Dust Aerosol Optical Depth Retrieval over a Desert Surface Using the SEVIRI Window Channels

Abstract

The authors present a new algorithm to retrieve aerosol optical depth (AOD) over a desert using the window channels centered at 8.7, 10.8, and 12.0 mm of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board the Meteosat Second Generation satellite. The presence of dust aerosols impacts the longwave outgoing radiation, allowing the aerosols over the desert surfaces to be detected in the thermal infrared (IR) wavelengths. To retrieve the aerosol properties over land, the surface contribution to the satellite radiance measured at the top of the atmosphere has to be taken into account. The surface radiation depends on the surface temperature, which is characterized by a strong diurnal variation over the desert, and the surface emissivity, which is assumed to be constant over a time span of 24 h. The surface emissivity is based on clear-sky observations that are corrected for atmospheric absorption and emission. The clear-sky image is a composite of pixels that is characterized by the highest brightness temperature (BT) of the SEVIRI channel at 10.8 mm, and by a negative BT difference between the channels at 8.7 and 10.8 mm.Because of the lower temperatures of clouds and aerosols compared to clear-sky conditions, the authors assume that the selected pixel values are obtained for a clear-sky day. A forward model is used to simulate the thermal IR radiation transfer in the dust layer. The apparent surface radiation for the three window channels in the presence of aerosols is calculated as a function of the surface emissivity and the surface temperature, the aerosol layer temperature, and the AOD for different aerosol loadings. From these simulations two emissivity ratios, which are stored in lookup tables (LUT), are calculated. The retrieval algorithm consists of processing the clear-sky image and computing the surface emissivity, processing the instantaneous image, and computing the apparent surface radiation for the three window channels. The two emissivity ratios are computed using the radiances at 8.7 and 10.8 mm and at 8.7 and 12.0 mm, respectively. The SEVIRI AOD is obtained by the inversion of these emissivity ratios using the corresponding LUT. The algorithm is applied to a minor dust event over the Sahara between 19 and 22 June 2007. For the validation the SEVIRI AOD is compared with the AOD from the Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) along the satellite track.

Retrieval of desert dust aerosol vertical profiles from IASI measurements in the TIR atmospheric window

“…These properties cannot be inferred from short-wave measurements, because short-wave and longwave spectral windows are not sensitive to the same particle sizes. Current thermal infrared (TIR) dust retrievals using measurements from AIRS (Aqua), IASI (Metop) or SE-VIRI (MSG) provide total optical depth (OD, Pierangelo et al, 2004Pierangelo et al, , 2005Zhang et al, 2006;De Paepe and Dewitte, 2009;Peyridieu et al, 2010Peyridieu et al, , 2012DeSouza-Machado et al, 2010;Klüser et al, 2011) and in some cases particle size (Pierangelo et al, 2005;Zhang et al, 2006;Peyridieu et al, 2012), mineral composition (Klüser et al, 2012) or an equivalent or radiative altitude, being that of the atmospheric model's layer that was filled with aerosols for the retrieval (Pierangelo et al, 2004;Peyridieu et al, 2010Peyridieu et al, , 2012DeSouza-Machado et al, 2010). This altitude is obtained either from look-up tables, or after running the retrieval successively with aerosols located at different levels and selecting the one that leads to the lowest residuals.…”

Description and validation of an AOT product over land at the 0.6 μm channel of the SEVIRI sensor onboard MSG

“…Roujean et al, 1992) or from other sensors such as MODIS or POLDER onboard LEO satellites. Besides, methods based on IR channels to retrieve an aerosol product over bright surfaces exist (Legrand and N'doumé, 2001;De Paepe and Dewitte, 2009). These could, in combination with our product, contribute to a better monitoring of aerosols from geostationary satellites.…”

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

“…Quantitative detection consists of deriving the AOT at a specific wavelength from satellite measurements (Hsu et al 2004;Zhang et al 2006;Li et al 2007;Brindley and Russell 2009). Another approach was proposed by Paepe and Dewitte (2009), where AOT at 8.7, 10.8, and 12 µm was derived by establishing a lookup table of emissivity ratios by assuming a clear day to be the day having the maximum value of BT 10.8 and negative BTD 8.7-11 . Such thresholds of BT/BTD for a clear day have a very dynamic behaviour that depends on environmental and seasonal conditions, making it difficult to agree on a reference clear-sky brightness temperature for each time and location.…”

“…BT 3.7 , BT 10.8 , and BT 11 , where the subscripts represent wavelengths in µm) have been proposed for qualitative monitoring of dust (Legrand, Fattori, and N'doume 2001;Schepanski et al 2007). Other methods derive dust indices or aerosol optical thickness (AOT), which expresses the fraction of radiation passing through a dust layer for quantitative monitoring of dust in the atmosphere (Hsu et al 2004;Zhang et al 2006;Li et al 2007;Jolivet et al 2008;Brindley and Russell 2009;Paepe and Dewitte 2009). Ground-based measurements collected by the Aerosol Robotic Network (AERONET) or European Aerosol Research Lidar Network (EARLINET) are widely used as truth data in such developments.…”