A Simple Sea Surface Albedo Computational Scheme Based on Phytoplankton Size Structure In the Ocean

Abstract:

One of the major sources of uncertainty in climate simulation and prediction lies in the radiation budget of the surface-atmosphere system, in particular, interactions between the atmosphere and the ocean. To describe the energy transport precisely, it is necessary to further study sea surface albedo (SSA), the ratio of upward to downward radiation just above the air-sea interface. Here, we develop a simple reconstructed SSA computational scheme including the contribution from the ocean based on the differences in the inherent optical properties (IOPs) of phytoplankton communities. The proposed scheme identifies different optical properties (absorption and backscattering coefficients) among phytoplankton size classes, namely picophytoplankton, nanophytoplankton, and microphytoplankton. Hierarchical cluster analysis is applied to classify phytoplankton community composition based on pigment measurements. Then, oceanic optical properties can be obtained. Also, sun glint reflectance is expressed as a function of solar zenith angle, wind speed, and wind direction. Whitecaps reflectance is parameterized with respect to pure seawater absorption coefficient. The reconstructed SSA scheme is validated using the Clouds and the Earth's Radiant Energy System (CERES) Ocean Validation Experiment (COVE) data at a regional scale, and the CERES surface fluxes product at a global scale. The reconstructed SSA scheme performs better than other SSA schemes at both local and global scales, which shows that incorporating ocean optics information does improve the accuracy of the SSA calculation. We envisage that the new SSA computational scheme would be a useful oceanic module in coupled atmosphere-ocean radiative transfer modeling in climate simulation and prediction.