International audienceThe collective representation within global models of aerosol, cloud, precipitation, and their radiative properties remains unsatisfactory. They constitute the largest source of uncertainty in predictions of climatic change and hamper the ability of numerical weather prediction models to forecast high-impact weather events. The joint ESA-JAXA EarthCARE satellite mission, scheduled for launch in 2017, will help to resolve these weaknesses by providing global profiles of cloud, aerosol, precipitation, and associated radiative properties inferred from a combination of measurements made by its collocated active and passive sensors. EarthCARE will improve our understanding of cloud and aerosol processes by extending the invaluable dataset acquired by the A-Train satellites CloudSat, CALIPSO, and Aqua. Specifically, EarthCARE's Cloud Profling Radar, with 7 dB more sensitivity than CloudSat, will detect more thin clouds and its Doppler capability will provide novel information on convection, precipitating ice particle and raindrop fall speeds. EarthCARE's 355-nm High Spectral Resolution Lidar will measure directly and accurately cloud and aerosol extinction and optical depth. Combining this with backscatter and polarization information should lead to an unprecedented ability to identify aerosol type. The Multi-Spectral Imager will provide a context for, and the ability to construct the cloud and aerosol distribution in 3D domains around the narrow 2D retrieved cross-section. The consistency of the retrievals will be assessed to within a target of ±10 W m⁻² on the (10 km²) scale by comparing the multi-view Broad-Band Radiometer observations to the top-of-atmosphere fluxes estimated by 3D radiative transfer models acting on retrieved 3D domains

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The forthcoming broadband radiometer (BBR) on board the Earth Clouds, Aerosols, and Radiation Explorer (EarthCARE) will provide quasi-instantaneous top-of-atmosphere radiance measurements for three different viewing angles. The role of BBR data will be to constrain the vertical radiative flux divergence profiles derived from EarthCARE measurements. Thus, the development of an instantaneous radiance-toflux conversion procedure is of paramount importance. This paper studies the scientific basis for determining fluxes from radiances measured by the BBR instrument. This is an attempt to evaluate a possible solution and assess its potential advantages and drawbacks. The approach considered has been to construct theoretical angular distribution models (ADMs) based on the multiangular pointing feature of this instrument. This configuration provides extra information on the anisotropy of the observed radiance field, which can be employed to construct accurate inversion schemes. The proposal relies on radiative transfer calculations performed with a Monte Carlo algorithm. Considering the intrinsic difficulty associated with addressing the range of atmospheric conditions needed to determine reliable ADMs, a synthetic database has been thoroughly constructed that considers a diverse range of surface, atmospheric, and cloud conditions that are conditioned to the EarthCARE orbit and physical constraints. Three inversion methodologies have been specifically designed for the BBR flux retrieval algorithm. In particular, an optimized classical inversion procedure in which the definition of an effective radiance leads to derive fluxes with averaged errors up to 1.2 and 5.2 W m 22 for shortwave clear and cloudy sky and 1.5 W m 22 for longwave radiation scenes and a linear combination of the three instantaneous radiances from which averaged errors up to 0.4 and 2.7 W m 22 for shortwave clear and cloudy sky and 0.5 W m 22 for longwave scenes can be obtained.

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Included in the Earth, Clouds, Aerosols, and Radiation Explorer (EarthCARE) satellite's array of instruments is a multi-view broad-band radiometer (BBR). BBR data will facilitate a radiative closure assessment of cloud and aerosol properties inferred from data gathered by EarthCARE's other passive and active sensors. The closure assessment will consist, in part, of comparisons between BBR radiances and radiances computed by three-dimensional (3D) radiative transfer models (RTM) that act on narrow 3D domains that derive from, and include, the retrieved cross-section of cloud and aerosol properties. Assessment domains D will be ∼100 km 2 . Following a brief outline of the closure experiment, a method is proposed for estimating the likelihood of BBR radiances providing a meaningful closure assessment of cloud and aerosol properties in D. The method capitalizes on the ability of Monte Carlo RTMs to compute contributions to radiances from any constituent in any given D. While this methodology introduces some circularity into the closure test, it might, nevertheless, be tolerable, given that the method's purpose is simply to identify, and thus avoid, assessments that are likely to be fruitless or misleading. A 3000 km long stretch of A-Train satellite data was used in this initial demonstration of the proposed methodology. Only results for solar radiation are shown. All radiative quantities used here were computed by a 3D Monte Carlo RTM. A control simulation provided proxy BBR measurements. Random 'errors' were introduced into the A-Train field to produce experimental fields that roughly mimic retrievals. Experimental and control radiances were compared in mock-closure assessments. Arbitrarily assuming that a fruitful assessment requires ∼75% of a BBR radiance to result from cloud and aerosol scattering events inside D, ∼70% of the (11 km) 2 domains were flagged as reliably testable for this example.