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What drives the observed variability and decadal trends in North African dust export?

What drives the observed variability and decadal trends in North African dust export?. David A. Ridley, Colette L. Heald Dept. Civil & Environmental Engineering, MIT. This work is supported by the Charles E. Reed Faculty Initiative Fund.

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What drives the observed variability and decadal trends in North African dust export?

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  1. What drives the observed variability and decadal trends in North African dust export? David A. Ridley, Colette L. Heald Dept. Civil & Environmental Engineering, MIT This work is supported by the Charles E. Reed Faculty Initiative Fund Thanks to: Joe Prospero, Charlie Koven, Kerstin Schepanski, Sophie Cowie, John Marsham and Owen Doherty.

  2. African dust aerosol Annual Dust AOD (2012) “Since the early 1990s there have been large year-to-year changes in Sahel rainfall but there is no consistent relationship to dust on Barbados or between dust and common climate indices.” • African dust accounts for half of global emissions • Health and ecosystem impacts • Radiative impacts, especially over the Atlantic • Sahel Precip Index no longer a good predictor of trans-Atlantic dust Summer dust conc Previous year’s Precip. Index J. Prospero, International Workshop on African Dust, Puerto Rico, 2011 Prospero et al. (2003) Ridley et al. (2013) Huneeus et al. (2011) Prospero et al. (1999), Griffin et al. (2001), Swap et al. (1992) Evan et al. (2006, 2010, 2011)

  3. Modelling Dust Emission GEOS-Chem chemical transport model MERRA reanalysis meteorology Wind Speed Soil Moisture DEAD dust scheme (Zender et al., 2003) Topographical source map (Koven et al., 2008) Vegetation modulation (Kim et al., 2013) Sub-grid wind parameterization (Ridley et al., 2013) Soil texture Vegetation Ginoux et al., 2001 Koven et al., 2008 Bareness fraction, Based on AVHRR NDVI • No ‘bare’ pixels  no emission • If vegetation cover > 0.3 no emission

  4. Evaluation of the dust simulation Daily AOD comparison over Africa using MODIS Deep Blue (2004-2008) Daily AOD comparison with 5 years of AERONET data at 8 sites • Seasonality and variability in dust AOD and concentration well captured WINTER SUMMER Observations GEOS-Chem Surface concentration at Barbados 5-95% 25-75% mean

  5. Variability and trends in dust AOD (DAOD) • Using 27 years of dust AOD (DAOD) derived from AVHRR & MODIS satellite data (Evan & Mukhopadhyay, 2010)

  6. Variability and trends in dust AOD (DAOD) Barbados SUMMER OBSERVATIONS SUMMER -3µg/m3 per decade MODEL -5µg/m3 per decade -0.03 per decade -0.02 per decade -0.02 per decade -0.02 per decade -0.04 per decade -0.03 per decade • Model reproduces seasonal trends observed in satellite DAOD and Barbados concentration

  7. Radiative impacts of dust trends • GEOS-Chem model coupled with the RRTMG model (Heald et al., submitted) 1982 – 2008 annual trend Surface Surface TOA +0.52 W/m2/decade +0.24 W/m2/decade • Warming trend over the mid-Atlantic of 0.52Wm-2 at surface and 0.24Wm-2 at TOA • Comparable direct radiative effect to the regional CO2 forcing since 1750

  8. What causes the trends in dust AOD METEOROLOGY CONSTANT SURFACE WINDS CONSTANT VEGETATION CONSTANT Surface winds drive the trend • Vegetation changes do not directly contribute to the trend • Precipitation and transport account for <10% close to source and 50% downwind • Surface winds account for most of trend close to source and 50% downwind • Wind stilling at dust source regions accounts for the majority of the trend in DAOD

  9. Can we rule out vegetation as a driver of trends? Summer Winter (2002-2006 minus 1982-1986) m/s • Stilling of surface winds doesn’t coincide with location of the greening

  10. Correlation between CMIP5 & reanalysis wind trends Large-scale climate-aerosol connections Reduced N. Atlantic aerosol [Booth, 2012] ? Reduced dust emission Warmer N. Atlantic SST Reduced dust emission Weaker surface winds Greening of Sahel Weaker surface winds Greening of Sahel [Cowie, 2013] Reduced inter-hemispheric SST gradient [Delworth, 2007; Hwang, 2013; Dunstone, 2013; Friedman et al., 2013] ? [Charney, 1975; Levis, 2004] Weakening of large-scale winds Northward shift of tropical rainfall ? Northward ITCZ shift [Doherty 2012, Fontaine, 2011] • Anthropogenic aerosol connection with ‘natural’ dust aerosol in the Tropics?

  11. Thank you

  12. How realistic are MERRA wind trends? • Significant trends in wind stilling across Africa and mid-Atlantic • Similar trends observed in ERA-Interim and NCEP reanalyses

  13. Cause of inter-annual variability DJFM AMJJAS • Surface winds are the main cause of variability off the coast of Africa • Transport and precipitation contribute up to two-thirds downwind • Vegetation has a negligible impact

  14. GEOS-Chem dust scheme • Increase of emissions from Bodele relative to West Africa • Small improvement relative to AERONET coarse AOD (r=0.73 and r=0.61, for winter and summer) • Increase in spatial correlation with MODIS coarse AOD (r=0.80 and r=0.75, for winter and summer

  15. Evaluation of the dust simulation 2x2.5 4x5 • Sub-grid wind PDF brings a reduction in the resolution dependence of emissions and better spatial agreement. March 2012

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