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The capability of the non-linear Rahman–Pinty–Verstraete (RPV) model to 1) accurately fit a large variety of Bidirectional Reflectance Factor (BRF) fields and 2) return parameter values of interest for land surface applications motivate the development of a computer efficient inversion package. The present paper describes such a package based on the 3 and 4 parameter versions of the RPV model. This software environment implements the adjoint code, generated using automatic differentiation techniques, of the cost function. This cost function itself balances two main contributions reflecting 1) the a priori knowledge on the model parameter values and, 2) BRF uncertainties together with the requirement to minimize the mismatch between the measurements and the RPV simulations. The individual weights of these contributions is specified notably via covariance matrices of the uncertainties in the a priori knowledge on the model parameters and the observations. This package also reports on the probability density functions of the retrieved model parameter values that thus permit the user to evaluate the a posteriori uncertainties on these retrievals. This is achieved by evaluating the Hessian of the cost function at its minimum. Results from a variety of tests are shown in order to document and analyze software performance against complex synthetic BRF fields simulated by radiation transfer models as well as against actual MISR-derived surface BRF products.

New satellite instruments have been delivering a wealth of information regarding land surface albedo. This basic quantity describes what fraction of solar radiation is reflected from the earth’s surface. However, its concept and measurements have some ambiguity resulting from its dependence on the incidence angles of both the direct and diffuse solar radiation. At any time of day, a surface receives direct radiation in the direction of the sun, and diffuse radiation from the various other directions in which it may have been scattered by air molecules, aerosols, and cloud droplets. This contribution proposes a complete description of the distribution of incident radiation with angles, and the implications in terms of surface albedo are given in a mathematical form, which is suitable for climate models that require evaluating surface albedo many times. The different definitions of observed albedos are explained in terms of the coupling between surface and atmospheric scattering properties. The analytical development in this paper relates the various quantities that are retrieved from orbiting platforms to what is needed by an atmospheric model. It provides a physically simple and practical approach to evaluation of land surface albedo values at any condition of sun illumination irrespective of the current range of surface anisotropic conditions and atmospheric aerosol load. The numerical differences between the various definitions of albedo for a set of typical atmospheric and surface scattering conditions are illustrated through numerical computation.

International audience; The community involved in modeling radiation transfer over terrestrial surfaces designed and implemented the first phase of a radiation transfer model intercomparison (RAMI) exercise. This paper discusses the rationale and motivation for this endeavor, presents the intercomparison protocol as well as the evaluation procedures, and describes the principal results. Participants were asked to simulate the transfer of radiation for a variety of precisely defined terrestrial environments and illumination conditions. These were abstractions of typical terrestrial systems and included both homogeneous and heterogeneous scenes. The differences between the results generated by eight different models, including both one-dimensional and three-dimensional approaches, were then documented and analyzed. RAMI proposed a protocol to quantitatively assess the consequences of the model discrepancies with respect to application, such as those motivating the development of physically based inversion procedures. This first phase of model intercomparison has already proved useful in assessing the ability of the modeling community to generate similar radiation fields despite the large panoply of models that were tested. A detailed analysis of the results also permitted to identify apparent“outliers” and their main deficiencies. Future undertakings in this intercomparison framework must be oriented toward an expansion of RAMI into other and more complex geophysical systems as well as the focusing on actual inverse problems.

Canopy radiative transfer (RT) models simulate radiative transfer processes in the solar domain at or near the Earth’s terrestrial surface, i.e., within plant canopies and over bare soil surfaces. Such models are capable of simulating the transmitted, reflected and absorbed radiation fluxes, as well as, the angular distribution of the reflected light above vegetated surfaces in the optical domain of the solar spectrum. This directional aspect is important since the brightness with which a given canopy target appears in Earth Observation data (pixel) depends not only on the structural and spectral properties of the target area but also on the viewing and illumination geometry at the time of measurement. The quantitative interpretation of remote sensing data thus hinges more and more on the exploitation of RT models: In operational contexts they are used to pre-compute Look-Up-Tables of quantities required by the inversion algorithms, whereas, in off-line applications they may be directly inverted against the measurements to yield sets of state variables that describe the properties of the observed target. In both cases, the accuracy and reliability of the solutions to the inverse problems are determined by the performance of the RT model as well as the remote sensing instrument. Reducing the uncertainty of RT models will thus increase the quality of the information derived from remote sensing data (which is of interest to scientists and policy makers), and augment the reliability of RT model studies in forward mode (which is of interest to space agencies when testing new sensor concepts or mission strategies). This understanding has led to a series of model intercomparison projects (MIP) aiming either to document the spread of currently available simulation models, or, else to assess and benchmark the quality of their simulation results, e.g. (Bull. Am. Meteorol. Soc. 73:1962–1970, 1998; J. Geophys. Res. 106:11937–11956, 2001; J. Geophys. Res. 109:D06210, 2004; J. Geophys. Res. 110, 2005; Bull. Am. Meteorol. Soc. 86:1275–1293, 2005; J. Geophys. Res., 2007). Among these MIPs the RAdiation transfer Model Intercomparison (RAMI) activity focuses on the proper representation of the radiative processes occurring in vegetated environments in the optical domain of the solar spectrum.

Multi-temporal analyses of surface properties are desired in order to monitor the various changes occurring at the Earth surface. Remote sensing data collected by various instruments constitute a unique data basis ensuring a systematic regional and global coverage for a range of ground spatial resolutions. The potential synergy in analyzing data gathered by various instruments is, however, hindered by the many differences with respect to the technical performances and capabilities of these instruments. It thus implies that simple but efficient tools and algorithms have to be devised in order to deliver surface products that are consistent in time and space and comparable even if derived Erom different instruments. The products should thus represent the same geophysical quantities, independently from the broad spectral and angular characteristics of the instruments; the relative performances of the sensors are in fact reflected by the uncertainty range associated to the products. The presentation focused on recent developments made in that direction and, more specifically, discussed a physically-based approach to estimate the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) for various instruments. Land cover changes studies will benefit through a construction of regional and global FAPAR time series independent of the lifetime of these specific sensors. The outline. of the methodology was summarized, and the results from an application conducted with SeaWiFS data were presented.