Thermal infrared remote sensing of mineral dust over land and ocean: a spectral SVD based retrieval approach for IASI

Abstract

Abstract. From the high spectral resolution thermal infrared observations of the Infrared Atmospheric Sounding Interferometer (IASI) mineral dust AOD (transferred from thermal infrared to 0.5 µm) is retrieved using a Singular Vector Decomposition of brightness temperature spectra. As infrared retrieval based on 8-12 µm observations, dust observation with IASI is independent from solar illumination. Through the linear combinations of suitable independent singular vectors weighted by their contribution to the observed signal, and a projection of different a-priori dust spectra on the resulting signal the dust can be well distinguished from the influence of surface emissivity and gas absorption. In contrast to lookup-table based single-channel retrievals this method takes advantage of the spectral shape of dust extinction and surface and atmosphere influence over the total 8-12 µm window band. Using different a-priori spectra for dust extinction allows also for an estimation of dust particle size in terms of effective radius based on the respective dust model size distributions. These dust models are also used for the transfer of infrared AOD to 0.5 µm.Four months of IASI observations covering Northern Africa and Arabia are used for evaluation. Two large scale dust events, one covering the Arabian Peninsula and adjacent parts of the Indian Ocean, the other over the Atlantic Ocean off the coast of West-Africa, are analysed and compared with other satellite images. They also show the good suitability of IASI data for dust observation at day and night. Monthly means derived from IASI observations represent well the known seasonal cycles of dust activity over Northern Africa and Arabia. IASI Dust AOD 0.5µm and AERONET coarse mode AOD 0.5µm are reasonably well (linearly) correCorrespondence to: L. Klüser (lars.klueser@dlr.de) lated with ρ = 0.623. Moreover, comparison of time series of AERONET and IASI observations shows that the evolution of dust events is very well covered by the IASI observations. Rank correlation between dust effective radius and AERONETÅngström exponent is −0.557 indicating the general capability of (qualitative) dust particle size information being provided by this method.

Mapping the physico-chemical properties of mineral dust in western Africa: mineralogical composition

“…The 10-12 µm band, which is sensitive to differences in the mineralogical composition amongst sources, is relevant to the retrieval of various spaceborne sensors, including IASI, AIRS and MODIS (De Souza Machado et al, 2006;Hudson et al, 2008a;Klüser et al, 2011;Laskina et al, 2012). Some of the discrepancies between our values and the OPAC database are, at least partially, due to differences in the optical constants of the individual minerals.…”

Multispectral information from TANSO-FTS instrument – Part 2: Application to aerosol effect on greenhouse gas retrievals

“…Nevertheless, these instruments have the advantage, among others, of being highly sensitive to the aerosol type. Recently, many works have been achieved from infrared spectrometers such as AIRS and IASI (Pierangelo et al, 2004(Pierangelo et al, , 2005De Souza-Machado, 2006;Klüser et al, 2011Klüser et al, , 2012Clarisse et al, 2010Clarisse et al, , 2013Quan et al, 2013;Peyridieu et al, 2013). The aerosol characteristics (AOD, mean altitude and size) obtained from infrared appear to be very promising to complement the aerosol parameters retreived from visible observations.…”

Retrieval of effective aerosol diameter from satellite observations

“…It is mainly caused by Aerosols Optical Depth(AOD), dust particle size and shape and the emissivity which in turn linked to dust chemical composition (e.g. Brindley et al 2012;Klüser et al 2011). The method presented here shows it is possible to reduce this correlation complexity when the brightness temperature difference is used to retrieve effective dust size.…”

“…The comparison between in-situ sampling during Saharan Mineral Dust Experiment (SAMUM) 2006 and AERONET effective 10 radii retrieval showed that the Sun photometer observations are smaller by a factor of two compared to the in-situ observations (Müller et al 2012). The underestimation of the dust size distribution also appears to be a common pattern among the current satellite algorithms (Klüser et al, 2011;Pierangelo et al 2005). The abundance of large particles over desert surfaces might have a role in reducing the accuracy of the current sunphotometer and satellite techniques (Ryder et al 2013b).…”

“…Klüser et al (2011) also used a Singular Vector Decomposition method on observed spectra from 5 the Infrared Atmospheric Sounding Interferometer (IASI) to extract dust effective radius.…”