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date: 22 August 2017

Mineral Dust Generation across Northern Africa and Its Impacts

Summary and Keywords

Mineral dust is the most important natural aerosol type by mass, with northern Africa the most prominent source region worldwide. Dust particles are lifted into the atmosphere by strong winds over arid or semiarid soils through a range of emission mechanisms, the most important of which is saltation. Dust particles are mixed vertically by turbulent eddies in the desert boundary layer (up to 6km) or even higher by convective and frontal circulations. The meteorological systems that generate winds strong enough for dust mobilization cover scales from dust devils (~100m) to large dust outbreaks related to low- and high-pressure systems over subtropical northern Africa (thousands of kilometers) and include prominent atmospheric features such as the morning breakdown of low-level jets forming in the stable nighttime boundary layer and cold pools emanating from deep convective systems (so-called haboobs). Dust particles are transported in considerable amounts from northern Africa to remote regions such as the Americas and Europe. The removal of dust particles from the atmosphere occurs through gravitational settling, molecular and turbulent diffusion (dry deposition), as well as in-cloud and sub-cloud scavenging (wet deposition). Advances in satellite technology and numerical dust models (including operational weather prediction systems) have led to considerable progress in quantifying the temporal and spatial variability of dust from Africa, but large uncertainties remain for practically all stages of the dust cycle. The annual cycle of dustiness is dominated by the seasonal shift of rains associated with the West African monsoon and the Mediterranean storm track. In summer, maximum dust loadings are observed over Mauritania and Mali, and the main export is directed toward the Caribbean Sea, creating the so-called elevated Saharan Air Layer. In winter the northeasterly harmattan winds transport dust to the tropical Atlantic and across to southern America, usually in a shallower layer.

Mineral dust has a multitude of impacts on climate and weather systems but also on humans (air pollution, visibility, erosion). Nutrients contained in dust fertilize marine and terrestrial ecosystems and therefore impact the global carbon cycle. Dust affects the energy budget directly through interactions with short- and long-wave radiation, with details depending crucially on particle size, shape, and chemical composition. Mineral dust particles are the most important ice-nuclei worldwide and can also serve as condensation nuclei in liquid clouds, but details are not well understood. The resulting modifications to cloud characteristics and precipitation can again affect the energy (and water) budget. Complicated responses and feedbacks on atmospheric dynamics are known, including impacts on regional-scale circulations, sea-surface temperatures, surface fluxes and boundary layer mixing, vertical stability, near-surface winds, soil moisture, and vegetation (and therefore again dust emission). A prominent example of such complex interactions is the anti-correlation between African dust and Atlantic hurricane activity from weekly to decadal timescales, the causes of which remain difficult to disentangle. Particularly in the early 21st century, research on African dust intensified substantially and became more interdisciplinary, leading to some significant advances in our understanding of this fascinating and multifaceted element of the Earth system.

Keywords: mineral dust, Sahara, Sahel, wind, radiation, low-level jet, haboob, aerosol-cloud interactions, biogeochemistry, hurricane

Introduction

Mineral dust particles lifted into the atmosphere by strong winds from arid or semiarid soils constitute the largest contribution to the global aerosol load by mass, reaching many megatons per year (see Figure 1 for an illustration). The Sahara and Sahel are the world’s most important dust sources with contributions to the global total on the order of 50% (e.g., Engelstaedter, Tegen, & Washington, 2006), and therefore northern Africa has always been a particular focus of dust research. Among many other dust regions, the Sahara contains the Bodélé Depression (Chad), the most active single source worldwide (e.g., Koren et al., 2006; Warren et al., 2007). Additional, rather minor sources are located in the dry areas of southern Africa (e.g., Prospero, Ginoux, Torres, Nicholson, & Gill, 2002), but these will not be covered here. Dust and sand storms are dramatic weather events with potentially hazardous impacts on humans (e.g., Knippertz & Fink, 2006). Moreover, the smaller dust particles especially can be lifted to great heights and reach remote areas such as Europe and South and North America in considerable concentrations (see Figure 1 as an illustration). Dust particles are removed from the atmosphere through complicated dry and wet deposition processes that are still not well understood (Bergametti & Forêt, 2014).

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Figure 1. The almost global reach of African dust. GEOS-5 model simulation, showing the four main aerosols: mineral dust from deserts (red), sea salt from spray (blue), soot and smoke from fires (green), and sulfate particles from fossil fuel combustion and volcanoes (white).

Image credit: William Putman, NASA/Goddard.

Dust and sand storms and long-range transport of dust particles have fascinated scientists for centuries (including, among others, Alexander von Humboldt and Charles Darwin; see historical overview in Knippertz & Stuut, 2014a). More recently, it has been realized that mineral dust is a key player in the Earth system with important impacts on the global energy and carbon cycles, acting on timescales of minutes to millennia (Knippertz & Stuut, 2014b; Shao et al., 2011). Arguably the most important effect of airborne dust particles is that they absorb and scatter both short- and long-wave radiation, the details of which mainly depend on size and shape of the particles, height of the dust layer, and chemical composition (Highwood & Ryder, 2014). In addition, mineral dust is the most important ice-nucleating particle in clouds worldwide and thereby affects precipitation and again radiation indirectly (e.g., Cziczo et al., 2013). Mineral dust can be involved in heterogeneous and multiphase atmospheric chemistry, affecting photo-oxidant concentrations and the composition of precipitation (e.g., Michel, Usher, & Grassian, 2003; Kandler et al., 2007). Deposition on plants, snow, and ice changes the amount of reflected solar radiation (e.g., Painter et al., 2007). Nutrients contained in dust fertilize terrestrial and marine ecosystems, and therefore affect the global carbon cycle (Shao et al., 2011).

Other aspects that have motivated intense research into the global dust cycle include its impact on air quality and human health. Frequent exposure to high dust concentrations occurring during dust storms has been related to respiratory diseases such as silicosis and is suspected of playing a role in the spread of infections and outbreaks of meningitis during the dry season in northern Africa (Morman & Plumlee, 2014). The dramatically reduced visibility during sand and dust storms can create hazardous situations for aviation but sometimes also for road or ship transport (e.g., Pauley, Baker, & Barker, 1995). Dimming of incoming solar light by dust particles is also of increasing interest for the quickly growing solar energy industry (Schroedter-Homscheidt, Oumbe, Benedetti, & Morcrette, 2013). From an agricultural perspective dust emission can be linked to soil erosion and decreasing productivity of affected areas (Sterk, 2003). Finally, dust deposits in glaciers, soils, and ocean or lake sediments constitute an important archive of past environmental changes supporting climate reconstructions over a wide range of timescales (Mahowald et al., 1999; Knippertz & Stuut, 2014b).

These aspects taken together have created a multidisciplinary and increasingly interlinked global community of dust researchers. It has motivated the inclusion of dust into numerical models for weather and climate simulations in more and more sophisticated ways. Dust concentrations are now being forecast by a growing number of operational centers on a daily basis, and powerful data assimilation systems are being developed to optimize the use of dust observations from the ground and from satellites (Benedetti et al., 2014). At the same time, interactions of dust with the atmosphere and Earth system through radiation, cloud microphysics, and biogeochemical effects are built into numerical models. These developments are supported by dedicated field campaigns taking detailed measurements of dust particles and their interactions with the atmosphere from the ground, ship, and aircraft (see Knippertz & Stuut, 2014b).

An overview of the dust cycle will be provided, giving details on its three main components—emission, transport, and deposition—including a systematic discussion of the most important meteorological phenomena responsible for dust uplift in northern Africa (The Dust Cycle). Knowledge of the spatial and temporal variability of dust concentrations across Africa will be summarized, including a short discussion on the observing systems used to derive available climatologies (Spatial and Temporal Variability). Interactions with Weather, Climate, and Biogeochemical Processes will explain in more detail the impacts of dust on climate and weather systems. The impact of African dust on Atlantic hurricanes, a topic that has received particular interest in the aftermath of the record-breaking 2005 hurricane season, nicely illustrates the complicated interactions of dust with weather and climate systems (Impact on Hurricanes).

