A model for the emission of PM10 dust was developed in 2001 (Draxler et al., 2001) using the concept of a threshold friction velocity which is dependent on surface roughness. Surface roughness in turn was correlated with geomorphology or soil properties for Kuwait, Iraq, part of Syria, Saudi Arabia, the United Arab Emirates and Oman. A dust emission rate was computed from each cell when the local wind velocity exceeded the threshold velocity for the soil characteristics of that emission cell. The dominant mechanism for the PM10 dust input model is “sand-blasting”. The emitted material was dispersed and transported using a modified Lagrangian particle-puff model (Draxler and Hess, 1998) using gridded meteorological data fields. Computations were made for the period of August 1990 through August 1991. The model calculated air concentrations from mid-May through mid-July, the period of the most frequent and intense dust storms. These calculations were compared with the measured data.
The model predicted about the right number of dust events over Kuwait (events occur 18% of the time). The model results agreed quantitatively with measurements at four locations in Saudi Arabia and one in Kuwait for one major dust event (>1000 µg/m3). However, for smaller scale dust events (200 – 1000 µg/m3), especially at the coastal sampling locations, the model substantially over-predicted the air concentrations. Part of the over-prediction was attributed to the entrainment of dust-free air by the sea breeze, a flow feature not represented by the large-scale gridded meteorological data fields used in the model computation. Another part of the over-prediction was the model’s strong sensitivity to threshold friction velocity and the surface soil texture coefficient (the soil emission factor), and the difficulty in accurately representing these parameters in the model. A comparison of the model predicted PM10 spatial pattern with the TOMS satellite aerosol index (AI) yielded a spatial pattern covering a major portion of Saudi Arabia that was quite similar to the observed AI pattern.
The initial research model configuration was only suited for use over Kuwait and Saudi Arabia. The model was restructured to use the default HYSPLIT land-use characteristics file defined on a one degree global grid. A preprocessing program was developed that accessed this file over any selected modeling domain to create a HYSPLIT input control file such that each emission point entry corresponded with a “desert” land-use grid cell. The desert cell was assumed to correspond with the “active sand sheet” category defined for the Kuwait simulations. The calculations then proceeded as before, such that particle emissions only occurred from locations in which the local friction velocity exceeded the threshold friction velocity. The Kuwait specific PM10 flux equation was replaced by a more generic relationship given by Westphal et al. (1987).
The two 10 day animations, for dust events in April 2001 and March 2002, represent the daily model particle positions at 0600 UTC superimposed over the TOMS aerosol index for that day. Particle emissions occurred automatically during the period based upon land-use and friction velocity. Satellite and model results may not always correspond due to errors in the model simulation as well as the fact that the TOMS AI may be obscured by clouds and tends to be more representative of dust at higher levels in the atmosphere rather than near the ground. However, regardless of the caveats, the match between model results and measurements is at times quite striking, especially for the event of April 2001 as the dust cloud moved across the Pacific.
Previous Experimental Operation
Daily forecasts of long range dust transport from northern Africa to the United States were produced using a combination between a lagrangian and a eulerian model. The HYSPLIT model simulated the emissions, transport, dispersion, and deposition of dust particles for an area covering Northern Africa and Southern Europe. This model was driven by the GFS meteorological forecast with a horizontal resolution of 0.5×0.5 degrees. The global model was initialized every hour by dividing the lagrangian particle masses provided by HYSPLIT by the volume of the grid in which they reside. The global simulation is driven by the GFS meteorological forecast with a horizontal resolution of 1×1 degrees. This three-dimensional transport-dispersion global model included wet and dry deposition of the dust particles. These settings took advantage of the higher resolution used by HYSPLIT to calculate the regional emissions of dust and the reduction in computation time required to run the global simulation. The global dust forecasting system produced 72-hour forecasts of surface and column integrated PM10 concentrations.
Initial Model Configuration
The emission algorithm developed in the previous discussion was incorporated into HYSPLIT (Draxler and Hess, 1997, 1998) following a similar approach to the model’s previous applications to wind blown dust simulations (Draxler et al., 2001; Escudero et al., 2006). For each month of the year, an input file is created with the center position (latitude, longitude) of all the grid cells previously identified as potential emission points (Ginoux et al., 2001, 2009). At each time step (6 min) of the computational period, particles are emitted from grid cells where the friction velocity exceeds the threshold friction velocity at that grid cell. Emissions can only occur from grid cells with no precipitation. Soil moisture is not currently available in the data base. Dust particles are defined to be spherical with a diameter of 4 µm and density of 2.5 g cm-3. Emitted particles will gravitationally settle and can be removed by rainfall. To avoid unnecessary computational overhead, particles older than 48 hours are dropped from the calculation and a maximum of 500,000 particles can be carried at any one time. If all grid cells were emitting for the full 48 hours, one million particles would be required. The HYSPLIT model is run in its 3D particle mode, where emitted particles, in addition to transport by the mean wind, are turbulently dispersed in each orthogonal direction. A 0.05 degree (about 5 km) by 100 m depth concentration grid is superimposed over the computational domain where particle mass is accumulated and converted to air concentration by dividing the total accumulated mass by the grid cell volume.
Current Model Configuration
The initial configuration was modified to use the Bowen ratio as a surrogate for soil moisture so that in addition to the initial model configuration requirements noted above, a large Bowen ratio, indicative of dry conditions was also required to initiate dust emissions. Additional information is provided in the evaluation report.
Draxler, R. R., P. Ginoux, and A. F. Stein (2010), An empirically derived emission algorithm for wind-blown dust, J. Geophys. Res., 115, D16212, doi:10.1029/2009JD013167.
Draxler, R.R, D.A. Gillette, J.S. Kirkpatrick, and J. Heller (2001), Estimating PM10 air concentrations from dust storms in Iraq, Kuwait, and Saudi Arabia, Atm. Environ,35: 4315-4330.
Draxler, R.R. and G.D. Hess (1998), An overview of the HYSPLIT_4 modelling system for trajectories, dispersion, and deposition. Aust. Meteor. Mag. 47, 295-308.
Draxler, R.R. and G.D. Hess (1997), Description of the HYSPLIT_4 modeling system. NOAA Technical Memo ERL ARL-224, December, 24 p.
Escudero, M., A. Stein, R. R. Draxler, X. Querol, A. Alastuey, S. Castillo, and A. Avila, (2006), Determination of the contribution of northern Africa dust source areas to PM10 concentrations over the central Iberian Peninsula using the Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT) model, J. Geophys. Res., 111, D06210, doi:10.1029/2005JD006395.
Ginoux, P., M. Chin, I. Tegen, J.M. Prospero, B. Holben, O. Dubovik, and S. J. Lin, (2001), Sources and distributions of dust aerosols simulated with the GOCART model, J. Geophys. Res., 106, D17, 20255-20274.
Ginoux, P., D. Garbuzov, and N.C. Hsu (2009), Anthropogenic and natural attribution of dust sources using MODIS Deep Blue Level 2 data, J. Geophys. Res., submitted.
Westphal, D.L., Toon, O.B., Carlson, T.N., 1987. A two-dimensional numerical investigation of the dynamics and microphysics of Saharan dust storms. J. Geophys. Res., 92, 3027-3029.
- Volcanic Ash
- Smoke Forecasting
- Smoke: Prescribed Burns
- Inverse Modeling
- Inline WRF-HYSPLIT Coupling
- DATEM Evaluation