科学家通过数值模拟实验进一步揭示影响季风行为的驱动因子(5)

• AMIP simulation datasets produced by CAS FGOALS-f3-L covering 1979 to 2014 are described.

• The dataset contains three ensemble members with different initial states by the time lag method.

• The model outputs contain a total of 37 variables and include the three-hourly mean, six-hourly transient, daily and monthly mean datasets.

Data availability statement The data that support the findings of this study are available from .

Disclosure statement No potential conflict of interest was reported by the authors.

本文介绍了中国科学院大气物理研究所开发的CAS FGOALS-f3-L 气候系统模式参加第六次国际耦合模式比较计划 (CMIP6)的DECK试验(Diagnostic, Evaluation and Characterization of Klima common experiments)中全球大气环流模式(AMIP)模拟数据, 其中包括CAS FGOALS-f3-L模式的动力框架, 物理过程简介以及模式试验设计, 数据信息以及初步评估结果. 模式采用时间滞后法产生不同初始场的三个集合成员, 并提供1979–2014年的模拟结果. 模式输出包括37个变量, 涉及3小时平均, 6小时瞬时, 日平均和月平均数据. 本文还评估了模式在不同时间尺度上的基本模拟性能. 结果表明CAS FGOALS-f3-L模式能够很好的模拟出大尺度全球大气环流和降水的基本特征, 能够很好的模拟出降水和850hPa风的MJO传播特征, 以及台风的活动和极端降水的发生频次特征. 该数据集贡献于CMIP计划在模式发展评估上的连续性.

CMIP6AMIPFGOALS-f3-LMJO台风极端降水

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The research presented in this paper was jointly funded by the National Key Research and development Program of China (Grant No. 2017YFA0604004), the National Natural Science Foundation of China (Grant Nos. 91737306, U1811464, 41530426, 91837101, 41730963, and 91637312).

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