1. PHAiRS 2005-2006: Dust Modeling PHAiRS 2005-2006: Dust Modeling Dazhong Yin Slobodan Nickovic William A. Sprigg March 14, 2006

2. Major activities Assimilation of NASA earth science observations into DREAM dust transport model Assessment of impacts of the assimilation of NASA data on dust modeling results Improvement of dust size resolution in DREAM Development of dust and atmospheric radiation interaction module in DREAM Development of quasi-operational DREAM Regionalize WRF-NMM for the southwestern US

3. Assimilation of NASA data-MODIS land cover Original land cover data used in DREAM is the Olson World Ecosystem (OWE) land cover dataset OWE data was first compiled based on collected maps, references, and observations of the 1970’s, with following update using observations of the 1980’s. The spatial resolutions is 10-minute (about 16 km). MODIS data represents 2001 land cover with a 30- second (about 1 km) spatial resolution.

4. Assimilation of NASA data-MODIS land cover MODIS data

5. Assimilation of NASA data-MODIS land cover Landcover on the modeling grid using OWE (left) and MODIS (right) data

6. Assimilation of NASA data-SRTM terrain data Original terrain elevation data used in DREAM is USGS terrain with a 30-second (about 1 km) spatial resolution. Shuttle Radar Topography Missions (SRTM) terrain data has spatial resolutions as high as 90 m. Because of DREAM model dynamics restriction, model grid spacing normally should not be less than 10 km. SRTM data was reassembled for DREAM with a 30-second spatial resolution.

7. Assimilation of NASA data-SRTM terrain data USGS terrain data (left) and SRTM data (right)

8. Assimilation of NASA data-Roughness length data Preview of roughness length data

9. Assimilation of NASA data-Roughness length data Original roughness length in DREAM –Over sea: Maxi(0.0018U*U*, 1.59E-5) –Over land: terrain height*0.0001+0.1+Maxi(0.0018U*U*, 1.59E-5)

10. Assimilation of NASA data-FPAR data Using category “barren, desert, or sparsely vegetated” based on FPAR data to pin point dust source area

11. Assimilation of NASA data-AMSR-E soil moisture data It requires at least two days of the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) data to completely cover our model domain An average soil moisture data for the modeling area using Dec 7-15, 2003 AMSR-E data was compiled This data was used to initialize soil moisture in DREAM

12. Assimilation of NASA data-AMSR-E soil moisture data Preview of the average soil moisture data

13. Assimilation of NASA data-AMSR-E soil moisture data

14. Assessment of impacts of NASA data

19. Improvement of dust size resolution in DREAM Four size categories

20. Improvement of dust size resolution in DREAM Eight size categories

21. Improvement of dust size resolution in DREAM Particle size distribution at sources as D’Almeida (1987) or Gomes et al. (1990)

22. Dust and atmospheric radiation interaction module in DREAM Dust particles contribute to atmospheric optical thickness (  ), single-scattering albedo (w), and asymmetry factor (g)

23. Dust and atmospheric radiation interaction module in DREAM Obvious dust radiative effects on the surface

24. Dust and atmospheric radiation interaction module in DREAM Negative feedback on atmospheric dust loading

25. Dust and atmospheric radiation interaction module in DREAM Better meteorological fields

26. Development of quasi-operational DREAM system Automatic download of the NCEP’s Global Forecast System (GFS), formerly Aviation (AVN) run of Medium Range Forecast (MRF) data GFS files with 12 hour time interval and 2.5 degree grid spacing Code to ingest GFS data to generate DREAM initial and boundary conditions Forecast wind-blown dust for the Southwest up to 72 hour in the future

27. Development of quasi-operational DREAM system

28. Development of quasi-operational DREAM system-some urgent needs Measurement data for model evaluation –In-situ meteorological data –In-situ PM2.5 and PM10 –In-site speciated PM observations –Satellite images showing dust plumes –AOT from remote sensing –3D dust observed dust concentrations, Lidar observation?

29. Development of quasi-operational DREAM system-some urgent needs

30. Updated NASA land cover data to refresh land use in the model

31. Development of quasi-operational DREAM system-some urgent needs Dust storm causes two pileups on I-8, Feb 15, 2006

32. Development of quasi-operational DREAM system-some urgent needs Dust source differences due to using different land cover data

33. Regionalization of the NCEP WRF-NMM for the southwestern US

34. Central lat 34.02N Central lon -108.90 Grid no. 151*219 Grid spacing 15 km

35. Regionalization of the NCEP WRF-NMM for the southwestern US

39. Acknowledgement Marvin Landis –visualization Jim Koermer of Plymouth State University- met observational data and met analysis products weather.unisys.com-surface weather maps www.rnrcc.tx.us- satellite imageswww.rnrcc.tx.us- US EPA-AQS PM data

40. Working for public health! (Picture by courtesy of Mike Moran)