Radiative Effects of Dust - Mineral Dust: A Key Player in the Earth System - page 276

hemisphere, and one where in the past it has been a challenge for models to represent
dust uplift and transport correctly. The problem in Asia is that pure mineral dust is
almost never observed except very close to source; the numerous anthropogenic
sources of aerosol result in a mixture in the fine mode at most times of year.
However, the dust is a dominant contributor to the coarse mode even when mixed
with anthropogenic aerosol.

11.4 Implications of Dust-Radiation Interactions

for Satellite Retrievals

Satellites observe radiation at the TOA and apply radiative transfer models and
estimates of aerosol properties to retrieve aerosol properties and, for example
surface temperature. Thus, inadequate modelling or identification of the presence
of dust which alters radiation in both the short-wave and the long-wave can lead to
biases. For example, Highwood et al. ( 2003 ) demonstrated a likely effect of greater
than 3 K consistent with dust outbreaks on eastern Atlantic sea surface temperatures
retrieved by AVHRR, whilst Weaver et al. ( 2002 ) showed that the effect of dust in
producing a systematic bias between assimilation temperatures and actual surface
temperatures can lead to problems with long-wave radiation in model simulations
that are nudged towards observations.
However, there are also issues with determining from satellites how much
dust is in the atmosphere in the first place. Particularly over land, there remain
some significant differences in the AOD retrieved from different instruments (e.g.
Carboni et al. 2012 ). The accuracy of the quantity retrieved in regions affected
by airborne dust can be affected by the optical properties assumed chosen for the
dust, in particular the phase function. Figure 11.6 shows the impact of differing
refractive indices (such as might be produced by differing dust composition) on the
widely used SEVIRI RGB Dust product. In this product, the degree of “pinkness”
represents the amount of dust in the atmosphere (as atmospheric dust load increases,
the signal in the 10.8 m channel that is used in the RGB Dust product tends to
be suppressed more rapidly than the blue and red channels, and thus, the RGB
Dust product becomes pink in colour). The “pinkness” of the RGB Dust product,
which is related to dust load, is reproduced here as a function of temperature
differences between different channels. For specific cases of dust and atmospheric
conditions and for several different commonly used refractive indices, the expected
temperatures are calculated and plotted on the coloured picture. As dust AOD
increases (towards the most pink part of Fig. 11.6 ), if the retrieval uses the optical
model of Fouquart et al. ( 1987 ) (crosses), the scene is much more likely to be
described as dusty than if the OPAC model (Hess et al. 1998 ) is used. The effect of
size distribution is less significant. A more comprehensive treatment of this subject
can be found in studies such as Brindley et al. ( 2012 ) and Bulgin et al. ( 2011 ).