A COMPARISON
OF
INTERANNUAL
SEASONAL
AND
VARIABILITY
AEROSOLS
OVER
INFERRED
BY
THE
THE
OF
SOIL
ATLANTIC
TOMS
AI
DUST
OCEAN
AND
AS
AVHRR
AOT
RETRIEVALS R. V. Cakmur Department
of Applied
Physics,
Columbia
University,
New
York,
New
York.
Physics,
Columbia
University,
New
York,
New
York,
R. L. Miller Department NASA
Ina
of Applied
Goddard
Institute
for Space
New York,
New
York.
Tegen
Max-Planck
Institute
Abstract, dust
(AOT)
daily
and
images
AOT
seasonal
variations
TOMS that
AI. the
the
On
monthly
common
increased: aerosol load
that
during
are
scales,
in the domain.
the
TOMS
AI. The
the
aerosol
load
reliable
sub-pixel
restricted
layer
are taken
partly
only
days
into
locations.
indicator
each
easily
exceeds
presence
the
of clouds.
of interannual
set
month, sampling Whether
variability
depends
reliably
Despite perature
the over
world
warming butions
the
onto
the
a coarser with
threshold
accurately a few days
AOT
due
dust
load
due
to the
the availability
its interannual
TOMS the
extent
turb
the Earth's
of
correlation
to its greater
AI should
upon
in
Calculations
average
grid,
When
correlation
ability
to
be regarded
as
of contamination
by
clouds.
Introduction
Hansen
sets,
AVHRR
climate
and scattering
the
It is suggested
uncertainty.
by the
along the
the
TOMS and AVHRR retrievals have only
satisfied
data
any particular
if
interpreting
availability.
data
a large
for the
are consistent,
when
of data
have
aerosol
is sensitive
reflectance
is low at most to both
excludes
Hemisphere to the
retrieval
data
evaluate constructed
retrieval
AI versus account
to estimate
is rarely
each
optical
Both
that
Northern
a consequence
averages
to
contribution
While
by each
common
are needed that
By rebinning
latter
in the
(AI).
a period
the
largest
for the TOMS
correlation
images
during
aerosol
index
1990,
upon
set.
implied
monthly
a threshold
is increased
infer
the
the data
loading
aerosol
and
this consistency suggests that both in any given scene. However, the two
7 to 10 daily
with
1984
make
absorption
using
of clouds AOT
--
constructed
these
of soil (or 'mineral')
(AVHRR)
aerosol
focuses
of each
is at least
month,
AVHRR
aerosols
correlation
any particular
presence
a more
time
between
variability of dust
of the
so that
at least
the
height
Radiometer (TOMS)
comparison
soil dust
property
interannual interannual
period
The
cycles
of two estimates
Resolution
Spectrometer
for the
where
seasonal
in the
per month
suggest
set
variability
High
of global, daily images, are commonly used comparison is based upon monthly averages,
eruptions.
radiative
the
averages
is substantially measure the
the
--
poor
Very
Mapping
to dominate
aerosol
AVHRR
data
Ocean,
assumed
to a different
Ozone
volcanic
Atlantic are
Total
Germany.
and interannual
Advanced
of each
from
subtropical and
cycle
Jena,
more than a decade models. The present
contamination load,
seasonal
are compared:
sets, comprising aerosol transport from
for Biogeochemistry,
The
aerosols
thickness
1.
Studies,
increase the
have have
et al., 1992;
few
actually
et al., 1999]. are
in globally
past
drawn
highly Duce,
cooled
Regional
1995;
[Houghton
Tegen
tem-
regions et al.,
of 1996;
in the observed
to aerosols, in space
surface
some
variations
attention variable
averaged
decades,
and
et al., 1996].
whose time
distri-
[Charlson
Aerosols
per-
effect),
and
droplets, times
dust
by
thus (the
aerosols by
solar
the
are
(also
contributors
acting
cloud
effect).
soil particles [Andreae,
known
in two ways: terrestrial
first,
as mineral
to aerosol
optical
lofted
dust)
radiative
the
and
most
dry
surfaces
1997].
is one of the forcing,
and
life-
common
land
et al.,
'direct'
for cloud
properties
from Tegen
(the
nuclei
By mass,
1995;
by absorbing
radiation
as condensation
changing
_indirect'
wind
and
Soil largest
may
have
increased intimeasaconsequence ofhuman disturbance aerosol transport are accounted for when interpreting the ofsoilsurfaces throughagriculture, deforestation, and TOMS AI. In contrast, the agreement between interanovergrazing [Tegen et al., 1996]. In order to quantify the nuai variations in the two retrievals -- measured by cornatural ing
and
anthropogenic
by soil dust
one needs continuous their horizontal and Original port
were
soil dust
derived
and
their
of radiative effect
of aerosol
from
distribution
ground-based
extends
back
and Prospero, Nees, 1986;
low
inferences
are
not
several
1972; Duee,
about
sufficient
forc-
decades
of both
we show
transFor
at certain
to the
1960's
lo-
[Carl-
Prospero et al., 1981; Prospero 1995]. These observations al-
particular
to map
source
the
global
regions,
but
distribution
they
of dust
aerosols, which has large regional variability. In the past two decades, satellite measurements have provided detailed inferences of the horizontal distribution of dust aerosols
over
globe
specific
[Moulin
regions
et al.,
et al., 1997;
King
as well
1997b;
Husar
et al., 1999].
as over
et al.,
Satellite
(e.g.,[Tegen
and
Fung,
entire
1995;
cycle
retrieval
after
smaller.
In section
correlation
remov-
suggests
TOMS
dust
two
reasons
We suggest
correlation
that
of the
of the
load
monthly
and
within
poor
interannual
when
constructed
using all the days presence of clouds
available in each data set. First, may preclude a sufficient number
the of
AVHRR
in any particular
the
retrievals
accurate estimation of the month to month variability.
month
monthly Second,
to allow
average along with undetected clouds
at the sub-pixel scale may introduce uncertainty into the TOMS AI. Our conclusions are presented in Section 5.
Tegen
2.
Datasets
and
TOMS
detects
of backward
scattered
An aerosol index contrast between
nels [Herman pends upon
et al., 1997; Tortes et al., 1998]. The the aerosol optical thickness (AOT),
rameterizations AGCMs
of dust
are
essential
uplift,
upon
the
There [King
validity are
coverage ticularly
dust
climate
of their
Aerosol
variability
Hemisphere these two
of soil dust calculated by High Resolution Radiome-
Optical
Thickness
of soil dust
(NH) subtropical retrievals. While
(AOT)
aerosols
over
[Husar
et al.,
et al.,
Tortes
1998],
consistent
1997;
scales could be used in the AGCM.
