The effect of soil moisture and wind speed on aerosol optical thickness retrieval in a desert environment using SEVIRI thermal channels

Parajuli, Sagar; Gherboudj, Imen; Ghedira, Hosni

doi:10.1080/01431161.2013.788262

Cited by 7 publications

(8 citation statements)

References 56 publications

(100 reference statements)

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“…Satellite observations, however, have some limitations that result in false identification of dust sources in some areas. One such area is where persistent dust transport/deposition takes place, and another is where pollution/biomass burning contributes significantly to the total dust load [e.g., Schepanski et al ., ; Parajuli et al ., ]. Some efforts have been made recently to improve dust source characterization by eliminating these false dust source areas.…”

Section: Introductionmentioning

confidence: 99%

Mapping erodibility in dust source regions based on geomorphology, meteorology, and remote sensing

2014

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Mineral dust in the atmosphere has implications for Earth's radiation budget, biogeochemical cycles, hydrological cycles, human health, and visibility. Currently, the simulated vertical mass flux of dust differs greatly among the existing dust models. While most of the models utilize an erodibility factor to characterize dust sources, this factor is assumed to be static, without sufficient characterization of the highly heterogeneous and dynamic nature of dust source regions. We present a high-resolution land cover map of the Middle East and North Africa (MENA) in which the terrain is classified by visually examining satellite images obtained from Google Earth Professional and Environmental Systems Research Institute Basemap. We show that the correlation between surface wind speed and Moderate Resolution Imaging Spectroradiometer deep blue aerosol optical depth (AOD) can be used as a proxy for erodibility, which satisfactorily represents the spatiotemporal distribution of soil-derived dust sources. This method also identifies agricultural dust sources and eliminates the satellite-observed dust component that arises from long-range transport, pollution, and biomass burning. The erodible land cover of the MENA region is grouped into nine categories: (1) bedrock: with sediment, (2) sand deposit, (3) sand deposit: on bedrock, (4) sand deposit: stabilized, (5) agricultural and urban area, (6) fluvial system, (7) stony surface, (8) playa/sabkha, and (9) savanna/grassland. Our results indicate that erodibility is linked to the land cover type and has regional variation. An improved land cover map, which explicitly accounts for sediment supply, availability, and transport capacity, may be necessary to represent the highly dynamic nature of dust sources in climate models.

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Section: Introductionmentioning

confidence: 99%

Mapping erodibility in dust source regions based on geomorphology, meteorology, and remote sensing

2014

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“…Different techniques of detection and aerosol property remote sensing have been successfully applied to SEVIRI measurements (Brindley and Russell, 2006;Brindley et al, 2012;De Pape and Dewitte, 2008;Li et al, 2007;Parajuli et al, 2013;Romano et al, 2013;Sannazzaro et al, 2014). These algorithms have been validated and inter-compared (Banks and Brindley, 2013;Breon et al, 2011;Schepanski et al, 2012).…”

Section: The Crew Databasementioning

confidence: 99%

Remote sensing of cloud top pressure/height from SEVIRI: analysis of ten current retrieval algorithms

et al. 2014

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Abstract. The role of clouds remains the largest uncertainty in climate projections. They influence solar and thermal radiative transfer and the earth's water cycle. Therefore, there is an urgent need for accurate cloud observations to validate climate models and to monitor climate change. Passive satellite imagers measuring radiation at visible to thermal infrared (IR) wavelengths provide a wealth of information on cloud properties. Among others, the cloud top height (CTH) -a crucial parameter to estimate the thermal cloud radiative forcing -can be retrieved. In this paper we investigate the skill of ten current retrieval algorithms to estimate the CTH using observations from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard Meteosat Second Generation (MSG). In the first part we compare ten SEVIRI cloud top pressure (CTP) data sets with each other. The SEVIRI algorithms catch the latitudinal variation of the CTP in a similar way. The agreement is better in the extratropics than in the tropics. In the tropics multi-layer clouds and thin cirrus layers complicate the CTP retrieval, whereas a good agreement among the algorithms is found for trade wind cumulus, marine stratocumulus and the optically thick cores of the deep convective system.In the second part of the paper the SEVIRI retrievals are compared to CTH observations from the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar (CPR) instruments. It is important to note that the different measurement techniques cause differences in the retrieved CTH data. SEVIRI measures a radiatively effective CTH, while the CTH of the active instruments is derived from the return time of the emitted radar or lidar signal. Therefore, some systematic differences are expected. On average the CTHs detected by the SEVIRI algorithms are 1.0 to 2.5 km lower than CALIOP observations, and the correlation coefficients between the SEVIRI and the CALIOP data sets range between 0.77 and 0.90. The average CTHs derived by the SEVIRI algorithms are closer to the CPR measurements Published by Copernicus Publications on behalf of the European Geosciences Union. U. Hamann et al.: Remote sensing of cloud top pressure/height from SEVIRIthan to CALIOP measurements. The biases between SEVIRI and CPR retrievals range from −0.8 km to 0.6 km. The correlation coefficients of CPR and SEVIRI observations vary between 0.82 and 0.89. To discuss the origin of the CTH deviation, we investigate three cloud categories: optically thin and thick single layer as well as multi-layer clouds. For optically thick clouds the correlation coefficients between the SEVIRI and the reference data sets are usually above 0.95. For optically thin single layer clouds the correlation coefficients are still above 0.92. For this cloud category the SE-VIRI algorithms yield CTHs that are lower than CALIOP and similar to CPR observations. Most challenging are the multi-layer clouds, where the correlation coefficients are for most algorithms between 0.6 and 0.8. Finally, we evaluate ...

