rainfall impacts only becoming apparent after a number of consecutive dry summers.

Persistent drought may lead to a reduction in soil stability via the cumulative effects of

drought stress on vegetation and consequently on the organic matrix of the soil. The

relatively small magnitude of the IDDI anomalies (excepting 1985) when compared with the

other periods discussed here suggests that the mechanisms that control dust production

during this part of the year are not as variable as those which determine production at other

times. As well as the direct effects of the previous year’s rainfall being minimal, so will be

the effects of variability of DL activity, as DLs are largely confined to the wet season. The

Sahel-Sahara zone will be predominantly influenced by the large-scale Harmattan

circulation, and it is likely that changes in dust production will be dependent on variability

in Harmattan wind strength. More specifically, production will depend on the frequency

with which the wind exceeds the threshold velocity required for deflation to occur. This will

depend on the properties of the soil, allowing for the influence of drought and degradation

on soil cohesion.

It should be remembered that this period is characterised by high dust loadings throughout

the Sahel-Sahara zone, and is the dustiest period in the Sahara. The frequency of dust

mobilisation events and the amounts of dust in the atmosphere are likely to be high enough

to ensure that factors which might be important in determining the variations in dust levels

in less dusty periods are of relatively little importance.

5.7.5. Individual monthly IDDI anomalies

When monthly IDDI anomalies are plotted by year (Figure 5.16), extended periods with

sustained low or high IDDI values, and hence dust loadings, are apparent. The most notable

of these are discussed below, in chronological order.

In the Sahel the period from September 1984 to April 1985 exhibits large positive IDDI

anomalies, apart from in January 1985, which is characterised by a near-zero anomaly. This


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is most likely to be a manifestation of the immediate and cumulative effects of the drought

that culminated in the record 1984 rainfall deficit.

Figure 5.16: Standardised anomalies of monthly IDDI over the Sahel and Sahara.Standardisation is performed using the mean and standard deviation for the seriesrepresenting each individual month.


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The first half of 1986 is characterised by negative IDDI anomalies in both the Sahel and

Sahara, suggesting that large-scale circulation mechanisms (probably related to the strength

of the Harmattan winds) are responsible for dust levels over this period.

July, August and September 1988 exhibit notable positive anomalies over the Sahel and

Sahara. These are the wettest three months of the year, reinforcing the hypothesis that

summer dust production is largely the result of DL activity which is in turn associated with

rainfall. The anomalies are greater over the Sahara, suggesting that the role of the DLs in

mobilising dust in the Sahel is offset by washout of the dust from the atmosphere by rainfall.

March to August 1991 in the Sahel, and March to July 1991 in the Sahara, are characterised

by persistently positive and often large anomalies. May 1991 stands out as a particularly

dusty month over both regions. The negative IDDI anomalies in January and February, and

the common pattern between the zones, suggests that the large-scale circulation is likely to

be responsible for the nature of the anomalies.

1992 is similar in some respects to 1986, in that IDDI anomalies are generally negative in

the first half of the year in the Sahel, and until August in the Sahara

Figure 5.17 presents the same monthly IDDI anomalies as Figure 5.16, but arranged by

month rather than year. Although not a great deal of new information can be gleaned from

this alternative format, it is useful in that it allows us to identify months which are

particularly anomalous in relation to the same month throughout the ten-year series. Such

months are candidates for studies based on comparisons of IDDI anomaly fields with

anomaly fields of other climatological variables. Such studies should provide information

concerning the mechanisms that are responsible for particular patterns of dust loadings over

the Sahel and Sahara. Anomalous months are identified as those which exhibit intermediate

to large magnitude anomalies over both the Sahel and the Sahara. Generally a large-

magnitude anomaly over one region is reflected by an anomaly which is of the same sign

and of a significant magnitude over the other region. The data in table 5.7 are used in the

following chapter to identify months of high and low IDDI loadings from which to create

composite IDDI fields for comparison with climatological data representing the same

periods.


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Figure 5.17: Standardised anomalies of monthly IDDI over the Sahel and Sahara (as inFigure 5.16), plotted for each month.

