Thermal Impact of Saharan Dust over Land. Part II: Application to Satellite IR Remote Sensing

Legrand, Michel; Cautenet, G.; Buriez, Jean Claude

doi:10.1175/1520-0450(1992)031<0181:tiosdo>2.0.co;2

Cited by 29 publications

(24 citation statements)

References 9 publications

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“…The first is BT 11µm -BT 12µm ≤ -0.5 K and BT 3.9μm -BT 11μm ≥ 25 K. The bulk transmittance of many aerosols displays a strong spectral variation in the 10-12 μm window regions. Thus, IR split window techniques have been developed at 11 and 12 μm to detect volcanic aerosols, particularly those from sulfur-rich eruptions (Prata, 1989;Barton et al, 1992), and dust outbreaks (Legrand et al, 1992(Legrand et al, , 2001Evan et al, 2006). Dust has a larger absorption at 12 µm than at 11 µm, so that dust plumes generally have a higher emissivity and lower transmissivity in the 12 µm channel (Ackerman, 1997;Dunion and Velden, 2004), which causes BT 11µm -BT 12µm to become negative.…”

Section: Detection Criteria Over Landsupporting

confidence: 78%

Asian Dust Detection from the Satellite Observations of Moderate Resolution Imaging Spectroradiometer (MODIS)

Zhao

2012

Aerosol Air Qual. Res.

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Asian dusts exert significant influences on regional air quality, weather, and climate. Detection of these highly variable aerosol events is challenging due to several factors, such as short lifetime, multiple scales, and strong interactions with local and regional surface and meteorological conditions. Since dust particles can directly alter solar and earth radiation in both visible (VS) and infrared (IR) spectral regions through scattering and absorption processes, both VS and IR remote sensing techniques can be used to detect dust plumes in the atmosphere. A dust detection system for multi-channel satellite imagers was applied in this study. The detection is based on the analysis of reflectance (or radiance) in VS channels or brightness temperature (BT) in IR channels. The magnitude of the difference in reflectance and/or BTs in selected channels due to dust is used to infer the signature of the dust particles. Descriptions of the detection system and its application for Asian dust using the Moderate-resolution Imaging Spectroradiometer (MODIS) satellite measurements are provided. The performance of the algorithm for Asian dust detection and its usefulness for monitoring the outbreaks and dispersion of Asian dust events were emphasized in the current study.

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Section: Detection Criteria Over Landsupporting

confidence: 78%

Asian Dust Detection from the Satellite Observations of Moderate Resolution Imaging Spectroradiometer (MODIS)

Zhao

2012

Aerosol Air Qual. Res.

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“…For these reasons, techniques have been developed which successfully employ satellite radiance measurements at 11 and 12 m to detect aerosols. These split window IR techniques have primarily been applied to the detection of volcanic aerosols, particularly those from sulfur-rich eruptions [e.g., 9,10], and dust outbreaks [11][12][13]. As demonstrated in Figure 3 for the case of Figure 1, dust absorbs more radiation at 12 µm than 11 µm, which causes the brightness temperature difference between the two to become negative.…”

Section: Dust Detection Over Landmentioning

confidence: 99%

Dust and Smoke Detection for Multi-Channel Imagers

Zhao

Ackerman

Guo³

2010

Remote Sensing

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A detection algorithm of dust and smoke for application to satellite multi-channel imagers is introduced in this paper. The algorithm is simple and solely based on spectral and spatial threshold tests along with some uniformity texture. Detailed examinations of the threshold tests are performed along with explanations of the physical basis. The detection is performed efficiently at the pixel level and output is in the form of an index (or flag): 0 (no dust/smoke) and 1 (dust/smoke). The detection algorithm is implemented sequentially and designed to run on segments of data instead of pixel by pixel for efficient processing. MODIS observations are used to test the operation and performance of the algorithm. The algorithm can capture heavy dust and smoke plumes very well over both land and ocean and therefore is used as a global detection algorithm. The method can be applied to any multi-channel imagers with channels at (or close to) 0. 47, 0.64, 0.86, 1.38, 2.26, 3.9, 11.0, 12.0 m (such as current EOS/MODIS and future JPSS/VIIRS and GOES-R/ABI) for the detection of dust and smoke. It can be used to operationally monitor the outbreak and dispersion of dust storms and smoke plumes that are potentially hazardous to our environment and impact climate.

