Remote sensing of mineral dust over land with MSG infrared channels: A new Bitemporal Mineral Dust Index

A new Bitemporal Mineral Dust Index (BMDI) is derived from Meteosat Second Generation (MSG) infrared observations over land at two different time slots per day. This daily dust index is evaluated with AErosol RObotic NETwork (AERONET) surface observations, MODerate resolution Imaging Spectro-radiometer (MODIS) “Deep Blue” Aerosol Optical Depth (AOD) and Ozone Monitoring Instrument (OMI) Aerosol Index, showing a good capability of the BMDI for dust detection and dust load estimation over land and also over deserts. BMDI dust detection is shown to be limited in scenes with high atmospheric humidity as e.g. coastal regions. In particular the insensitivity of BMDI to biomass burning aerosol is shown, leading to the possibility of remote sensing of mineral dust also in regions with large contributions of biomass burning aerosol to the total column aerosol concentrations. Time series of mineral dust as inferred from BMDI for the year 2006 are presented for four regions over the Sahara. These time series show strong (and different) annual cycles of dust load for all four regions. Especially the strong episodic character of atmospheric dust in the main source regions can be inferred from BMDI observations

Observations of shallow convective clouds generated by solar heating of dark smoke plumes

The SEVIRI instrument on the Meteosat Second Generation satellite with both fine spatial and temporal resolution allows to detect and follow the dynamics of fast developing meteorological events like spreading smoke plumes and the lifecycles of convective clouds. Smoke plumes have the ability to change the atmospheric heat content due to absorption and reduced reflection of solar radiation. By these means they can trigger formation of shallow convective clouds at their edge. A heavy smoke plume emerging from burning Lebanese oil tanks and spreading over adjacent deserts on 17 July 2006 has been observed as an example of such an effect. This study suggests a physical explanation of the observed convection along the edge of the smoke plume, namely the strong thermal contrast resulting from solar heating of the smoke layer

Synergetic aerosol retrieval from SCIAMACHY and AATSR onboard ENVISAT

International audienceThe synergetic aerosol retrieval method SYNAER (Holzer-Popp et al., 2002a) has been extended to the use of ENVISAT measurements. It exploits the complementary information of a radiometer and a spectrometer onboard one satellite platform to extract aerosol optical depth (AOD) and speciation (as choice from a representative set of pre-defined mixtures of water-soluble, soot, mineral dust, and sea salt components). SYNAER consists of two retrieval steps. In the first step the radiometer is used to do accurate cloud screening, and subsequently to quantify the aerosol optical depth (AOD) at 550 nm and spectral surface brightness through a dark field technique. In the second step the spectrometer is applied to choose the most plausible aerosol type through a least square fit of the measured spectrum with simulated spectra using the AOD and surface brightness retrieved in the first step. This method was developed and a first case study evaluation against few (15) multi-spectral ground-based AERONET sun photometer observations was conducted with a sensor pair (ATSR-2 and GOME) onboard ERS-2. However, due to instrumental limitations the coverage of SYNAER/ERS-2 and the AERONET network in 1997/98 is very sparse and thus only few coincidences with AERONET were found. Therefore, SYNAER was transferred to similar sensors AATSR and SCIAMACHY onboard ENVISAT. While transferring to the new sensor pair a thorough evaluation of the synergetic methodology and its information content has been conducted, which led to significant improvements in the methodology: an update of the aerosol model, an improved cloud detection, and an enhanced dark field albedo characterization. This paper describes the information content analysis and these improvements in detail and presents first results of applying the SYNAER methodology to AATSR and SCIAMACHY

Aerosol retrieval experiments in the ESA Aerosol_cci project

Within the ESA Climate Change Initiative (CCI) project Aerosol_cci (2010–2013), algorithms for the production of long-term total column aerosol optical depth (AOD) datasets from European Earth Observation sensors are developed. Starting with eight existing pre-cursor algorithms three analysis steps are conducted to improve and qualify the algorithms: (1) a series of experiments applied to one month of global data to understand several major sensitivities to assumptions needed due to the ill-posed nature of the underlying inversion problem, (2) a round robin exercise of "best" versions of each of these algorithms (defined using the step 1 outcome) applied to four months of global data to identify mature algorithms, and (3) a comprehensive validation exercise applied to one complete year of global data produced by the algorithms selected as mature based on the round robin exercise. The algorithms tested included four using AATSR, three using MERIS and one using PARASOL. This paper summarizes the first step. Three experiments were conducted to assess the potential impact of major assumptions in the various aerosol retrieval algorithms. In the first experiment a common set of four aerosol components was used to provide all algorithms with the same assumptions. The second experiment introduced an aerosol property climatology, derived from a combination of model and sun photometer observations, as a priori information in the retrievals on the occurrence of the common aerosol components. The third experiment assessed the impact of using a common nadir cloud mask for AATSR and MERIS algorithms in order to characterize the sensitivity to remaining cloud contamination in the retrievals against the baseline dataset versions. The impact of the algorithm changes was assessed for one month (September 2008) of data: qualitatively by inspection of monthly mean AOD maps and quantitatively by comparing daily gridded satellite data against daily averaged AERONET sun photometer observations for the different versions of each algorithm globally (land and coastal) and for three regions with different aerosol regimes. The analysis allowed for an assessment of sensitivities of all algorithms, which helped define the best algorithm versions for the subsequent round robin exercise; all algorithms (except for MERIS) showed some, in parts significant, improvement. In particular, using common aerosol components and partly also a priori aerosol-type climatology is beneficial. On the other hand the use of an AATSR-based common cloud mask meant a clear improvement (though with significant reduction of coverage) for the MERIS standard product, but not for the algorithms using AATSR. It is noted that all these observations are mostly consistent for all five analyses (global land, global coastal, three regional), which can be understood well, since the set of aerosol components defined in Sect. 3.1 was explicitly designed to cover different global aerosol regimes (with low and high absorption fine mode, sea salt and dust)

Observations of convective clouds generated by solar heating of dark smoke plumes

International audienceThe SEVIRI instrument on the Meteosat Second Generation satellite with both fine spatial and temporal resolution allows to detect and follow the dynamics of fast developing meteorological events like spreading smoke plumes and the lifecycles of convective clouds. Smoke plumes have the ability to change the atmospheric heat content due to absorption and reduced reflection of solar radiation. By these means they can alter the temperature profile of the atmosphere and trigger convective clouds. A heavy smoke plume emerging from burning Lebanese oil tanks and spreading over adjacent deserts on 17 July 2006 has been observed as an example of such an effect. This study suggests a physical explanation of the observed convection along the edge of the smoke plume, namely the strong thermal contrast resulting from solar heating of the smoke layer

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

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<sub>0.5 μm</sub> and AERONET coarse mode AOD<sub>0.5 μm</sub> are reasonably well (linearly) correlated 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 AERONET Ångström exponent is −0.557 indicating the general capability of (qualitative) dust particle size information being provided by this method