A numerical simulation of dust storms in China

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<ul><li><p>Environmental Modelling &amp; Software 19 (2004) 141151www.elsevier.com/locate/envsoft</p><p>A numerical simulation of dust storms in ChinaZhenxin Song </p><p>The Atmospheric Science Department of Lanzhou University, Lanzhou, 730000, Peoples Republic of ChinaReceived 30 September 2002; received in revised form 20 January 2003; accepted 18 February 2003</p><p>Abstract</p><p>Wind erosion occurs in many arid, semiarid and agricultural areas of the world. The desert areas of China, which occupyapproximately 13% of Chinas total surface area, are major sources of Asian dust. The major wind-erosion areas are the sandylands in western and northwestern China together with the extensive regions of the Gobi desert in northern and northeastern China,especially along the basin of the Yellow River. In this paper, dust storms which occurred in China in the spring of 2002 weresimulated using an integrated numerical modeling system.</p><p>The purpose of the simulation is to produce quantitative predictions of wind erosion on regional scales. The integrated winderosion modeling system used in this study coupled the following three major components: (1) An atmospheric prediction model,together with a land-surface model; (2) a wind-erosion model and (3) a geographic information database. The atmospheric modelprovides the necessary input data for the wind erosion scheme, including wind speed and precipitation. It also provides input datafor the land-surface model that produces predictions for soil moisture. Dust transport and deposition are also considered in theatmospheric model. The wind-erosion model predicts streamwise saltation and dust emission rate for given atmospheric, soil andland surface conditions. The geographic information database provides spatially distributed parameters, such as soil type and veg-etation coverage, for the atmospheric, land surface and wind erosion models.</p><p>Dust storms in China occur mainly in spring and winter, but most frequently in April. In spring, surface soils frozen in theprevious winter become especially loose, creating a favorable condition for wind erosion. As an example, the severe dust stormsof 1520 March were simulated. The results show the integrated modeling system can simulate the main characteristics of the duststorms. The system produced estimates of wind erosion intensity and patterns that are in agreement with observations. Such asystem offers the possibility of determining wind erosion patterns on broad scales with high spatial resolution, as well as dusttransport and deposition. 2003 Elsevier Ltd. All rights reserved.</p><p>Keywords: Wind erosion; Dust storm; Numerical simulation; Integrated modeling system</p><p>1. Introduction</p><p>Wind erosion is a serious environmental problem inarid and semi-arid regions of China and in many otherparts of the world. Strong wind erosion events, such assevere dust storms, may threaten human lives and causesubstantial economic damage. The northwestern Chinaregion is one part of the central Asia dust storm area.The desert areas of China, which occupy approximately13% of Chinas total surface areas, are major sources ofAsian dust. These areas include the temperate arid land</p><p> Present address: National Meteorological Centre, Zhong GuancunSouth Street 46, Beijing 100081, China. Tel.: +86-10-6840-7469; fax:+86-10-6840-8584.</p><p>E-mail address: songzhenxin@vip.sina.com (Z. Song).</p><p>1364-8152/$ - see front matter 2003 Elsevier Ltd. All rights reserved.doi:10.1016/S1364-8152(03)00116-6</p><p>from 75E to 125E and from 35N to 50N (Liu, 1985).The major wind erosion areas are sandy lands in westernand northwestern China together with the extensiveregions of the Gobi desert in northern and northeasternChina, especially along the basin of the Yellow River(Liu, 1985; Walker, 1982). The dust storms occurring inthe north part of China and Mongolia are called EastAsian dust weather. Recently, dust storms occurred fre-quently in the spring in China, which caused the wideattention of the public and the government. Wind erosionis an environmental process influenced by geological andclimatic variations as well as human activities. It occurswhen a soil surface is unprotected by vegetation coverand sufficiently dry, under such conditions, wind is ableto pick up sand sized particles, which bounce along thesurface and eject more particles, including dust particles.</p></li><li><p>142 Z. Song / Environmental Modelling &amp; Software 19 (2004) 141151</p><p>Those dust particles, which usually contain most of theorganic matter and nutrients, may be carried a long dis-tance by the wind, notably as dust storm or dust hazes.It reduces soil productivity and leads to land degra-dation. Wind erosion causes loss to public utilities. Forinstance, dust suspension reduces visibility, sandblastingdestroys young crops, and dust related air pollutioncauses a health hazard, etc. Hence, the simulation andforecast of a dust storm is not only important for longterm sustainable agriculture but also has significanteconomic benefits.