5.8. Summary

The IDDI provides useful information concerning the temporal and spatial distribution of

dust loadings, which allows us to identify the major sources of mineral dust in Africa. These

sources show a high degree of seasonality, which is indicative of seasonal shifts in the

regional atmospheric circulation. Mean monthly IDDI fields dramatically demonstrate the

seasonal evolution of North African dust sources, illustrating the importance of the northern

and central Sahelian latitudes from December to March and in May and June, and of the

Sahara from February to May. A shift of dust production from the central Sahel in May to

the west Sahel-Sahara in July and August is apparent. The degree to which regions of high


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summer dust loadings are geographically constrained by the position of the surface

discontinuity between the monsoonal and Saharan air masses is striking.

There is a tendency for dust levels over Sahelian regions to reflect those over the Sahara at

certain times of the year, particularly during the spring and summer. There is a significant

amount of evidence to suggest that the major determinant of dust loadings in these periods is

the amount of disturbance line (DL) activity. However, the results also suggest that dust

generation mechanisms over Saharan and Sahelian regions may become decoupled under

certain conditions, particularly when persistent drought acts to preferentially enhance the

erodibility of Sahelian soils. This is particularly evident for the two months immediately

following the end of the wet season; the November-December period is the only time during

which no significant correlations are apparent between zonally averaged IDDI for the Sahel

and Sahara regions examined in this study.

It is speculated that at least some of the observed increase in dust levels over the past few

decades may be related to changes in the nature of the rain-producing DLs. The relationship

between DL activity and dust levels over the Sahel in summer will depend on the amount of

wet deposition resulting from rainfall. This in turn will depend on the frequency of rain

events, i.e. on the aridity of the region. It is possible that observed changes in DL activity

have led to a situation in which dust mobilisation has remained relatively constant while

dust-removal processes have become less effective. Of course dust mobilisation may have

increased, or even diminished – what is important is the relative roles of mobilisation and

removal processes.

Dry season Sahelian dust concentrations are likely to have increased in part as a result of the

southward shift of the pluvial and geomorphological zones characteristic of the boundary

between the semi-arid Sahel and the arid Sahara. Within this zone, the ratio of rainfall

erosion of soils to rainfall stabilisation of soils (via the initiation of vegetation growth) will

be high relative to the wetter regions further south. Whether a shift in this ratio constitutes

land degradation or desertification is arguable. Tucker et al. (1991, 1994) and Nicholson and

Tucker (1998) have found that vegetation extent in the Sahel varies considerably on an

interannual timescale in response to rainfall (c.f. Chapter 2), and does not constitute

systematic desertification or land degradation. Similarly, variations in dust production may

be largely a manifestation of the interannual variability, with the increases in dry-season

aerosol concentrations being partly due to the increased number of dry years since the

1960s, and the consequent prevalence of desert-boundary type land-atmosphere interactions.

Of course, the response of the surface geomorphology to climate will be less instantaneous


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than that of vegetation, and the removal of soil material is not necessarily reversible in the

short term, so the dry season dust response to interannual rainfall variability will be more

complex than that of vegetation, with rainfall impacts on dust production manifesting

themselves over several years rather than any single season.

The hypothesised changes described above will ultimately also be a result of the weaker wet

season convective events. These may be the result of a southwards shift in the trajectories of

the DLs, or of a reduction in their meridional extent, with the weaker convection associated

with the edges of these systems being responsible for reduced rainfall in the Sahelian

margins. However, Lamb et al. (1998) report a general decline in the frequency and intensity

of such systems, and the work reviewed in Chapter 2 suggests that reduced rainfall is

associated with more complex climate changes than a simple southwards shift in climatic

zones.

Evidence for such climatic changes also suggests the possibility of changes in the

mechanisms of dust mobilisation and transport throughout the year, and changes in rainfall

are likely to be only a partial explanation for increases in atmospheric dust loadings. The

commonality of IDDI indices over Sahelian and Saharan regions, and the low variability of

January-April IDDI in the Sahel, suggest that dust production in the Sahel during the early

part of the calendar year is determined by the large-scale circulation rather than the

condition of the Sahelian soils. Exceptions to this general rule may occur after several years

of extreme drought.

Analysis of timeseries of IDDI indices over different zones for different periods and for

individual months has identified months and periods characterised by anomalous dust

loadings. Where the anomalies are common to Sahelian and Saharan regions they indicate

the likelihood of large-scale dust-mobilisation processes connected with patterns of the

region circulation. Analyses of circulation patterns in conjunction with fields of IDDI data

will be presented in Chapter 6, which will deal with the climatology associated with dust

production, and spatial relationships between rainfall and subsequent dust production.

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