Comparison Both TOMS
Chiapello retrieval, AI can retrieval
1997;
the
but
height
seasonal
cycle
AI depends
aerosol
[Carlson
on
dust
pa-
implies if observed
In section
a consistent seasonal
layer,
has
a
1972;
seasonal variations
cycle in the
from
over
the
pure
properties
of the
relationship;
weak
regression
coefficient
of the
water
but
of the
Earth's
covered
UV,
only the
also
over
Rayleigh using chanAI deheight
aerosol
spatial
par-
and sea-
relating
and
ice [Herman
a low altitude
a small
AI cannot
Hsu
distinguish
the
upon
of the
for
1997].
aerosol
layer
within
upwelling roughly
1999]. measures
to derive
atmospheric
re-
et al., the
soil dust
UV
except
from more weakly absorbing [Herman et al., 1997; Torres
AVHRR
wavelength
the
small
absorbing
perturbation
et al.,
contrast,
because
is very
a kilometer of the surface aerosol types or clouds. et al., 1998;
land,
surface
by snow
because
creates
an
reflectance
AOT
column.
at
the
corresponding absorbing the entire
However,
to
aerosols thickness
AVHRR
is lim-
ited to retrieval over the ocean because presented by the nonuniform reflectivity
of the difficulty of the Earth's
land
1997].
surface
each
derives
of the
dust
tering
of
such
departures
AOT and AI is attributed to variations in the height of the aerosol layer. TOMS detects aerosols not only
that height
upon
(AI) is constructed the 340 and 380 nm
all aerosol types --- including weakly like industrial sulfates throughout
2, we describe each which an AOT and 3, we show
optical
linear
variability
630 nm
care. AOT
addition-
which
and Prospero,
et al., 1995]. In section and the conditions under be compared.
sonal
However,
features
based
UV radiation
layer,
an approximate
In
the TOMS of the
aerosol
soot,
ticles, and instrument viewing angle. [Hsu et al., 1999] use measurements from ground-based sun photometers to show that daily variations of the AOT and AI have
regions
Herman
to evaluate
of the
flectivity
from ac-
of the two retrievals requires some and AVHRR are sensitive to the
the column, upon
t)ronounced
load,
et al.,
To-
the Northern
Atlantic as inferred each dataset contains
uncertainties
various time rameterizations
and
(TOMS) Aerosol Index seasonal cycle and inter-
knowledged
ally
load global
and multi-decadal span, two retrievals are parattractive to aerosol modelers in their effort
(AVHRR)
within
response
of the aerosol
because
tal Ozone .Mapping St)ectrometer (AI). This paper compares the annual
the
estimates
However,
to evaluate the distribution their models: Advanced Very ter
and deposition.
parameterizatiou.
satellite
1999].
pa-
and Tegen, 1998], including the and this estimate will depend
of the
many
et al.,
transport,
to calculate
to aerosol forcing [Miller anthropogenic component,
(AGCM)
and
aerosols
scattering. the spectral
model
smoke,
of absorbing
ate
circulation
dust,
the presence
as soil
general
form
particular
Miller, 1998]). In particular, the observed horizontal distribution of soil dust aerosols can be used to evaluatmospheric
using This
AVHRR any
for the
averages,
4,
is substantially
when the monthly averages are formed for which both retrievals are available.
estimates
scene.
of each is much
the interannual
correlation
similar
--
of the
of dust aerosols the aerosol dis-
1994,
that
increased only days high
averages
seasonal
Herman
estimates
seasonal cycle and interannual variability are a useful test of inodels that predict tribution
the
1997;
monthly
ing the
and
record
relating
climate,
measurements.
the observational
son and
upon
and global measurements vertical distribution.
estimates aerosols,
cations
components
aerosols
an by
at 630nm. aerosol
spherical
non-spherical, rors
in retrieval
[Husar
optical
and
particles. this
et al.,
thickness
In fact,
a.ssumption
[Mishchenko
assuming
et al.,
dust may
1995].
AVHRR Mie
scat-
aerosols introduce Furthermore,
are er-
the AOTretrievalassumes a meanparticleradiusof 0.1#m,a valuethatis appropriate forsulfateaerosols but smallerthantypicaldustparticlesizes[Tegen and
Sahara,
Lacis,
and
1996;
assumed
Moulin
et al., 1997c].
to be perfect
albedo
of unity;
reflectors,
again,
this
for sulfate
aerosols
than
Lastly,
ocean
albedo
the
of the
overpass
introduced AOT
time
by
soil dust
[Hansen
[Ignatov
et al.,
retrieval
of AOT
to
et al.,
original
derived,
the
section,
inferred
by the
parison
is complicated
trievals
do not
Ocean,
(e.g.,
by
In
this
reflection the
the
dust
aerosol
Tegen
rather
aerosol
in this
et al.,
1997; that
AVHRR,
African The
second
noted
above,
viewing
angle, time
large
results
daily
AI
scatter
in addition that
its effect
ages
of the
upon
two
(The
of the
the
the
data
On
AI and
AI,
sets,
day
overpass
ages nual
of the AI remain variations in the
frequency
are
not
In contrast, curs TOMS variation
the and
surface cycle
AVHRR,
in layer
height
tions of AI by [Tortes interested in whether
and
attempt
using
the
aver-
and interanlayer. During Africa traa few kilo-
Prospero,
across
[Chiapello
the
Monthly
the
oc-
height
of
changes
in the
on a uniform
TOMS
is matched sets
day,
are
is on
over
data
1°
a 1.25 °
is missing
to the
is on
at certain
9 days,
side
ev-
frequency.
roughly
the
nadir
roughly
overpass
is around
closest
at the
locations
are available
location
the
latto
on a daily
sea-glint
ocean
frequency
with
available
and
half
of the
re-
of the
satellite
sun. the
presence
of clouds
of each
retrieval.
Clouds
from
imporby [Hsu
Rayleigh
scattering
et al., 1997].
Thus,
further exhibit
at the
a small
limits
the
a small
de-
AI wavelengths
value
of the
TOMS
retrieved
accurately
aerosols choose
present. a reflectivity
TOMS
380 nm reflectivity.
threshold,
say
with
no
distinguish these two cases, threshold to be compared to
or
else
we the
15 percent,
is adulterated
scene
If the reflectivity
exceeds
then
that
by the presence
for that
a clear
particular
we assume of clouds,
day.
and
We also
the
the
discard
discard
AI the
values
AI less than zero, since this is generally the sigof either clouds or a layer of weakly absorbing like the
whether
sulfates.
TOMS
The
the
more
results
wise noted. Husar
presented
discarded
in this
1997;
article
are based unless
half
of the
during
any
Atlantic,
(e.g.,
Herman
weakly
[Moulm
et al.,
absorbing daily
be-
1997],
aerosols
TOMS
particular
upon other-
where
the
et al., 1997b; the
presence
cause
slightly
AI retrievals
month;
to
is cho-
threshold
the NH subtropical is highest
correlation is insensitive
of 15 or 25 percent
Over
and
than
threshold
the AOT
15 percent
et al.,
of clouds
that
AVHRR
stringent
concentration
more
X, Ve find
AI and
a reflectivity
sen.
dust
-To
is be
to be
monthly
aver-
1995].