The Dust Cycle

The mineral dust cycle is composed of three main elements, which are described in detail. The bulk of atmospheric dust is produced by Aeolian (wind-driven) erosion (Emission), while anthropogenic factors such as road or agricultural dust are usually limited to small areas and are not discussed here. The lifted particles can be carried upward by turbulent winds or larger convective or frontal systems, and are finally transported over longer distances by synoptic circulation systems (Transport). Dust particles fall out due to gravitational settling, get deposited by turbulent motions on plants or other surfaces, or get rained or washed out by precipitation (Deposition). A wide range of meteorological systems can create dust emission and initial transport conditions, which are described specifically for northern Africa in Meteorological Systems. A correct description of the spatial and temporal variability of emission, transport, and deposition of dust is required to estimate and forecast atmospheric dust concentrations and their impacts.

Emission

Dust emission involves nonlinear processes governed by both the meteorology and the state and properties of the surface (Marticorena, 2014). The number of fine particles present in a free state at the surface of erodible soils is usually insignificant, as most of them are incorporated into coarser sand-sized aggregates. The force exerted on a soil surface by wind is the shear stress τ‎, which can be expressed as τ = ρa u*2, with ρa being the air density and u* the wind friction velocity. For neutral conditions u* is defined by u(z) = u*/κ‎ ln z/z0, where κ‎ is the von Kármán constant, u(z) the wind velocity at a height z above the surface, and z0 the aerodynamic roughness length. The mobilization of soil aggregates only occurs above a critical threshold of wind stress u*t. Above that threshold, wind stress counterbalances the particle weight, inter-particle forces, and capillary forces between grains, which for lower values of u* maintain aggregates on the ground; u*t controls both the occurrence of dust emission and its intensity and is a function of the soil grain diameter (Bagnold, 1941). For larger grains, u*t increases due to the weight of particles, such that gravitational effects dominate. For small particles, u*t increases mainly due to the larger inter-particle cohesive forces reinforcing grain bonds. These two effects lead to a minimum in u*t for a grain size around 80 µm. These particles are too heavy to stay in suspension for longer periods and therefore saltate or creep, leading to a horizontal dust flux (Figure 2).

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Figure 2. Dust production. Schematic diagram showing the vertical dust flux produced during the “sandblasting” process, when larger saltating grains (horizontal flux) hit the surface and break the inter-particle bonds linking dust particles together or to the surface.

Figure based on Laurent (2005).

Non-erodible elements such as pebbles, stones, or vegetation dissipate part of the wind momentum, which is therefore not available to mobilize particles. This leads to a global decrease of the stress acting on the erodible part of the surface and thus to an apparent increase of u*t. Soil moisture can increase u*t by promoting the development of capillary forces between soil grains (Fécan, Marticorena, & Bergametti, 1998). In the same way, physical (Gomes, Rajot, Alfaro, & Gaudichet, 2003) and biological (Belnap, Phillips, & Miller, 2003) crusts can enhance the binding of particles. Theoretical and experimental work using wind tunnels showed that the horizontal dust flux is approximately proportional to the third power of u* (Bagnold, 1941; Gillette, 1979), making dust emission very sensitive to the highest wind speeds. The actual release of finer dust particles, which can be transported over long distances, occurs when the saltating aggregates hit the ground and break the inter-particle bonds linking dust particles together or to the surface (Warren et al., 2007), creating a vertical dust flux (Figure 2). This is often referred to as a sandblasting process. Dust emission only rarely occurs in the absence of saltation (Gillette, 1977; Klose & Shao, 2012; Sow, Alfaro, Rajot, & Marticorena, 2009).

A number of dust emission schemes have been developed trying to represent the complicated physical processes at the interface between the atmosphere and the surface in a simplified way. Marticorena and Bergametti (1995) parameterize u*t for “rough” and “smooth” surfaces in arid and semiarid areas using the so-called drag partition between roughness elements and the erodible surface. Using this approach, the horizontal dust flux can be simulated successfully for a range of soil substrates and wind friction velocities (Marticorena, Bergametti, Aumont, & Legrand, 1997). Only sandblasting schemes allow simulation of both the mass and the size distribution of the vertical dust flux explicitly. Alfaro and Gomes (2001) proposed a model in which dust of a given size is produced when the kinetic energy of the saltating soil particles exceeds the corresponding threshold. The dust size distribution varies therefore as a function of the saltating particle size and their velocity. Predicting the emitted size distribution correctly is a challenging for dust models but has large impacts on dust radiative effects (Kok, 2011). Shao (2004) developed an elaborated version of a dust scheme that takes the saltation bombardment, the aerodynamic entrainment, and the aggregate disintegration into account.

A general problem for all dust emission schemes, particularly the more complex ones, is to obtain adequate information on the characteristics and state of soils in sufficient temporal and spatial resolution to put into numerical dust models. Regional and global input databases of surface roughness, soil dry size distribution, and soil texture have been developed, mostly on the basis of satellite data (Laurent, Marticorena, Bergametti, Léon, & Mahowald, 2008; Marticorena et al., 1997; Prigent, Tegen, Aires, Marticorena, & Zribi, 2005; Tegen et al., 2002). However, surface dynamics such as seasonal vegetation, temporary surface crusts, limited supply of fine particles, and specific soils (e.g., the diatomite soil in the Bodélé Depression) remain substantial and largely unresolved challenges. Kardous, Berganetti, and Marticorena (2005) point to the necessity of investigating the agricultural practices in semiarid areas such as the Sahel that can have substantial impacts on dust generation in areas strongly influenced by humans. Modeling of dust emission also critically hinges on the quality and resolution of input wind fields (Laurent, Heinold, Tegen, Bouet, & Cautenet, 2008; Menut, 2008), as discussed in more detail in Meteorological Systems. The highly nonlinear relationship between wind speed and emission (often cubic above the emission threshold) leads to a significant importance of rare high-wind events in some source areas (Cowie, Marsham, & Knippertz, 2015).

There is no long-term, reliable network of quantitative observations of dust emission over North Africa. Most available data are from measurement campaigns such as the Bodélé Dust Experiment (BoDEx) (Washington, Todd, Engelstaedter, Mbainayel, & Mitchell, 2006), the African Monsoon Multidisciplinary Analysis (AMMA) (Marticorena et al., 2010), the Saharan Mineral Dust Experiment (SAMUM) (Ansmann et al., 2011), and Fennec (Allen, Washington, & Saci, 2015). Satellites cannot measure emission directly but observations of emitted and transported dust give useful indirect information to evaluate simulations, at least in terms of spatio-temporal variations (see Spatial and Temporal Variability). Estimates of North African dust emission range from 240 Tg yr−1 using satellite observations (Kaufman et al., 2005) to 760 Tg yr−1 using modeling approaches (Laurent et al., 2008) with even higher values in some older studies (see Table 1 in Engelstaedter, Tegen, & Washington, 2006). One reason for these large discrepancies is different assumptions about particle size made by different authors.

Transport

Once lifted from the surface, the fate of fine mineral dust particles (with radii of few μ‎m or less) depends on the atmospheric motions that carry them upward (or downward) and horizontal winds that lead to long-range transport of dust away from the main source regions. Due to their weight, dust particles do not exactly behave like a passive tracer, but undergo gravitational settling, although typical timescales are many days for particles smaller than 10 μ‎m. The initial transport away from the surface mostly depends on the characteristics of the planetary boundary layer (PBL). During the daytime dry convective turbulence is usually intense over hot deserts and creates a well-mixed dust layer from the surface to the PBL top, which is often capped by a sharp inversion (Knippertz et al., 2009). The depth of the PBL varies strongly between seasons and geographically, reaching 5–6 km in summer of the Sahara but significantly less in winter and over the Sahel (see also Spatial and Temporal Variability). During the night, active mixing is often restricted to the immediate vicinity of the surface, such that dust particles in the residual layer are mostly transported horizontally by the prevailing winds. This can lead to differential advection of dust in the lowest kilometers of the atmosphere during the night, followed by homogenization of the different layers in the course of the day (Knippertz et al., 2009) (Figure 3). Advection of dust-laden hot desert air toward cooler air over the Atlantic, the Mediterranean, or southern West Africa can create an up-gliding along isentropic surfaces, which ultimately leads to elevated dust layers. For example, the Saharan dust layer above the trade wind inversion over the low-latitude Atlantic Ocean can sometimes reach up to 5–7 km above sea level in summer (Kalu, 1979). This layer often stretches from Africa to the Caribbean Sea and has been referred to as the Saharan Air Layer (SAL) (e.g., Karyampudi & Carlson, 1988) (Figure 4). Mixing of dust particles out of the PBL can be achieved through deep moist convection (particularly in summer over the Sahel) and through frontal lifting (particularly over the northern Sahara in winter), although in both cases a fraction of the dust is likely being scavenged if precipitation occurs in these circumstances. Upward transport can also be fostered through orographic effects or albedo anomalies, possibly even out of the PBL (Cuesta, Marsham, Parker, & Flamant, 2009; Marsham, Parker, Grams, Johnson, et al., 2008).

