A new initiative dedicated to the benchmarking of coupled surface-atmosphere
RAMI4ATM is a new initiative dedicated to the benchmarking of coupled surface-atmosphere radiative transfer models. RAMI4ATM will thus extend the RAdiation transfer Model Intercomparison (RAMI) to the simulation of satellite observations. Compared to current benchmarks, the major difference is that RAMI4ATM will account for atmospheric radiative effects occurring between the surface and the simulated signal reaching a given spaceborne or airborne radiometer. Models participating in RAMI4ATM should support the simulation radiative processes at the surface, in the atmosphere and account for the radiative coupling between the two.
Over the past decades, many radiative transfer models have been developed and are widely used for e.g. vicarious calibration and lookup table generation for atmospheric correction. Many of these models ship atmospheric property databases. Subcomponents of these models have been extensively tested in ideal conditions but so far, no initiative similar to RAMI has been undertaken to systematically compare models when they are used to simulate actual remote sensing observations. The uncertainties of these models has not been clearly assessed in realistic usage conditions.
Similarly to RAMI-1, the primary goal of RAMI4ATM will be to document the variability between coupled surface-atmosphere models when run under well-controlled, but realistic, conditions. Surface properties will be defined by the simple homogeneous scenes as defined within RAMI-V.
This new phase is oriented toward the support of calibration and validation activities relying on the use of radiative transfer models for the simulation of remote sensing observations in the visible and, near-infrared spectral regions. It is therefore primarily directed at users of models used for calibration and validation activities. Participation from model developers is however also welcome.
RAMI4ATM is expected to be initiated before the end of this year. The expected outcome of this exercise is as follows: