Automated parameter tuning applied to sea ice in a global climate model
Automated parameter tuning applied to sea ice in a global climate model
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DOI：
10.1007/s00382-017-3581-5
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发表时间：
2017
期刊：
影响因子：
4.6
通讯作者：
L. Roach;S. Tett;M. Mineter;K. Yamazaki;C. Rae
中科院分区：
文献类型：
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作者：
L. Roach;S. Tett;M. Mineter;K. Yamazaki;C. Rae
摘要本研究探讨了气候模式预估中海冰分布的很大一部分是由于模式参数约束较差造成的假设。将新的自动化优化方法应用于全球耦合气候模式（HadCM3）中的历史海冰，以计算将模拟与观测之间的差异减小到模式噪声范围内所需的参数组合。与HadCM3的标准配置相比，优化参数得到的模拟海冰时间序列更符合整个卫星记录（1980年至今）的北极观测，特别是在9月的极小期。与观测到的南极趋势和平均区域海冰分布的差异反映了气候模式中更广泛的结构不确定性。我们还发现优化后的参数对模式气候学没有不利影响。这种简单的方法为参数不确定性对海冰范围趋势传播的贡献提供了证据，并且可以定制用于研究其他气候变量的不确定性。
AbstractThis study investigates the hypothesis that a significant portion of spread in climate model projections of sea ice is due to poorly-constrained model parameters. New automated methods for optimization are applied to historical sea ice in a global coupled climate model (HadCM3) in order to calculate the combination of parameters required to reduce the difference between simulation and observations to within the range of model noise. The optimized parameters result in a simulated sea-ice time series which is more consistent with Arctic observations throughout the satellite record (1980-present), particularly in the September minimum, than the standard configuration of HadCM3. Divergence from observed Antarctic trends and mean regional sea ice distribution reflects broader structural uncertainty in the climate model. We also find that the optimized parameters do not cause adverse effects on the model climatology. This simple approach provides evidence for the contribution of parameter uncertainty to spread in sea ice extent trends and could be customized to investigate uncertainties in other climate variables.