Climate Dynamics

, Volume 52, Issue 5–6, pp 2837–2853 | Cite as

Remote forcing of the northern tropical Atlantic SST anomalies on the western North Pacific anomalous anticyclone

  • Jinqing Zuo
  • Weijing LiEmail author
  • Chenghu SunEmail author
  • Hong-Chang Ren


This study uses both observations and numerical modeling experiments to investigate the lead-lag relationship and the associated physical mechanism of the western North Pacific anomalous anticyclone (WNPAC) with sea surface temperature (SST) anomalies over the northern tropical Atlantic (NTA). The results show that the WNPAC from late spring to the middle of autumn has a significant in-phase relationship with the NTA SST anomalies up to two seasons ahead. This relationship reaches a peak when the NTA SST leads by approximately 1–2 months and is nearly independent of the El Niño-Southern Oscillation variability. Diagnosis based on observations and numerical experiments using the Community Atmospheric Model version 5.3 reveals that the NTA warming favors intensified local convection activity during the spring–autumn seasons, causing enhanced low-level convergence and upper-level divergence (i.e., ascending motion) over the NTA and opposite flow anomalies over the central tropical Pacific. The enhanced subsidence over the central tropical Pacific, in turn, triggers an anomalous low-level anticyclone over the western North Pacific. Moreover, the intensity of the anomalous local convection activity that is associated with the NTA SST is closely related to the seasonal migration of the Atlantic intertropical convergence zone (ITCZ). As the Atlantic ITCZ migrates northward, the NTA SST-induced local convection activity extends northward from a narrow band near the equator during early spring to nearly the entire NTA region during the middle of summer, leading to the strongest remote effect of the NTA SST anomalies on the WNPAC during late summer and early autumn.


SST forcing Northern tropical Atlantic WNP anomalous anticyclone ITCZ 



This work is jointly supported by the National Key Research Program and Development of China (2017YFC1502300), the 973 Program of China (2013CB430203), and the China Meteorological Special Program (GYHY201406018). The authors are grateful to the two anonymous reviewers for their insightful comments, which helped us improve the quality of this paper.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Laboratory for Climate Studies and CMA–NJU Joint Laboratory for Climate Prediction StudiesNational Climate Center, China Meteorological AdministrationBeijingChina
  2. 2.Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science and TechnologyNanjingChina
  3. 3.National Meteorological Information CenterChina Meteorological AdministrationBeijingChina
  4. 4.National Meteorological CenterChina Meteorological AdministrationBeijingChina

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