To
inferred
by
old
of 25 percent
for tile
per
month.
over
the
to account theoretical
calcula-
et al., 1998]. We are particularly the TOMS AI corroborates the
amplitude of the AVHRR dust models underestimate
re-
ages are constructed on average from 10 to 15 daily retrievals (Fig. la). For comparison, a reflectivity thresh-
et al., loading
1972].
Atlantic
the the
AI
after
are gridded at the same the two grids with respect
corresponds
this
In practice,
retrieval
angle, which oththe AI with the 6
satellite.)
of dust
we will
from
tween
transport
to the
when
away
aerosols
[Carlson
seasonal
directly
also minimizes
the
is,
in the
available while
of TOMS,
retrieval
which
time,
daily
averages
given case
at any location
aver-
of the
surface
height
original
sensitive to seasonal height of the aerosol
wintertime
adjacent
compare
the
sea-
monthly the
are
data
In the
AVHRR,
trievals
we compare than
that
That
variations
point
Both
on any
ery 6 days,
of the nature
the NH summer, soil dust originating from verses the Atlantic.Ocean in a layer centered above
difupon
layer
[Tegen
AI may represent a scene where the aerosol layer almost entirely obscured by clouds -- and cannot
retrieval:
and
(e.g.
we assume
grid
TOMS
prevents
the effect of synoptic and height of aerosol transport
rather
use of monthly
AOT
but
locations.
[Herman
instrument
aerosol
basis,
parture
daily
retrievals
each
excluding present
depend
cycle,
1° latitude
point.
availability
southern
and
importance of the instrument viewing erwise imposes cyclic variations upon
meters
by
AVHRR
et al.,
the slightly
retrievals
seasonal
AVHRR
retrievals
by each
to AOT.
To minimize variations in the
and
from
albedo,
variations
enough
is
Africa
from
represented
single
scales,
comparable. mesoscale
values.
the
region
both
scales,
comparable.
by 1° grid. Both datasets itudes; in order to match
For
At-
in TOMS.
quantities
height,
choose
Chiapello
time directly
of the
point
thus
North
aerosols
complication
aerosol
are
burning
physical
sonal
carbonaceous
biomass
ferent as
and
re-
and We
from
we assume
comthe
subtropical
load
originating
region,
This
types. NH
as
First,
predominately record variations of soil dust, North American industrial sulfates potentially in
is used
(AVHRR),
aerosol
[Li et al., 1996;
1999]).
per se, but
additional
soil
AOT.
retrieval
the aerosol layer are assumed to be of secondary tance to the AI. An identical assumption is made
longitude
a second
variability
factors.
of comparison because
by
dust
AVHRR
two
soil dust and
detect
dominated
AI and
detect
domain
lantic
we correlate
TOMS
(TOMS)
potentially our
are
longitude,
next
absorption
interannual
AOT
The
mea-
which
AVHRR
et al., 1999] who interpreted interannual AI as a proxy for changes in the AOT.
study.
In
On
AVHRR
photometer
As a result,
was
1998].
d to the
1997]).
moval
the uncertainty
sun
1995].
scattering
to be independent the
compared
are
approximation
To measure
generation
for
a single
is assumed
surements in this
with
assumptions,
was
Mie scatterers
is a better
of day.
these
retrieval
The
compare
et al.,
seasonal cycle, since this cycle downwind
certain of the
tropics, standard The in the
Fig. entire
availability deviation presence availability
makes
available
la represents period
roughly
the
of comparison;
varies from month of around 4 days. of clouds of the
5 extra
availability in
the
to month
days
averaged NH
sub-
with
a
leads to a greater reduction AVHRR daily retrievals. In
theAVHRR AOTretrieval algorithm, cloudsaredistinguished fromaerosols bytheirspectral signature, using a testthatiseffective forvalues oftheAOTlessthan2 [Husaretal., 1997] -- m fact, we found few daily values of AOT above
within 1.5.
typically
our domain
Over
the tropical
available
fewer
variations
exceeded
Atlantic,
than
less near the Intertropical shown in Fig. lb. The month
that
1.2, and
daily
10 days
retrievals
per
uncertainty to
be
that
each
ranges
remain
from
by
the
instrument
From
the
within from
data
1984
from
nearly
each the
At each minimum
decades
which
is easily
any
formed.
At
grid
using
interpolation
linear
the
preceding and only at grid
lacking
monthly
3 daily
84 months);
retrievals
otherwise,
from
the analysis.
Interpolation
daily
or more
when
images.
Pinatubo.
somewhat
averages 3 daily
the
that
can
retrievals
in
monthly
only
(out the
of a maximum
grid
point
allows
one retrieval
(Nonetheless,
our
locations
that
V_e also correlate summer
months
lnonths
over
(June
to
contains
or
to compare
trieval,
monthly
every
the
the
three are
grid point
of each
and subtracting
to the
28 potential
is 21 months. variations
Fi-
of each
are constructed of the
of data.
ourselves with
threshold
which
re-
by forming
12 calendar
a
months
this seasonal
cycle
Prospero,
at from
averages.
of Seasonal Variations
and
itude,
from
pollution
1972;
Chiapello
where
the
AVHRR
soil
dust,
AOT the
spatial retrievals
various
summertime (:ally
thick
distribution
soil dust AOT
figure, the
the
dust
[Swap
et al.,
transport
record
any
images
Trade
axe shown
aerosol mean aerosol
types of each plume
in Fig. 2. The contributing
be degraded
retrieval.
Both across
show the
an optiAtlantic
of
between
by other
aerosol
each
retrieval
Near
the
as well, peaks
A similar
aerosol
The
land
at north-
the
summer
shift
is indicated
1997a].
in the
so that
during
northward
NH summer et al.,
the
as summer approaches and the trade winds that trans-
retrieval
changes
longitudinally
equator,
poleward
1996].
(not shown), to the west;
shift
in dust
by Meteosat is accompanied
source
region.
Saharan
over the Cape Verde Islands the year, while the occurrence at the
surface
during
source regions seasonal cycle
(24°W, of east-
the winter
brings
in the Sahel [Chiais more pronounced
month,
averaged
along
15.5°N
between
the
longi-
tudes of Dakar and that the summertime
the Cape Verde Islands. Note also maximum of the AI at northern
latitudes
twice
is roughly
the
curs to the south (Fig. 3a). value of the AVHRR AOT latitude.
Africa layer
two
during centered
whereas
version of the 630nm
extending
presence
endar
figure
and
In and
TOMS AI retrieval, as indicated by Fig. 4, which the ratio of the AI and AOT as a function of cal-
the
illustrates
the
AI
in the shows
North
annual
type.
agreement
variations are small decrease in amplitude
dust additionally from pello et al., 1995]. The
AI and AVHRR to the
and
a 'dust
TOMS
mainly
each
winds
[Carlson
aerosol
shift
dust is transported 16°N) throughout
North created
retrieval has a different sensitivity. the seasonal cycle within the dust
region.
