Improved decadal climate prediction in the North Atlantic using EnOI-assimilated initial condition

• Published in: Science bulletin (Beijing) 2017-08, Vol.62 (16), p.1142-1147
• Main Authors: Wei, Min, Li, Qingquan, Xin, Xiaoge, Zhou, Wei, Han, Zhenyu, Luo, Yong, Zhao, Zongci
• Format: Article
• Language: English
• Subjects: AMO; BCC-CSM; China; climate; climate models; data collection; Decadal prediction; EnOI; ice; Initialization; latitude; prediction; surface water temperature; 初始化过程; 北大西洋; 年代际; 数据同化; 气候系统模式; 气候预测模型; 海洋温度; 海洋表面温度
• ISSN: 2095-9273
• DOI: 10.1016/j.scib.2017.08.012

Decadal prediction experiments of Beijing Climate Center climate system model version 1.1 （BCC- CSM1.1） participated in Coupled Model Intercomparison Project Phase 5 （CMIPS） had poor skill in extratropics of the North Atlantic, the initialization of which was done by relaxing modeled ocean temperature to the Simple Ocean Data Assimilation （SODA） reanalysis data. This study aims to improve the prediction skill of this model by using the assimilation technique in the initialization. New ocean data are firstly generated by assimilating the sea surface temperature （SST） of the Hadley Centre Sea Ice and Sea Surface Temperature （HadlSST） dataset to the ocean model of BCC-CSM1.1 via Ensemble Optimum Interpolation （EnOI）. Then a suite of decadal reforecasts launched annually over the period 1961- 2005 is carried out with simulated ocean temperature restored to the assimilated ocean data. Comparisons between the re-forecasts and previous CMIP5 forecasts show that the re-forecasts are more skillful in mid-to-high latitude SST of the North Atlantic. Improved prediction skill is also found for the Atlantic multi-decadal oscillation （AMO）, which is consistent with the better skill of Atlantic meridional overturning circulation （AMOC） predicted by the re-forecasts. We conclude that the EnOl assimilation generates better ocean data than the SODA reanalysis for initializing decadal climate prediction of BCC-CSM1.1 model.