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Few weeks after its launch in April 2018, Sentinel-3B of the European Space Agency has been put in a tandem phase with its twin Sentinel-3A already in orbit. Both platforms were on the same track with the same geometrical conditions to gather acquisitions over the same targets only thirty seconds apart. This tandem phase lasted from early June to mid October 2018 to provide a unique opportunity for each S-3 sensors to increase knowledge of payload differences, reduce uncertainties when comparing data and to homogenise differences by defining appropriate adjustments. The inter-unit consistency is critical for the mission. The outcome of the tandem phase analysis provides a strong reference for assessing other cross-calibration methodologies, one of those being based on the use of Deep Convective Clouds (DCCs). Whereas a physical model of DCC reflectance must be provided to compare Ocean and Land Colour Instrument (OLCI) measurements with an absolute reference, DCC observations are rather used for their whiteness, brightness, and large spatial extent, for interband monitoring. In this presentation, we present and validate a DCC-based radiometric validation methodology adapted to OLCI with a specific emphasis on its ability to accurately monitor the cross-calibration of the independent sensors. We base the analysis on a careful analysis of the OLCI DCC reflectance measurements with a sensitivity assessment of the data selection employed (use of SLSTR synergetic brightness temperature or reflectance in absorption bands, analysis and handling of saturated pixels) as well as a cautious analysis of the FOV-dependency of the results. Performance is assessed by comparisons with the cross-calibration reference of the tandem analysis, in and out of the tandem phase acquisition period. The methodology covers the complete OLCI spectrum (to the exception of absorption bands) with precision less than about 1%.

During the commissioning phase of Sentinel-3B, the satellite was placed in close formation with Sentinel-3A for several months. This configuration provides a unique opportunity to compare measurements from the two satellites, opening new perspectives for inter-calibration. We will briefly present an overview of activities performed using tandem data and describe in more details two applications for Sentinel-3 optical instruments. A first application is the estimation of inter-satellite calibration biases. We describe the methodology used to intercompare the multispectral OLCI A and B instruments, using re-gridding, conversion to reflectance and spectral adjustment of the Rayleigh signal. Statistics are then computed for the different classes of scene. Clouds are particularly interesting targets because of their abundance and white reflectance spectrum. Thanks to this method, it has been possible to estimated inter-calibration biases with an uncertainty lower than 0.5% across the full instrument field-of-view. Biases have been shown to be temporally stable during the tandem period. The efficiency of this inter-calibration has been assessed by aligning OLCI-A on OLCI-B with a custom reprocessing. We also demonstrate the positive impact on inter-comparison of Level 2 land and ocean products. A second type of application concerns the validation of per-pixel uncertainties. For this goal, differences between SLSTR A and B measurements (L1 or L2) are compared to ex-ante uncertainties provided by models. More precisely, the independent components of the uncertainties are used to normalize the inter-satellite differences. This normalized difference is expected to behave like a normal distribution with a standard deviation of 1. Although the agreement is relatively satisfactory for data with the highest quality level, some significant variations have been observed for lower quality indices. This information can help improve processing algorithms and/or uncertainty estimates.

Sentinel-3A (S3A), carrying the Ocean and Land Colour Instrument (OLCI), was successfully launched on February 16th 2016. It was the first of the series planned by the European Commission (EC) in the frame of COPERNICUS Sentinel program. Sentinel-3B is planned for launch in late 2017, bearing identical instruments, thus improving the global Earth coverage. The OLCI series providing global coverage at 300m resolution will therefore represent a major breakthrough in the family of ocean colour sensors. For being an operational mission feeding in downstream Copernicus services like CMEMS, it is essential to ensure product quality prior public release. As for most ocean color missions, this supposes the implementation of a system vicarious calibration (SVC). Based on the methodologies applied to MERIS (and historically to older sensors), SVC of OLCI is performed separately for near-infrared (NIR) and visible (VIS) bands. NIR bands SVC is performed over dedicated oligotrophic targets. Over such waters the marine signal is negligible in this spectral region compared to the contribution of the atmosphere. This avoids the use of in situ colocated data and provides enough sensor observations for the analysis and the computation of vicarious calibration gains. Different methodologies are tested and their intercomparison provides the conclusion that a simple unweighted regression on the NIR aerosol reflectances provides robust consistency in the obtained gains. On the other hand, VIS bands SVC relies on OLCI observations matching very high quality in situ measurements after calibration of the NIR. For the time being, only two operational stations provide sufficiently high quality data for this purpose: BOUSSOLE in the Mediterranean Sea and MOBY in the Pacific Ocean. The number of accurate vicarious calibration matchups to ensure statistically reliable gains is discussed. To increase the statistics and improve reliability, an alternative procedure based on the use of global daily climatologies is shown to provide consistent additional measurements for the computation of robust SVC gains in the VIS. In this presentation, the implemented SVC procedures for OLCI are described along with the analysis ensuring their reliability. OLCI product quality improvement brought by SVC is shown through the analysis of individual user products as well as by comparison with in situ data and other sensors.

