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

Bernard, E.; Moulin, C.; Ramon, Didier; Jolivet, Dominique; Riédi, J.; Nicolas, Jean‐Marie

doi:10.5194/amt-4-2543-2011

Cited by 17 publications

(14 citation statements)

References 67 publications

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“…As to AOD retrieval over land using MSG/SEVIRI data, Popp et al (2007) used a "background method" which is not suitable for bright surfaces with absorbing aerosol to retrieve the AOD. Bernard et al (2011) evaluated this method, confirming that this method is suitable for most Europe areas. Carrer et al (2010) put forward daily estimates of AOD over land based on a directional and temporal analysis of visible observations from MSG/SEVIRI.…”

Section: Introductionmentioning

confidence: 63%

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Retrieval of aerosol optical depth over land based on a time series technique using MSG/SEVIRI data

et al. 2012

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Abstract.A novel approach for the joint retrieval of aerosol optical depth (AOD) and aerosol type, using Meteosat Second Generation -Spinning Enhanced Visible and Infrared Imagers (MSG/SEVIRI) observations in two solar channels, is presented. The retrieval is based on a Time Series (TS) technique, which makes use of the two visible bands at 0.6 µm and 0.8 µm in three orderly scan times (15 min interval between two scans) to retrieve the AOD over land. Using the radiative transfer equation for plane-parallel atmosphere, two coupled differential equations for the upward and downward fluxes are derived. The boundary conditions for the upward and downward fluxes at the top and at the bottom of the atmosphere are used in these equations to provide an analytic solution for the AOD. To derive these fluxes, the aerosol single scattering albedo (SSA) and asymmetry factor are required to provide a solution. These are provided from a set of six pre-defined aerosol types with the SSA and asymmetry factor. We assume one aerosol type for a grid of 1 • ×1 • and the surface reflectance changes little between two subsequent observations. A k-ratio approach is used in the inversion to find the best solution of atmospheric properties and surface reflectance. The k-ratio approach assumes that the surface reflectance is little influenced by aerosol scattering at 1.6 µm and therefore the ratio of surface reflectances in the solar band for two subsequent observations can be wellapproximated by the ratio of the reflectances at 1.6 µm. A further assumption is that the surface reflectance varies only slightly over a period of 30 min. The algorithm makes use of numerical minimisation routines to obtain the optimal solution of atmospheric properties and surface reflectance by selection of the most suitable aerosol type from pre-defined sets.A detailed analysis of the retrieval results shows that it is suitable for AOD retrieval over land from SEVIRI data. Six AErosol RObotic NETwork (AERONET) sites with different surface types are used for detailed analysis and 42 other AERONET sites are used for validation. From 445 collocations representing stable and homogeneous aerosol type, we find that >75 % of the MSG-retrieved AOD at 0.6 and 0.8 µm values compare favourably with AERONET observed AOD values, within an error envelope of ± 0.05 ± 0.15τ and a high correlation coefficient (R>0.86). The AOD datasets derived Published by Copernicus Publications on behalf of the European Geosciences Union. L. Mei et al.: Retrieval of aerosol optical depth over landusing the TS method with SEVIRI data is also compared with collocated AOD products derived from NASA TERRA and AQUA MODIS (The Moderate-resolution Imaging Spectroradiometer) data using the Dark Dense Vegetation (DDV) method and the Deep Blue algorithms. Using the TS method, the AOD could be retrieved for more pixels than with the NASA Deep Blue algorithm. This method is potentially also useful for surface reflectance retrieval using SEVIRI observations. The current paper focuses on AOD retrieval ...

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Section: Introductionmentioning

confidence: 63%

“…The method presented by Brindley and Ignatov (2006) can provide both AOD and size information for mineral aerosol. However, most AOD retrieval algorithms over land focus on daily or hourly average AOD products (Bernard et al, 2009(Bernard et al, , 2011Govaerts et al, 2010) or certain aerosol type (Brindley and Ignatov, 2006).…”

Section: Introductionmentioning

confidence: 99%

Retrieval of aerosol optical depth over land based on a time series technique using MSG/SEVIRI data

et al. 2012

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“…Aerosols, also called particulate matter in the context of air quality, are responsible for serious health problems all over the world, as they are known to favour respiratory and cardiovascular diseases as well as cancers (Brook et al, 2004). The World Health Organization (WHO) has set regulatory limits for aerosol concentrations, which are annual means of 20 and 10 µg m −3 for PM 10 and PM 2.5 (particulate matter with diameters less than 10 and 2.5 µm, respectively) concentrations.…”