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“…However, at Liwa the dust emission is weak, though the wind speeds are higher, and these could be due to the peculiarities of the soil and surface properties. This result confirms the previously obtained result, which found that the UAE is not a strong source of dust [ Eck et al ., ; Parajuli et al ., ]. Rather, the aerosol loading over the UAE region is greatly influenced by the long‐range transported dust.…”

Section: Resultsmentioning

confidence: 99%

“…This large variability could be attributed to the high frequency of occurrence, as well as the intensity of dust events. In fact, recent studies show that UAE is not a strong source of dust, and the aerosol properties at those locations are strongly modulated by the long‐range dust transport [ Eck et al ., ; Parajuli et al ., ; Gherboudj and Ghedira , ].…”

Section: Description Of the Input Datamentioning

confidence: 99%

Dust emission parameterization scheme over the MENA region: Sensitivity analysis to soil moisture and soil texture

Gherboudj

Beegum

Marticorena

et al. 2015

J. Geophys. Res. Atmos.

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The mineral dust emissions from arid/semiarid soils were simulated over the MENA (Middle East and North Africa) region using the dust parameterization scheme proposed by Alfaro and Gomes (2001), to quantify the effect of the soil moisture and clay fraction in the emissions. For this purpose, an extensive data set of Soil Moisture and Ocean Salinity soil moisture, European Centre for Medium‐Range Weather Forecasting wind speed at 10 m height, Food Agricultural Organization soil texture maps, MODIS (Moderate Resolution Imaging Spectroradiometer) Normalized Difference Vegetation Index, and erodibility of the soil surface were collected for the a period of 3 years, from 2010 to 2013. Though the considered data sets have different temporal and spatial resolution, efforts have been made to make them consistent in time and space. At first, the simulated sandblasting flux over the region were validated qualitatively using MODIS Deep Blue aerosol optical depth and EUMETSAT MSG (Meteosat Seciond Generation) dust product from SEVIRI (Meteosat Spinning Enhanced Visible and Infrared Imager) and quantitatively based on the available ground‐based measurements of near‐surface particulate mass concentrations (PM10) collected over four stations in the MENA region. Sensitivity analyses were performed to investigate the effect of soil moisture and clay fraction on the emissions flux. The results showed that soil moisture and soil texture have significant roles in the dust emissions over the MENA region, particularly over the Arabian Peninsula. An inversely proportional dependency is observed between the soil moisture and the sandblasting flux, where a steep reduction in flux is observed at low friction velocity and a gradual reduction is observed at high friction velocity. Conversely, a directly proportional dependency is observed between the soil clay fraction and the sandblasting flux where a steep increase in flux is observed at low friction velocity and a gradual increase is observed at high friction velocity. The magnitude of the percentage reduction/increase in the sandblasting flux decreases with the increase of the friction velocity for both soil moisture and soil clay fraction. Furthermore, these variables are interdependent leading to a gradual decrease in the percentage increase in the sandblasting flux for higher soil moisture values.

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The effect of soil moisture and wind speed on aerosol optical thickness retrieval in a desert environment using SEVIRI thermal channels

Cited by 7 publications

References 56 publications

Mapping erodibility in dust source regions based on geomorphology, meteorology, and remote sensing

Mapping erodibility in dust source regions based on geomorphology, meteorology, and remote sensing

Remote sensing of cloud top pressure/height from SEVIRI: analysis of ten current retrieval algorithms

Dust emission parameterization scheme over the MENA region: Sensitivity analysis to soil moisture and soil texture

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