</p><p>Considerable insight has been gained into the physicsof wind erosion since Bagnold published his pioneerwork The Physics of Blown Sand and Desert Dunes in1941 (Bagnold, 1941). Suspension, saltation, and creepare the three distinct modes which occur during winderosion (Bagnold, 1941). Shao (2000) treats the physicsof wind erosion rigorously from the viewpoint of fluiddynamics and soil physics. The purpose of developing awind erosion modeling system is to produce a quantitat-ive prediction of wind erosion on scales from paddockto global. The system should have the capacity of mode-ling the complete wind erosion process, from particleentrainment through transport to deposition. It is a formi-dable task because wind erosion is governed by a widerange of factors involving atmospheric conditions, soilstates and surface properities. A lot of progress on thesimulation of dust weather has made. The first attempt tocombine the information of atmospheric data with land-surface data for wind erosion assessment was made byGillette and Hanson (1989) in their investigation of thespatial and temporal variations of dust production in theUnited States. In atmospheric studies, dust emission andtransport have been under research since the late eighties(e.g. Westphal et al., 1988; Tegen and Fung, 1994,1995). However, in most of these studies, crude winderosion schemes and coarse land surface data were used,which limited the reliability of the modeling results.Marticorena and Bergametti (1995); Shao et al. (1996)and Marticorena et al. (1997) have developed betterwind erosion schemes which account for the impact ofsurface properties on sand drift and dust emission. Shaoand Leslie (1997) and Lu and Shao (2001) havedeveloped and implemented an almost fully integratedwind erosion modeling and prediction system.</p><p>In the spring of 2002, a research group was estab-lished in CMA (Chinese MeteorologicalAdministration). Members of the group come from NMC(National Meteorological Centre), NSMC (National Sat-ellite Meteorological Centre), IAP CAS (Institute ofAtmospheric Physics, Chinese Academy of Sciences)and IGE CAS (Institute of Geography, Chinese Acad-emy of Sciences). The Group used an integrated winderosion modeling system developed by Shao and Li(1999 and Shao and Lu, 2000), land surface data andGIS data to make real time forecast of dust storms that</p><p>occurred in China from March to May in 2002. Duringthese periods, NMC provided numerical forecasts pro-ducts on dust weather every day. It is the first real timeforecast of dust weather in China. In this paper, wereport the basic facts on dust simulation and predictionin China in the spring of 2002. At the same time themodel results are compared with observation images.</p><p>2. An integrated wind erosion prediction system</p><p>2.1. System structure</p><p>The framework of an integrated wind erosion mode-ling system is as illustrated in Fig. 1. It is composed ofan atmospheric model, a land surface scheme, a winderosion scheme, a transport and deposition scheme anda geographic information database. The atmosphericmodel provides input data for other three model compo-nents. The land surface scheme simulates energy,momentum and mass exchanges between the atmos-phere, soil and vegetation, but more important in thecontext of wind erosion modeling, it produces the soilmoisture as an output. The wind erosion scheme obtainsfriction velocity from the atmospheric model, soil moist-ure from the land surface scheme and other spatially dis-tributed parameters from the GIS database. The winderosion scheme predicts streamwise saltation flux anddust emission rate for different particle-size groups. Thetransport and deposition model obtains flow velocity,turbulence data and precipitation from the atmosphericmodel and dust emission rate and particle-size infor-mation from the wind erosion scheme. Fig. 1 also illus-trates a possible computational procedure, the atmos-pheric model is first run after initialization for</p><p>Fig. 1. The structure of integrated wind erosion modeling systemconsisting of an atmospheric prediction model, a land surface model,wind erosion model, a transport and deposition scheme and a GIS data-base.</p></li><li><p>143Z. Song / Environmental Modelling &amp; Software 19 (2004) 141151</p><p>atmospheric dynamics and atmospheric physics. This isfollowed by running the land surface scheme and winderosion scheme. Finally, the calculation of dust transportand deposition is carried out.</p><p>2.2. Weather prediction model</p><p>The atmospheric model of the integrated system is ahigh resolution limited area weather prediction modeldeveloped at The University of New South Wales byLeslie and his colleagues (Leslie and Purser, 1991),referred to as HIRES (High Resolution Limited AreaModel). It is a primitive equation model on a Lambert-Conformal projection and utilizes the s coordinate withthe Arakawa C grid. The equation system used fornumerical weather prediction consists of seven basicequations for velocity components, the continuity equ-ation, the thermodynamic equation, the moisture equ-ation and the equation of state. As dust transport is alsoof concern, the dust concentration equation has beenadded to the equation system. The simulation area is30E, 5N to 180E, 65N with spatial resolution of 50km. The area of data analysis is 72E, 5N to 148E,53N. The atmospheric data required for HIRES initialis-ation and boundary conditions are derived from theT213-GCM of the China Meteorological Administration.In the vertical, the atmosphere is divided into 16 layers.An advanced soil moisture parameterization scheme hasbeen linked (Irannejad and Shao, 1998).</p><p>2.3. Wind erosion model</p><p>The wind erosion model comprises three key para-meterizations representing: (i) the erosion threshold fric-tion velocity ut , (ii) the streamwise sand flux Q, (iii)the dust emission flux F(i) for N size classes of dustparticles. The modeling of these processes is based,respectively, on a model of the wind erosion attenuationby roughness elements, the saltation model of Owen(1964). The main outputs from the wind erosion modelare threshold velocity ut (m/s), horizontal sand flux Q(of dimensions M L2 T1), and vertical dust flux F(g/m2s). The vertical dust flux F then become an inputas the dust source term in the dust transport model. Inour simulation and forecast six particle bins are used inthe model. A division of dust particles into different sizegroups has been proposed to be d2 m, 2 d11m, 11 d22 m, 22 d40 m, 40 d80m and d 80 m. It is assumed that particles sus-pended in the atmosphere are composed of N particlesize , each with a size di (i=1,N). The discussion islimited to a single particle size, where the multi-particlecase can be reproduced by superimposing the single par-ticle situations. If the concentration of the ith particle isci = c(di), then the total concentration is</p><p>ctotal Ni=1</p><p>ci</p><p>. The transport model predicts atmospheric dust concen-tration by solving a continuity equation of dust writtenin the form of Eqs. (1) and (2). Writing the equations toa s coordinate, producespsc(d)t </p><p>psuc(d)x </p><p>psvc(d)y </p><p>sc(d)(pss</p><p> grwt) psxKphr</p><p>c(d) /rx ps</p><p>yKphr</p><p>c(d) /ry (1)</p><p>g2</p><p>pssKphr</p><p>3c(d) /rs</p><p>with boundary conditions</p><p>c(d)(pss grwt)</p><p>g2</p><p>psKpzr3</p><p>c(d)s grF(d) at the surface</p><p>c(d) /rz 0 at the top</p><p>(2)</p><p>where c(d) is the concentration of dust particles of diam-eter d, wt is the settling velocity of particles (which is afunction of d), and F is the vertical dust flux; u, v, sand ps are wind velocity and surface pressure, respect-ively, and r is air density. The horizontal dust particlediffusivity Kph is assumed to be equal in the x and ydirections. The vertical dust particle diffusivity Kpz isassumed to be a function of the particle diameter d.</p><p>2.4. Dust emission model</p><p>Lu and Shao (1999) have proposed a dust-emissionmodel which, in contrast to energy-based models, esti-mates dust emission on the basis of the volume removedby impacting sand grains as they plough into the soilsurface. Also, in this model, saltation bombardment isconsidered to be the main mechanism for dust emission.In our simulation, dust emission model developed byShao (2001) was used. Three mechanism responsible fordust emission can be identified: (1) direct liftoff of dustparticles by aerodynamic forces; (2) release of dust par-ticles as saltating particles strike the surface causingabrasion; and (3) disintegration of dust coats on sandgrains and clay aggregates during saltation. The dustemission rate related to these three mechanisms can beformally expressed asF Fa Fb Fc (3)where Fa is aerodynamic lift, which is insignificant ingeneral, because particles lifted by fa (aerodynamicforces) are weak in normal wind erosion conditions. Fb issaltation bombardment, which refers to striking particlesovercome fi (inter-particle binding forces) and result instrong emission. Fc is aggregates disintegration, whichmeans fine particles exist as aggregates. In weak events,</p></li><li><p>144 Z. Song / Environmental Modelling &amp; Software 19 (2004) 141151</p><p>they behave as grains. While in strong events, they disin-tegrate.</p><p>2.5. Dry and wet deposition</p><p>Dust particles are delivered back to the surface byboth dry and wet deposition. Dry deposition is the dustflux from the atmosphere to the surface through molecu-lar and turbulent diffusion and gravitational settling,while wet deposition is the dust transfer to the surfacethrough precipitation. Dry deposition dust flux, Fd , canbe expressed asFd rwd[c(z)c(0)] (4)where c(0) and c(z) are, respectively, dust concentrationat the surface and at the reference level z and wd is thedry-deposition velocity. Raupach (1991) have proposeda single-layer dry-deposition model which is lessdemanding on data and parameterizations. In this model,the dry-deposition velocity is treated as a bulk single-layer conductance made up of three components actingin parallel</p><p>wd wt gbb gbm (5)where gbb is molecular conductance and gbm is impactionconductance. Wet deposition is not considered in thiswork.</p><p>2.6. Input GIS (Geographic Information System) dataand model output</p><p>The stati...</p></li></ul>