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Figure 3. Vertical mixing. Range-corrected attenuated backscattering at 1064 nm at the southern Moroccan city of Ouarzazate at 0924–1225 UTC on 04 June 2006 together with wind measurements by radiosonde launched at 1039 UTC. The observations were taken during the first SAMUM field campaign and illustrate differential advection during the night and homogenization during the day.

Figure from Knippertz et al. (2009), published under Creative Commons Attribution 4.0 International License.

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Figure 4. Saharan Air Layer. Schematic depiction of the classical conceptual model showing an extensive Saharan dust plume stretching from West Africa across the Atlantic. Note that the trade wind inversion height is exaggerated with respect to the height of the convective cloud, particularly to the north where it is usually lower than to the south. Also, the top of the marine mixed layer, which rises to the west underneath the trade wind inversion, is not depicted.

Figure taken from Karyampudi et al. (1999).

In terms of horizontal displacement, synoptic-scale circulations are the most important controlling mechanisms. The “steering” level, that is, the level with the strongest control on the overall dust trajectory, depends on the vertical extent of the dust layer and therefore is typically around 700 hPa in summer and around 850 hPa in winter. The main long-range transport paths are: (1) westward over the North Atlantic to the south of the Azores High to North or South America, (2) northward across the Mediterranean to southern Europe, usually ahead of upper-level troughs, and (3) along easterly trajectories across the eastern Mediterranean to the Middle East, often in connection with cyclonic disturbances, sometimes referred to as Khamsin or Sharav cyclones (Middleton & Goudie, 2001 and references therein; see also Meteorological Systems). Individual dust storms can of course deviate strongly from those more climatological pathways.

Deposition

The mineral dust cycle is highly sensitive to the rate of removal of dust particles from the atmosphere back to the surface through dry and wet deposition (see overview in Bergametti & Forêt, 2014). Dry deposition is the dust flux from the atmosphere to the surface through molecular and turbulent diffusion, and gravitational settling. Dry deposition of dust depends on particle size (large particles fall faster), flow properties, and surface characteristics and includes processes such as gravitational settling, turbulent transfer, Brownian diffusion, impaction, interception, and particle rebound (Zhang, Gong, Padro, & Barrie, 2001). Wet deposition is the dust transfer to the surface related to precipitation and includes in-cloud and sub-cloud scavenging.

Experimental studies show a wide range in deposition velocities depending on the measurement techniques used (total, dry or wet, and soluble or insoluble deposition). Albani et al. (2014) present a compilation of dust deposition flux data, restricting the size range to be consistent with their dust model. They find that many stations around the Sahara have annual fluxes on the order of 20 g m−2. Annual deposition values observed from ground stations range from less than 1 g m−2 for western Europe up to 100 to 200 g m−2 close to Saharan source areas (Bergametti & Forêt, 2014; Middleton & Goudie, 2001) (Figure 5, top).

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Figure 5. Dust deposition. Top: Compilation of annual deposition flux measurements. Figure from Bergametti & Forêt (2014). Bottom: Annual distribution of total deposition for the year 2000 based on the AEROCOM median model.

Figure from Huneeus et al. (2011) used under CC Attribution 3.0 License.

Aerosol removal processes remain an important source of uncertainty in models, and their evaluation remains difficult due to the locations and periods for which in situ observations are available. Close to source regions, where large particles are present and where precipitation is often rare, dry deposition is generally the dominant process. Far from sources, larger particles have been deposited and therefore wet deposition dominates (Bergametti et al., 1989). Dry deposition depends strongly on particle size distribution and shape, the density of the particle and the “stickiness” of the underlying surface (e.g., vegetated areas; Zhang, Gong, Padro, & Barrie, 2001). The efficiency of the wet deposition depends on the type and intensity of the precipitation and the size distribution of raindrops. These parameters are often not reliably represented in climate models, for example because of the usage of simple parameterizations for convective rainfall. The wet deposition efficiency also depends on the size distribution and the chemical characteristics of the dust aerosol (Bergametti & Forêt, 2014), another two parameters that are fraught with substantial uncertainty in dust models.

Figure 5 (bottom) shows a total deposition climatology derived from models participating in the intercomparison project AEROCOM, which broadly agrees with the measurements shown in Figure 5 (top), although individual models deviate strongly from each other. A large fraction of North African dust is deposited over the Sahara and Sahel itself followed by the broad plume westward into the subtropical and tropical Atlantic. Deposition fluxes into the northern Atlantic and Europe are smaller but still significant (see also Mahowald, 2007).

Meteorological Systems

Meteorological systems that cause near-surface winds strong enough to mobilize and transport dust occur on spatial scales from a few meters to thousands of kilometers (for an overview see Knippertz & Todd, 2012; Knippertz, 2014). The largest (i.e., synoptic) scales are dominated by extratropical weather systems with marked regional and seasonal differences. Following Knippertz (2014), these systems can be classified into desert depressions without a clear frontal structure, well developed cyclones with dust emission behind (and sometimes also ahead of) the cold front, weak cyclonic disturbances with long trailing cold fronts and strong post-frontal ridge formation, and intensified subtropical high-pressure systems.

In the northern and central Sahara, surface depressions regularly form in connection with southward penetrating upper-level troughs or cut-off lows from Europe or the adjacent Atlantic Ocean, in particular during spring and winter (e.g., Thorncroft & Flocas, 1997). Some of these develop into intense frontal cyclones. Typical examples are the so-called Khamsin, Sharav or desert depressions, which form in the lee of the Atlas Mountains and then track east or northeastward, causing dust storms along the Mediterranean coast (Alpert & Ziv, 1989; El Fandy, 1940; Bou Karam, Flamant, Cuesta, Pelon, & Williams, 2010; Pedgley, 1972) (Figure 6). However, only a few of all depressions develop a clearly identifiable pressure minimum that can be tracked over longer distances and time periods (Fiedler, Schepanski, Knippertz, Heinold, & Tegen, 2014). Dust mobilized along the trailing cold front of such systems can occasionally reach as far south as the Sahel.

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Figure 6. Khamsin cyclone. The satellite image at 1200 UTC 22 January 2004 is a composite of three infrared (IR) channels from the Meteosat Second Generation (MSG) Spinning Enhanced Visible and InfraRed Imager (SEVIRI) instrument. High, optically thick clouds appear in red in this image and dust in magenta. The synoptic station reports shown in this Figure indicate severe dust storms with wind speeds of up to 35 knots and a visibility down to 100 m behind the cold front over Egypt and Libya.

Figure taken from Knippertz and Todd (2012).

In the Sahel and southern Sahara, intense dust storms frequently occur during the West African dry season (December to April) in connection with low-level pressure surges that are associated with an intensification of anticyclonic conditions over northern Africa (Kalu, 1979; Klose, Shao, Karremann, & Fink, 2010). These are related to cold air intrusions from the mid-latitudes and are sometimes enhanced by evaporational cooling (Gläser, Knippertz, & Heinold, 2012; Knippertz & Fink, 2006). The increased south–north pressure gradient across northern Africa associated with a strengthened subtropical anticyclone leads to an intensification of the harmattan winds, sometimes referred to as harmattan surges (Fiedler, Kaplan, & Knippertz, 2015). In weak cases, this may only cause localized emissions from preferential sources (Knippertz et al., 2011) such as the Bodélé Depression in Chad, where orographic channeling accelerates the low-level north-easterlies (Washington & Todd, 2005). In strong cases, long-lived, fast-moving dust fronts can form, which become almost continental in scale (Knippertz & Fink, 2006; Shao, Fink, & Klose, 2010; Tulet, Mallet, Pont, Pelon, & Boone, 2008) (Figure 6).

