A Model for Calculating Desert Aerosol Turbidity over the Oceans from Geostationary Satellite Data

Norton, C. C.; Mosher, Frederick R.; Hinton, Barry B.; Martin, David W.; Santek, David; Kuhlow, William

doi:10.1175/1520-0450(1980)019<0633:amfcda>2.0.co;2

Cited by 59 publications

(20 citation statements)

References 13 publications

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“…During Asian dust storms, dust particle size may vary between 0.01 and 100 μm. Techniques have been under development since the 1970s for dust identification from VIR (visible and near-infrared) (Griggs, 1975;Carlson, 1979;Norton et al, 1980) and TIR images (Shenk and Curran, 1974;Ackerman, 1989). The TIR method has the advantage of being able to detect dust over high albedo surfaces and in nighttime.…”

Section: Dust Storm Monitoringmentioning

confidence: 99%

A review on East Asian dust storm climate, modelling and monitoring

Shao

Dong

2006

Global and Planetary Change

434

288

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Section: Dust Storm Monitoringmentioning

confidence: 99%

A review on East Asian dust storm climate, modelling and monitoring

Shao

Dong

2006

Global and Planetary Change

434

288

View full text Add to dashboard Cite

“…Such methods have been successfully applied over water [Griggs, 1975[Griggs, , 1979; Mekler et al, 1977;Koepke and Quenzel, 1979] to produce an operational product from NOAA-AVHRR measurements [Rao et al, 1989;Ignatov et al, 1995]. Most of the remote sensing studies have been devoted to Saharan dust [Fraser, 1976;Carlson, 1979;Norton et al, 1980;Dulac et al, 1992;Jankowiak and Tanr& 1992]. Over the land, so far there has been no real attempt to retrieve aerosol at a global scale.…”

Section: Introductionmentioning

confidence: 99%

Operational remote sensing of tropospheric aerosol over land from EOS moderate resolution imaging spectroradiometer

Kaufman¹,

Tanré²,

Remer³

et al. 1997

J. Geophys. Res.

1,611

1,023

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Abstract. Daily distribution of the aerosol optical thickness and columnar mass concentration will be derived over the continents, from the EOS moderate resolution imaging spectroradiometer (MODIS) using dark land targets. Dark land covers are mainly vegetated areas and dark soils observed in the red and blue channels; therefore the method will be limited to the moist parts of the continents (excluding water and ice cover). After the launch of MODIS the distribution of elevated aerosol concentrations, for example, biomass burning in the tropics or urban industrial aerosol in the midlatitudes, will be continuously monitored. The algorithm takes advantage of the MODIS wide spectral range and high spatial resolution and the strong spectral dependence of the aerosol opacity for most aerosol types that result in low optical thickness in the mid-IR (

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“…The disadvantage of surface observation with coarse horizontal resolution can be overcome with the aid of satellite remote sensing. Earlier researchers utilized satellite visible and infrared measurements to detect dust storm over land and water (Shenek and Curran, 1974) and others utilized visible spectrum to monitor dust outbreaks as well as to estimate dust optical depth over oceanic regions (Carlson, 1978;Norton et al, 1980). However, monitoring dust aerosol outbreaks over land using satellite visible and near-infrared data is difficult due to the bright underlying desert surface.…”

Section: Introductionmentioning

confidence: 99%

Operational retrieval of Asian sand and dust storm from FY-2C geostationary meteorological satellite and its application to real time forecast in Asia

Niu

et al. 2008

Atmos. Chem. Phys.

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Abstract. This paper describes an operational retrieval algorithm for the sand/dust storm (SDS) from FY-2C/S-VISSR (Stretched-Visible and Infrared Spin-Scan Radiometer) developed at the National Satellite Meteorological Center (NSMC) of China. This algorithm, called Dust Retrieval Algorithm based on Geostationary Imager (DRAGI), is based on the optical and radiative physical properties of SDS in mid-infrared and thermal infrared spectral regions as well as the observation of all bands in the geostationary imager, which include the Brightness Temperature Difference (BTD) in split window channels, Infrared Difference Dust Index (IDDI) and the ratio of middle infrared reflectance to visible reflectance. It also combines the visible and water vapor bands observation of the geostationary imager to identify the dust clouds from the surface targets and meteorological clouds. The output product is validated by and related to other dust aerosol observations such as the synoptic weather reports, surface visibility, aerosol optical depth (AOD) and ground-based PM 10 observations. Using the SDS-IDD product and a data assimilation scheme, the dust forecast model CUACE/Dust achieved a substantial improvement to the SDS predictions in spring 2006.

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A Model for Calculating Desert Aerosol Turbidity over the Oceans from Geostationary Satellite Data

Cited by 59 publications

References 13 publications

A review on East Asian dust storm climate, modelling and monitoring

A review on East Asian dust storm climate, modelling and monitoring

Operational remote sensing of tropospheric aerosol over land from EOS moderate resolution imaging spectroradiometer

Operational retrieval of Asian sand and dust storm from FY-2C geostationary meteorological satellite and its application to real time forecast in Asia

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