[Moulin
the
we define
the
potential
will not
during
biomass
1997]. (e.g.
both
load peaks during NH winter; the ITCZ moves northward, latitudes,
into
dominant
that
we average
dust
by
40.5°W to 18.125°W longitude and from 5.5°N to 25.5°N lat-
will
Longitudinal for a gradual
across
et al.,
is the
that
retrievals
in the
vated
of the TOMS
et al.,
aerosols
et al., 1999],
from coast),
for which each 3a and b show
region. except
America
observations
we expect and
formed
as sulfate
[Husar
in situ
region,
two
North
upon
this
1972], The
Chiapello
(e.g., [Hsu et al., 1999]). an additional plume ex-
winter
surface,
steps.
the near
wintertime near
900mb
the TOMS wavelength First,
Fig.
maximum
In contrast, shows little
These contrasts can be attributed in the height of the aerosol layer.
3. Comparison Interannual
measurements
1972;
aerosols
is interpreted
region,' extending (near the African
erly
qual-
omitted.) from our
devoid
limiting
interannual
anomalies
average
the monthly
consistently
eastward
Atlantic,
by seasonal
the correlation results
to September,
7 years);
nally,
seven-year
are
the retrievals
pos-
is excluded
and Prospero,
to carbonaceous
tending
ern
averages
ground-based
burning during the dry season The AVHRR retrieval shows
port
is constructed
itatively unchanged when these months are The 63 month threshold is chosen to exclude analysis
re-
following months. Interpolation is points having at least 63 months
sible
months
and
average
between
with
include
contamination
but
[Carlson
attributed
types Figs.
period
which
1995; Li et al., 1996; Chiapello et al., 1999]. The plume extending westward off the coast of Southern Africa is
the
available
are formed from a each month: this
monthly
points
month,
which
correlation
seven-year
by TOMS,
of AVHRR
load
effect,
the
of El Chichon
exceeded
a particular
more
the
ing winter
Based
overesti-
of retrievals
excludes
eruptions
the number
of the applied
reduce
we examine
1990,
and
This
Africa,
as dust originating from the fringes of the Sahara NH summer and additionally from the Sahel dur-
by industrial
aerosol
AI
location, monthly averages of 3 daily retrievals within
threshold (tuces
to
volcanic
would
two
set,
the
[Tortes et al., 1998]. A into tile former as a re-
footprint.
we are unable to quantify, between the two retrievals.
upon
North
identify during
introduce
the
TOMS
by the AVHRR AOT uncertainty is introduced of its larger
be
causing
as to
2 to 3 days.
undetected
retrieval,
underestimated
mated larger sult
into
and
Convergence Zone (ITCZ), standard deviation of month
in availability
clouds
are
month,
We will consider the effect of data availability correlation of the two retrievals in Section 4. Sub-pixel
none
from
occurs
[Carlson
in an
transport
is centered et al.,
et al.,
closer
1995].
AI into an equivalent retrieved by AVHRR [Hsu
ele-
and Prospero,
[Chiapello
1 of
oc-
to seasonal changes Aerosol transport off
NH summer 700 mb
that
the maximum variation with
to
Con-
AOT at involves
1999],
which
is baseduponcalculations by [Torteset used
together
the
with
AI into
verted
upon
the
1999]
derive
630 nm value.
an
the
Angstrom
most
important
of 700mb
factor of just sonal contrast AOT both
that
the
[Hsu
as the the
Based
by itself
in Fig. 4. This
and
winter
retrievals
is also roughly
maxima
suggest
of the
that
the
estimate
adjacent
are
the
uncertainty
can
be estimated
1
AI by
a
Thus,
of dust
trans-
of comparison. resemblance,
aerosol
layer
a more mation
precise on the
port.
is limited
uncertainty
comparison would vertical distribution
Nonetheless,
the
by the
seasonal
the
cycles
present
inferred
variations
Interannual by
removing
ages,
the
have
erage, annual
from
a spatial
measures
distribution
the
anomalies;
from
two
(the
sets
(the 'noise')
of gridded
daily
to be
0.2
AOT
is estimated
[Hsu
et al.,
the
of each of these
is meaningful
to the
is larger
of each 1999],
at less
TOMS
while
than
time
that
0.04
uncertainty is estimated
of the
1997].
data
the
layer
are of secondary
on interannual
time
directly
to the
AOT.
sets,
equal
to the
is roughly
When grid
the
points,
two the
prior
are
of the
compared
data
by dots.
The
over
upon
which
measurement the
of this
broader area the substantial
than the dust region dust concentrations
observations surements roughly
available of the
three
dust
days,
each
month.
aerosol
Independent
amount
according
to Fig.
mea-
are
separated
6a,
which
by shows
the lag autocorrelation of the TOMS AI falling to zero over this duration. _Ve estimate the number of independent
daily
the
number
of successive
images
apart.
(For example,
daily
days
first, fourth, counted as
images
and three
available
in each
seventh day independent
month
spaced images
by counting three
available
of the month measurements,
or more on the would be whereas
the
north
Barbados year.
coeffi-
at individual leads
cycle;
at least
to a
Fig. 8a coeffilocations
63 monthly
predominance
uncertainty,
validity
roughly
of independent
sea-
av-
of dust
over that by other aerosol types and the preof the month to month variations of each re-
the
number
of the
cycle
of the seasonal to form
Nonetheless,
of the
AI,
correlation
seasonal
are
square-root
of
to the
be compared
absence
of the
The uncertainty of the monthly averages and anomalies should be further reduced from the daily value by the
height
in the correlation coefficient. distribution of the correlation
denoted
trieval best
section,
in the
of the two retrievals is revariance shared by the two
retrievals
to the removal
are
Year
the sea-
previous
it can
re-
to may 3).
by removing
In the
of
both
importance
square
removal
sufficient
erages
agreement 7b); (Fig.
in the
period
30 percent.
reduction the spatial
without
of each the
reasonable coefficient
to
(Fig.
scales,
cycle, the correlation to 0.55 (Fig. 7c). The
cient,
for
variations
to the
is largest.
corresponding
As noted
so that sonal duced
close
of latitude
7b).
for our
dominance
variations
due
can be compared
AVHRR
variathan
condition
region
set
month
as a function
interannual
aerosol
record rather
coast,
is partly
in each
the same
variations
varia-
deviation
dust
of
month
time series exhibit by the correlation
agreement
identify
scattering dominance
AVHRR
et al.,
The two as reflected
subtropical deviation
to
to month
the
(Fig.
cient
AI
month
over
anomalies uncertainty
This
African
standard
that
anomalies
The
the
cycle
cycle
the
the
from case,
NH
predominately and reflectance
we assume
retrieval's
uncer-
near
where
6 is
In any and
month
variability.
and This
images
of the the
a necessary
transport
sonal
Thus,
would within
images
standard
uncertainty,
This
to year
Over
by the
5).
averaged
trievals
av-
that
above.
half
of interannual
seasonal
greater shows
the
[Stowe
the
data
aver-
extent
than
retrieval.
of the
layer.
deviation of the inter5. The standard devi-
correlation
images
re-
calculated
monthly
resembling
'signal')
two
aerosol sets,
the
amplitude
our
data
amplitude
tainty
typical
that
other; differbe attributed
of the
from
by the standard shown in Fig.
monthly the
cycle
the
each can
height
infortrans-
suggests
in the two data
seasonal
as indicated variability,
ation
this
in the
variations
of
height;
require detailed of the aerosol
trievals are roughly consistent with ences in the two retrievals themselves to seasonal
in this
comparison
of AOT
height
cited
large
3a).
in the
averages
Fig. 7a shows
imum
variations
monthly
to be less than
region,
by
seasonal
of the
fifth that
month.
since
redundant.
