.[1] In this paper, synergy refers to a process where the use of multiple satellite observations makes the retrieval more precise than the best individual retrieval. Two general strategies can be used in order to use multi-wavelength observations in an inversion scheme. First, the multi-wavelength observations are merged in the input of the retrieval scheme. This means that the various satellite observations are used simultaneously and that their possible interactions can be exploited by the retrieval scheme. Second, each multi-wavelength observations are used independently to retrieve a same geophysical variable and then, these independent retrievals are combined a posteriori using for example a simple weighted averaging. In this paper, it is shown that the first approach provides better synergy results: The retrieval is better suited to optimize the use of all the information available because they are provided to the algorithm simultaneously. In particular, the retrieval process is able, in this case, to exploit the possible interactions between the various input information. The two retrieval approaches are tested and compared using an application for the retrieval of atmospheric profiles and integrated column quantities (temperature, water vapor, and ozone) using MetOp-A observations from IASI, AMSU-A and MHS instruments. Although real satellite observations are considered in this analysis, the results are dependent on the correlation structure in the training data set (i.e. ECMWF analysis) used to calibrate the retrieval algorithm. However, it can be seen that the infrared and microwave observations have a good synergy for the retrieval of atmospheric temperature, water vapor, and for ozone thanks to an indirect synergy.Citation: Aires, F., O. Aznay, C. Prigent, M. Paul, and F. Bernardo (2012), Synergistic multi-wavelength remote sensing versus a posteriori combination of retrieved products: Application for the retrieval of atmospheric profiles using MetOp-A, J. Geophys.

PLEIADES is a dual Earth observation system composed of two satellites, PLEIADES-1A and PLEIADES-1B, respectively launched at the end of 2011 and 2012. This imagery system, led by CNES, has four spectral bands, blue, green, red and near infrared, with a spatial resolution of 2.8 m and a panchromatic band with a resolution of 0.7 m in vertical viewing. Its swath is about 20 km.In the framework of the PLEIADES radiometric calibration, studies took place in order to determine the calibration precision that could be reached from the acquisitions realized on the Moon. Indeed, the precisions reached from observations of calibration sites on Earth (African deserts, Antarctica, clouds, instrumented sites) are about 2-3% for most of the spectral bands in the visible and the near infrared spectra. It is very difficult to further improve this precision down to 1% because each method has its own limitations, generally due to atmospheric disturbances. In this context, the Moon seems to be an ideal calibration site: there is no atmosphere and its surface properties -thus its optical propertiesare perfectly stable. Taking advantage of the high level of agility of PLEIADES, we performed an intensive observation campaign of the Moon in addition to the nominal acquisitions -when the Moon phase angle is about 40°. This intensive observation of the Moon, named POLO for Pleiades Orbital Lunar Observations, consists of a thousand acquisitions covering the phase angle range ±115 deg. The Moon was acquired as frequently as once every orbit, which represents acquisitions every 100 minutes. This paper provides an overview of these lunar experiments and an assessment of the variation of the irradiance of the Moon with phase angle. This paper also discusses a way to improve the phase angle dependence of existing lunar models.

Abstract. The Medium Resolution Imaging Spectrometer (MERIS) launched in February 2002 on-board the EN-VISAT spacecraft is making global observations of top-ofatmosphere (TOA) radiances. Aerosol optical properties are retrieved over land using Look-Up Table (LUT) based algorithm and surface reflectances in the blue and the red spectral regions. We compared instantaneous aerosol optical thicknesses retrieved by MERIS in the blue and the red at locations containing sites within the Aerosol Robotic Network (AERONET). Between 2002 and 2005, a set of 500 MERIS images were used in this study. The result shows that, over land, MERIS aerosol optical thicknesses are well retrieved in the blue and poorly retrieved in the red, leading to an underestimation of the Angstrom coefficient. Correlations are improved by applying a simple criterion to avoid scenes probably contaminated by thin clouds. To investigate the weakness of the MERIS algorithm, ground-based radiometer measurements have been used in order to retrieve new aerosol models, based on their Inherent Optical Properties (IOP). These new aerosol models slightly improve the correlation, but the main problem of the MERIS aerosol product over land can be attributed to the surface reflectance model in the red.