Advertisement

Development, Implementation, and Evaluation of a Physics-Based Windblown Dust Emission Model

  • Hosein ForoutanEmail author
  • Jeff Young
  • Peng Liu
  • Limei Ran
  • Jonathan Pleim
  • Rohit Mathur
Conference paper
Part of the Springer Proceedings in Complexity book series (SPCOM)

Abstract

A physics-based windblown dust emission parameterization scheme is developed and implemented in the CMAQ modeling system. A distinct feature of the present model includes the incorporation of a newly developed, dynamic relation for the surface roughness length, which is important in correctly predicting both the friction velocity and the roughness correction factor used in the dust emission model. Careful attention is paid in integrating the new dust module within the CMAQ to ensure the required input parameters are correctly configured. The model is evaluated for two test cases including the continental United States and the Northern hemisphere, and is shown to be able to capture the occurrence of the dust outbreak and the level of the soil concentration.

Keywords

Windblown dust Emission parameterization Surface roughness CMAQ 

References

  1. Appel KW, Napelenok S, Hogrefe C, Foley KM, Pouliot G, Roselle SJ, and Pleim JE (2015) Evaluation of the community multiscale air quality model version 5.1. In: 14th annual CMAS conference, Chapel Hill, NC, Oct 5–7Google Scholar
  2. Fecan F, Marticorena B, Bergametti G (1999) Parameterization of the increase of the aeolian erosion threshold wind friction velocity due to soil moisture for arid and semi-arid areas. Ann Geophys 17:149–157. doi: 10.1007/s005850050744 CrossRefGoogle Scholar
  3. Hébrard E, Listowski C, Coll P, Marticorena B, Bergametti G, Määttänen A, Montmessin F, Forget F (2012) An aerodynamic roughness length map derived from extended Martian rock abundance data. J Geophys Res 117:E04008. doi: 10.1029/2011JE003942 CrossRefGoogle Scholar
  4. Huneeus N et al (2011) Global dust model intercomparison in AeroCom phase I. Atmos Chem Phys 11:7781–7816. doi: 10.5194/acp-11-7781-2011 CrossRefGoogle Scholar
  5. King J, Nickling WG, Gillies JA (2005) Representation of vegetation and other nonerodible elements in Aeolian shear stress partitioning models for predicting transport threshold. J Geophys Res 110:F04015. doi: 10.1029/2004JF000281
  6. Lu H, Shao Y (1999) A new model for dust emission by saltation bombardment. J Geophys Res 104:16827–16842. doi: 10.1029/1999JD900169 CrossRefGoogle Scholar
  7. Pleim JE, Xiu A (1995) Development and testing of a surface flux and planetary boundary layer model for application in mesoscale models. J Appl Meteorol 34:16–32. doi: 10.1175/1520-0450-34.1.16 CrossRefGoogle Scholar
  8. Shao Y, Lu H (2000) A simple expression for wind erosion threshold friction velocity. J Geophys Res 105:22437–22443. doi: 10.1029/2000JD900304 CrossRefGoogle Scholar
  9. Thomas M, Gautier C, Ricchiazzi P (2009) Investigations of the March 2006 African dust storm using ground-based column-integrated high spectral resolution infrared (8–13 μm) and visible aerosol optical thickness measurements: 1. Measurement procedures and results. J Geophys Res 114:D11202. doi: 10.1029/2008JD010928 CrossRefGoogle Scholar
  10. Todd MC et al (2008) Quantifying uncertainty in estimates of mineral dust flux: an intercomparison of model performance over the Bodélé depression, Northern Chad. J Geophys Res 113:D24107. doi: 10.1029/2008JD010476 CrossRefGoogle Scholar
  11. Uno I et al (2006) Dust model intercomparison (DMIP) study over Asia: overview. J Geophys Res 111:D12213. doi: 10.1029/2005JD006575 CrossRefGoogle Scholar
  12. White BR (1979) Soil transport by winds on Mars. J Geophys Res 84:4643–4651. doi: 10.1029/JB084iB09p04643 CrossRefGoogle Scholar
  13. Xi X, Sokolik IN (2015) Seasonal dynamics of threshold friction velocity and dust emission in Central Asia. J Geophys Res Atmos 120:1536–1564. doi: 10.1002/2014JD022471 CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Hosein Foroutan
    • 1
    Email author
  • Jeff Young
    • 1
  • Peng Liu
    • 1
  • Limei Ran
    • 1
  • Jonathan Pleim
    • 1
  • Rohit Mathur
    • 1
  1. 1.Computational Exposure Division, National Exposure Research LaboratoryU.S. Environmental Protection AgencyResearch Triangle ParkUSA

Personalised recommendations