(Fig.
is especially
retrieval
AI (Fig.
of availability
in the two data sets in aerosol absorption
of the
AOT each
entirely
tions tions
source
and
c show
not
retrieval
comparison
and
4 AVHRR
is exceeded
measurement
second,
6b
independent
each
of 0.66.
for
are
a conservative
ported off Africa remains constant throughout the year, even as latitude of transport varies. Clearly, our attempt to infer seasonal variations in AOT from the TOMS AI accounting
roughly
this
the ratio
amount
region_
days
first,
Figs.
AI images
images
Fig.
the
two.)
Atlantic,
AI to an
the
dust
TOMS
on
as
of daily
upon
increase
only
the
the effect of raising the aerosol layer level near 900 mb to its summer elwould
available
count
380 nm
5% larger.)
in relating
height.
et al.,
indicates
same is roughly
factor
aerosol
mea-
in regions
by dust,
images the
of
over two. This is consistent with the seaof the ratio of the TOMS AI and AVHRR
shown
summer
Angstrom
the
photometer
measurements
latter
is con-
and sun
exponent the
is the
of [Hsu et al., 1999], from its wintertime evation
such
AOT
model
is dominated
precisely,
AOT
this
1998], is to convert
a theoretical
from
is approximately
(More
AVHRR
load
al.,
height
wavelength
upon
aerosol
AOT
using
derived
Based
where
layer Second,
value,
parameter
surements.
Thus,
AOT.
a 630 nm
dependence
exponent
aerosol
a 380nm
into
AOT
the
satisfied
within
our
figure
displays
[Moulin
et al.,
[Li et al.,
According
to
given the inclusion reduced when the
1996] Fig. of the seasonal
dust
time
scales.
region the
depends,
defined
above. over
a
in order to encompass that are observed to and
during
certain
8a,
assumptions
correlation
1997a]
downwind
correlations
toward
months that
of the are
high
seasonal cycle, are generally cycle is removed (Fig, 8b).
Despite agreement on the seasonal the TOMS AI and AVHRR AOT on interannual
two comparison
cycle of dust loading, are not well correlated
6 Theuncertainty intheTOMSAIretrieval ofsoildust the monthly averages are restricted to days when both is potentially largestduringthe NHwinter,whenthe the TOMS AI and AVHRR AOT retrievals are available. aerosol layeris closest tothesurface, resulting in a low Clouds are absent from these scenes, which otherwise valueoftheAIthatcouldbeadulterated bythepresence prevent retrieval by AVHRR and TOMS, the latter to a ofmoreweakly absorbing aerosols orclouds. Incontrast, lesser extent. The monthly anomalies are correlated at summertime
transport
well above stronger thermore, show tile
the
of dust
surface,
compared POLDER
evidence
its
the Atlantic
corner
burning
of the
and
dust
which
estimates, to just guished the
we repeat
uncertainty
idently
of the
not
seasonal
improved
all months,
aerosols
during 1996; upon
[Chiapello our com-
the
cycle,
equal
value
this
the
period
season.
\Ve also
between
1985
the
and
Dec
retrievals.
grid
correlation
the
almost exclusively by minimized the effects
of
correlations
increased
calibration,
(results
not
4. Estimation Averages
tent
over
the
were
not
shown).
NH subtropical
Atlantic,
if seasonal
Here,
interannual
is at least
partly
two
retrievals
averages when
are
and
both
weak
the result
ability of daily images of each retrieval (c.f.
highly
retrievals
of clouds
that
correlated
limit
when
are constructed
are available.
sufficient the
we "also show number
average
of daily
for any
imal correlation the data (Fig. in the AVHRR Fig. 9 shows
that
The
only
retrievals
particular
of monthly
the
using large
the
a small
the
region.
under
uncer-
number
number
of
of common
84 months,
dust
scenes,
large
averaged
over
Reflecting
the
this value is at individual
2.
consider
how
many
daily
retrievals
are
to estimate precisely the monthly anomalies, and either retrieval satisfies this threshold. To es-
timate
the
minimum
to form
an accurate
versions
of the TOMS
sonal
cycle
number
number
of daily
retrievals
monthly
average,
we correlate
AI monthly
averages
removed
from
each.
of available
days
is used
needed
with
In one version,
the
monthly
to form
two
the seathe
the
full
monthly
aild directionality
using
where
degraded discarding
there
Because
of all of
least old,
the
lle),
of the
are at least
upon
remaining
available jacent
only (out
months.
ison, but remaining
uncertainty
number
accurately
For
the
example,
daily
of aver-
in the
for a particular
'10
month
retrievals
10. In addition,
is
at locations
a corresponding
monthly average is formed by at random so that each aver10 values.
with
using
At
less
linear
(Increasing
the number
the
minimum
of 84) satisfy
months
are filled
reduced
results. an average
all the available
63 months
many retrievals of the data set
average increases as days are disthe potential error -- this calcu-
version of the daily retrievals
age is based a
precisely
of the Earth's
we ask is how the two versions
an estimate
11 shows
days
sets, when
in the degraded version full amount of available
well correlated.
case (Fig.
vari-
uncertainty
of the two data
Fig. formed
low interan-
comprised
averages than the
question before
provides
clay'
AI has
to estimate
no longer
averages that the
shared
8b) reflects in part the large AOT monthly anomalies.
polarization
8b).
needed whether
containing t POI.DER: reflectances
to the (Fig.
identical
of AVHRR daily retrievals, with a standard deviation
of just we
the
only
daily retrievals required to estimate age of any particular month.
the avail-
only
TOMS
month; anomalies
the correlation
of the
within
paucity 3 days
points
lation
ance suggests that both retrievals consistently and accurately measure the dust load of any particular scene. However,
for each
points
from
from 10 shows
in a degraded monthly carded --- along with
correlation
comprising the monthly Fig. 1). Below, we show
anomalies
relative around
are
varia-
are taken into account. share far less variance.
the
days
a potentially
Fig.
retrievals. The (:an be discarded
consisaerosol
tions in the height of transport However, the monthly anomalies that
grid
have
constructed
That is, the monthly are formed with less
Monthly
AI and AVHRR AOT provide of the seasonal cycle of the dust
we suggest
compared
averages. In the second (or 'degraded') version, averages are formed after removing observations at random.
of Retrieval
The TOMS estimates
load
the
9b),
available
are constructed averages
available
the
Next,
to
when
days
grid
AVHRR retrievals were provided the NOAA-9 satellite; while this inter-satellite
averages
daily
between AVHRR
1987,
monthly
being
computed
(Fig.
