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Dust Detection in MODIS Image Spectral Thresholds based on Zhao et al., 2010 Pawan Gupta NASA Goddard Space Flight Center GEST/University of Maryland Baltimore County NASA ARSET Air Quality Training Salt Lake City, April 22-25, 2013

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Global Dust Sources

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Dust Source Strength Global dust emission strength is estimated using data on dust loading in the atmosphere, surface material characteristics, marine sediments, and numerical dust transport models. Recent studies estimate that global dust-emission rates falls within a range from less than 1000 to 3000 Tg yr 1 Estimates show a wide range of values, reflecting differences in modeling procedures, model resolution, the considered time scale, and specification of the source areas. About 80% of the dust is from the Northern Hemisphere. Seven to twenty percent of the dust emissions are less than 1 m in diameter (Cakmur et al., 2006; Schulz et al., 1998) The world's largest source of dust is the Sahara Desert - 160 to 760 Tg yr 1 Removal of dust from atmosphere is by direct contact with the surface without precipitation (dry deposition), or through scavenging by cloud droplet and precipitation (wet deposition).. Current estimates of the atmospheric dust loading range from less than 10 Tg to 35 Tg, an uncertainty factor of about 34.

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Available Satellite Aerosol Products for Dust Detection Work well over ocean but not over land Good for qualitative purpose only Only available over dark land targets (not available over desert s) Lack of information on scattering aerosols Sensitive to absorbing aerosols (fine dust) more sensitive to elevated aerosols Large footprint cloud contamination Sensitive to small mode aerosols Can be used with MODIS data to separate dust from non-dust aerosols Available over both dark and bright targets Narrow swath (almost point measurement) Very limited global coverage, Larger uncertainties in retrieved data sets Very good to estimated vertical distribution of aerosols, Limited swath width (360km) It can separate dust and non-dust aerosols NO daily observations for air quality Sensor Product Comment Available over land bright targets Angstrom coefficient & Single Scattering Albedo also can be used to detect dust (Ginoux et al., 2010) s)

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Spectral Signature Qu et al., 2006

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Spectral Response of Dust and Clouds Xie et al., 2009 BT11-BT12 >0.0 for clouds BT11-BT12

Dust Detection Test # 1 Pixel should pass these two conditions - R 0.47m, R 0.64m, R 0.86m, R 1.38m > 0 BT 3.9m, BT 11m, BT 12m > 0K If pixel deos not pass these tests Flaged as bad data Pixels in RED Remove bad pixels points from the image

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Dust Detection Test # 2 Remove cloudy pixels from the image BT 11m BT 12m 0.5K & BT 3.9m BT 11m 20K & R 1.38m < 0.055 If pixel failed any of these test..then flag is set as other class Pixels in BLUE

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Dust Detection Test # 3 Dust Detection - If MNDVI 0.005 then DUST If BT 3.9m - BT 11m >= 25K - then DUST DUST PIXELS are in YELLOW

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Dust Detection Test # 4 Thick Dust Detection -- If MNDVI