The climate variability in global land precipitation in FGOALS-f3-L: A comparison between GMMIP and historical simulations

ABSTRACT

The climate variability in global land precipitation is important for the global hydrological cycle. Based on the Coupled Model Intercomparison Project Phase 6 (CMIP6) historical experiments and the Global Monsoons Model Intercomparison Project (GMMIP) Tier-1 experiments, the spatial-temporal characteristics of global and regional land precipitation long-term climate changes in CAS FGOALS-f3-L are evaluated in this study. By comparing these two kinds of experiments, the precipitation biases related to the SSTs are also discussed. The results show that the two experiments could capture the precipitation trend and amplitude to a certain degree compared with observations. The GMMIP simulations show a higher skill than the historical runs verified by correlation coefficients partly because the observed monthly mean SST was prescribed. For the Northern Hemisphere, GMMIP can reproduce the trend and variability in global precipitation, while historical simulations cannot reproduce the trend and variability. However, both experiments fail to simulate the amplitude of the southern hemisphere summer precipitation anomalies. Ensemble empirical mode decomposition (EEMD) was applied to compare the simulated precipitation on different time scales. The sea surface temperature anomaly (SSTA) bias, especially the La Niña-type SSTA, is the dominant source of the model bias for simulating interannual precipitation anomalies. The authors also emphasize that the response of precipitation anomalies to the ENSO effect varies regionally. This study highlights the importance of the multiannual variability in SSTAs in global and hemispheric precipitation simulations. The ways to improve the simulation of global precipitation for CAS FGOALS-f3-L are also discussed.

Graphical abstract

摘要

全球降水对人们生产生活和经济发展都至关重要。因此, 评估模式对降水的模拟能力至关重要。近期大气物理研究所发布了两套CMIP6试验数据, 结合GPCC降水资料, 本文评估了两组试验对1900–2014年全球陆地降水以及各半球夏季降水模拟性能。结果表明, 无论是年际尺度还是长期趋势的模拟, GMMIP试验均表现出更好的模拟性能。考虑到两组试验设计的角度和海温对年际降水的重要影响, 本文探讨了全球海温异常尤其是ENSO事件对全球降水和各半球夏季降水的重要性。结果表明, 赤道太平洋地区海温对降水模拟影响显著, 其影响主要集中在中低纬地区。这对降水模拟的改进有很大帮助。

KEYWORDS:

• CMIP6
• GMMIP
• global precipitation simulation
• climate variability
• monsoon simulation

关键词:

• CMIP6
• GMMIP
• 全球降水模拟
• 气候变率
• 季风模拟

Acknowledgments

We would like to thank the two anonymous reviewers for their suggestions, which have improved the manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The research presented in this paper was jointly funded by the National Key Research and Development Program of China [Grant No. 2017YFA0604004] and the National Natural Science Foundation of China [Grant Nos. 91737306, 41530426, 91837101, 91937302, and 41606032].