Understanding the long-term variability of African dust as recorded in surface concentrations and TOMS observations Isabelle Chiapello (LOA, Lille, France)

Slides:



Advertisements
Similar presentations
4 th Training Course on WMO SDS-WAS products (satellite and ground observation and modeling of atmospheric dust) Casablanca-Morocco, November 17-20, 2014.
Advertisements

4th Training Course on WMO SDS-WAS products: (satellite and ground observation and modelling of atmospheric dust) November 2014, Casablanca, Morocco.
Uganda’s climate: change and variability Prof Chris Reason, UCT & Lead Author, WG1 AR5 Regional circulation and climate Climate variability Long-term projections.
Diurnal Variability of Aerosols Observed by Ground-based Networks Qian Tan (USRA), Mian Chin (GSFC), Jack Summers (EPA), Tom Eck (GSFC), Hongbin Yu (UMD),
Climatology Lecture 8 Richard Washington Variability of the General Circulation.
Climatology Climatology is the study of Earth’s climate and the factors that affect past, present, and future climatic changes. Climate describes the long-term.
Jiangfeng Wei Center for Ocean-Land-Atmosphere Studies Maryland, USA.
DIRECT TROPOSPHERIC OZONE RETRIEVALS FROM SATELLITE ULTRAVIOLET RADIANCES Alexander D. Frolov, University of Maryland Robert D. Hudson, University of.
 Similar picture from MODIS and MISR aerosol optical depth (AOD)  Both biomass and dust emissions in the Sahel during the winter season  Emissions.
TEMPLATE DESIGN © North African Dust Export: A Global 3-D Model Analysis Using MODIS, MISR, CALIPSO, and AERONET Observations.
Environmental Modeling Center ______________________________________________ Climate Change and Air Quality Workshop MCNC On the intercontinental transport.
European Geosciences Union General Assembly 2006 Vienna, Austria, 02 – 07 April 2006 Paper’s objectives: 1. Contribute to the validation of MODIS aerosol.
Princeton University Global Evaluation of a MODIS based Evapotranspiration Product Eric Wood Hongbo Su Matthew McCabe.
Climate Impacts Discussion: What economic impacts does ENSO have? What can we say about ENSO and global climate change? Are there other phenomena similar.
INTERDECADAL OSCILLATIONS OF THE SOUTH AMERICAN MONSOON AND THEIR RELATIONSHIP WITH SEA SURFACE TEMPERATURE João Paulo Jankowski Saboia Alice Marlene Grimm.
Statistical Projection of Global Climate Change Scenarios onto Hawaiian Rainfall Oliver Timm, International Pacific Research Center, SOEST, University.
Climate and Food Security Thank you to the Yaqui Valley and Indonesian Food Security Teams at Stanford 1.Seasonal Climate Forecasts 2.Natural cycles of.
Ocean Response to Global Warming William Curry Woods Hole Oceanographic Institution Wallace Stegner Center March 3, 2006.
ANTHROPOGENIC AND VOLCANIC CONTRIBUTIONS TO THE DECADAL VARIATIONS OF STRATOSPHERIC AEROSOL Mian Chin, NASA Goddard Space Flight Center Plus: Thomas Diehl,
30 years of African dust: From emission to deposition Using GEOS-Chem and MERRA to determine the causes of variability and trends David A. Ridley, Colette.
Investigation of Decadal Changes in Aerosol and Asthma Sponsors: National Aeronautics and Space Administration (NASA) NASA Goddard Space Flight Center.
3. Climate Change 3.1 Observations 3.2 Theory of Climate Change 3.3 Climate Change Prediction 3.4 The IPCC Process.
School of Earth and Environment INSTITUTE FOR CLIMATE AND ATMOSPHERIC SCIENCE Dust Variability Kerstin Schepanski k.
© Crown copyright Met Office Climate Projections for West Africa Andrew Hartley, Met Office: PARCC national workshop on climate information and species.
Applications and Limitations of Satellite Data Professor Ming-Dah Chou January 3, 2005 Department of Atmospheric Sciences National Taiwan University.
GOCART Model Study of Anthropogenic Aerosol Radiative Forcing Mian Chin NASA Goddard Space Flight Center.
Atlantic Multidecadal Variability and Its Climate Impacts in CMIP3 Models and Observations Mingfang Ting With Yochanan Kushnir, Richard Seager, Cuihua.
Occurrence of TOMS V7 Level-2 Ozone Anomalies over Cloudy Areas Xiong Liu, 1 Mike Newchurch, 1,2 and Jae Kim 1,3 1. Department of Atmospheric Science,
By Anthony R. Lupo Department of Soil, Environmental, and Atmospheric Science 302 E ABNR Building University of Missouri Columbia, MO
Using MODIS fire count data as an interim solution for estimating biomass burning emission of aerosols and trace gases Mian Chin, Tom Kucsera, Louis Giglio,
The Relations Between Solar Wind Variations and the North Atlantic Oscillation Rasheed Al-Nuaimi and Kais Al-Jumily Department of Atmospheric Sciences.
Modern Climate Change Darryn Waugh OES Summer Course, July 2015.
DYNAMO Webinar Series Dynamics of the Madden-Julian Oscillation Field Campaign Climate Variability & Predictability.