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“…Subsequently, Legrand et al (1983Legrand et al ( , 1985, using METEOSAT infrared radiance data, studied dust aerosols over North Africa and Arabia. The studies carried out thereafter have demonstrated the potential of infrared radiance for quantitative estimates of dust aerosols (Ackerman, 1989;Legrand et al, 1989Legrand et al, , 1992Legrand et al, , 1994Legrand et al, , 2001Tanré and Legrand, 1991;Leon and Legrand, 2003).…”

Section: Problems In Quantification Of Dustmentioning

confidence: 99%

Dust aerosols over India and adjacent continents retrieved using METEOSAT infrared radiance Part I: sources and regional distribution

2006

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Abstract. Mineral dust constitutes the single largest contributor to continental aerosols. To accurately assess the impact of dust aerosols on climate, the spatial and temporal distribution of dust radiative properties is essential. Regional characteristics of dust radiative properties, however, are poorly understood. The magnitude and even sign of dust radiative forcing is uncertain, as it depends on a number of parameters, such as vertical distribution of dust, cloud cover and albedo of the underlying surface. In this paper, infrared radiance (10.5-12.5 µm), acquired from the METEOSAT-5 satellite (∼5-km resolution), was used to retrieve regional characteristics of dust aerosols for all of 1999. The infrared radiance depression, due to the presence of dust in the atmosphere, has been used as an index of dust load, known as the Infrared Difference Dust Index (IDDI). There have been several studies in the past carried out over the Sahara using IDDI as a measure of dust load. Over the Indian region, however, studies on dust aerosols are sparse. Spatial and temporal variability in dust loading and its regional distribution over various arid and semiarid regions of India and adjacent continents (0-35 • N; 30 • E-100 • E) (excluding Sahara) have been studied and the results are examined along with surface soil conditions (such as vegetation cover and soil moisture). The advantage of the IDDI method is that information on aerosol properties, such as chemical composition or microphysical properties, is not needed. A large day-to-day variation in IDDI was observed over the entire study region, with values ranging from 4 to 22 K. It was observed that dust activity starts by March over the Indian deserts, as well as over deserts of the Africa and Arabian regions. The IDDI reaches maximum during the period of May to August. Regional maps of IDDI, in conjunction with biomass burning episodes (using TERRA satellite fire pixel counts), suggest that large IDDI values observed during the winter months over Northern India could be due to a possible deposition of black carbon on larger dust aerosols. The IDDI values have beenCorrespondence to: S. K. Satheesh (satheesh@caos.iisc.ernet.in) compared with another year (i.e. 2003), with a large number of dust storms reported by meteorological departments based on visibility data. During the dry season, the magnitude of the monthly average IDDI during 2003 was slightly higher than that of 1999. The monthly mean IDDI was in the range from 4 to 9 K over the Indian deserts, as well as over the deserts of Africa and Arabia. The maximum IDDI during a month was in the range from 6 to 18 K. Large IDDI values were observed even over vegetated regions (such as the vegetated part of Africa and central India), attributed to the presence of transported dust from nearby deserts.

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Thermal Impact of Saharan Dust over Land. Part II: Application to Satellite IR Remote Sensing

Cited by 29 publications

References 9 publications

Asian Dust Detection from the Satellite Observations of Moderate Resolution Imaging Spectroradiometer (MODIS)

Asian Dust Detection from the Satellite Observations of Moderate Resolution Imaging Spectroradiometer (MODIS)

Dust and Smoke Detection for Multi-Channel Imagers

Dust aerosols over India and adjacent continents retrieved using METEOSAT infrared radiance Part I: sources and regional distribution

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