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张星, 周天军, 张文霞, 等. 2023. 气候系统模式FGOALS-g3模拟的全球季风:版本比较和海气耦合过程影响分析[J]. 大气科学, 47(2): 470−486. doi: 10.3878/j.issn.1006-9895.2112.21099
引用本文: 张星, 周天军, 张文霞, 等. 2023. 气候系统模式FGOALS-g3模拟的全球季风:版本比较和海气耦合过程影响分析[J]. 大气科学, 47(2): 470−486. doi: 10.3878/j.issn.1006-9895.2112.21099
ZHANG Xing, ZHOU Tianjun, ZHANG Wenxia, et al. 2023. Global Monsoon Simulated by FGOALS-g3 Climate System Model: A Comparison with the Previous Version and Influences of Air–Sea Coupling [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 47(2): 470−486. doi: 10.3878/j.issn.1006-9895.2112.21099
Citation: ZHANG Xing, ZHOU Tianjun, ZHANG Wenxia, et al. 2023. Global Monsoon Simulated by FGOALS-g3 Climate System Model: A Comparison with the Previous Version and Influences of Air–Sea Coupling [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 47(2): 470−486. doi: 10.3878/j.issn.1006-9895.2112.21099

气候系统模式FGOALS-g3模拟的全球季风:版本比较和海气耦合过程影响分析

Global Monsoon Simulated by FGOALS-g3 Climate System Model: A Comparison with the Previous Version and Influences of Air–Sea Coupling

  • 摘要: 本文基于观测和再分析资料,采用水汽收支诊断和合成分析方法,对新一代气候系统模式FGOALS-g3模拟的全球季风进行了系统评估,给出其较之前版本FGOALS-g2的优缺点,并通过与其大气分量模式GAMIL结果的比较,讨论了海气耦合过程的影响。结果表明,FGOALS-g3能合理再现全球季风气候态的基本特征,包括年平均、年循环模态、季风降水强度和季风区范围等,但模式低估陆地季风区年平均降水,高估海洋平均降水,模拟的热带地区春秋非对称模态偏强。研究指出FGOALS-g3模拟的陆地季风区范围偏小,这与模式模拟的夏季水汽垂直平流(尤其是热力项)偏小有关。年际变率上,FGOALS-g3能再现El Niño年全球季风降水偏少的整体特征,其不足之处在于部分季风区的降水异常存在一定偏差,例如其模拟的El Niño年西非季风区降水偏多和西南印度洋的偶极子型降水异常,均与观测分布不一致,且模式中西北太平洋季风区降水较观测偏多。这是由于El Niño年,模式中西非高层无弱辐合中心,且海洋性大陆较观测偏暖,对流中心西移。相较于FGOALS-g2,FGOALS-g3对环流、季风降水的年际变率和季风–ENSO关系的模拟有改善。比较耦合和非耦合模拟结果,耦合模式的偏差大多源自大气模式本身,海气耦合过程部分提高了对亚澳季风区和热带印度洋的降水和环流的模拟,但耦合过程引起的海温偏差增强了气候态上印度半岛的干偏差和热带印度洋的湿偏差。

     

    Abstract: Based on the observation and reanalysis data, this study systematically evaluates the global monsoon simulated by the new version of the climate system model FGOALS-g3 by applying moisture budget diagnosis and composite analysis. Moreover, this work analyzes the advantages and disadvantages of the new version when compared with FGOALS-g2. Influences of the air–sea coupling process on the simulated results are discussed by comparing with the corresponding atmospheric component model GAMIL. FGOALS-g3 reasonably reproduces the basic characteristics of the climatology of the global monsoon, including the annual mean precipitation as well as circulation, annual cycle modes, monsoon precipitation intensity, and monsoon region. However, the model underestimates the annual mean precipitation over the land monsoon region, overestimates the annual mean precipitation over the ocean region, and the simulated spring–fall asymmetric mode of the annual cycle is stronger in the tropical monsoon region. The results show that the smaller land monsoon region than the observation in FGOALS-g3 is associated with the weaker vertical moisture advection (especially the thermodynamic term) in summer. For the inter-annual variability, FGOALS-g3 can reproduce the drier pattern of the global monsoon during the El Niño year. However, some biases in precipitation anomalies exist in some monsoon regions. For instance, the precipitation in the west African monsoon region is more than normal, and the precipitation in the southwest Indian Ocean is a dipole anomaly, both of which are inconsistent with the observation. Moreover, the precipitation in the northwest Pacific monsoon region is greater than the observation during the El Niño year. There is no weak convergence center in the upper layer of western Africa in the simulation, and the simulated maritime continent is warmer than observation, resulting in the convective center moving westward during the El Niño year. Compared with FGOALS-g2, FGOALS-g3 improves the simulation of monsoon circulation, inter-annual variability of monsoon precipitation, and monsoon–ENSO relationship. When comparing the coupled and uncoupled simulations, most biases in the coupled model originate from the atmospheric model itself, and the air–sea coupling process partially improves the simulation of precipitation and circulation of the Asian–Australian monsoon region and the tropical Indian Ocean. However, the sea surface temperature bias caused by the coupled process enhances the dry bias of the Indian Peninsula and the wet bias of the tropical Indian Ocean.

     

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