During the summer monsoon season, the large-scale pressure distribution is characterized by a pronounced heat low centered over northern Mali and fairly strong pressure gradients toward the Atlantic to the west, the Gulf of Guinea to the south, and the Mediterranean Sea to the northeast (Lavaysse et al., 2009). Due to the orographic barriers of the Atlas and Hoggar Mountains, the three most important inflow regions are the very strong and persistent Atlantic inflow over Western Sahara and Mauritania (Grams et al., 2010; Knippertz, 2008; Todd et al., 2013), the southerly monsoon flow over the Sahel (Bou Karam et al., 2008; Flamant et al., 2007) and the northeasterly inflow from the eastern and central Mediterranean Sea that can take the form of cold-air surges (Knippertz et al., 2009). During the day, the deep and well-mixed PBL impedes the response of low-level winds to large-scale pressure gradients. During the night, when the low levels stabilize, a more coherent flow toward the heat low can be observed (Parker et al., 2005). The southerly monsoon flow can develop a sharp leading edge that behaves almost like a gravity current and leads to dust emission (Bou Karam et al., 2008).

An important phenomenon that occurs over cloud-free, dry regions with marked background pressure gradients during all seasons is the formation of nocturnal low-level jets (LLJs) (Fiedler, Schepanski, Heinold, Knippertz, & Tegen, 2013; Knippertz, 2008; Todd, Washington, Raghavan, Lizcano, & Knippertz, 2008). These are dynamically related to the decoupling of the layer above the radiatively generated temperature inversion from surface friction during the night (Figure 7). One physical mechanism that supports LLJ formation is that after sunset the wind in this layer performs an inertial oscillation around the geostrophic wind (or a friction-affected equilibrium wind) (Van de Wiel et al., 2010). As the oscillation period is determined by 2π‎ divided by the Coriolis parameter, f, the central Sahara is optimally placed to experience highly supergeostrophic (faster than the geostrophic wind) flow in the jet level around sunrise (Heinold, Knippertz, & Beare, 2014). Downward mixing of momentum from the LLJ during the build-up of the PBL in the morning leads to a peak in near-surface gusts and dust emission during these hours (Engelstaedter & Washington, 2007; Schepanski et al., 2009; Washington, Todd, Engelstaedter, Mbainayel, & Mitchell, 2006). This effect has been observed very clearly for the Bodélé Depression during BoDEx, although in nights with very strong background winds, the mechanical steering of the PBL during the night impedes a decoupling and thus an undisturbed inertial oscillation (Todd et al., 2008).

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Figure 7. LLJ formation and surface winds. Schematic depiction of typical changes in low-level wind, gusts, potential temperature, and turbulence over the Sahara. Note that UTC and local time are identical here.

Figure taken from Knippertz (2008).

On the meso-scale (a few to several hundred kilometers), density currents driven by the cooling associated with the evaporation of convective precipitation in the hot and dry desert air (so-called convective “cold pools”) play an important role. Dust storms along the leading edge of a rapidly spreading cold pool are often called haboobs and have first been documented for squall-line type convection in the Sudan (Freeman, 1952; Sutton, 1925). Over northern Africa haboobs are most frequent at the margins of the Sahara, where enough moisture is available to sustain the parent deep moist convection. A number of detailed observational studies on Sahelian haboobs using aircraft and ground-based radar have been published (Flamant et al., 2007; Marsham, Parker, Grams, Taylor, & Haywood, 2008; Williams et al., 2009). Figure 8 (top) shows a photograph of a typical haboob over the Sahel with a sharp leading edge appearing like a moving wall of dust. Updrafts in this area can reach more than 8 m s–1 and particles or other small objects can be transported upward and rearward in the head of this gravity current reaching heights of about 2.5 km (Williams et al., 2009). Haboobs have also been discovered over Morocco and Algeria, where they are related to moist convection over the Atlas Mountains, particularly during the summer half year (Emmel, Knippertz, & Schulz, 2010; Knippertz et al., 2007; Redl, Fink, & Knippertz, 2015; Solomos, Kallos, Mavromatidis, & Kushta, 2012) or to more frontal features associated with cyclonic disturbances (Figure 8, bottom). Occasionally, haboob activity extends from the Sahel far into the central and even northern Sahara (Cuesta, Lavaysse, Flamant, Mimouni, & Knippertz, 2010; Knippertz et al., 2009; Roberts & Knippertz, 2014). There is evidence that such situations are connected to moisture transport in the southerly sectors of intense African Easterly Waves, particularly if these interact with disturbances in the subtropics (Knippertz & Todd, 2010).

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Figure 8. Haboob dust storms. Top: Photograph of a haboob arriving over Niamey on 26 June 2012. Courtesy of Laurent Labbé. Bottom: Visible satellite image at 17 UTC 09 October 2008 showing a haboob emanating from a cyclonic disturbance over Morocco and Algeria.

© EUMETSAT 2008.

The dynamics, climatology, and contribution to the total dust budget of haboobs are still not very well understood to date. This is caused on the one hand by a scarce observational network in the Sahara, combined with difficulties of detecting haboobs from space due to the cloudiness associated with the parent convection (Heinold et al., 2013; Kocha, Tulet, Lafore, & Flamant, 2013; Williams, 2008), and on the other hand by the challenges of numerically simulating the organized moist convection causing a haboob, which requires high resolution and a suitable trigger for convection (Pantillon, Knippertz, Marsham, & Birch, 2015; Reinfried et al., 2009). Examples have been documented where even large haboobs are not reflected at all in operational analysis (Knippertz et al., 2009; Sodemann et al., 2015). Recent high-resolution modeling studies suggest an important contribution of haboobs to dust uplift during the summer monsoon, which is not reproduced by simulations using parameterized convection (Heinold et al., 2013).

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Figure 9. Dust devils. Example of a tall dust devil in Tanzania.

Courtesy of Philippe Peyrillé.

On the microscale (< 2 km) dust is mobilized in connection with dry convective mixing in the PBL, part of which is realized through rotating dust devils (Figure 9) and part through non-rotating convective plumes. Dust devils typically have diameters of 3–100 m, lifetimes of a few minutes, and tangential winds of 3–15 m s–1 (Sinclair, 1969). They are caused by convergence of ambient vorticity in regions of intense dry convective uplift. Dust plumes, in contrast, are characterized by larger diameters and lifetimes up to an hour, and also by weaker winds and smaller dust fluxes. Typical conditions for the formation of dust devils or plumes include moderate, near-surface wind shear and a large temperature contrast between the surface and the lowest few meters of the atmosphere (difference between temperatures at 1 and 2 m above ground on the order of 1 K, with superadiabatic stratification reaching as high as several hundred meters above ground (Ryan, 1972). The latter corresponds to high sensible heat fluxes, which requires intense downward solar radiation, a dry soil, and low aerosol optical thickness (AOT) (Ansmann et al., 2009). Very few studies have addressed dust devil/plume activity in and around the Sahara specifically (Mattson, Nihlén, & Wang, 1993; McGinnigle, 1966). Ansmann et al. (2009) present lidar measurements from southern Morocco, which indicate coherent dust plumes of more than 2 km vertical extension. Koch and Renno (2005) argued that dust devils and plumes together contribute considerably to regional and global dust emissions but later assessments suggest a rather marginal contribution (Jemmett-Smith, Marsham, Knippertz, & Gilkeson, 2015). More recently, first attempts have been made to simulate dust devils numerically, using large eddy models (Ito, Niino, & Nakanishi, 2013; Raasch & Franke, 2011; Sullivan & Patton, 2011). Another important aspect of the vigorous PBL mixing over arid or semiarid subtropical land surfaces during the daytime is the homogenization of dust from different sources and the vertical transport to heights of more than 5 km (Cuesta et al., 2009; Marsham, Parker, Grams, Johnson, et al., 2008).

Spatial and Temporal Variability

The spatial and temporal variability of dust in the atmosphere is the result of the processes discussed in The Dust Cycle, predominantly the location of sources, the variability in winds that create emission, transport pathways, and precipitation causing wet deposition. An assessment of this variability requires reliable observational sources. Given the inaccessibility and low population density of the vast extensions of the Sahara, ground-based observations over longer periods are rather sparse (see Figure 10). Therefore additional information from satellites and increasingly numerical models are used for an integral assessment. One relatively new approach in this context is the assimilation of satellite and ground observations into numerical prediction models for weather and atmospheric composition, which helps to create better forecasts but also offers opportunities to create aerosol analysis data sets (Benedetti et al., 2014).

