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Understanding the long-term Understanding the long-term variability of African dust as recorded variability of African dust as recorded in surface concentrations and TOMS in surface concentrations and TOMS
observationsobservations
Isabelle Chiapello (LOA, Lille, France)Isabelle Chiapello (LOA, Lille, France)
Cyril Moulin (LSCE, Paris, France) Cyril Moulin (LSCE, Paris, France)
Joseph M. Prospero (University of Miami, Joseph M. Prospero (University of Miami, USA)USA)
IntroductionIntroductionMineral dust are emitted by wind erosion of arid and semi-arid areas. Particles are transported far from their source-regions over oceans (more than thousands kilometers). The main source is Africa (Sahara and Sahel).
Mineral dust is thought to play an important role in climate processes, but their radiative effect is highly uncertain (sign unknown). Addidtionnally dust has an impact on biogeochemical cycles, atmospheric chemistry, health, …
Mineral dust is characterized by a high spatial and temporal variability (daily, seasonal and interannual)
The natural variability is so high that there is a lack of reliable estimates of the anthropogenic fraction of mineral dust (related to human pressure in the Sahel region)
MODIS January 26 2003 (14h25): Dust over West Sahara, Mauritania, and Senegal
Louis Gonzales, http://www-loa.univ-lille1.fr/
11stst Objective ObjectiveWhich climate factors control the natural varibility of the dust transport from Africa ?
Prospero & Nees (1986) have shown a positive correlation between summer Barbados concentration and Sahel drought
Changes in the intensity of the emissions
Moulin et al. (1997) have shown a positive correlation between METEOSAT/VIS DOT over the Atlantic and the North Atlantic Oscillation (NAO)
Changes in the tranport pattern
Here we use 20 years of TOMS data to understand these impacts
22ndnd Objective ObjectiveWhat is the impact of Sahelian population increase on African dust emissions (if it exists) ?
Sokolik et al. (1996) suggest an anthropic contribution between 30 and 50% (dust from degraded soils)Prospero et al. (2002) show that the largest and most active dust sources are located in regions of Sahara where there is little or no human activity, suggesting a low anthropic component of dustRecent estimates from models (Tegen et al., 2004; Mahowald et al., 2004) vary from <10% to 0-50% !!!
➲ The analysis of long-term ground-based (35 years) and satellite (20 years) dust observations should allow to progress in our investigation of the natural component of African dust vs that related to human induced soil degradation
The satellitesThe satellitesSatellite sensors allow atmospheric dust observations with a good temporal frequency (daily in general) and spatial coverageMETEOSAT and TOMS are not accurate sensors but they provide daily observations since more than 20 years.
Moulin et al., JGR, 1997
TOMSTOMSSensor initially planned to retrieve atmospheric ozone based on UV measurements (300-400 nm).Contrary to METEOSAT, TOMS provides a qualitative index of aerosols (Absorbing Aerosol Index or AAI), which is available at global scale over both land and oceans.
Herman et al., JGR, 1997 NASA/GSFC
2 TOMS sensors have been used:
-TOMS/Nimbus 7 (1979-1992)
-TOMS/Earth-Probe (1997-2000)
TOMS Dust Optical TOMS Dust Optical ThicknessThickness
Computed from the daily maps of AAI from TOMS/Nimbus-7 (1979-1992) andTOMS/Earth-Probe (1997-2000)
http://jwocky.gsfc.nasa.gov/aerosols/aerosols.html
The AAI is converted in Dust OpticalThickness (DOT) from a comparison of coincident TOMS AAI and METEOSAT DOT daily pixels over the Atlantic for 1986-88 (Nimbus-7) and 1997 (Earth-Probe)
Chiapello & Moulin, GRL, 2002
Validation of TOMS DOTValidation of TOMS DOT
Comparison with ground-basedsun-photometer measurements from the AERONET network and field campaigns in Africa(the size of a TOMS pixel is1°x1.25°)
The accuracy is not high but there is no bias with season or sensor! 0,0
0,4
0,8
1,2
1,6
2,0
0,0 0,4 0,8 1,2 1,6 2,0
Sun-Photometer AOT
TO
MS
DO
T
Cape Verde IslandDakarBanizoumbouGaoM'Bour
TOMS N7+ TOMS EP, Summer
400 pts, slope 1.08 0.02, R=0.82
TOMS DOT climatology TOMS DOT climatology over 20 years (1979-over 20 years (1979-
2000)2000)
Set of African dust observations available over both land and ocean and for 20 years!
Variability of dust transport Variability of dust transport over the Atlantic (15-30°N, 10-over the Atlantic (15-30°N, 10-
30°W)30°W)
0,0
0,2
0,4
0,6
0,8
1,0
Mea
n D
iust
Op
tica
l Th
ickn
ess
Mean METEOSAT DOTMean Nimbus 7 TOMS DOTMean Earth-Probe TOMS DOT
Monthly averages
Summer peaks + winter peaks
NAO and winter transportNAO and winter transport
Chiapello & Moulin, GRL, 2002
-10
-8
-6
-4
-2
0
2
4
6
1980 1985 1990 1995 2000
DO
T
NA
O Index
Year
0.1
0.2
0.3
0r=0.51
The North Atlantic Oscillation depends partly on the intensity of the Açores high pressure center and controls the meteorological conditions in winter over north Atlantic.
We use the winter NAO index of Hurrell (1995) updated each year
High variability of the winter dust export over the Atlantic
linked to the NAO
NAO and meteorologyNAO and meteorology High NAO Low NAO
Winter 1986 NAO index=0.5Winter 1989 NAO index=5.07
+ Trades - Trades
Changes in strength and location of the Azores anticyclone
exert a strong influence on winter
dust transport
The NAO exerts a strong influence on the large-scale variations of both
atmospheric circulation and hydrological cycle in the NH
NAO controls winter export ...NAO controls winter export ...
