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An assessment of uncertainties An assessment of uncertainties in the estimation of dust emission in the estimation of dust emission rate due to vegetationrate due to vegetation

2008. 7. 2Eunjoo Jung & Soon-Chang Yoon

School of Earth and Environmental SciencesSeoul National University

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1. PurposePurpose - Improvement of dust emission scheme by evaluating uncertainties in dust emission estimation due to vegetation 2. MethodMethod - Sensitivity tests of dust emission scheme - Numerical simulation of East Asian dust event in Mar. 2004 using regional-scale dust transport model3. ValidationValidation - PM10, LIDAR - WMO SYNOP observations4. Discussion and conclusionDiscussion and conclusion

OutlineOutline

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Model dust fluxes during dust events in 2002

Seasonal vegetation cover in East Asia

15-25 March 2002 4-14 April 2002

(Uno et al., 200, JGR)

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Drag partition schemeDrag partition scheme

n : number of roughness elementsb : mean breadth of roughness elementsh: mean height of roughness elementsS: ground area

: frontal area index

S

nbh

h

b

where : the ratio of the drag coefficient for an roughness element, CD to that for the ground surface, CS 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

SSRCC SD

s

)/(1

1(Raupach et al.,1993)(Raupach et al.,1993)

SR

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where - (=Ab/Af): 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=0.16meff = f() [Okin, 2008, JGR]

Measured wind shear stress ratio (SSR) vs. Frontal Area Index

)1)(1(

1"

mmSSR s

Raupach et al. (1993, JGR)Raupach et al. (1993, JGR)

)1)(1(

1

)1(

'

cc

Ss

vvSSR

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Dependence of streamwise sand flux on SSR

(Lancaster and Baas,1998: 0.38<u*<0.62m/s)

),1979,(11),(2*

2*

*

*3*** JGRWhite

u

u

u

uug

uuQ tststS

)(**

* fu

SSR

uu ttts

Q: streamwise sand flux in [ML-1T] u*t: threshold friction velocity for a smooth surfaceu*ts: threshold friction velocity for a rough surface with roughness elements

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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*)=cyf(d)[(1-)+p](1+m)(g/u*

2)Q(u*,D,)

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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. 2004

Experiment m=0.16 m=m_eff

Frontal Area Index data1 EXP1A EXP1B

Frontal Area Index data2 EXP2A EXP2B

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T

G

BTUHu Ho

Spatial distribution of vegetation cover and frontal area indices in East Asia

T: the Taklamakan desertG: the Gobi desertBTU: sandy deserts in N ChinaHu: Hunshandake desertHo: Horqin desert

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NCEP MSLP reanalysis and dust weather codes during the Asian dust event

LL

HH

LL

LL

LL

LL

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Simulated vs. measured PM10

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Time-height cross section of model PM20vs. LIDAR in Beijing

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Comparison of model dust fluxes

Experiment

Area-averaged

(95-125E,38-48N)

Emission rate (g/m2/s)

Area-averaged

(95-125E,38-48N)

Dry deposition rate (g/m2/s)EXP1A 104.6 94.8EXP1B 76.0 ( -27.4%) 68.8 (-27.4%)EXP2A 122.2 (+16.8%) 112.2 (+18.4%)EXP2B 97.3 ( +7.0%) 89.4 ( -5.6%)

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model dust emission rates vs. friction velocity

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Spatial distribution of threshold friction velocity

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Conclusion

The dust transport model predicted well the dust event during 9-11 March 2004.

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.

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Thank you!!

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Source of uncertainties due to vegetation in dust emission scheme

1. Estimation of vegetation cover, vc, 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, vc, following (Shao, 2000) = - C ln(1-vc) 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