Work based on ground stations usually has the best temporal coverage (3–6 hourly, in some cases for more than 60 years) and therefore allows analysis of interannual variability and even decadal trends but suffers from poor spatial coverage and thus representability problems (Cowie, Knippertz, & Marsham, 2014; Cowie, Knippertz, & Marsham, 2013; Klose, Shao, Karremann, & Fink, 2010; Mahowald, Ballantine, Feddema, & Ramankutty, 2007; Mbourou, Bertrand, & Nicholson, 1997). Usually these station records provide estimates of (a) visibility, a reasonable proxy for dust loading in the desert, (b) human observations of dust uplift, dust in suspension, and dust haze (following a coding established by the World Meteorological Organization), and (c) wind speed.

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Figure 10. Dust climatology. Annual cycle of the relative frequency of dust events from station observations according to the legend. The topographic height is shaded in gray. The blue areas represent the 8 × 10−6 s−1 level of horizontal convergence and the black dashed lines the position of the lowest 925 hPa geopotential height between 0° and 28°N. Yellow and orange areas indicate regions of TOMS/OMI Aerosol Index exceeding 1.8 and 3. Reference period is 1983–2008.

Figure from Klose et al. (2010).

Satellite observations provide much better spatial coverage than stations but often for much shorter time periods. Most climatologies are presented in the form of aerosol optical thickness (AOT) or a more qualitative dust or aerosol index (e.g., Figure 10). Satellite data have also been used for source identification (e.g., Ginoux, Garbuzov, & Hsu, 2010; Muhs, Prospero, Baddock, & Gill, 2014; Prospero, Ginoux, Torres, Nicholson, & Gill, 2002; Schepanski, Tegen, Laurent, Heinold, & Macke, 2007), but disagreement between the different approaches is substantial (see Figure 1 in Formenti et al., 2011; Schepanski, Tegen, & Macke, 2012). AOT or dust index retrievals have been developed for both geostationary and polar orbiting satellites, covering a wide range of instruments and wavelengths from infrared to ultraviolet, all with their specific limitations (see overview in Chiapello, 2014). Some products (particularly those in the visible part of the spectrum such as the classical aerosol product from the Moderate Resolution Imaging Spectroradiometer [MODIS]) are only available over the ocean. As AOT represents the total atmospheric column, high aerosol loadings do not necessarily correspond to high surface concentrations and low horizontal visibilities. In addition to dust, aerosols such as soot from burning biomass contribute to the AOT, particularly over the Gulf of Guinea region during November to March.

Cowie et al. (2014) present a station-based climatology focusing on emission and emission thresholds. They find that north of 23°N the frequency of dust storms peaks in spring, while to the south the seasonal cycle is more variable. Particularly in the Sahel the seasonal rainfalls create an annual cycle in emission threshold, which affects the frequency of dust storms but interestingly also decadal trends (Cowie et al., 2013). Observations of visibility and dust in suspension reflect the combined effects of emission and transport and therefore depend on the position of the station in relation to emitting dust sources and the wind regime transporting the dust toward the station (Klose et al., 2010; Mbourou et al., 1997). Figure 10 shows a combination of station observations of dust and the aerosol index from the Total Ozone Mapping Spectrometer (TOMS) and Ozone Monitoring Instrument (OMI) sensors, which provide one of the longest dust products from space. It illustrates that the seasonal variation in dustiness changes with the rainfall regime, with very few dust observations to the south of the main convergence line and trough in 925-hPa geopotential outside of boreal summer, when haboobs occur in the Sahel (Largeron et al., 2015; Marticorena et al., 2010). South of 15°N, dust is typically observed from October to April or May, peaking in December and January, while wet removal during the time of the West African monsoon impedes larger dust loadings. Going further north, the length of the dust season grows, finally covering the whole year. At many Saharan stations, the frequency of dust days peaks in summer. This is in contrast to the spring maximum in emission frequency found by Cowie et al. (2014) and may be related to the high intensity of dust emission from haboob dust storms and a stronger concentration of dust in the convergent Saharan heat low. The TOMS/OMI satellite product clearly shows the seasonal migration of the dust plume (Figure 10). The overall minimum occurs in autumn followed by a winter maximum over the Gulf of Guinea, probably with significant contributions from combustion aerosol. In spring the atmospheric dust loading generally increases, finally forming a band of enhanced dustiness extending from the Red Sea to the Atlantic, centered at around 15°–20°N. The Bodélé Depression–Ténéré region (Chad and Niger) stands out as a local maximum during this season. In boreal summer, the maximum over the area of the Saharan heat low strengthens and low aerosol index values are found over the wet southern parts of West Africa. This is also the time when large amounts of dust are exported to the subtropical and tropical Atlantic Ocean due to the strong midlevel flow around the African Easterly Jet (AEJ), leading to the formation of the Saharan Air Layer (SAL) (see Transport).

With respect to the diurnal cycle of dust emission and visibility, consistent peaks during late morning to mid-afternoon are found for most regions and seasons, closely related to the development of the convective boundary layer (Cowie et al., 2014; Mbourou et al., 1997). The breakdown of the nocturnal LLJ plays an important role to create this diurnal peak (see Meteorological Systems). Geostationary satellite images sensitive to dust have a high temporal resolution and therefore provide an alternative approach to study the diurnal cycle. Work by Schepanski et al. (2009) using with the Meteosat Second Generation (MSG) Spinning Enhanced Visible and InfraRed Imager (SEVIRI IR) dust index (Brindley, Knippertz, Ryder, & Ashpole, 2012) largely confirms the morning peak in dustiness. However, it has also been argued that the dust emission created from haboobs over the summertime Sahel and Sahara is often overlooked by satellites due to cloud contamination (Heinold et al., 2013; Kocha, Tulet, Lafore, & Flamant, 2013).

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Figure 11. Vertical variability. Aerosol layer mean altitude retrieved by AIRS over the period 2003–2008 for July (top) and December (bottom). Altitude is shown only for pixels with 10 μ‎m AOT≥0.10.

Figure from Peyridieu et al. (2010) used under CC Attribution 3.0 License.

In recent years, the development of space-borne lidar (light detection and ranging) techniques has provided an unprecedented view of the vertical structure of the mineral dust distribution. One example is the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission, the first satellite involving a lidar specifically designed to study aerosols and clouds (e.g., Ben-Ami, Koren, & Altaratz, 2009). In addition, Peyridieu et al. (2010) have shown the ability of infrared sounders like the Atmospheric Infrared Sounder (AIRS) to retrieve the dust layer mean altitude quite accurately by comparing their results with the CALIOP-altitude product over the Atlantic. These products demonstrate that in winter vertical mixing is weaker and occurs farther south over the tropical Atlantic Ocean, such that most of the dust is transported within the trade wind layer below 1.5–3 km (Figure 11, bottom). In summer aerosol layer heights of 4km and more frequently occur in the region of the SAL stretching from the West African coast to the Caribbean Sea (Figure 11, top).

Interactions with Weather, Climate, and Biogeochemical Processes

Dust particles influence the regional and global radiation balance, cloud microphysics, biogeochemical processes, and atmospheric dynamics and chemistry in many ways. Some of these are not well understood and remain a source of uncertainty for climate projections and reconstructions of past climate states. Emission, transport, and deposition of atmospheric dust particles depend on meteorological and soil parameters such as surface wind speed, precipitation, and vegetation cover in dust source areas, which creates a potential for feedback mechanisms. These cannot be studied easily from observations alone and therefore often rely additionally on results from large-scale dust models. The most important results are summarized with regard to radiative effects, atmospheric dynamics, cloud microphysics, and biogeochemical aspects.

Direct Radiative Effects

Dust particles interact with both short- and long-wave radiation depending on their size and chemical composition (Highwood & Ryder, 2014), thereby altering the energy and water cycles (Miller, Knippertz, Pérez García-Pando, Perlwitz, & Tegen, 2014). Solar radiation can be reflected and absorbed by atmospheric particles. With diameters of 2 μ‎m and larger, dust particles can also absorb and re-emit outgoing terrestrial radiation. Dust particle size and complex refractive indices determine their optical properties and thus the magnitude and sign of their radiative effects. These properties can be determined directly by measurements of dust samples or specific minerals in the laboratory or field, or indirectly through inversion techniques by remote sensing, but the results often disagree. This is mainly due to different a priori assumptions about particle properties, which depend on particular size distribution and shape as well as mineral or chemical content. As an example, Figure 12 shows the dependence of single scattering albedo on size and refractive index. In particular, iron content is an important factor that can substantially change the optical properties of dust aerosol (e.g., Sokolik & Toon, 1999), but there is a lack of information on the wavelength-dependent complex refractive indices of dust from different source regions.

