Mineral dust aerosols: Difference between revisions

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See [http://acmg.seas.harvard.edu/publications/fairlie2007.pdf ''Fairlie et al'', 2007] and [http://acmg.seas.harvard.edu/publications/fairlie2009.pdf ''Fairlie et al'', 2010].
See [http://acmg.seas.harvard.edu/publications/fairlie2007.pdf ''Fairlie et al'', 2007] and [http://acmg.seas.harvard.edu/publications/fairlie2009.pdf ''Fairlie et al'', 2010].
== Source code and data ==
The source code for the GEOS-Chem dust emissions & chemistry modules are contained in files <tt>dust_mod.f</tt> and <tt>dust_dead_mod.f</tt>.
For more information about the data, please see the README files in the following GEOS-Chem data directories:
#[ftp://ftp.as.harvard.edu/pub/geos-chem/data/GEOS_2x2.5/dust_200605/README GEOS_2x2.5/dust_200605]
#
#
#
#


== References ==
== References ==

Revision as of 14:29, 24 February 2010

Overview

From Fairlie et al, 2007:

We implemented two dust mobilization schemes in GEOS-Chem: (1) the scheme of Ginoux et al. (2004, hereafter G04), developed for the GOCART CTM and (2) the dust entrainment and deposition (DEAD) scheme of Zender et al. (2003a, b hereafter Z03a,b). Both schemes treat the vertical dust flux as proportional to the horizontal saltation flux. The DEAD scheme (Z03) follows MB95 in computing a total horizontal saltation flux, Qs, based on the theory of White (1979):

               RHOair                 (      U*,t  )   (      U*,t   )^2
     Qs = Cz * --------- * Ustar^3 *  ( 1 - ------ ) * ( 1 + ------- )      (1)
                  g                   (       U*   )   (       U*    )

where U* is the friction velocity, U*,t(D) is the threshold friction velocity, RHOair is the air density, g is the acceleration of gravity, and Cz is a global tuning parameter. Qs is computed at D = 75μm, where U*,t is a minimum, and the total vertical flux is given by:

     F = Am * Sz * ALPHA * Qs     (2)

where the sandblasting mass efficiency, ALPHA, depends on the fraction Mclay of clay in the soil, Am is the fraction where the sandblasting mass efficiency, ALPHA, depends on the fraction Mclay of clay in the soil, Am is the fractional area of land suitable for mobilization, and Sz is the ‘‘erodibility,’’ an efficiency factor that favors emissions from specified geographic features. We followed Z03b in using ‘‘geomorphic erodibility,’’ which depends on upstream runoff area, and set Mclay = 0.2 globally. We computed U from the 10-m wind speed assuming neutral stability below and used a roughness length Z0 = 100 mm, recommended by Z03a for dust mobilization candidate cells. F is distributed by particle size as a globally uniform tri-modal lognormal probability density function, which we project on to the selected size bins specified above.al area of land suitable for mobilization, and Sz is the ‘‘erodibility,’’ an efficiency factor that favors emissions from specified geographic features. We followed Z03b in using ‘‘geomorphic erodibility,’’ which depends on upstream runoff area, and set Mclay = 0.2 globally. We computed U from the 10-m wind speed assuming neutral stability below and used a roughness length Z0 =100 mm, recommended by Z03a for dust mobilization candidate cells. F is distributed by particle size as a globally uniform tri-modal lognormal probability density function, which we project on to the selected size bins specified above.

The GOCART scheme (G04) follows Gillette and Passi (1988) in computing a size segregated vertical dust flux, Fp, for each size class, p:

     Fp = Cg * S * sp * U10^2 * ( U10 - U*,t )     (3)

where the ‘‘source function,’’ S, serves the same role as the product Am * Sz in DEAD (Eq. (2)), sp is the mass fraction applied to each size class, U10 is the 10-m wind speed, and Cg is a global constant. S confines dust emissions to topographic depressions in desert and semi-desert areas of the world (Ginoux et al., 2001, hereafter G01) and is time invariant....