0.1 1.25 0.4 1.0
But not summer export!But not summer export!
0.1 1.25 0.4 1.0
Recent evolution of drought Recent evolution of drought in Sahelin Sahel
Anual rainfall index in Sahel
-1,5
-1
-0,5
0
0,5
1
1960
1962
1964
1966
1968
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
Nicholson, 1993Lhote, 2002 r=0,9
Start of TOMS observations
L’hôte et al. (2002)
Drought dominates since 1970
Only 3 wet years ( 1975, 1994 and1999), among which 2 are recent
At the end of 2000 the drought continues, although it is less extended geographically, the wet years are still very isolated from each other
Annual rainfall over Sahel
We use a Sahelian Annual Drought (SAD) index derived from rainfall index of L’Hôte et al. (2002).
An impact of Sahel An impact of Sahel drought ?drought ?
Rain in the Sahel occur between July and September and control the drought conditions, and consequently dust emissions, for the rest of the year.
Sahel/Atlantic: r=0.88
SAD/Atlantic: r=0.44
SAD/Sahel: r=0.56
Moulin & Chiapello, GRL, 2004
1980 1985 1990 1995 2000
DO
TSR
D Index
Year
-1.5
-1.0
-0.5
0.0
0.5
0.2
0.4
0.6
0.8
Atlantic
Sahel
Drought in Sahel controls summer Drought in Sahel controls summer export ...export ...
0.1 1.25 0.4 1.0
… … and winter export south of 15°N !!and winter export south of 15°N !!
0.1 1.25 0.4 1.0
Dust and climate : summaryDust and climate : summary
DOTCorrelationwith NAO
Correlationwith drought
WINTER
SUMMER
35 years of in-situ 35 years of in-situ measurements at Barbados measurements at Barbados
(west Indies)(west Indies)
0
10
20
30
40
50
60
70
Mo
nth
y S
DC
(µ
g/m
3)
0
5
10
15
20
25
An
nu
al S
DC
(µ
g/m
3)
Is this unique data set representative of the dust transport over the whole Atlantic ?
Barbados
The Barbados is The Barbados is representative of the representative of the
Atlantic dust exportAtlantic dust export
0
10
20
30
SD
C (
µg
/m3
)
0
0,1
0,2
0,3
0,4
Sa
tell
ite
DO
T
Atlantic (satellite)
Barbados (ground)
r=0.73Winter
0
10
20
30
40
50
60
1966 1970 1974 1978 1982 1986 1990 1994 1998
SD
C (
µg
/m3
)
0
0,2
0,4
0,6
0,8
1
Sa
tell
ite
DO
T
Barbados (ground)
Atlantic (satellite)
Sahel (satellite)
Summer r=0.50
Barbados «records» NAO and Barbados «records» NAO and Sahel droughtSahel drought
0
10
20
30
40
50
60
1966 1970 1974 1978 1982 1986 1990 1994 1998
SD
C (
µg
/m3
)
-1
-0,5
0
0,5
1
1,5
SA
D I
nd
ex
Winter r=0.30
Chiapello, Moulin & Prospero, JGR, 2005
0
5
10
15
20
25
30
1966 1970 1974 1978 1982 1986 1990 1994 1998
SD
C (
µg
/m3
)
-6
-4
-2
0
2
4
6
NA
O I
nd
ex
Summer r=0.65
Barbados 35-years record Barbados 35-years record shows a residual increase in shows a residual increase in
the dust loadsthe dust loads
➲ There is a progressive increase of residual dust export at Barbados between 1966 and 2000 (~6 µg/m3 over 35 years, i.e. a factor 2)
-10
0
10
20
30
1965 1970 1975 1980 1985 1990 1995 2000Year
SD
C (
µg
/m3
)
MEASUREMENTSESTIMATED NATURAL VARIABILITYRESIDUAL TRENDINCREASE 0,17 µgm-3/Year, R=0,50 We estimate the natural
variability from a bi-linear regression with NAO, and Drought in Sahel
SDCtheoretical=6.1(SAD) + 0.85(NAO) +10.4, R=0.71
Is this increase also recorded on Is this increase also recorded on 20 years of TOMS observations?20 years of TOMS observations?
For each TOMS pixel, we estimate the natural variability from a bi-linear regression with NAO, and drought in Sahel (if R>0.6)
➲ The residual TOMS DOT show a linear increase with year over Atlantic and some Sahel regions
SLOPE/Year R/Year % OF INCREASE in 22 years
An increase coincident to semi-An increase coincident to semi-arid regions affected by land arid regions affected by land degradation due to human degradation due to human
pressurepressurePopulation Sahel
0
5000
10000
15000
1965 1970 1975 1980 1985 1990 1995 2000 2005
SenegalMauritaniaMaliBurkina FasoNigerChad
Increase of population over Sahel (FAO)
Wind erosion severity (UNEP/ISRIC)
Increase of dust in TOMS observations
Mali and Niger
ConclusionsConclusionsThe ground-based and satellite long-term African dust records show:
Intensity of dust transport is influenced by NAO (winter) and strongly controled by Sahel drought (summer and winter). Prospero & Nees (1986) and Moulin et al. (1997) were right !
Most of the year-to-year variability of transport is related to emissions over Sahel not over Sahara
When removing this natural variability, there is a progressive increase in the 35-years dust loads at Barbados, also recorded in the 20-years TOMS observations over Atlantic and some Sahel regions affected by soil degradationAn human impact is highly suspected to explain an increase of 40-50% of the dust loads measured in the last 2 decades