基于遗传算法的DMS模型标定

B. Qu, A. Gabric, Jiaojiao Xi
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引用次数: 0

摘要

近年来,研究人员认为北冰洋二甲基硫化物(DMS)通量的排放对全球变暖起着重要作用。采用遗传算法(GA)对北冰洋巴伦支海(70-80N, 30-35E) DMS模式参数进行了标定。进行了两步遗传校正。第一步是基于CHL卫星SeaWIFS 8 d数据对最敏感参数进行校准。然后对DMS模型进行另外5个最敏感参数的校准。1998-2002年CHL校正的最佳拟合值为-0.76。结果表明,遗传算法是一种有效的多参数标定工具。模式模拟表明,CHL量的显著年际变化导致北冰洋研究区域观测和模拟的DMS产量和DMS通量的显著年际变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DMS model calibration using Genetic Algorithm
Recent researchers suggested Dimethyl sulphide (DMS) flux emission in Arctic Ocean plays an important role for the global warming. A Genetic Algorithm (GA) method was developed and used in calibrating the DMS model parameters in Barents Sea in Arctic Ocean (70-80N, 30-35E). Two-step GA calibrations were performed. First step was to calibrate the most sensitive parameters based on Chlorophyll_a (CHL) satellite SeaWIFS 8-day data. DMS model was then calibrated for another 5 most sensitive parameters. The best fitness was as good as -0.76 for CHL calibration in 1998-2002. The GA proved an efficient tool in the multiple-parameter calibration task. Model simulations indicate significant inter-annual variation in the CHL amount leading to significant inter-annual variability in the observed and modeled production of DMS and DMS flux in the study region in Arctic Ocean.
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