Section: Introductionmentioning

confidence: 99%

Monitoring aerosols over Europe: an assessment of the potential benefit of assimilating the VIS04 measurements from the future MTG/FCI geostationary imager

et al. 2019

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Abstract. The study assesses the possible benefit of assimilating aerosol optical depth (AOD) from the future space-borne sensor FCI (Flexible Combined Imager) for air quality monitoring in Europe. An observing system simulation experiment (OSSE) was designed and applied over a 4-month period, which includes a severe-pollution episode. The study focuses on the FCI channel centred at 444 nm, which is the shortest wavelength of FCI. A nature run (NR) and four different control runs of the MOCAGE chemistry transport model were designed and evaluated to guarantee the robustness of the OSSE results. The synthetic AOD observations from the NR were disturbed by errors that are typical of the FCI. The variance of the FCI AOD at 444 nm was deduced from a global sensitivity analysis that took into account the aerosol type, surface reflectance and different atmospheric optical properties. The experiments show a general benefit to all statistical indicators of the assimilation of the FCI AOD at 444 nm for aerosol concentrations at the surface over Europe, and also a positive impact during the severe-pollution event. The simulations with data assimilation reproduced spatial and temporal patterns of PM10 concentrations at the surface better than those without assimilation all along the simulations and especially during the pollution event. The advantage of assimilating AODs from a geostationary platform over a low Earth orbit satellite has also been quantified. This work demonstrates the capability of data from the future FCI sensor to bring added value to the MOCAGE aerosol simulations, and in general, to other chemistry transport models.

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“…Large number of uncertainties of the AOD retrieved over land [18] as well as poor temporal resolution of polar orbiting satellites, which are often used for the AOD observations, lay at the foundation for the motivation for this study. In addition, a small number of aerosol monitoring stations in the Central-Eastern part of Europe, where the AOD is relatively high [30], causes problems with the study of the spatial and temporal variation of AOD and radiative forcing.…”

Section: Introductionmentioning

confidence: 99%

“…The Satellite Application Facilities (SAF) operational algorithm uses data in visible (0.6 μm) and near infrared (1.6 μm) channels [16,17]. The algorithm construction includes the assumption that the top of the atmosphere reflectance increases with the aerosol load, which is untrue only in the case of absorbing aerosols above bright surfaces [18]. The surface reflectance estimation is based on choosing the minimum TOA reflectance in a 14-day period.…”

Section: Introductionmentioning

confidence: 99%

Retrieval of Aerosol Optical Depth from Optimal Interpolation Approach Applied to SEVIRI Data

Zawadzka

Markowicz

2014

Remote Sensing

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This paper presents two algorithms used to derive Aerosol Optical Depth (AOD) from a synergy of satellite and ground-based observations, as well as aerosol transport model output. The Spinning Enhanced Visible Infrared Radiometer (SEVIRI) instrument on board Meteosat Second Generation (MSG) allows us to monitor aerosol loading over land at high temporal and spatial resolution. We present the algorithms which were fed with the data acquired via the SEVIRI channel 1, and also channels 1 and 3 in conjunction. In both cases, the surface reflectance is the most important parameter that should be estimated during the retrieval process. The surface properties are estimated during days with a low AOD (less than 0.1 at 500 nm) based on the radiance measured by the SEVIRI detector and aerosol optical properties modeled with the aerosol transport model or measured by the MODIS sensor. For data from the model and the MODIS, ground-based stations equipped with a sun photometer have been applied to correct the AOD fields using the optimal interpolation method. By assuming that surface reflectance at the SEVIRI resolution changes slowly over time, the AOD has been computed. Comparison of the SEVIRI AOD with the sun photometer observations shows good agreement/correlation. The mean bias is small (an order of 0.01-0.02) and the root mean square (rms) is about 0.05 for both one-and two-channel methods. In addition, the rms for the one-channel method does not change with the AOD.

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

Cited by 17 publications

References 67 publications

Retrieval of aerosol optical depth over land based on a time series technique using MSG/SEVIRI data

Retrieval of aerosol optical depth over land based on a time series technique using MSG/SEVIRI data

Monitoring aerosols over Europe: an assessment of the potential benefit of assimilating the VIS04 measurements from the future MTG/FCI geostationary imager

Retrieval of Aerosol Optical Depth from Optimal Interpolation Approach Applied to SEVIRI Data

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