The Ocean–Land–Atmosphere Model: Optimization and Evaluation of Simulated Radiative Fluxes and Precipitation

Abstract

Abstract This work continues the presentation and evaluation of the Ocean–Land–Atmosphere Model (OLAM), focusing on the model’s ability to represent radiation and precipitation. OLAM is a new, state-of-the-art earth system model, capable of user-specified grid resolution and local mesh refinement. An objective optimization of the microphysics parameterization is carried out. Data products from the Clouds and the Earth’s Radiant Energy System (CERES) and the Global Precipitation Climatology Project (GPCP) are used to construct a maximum likelihood function, and thousands of simulations using different values for key parameters are carried out. Shortwave fluxes are found to be highly sensitive to both the density of cloud droplets and the assumed shape of the cloud droplet diameter distribution function. Because there is considerable uncertainty in which values for these parameters to use in climate models, they are targeted as the tunable parameters of the objective optimization procedure, which identified high-likelihood volumes of parameter space as well as parameter uncertainties and covariances. Once optimized, the model closely matches observed large-scale radiative fluxes and precipitation. The impact of model resolution is also tested. At finer characteristic length scales (CLS), smaller-scale features such as the ITCZ are better resolved. It is also found that the Amazon was much better simulated at 100- than 200-km CLS. Furthermore, a simulation using OLAM’s variable resolution functionality to cover South America with 100-km CLS and the rest of the world with 200-km CLS generates a precipitation pattern in the Amazon similar to the global 100-km CLS run.