Dust Observations and Climatology - Mineral Dust: A Key Player in the Earth System - page 169

MISR (Kalashnikova and Kahn 2006 ), it has become possible to distinguish mineral
dust from other aerosol species with an improved accuracy.
No single satellite instrument, associated algorithm and retrieval are without
limitation. Uncertainties have manifold causes including cloud contamination,
assumptions on optical properties and variability in surface properties, as, for
example, land surface albedo and emissivity. Specificities in resolution, sampling
and coverage of satellite sensors also cause significant differences in the dust
observations provided by space measurements. Generally, different aerosol algo-
rithms and retrievals agree better over ocean than over land, where the absolute
uncertainties on AOD remain relatively high. Recently Carboni et al. ( 2012 )have
demonstrated discrepancies between different satellite aerosol products, especially
during intense dust events.
Despite progress, especially with the Deep Blue algorithm, passive remote
sensing from space of dust loads over arid continental surfaces has remained more
challenging. New algorithms are currently being developed to continue the advances
on satellite retrievals of aerosol over arid surfaces, as from POLDER polarized
multidirectional spectral measurements (Dubovik et al. 2011 ). The performance of
this kind of algorithm is promising, as it is expected to provide retrievals of an
extended set of aerosol physical and optical properties along with surface properties
with better accuracy.
Finally, progressing towards more accurate global estimates of desert dust loads
and key properties, radiative effects and impacts on air quality will necessarily
rely on integrated approaches based on multiple satellite observation analysis,
verified with ground-truth measurements from reference networks, as AERONET,
and combined to multi-scale models (Yu et al. 2006 ).
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