Geoscience Reference
In-Depth Information
20.1.3
Modelling dust
concentration in the atmosphere (e.g. Prospero and Lamb,
2003). Data are available from 1965 in Barbados and at
about 30 stations spread across the main ocean basins
from the early 1980s until late 1996. Aerosols are col-
lected by high-volume filter samplers, some of which are
controlled by a wind sensor system, which limits sampling
to the open-ocean sector and minimizes the impact from
local aerosol sources. Daily data are available from some
stations, mainly in the North Atlantic, while elsewhere the
data are weekly.
20.1.3.1 Introduction
Probably the largest effort in dust research since the late
1990s has gone into developing dust schemes for numeri-
cal models of climate. Initially these efforts were focused
on the Last Glacial Maximum (Joussaume, 1993) during
which dust loadings may have been an order of magnitude
higher than present (Harrison
et al.
, 2001). Recognition
of the important and complicated role that dust plays in
climate, particularly in altering the radiation budget that
drives the climate system, led to a concentration of effort
in improving the dust cycle in climate (more recently Earth
System) models. As a result of the progress made, knowl-
edge of global dust loadings and transport is increasingly
dependent on numerical models rather than observations.
Numerical models are representations of the workings
of the atmosphere based on the laws of physics. They fall
into the following categories, based on time and space
distinctions: weather forecasting models (also called nu-
merical weather prediction, NWP), global climate models,
which are used for longer-term simulations, and regional
models, where the numerical simulation covers a smaller
domain of the Earth, typically part of a continent such as
southern Africa. In all these models, space is effectively
treated as discrete grid boxes, larger in the global models
(e.g. 2.5
20.1.2.5
AERONET: Aerosol Robotic Network
AERONET is a network of ground-based remote sens-
ing aerosol sensors in the form of Cimel sun photometers
(Holben
et al.
, 1998). The network provides observations
that include cloud-screened measures of spectral aerosol
optical depth (AOD), aerosol volume size and single scat-
tering albedo. From the perspective of measuring desert
dust, the key quantification provided is that of the average
total aerosol column within the atmosphere. AERONET
now has more than 200 locations of quality-assured data
for more than one year, 26 locations for more than 5 years
and 10 locations for more than 7 years. However, most of
these are not in the known dust regions of the world and
very few are within even a few hundred kilometres of key
dust source regions.
2.5 degrees latitude-longitude) and signifi-
cantly smaller in the NWP and regional models with
×
1
/
2
20.1.2.6
Field and aircraft campaigns
degree typical and better than
1
/
4
degree possible. In many
of these models, the dust cycle is now an integral compo-
nent, which interacts with other important components of
the climate system. The core of the dust cycle components
are: dust entrainment, transport and deposition.
There are very few ground-based measurements from key
dust regions of the world. Advances in dust retrieval
through satellite remote sensing has led to the identifi-
cation of specific source regions (see Section 20.1.4 on
distribution of dust) and this, in turn, has encouraged ded-
icated campaigns to key dust regions. Notable to date
are the Saharan Mineral Dust Experiment (SAMUM),
which featured summertime observations in Morocco, the
African Multidisciplinary Monsoon Analysis (AMMA)
and its subprogrammes, e.g. the Atmospheric Radiation
Measurement (ARM) facility, which was deployed to Ni-
amey, Niger, and BoDEX 2005 (The Bodele Dust Exper-
iment) which retrieved the first ground-based data from
the Bodele Depression, Chad, in February-March 2005
(Tegen
et al.
, 2006). The Bodele is frequently referred
to as the world's most intense dust source. As described
above (dust sinks, Section 20.1.1.3), there are only a very
limited number of studies concerning the physical mea-
surement of longer-term dust deposition rates using dust
traps (e.g. Ta
et al.
, 2004; Reheis, 2006), although there are
several examples of short-term studies in specific source
20.1.3.2
Dust entrainment in models
The background to physical sediment entrainment is cov-
ered in Chapter 18. In models, dust production is assessed
at each grid box and is based essentially on a power func-
tion of wind friction velocity (
U
∗
) in excess of a threshold
value (
U
∗
t
). Wind is computed by the model as part of the
equations of motion and the characteristics of the wind
in the boundary layer and its interaction with surface fea-
tures. Height in the numerical models is dealt with in
discrete layers, of which there are generally too few in the
boundary layer to truly represent
U
∗
. Near-surface wind
speed is therefore sometimes used as a substitute.
In simple dust schemes, parameters important to en-
trainment, such as the erodible fraction, are assigned arbi-
trary (i.e. nonphysical) values in regions for which satellite