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Figure 12. Dust optical properties. Black lines represent the spectral single-scattering albedo for size distributions close to source and red lines that for transported dust. Solid lines are for an absorbing refractive index, dashed lines for a less absorbing one.

Figure from Highwood & Ryder (2014).

The optical properties of dust are fed into radiative transfer models in order to compute the fractions of absorbed and transmitted radiation passing through an atmospheric layer that contains dust. Net radiative forcing by dust is defined as the difference of net irradiance of the dust-containing atmosphere and a clear atmosphere, including both short- and long-wave effects. In addition to dust optical properties, the magnitude of the net radiative forcing depends on other parameters such as the presence of clouds, the vertical distribution of the dust particles, and on the albedo of the underlying surface. The uncertainties in dust optical properties, for example, resulting from different assumptions on size distribution, are so large that they can change the sign of the radiative forcing in global circulation models and thus the estimated impact of dust on climate (Perlwitz, Tegen, & Miller, 2001). Model estimates of global average net radiative forcing by dust at the top of the atmosphere (TOA) range from −0.6 W m−2 (Yoshioka et al., 2007) to +0.35 W m−2 (Balkanski, Schulz, Claquin, & Guibert, 2007).

Positive net forcing may occur regionally over bright surfaces like the Sahara Desert, while negative values prevail over dark ocean surfaces (Miller et al., 2014). Over source regions, short-wave effects are usually small and hard to measure from space due to the small differences in albedo between the dust layer and the underlying surface. Warming through long-wave effects on the other hand can be large (Zhang & Christopher, 2003). Due to the presence of larger particles near sources, optical properties can differ substantially from dust transported over longer distances, creating different heating rates and thus radiative forcing (Ryder, Highwood, Lai, Sodemann, & Marsham, 2013; Ryder et al., 2013). Satellite estimates for the downstream tropical Atlantic region suggest a cooling effect on the order of −6 W m−2 (Christopher & Jones, 2007). This estimate is dominated by short-wave cooling compensated to about 20% by long-wave warming. Case studies of instantaneous dust net radiative heating of the atmosphere during individual strong dust events estimate values as high as 100 W m−2 resulting from strongly increased short-wave heating only partly compensated by equally increased long-wave cooling (Slingo et al., 2006).

Atmospheric Dynamics

Radiative forcing by dust influences the energy distribution within the atmosphere. At the surface below a dust cloud incoming solar radiation is reduced, which results in a decrease in latent heating and therefore a weakening of the hydrological cycle (Miller, Tegen, & Perlwitz, 2004; Yoshioka et al., 2007). The reduction of incoming radiation at the Earth’s surface by dust can be substantial, while at the same time the TOA forcing is small. This leads to a warming of the atmospheric column, the magnitude, and even the sign of which, however, depends on dust size distribution and optical properties (Miller et al., 2014). The resulting heating or cooling of the surface and atmosphere affects stability and thus vertical fluxes of energy. If there are gradients to neighboring areas, the atmospheric heating and cooling can drive regional circulations. The resulting temperature adjustment depends crucially on whether the dust is located in a convectively mixed region (e.g., tropical Africa and the adjacent Atlantic Ocean) or a subsidence region (e.g., the Sahara). Given the uncertainties in dust optical effects, our capability to predict regional responses to dust and connected impacts such as that on precipitation is limited (Miller et al., 2014). If precipitation is affected in a negative way over a dust source region, a positive feedback loop can be established through effects on soil moisture and vegetation cover.

Usually the presence of dust stabilizes the planetary boundary layer (PBL) downwind of the dust source due to reduced solar insolation at the surface, leading to reduced eddy mixing within the PBL and therefore a decreased impact on low-level jets (LLJs) on surface wind speed (e.g., Pérez, Nickovic, Pejanovic, Baldasano, & Özsoy, 2006). The reduction of dust mobilization is typically on the order of 10% compared to a model where the dust distribution has no radiative effect (Perlwitz, Tegen, & Miller, 2001; Rémy et al., 2015; Tegen et al., 2006; Yue, Wang, Liao, & Fan, 2010). Figure 13 shows an example of sensitivity experiments with a global aerosol model for dust-induced changes in surface temperature, wind speed, pressure, and dust optical depth for an intense dust storm over northeastern Africa in April 2012. Long- and short-wave feedbacks are treated separately. During the night, long-wave forcing, particularly thermal re-emission by the dust cloud, dominates, leading to a substantial warming, particularly underneath the mainly north–south oriented dust plume. In this area values exceed 3K (Figure 13a). The thermal forcing at the surface and at higher levels leads to a reduction of mean sea-level pressure (MSLP) of up to 1 hPa (Figure 13c). The change in MSLP gradient delays the propagation of the front but increases the wind behind the leading edge by more than 1 m s−1, also due to enhanced turbulent momentum fluxes resulting from the reduced low-level stability (Figure 13e). The greater emission (and possibly smaller differences in transport) leads to a much higher dust optical depth by up to 0.5 (Figure 13g). During the day, short-wave forcing dominates, leading to a broad area of lower surface temperatures of more than −3K (Figure 13b) and higher pressure of more than 1 hPa (Figure 13d). In other cases, daytime cooling of more than 20K have been modeled (Tegen et al., 2006). The change in pressure gradient, together with reduced turbulence, decreases the wind behind the front but increases it to the southeast and northwest (Figure 13f), leading to overall substantially reduced emission (Figure 13h). Particularly for surface wind speeds near the emission threshold even small differences can lead to considerably reduced dust emission. Adding the two effects together results in a net reduction of dust loading (not shown).

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Figure 13. Atmospheric dynamics. Model sensitivity experiments for an intense dust storm over northeastern Africa using the MACC-II global forecasting system developed by the European Centre for Medium-Range Weather Forecasts (ECMWF). Left-hand-side (right-hand-side) panels show differences between a forecast with long-wave (short-wave) radiation responding to prognostic dust and a reference run with an aerosol climatology, both started at 00 UTC 17 April 2012 and valid for 00 UTC (12 UTC) on 18 April 2012. Individual panels show differences in: (a, b) 2-m temperature (in K), (c, d) mean-sea-level pressure (in Pa), (e, f) wind speed used for dust production (in m s–1), and (g, h) dust optical depth (dimensionless).

Figure compiled from Rémy et al. (2015) used under CC Attribution 3.0 License.

In addition, dust can have a number of indirect effects on atmospheric and cloud dynamics. Atmospheric heating by absorbing aerosol particles, such as mineral dust, reduces midlevel relative humidity and convective instability, which may lead to a reduction in cloud cover (the so-called semi-direct aerosol effect) (Hansen, Sato, & Ruedy, 1997). Including radiative effects of dust in global and regional weather prediction models generally improves forecasts (e.g., Pérez et al., 2006).

Cloud Microphysics

The influence of aerosol particles on cloud characteristics such as lifetime, cloud cover, droplet size distribution, or glaciation is a major uncertainty in climate research. Dust particles can affect both liquid and ice clouds, but many details in the involved processes are not well understood and therefore not represented in the current generation of climate models (Nenes, Murray, & Bougiatioti, 2014). The uncertainties in microphysical processes add to those related to dynamical effects on cloud formation and precipitation already discussed in Atmospheric Dynamics. Changes in cloud characteristics (e.g., droplet size) due to dust also affect the radiation budget in addition to the direct effects discussed in Direct Radiative Effects.

