Jiang Tao, Liu Hongbo, Huang Honghui, Yang Jian. Migration patterns and habitat use of the tapertail anchovy Coilia mystus in the Oujiang River Estuary and the Zhujiang River Estuary, China[J]. Acta Oceanologica Sinica, 2019, 38(8): 35-40. doi: 10.1007/s13131-019-1436-0
Citation: Zhenya Song, Hailong Liu, Xingrong Chen. Eastern equatorial Pacific SST seasonal cycle in global climate models: from CMIP5 to CMIP6[J]. Acta Oceanologica Sinica, 2020, 39(7): 50-60. doi: 10.1007/s13131-020-1623-z

Eastern equatorial Pacific SST seasonal cycle in global climate models: from CMIP5 to CMIP6

doi: 10.1007/s13131-020-1623-z
Funds:  The National Key R&D Program of China under contract No. 2016YFA0602200; the Basic Scientific Fund for National Public Research Institute of China under contract No. 2016S03; the grant of Qingdao National Laboratory for Marine Science and Technology under contract Nos 2017ASTCP-ES04 and QNLM20160RP0101; the National Natural Science Foundation of China under contract No. 41776019; the Shanghai Natural Science Foundation under contract No. 16ZR1416200; the China-Korea Cooperation Project on Northwestern Pacific Climate Change and its Prediction.
More Information
  • Corresponding author: E-mail: luckychen@nmefc.cn
  • Received Date: 2019-08-15
  • Accepted Date: 2019-09-27
  • Available Online: 2020-12-28
  • Publish Date: 2020-07-25
  • The sea surface temperature (SST) seasonal cycle in the eastern equatorial Pacific (EEP) plays an important role in the El Niño–Southern Oscillation (ENSO) phenomenon. However, the reasonable simulation of SST seasonal cycle in the EEP is still a challenge for climate models. In this paper, we evaluated the performance of 17 CMIP6 climate models in simulating the seasonal cycle in the EEP and compared them with 43 CMIP5 climate models. In general, only CESM2 and SAM0-UNICON are able to successfully capture the annual mean SST characteristics, and the results showed that CMIP6 models have no fundamental improvement in the model annual mean bias. For the seasonal cycle, 14 out of 17 climate models are able to represent the major characteristics of the observed SST annual evolution. In spring, 12 models capture the 1–2 months leading the eastern equatorial Pacific region 1 (EP1; 5°S–5°N, 110°–85°W) against the eastern equatorial Pacific region 2 (EP2; 5°S–5°N, 140°–110°W). In autumn, only two models, GISS-E2-G and SAM0-UNICON, correctly show that the EP1 and EP2 SSTs vary in phase. For the CMIP6 MME SST simulation in EP1, both the cold bias along the equator in the warm phase and the warm bias in the cold phase lead to a weaker annual SST cycle in the CGCMs, which is similar to the CMIP5 results. However, both the seasonal cold bias and warm bias are considerably decreased for CMIP6, which leads the annual SST cycle to more closely reflect the observation. For the CMIP6 MME SST simulation in EP2, the amplitude is similar to the observed value due to the quasi-constant cold bias throughout the year, although the cold bias is clearly improved after August compared with CMIP5 models. Overall, although SAM0-UNICON successfully captured the seasonal cycle characteristics in the EEP and the improvement from CMIP5 to CMIP6 in simulating EEP SST is clear, the fundamental climate models simulated biases still exist.
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