all the
even higher when restricted to summer months (Fig. 9d). While the two retrievals are highly correlated when their
tainty,
is ev-
level
using
The correlation is near 0.7 within the dust region, indicating that the two retrievals share a.s much as half their variance. The correlation and shared variance are
ourselves
of aerosol transport of soot aerosols dur-
restricted
Jan
higher
formed
monthly
is also the case at individual
AOT is not due to the lower level during NH winter, nor the presence
anomalies
these
to 0.07,
to the
a substantially
soil dust
to September), distin7. The correlation in
points, as shown in Fig. 8d. The disagreement the monthly anomalies of the TOMS AI and
ing
in
Novem-
restricting
compared
which
types. Furcoefficients
into
the correlation
the summer months (June by a darker lille in Fig.
absence
using
introduce
is much
soot
region
ber and December (at least for the year et al., 2000]). To remove these effects parison,
occurs
AI signature
to that of other aerosol l estimates of Angstrom
of biomass
southeast
across
where
of grid
locations the
than
10 daily
interpolation
the
from
available
at
thresh-
retrievals
between
threshold
points
where
10 day
ad-
63 to 74
for compar-
did not change the degree of correlation at the locations.) To increase the number of months at least
10 days,
were screened for clouds using reflectivity threshold. Within
the
TOMS
daily
retrievals
a less stringent 25 percent the dust region, this al-
lowsroughly5additional retrievals tocontribute monthly
average,
available
in an
old
allows
so that average
the
two
to be correlated again
didn't
ing
at least
each
grid
in each Fig.
month.
63 months point,
case with
different
version
did not was
15 daily monthly set,
degraded
suggesting
10 days; causes
erage.
However,
duced
to
TOMS sist
AI
--
then
able
much
the
a small
than
become
are
number 10
days,
increasingly and
removal
7 daily of the
In deriving
retrievals
that
the
erages
in each
daily
version
version
thereby separated Fig. 6a). Thus, ages
used
to
(Fig.
lld)
are
not
the
not
dust
independent.
In this
Conversely,
7 retrievals will
day
1 shows
threshold
bunched
not
that
in the
northern
the
poor
correlation
AOT
in the absence
fewer
early
for a precise
of retrievals means in any using
part
region
TOMS
estimate
month,
permitted
grid:
of the
a result by
cycle
the
presence
is,
trade
AVHRR
grid
box
to 4 ° latitude
two
5.
cy-
shown
in Fig.
12b.
result
from
as
to
AVHRR
retrieval
correlation
is not
on
the
increased (Fig. 12d). can be de-
retrievals is the
at interannual
time
presence
of undetected
AI [Tortes to quantify
et al., 1998], this effect.
scales.
One
sub-pixel although
pos-
clouds
in
we have
not
Conclusions
--
the
even
with
critethresh-
This
suggests
AI and
AVHRR
AOT
partly
by AVHRR
limited
number
of clouds.
One
away
spatial
reso-
monthly the size
by 5 ° longitude
We
compared
two
estimates
of
the
seasonal
cycle
and interannual ferred from the
variability AVHRR
of soil dust aerosols, as inAOT and TOMS AI satellite
retrievals.
data
are attractive
elers
Both
because
erage.
sets
of their
inulti-decadal
We undertook common
models,
the
features
to evaluate
load
information
lution in return for increased precision of the averages. V_re found that we had to increase of the
seasonal
interpreted
the
correlation
of the
the
including
comparison
that
distribution
AGCMs.
of the
cov-
to iden-
could
calculated
Each
mod-
and global in order
of variability
dust
to aerosol
span
be by
used
aerosol
retrievals
is sen-
different
aerosol
types.
SVe focused
our
atten-
tion upon the NH subtropical Atlantic Ocean, where soil dust makes the largest contribution to the total aerosol
or late
number of retrievals available is to reconstruct each data set
that
the
phasizes
estimate
is at least
of the
be
the
adjagained
sitive to a different aerosol property -- reflectance in the ease of AVHRR, and absorption for TOMS -- and em-
than
AI exceeds
of the region.
of the
of increasing the particular month a coarser
dust
of the seasonal
imprecise
particular
the
to im-
to derive accuare independent.
TOMS
any advantage
of the
occur
rived by considering only summer months, and suggests that there are additional reasons for the disagreement of
tify
(and
15 percent cloud reflectivity AOT retrievals exceed this
that
to the
the
throughout
old only
due
av-
averages
case,
together
be sufficient
while
the more stringent rion -- the AVHRR
for any
or re-
monthly
of the monthly average, since some of the contained within the 7 values is redundant. Fig.
reli-
region.
assumed the
monthly
images might be sufficient averages if all the images
month
to form
independent
seven daily rate monthly in the
If we in-
in the
degraded
often
presum-
obviates
rebinning,
However,
20 AVHRR grids;
data
removal
is a
the new
of the
by three or more days, according it is possible that the seven daily
calculate
together original
Nonetheless,
could
This
that
AVHRR
after
availability
ITCZ.
given
to
compris-
of the TOMS
are needed
are statistically
of the
their
points.
upon
in order
when restricted to the NH summer months This is unexpected since the 7 day threshold
the TOMS attempted
coefficients of at variance is shared
comprising
these
grid.
reis re-
which
improvement
coarser
from
retrievals
greater
av-
retrievals
other,
two
vicinity
by averaging
boxes
--
of AVHRR
availability
of missing
to each
monthly
versions
two
we have
images
locations
of 5 daily
of daily
average
this threshold,
quired
to
in the
constructed
sibility
decorrelated.
monthly
ably,
This
with the AI data
the
degraded
16 TOMS
cle is increased
to
sufficient
in the
anomalies have correlation so that at least half of the
at least
aver-
is limited
correlated full TOMS
change
was
and
AGCM
averages
in retrieval
grid
the AI
10 days
increase
of the
of a climate
63 monthly
by averaging
in
as the number
retrievals
apparently, as the
estimates
from
correlation
typical
at least
cent
10.) of the
15 daily
the original
AI monthly least 0.7 --
50 times,
the monthly average. Similarly, the when the degraded version is limited
only
fewer
that
version
that
trievals
very past
At
(The
resolution
small
but
at randora
AI. The
it remains highly formed from the
accurately is high
to only
repeated
--
have
ing at least
contain-
threshold.
removed
change
thresh-
points,
fifty calculations.
increased
retrievals, anomalies
estimate correlation
days
of the
age correlation
the
was
of the TOMS
of calculations
of grid
to either
arc
anomalies
at locations
correlation
11 is the average
When
number
according
the
monthly
agreement
to any
retrievals
reflectivity
of the
at a larger the
20 daily This
versions
affect
the degraded
15 to
7
[Li et al., 1996;
1999].
Within
inates
each
with
this
Tegen
region,
retrieval,
sulfate
and
et al.,
and
that
the
carbonaceous
small.
