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Tortes et al., 1998], consistent features on various time scales could be used to evaluate dust pa- rameterizations in the AGCM. Comparison of the two retrievals.

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



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-

Change

Atmospheric

J.

with

Pro-

of the

uct over

M.,

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Carlson, T. movement

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[email protected])

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

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