地球科学进展

地球科学进展 ›› 2006, Vol. 21 ›› Issue (4): 424 -429. doi: 10.11867/j.issn.1001-8166.2006.04.0424

所属专题： “沙尘天气追因、影响及治理”虚拟专刊；

学术论文 上一篇    下一篇

有关粉尘释放模型的应力分配模式存在问题的讨论
梅凡民 1,2,王涛 1,张小曳 3,陈敏 2   
  1. 1.中国科学院寒区旱区环境与工程研究所沙漠与沙漠化重点实验室，甘肃 兰州 730000；2. 西安工程大学环境科学与工程系，陕西 西安 710048；3.中国气象局大气成分观测与服务中心，北京 100081
  • 收稿日期:2005-08-29 修回日期:2005-11-10 出版日期:2006-04-15
  • 通讯作者: 梅凡民 E-mail:fanmin68@yahoo.com.cn
  • 基金资助:

    国家重点基础研究发展计划项目“沙尘暴形成机制及预报、预警方法”（编号：G2000048703）和“沙漠化综合防治战略与优化模式”（编号：G2000048705）；中国博士后科学基金项目（编号：2005037163）资助.

Problems of the Shear Stress Partition Sub-models of a Dust  Production Model

Mei Fanmin 1,2,Wang Tao 1,Zhang Xiaoye 3,Chen Min 2   

  1. 1.Key laboratory of Desert and Desertification, Cold and Arid Regions Environmental and Engineering Research Institute,CAS,Lanzhou 730000,China; 2.Department of Environmental Science and Technology, Xi’an University of Engineering and Technology, Xi’an 710048, China; 3. Center for Atmosphere Watch and Services,CMA, Beijing 100081,China
  • Received:2005-08-29 Revised:2005-11-10 Online:2006-04-15 Published:2006-04-15
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准确模拟粉尘释放通量对评价粉尘气溶胶的气候效应、沙漠化和沙尘暴防治具有重要意义。敏感性试验、室内和野外风洞实验表明被广泛使用的DPM（Dust Production Model）粉尘释放模型的2个应力分配模式——Marticorena模式和 Alfaro模式存在明显问题：由于目前空气动力学粗糙度模式还不能考虑粗糙元间隙率和粗糙元分布状况空气动力学粗糙度的影响，以空气动力学粗糙度为主要参数的Marticorena模式和 Alfaro模式还不能考虑粗糙元间隙率和粗糙元分布状况对应力分配的影响，而相关实验表明这些因素对应力分配存在显著影响；Marticorena模式和 Alfaro模式预测的应力分配系数和起动摩阻风速存在显著差异，目前实验结果还不能判断二者正确与否；Marticorena模式和 Alfaro模式预测的能够有效控制风蚀的应空气动力学粗糙度与实际观测相矛盾。针对上述问题提出了通过风洞实验改进当前应力分配模式的主要途径。

关键词: 风蚀, 粉尘释放, 模型, 应力, 应力分配

Simulation of dust emission flux is very fundamental for evaluating climatic effects of dust aerosols and controlling desertification process and dust storm. The two shear stress partition models were proposed by Marticorena and Alfaro respectively for evaluating effect of roughness elements on dust production. The existing problems of them are discussed on basis of sensitive tests, previous wind tunnel and field experiments. First, the influence of porosity and spatial heterogeneity of roughness elements on shear stress partition was not taken into account because all equations about roughness length can not involve such factors as porosity and spatial heterogeneity of roughness elements. However, it is proved that these factors cannot be neglected by many experiments. Second, the result from sensitive test of Marticorena's Model is in disagreement with that of Alfaro's Model, implying that the models need to be investigated further by wind tunnel experiment. Third, regarding the roughness length to efficiently suppress wind erosion, the values predicted respectively by the models are questioned by some wind erosion experiment data, therefore the relationship between shear stress partition and roughness length need to be reassessed. In terms of these problems of the models, two approaches are proposed: improving roughness length formula and tuning empirical constants of the models by wind tunnel experiment.

Key words: Shear stress, Shear stress partition, Wind erosion, Dust production.

中图分类号: 

[1] Tegen I, Fung I. Modeling mineral dust in the atmosphere: sources, transport, and optical thickness[J]. Journal of Geophysical Research,1994, 99:22 897-22 914.

