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PHAiRS 2005-2006: Dust PHAiRS 2005-2006: Dust ModelingModeling

Dazhong Yin Slobodan Nickovic William A. SpriggDazhong Yin Slobodan Nickovic William A. Sprigg

March 14, 2006 March 14, 2006

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Major activitiesMajor 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

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Assimilation of NASA data-MODIS land Assimilation of NASA data-MODIS land covercover

• 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.

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Assimilation of NASA data-MODIS land Assimilation of NASA data-MODIS land covercover

• MODIS data

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Assimilation of NASA data-MODIS land Assimilation of NASA data-MODIS land covercover

• Landcover on the modeling grid using OWE (left) and MODIS (right) data

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Assimilation of NASA data-SRTM terrain Assimilation of NASA data-SRTM terrain datadata

• 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.

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Assimilation of NASA data-SRTM terrain Assimilation of NASA data-SRTM terrain datadata

• USGS terrain data (left) and SRTM data (right)

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Assimilation of NASA data-Roughness length Assimilation of NASA data-Roughness length datadata

• Preview of roughness length data

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Assimilation of NASA data-Roughness length Assimilation of NASA data-Roughness length datadata

• 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)

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Assimilation of NASA data-FPAR dataAssimilation of NASA data-FPAR data

• Using category “barren, desert, or sparsely vegetated” based on FPAR data to pin point dust source area

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Assimilation of NASA data-AMSR-E soil Assimilation of NASA data-AMSR-E soil moisture datamoisture 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

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Assimilation of NASA data-AMSR-E soil Assimilation of NASA data-AMSR-E soil moisture datamoisture data

• Preview of the average soil moisture data

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Assimilation of NASA data-AMSR-E soil Assimilation of NASA data-AMSR-E soil moisture datamoisture data

NASA EOS data Representative model run Implementation timeMODIS land cover run_2_c May, 2005

MODIS land cover, SRTM terrain data run_4_a July, 2005

MODIS land cover, SRTM terrain data, Roughness length data

run_5_a August, 2005

MODIS land cover, FPAR data run_6_a October, 2005MODIS land cover, AMSR-E soil moisture data

run_15_a November, 2005

MODIS land cover, SRTM terrain data, Roughness length data, AMSR-E soil moisture data

run_10_a January, 2006

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Assessment of impacts of NASA dataAssessment of impacts of NASA data

MODIS land cover

SRTM terrain

NASA roughness length

FPAR data

AMSR-E soil moisture

run1arun2c Yrun4a Y Yrun5a Y Y Yrun5b Y Y Yrun6a Y Yrun15a Y Yrun10a Y Y Y Y

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Assessment of impacts of NASA dataAssessment of impacts of NASA data

Wind speed-case 1

0.7400.7450.7500.7550.7600.7650.7700.7750.780

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Wind direction-case1

0.7200.7250.7300.7350.7400.7450.7500.7550.760

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Temperature-case 1

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Assessment of impacts of NASA dataAssessment of impacts of NASA data

Wind speed-case 2

0.7250.7300.7350.7400.7450.7500.7550.7600.765

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Wind direction-case 2

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Temperature-case 2

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Assessment of impacts of NASA dataAssessment of impacts of NASA data

PM10-case 1

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PM2.5-case 1

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Assessment of impacts of NASA dataAssessment of impacts of NASA data

PM2.5-case 2

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PM10-case2

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Improvement of dust size resolution in Improvement of dust size resolution in DREAMDREAM

• Four size categories

Dust category Size bin

(m) Typical particle

radius (m)

Particle density (kg/m3)

Associated soil

component 1 0~3.4 0.73 2500 Clay 2 3.4~12 6.10 2650 small silt 3 12~28 18.00 2650 large silt 4 >28 38.00 2650 Sand

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Improvement of dust size resolution in Improvement of dust size resolution in DREAMDREAM

• Eight size categories k Type Typical particle radius

Rk (m)

Particle density

pk (g cm-3)

Productivity

factor

k

Bagnold param.

kA

1 Clay 0.15 2.50 0.02 1.0

2 Clay 0.25 2.50 0.04 0.9

3 Clay 0.40 2.50 0.15 0.8

4 Clay 0.80 2.50 0.67 0.8

5 Silt 1.50 2.65 1.00 0.7

6 Silt 2.50 2.65 1.00 0.6

7 Silt 4.00 2.65 1.00 0.5

8 Silt 8.00 2.65 1.00 0.4

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Improvement of dust size resolution in Improvement of dust size resolution in DREAMDREAM

• Particle size distribution at sources as D’Almeida (1987) or Gomes et al. (1990)

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Dust and atmospheric radiation interaction Dust and atmospheric radiation interaction module in DREAMmodule in DREAM

• Dust particles contribute to atmospheric optical thickness (), single-scattering albedo (w), and asymmetry factor (g)

kextk

kkkk QM

r)(

4

3)()(

8

1

8

1

8

1

8

1

)(

)()()(

kk

kkkw

w

8

1

8

1

)()(

)()()()(

kkk

kkkk

w

wgg

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Dust and atmospheric radiation interaction Dust and atmospheric radiation interaction module in DREAMmodule in DREAM

• Obvious dust radiative effects on the surface

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Dust and atmospheric radiation interaction Dust and atmospheric radiation interaction module in DREAMmodule in DREAM

• Negative feedback on atmospheric dust loading

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Dust and atmospheric radiation interaction Dust and atmospheric radiation interaction module in DREAMmodule in DREAM

• Better meteorological fields

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Development of quasi-operational DREAM Development of quasi-operational DREAM systemsystem

• 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

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Development of quasi-operational DREAM Development of quasi-operational DREAM systemsystem

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Development of quasi-operational DREAM Development of quasi-operational DREAM system-some urgent needssystem-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?

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Development of quasi-operational DREAM Development of quasi-operational DREAM system-some urgent needssystem-some urgent needs

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Development of quasi-operational DREAM Development of quasi-operational DREAM system-some urgent needssystem-some urgent needs

• Updated NASA land cover data to refresh land use in the model

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Development of quasi-operational DREAM Development of quasi-operational DREAM system-some urgent needssystem-some urgent needs

• Dust storm causes two pileups on I-8, Feb 15, 2006

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Development of quasi-operational DREAM Development of quasi-operational DREAM system-some urgent needssystem-some urgent needs

• Dust source differences due to using different land cover data

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Regionalization of the NCEP WRF-NMM for Regionalization of the NCEP WRF-NMM for the southwestern USthe southwestern US

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Regionalization of the NCEP WRF-NMM for Regionalization of the NCEP WRF-NMM for the southwestern USthe southwestern US

• Central lat 34.02N

• Central lon -108.90

• Grid no. 151*219

• Grid spacing 15 km

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Regionalization of the NCEP WRF-NMM for Regionalization of the NCEP WRF-NMM for the southwestern USthe southwestern US

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Regionalization of the NCEP WRF-NMM for Regionalization of the NCEP WRF-NMM for the southwestern USthe southwestern US

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Regionalization of the NCEP WRF-NMM for Regionalization of the NCEP WRF-NMM for the southwestern USthe southwestern US

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Regionalization of the NCEP WRF-NMM for Regionalization of the NCEP WRF-NMM for the southwestern USthe southwestern US

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AcknowledgementAcknowledgement

• 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 images

• US EPA-AQS PM data

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Working for public health!Working for public health!

(Picture by courtesy of Mike Moran)