Advances in Atmospheric Sciences

, Volume 35, Issue 4, pp 397–409 | Cite as

Impact of SST Anomaly Events over the Kuroshio–Oyashio Extension on the “Summer Prediction Barrier”

  • Yujie Wu
  • Wansuo DuanEmail author
Original Paper


The “summer prediction barrier” (SPB) of SST anomalies (SSTA) over the Kuroshio–Oyashio Extension (KOE) refers to the phenomenon that prediction errors of KOE-SSTA tend to increase rapidly during boreal summer, resulting in large prediction uncertainties. The fast error growth associated with the SPB occurs in the mature-to-decaying transition phase, which is usually during the August–September–October (ASO) season, of the KOE-SSTA events to be predicted. Thus, the role of KOE-SSTA evolutionary characteristics in the transition phase in inducing the SPB is explored by performing perfect model predictability experiments in a coupled model, indicating that the SSTA events with larger mature-to-decaying transition rates (Category-1) favor a greater possibility of yielding a more significant SPB than those events with smaller transition rates (Category-2). The KOE-SSTA events in Category-1 tend to have more significant anomalous Ekman pumping in their transition phase, resulting in larger prediction errors of vertical oceanic temperature advection associated with the SSTA events. Consequently, Category-1 events possess faster error growth and larger prediction errors. In addition, the anomalous Ekman upwelling (downwelling) in the ASO season also causes SSTA cooling (warming), accelerating the transition rates of warm (cold) KOE-SSTA events. Therefore, the SSTA transition rate and error growth rate are both related with the anomalous Ekman pumping of the SSTA events to be predicted in their transition phase. This may explain why the SSTA events transferring more rapidly from the mature to decaying phase tend to have a greater possibility of yielding a more significant SPB.

Key words

Kuroshio–Oyashio Extension SST summer prediction barrier error growth 

摘 要

黑潮延伸区海表温度距平(KOE-SSTA)的夏季预报障碍(SPB)现象是指KOE-SSTA的预报误差总在北半球夏季快速增长并导致显著的预报不确定性. 与SPB相关的误差快速增长经常发生在KOE-SSTA事件的成熟-衰减转换位相, 即8-9月. 因此, 本文利用耦合模式设计可预报性试验, 对KOE-SSTA在成熟-衰减转换位相的发展特征对SPB的影响作用进行了研究. 结果表明, 具有较大成熟-衰减位相转换速度的KOE-SSTA事件(Category-1)更容易产生显著的SPB现象. 机制研究表明, Category-1的SSTA事件会在转换位相产生显著的异常Ekman抽吸作用, 从而导致显著的与SSTA事件相关的垂直温度平流误差, 最终导致更快的海温误差增长和更大的海温预报误差. 进一步研究发现, 对于KOE-SSTA事件本身, 成熟-衰减位相的转换速度也是由异常Ekman抽吸作用所产生的SSTA变化所决定的. 因此, KOE-SSTA的位相转换速度和误差增长速率均与事件本身的异常Ekman抽吸作用密切相关. 该特征就是具有更快成熟-衰减位相转换速度的KOE-SSTA事件更容易产生显著SPB现象的主要决定因素.


黑潮延伸区 SST 夏季预报障碍 误差增长 


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The authors are grateful for the insightful comments and constructive suggestions provided by the anonymous reviewers. This work was jointly sponsored by the National Natural Science Foundation of China (Grant No. 41376018), the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA11010303), the China Meteorological Administration Special PublicWelfare Research Fund (GYHY201506013), the Project for Development of Key Techniques in Meteorological Forecasting Operation (YBGJXM201705), and the Open Foundation of the LASG/IAP/CAS.


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Copyright information

© Institute of Atmospheric Physics/Chinese Academy of Sciences, and Science Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Laboratory for Climate Studies, National Climate CenterChina Meteorological AdministrationBeijingChina
  2. 2.State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina
  3. 3.CMA-NJU Joint Laboratory for Climate Prediction StudiesNanjing UniversityNanjingChina
  4. 4.University of Chinese Academy of SciencesBeijingChina

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