Although the DEAD and GOCART schemes differ in detail, they differ most fundamentally in representing the role of vegetation. GOCART restricts emissions to persistent arid regions, whereas DEAD permits regions that become seasonally devegetated to mobilize....

Validation

See Fairlie et al, 2007 and Fairlie et al, 2010.

Source code and data

The source code for the GEOS-Chem dust emissions & chemistry modules are contained in files dust_mod.f and dust_dead_mod.f.

For more information about the data, please see the README files in the following GEOS-Chem data directories:

  1. GEOS_2x2.5/dust_200605

References

  1. Chin, M., P. Ginoux, S. Kinne, B. Holben, B. Duncan, R. Martin, J. Logan, A. Higurashi, and T. Nakajima, Tropospheric aerosol optical thickness from the GOCART model and comparisons with satellite and sunphotometers measurements, J. Atmos Sci., 2001.
  2. Chin, M., et al., Aerosol distribution in the Northern Hemisphere during ACE-Asia: results from global model, satellite observations, and Sun photometer measurements, J. Geophys. Res., 109, D23S90, 2004.
  3. Fairlie, T.D., D.J. Jacob, J.E. Dibb, B. Alexander, M.A. Avery, A. van Donkelaar, and L. Zhang, Impact of mineral dust on nitrate, sulfate, and ozone in transpacific Asian pollution plumes, Atmos. Chem. Phys., submitted, 2010. PDF
  4. Fairlie, T. D., D.J. Jacob, and R.J. Park, The impact of transpacific transport of mineral dust in the United States, Atmos. Environ., 41, 1251-1266, 2007. PDF
  5. Gillette, D.A., Passi, R., Modeling dust emission caused by wind erosion, J. Geophys. Res., 93, 14,233–14,242, 1988.
  6. Ginoux, P., et al., Sources and distributions of dust aerosols simulated with the GOCART model, J. Geophys. Res, 106 (D17), 20255–20274, 2001.
  7. Ginoux, P., et al., Long-term simulation of global dust distribution with the GOCART model: correlation with North Atlantic oscillation, Environmental Modeling and Software, 19, 113–128, 2004.
  8. White, B.R., Soil transport by winds on Mars, J. Geophys. Res., 84, 4643–4651, 1979.
  9. Zender, C.S., Bian, H., Newman, D., The mineral dust entrainment and deposition (DEAD) model: description and 1990s dust climatology, J. Geophys. Res, 108 (D14), 4416, 2003a.
  10. Zender, C.S., Newman, D., Torres, O., Spatial heterogeneity in aeolian erodibility: uniform, topographic, geomorphic and hydrologic erodibility, J. Geophys. Res., 108 (D17), 4543, 2003b.
  11. Zhang, L., Gong, S., Padro, J., Barrie, L., A size-segregated particle dry deposition scheme for an atmospheric aerosol module, Atm. Environ., 35, 549–560, 2001.

--Bob Y. 10:34, 22 February 2010 (EST)

Known issues

Low bias at 4x5 resolution

The following comments are in the documentation header to source code file dust_dead_mod.f, which is the implementation of Zender's DEAD scheme in GEOS-Chem:

T. Duncan Fairlie wrote:

NOTE: The current [dust] code was validated at 2 x 2.5 resolution. We have found that running at 4x5 we get much lower (~50%) dust emissions than at 2x2.5. Recommend we either find a way to scale the U* computed in the dust module, or run a 1x1 and store the the dust emissions, with which to drive lower resolution runs.
-- Duncan Fairlie, 1/25/07

Daniel Jacob wrote:

NOTE: [We'll] implement the [dust] code in the standard [GEOS-Chem] model and put a warning about expected low bias when the simulation is run at 4x5. Whoever is interested in running dust at 4x5 in the future can deal with making the fix.
-- Daniel Jacob, 1/25/07

--Bob Y. 10:34, 22 February 2010 (EST)