Radiative transfer in atmosphere-ocean and atmosphere-mountain systems: Application and parameterization

This dissertation documents the development of a computationally efficient coupled atmosphere--ocean radiative transfer model and parameterization of the mountain effect on surface fluxes for the application to climate models. A coupled atmosphere--ocean radiative transfer model based on the analytic four--stream approximation has been developed. To take into account the reflection and transmission of the wind-blown air--water interface, a Monte Carlo method has been employed to simulate the traveling of photons and to evaluate the reflectance and transmittance of the sea surface. For the ocean part, existing bio-optical models, which correlate the concentration of chlorophyll and the absorption and scattering coefficients of phytoplankton and other matters, have been integrated into this coupled model. Comparing to the values computed by more discrete streams and observation data illustrates that the relative accuracies of the surface albedo and total transmission in the ocean determined from the present model are generally within 10%.;We developed a 3D Monte Carlo photon tracing program for the transfer of radiation in inhomogeneous and irregular terrain to calculate broadband solar and thermal infrared fluxes. An area of 100x100 km2 in the Tibetan Plateau is selected for this study. We showed that anomalies of surface solar fluxes with reference to a flat surface can be as large as 300 W/m2, depending on time of day, mountain configuration, and albedo. Surface temperature is the dominating factor in determining anomalies of the surface infrared flux distribution relative to a flat surface with values as high as 70 W/m2. The average surface solar flux over regional domains can deviate from the smoothed surface conventionally assumed in climate models and GCMs by 50-120 W/m2.;On the basis of the results from Monte Carlo simulation, we developed a parameterization of surface solar fluxes as a function of topographic parameters including the elevation, sky view factor, and terrain configuration factor. Analysis using multiple linear regression shows that 95%, 50%, and 72% of the variations of the direct, diffuse, and reflected-associated fluxes, respectively, can be explained by regression models.