Studies on interactions with water clouds are complicated by the fact that pure mineral dust particles near sources have been observed to be completely hydrophobic (Kaaden et al., 2009), which would impede meaningful interactions with liquid clouds, while other studies find an ability of dust particles to form cloud condensation nuclei (CCN). The latter could be the result of coatings by soluble material (e.g., sulfates, nitrates, and chlorides) in the soil or in the atmosphere (Andreae & Rosenfeld, 2008; Wurzler, Reisin, & Levin, 2000). These have been related to anthropogenic emissions, for example of fraction ammonium sulfate (Kaaden et al., 2009). However, adsorption of water by dust minerals has been observed even without any coatings (Koretsky, Sverjensky, Salisbury, & D’Aria, 1997) and dust particles have been found to be very effective CCN (e.g., Kumar, Nenes, & Sokolik, 2009; Karydis, Kumar, Barahona, Sokolik, & Nenes, 2011). As source regions are usually dry, interactions between dust particles and liquid clouds are rare and more commonly occur after long-range transport, enhancing the likelihood of more hygroscopic behavior of originally hydrophobic particles through mixing and processing. Effects of dust on liquid clouds can also affect deep convection in later development stages (Rosenfeld, Yu, et al., 2011).

For impacts on ice formation in clouds, such chemical processing is not needed, because, due to its size and composition, mineral dust is generally regarded as the most important ice-nucleating particle (INP) worldwide (e.g., Cziczo et al., 2013; Nenes, Murray, & Bougiatioti, 2014). However, the efficiency of this process depends crucially on the chemical composition of the particle, with feldspars having been proposed to be the most active ice-nucleating component of dust (Figure 14; Atkinson et al., 2013). Generally speaking, primary ice formation can occur either homogeneously (involving only the freezing of liquid droplets) or heterogeneously (involving an INP). As the former only occurs at temperatures below −35°C, INPs play an important role in the large majority of ice clouds. Heterogeneous ice nucleation is subdivided into immersion freezing (INP is immersed within a super-cooled liquid droplet), condensation freezing (condensation of water vapor onto the INP prior to freezing), deposition freezing (deposition of water vapor directly onto the INP surface), and contact freezing (through collision between an INP and the air-liquid interface of a super-cooled droplet) (Vali, 1985), but so far it is not entirely clear which of the identified mechanisms are important under which conditions (Nenes, Murray, & Bougiatioti, 2014). It is difficult to distinguish between the different freezing processes from observations (e.g., DeMott et al., 2003), but, for example, lidar measurements show that dust particles start to act as ice nuclei across a wide range of temperatures (e.g., Ansmann et al., 2008). Laboratory studies are used to clarify the roles of freezing mechanisms (Hoose & Möhler, 2012) and to develop parameterizations for numerical models, but even in the most detailed microphysical models, the description of ice nucleation processes is far from complete.

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Figure 14. Dust and cloud microphysics. Dependence of ice-active site densities (ns) on temperature for a range of minerals common in mineral dust, which were immersed in water droplets.

Figure from Atkinson et al. (2013).

Biogeochemical Aspects

Deposited soil dust particles add essential nutrients like iron (Fe) and phosphorus (P) into terrestrial and marine ecosystems (Jickells et al., 2005; Jickells, Boyd, & Hunter, 2014). In large areas of the ocean, iron availability regulates marine productivity and hence the oceanic carbon cycle (Martin, Gordon, & Fitzwater, 1991; Shao et al., 2011). Microorganisms in the ocean use iron in enzyme systems, including those for photosynthesis and nitrogen fixation, and therefore additions of iron in a biologically usable form enhance these processes (Okin et al., 2011). In nutrient-rich regions of the oceans the addition of iron can enhance primary production, species composition, and CO2 uptake, while in nutrient-poor regions such as the subtropical Atlantic iron supply from dust can enhance nitrogen fixation (Moore, Doney, Lindsay, Mahowald, & Michaels, 2006). Overall aerosol iron solubility in the ocean is controlled by independent atmospheric and oceanic factors (Baker & Croot, 2010). The solubility of soil dust particles close to their sources is only on the order of 1% or less (Bonnet & Guieu, 2004). Photochemical processes, chemical reactions with organic acids, or cloud processing can make iron more soluble during long-range transport (Zhu, Prospero, & Millero, 1997; Meskhidze, Chameides, & Nenes, 2005; Johnson & Meskhidze, 2013), but details depend strongly on mineralogy (Journet, Desbouefs, Caqineau, & Colin, 2008). At low pH values (less than 2) iron is more easily dissolved, such that coatings of dust particles with acid compounds (e.g., sulfuric acid) may greatly enhance its availability for oceanic microorganisms. As yet, it is unknown if the iron fertilization by dust is an important contributor to the oceanic CO2 sink at a global scale. Best estimates for glacial-interglacial cycles are a contribution on the order of 30 ppm (Kohfeld & Ridgwell, 2009; Sigman, Hain, & Haug, 2010). Particularly over the open ocean, far away from river input, iron deposition through dust particles is thought to significantly contribute to ocean iron (Tagliabue et al., 2016). Through long-range transport locations far away from major sources, such as the Caribbean Sea, can be affected (Prospero & Mayol-Bracero, 2013). Changes in atmospheric dust input into the ocean on decadal, annual, or even intraseasonal scales can severely affect marine ecosystems such as coral reefs (Shinn et al., 2000) or colonies of cyanobacteria, leading to “algal bloom” (e.g., Lenes et al., 2008).

For terrestrial ecosystems, transported desert dust is suspected to contribute crucial micronutrients to nutrient-poor soils. In particular the deposition of Saharan dust into the phosphorus-limited Amazon rainforest appears to be necessary to sustain the ecosystem in its current form (Swap, Garstang, Greco, Talbot, & Kallberg, 1992; Bristow, Hudson-Edwards, & Chappell, 2010; Koren et al., 2006; Yu et al., 2015). Given the enormous biological activity of the Amazon, changes in this link have potentially substantial implications for the global carbon budget.

Impact on Hurricanes

Proposed relationships between dust from northern Africa and tropical cyclone (TC) activity over the Atlantic Ocean are reviewed in order to illustrate the full complexity of interactions between dust on one hand and weather and climate phenomena on the other hand. Research into this topic was instigated by the stark contrast between the record hurricane season of 2005, which was anomalously dust-free, and the following years of 2006 and 2007, which were dusty but quiescent. This contrast sparked some contradictory interpretations (Foltz & McPhaden, 2008b; Kerr, 2007; Lau & Kim, 2007; Sun, Lau, & Kafatos, 2008).

On short timescales, there is some evidence that direct radiative forcing by dust contributes to tropospheric stabilization through cooler sea-surface temperatures (SSTs) and a warmer and drier atmosphere (Reale, Lau, Kim, & Brin, 2009; Wong, Dessler, Mahowald, Yang, & Feng, 2009). Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical thickness (AOT) retrievals suggest a suppression of deep convection over the tropical North Atlantic in the presence of dust, associated with the warmer and drier air below 700 hPa (Wong & Dessler, 2005). Dust forcing has also been shown to modify the track of individual TCs (e.g., Chen et al., 2015). However, it appears very difficult to quantify the importance of these effects relative to Saharan Air Layer (SAL) variability unrelated to dust and variability of the tropical Atlantic in general. Consequently, the inference of causality made in some studies has to be questioned (Braun, 2010). For example, the fact that the inclusion of midlevel humidity (and temperature) measurements into meso-scale simulations provides improved forecasts of developing and non-developing systems, irrespective of the effect of dust (Biswas & Krishnamurti, 2010; Ismail et al., 2010; Sun et al., 2009; Wu, Braun, Qu, & Hao, 2006), can easily lead to misinterpretations on the role of the dust in the SAL. In general, connections between a TC and the SAL appear to be a combination of thermodynamic (usually detrimental) and dynamical mechanisms (shear, vorticity) (Bretl et al., 2015; Dunion & Velden, 2004), which vary with cyclone development stage, the relative position of the TC and SAL, and other external conditions such as SST and tropospheric shear (Jones, Cecil, & Dunion, 2007; Karyampudi & Pierce, 2002; Pan, Wu, & Shie, 2011; Sippel, Braun, & Shie, 2011; Vizy & Cook, 2009).

