Earth Sciences Commons^™

Assessing Optimal Set Of Implemental Physical Parameterization Schemes In A Multi-Physics Land Surface Model Using Genetic Algorithm, S. Hong, X. Yu, S. K. Park, Y.-S. Choi, Boksoon Myoung

Mathematics, Physics, and Computer Science Faculty Articles and Research

Optimization of land surface models has been challenging due to the model complexity and uncertainty. In this study, we performed scheme-based model optimizations by designing a framework for coupling "the micro-genetic algorithm" (micro-GA) and "the Noah land surface model with multiple physics options" (Noah-MP). Micro-GA controls the scheme selections among eight different land surface parameterization categories, each containing 2–4 schemes, in Noah-MP in order to extract the optimal scheme combination that achieves the best skill score. This coupling framework was successfully applied to the optimizations of evapotranspiration and runoff simulations in terms of surface water balance over the Han River …