In the frame of the ESA Scientific Exploitation of Operational Missions project, ACRI-ST is responsible for the development and the intercomparison of new algorithms to validate the Sentinel 2 L1C product radiometry, beyond the baseline algorithms used operationally in the frame of the S2 Mission Performance Centre. In this context ACRI-ST is in charge of the definition and implementation of a validation approach based on the exploitation of deep convective cloud (DCC) observations. Due to their physical properties, DCCs appear from the remote sensing point of view to have bright tops and white behavior; they can be used as invariant targets to monitor the radiometric response degradation of reflective solar bands. The observation of such targets allows an interband radiometry validation in the VIS-NIR domain (MSI bands between 443 and 865 nm) from a reference band considered as correctly calibrated. We first present the DCC data selection criteria appropriate for the radiometric validation of the Sentinel-2 MSI instrument. The validation methodology is then thoroughly described and justified. It is based on the simulation of DCC top-of-atmosphere reflectance using radiative transfer modeling and its comparison to the actual MSI measurements to assess systematic interband biases. Final results and uncertainties are computed through the statistical analysis of a large collection of individual observations with a view to provide consolidated interband radiometric gains for MSI. These show the very good radiometric performance of MSI with interband gains much lower than 2%.

International audience; This paper presents the under-going development of the ground segment algorithms of the SWIM instrument. SWIM is a wave scatterometer which will be embarked on the Chinese French oceanography mission, CFOSAT. SWIM aims at measuring the 2D oceanic wave spectra; it is a Ku band real aperture radar.Simulations are performed to get data along the satellite track: radar signals are obtained simulated interaction with a realistic sea surface and taking into account the radar geometry. Then, the simulated data are processed with software prototypes.

L'augmentation considérable du trafic aérien depuis quelques décennies a motivé des recherches sur l'impact des traînées de condensation sur le climat. Lorsque celles-ci persistent, elles induisent une couverture nuageuse additionnelle en cirrus dont l'impact sur le climat est difficile à quantifier. La condition physique de la persistance des trainées de condensation est la sursaturation en glace (humidité relative supérieure à la saturation), phénomène assez fréquent dans la haute troposphère et condition nécessaire pour la formation des cirrus. Dans ce contexte, les sondeurs infrarouges ont l'avantage de fournir, de manière globale et continue, des mesures conjointes de propriétés nuageuses et de profils atmosphériques de température et de vapeur d'eau. Nous utilisons dans cette étude les bases de données climatiques TIROS-N Observation Vertical Sounder (TOVS) puis Atmospheric InfraRed Sounder (AIRS). Ces deux instruments n'ont pas une résolution verticale suffisante pour détecter la présence de fines couches de sursaturation en glace. Des synergies avec d'autres types observations permettent de le mettre en évidence et de le corriger. Nous démontrons notamment à l'aide du lidar CALIOP (Cloud-Aerosol LIdar with Orthogonal Polarization) que l'humidité relative de la haute troposphère dans les cirrus, déterminée par AIRS, montre un biais négatif en comparaison de mesures in situ. Ce biais est lié à la résolution verticale de AIRS et il est d'autant plus prononcé que les nuages sont géométriquement fins. Il est difficile de détecter la sursaturation car cette dernière est plus à même d'apparaître sur de fines épaisseurs. Une méthode de correction est alors proposée pour mieux estimer les fréquences d'occurrence de la sursaturation en glace à l'échelle globale. La synergie entre AIRS et des mesures aéroportées de la campagne MOZAIC (Measurement of OZone and water vapour by AIrbus in-service airCraft) nous permet de construire une probabilité d'occurrence de la sursaturation en fonction de l'humidité relative déterminée par AIRS, quelque soit la valeur de cette humidité relative. Cette probabilité permet de construire des climatologies de la sursaturation en glace. Enfin, son couplage avec la détermination conjointe des propriétés nuageuses permet d'établir des climatologies des situations atmosphériques favorables à la persistance et à l'impact sur le climat des traînées de condensation.