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Geostationary meteorological satellites are unique tools to monitor atmospheric aerosols from space. The observation of the Earth several times per hour allows these types of imaging systems to provide high-temporal-resolution observations of these suspended particles, which are of interest for research and operational topics, including climate, air quality, numerical weather prediction, and volcanic risk management. However, some challenges need to be addressed to achieve the sub-daily retrieval of aerosol properties mainly due to the varying sensitivity of geostationary imagers to aerosols during the day. In this article we propose a new algorithm named iAERUS-GEO (instantaneous Aerosol and surfacE Retrieval Using Satellites in GEOstationary orbit) that estimates the diurnal evolution of aerosol optical depth (AOD) over land and ocean from the Meteosat Second Generation (MSG) satellite. This is achieved by the use of an optimal-estimation method combined with several aerosol models and other features, including the daily retrieval of the surface reflectance directionality using Kalman filtering. AOD estimates provided by iAERUS-GEO every 15 min – the acquisition frequency of the Spinning Enhanced Visible InfraRed Imager (SEVIRI) on MSG – are assessed with collocated reference aerosol observations. First, comparison to AERONET ground-based data proves the overall satisfactory accuracy of iAERUS-GEO over land, with the exception of some higher biases found over bright surfaces and for high scattering angles. The confidence measure provided by iAERUS-GEO is proved useful to filter these less satisfactory retrievals that generally arise due to a low information content on aerosols provided by SEVIRI. Second, comparison to the GRASP/POLDER satellite product shows similar scores for the two aerosol data sets, with a significantly larger number of retrievals for iAERUS-GEO. This added value – which we illustrate here by inspecting the sub-daily variation in AOD over selected regions – allows geostationary satellites to break the temporal barrier set by traditional aerosol remote sensing from the low Earth orbit. Furthermore, the aerosol retrievals presented in this work are expected to be improved in the near future thanks to the enhanced sensing capabilities of the upcoming Meteosat Third Generation Imager mission.

This study investigates the magnitude of the error introduced by the co-registration and interpolation in computing Stokes vector elements from observations by the Multi-viewing, Multi-channel, Multi-polarisation Imager (3MI). The Stokes parameter derivation from the 3MI measurements requires the syntheses of three wide-field-of-view images taken by the instrument at 0.25 s interval with polarizers at different angles. Even though the synthesis of spatially or temporally inhomogeneous data is inevitable for a number of polarimetric instruments, it is particularly challenging for 3MI because of the instrument design, which prioritizes the stability during a long life cycle and enables the wide-field-of-view and multiwavelength capabilities. This study therefore focuses on 3MI's motion-induced error brought in by the co-registration and interpolation that are necessary for the synthesis of three images. The 2-D polarimetric measurements from the Second-generation Global Imager (SGLI) are weighted and averaged to produce two proxy datasets of the 3MI measurements, with and without considering the effect of the satellite motion along the orbit. The comparison of these two datasets shows that the motion-induced error is not symmetric about zero and not negligible when the intensity variability of the observed scene is large. The results are analyzed in five categories of pixels: (1) cloud over water, (2) clear sky over water, (3) coastlines, (4) cloud over land, and (5) clear sky over land. The most spread distribution of normalized polarized radiance (Lp) difference is in the cloud-over-water class, and the most spread distribution of degree of linear polarization (DOLP) difference is in the clear-sky-over-water class. The 5th to 95th percentile ranges of Lp difference for each class are (1) [-0.0051,0.012], (2) [-0.0040,0.0088], (3) [-0.0033,0.012], (4) [-0.0033,0.0062], and (5) [-0.0023,0.0032]. The same percentile range of DOLP difference for each class are (1) [-0.023,0.060], (2) [-0.043,0.093], (3) [-0.019,0.082], (4) [-0.0075,0.014], and (5) [-0.011,0.016]. The medians of the Lp difference are (1) 0.00035, (2) 0.000049, (3) 0.00031, (4), 0.000089, and (5) 0.000037, whereas the medians of the DOLP difference are (1) 0.0014, (2) 0.0015, (3) 0.0025, (4) 0.00027, and (5) 0.00014. A model using Monte Carlo simulation confirms that the magnitude of these errors over clouds are closely related to the spatial correlation in the horizontal cloud structure. For the cloud-over-water category, it is shown that the error model developed in this study can statistically simulate the magnitude and trends of the 3MI's motion-induced error estimated from SGLI data. The obtained statistics and the simulation technique can be utilized to provide pixel-level quality information for 3MI Level 1B products. In addition, the simulation method can be applied to the past, current, and future spaceborne instruments with a similar design.