Operational assimilation of dust optical depth Bruce Ingleby, Yaswant Pradhan and Malcolm Brooks © Crown copyright 08/2013 Met Office and the Met Office.
Preliminary validation of the mineral dust transport model C. Schmechtig, L. Menut, B. Marticorena, B. Chatenet LISA, UMR 7583, 61 avenue du Général de.
Regional Scale Air Pollution Rudolf B. Husar Center for Air Pollution Impact and Trend Analysis Washington University, St. Louis, MO, USA 6 th Int. Conf.
C20C Workshop ICTP Trieste 2004 The Influence of the Ocean on the North Atlantic Climate Variability in C20C simulations with CSRIO AGCM Hodson.
Characterization of tropical convective systems Henri Laurent IRD/LTHE Cooperation with Brazil CTA (Centro Técnico Aeroespacial) CPTEC (Centro de Previsião.
Dust Modeling at the NASA Goddard Institute for Space Studies Ron Miller, Susanne Bauer, Reha Cakmur, Jan Perlwitz, Peng Xian.
Evaluation of RM3 Weather Forecasts over Western Africa Dr. Leonard M. Druyan 1 ; Dr. Matthew B. Fulakeza 1 ; Ruben Worrell 2 ; Kristal Quispe 3, and Kush.
Desert Aerosol Transport in the Mediterranean Region as Inferred from the TOMS Aerosol Index P. L. Israelevich, Z. Levin, J. H. Joseph, and E. Ganor Department.
Fog- and cloud-induced aerosol modification observed by the Aerosol Robotic Network (AERONET) Thomas F. Eck (Code 618 NASA GSFC) and Brent N. Holben (Code.
PROMISE Coordinator’s Summary of Year 2 Annual Report delivered on time (almost!) Cost statement still to be completed but expenditure and man months seem.
   Alys Thomas 1, J.T. Reager 1,2, Jay Famiglietti 1,2,3, Matt Rodell 4 1 Dept. of Earth System Science, 2 UC Center for Hydrologic Modeling, 3 Dept.
Synergy of MODIS Deep Blue and Operational Aerosol Products with MISR and SeaWiFS N. Christina Hsu and S.-C. Tsay, M. D. King, M.-J. Jeong NASA Goddard.
Introduction 1. Advantages and difficulties related to the use of optical data 2. Aerosol retrieval and comparison methodology 3. Results of the comparison.
Theory West African dust outbreaks and the relationship with North Atlantic hurricanes Amato T. Evan, Christopher S. Velden, Andrew K. Heidinger & Jason.
ESTIMATION OF SOLAR RADIATIVE IMPACT DUE TO BIOMASS BURNING OVER THE AFRICAN CONTINENT Y. Govaerts (1), G. Myhre (2), J. M. Haywood (3), T. K. Berntsen.
Northwest European High Summer Climate Variability, the West African Monsoon and the Summer North Atlantic Oscillation Jim Hurrell, NCAR, & Chris Folland,
Global and Local Dust over North America Initial Assessment by a Virtual Community on Dust Coordinated by R.
Climate Variability and Basin Scale Forcing over the North Atlantic Jim Hurrell Climate and Global Dynamics Division National Center for Atmospheric Research.
Estimating PM 2.5 from MODIS and MISR AOD Aaron van Donkelaar and Randall Martin March 2009.
Assessing the Influence of Decadal Climate Variability and Climate Change on Snowpacks in the Pacific Northwest JISAO/SMA Climate Impacts Group and the.
Ocean Response to Global Warming/Global Change William Curry Woods Hole Oceanographic Institution Environmental Defense May 12, 2005 Possible changes in.
Dust aerosols in NU-WRF – background and current status Mian Chin, Dongchul Kim, Zhining Tao.
Aerosol Radiative Forcing from combined MODIS and CERES measurements
Methods of Detection of change and feedback in semi-arid regions (North Africa and Sahel) Chehbouni A. Ghani ; L. Jarlan and E. Mougin Center of Space.
What drives the observed variability and decadal trends in North African dust export? David A. Ridley, Colette L. Heald Dept. Civil & Environmental Engineering,
Estimation of the contribution of mineral dust to the total aerosol depth: Particular focus on Atlantic Ocean G. Myhre, A. Grini, T.K. Berntsen, T.F. Berglen,
MODIS Atmosphere Products: The Importance of Record Quality and Length in Quantifying Trends and Correlations S. Platnick 1, N. Amarasinghe 1,2, P. Hubanks.
NAME SWG th Annual NOAA Climate Diagnostics and Prediction Workshop State College, Pennsylvania Oct. 28, 2005.
Indicators for Climate Change over Mauritius Mr. P Booneeady Pr. SDDV Rughooputh.
The role of Atlantic ocean on the decadal- multidecadal variability of Asian summer monsoon Observational and paleoclimate evidences Observational and.
Incorporating Satellite Time-Series data into Modeling Watson Gregg NASA/GSFC/Global Modeling and Assimilation Office Topics: Models, Satellite, and In.
The Great 20 th Century Drying of Africa Ninth Annual CCSM Workshop Climate Variability Working Group 9 July 2004, Santa Fe Jim Hurrell, Marty Hoerling,
Mayurakshi Dutta Department of Atmospheric Sciences March 20, 2003
Massachusetts Institute of Technology
The Indian Monsoon and Climate Change
A Comparison of Profiling Float and XBT Representations of Upper Layer Temperature Structure of the Northwestern Subtropical North Atlantic Robert L.
Understanding and forecasting seasonal-to-decadal climate variations
Presentation transcript:

Understanding the long-term variability of African dust as recorded in surface concentrations and TOMS observations Isabelle Chiapello (LOA, Lille, France) Cyril Moulin (LSCE, Paris, France) Joseph M. Prospero (University of Miami, USA)

Introduction Mineral 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 (14h25): Dust over West Sahara, Mauritania, and Senegal Louis Gonzales,

1 st Objective Which 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

2 nd Objective What 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 dust Recent 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 satellites Satellite sensors allow atmospheric dust observations with a good temporal frequency (daily in general) and spatial coverage METEOSAT and TOMS are not accurate sensors but they provide daily observations since more than 20 years. Moulin et al., JGR, 1997

TOMS Sensor initially planned to retrieve atmospheric ozone based on UV measurements ( 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 ( ) -TOMS/Earth-Probe ( )

TOMS Dust Optical Thickness Computed from the daily maps of AAI from TOMS/Nimbus-7 ( ) and TOMS/Earth-Probe ( ) The AAI is converted in Dust Optical Thickness (DOT) from a comparison of coincident TOMS AAI and METEOSAT DOT daily pixels over the Atlantic for (Nimbus-7) and 1997 (Earth-Probe) Chiapello & Moulin, GRL, 2002

Validation of TOMS DOT Comparison with ground-based sun-photometer measurements from the AERONET network and field campaigns in Africa (the size of a TOMS pixel is 1°x1.25°) The accuracy is not high but there is no bias with season or sensor! TOMS N7+ TOMS EP, Summer 400 pts, slope 1.08  0.02, R=0.82

TOMS DOT climatology over 20 years ( )  Set of African dust observations available over both land and ocean and for 20 years!

Variability of dust transport over the Atlantic (15-30°N, 10-30°W) Monthly averages Summer peaks + winter peaks

NAO and winter transport Chiapello & Moulin, GRL, 2002 r=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 meteorology High NAO Low NAO Winter 1986 NAO index=0.5 Winter 1989 NAO index= 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 But not summer export!

Recent evolution of drought in Sahel 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 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 Atlantic Sahel

Drought in Sahel controls summer export … and winter export south of 15°N !!

Dust and climate : summary DOT Correlation with NAO Correlation with drought WINTER SUMMER

35 years of in-situ measurements at Barbados (west Indies) Is this unique data set representative of the dust transport over the whole Atlantic ? Barbados

The Barbados is representative of the Atlantic dust export r=0.73 Winter Summer r=0.50

Barbados «records» NAO and Sahel drought Winter r=0.30 Chiapello, Moulin & Prospero, JGR, 2005 Summer r=0.65

Barbados 35-years record shows a residual increase in the dust loads ➲ There is a progressive increase of residual dust export at Barbados between 1966 and 2000 (~6 µg/m 3 over 35 years, i.e. a factor 2) We estimate the natural variability from a bi-linear regression with NAO, and Drought in Sahel SDC theoretical =6.1(SAD) (NAO) +10.4, R=0.71

Is this increase also recorded on 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/YearR/Year% OF INCREASE in 22 years

An increase coincident to semi-arid regions affected by land degradation due to human pressure Increase of population over Sahel (FAO) Wind erosion severity (UNEP/ISRIC) Increase of dust in TOMS observations Mali and Niger

Conclusions The 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 degradation An human impact is highly suspected to explain an increase of 40-50% of the dust loads measured in the last 2 decades