Abstract
This paper describes the datasets from the Scenario Model Intercomparison Project (ScenarioMIP) simulation experiments run with the Chinese Academy of Sciences Flexible Global Ocean-Atmosphere-Land System Model, GridPoint version 3 (CAS FGOALS-g3). FGOALS-g3 is driven by eight shared socioeconomic pathways (SSPs) with different sets of future emission, concentration, and land-use scenarios. All Tier 1 and 2 experiments were carried out and were initialized using historical runs. A branch run method was used for the ensemble simulations. Model outputs were three-hourly, six-hourly, daily, and/or monthly mean values for the primary variables of the four component models. An evaluation and analysis of the simulations is also presented. The present results are expected to aid research into future climate change and socio-economic development.
摘要
本文介绍了中国科学院大气物理研究所研发的CAS FGOALS-g3模式在第六次国际耦合模式比较计划(CMIP6)的情景模式比较计划(ScenarioMIP)试验数据集。FGOALS-g3模式由8个共享社会经济路径(SSPs)驱动,它们分别具有不同的未来温室气体排放、浓度和土地利用情景。通过使用历史试验模拟结果进行初始化,模式完成了所有的第1层和第2层试验。模式输出数据包含四个分量模式的3小时、6小时、每日和/或每月平均的主要变量。文章对各组试验的模拟结果进行了初步的评估和分析。本文所涉及的试验结果将有助于对未来气候变化评估以及为社会经济发展制定相关政策提供数据支撑。
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This study was supported by the National Key Research and Development Program of China (Grant Nos. 2017YFA0603903, 2017YFA0603901, and 2017YFA060 3902), the Strategic Priority Research Program of Chinese Academy of Sciences (Grant No. XDB42010404) and the National Basic Research (973) Program of China (Grant Nos. 2015CB954102).
Data availability statement and sharing policy
The data that support the findings of this study are available at https://esgfnode.llnl.gov/projects/cmip6/. The citation for ScenarioMIP is “CAS FGOALS-g3 model output prepared for CMIP6 ScenarioMIP. Earth System Grid Federation. Doi: https://doi.org/10.22033/ESGF/CMIP6.2056”. Users are encouraged to download and share the data mentioned in this paper. All the datasets are free.
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Pu, Y., Liu, H., Yan, R. et al. CAS FGOALS-g3 Model Datasets for the CMIP6 Scenario Model Intercomparison Project (ScenarioMIP). Adv. Atmos. Sci. 37, 1081–1092 (2020). https://doi.org/10.1007/s00376-020-2032-0
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DOI: https://doi.org/10.1007/s00376-020-2032-0