Both
retrievals
month
corresponding
1997;
we assume
the
to maximum
et al.,
soil dust
variability
aerosols
identify
Chiapello
that
dom-
associated
is comparatively
same
climatological
dust
loading,
includ-
ing the variation of this month with latitude. Because the AI varies with the vertical distribution of the aerosol, the
amplitude
compared sonal
of its
with
variations for,
by each
retrieval
When sharply
of the
cycles
cycle
correlation
assumption
of [Hsu
tions
height
in the
cannot However, aerosol
of the
be
directly
when layer
sea-
are ac-
dust
load
implied
from
the monthly
are comparable.
the seasonal the
cycle AOT.
height
the seasonal
reduced•
importance pared on
of the
in the
counted
averages,
seasonal
that
For
is removed between
this
comparison,
et al., 1999] of the
the
aerosol
that layer
two
retrievals
we followed year
to year
is the
varia-
are of secondary
to the AI, which thus can be directly cominterammal time scales to the AOT. In a sep-
aratestudy(tobereported uponelsewhere), wetested thisassumption by comparing the AI anddustAOT produced bytheGoddard Ozone Chemistry Aerosol Radiation
and
Transport
communication).
model
This
tial distribution of dust winds and precipitation sinks
in a tracer
monthly sonal
cycle.
scales, interannual variations of the The poor substantially
model
_,Ve found
moll
the
AI
after
and
variations
and
retrievals.
This
because
AOT
retrieval
monthly We
clouds
averages
suggest
for the
have
that
poor
anomalies vations.
limit
contamination
ever,
there
ison
of spatial
height time by
days
consistency
this
AVHRR
TOMS
AI, its
uncertainty.
is partly
correlation,
responsible
when
the
monthly
using all available daily how many daily retrievals
a reliable
age by correlating anomalies. The
of the the
larger
uncertainty
interannual
to form
than
a potentially
are constructed We estimated
needed
extent
estimate
of the
monthly
two versions of the TOMS anomalies in one version
all tim available
aver-
AI monthly were con-
structed
using
retrievals version,
per month within the dust region. In the other a certain number of observations were discarded
so that the uncertainty.
monthly When
with
than
fewer
data,
obserwere
typically
15 or more
anomaly was estimated with greater the degraded version was constructed
7 to 10 retrievals
per
month,
the corre-
lation with the original suggests that estimates
TOMS AI was quite low. This of interannual variations of soil
dust transport over the 7 retrievals per month.
Atlantic require roughly An additional constraint
from
the
3 day
7 retrievals the TOMS greater liable
to retrieve
Whether
indicator
of TOMS,
due
although
any
both
case,
of accurately years the
climatological In order
binned improved
the
to increase data
the
correlation
number any
a coarser with
the TOMS
large
effect.
In
be capable
cycle,
since
necessary
AOT
month, This
seven to form
month.
of AVHRR
particular grid.
upon
should
of any calendar
during onto
seasonal
this
correlation.
re-
in an
we inter-
correlation 8b).
That
be of lesser was
Sub-pixel
TOMS by
when
How-
the
compar-
to the
not
the
is, sub-pixel
importance.
restricted did
suggests
the
obscured
latter.
rebinning
at individThis
between
is mainly
interan-
summer
improve
the
contamination
sum-
by clouds
may be particularly important during this season, when mesoscale and synoptic variations of cloud cover associated
with The
African
high
AI and
waves
is largest.
correlation
AVHRR
interannual
of scenes
AOT
aerosol
suggest
needed month
AVHRR
old
that
per
month
result
AOT
is not
could
if a more
exclude TOMS
make
a large cloud
not
clouds.
two retrievals
the
be adjudicated 1997b],
In the
averages and thus the availability of
more
thresh-
daily
improvement. screening
using
which
retrievals This
their
region.
might
algorithm
could of the effect of
the disagreement
at interannual Meteosat
despite
our dust
meantime,
time
retrievals
restricted
be-
scales
might
[Moulin
areal
In addition,
of
scenes, but retrievals
fewer scenes. In addition, the uncertainty AI could be reduced by quantifying the
tween
of
by lack
the seven-day
a few
precise
TOMS
estimates
individual of AVHRR
monthly However,
only
sub-pixel
clude
within number
far below
we estimated;
to the
current
are limited
to estimate accurate to month variability.
the
comInon
that
variability
precision of either retrieval rather by the insufficient
et al.,
coverage,
a more
in-
precise
com-
parison of the annual cycle of dust loading may be possible using TOMS AOT retrievals that incorporate information on aerosol height more precisely and systematically than we have done here [Tortes et al., 1998]. The the
limited
interannual
presence
aerosol
in each
types.
may
include
and
sea
In
tried
to
TOMS
of aerosol troduction will can
available
index
identify
1997;
dust,
this
additional
the
Chiapello
et
al.,
[Mishchenko Despite dust
as the
and
Similarly,
that Travis,
two-channel
about aerosol the additional
particle channel
et al., 2000]. the
limited
at interannual loading,
such coefficient,
[Mishchenko
2000].
lim-
Ocean, source
1999]. The in.in the retrieval
information,
type
by
Atlantic dominant
or Angstrom
aerosol
aerosols,
carbonaceous
difference
subtropical to be the
AVHRR will replace assumptions size with inferences derived from
trievals
include
other
retrievals
carbonaceous
may
to minimize
of refraction
by
AVHRR
variability [Chiapello et al., of polarization measurements
make
particle
may also indicate
of variability
sulfates,
while
We
set
addition
industrial
salt,
correlation
data
iting our study to the NH where we expect soil dust
we re-
resulted
AI, which
mertime
to the
no agreement
averages
Similarly,
aerosols.
re-
[Tortes limita-
relatively
quantify
observations
mean
available
depends clouds serious
AVHRR
the
as a more
sub-pixel o, more
not
sufficient
days. Only due to its
variability
instrument's
and
the
load in the presence
to the
estimating
so that
be regarded
we did
TOMS
provide
trievals
the aerosol
it should
of undetected This is potentially
footprint,
of dust,
consecutive this threshold,
of interalmual
the importance et al., 1998]. tion
time
nmst not represent AI is able to exceed
ability
of clouds.
decorrelation
at least results
may
almost
months.
corn-
suggests
was
of each
a higher
7c versus
of the
AVHRR
averages
showed
that
uncertainty
of the
spatial
agreement
AOT
cloud
only
the availability
to a greater
AVHRR
are
seasonal
Fig.
is intrinsic
AOT
that both the TOMS AI and AVHRR AOT accurately estimate the aerosol load of any particular scene. However,
AI and
(c.f.
of the sea-
of the AI are dominated
using
there
precision
region
compared
points
sampling
in aerosol
to the AI on daily
dust
correlation, grid
the
dust
the removal
are constructed
two
nual
increased
In addition,
the
that
interannual agreement is in contrast to the larger correlation that results when the
anomalies
to
model.
variations AOT.
monthly
over
that
is, while
strongly
retrieval
aerosols by combining observed with prescribed dust sources and
correlated,
That
contribute
personal
a realistic
averages.
ual
of the
perfectly
Ginoux,
calculates
as due to the
monthly
spa-
transport
averages
almost
(Paul
model
preted
for
variance time
which
shared
scales,
both
data
the
by
the
seasonal
sets
agree,
two
re-
cycle
of
can
be
9 usedto constrain
dust underestimate
of aerosols AOT
models. Certain in comparison
the summertime
downwind
from
et al., 2000]; sonal
cycle
annual
variability.
to stronger
the
than
[Miller
and
Tegen,
to more
of aerosols
1999].