One problem in interpreting the literature coherently, as pointed out by Braun (2010), is the loose usage of the term SAL, which is often defined on the basis of midlevel dryness (and sometimes even shear) instead of origin, stratification, and dust content (see examples in Dunion & Marron, 2008; Dunion, 2011; Shu & Wu, 2009; Sun et al., 2009). This can be misleading, as dryness is predominantly a signature of subsidence rather than Saharan origin or aerosol composition. Aircraft measurements close to the West African continent (Zipser et al., 2009) show in fact a considerable variation in SAL stability, humidity, and dust content, which affects the impact of the SAL on TC development (Ismail et al., 2010; Reale et al., 2009). There is also evidence of dust influencing TC dynamics via cloud microphysical processes, but the ability of dust particles to serve both as cloud condensation and ice nuclei makes its effect very sensitive to dynamical details of a given TC and probably to the vertical distribution of dust and the particle size distribution (Jenkins, Pratt, & Heymsfield, 2008; Jenkins & Pratt, 2008; Jury & Santiago, 2010; Zhang, McFarquhar, Cotton, & Deng, 2009; Zhang, McFarquhar, Saleeby, & Cotton, 2007).

On timescales from interannual to decadal the emerging picture is no less complicated. Statistical results show an anticorrelation between dust in the Main Development Region (MDR) and different measures of hurricane activity on interannual timescales (Figure 15, left; Evan et al., 2008; Evan, Dunion, Foley, Heidinger, & Velden, 2006). There is good evidence for a direct radiative effect of dust on hurricanes via a cooling of the underlying SST during summer, when the shallow mixed layer allows the largest temperature response to external forcing (Schollaert & Merrill, 1998). Negative correlations between dust AOT and SST have been documented on timescales of days (Avellaneda, Serra, Minnett, & Stammer, 2010; Jury & Santiago, 2010), months (at various time lags, see Figure 15, right; Evan et al., 2008; Lau & Kim, 2007; Schollaert & Merrill, 1998), years (Avellaneda et al., 2010; Foltz & McPhaden, 2008a), and decades (Foltz & McPhaden, 2008b; Wong, Dessler, Mahowald, Colarco, & da Silva, 2008). However, the magnitude and timescale of this effect depends crucially on (a) the depth of the mixed-layer, ocean currents, and wind-induced latent heat loss (Avellaneda et al., 2010; Foltz & McPhaden, 2008a), (b) effects of other aerosols (e.g., volcanic aerosol in the stratosphere) (e.g., Evan, Vimont, Heidinger, Kossin, & Bennartz, 2009), (c) the details of the atmospheric response to the dust radiative forcing involving the turbulent and long-wave heat exchange with the atmosphere and potential feedbacks (Miller, 2012), which are neglected in many studies, and (d) maybe most important, clouds, which are also influenced by dust through cloud microphysical and dynamical effects such as dust-induced stability changes (Kaufman, Koren, Remer, Rosenfeld, & Rudich, 2005).

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Figure 15. Dust and hurricanes. Left: Standardized time series of total tropical cyclone days (line with green circles) and average dust cover (line with orange diamonds), with the dust series on an inverse scale. Both time series were created by averaging the dust coverage or summing tropical cyclone days over the region of 0°–30°N and 15°–60°W for the time period of August 20 through September 30. Figure modified from Evan et al. (2006). Right: Lag/lead relationship between Hadley SSTs and dust cover averaged over the main development region for June. Asterisks denote correlations significant at the 95% level on the basis of a two-tailed t-test.

Figure from Evan et al. (2008).

More uncertainty is introduced by dust-related biases in SST retrievals based on satellite infrared data (Foltz & McPhaden, 2008a). The literature suggests that dust radiative forcing is most important on timescales above interannual (Miller & Tegen, 1998) and accounts for about 30% of SST variability in the North Atlantic or on the order of 0.5°C (Avellaneda et al., 2010; Evan et al., 2009; Foltz & McPhaden, 2008a). These values are based upon the SST anomaly calculated using a mixed-layer energy budget, but its treatment of the response of the overlying atmosphere to dust is generally specified or highly simplified.

An interesting aspect of the dust-hurricane relationship on decadal timescales is the correlation of both features to the Atlantic Meridional Mode (AMM) and the West African monsoon along with Sahel precipitation (Wang, Dong, Evan, Foltz, & Lee, 2012; Wu, 2007). The former modifies the large-scale conditions for TC development through variations of SST and shear over the MDR (Kossin & Vimont, 2007), while changing the interhemispheric temperature gradient that drives the monsoon circulation (Foltz & McPhaden, 2008b). The latter can influence dustiness over the Atlantic through changes in dust emission via soil moisture, vegetation, and winds, along with transport through the position and strength of the African Easterly Jet (AEJ) (Prospero & Lamb, 2003; Wong et al., 2008), which in turn influences TC activity via African Easterly Wave (AEW) activity and shear. Dust radiative effects on the other hand can serve as a driver for AMM variability (Evan, Foltz, Zhang, & Vimont, 2011; Foltz & McPhaden, 2008b). Wong et al. (2008), however, argue that an influence of the SSTs on dust is more likely than vice versa, due to the coincidence of a basin-wide cooling of the ocean, while the latter would have a clear east–west gradient. Wu and Tao (2011) claim that Sahel rainfall is a key element in the link of dust to hurricane activity, as it is associated with changes to the AEJ, AEWs, and larger-scale changes in upper-level circulation and thus shear. Interestingly, though, Fink, Schrage, and Kotthaus (2010) show that the correlation between Atlantic TC activity and Sahel rainfall has deteriorated since the 1990s. A possible reason is that the improved conditions for TC genesis over the Atlantic since the mid-1990s (warmer SSTs, less troposphere-deep shear) have made TCs less sensitive to the effects of the West African monsoon.

Concluding Remarks

An attempt has been made to provide a broad overview of the state-of-the-art in research on mineral dust aerosol from northern Africa, that is, from sources in the Sahara and Sahel. The Dust Cycle described the general elements of the dust cycle: emission, transport, deposition, and involved meteorological systems. Spatial and Temporal Variability discussed ground and space-based observational systems and climatologies derived from these data with a focus on geographical and vertical distribution, and seasonal and diurnal cycles. Interactions with Weather, Climate, and Biogeochemical Processes then summarized the most important impacts of dust on weather and climate systems: radiation, cloud microphysics, atmospheric dynamics, and biogeochemical processes affecting the carbon cycle. Impacts on humans, for example through air pollution, turbidity, and soil erosion, were not covered. Finally, the specific problem of interactions between dust from Africa and Atlantic hurricane activity was discussed to illustrate the complex role dust plays in the climate system (Impact on Hurricanes).

It is hoped that a good idea of the richness and interdisciplinarity of scientific questions around this fascinating element of the Earth system has been conveyed. At the same time, this discussion is meant to provide a basis to understand challenges and opportunities for future research. By now, dust modules have been integrated into many climate and also operational weather prediction models, some already with interactions between dust and radiation (Benedetti et al., 2014; Tegen & Schulz, 2014). Interactions with cloud microphysics and the biosphere have been built into some research models, but many details of the involved processes are not well understood and require complicated chemical modifications to the dust particles. In order to enhance the operational prediction, data assimilation systems are being developed for ground- and space-based observations to correct forecast biases, improve models, and generate aerosol re-analyses, which in turn have some promise to foster our quantitative understanding of the dust cycle. Space-based remote sensing of dust has advanced in many ways, now giving us a much better model constraint in space and time, but many uncertainties remain, for example those associated with assumptions about optical properties, or dust in cloudy areas. Information on the vertical distribution of dust is also still rather limited. Despite all these efforts, models still suffer from many uncertainties related to insufficient knowledge of soil parameters, size distribution, and optical properties of dust particles as well as problems with the representation of high-wind dynamics and wet deposition processes. For Africa in particular the poor representation of deep moist convection and associated haboob dust storms is a problem (Heinold et al., 2013; Pantillon, Knippertz, Marsham, Panitz, & Bischoff-Gauss, 2016). Given the remaining limitations of both space-based remote sensing and the sparse station network in major source areas, there is an urgent need to advance our observational database and process understanding through targeted field campaigns or dedicated measurement systems, but the current geopolitical situation in and around the Sahara makes this rather challenging. In the long run, improvements of process understanding fostered by better observations will lead to improved numerical dust models, which can better quantify the dust cycle and its impacts on radiation and clouds. Only then will we be able to convincingly tackle complex interaction and feedback problems such as the relationship between dust and tropical cyclones, which, given the destructive power of hurricanes and their potential to amplify in a warming climate, is vital.

Suggested Reading

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Pye, K. (1987). Aeolian dust and dust deposits. London: Academic Press.Find this resource:

Shao, Y. (2008). Physics and modelling of wind erosion. Dordrecht, The Netherlands: Springer.Find this resource:

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