Photon transport in three-dimensional structures treated by random walk techniques: Monte Carlo benchmark of ocean colour simulations Original Research Article

The analysis of light-rays penetrating transparent media like air and water constitutes a pertinent problem in climatic research and in the development of algorithms for the retrieval of bio-geo-chemical parameters of suspended matter and dissolved pollutants from remotely sensed ocean colour data. On the basis of the neutron transport code TIMOC a visible and near-infrared photon transport code, called PHO-TRAN, has been developed and tested both against a theoretical benchmark of models and on real data. The photon transport allows for reflection, refraction, absorption and all relevant light-scattering models, such as elastic scattering by molecules and strongly forward scattering processes by particulates, in quite general three-dimensional geometries. The scores are flux, radiance, irradiance, averaged over regions or surfaces as well as point detectors. In some cases it is also possible to solve the adjoint problem, as for example in the case of strongly collimated light sensors with extended sources. Adjoint problems – as encountered when complex geometry structures are to be considered in the vicinity of a detector – are solved to evaluate the effects of sensor shadowing and self-shadowing, in order to provide vicarious calibration information for operational satellite remote sensors. While the features listed above, are not all unique, PHO-TRAN offers also the possibility to sample first-order derivatives of almost all responses with respect to certain input parameters, like material densities and characteristic constants used in scattering models. The knowledge of derivatives, which can be determined with very little supplementary computing effort, provides valuable additional information which provides sensitivity profiles and allows for multivariate perturbation estimates, uncertainty analysis and data adjustment. This paper describes mainly the benchmarking of the developed Monte Carlo procedures.