[2] Tegen I, Lacis A A. Modeling of particle size distribution and its influence on the radiative properties of mineral dust aerosol[J]. Journal of Geophysical Research,1996,101(D14):19 237-19 244.

[3] Claquin T, Schulz M, Balkanski Y. Modeling the mineralogy of atmospheric dust sources[J]. Journal of Geophysical Research,1999,104:22 243-22 256.

[4] Guelle W, Balkanski J, Schulz M, et al. Modelling the atmospheric distribution of mineral aerosol, comparison with ground measurements and satellite observations for yearly and synoptic timescales over the North Atlantic[J]. Journal of Geophysical Research, 2000, 105:1 997-2 012.

[5] Ginoux P, Chin M, Tegen I, et al. Sources and distribution of dust aerosols simulated with GOCART model[J]. Journal of Geophysical Research, 2001, 106(D17): 20 225-20 273.

[6] Marticorena B, Bergametti G. Modeling the atmospheric dust cycle: 1. Design of a soil-derived dust emission scheme [J]. Journal of Geophysical Research, 1995,100(D8):16 415-16 430.

[7] Marticorena B, Bergametti G, Amount B, et al. Modeling the atmospheric dust cycle: 2. Simulation of Saharan dust source[J]. Journal of Geophysical Research, 1997, 102(D4): 4 387-4 404.

[8] Alfaro S C, Gomes L. Modeling mineral aerosol production by wind erosion: Emission intensities and aerosol size distribution in source areas[J]. Journal of Geophysical Research,2001,106 (D16):18 075-18 084.

[9] Mei Fanmin, Zhang Xiaoye, Lu Huayu, et al. Review on progress in modeling dust production by wind erosion[J]. Journal of Desert Research,2004,24(6):791-797. [梅凡民,张小曳,鹿化煜,等. 若干粉尘释放模型述评[J].中国沙漠,2004, 24(6):791-797.]

[10] Callot Y, Marticorena B, Bergametti G. Geomorphologic approach for modeling the surface features of arid environments in a model of dust emissions: Application to the Saharan desert [J]. Geodinamica Atca,2000,13:245-270.

[11] Gong S L, Zhang X Y, Zhao T L, et al. Characterization of soil dust and its transport and distribution during 2001 ACE-Asian: 2. Model simulation and validation [J]. Journal of Geophysical Research, 2003, 108(D9), doi:10. 1029/2002JD002633.

[12] Zhang X Y, Gong S L, Zhao T L, et al. Sources of Asian dust and role of climate change versus desertification in Asian dust emission [J]. Geophysical Research Letters,2003,30(24), doi:10.1029/2003GL018206.

[13] Alfaro S C, Gomes L. Improving the large-modeling of the saltation fluxes of soils particles in the presence of nonerodible elements [J]. Journal of Geophysical Research,1995,100(D8):16 357-16 366.

[14] Wolfe S A, Nickling W G. Shear stress partitioning in sparsely vegetated desert canopies [J]. Earth Surface Processes and Landforms, 1996, 21: 607-620.

[15] Wyatt V E, Nickling W G. Drag and shear stress partitioning in sparse desert creosote communities[J]. Canadan Journal of Earth Science, 1997, 34:1 486-1 498.

[16] Lancaster N, Baas A. Influence of vegetation cover on sand transport by wind: Field studies at Owens Lake, California [J]. Earth Surface Processes and Landforms,1998,23:69-82.

[17] Lancaster N. Relations between aerodynamic and surface roughness in a hyper-arid cold desert: Mcmurdo day valleys, Antarctica [J]. Earth Surface Processes and Landforms,2004,29:853-867.

[18] Gillies J, Lancaster N, Nickling W, et al. Field determination of drag forces and shear stress partitioning effects for a desert shrub (Sarcobatus vermiculatus, greasewood) [J]. Journal of Geophysical Research,2000,105 (D20):24 871-24 880.

[19] Gillies J, Nickling W, King J. Drag coefficient and plant form-response to wind speed in three plant species: Burning bush (Euonymus alatus), Colorado blue spruce (Picea pungens glauca) and fountain grass (Pennisetum setaceum) [J]. Journal of Geophysical Research,2003,107(D 24):10-1-15-1.

[20] Crawley D, Nickling W. Drag partition for regularly arrayed rough surfaces [J]. Boundary-Layer Meteorol, 2002,107:445-468.

