Simultaneous parameter optimization of an Arctic sea ice ocean model by a genetic algorithm
Monthly Weather Review(2019)
摘要
AbstractImprovement and optimization of numerical sea ice models are of great relevance for understanding the role of sea ice in the climate system. They are also a prerequisite for meaningful prediction. To improve the simulated sea ice properties, we develop an objective parameter optimization system for a coupled sea ice-ocean model based on a genetic algorithm. To take the interrelation of dynamic and thermodynamic model parameters into account, the system is set up to optimize 15 model parameters simultaneously. The optimization is minimizing a cost function composed of the model-observation misfit of three sea ice quantities (concentration, drift and thickness). The system is applied for a domain covering the entire Arctic and northern North Atlantic Ocean with an optimization window of about two decades (1990 - 2012). It successfully improves the simulated sea ice properties not only during the period of optimization but also in a validation period (2013 - 2016). The similarity of the final values ...
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