Information content analyses on cloud top altitude (CTOP) and geometrical thickness (CGT) from multi-angular A-band measurements in the case of monolayer homogeneous clouds are conducted. In the framework of future multi-angular radiometer development, we compared the potential performances of the 3MI (Multi-viewing, Multi-channel and Multi-polarization Imaging) instrument developed by EUMETSAT, which is an extension of POLDER/PARASOL instrument and MSPI (Multiangle SpectroPolarimetric Imager) developed by NASA's Jet Propulsion Laboratory. Quantitative information content estimates were realized for thin, moderately opaque and opaque clouds for different surface albedo and viewing geometry configurations. Analyses show that retrieval of CTOP is possible with a high accuracy in most of the cases investigated. Retrieval of CGT is also possible for optically thick clouds above a black surface, at least when CGT > 1–2 km and for thin clouds for CGT > 2–3 km. However, for intermediate optical thicknesses (COT ≃ 4), we show that the retrieval of CGT is not simultaneously possible with CTOP. A comparison between 3MI and MSPI shows a higher information content for MSPI's measurements, traceable to a thinner filter inside the oxygen A-band, yielding higher signal-to-noise ratio for absorption estimation. Cases of cloud scenes above bright surfaces are more complex but it is shown that the retrieval of CTOP remains possible in almost all situations while the information content on CGT appears to be insufficient in many cases, particularly for COT

Cloud thermodynamic phase (ice, liquid, undetermined) classification is an important first step for cloud retrievals from passive sensors such as MODIS (Moderate Resolution Imaging Spectroradiometer). Because ice and liquid phase clouds have very different scattering and absorbing properties, an incorrect cloud phase decision can lead to substantial errors in the cloud optical and microphysical property products such as cloud optical thickness or effective particle radius. Furthermore, it is well established that ice and liquid clouds have different impacts on the Earth's energy budget and hydrological cycle, thus accurately monitoring the spatial and temporal distribution of these clouds is of continued importance. For MODIS Collection 6 (C6), the shortwave-derived cloud thermodynamic phase algorithm used by the optical and microphysical property retrievals has been completely rewritten to improve the phase discrimination skill for a variety of cloudy scenes (e.g., thin/thick clouds, over ocean/land/desert/snow/ice surface, etc). To evaluate the performance of the C6 cloud phase algorithm, extensive granule-level and global comparisons have been conducted against the heritage C5 algorithm and CALIOP. A wholesale improvement is seen for C6 compared to C5.

Most of the current aerosol retrievals from passive sensors are restricted to cloud-free scenes, which strongly reduces our ability to monitor the aerosol properties at a global scale and to estimate their radiative forcing. The presence of aerosol above clouds (AAC) affects the polarized light reflected by the cloud layer, as shown by the spaceborne measurements provided by the POlarization and Directionality of Earth Reflectances (POLDER) instrument on the PARASOL satellite. In a previous work, a first retrieval method was developed for AAC scenes and evaluated for biomass-burning aerosols transported over stratocumulus clouds. The method was restricted to the use of observations acquired at forward scattering angles (90–120°) where polarized measurements are highly sensitive to fine-mode particle scattering. Non-spherical particles in the coarse mode, such as mineral dust particles, do not much polarize light and cannot be handled with this method. In this paper, we present new developments that allow retrieving also the properties of mineral dust particles above clouds. These particles do not much polarize light but strongly reduce the polarized cloud bow generated by the liquid cloud layer beneath and observed for scattering angles around 140°. The spectral attenuation can be used to qualitatively identify the nature of the particles (i.e. accumulation mode versus coarse mode, i.e. mineral dust particles versus biomass-burning aerosols), whereas the magnitude of the attenuation is related to the optical thickness of the aerosol layer. We also use the polarized measurements acquired in the cloud bow to improve the retrieval of both the biomass-burning aerosol properties and the cloud microphysical properties. We provide accurate polarized radiance calculations for AAC scenes and evaluate the contribution of the POLDER polarization measurements for the simultaneous retrieval of the aerosol and cloud properties. We investigate various scenes with mineral dust particles and biomass-burning aerosols above clouds. For clouds, our results confirm that the droplet size distribution is narrow in high-latitude ocean regions and that the droplet effective radii retrieved from both polarization measurements and from total radiance measurements are generally close for AAC scenes (departures smaller than 2 μm). We found that the magnitude of the primary cloud bow cannot be accurately estimated with a plane parallel transfer radiative code. The errors for the modeling of the polarized cloud bow are between 4 and 8% for homogenous cloudy scenes, as shown by a 3-D radiative transfer code. These effects only weakly impact the retrieval of the Aerosol Optical Thickness (AOT) performed with a mineral dust particle model for which the microphysical properties are entirely known (relative error smaller than 6%). We show that the POLDER polarization measurements allow retrieving the AOT, the fine-mode particle size, the Ångström exponent and the fraction of spherical particles. However, the complex refractive index and the coarse-mode particle size cannot be accurately retrieved with the present polarization measurements. Our complete and accurate algorithm cannot be applied to process large amounts of data, so a simpler algorithm was developed to retrieve the AOT and the Ångström exponent above clouds in an operational way. Illustrations are provided for July–August 2008 near the African coast. Large mean AOTs above clouds at 0.865 μm (>0.3) are retrieved for oceanic regions near the coasts of South Africa that correspond to biomass-burning aerosols, whereas even larger mean AOTs above clouds for mineral dust particles (>0.6) are also retrieved near the coasts of Senegal. For these regions and time period, the direct AAC radiative forcing is likely to be significant. The final aim of this work is the global monitoring of the AAC properties and the estimation of the direct aerosol radiative forcing in cloudy scenes.