[21] MacKinnon J, Clow D, Tigges K, et al. Comparison of aerodynamically and model-derived roughness lengths (zo) over diverse surfaces, central Mojave Desert, California, USA [J]. Geomorphology,2004, 63:103-113.

[22] Wooding R A, Bradley E F, Marshall J K. Drag due to regular arrays of roughness elements of varying geometry [J]. Boundary Layer Meteorology,1973, 5: 285-308.

[23] Arya S P S. A drag partition theory for determining the large-scale roughness parameter and wind stress on Arctic pack ice[J]. Journal of Geophysical Research,1975, 80:3 347-3 454.

[24] Raupach M R. Drag and drag partition on rough surfaces [J].Boundary-Layer Meteorol,1992, 60: 375-395.

[25] Raupach M, Gillette D, Leys J. The effect of roughness elements on wind erosion threshold [J]. Journal of Geophysical Research,1993,98:3 023-3 029.

[26] Eillot W P. The growth of atmospheric internal boundary layer[J]. EOS Transactions AGU,1958, 39:1 048-1 054.

[27] Lettau H H. Note on aerodynamic roughness-parameter estimation on the basis of roughness element description[J]. Journal of Applied Meteorology, 1969,8:828-832.

[28] Minvielle F, Marticorena B, Gillette D A, et al. Relationship between the aerodynamic roughness length and the roughness density in cases of low [J]. Environmental Fluid Mechanics,2003, 3: 249-267.

[29] Gillette D A, Stockton P H. The Effects of nonerodible particles on wind erosion of erodible surfaces [J]. Journal of Geophysical Research,1989, 94 (D10):12 885-12 893.

[30] Marshall J K. Drag measurements in roughness arrays of varying density and distribution [J]. Agricultural Meteorology,1971, 8:269-292.

[31] Stockon P H, Gillette D A. Field measurements of sheltering effect of vegetaion on erodible land surface[J]. Land Degrad Rhabil, 1990,2:77-85.

[32] Marticorena B, Bergametti G, Gillette D, et al. Factors controlling threshold friction velocity in semiarid and arid areas of the United States [J]. Journal of Geophysical Research,1997, 102(D19):23 277-23 287.

[33] Alfaro S, Rajot L, Nickling W. Estimation of PM20 emissions by wind erosion: Main sources of uncertainties [J]. Geomorphology,2004,59:63-74.

[34] Buckley R. The effect of sparse vegetation on the transport of dune sand by wind[J]. Nature,1987, 325: 426-428.

[35] Ling Quanyu,Qu Jianjun,Jin Jiong. Influence of sparse natural vegetation on sand-transporting quantity[J]. Journal of Desert Research, 2003,23(1):12-17.[凌裕泉,屈建军,金炯. 稀疏天然植被对输沙量的影响[J].中国沙漠,2003,23(1):12-17.]

[36] Dong Zhibao, Chen Weinan, Dong Guangrong, et al. Influence of vegetation cover on the wind erosion of sandy soil[J]. Acta Scientiae Circumstantiae,1996, 19(1):437-443. [董治宝,陈渭南,董光荣,等.植被覆盖对风沙土风蚀的影响[J].环境科学学报,1996, 19(1):437-443.]

[37] Dong Z B, Liu X P, Wang X M. Aerodynamic roughness of gravel surfaces[J]. Geomorphology,2002, 43:17-31.

[38] Qu Jianjun, Huang Ning, Tuo Wanquan, et al. Structural characteristics of Gobi sand-drift and its significance [J]. Advances in Earth Science,2005,20(1):19-23. [屈建军, 黄宁,拓万全,等. 戈壁风沙流结构特性及其意义[J].地球科学进展,2005,20(1):19-23.]

[39] Huang Fuxiang, Niu Haishan, Wang Mingxing, et al. The relationship between vegetation cover and sand transport flux at Mu Us Sandland [J]. Acta Geographica Sinica,2001,56(6):700-711. [黄富祥,牛海山,王明星,等. 毛乌素沙地植被覆盖率与风蚀输沙率定量关系 [J]. 地理学报,2001,56(6):700-711.]

[40] Wasson R J, Nanninga P M. Estimating wind transport of sand on vegeted surfaces [J]. Earth Surface Processes and Landforms,1986, 11:505-514.

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