Climate Dynamics

, Volume 41, Issue 11–12, pp 2797–2815 | Cite as

Intercomparison between observed and simulated variability in global ocean heat content using empirical mode decomposition, part I: modulated annual cycle

  • Xianyao Chen
  • Yuanling Zhang
  • Min Zhang
  • Ying Feng
  • Zhaohua Wu
  • Fangli Qiao
  • Norden Eh Huang


This study proposes a new more precise and detailed method to examine the performance of IPCC AR4 models in simulation of nonlinear variability of global ocean heat content (OHC) on the annual time scale during 1950–1999. The method is based on the intercomparison of modulated annual cycle (MAC) of OHC and its instantaneous frequency (IF), derived by Empirical Mode Decomposition and Hilbert-Huang Transformation. In addition to indicate the general agreement in gross features globally between models and observation, our results point out the problems both in observation and in modeling. In the well observed Northern Hemisphere, models exhibit extremely good skills to capture nonlinear annual variability of OHC. The simulated MACs are highly correlated with observations (>0.95) and the IF of MACs varies coherently with each other. However, in sparsely observed Southern Hemisphere (SH), even though the simulated MACs highly correlate with observations, the IF shows significant difference. This comparisons show that the models exhibit coherent variability of IF of MACs in SH with each other, but not with observations, revealing the problems in the objective analyzed dataset using sparse observations. In the well observed tropic region, the models lack the coherence with the observations, indicating inadequate physics of the models in the tropical area. These results illustrate that the proposed method can be used routinely to identify problems in both models and in observation of the global ocean as a critical component of global climate change.


Ocean heat content Modulated annual cycle Empirical mode decomposition Instantaneous frequency Instantaneous amplitude CMIP3 



This works was supported by National Science Foundation of China 41176029 and 41106033, Public science and technology research funds projects of ocean 201105019, and Chinese Polar Research Project CHINARE2012-04-04. ZW and NEH were supported by a grant from Federal Highway Administration, DTFH61-08-00028, and grants from NSC, NSC95-2119-M-008-031-MY3, NSC97-2627-B-008-007, and a grant from NCU 965941.

Supplementary material

382_2012_1554_MOESM1_ESM.docx (71 kb)
Supplementary material 1 (DOCX 72 kb)


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Xianyao Chen
    • 1
  • Yuanling Zhang
    • 1
  • Min Zhang
    • 1
  • Ying Feng
    • 1
  • Zhaohua Wu
    • 2
  • Fangli Qiao
    • 1
  • Norden Eh Huang
    • 1
    • 3
  1. 1.Key Laboratory of Data Analysis and Applications, The First Institute of OceanographyState Oceanic AdministrationQingdaoChina
  2. 2.Florida State UniversityTallahasseeUSA
  3. 3.National Central UniversityChung-LiTaiwan, ROC

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