The Spinning Enhanced Visible and InfraRed Imager (SEVIRI) aboard Meteosat Second Generation (MSG) launched in 2003 by EUMETSAT is dedicated to the Nowcasting applications and Numerical Weather Prediction and to the provision of observations for climate monitoring and research. We use the data in visible and near infrared (NIR) channels to derive the aerosol optical thickness (AOT) over land. The algorithm is based on the assumption that the top of the atmosphere (TOA) reflectance increases with the aerosol load. This is a reasonable assumption except in case of absorbing aerosols above bright surfaces. We assume that the minimum in a 14-days time series of the TOA reflectance is, once corrected from gaseous scattering and absorption, representative of the surface reflectance. The AOT and the aerosol model (a set of 5 models is used), are retrieved by matching the simulated TOA reflectance with the TOA reflectances measured by SEVIRI in its visible and NIR spectral bands. The high temporal resolution of the data acquisition by SEVIRI allows to retrieve the AOT every 15 min with a spatial resolution of 3 km at sub-satellite point, over the entire SEVIRI disk covering Europe, Africa and part of South America. The resulting AOT, a level 2 product at the native temporal and spatial SEVIRI resolutions, is presented and evaluated in this paper. The AOT has been validated using ground based measurements from AErosol RObotic NETwork (AERONET), a sun-photometer network, focusing over Europe for 3 months in 2006. The SEVIRI estimates correlate well with the AERONET measurements, r = 0.64, with a slight overestimate, bias = −0.017. The sources of errors are mainly the cloud contamination and the bad estimation of the surface reflectance. The temporal evolutions exhibited by both datasets show very good agreement which allows to conclude that the AOT Level 2 product from SEVIRI can be used to quantify the aerosol content and to monitor its daily evolution with a high temporal frequency. The comparison with daily maps of Moderate Resolution Imaging Spectroradiometer (MODIS) AOT level 3 product shows qualitative good agreement in the retrieved geographic patterns of AOT. Given the high spatial and temporal resolutions obtained with this approach, our results have clear potential for applications ranging from air quality monitoring to climate studies. This paper presents a first evaluation and validation of the derived AOT over Europe in order to document the overall quality of a product that will be made publicly available to the users of the aforementioned research communities.

Simulations of total and polarized cloud reflectance angular signatures such as the ones measured by the multi-angular and polarized radiometer POLDER3/PARASOL are used to evaluate cloud heterogeneity effects on cloud parameter retrievals. Effects on optical thickness, albedo, effective radius and variance of the cloud droplet size distribution and aerosol parameters above cloud are analyzed. Three different clouds that have the same mean optical thicknesses were generated: the first with a flat top, the second with a bumpy top and the last with a fractional cloud cover. At small scale (50 m), for oblique solar incidence, the illumination effects lead to higher total but also polarized reflectances. The polarized reflectances even reach values that cannot be predicted by the 1-D homogeneous cloud assumption. At the POLDER scale (7 km × 7 km), the angular signature is modified by a combination of the plane–parallel bias and the shadowing and illumination effects. In order to quantify effects of cloud heterogeneity on operational products, we ran the POLDER operational algorithms on the simulated reflectances to retrieve the cloud optical thickness and albedo. Results show that the cloud optical thickness is greatly affected: biases can reach up to −70, −50 or +40 % for backward, nadir and forward viewing directions, respectively. Concerning the albedo of the cloudy scenes, the errors are smaller, between −4.7 % for solar incidence angle of 20° and up to about +8 % for solar incidence angle of 60°. We also tested the heterogeneity effects on new algorithms that allow retrieving cloud droplet size distribution and cloud top pressures and also aerosol above clouds. Contrary to the bi-spectral method, the retrieved cloud droplet size parameters are not significantly affected by the cloud heterogeneity, which proves to be a great advantage of using polarized measurements. However, the cloud top pressure obtained from molecular scattering in the forward direction can be biased up to about 60 hPa (around 550 m). Concerning the aerosol optical thickness (AOT) above cloud, the results are different depending on the available angular information. Above the fractional cloud, when only side scattering angles between 100 and 130° are available, the AOT is underestimated because of the plane–parallel bias. However, for solar zenith angle of 60° it is overestimated because the polarized reflectances are increased in forward directions.