Ocean Atmosphere General Circulation Models (OAGCM) exhibit significant model biases, e.g., the tropical bias in the Intertropical Convergence Zone cold tongue complex. A significant part of such biases is due to uncertainties in the model parameters. Thus far, however, parameter tuning in OAGCMs remains rudimentary. This collaborative project will develop a novel strategy for systematic parameter optimization in OAGCMs, using an ensemble based data assimilation strategy, focusing on the outstanding tropical bias problem. Building on an existing coupled data assimilation system, an adaptive coupled ensemble Kalman Filter system (AcEnKF) for a simultaneous estimation of model parameter and state, will be developed. Different assimilation techniques to search for an effective method of parameter optimization in OAGCMs will be studied, as also coupled dynamics relevant to parameter optimization in the tropical climate system for both the climatology and climate variability. The work is expected to give the first comprehensive evaluation of the ensemble based strategy for parameter optimization in OAGCMs. The study will also shed light on the mechanism of the coupled dynamics of the tropical climate system and its sensitivity to model parameters. In spite of potential difficulties, this pilot study represents a significant step forward in the improvement of OAGCMs. This activity has significant broader impacts: it will lay a foundation for a systematic improvement of OAGCMs and, more generally, future coupled earth system models.
