An Empirically Derived Emission Algorithm for Wind Blown Dust


Roland R. Draxler, Paul Ginoux, Ariel F. Stein


Journal of Geophysical Research, 2010, 115, D16212, doi:10.1029/2009JD013167


Abstract - A wind blown dust emission algorithm was developed by matching the frequency of high AOD events derived from the MODIS Deep Blue algorithm with the frequency of friction velocities derived from NCEPís NAM model. The threshold friction velocity is defined as the velocity that has the same frequency of as the 0.75 AOD. The AODs are converted to an emission flux which is used to compute the linear regression slope of the flux to the friction velocity. The slope represents the potential of a particular land surface to produce airborne dust and in combination with the friction velocity is used as a predictor for wind blown dust emissions. Calculations for a test period of June and July 2007 showed the model prediction to capture the major measured plume events in timing and magnitude, although peak events tended to be over-predicted and many of the near-background level ambient concentrations were under-predicted. Most of the airborne dust loadings are attributed to locations with relatively low threshold friction velocities (< 45 cm s-1), although these locations only comprised of 9% of the total number of source locations. There was some evidence that the duration of wind blown dust plume events was comparable to the 3-day sampling frequency of the IMPROVE monitoring network. Higher temporal frequency AIRNow observations at Phoenix showed a surprisingly good fit with the magnitude of the model predicted peak concentrations.



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