A fast radiative transfer model for optical remote sensing image simulation with multilayer clouds

Multi-layer cloud systems, as the dominant configuration of global cloud distributions, significantly influence cloud parameter retrieval, atmospheric radiative budgets, and climate model simulations through their radiative transfer characteristics. To overcome limitations in current radiative transfer models particularly simulation inaccuracies and computational demands arising from single-layer cloud assumptions this study introduces a novel rapid radiative transfer modeling approach for multi-layer clouds. By systematically decoupling radiative interactions between the atmosphere and heterogeneous boundary layers and integrating the successive order of radiative decomposition principle with the doubling-adding algorithm, we developed a computationally efficient radiative transfer model tailored to the infrared spectrum (2-14 μm). Theoretical validation confirms the model's capability to resolve radiative coupling effects between multi-layer clouds, exhibiting a 25.63% average discrepancy between simulated results and MODIS L1B observations. This work offers a robust technical framework for advancing the assessment of cloud radiative forcing and refining cloud parameterization schemes in climate models.