Coupled surface‐atmosphere reflectance (CSAR) model: 1. Model description and inversion on synthetic data

Abstract

Absorption and scattering processes in the atmosphere affect the transfer of solar radiation along its double path between the Sun, the Earth's surface, and the satellite sensor. These effects must be taken into account if reliable and accurate information on the surface must be retrieved from satellite remote sensing data. One approach consists in characterizing the state of the atmosphere from independent observations and correcting the data with the help of radiation transfer models. This approach requires a detailed and accurate description of the composition of the atmosphere (e.g., aerosol and water vapor profiles in the case of advanced very high resolution radiometer data) at the time of the satellite overpass and requires significant computer resources. An alternative method is to attempt to simultaneously retrieve surface and atmospheric parameters by inverting a coupled surfaceatmosphere model against remote sensing data. This study describes such a coupled model and the results of its inversion against synthetic data, using a nonlinear inversion technique. The results obtained are encouraging in that realistic directional reflectances at the top of the atmosphere can be produced, and the inversion of the model against these synthetic data is capable of estimating surface and atmospheric variables. The accuracy of the retrieval is studied as a function of the amount of noise added to the data. It is shown that some surface or atmospheric parameters are easier to retrieve than others with such a coupled model, and that although it appears to be difficult to accurately and reliably estimate the water vapor amount from channel 2, there is a definite possibility of retrieving the aerosol loading from simulated channel 1 data, if the type of aerosol can be assumed.The scale, intensity, and persistence with which human activities have affected the environment and changed the composition of the atmosphere have raised questions about the sensitivity of the climate system to these perturbations and, in particular, about the likelihood of large-scale and long-term effects [Houghton et al., 1990;Jiiger and Ferguson, 1991]. The widespread concern results from the fact that these changes may be unpredictable and largely undesirable. No consensus has been reached yet in the political arena on the need to take action, or even on the extent and severity of the measures that might be adopted, except that there is general agreement on the need for a much better understanding of the processes involved and for a reduction in the uncertainties associated with current predictions.The most significant worldwide effort in this area is coordinated under aegis of the International Geosphere Biosphere Program (IGBP), also known as the Global

Mapping Surface Broadband Albedo from Satellite Observations: A Review of Literatures on Algorithms and Products

“…The main difference between them is that the joint optimal methods do not use prior BRDF database. Instead, the Rahman-Pinty-Verstraete (RPV) [69] BRDF model and radiative transfer model (RTM) are used for inverting from multi-angular TOA measurements.…”

Simultaneous retrieval of aerosol and surface optical properties from combined airborne- and ground-based direct and diffuse radiometric measurements

“…Surface reflectance in the code is implemented either through the Lambertian (isotropic) approximation or semi-empirical bidirectional reflectance distribution function (BRDF) models such as Coupled Surface-Atmosphere Reflectance (CSAR) model (Rahman et al, 1993a, b) or RossLi BRDF model (Lucht et al, 2000;Wanner et al, 1995Wanner et al, , 1997. For an ocean surface, we use the Cox and Munk model (Cox and Munk, 1954a, b;Nakajima and Tanaka, 1983).…”

“…No specific restrictions on spectral dependence of these parameters are assumed other than spectral smoothness constraints. Since retrieved parameters are analyzed in logarithmic space as stated in section 2.4 and the CSAR model parameter takes negative values (i.e., −0.5≤ ≤0.5; Rahman et al, 1993a), a simple transformation in the form (1 + ) is used. Figure 9 shows spectral bidirectional reflectance factors (BRF) in the solar principal plane at selected wavelengths from the CSAR model inversion for Mongu, Mexico City, Oklahoma, and Barrow.…”

The influence of cloud top variability from radar measurements on 3-D radiative transfer

“…This albedo is also known as "white-sky" albedo (Lucht, 2000). The parameterisation of the BRDF for pasture land is taken from Rahman et al (1993).…”