Seoul National Univ UAW2008 An assessment of uncertainties in the estimation of dust emission rate due to vegetation Eunjoo Jung & Soon-Chang Yoon School of Earth and Environmental Sciences Seoul National University

Seoul National Univ UAW2008 Purpose 1. Purpose - Improvement of dust emission scheme by evaluating uncertainties in dust emission estimation due to vegetation Method 2. Method - Sensitivity tests of dust emission scheme - Numerical simulation of East Asian dust event in Mar using regional-scale dust transport model Validation 3. Validation - PM10, LIDAR - WMO SYNOP observations Discussion and conclusion 4. Discussion and conclusion Outline

Seoul National Univ UAW2008 Model dust fluxes during dust events in 2002 Seasonal vegetation cover in East Asia March April 2002 (Uno et al., 200, JGR)

Seoul National Univ UAW2008 Drag partition scheme n : number of roughness elements b : mean breadth of roughness elements h: mean height of roughness elements S: ground area : frontal area index h b where  : the ratio of the drag coefficient for an roughness element, C D to that for the ground surface, C S having no roughness element where  : total wind shear stress acting on ground area S  R : a part of  acting on the roughness elements averaged over S  S : a part of  acting on the bare surface averaged over S (Raupach et al.,1993)

Seoul National Univ UAW2008 where -  (=A b /A f ): the ratio of roughness-element basal area to frontal area -m: the parameter accounting for the spatial inhomogeneity of surface stress  =202,  =1.45, and m=0.16  m eff = f( ) [Okin, 2008, JGR] Measured wind shear stress ratio (SSR) vs. Frontal Area Index Raupach et al. (1993, JGR)

Seoul National Univ UAW2008 Dependence of streamwise sand flux on SSR (Lancaster and Baas,1998: 0.38< u * <0.62m/s) Q: streamwise sand flux in [ML -1 T] u *t : threshold friction velocity for a smooth surface u *ts : threshold friction velocity for a rough surface with roughness elements

Seoul National Univ UAW2008 The effect of vegetation on vertical dust flux  Two field measurements 1. Gillette (1977): bare crusted soil in Texas 2. Nickling and Gillies (1993):various vegetation types in Mali, West Africa  Dust emission scheme (Shao, 2004) F(d, D, u*)=c y  f (d)[(1-  )+  p ](1+  m )(g/u * 2 )Q(u *,D, )

Seoul National Univ UAW2008  Model: regional-scale dust model (Shao et al., 2002) - Horizontal resolution: 50 km x 50 km - Vertical resolution: 25  levels  Period - Asian dust event during 7-11 March, 2004  Data - Atmospheric data interpolated from CMA T213 analysis - GIS data with horizontal resolution of 5km x 5km  Experimental Design  Validation - PM10, LIDAR, WMO SYNOP observations Numerical simulation of a dust event in Mar Experimentm=0.16m=m_eff Frontal Area Index data1EXP1AEXP1B Frontal Area Index data2EXP2AEXP2B

Seoul National Univ UAW2008 T G BTU Hu Ho Spatial distribution of vegetation cover and frontal area indices in East Asia T: the Taklamakan desert G: the Gobi desert BTU: sandy deserts in N China Hu: Hunshandake desert Ho: Horqin desert

Seoul National Univ UAW2008 NCEP MSLP reanalysis and dust weather codes during the Asian dust event L H L L L L

Seoul National Univ UAW2008 Simulated vs. measured PM10

Seoul National Univ UAW2008 Time-height cross section of model PM20 vs. LIDAR in Beijing

Seoul National Univ UAW2008 Comparison of model dust fluxes Experiment Area-averaged (95-125E,38-48N) Emission rate (  g/m 2 /s) Area-averaged (95-125E,38-48N) Dry deposition rate (  g/m 2 /s) EXP1A EXP1B 76.0 ( -27.4%) 68.8 (-27.4%) EXP2A122.2 (+16.8%)112.2 (+18.4%) EXP2B 97.3 ( +7.0%) 89.4 ( -5.6%)

Seoul National Univ UAW2008 model dust emission rates vs. friction velocity

Seoul National Univ UAW2008 Spatial distribution of threshold friction velocity

Seoul National Univ UAW2008 Conclusion The dust transport model predicted well the dust event during 9-11 March Comparison of the four simulations shows significant differences in dust fluxes from 7% to 61% each other. It is essential to quantitatively estimate the non- uniformity of wind shear stress for different vegetation types and vegetation covers It is desirable to replace frontal area index with a more directly measurable quantity such as vegetation cover.

Seoul National Univ UAW2008 Thank you!!

Seoul National Univ UAW2008 Source of uncertainties due to vegetation in dust emission scheme 1.Estimation of vegetation cover, v c, from MODIS/Terra fPAR (fraction of Photosynthetically Active Radiation) based on Darke et al. (1997) and Wittich & Hansing (1995) 2. Estimation of frontal area index,, as a function of vegetation cover, v c, following (Shao, 2000) = - C ln(1-v c ) where C is dependent on vegetation type (desert, grass, shrubs, crops, trees) 3. Non-uniformity of wind shear stress, m SSR = [(1+m  )(1-m  )] -1/2