I. Chiapello et al., Detection of mineral dust over the North Atlantic Ocean and Africa with the Nimbus 7 TOMS, J GEO RES-A, 104(D8), 1999, pp. 9277-9291
It has recently been found that the ultraviolet measurements obtained with
the Nimbus 7 total ozone mapping spectrometer (TOMS) instrument can be used
to retrieve information on the distribution of aerosols over oceanic and c
ontinental surfaces. Here we examine the use of the derived TOMS aerosol in
dex (AI) for the detection of absorbing aerosol in terms of mineral dust ae
rosol over the North Atlantic Ocean and North Africa. Specifically, we comp
are the TOMS AI with the time series of daily aerosol measurements made in
the boundary layer at Sal Island (Cape Verde), Barbados, and Miami and in t
he free troposphere on Tenerife (Canary Islands); these sites are frequentl
y impacted by African dust events. At Tenerife, over the time period 1988-1
992, TOMS detected 80% of the African dust events that yielded daily averag
e dust concentrations greater than 20 mu g m(-3); at Barbados and Miami, TO
MS detected 65% and 44% respectively of the events over the period 1979-199
2. If we exclude events during which some of the TOMS data are missing and
also short (1-day) dust events, TOMS detected 99% of the events at Tenerife
, 97% at Barbados, and 81% at Miami. TOMS was also successful in detecting
the "low altitude" African dust events recorded at Sal during the winter se
ason. Over Africa we compare the TOMS AI data with ground-based measurement
s of aerosol optical thickness (AOT) obtained during field experiments in S
enegal and Niger; these yield a nearly linear relationship between the TOMS
AI and the AOT. Discrepancies between ground-based measurements (in terms
of dust concentrations or AOT) and TOMS AI can be attributed to a number of
factors: variations in the physical properties of the aerosol; the sensiti
vity of the TOMS response to the altitude of the aerosol layer; or the coar
se spatial resolution of the TOMS pixel. Nonetheless, our results clearly s
how that the TOMS AI provides a remarkably accurate picture of mineral dust
distributions in the atmosphere over both continental and oceanic regions.