| 摘要: |
| 北太平洋海域是反映全球气候变化的敏感区域，特别是对紧邻西北太平洋的东亚地区的天气与气候变化有重大影响。本文选取第六次国际耦合模式比较计划(CMIP6)中的28个模型结果，并计算得到其多模式集合平均(MME)模型结果，基于多种评估指标，并与再分析资料ERSST v5比较，评价了29个模型对北太平洋海表温度(Sea Surface Temperature，SST)的季节、年际和年代际变化的模拟能力，利用综合评分标准方法(MR)量化了模型结果的整体性能。结果表明，MME能够准确地模拟全年和四季变化，模型的偏差大部分集中在1-3月和7-9月，FGOALS-g3与NorCPM1的偏差高于其他模型。北太平洋SST在1915-2014年有明显的上升趋势，MME结果为0.055℃/10a,与再分析数据(0.059℃/10a)结果相近。两者相关系数为0.99、相对偏差为0.06、相对均方根误差为0.25。通过泰勒图的综合评估，不同的模型对同一的海域表现不同，对区域的模型选择不可随机。MR方法评价结果表明，在有9个模型评分为A级，其中MME为A级中第三，证明采用了模型集合平均的方法有效减少了单个模型系统误差。 |
| 关键词: CMIP6 北太平洋 气象要素 模式评估 |
| DOI：10.11693/hyhz20240700164 |
| 分类号: |
| 基金项目:崂山实验室科技创新项目（LSKJ202202104） |
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| ASSESSMENT OF CMIP6 MODELS IN REPRODUCING THE OBSERVED SEA SURFACE TEMPERATURE IN THE NORTH PACIFIC OCEAN |
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WangShuaiqi, SunQun, GuoWenning
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College of Marine and Environmental Sciences,Tianjin University of Science and Technology
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| Abstract: |
| The North Pacific Ocean is a sensitive region reflecting global climate change, especially having a significant impact on weather and climate change in East Asia, which is immediately adjacent to the Northwest Pacific Ocean. In this paper, we selected 28 model results from the Sixth International Coupled Model Intercomparison Programme (CMIP6) and computed their multi-model ensemble averaging (MME) model results, and evaluated the seasonal, inter-annual and inter-decadal variability of the North Pacific sea surface temperature (SST) of 29 models based on a variety of assessment metrics and in comparison with reanalysed information ERSST v5, using the integrated scoring criteria method. SST in the North Pacific Ocean (NP), and the overall performance of the model results was quantified using a combined scoring criteria approach (MR). The results show that MME is able to accurately simulate year-round and seasonal variations, with most of the model biases concentrated in January-March and July-September, and the biases of FGOALS-g3 and NorCPM1 are higher than those of other models. The North Pacific SST has a clear upward trend in 1915-2014, with an MME result of 0.055°C/10a, which is similar to the result of the reanalysis data (0.059°C/10a). The correlation coefficient of the two is 0.99, the relative deviation is 0.06, and the relative root-mean-square error is 0.25. Through the comprehensive evaluation of the Taylor diagrams, different models perform differently for the same sea area, and the model selection of the region cannot be random.The evaluation results of the MR method show that there are nine models scoring A level, of which the MME is the third one in the A level, which proves that the model ensemble averaging method is used to effectively reduce the individual model systematic errors. |
| Key words: CMIP6 North Pacific Ocean meteorological elements model assessment |