Larko,
and
AVHRR Paul
including
and
the
Ginoux,
Larry
conversations
with
Michael
"_Veaver.
(ATM-97-27872)
their
Cairns,
Carl
William
was
supported
the
National
and
the
Atlantic
gram of the National Oceanic istration (NA86GP0556).
that
benefited
the
sub-
and Clark Dy-
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Atmospheric
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This
preprint
was
prepared
v5.01, with the extension package version 1.6b from 1999/08/19.
with
AGU's
'AGU ++'
LATEX macros by P. W. Daly,
11 Figure
Captions
Fig. 1: Average AOT. Fig.
number
2: Climatological
mean AVHRR AVHRR AOT. 3: Seasonal
from
40.5°W
Fig.
4:
Fig.
and
5:
of the Verde
d) NH summer
year,
location,
of the
the
function
separated
each
Fig.
7:
a)
averages. unit
month Spatial
For
standard
Monthly Values
anomalies corresponding
Fig.
8:
seasonal 0.58. the
cycle The
Fig. 9: retrievals Fig.
10:
over
the
Fig.
11:
version
removed.
correlation
location
is denoted
The
The dust
number
12:
monthly
AOT,
averaged
AVHRR
a) Annual
mean
d) NH summer
zonally
AOT,
dust
AOT,
across
averaged
TOMS
b) AVHRR
AI, b) annual
(June-September)
mean
the NH subtropical
at 15.5°N
between
retrievals
with
average
c) NH summer
Atlantic
the
longitudes
the
(June-September)
seasonal TOMS
cycle AI, and
of the
AI daily over
observations
retrievals
the
dust
were
high-pass
region.
available
was computed
TOMS
of each
period,
each
(At
filtered
any
month
by counting
b)
Seasonal
by removing
AOT
including 99.9%
at locations
a) including
the
seasonal
confidence
where
AI (solid)
data
(June-September)
and
1988
is averaged
individual
for the
TOMS
daily
images
successive
days.
AVHRR but
AI. The
observations
computed
99%,
monthly
of indepedent
average
months
AI and
is computed
AOT
AVHRR
region
spatial
average
95%,
AVHRR
autocorrelation
set cycle
and been
of the
AVHRR
spatial
cycle
are denoted
by thicker
the
seasonal
cycle,
63 months
have
the
monthly
zero
of each
monthly
mean
data
and
set,
averages
c)
in (a).
lines.
cycle,
b) with
to the
a, b) 0.21,
(dotted)
to have
average
from
d) restricted are
AOT
normalized
ttle seasonal
levels
at least
has
the
seasonal
summer
months,
0.28,
0.35,
and
3 or more
daily
retrievals;
removed, with
c, d ) 0.37,
the 0.47,
otherwise,
by a dot. with
of days
the
during
monthly
averages
any particular
TOMS discarded
(after
removal
AI where until
the
of the
of each
month
seasonal
monthly
averages
degraded
version
the monthly average. Correlations are computed of daily retrievals: e.g. in panel e , this minimum Fig.
AI, and
AI and
when
retrieval
both
computed
retrievals
using
are available
only
the
days
at a grid
when
point,
both
averaged
region.
Correlation are
The
84-month
months,
As in Fig. 8, but are available,
of the
retrievals
spatial
summer
retrievals,
of lag for the TOMS
the the
the
of TOMS
to the
AOT TOMS
for a) TOMS
AOT.
or more
to NH summer
Correlation
c) restricted
over
of the
to 1990
coast).
of indepedent
by three within
year
b) Number
number
of comparison,
deviation
1984
mean
AI and
AI and
30 days.
similar.)
The
average
ease
TOMS
than
is quite
within
from
AVHRR
African
TOMS
AI, b) entire
as a function
AOT.
the
AVHRR
higher
AI, and c) AVHRR
AI and
month
AI and b) AVHRR
of the
(June-September)
frequencies
per
Islands.
TOMS
6: a) Autocorrelation
to remove
TOMS
(near
ratio
deviation
available
(June-September)
longitude
Cape
a) entire
of the
of the a) TOMS
cycle
Standard
removed,
Fig.
cycle
Sal,
retrievals
c) NH summer
to 18.125°W
Seasonal
of Dakar
average
AOT,
Fig.
of daily
As in Fig. average
8, but
is formed
with with
both at least
the
TOMS
10 daily
cycle) are has
of monthly
formed
after
averages discarding
of the daily
TOMS
AI with
retrievals
a) 1, b) 3, c) 5, d) 7, e) 10, f) 15 retrievals
a 'degraded'
at random. available
at locations where at least 63 months have the minimum is 10. Otherwise, the location is marked in yellow. and
AVHRR
retrievals.
AOT
rebinned
onto
a 4 ° latitude
by
5° grid.
Daily to form number Each
12
O)
Average
2
no.
4
of
days
6
Average
no.
8
of
doys
in
e month,
10
12
in
TOMS
14
o month,
16
18
AVHRR
, ,!
4
Figure 1. Average b) AVHRR AOT.
number
of daily
5
6
retrievals
7
available
8
9
per month
10
from
11
12
1984 to 1990 for a) TOMS
AI and
13
o)
Annuol
c)
JJAS
0.0
0.5
meon
meon
1.0
TOMS
Annuol
(84-90)
TOMS (84-90)
1.5
2.0
2.5
JJAS
d)
5.0
.3.5
0.00
0.08
0.16
meon
meon
AVHRR (84-90)
AVHRR
0.24
Figure 2. Climatological average of the TOMS AI and AVHRR AOT retrievals, AI, b) annual mean AVHRR AOT c) NH sflmrner (,]une-September) mean TOMS (June-September)
mean
AVHRR
AOT.
0.52
(84-90)
0.40
0.48
0,56
a) Annual mean TOMS AI, and d) NH summer
14
o)
TOMS
Ann
Cycle
b)
(84-90)
25
25
20
20
15
AVHRR
Ann
Cycle
(84-90)
15
o _J
10
10
Jo
FeMoApMoJu
JI
Au SeOcNoDe
Ja
FeMoApMoJu
JI Au SeOcNoDe
.... [;%i o.oo
Figure subtropical
3.
0.30
0.60
Seasonal Atlantic
0.90
cycle from
1.2o
of 40.5°W
1.50
the
a) to
1.8o
TOMS 18.125°W
2.1o
AI
0.00
and
longitude
b)
AVHRR (near
the
0.07
0.14
AOT,
averaged
African
coast).
0.21
0.28
zonally
0..35
across
0.42
the
0.49
NH
15
6
1
I
I
I
I
I
I
I
I
I
I
H-
o
