Biases in the Tropical Indian Ocean subsurface temperature variability in a coupled model

  • Rashmi Kakatkar
  • C. GnanaseelanEmail author
  • Jasti S. Chowdary
  • J. S. Deepa
  • Anant Parekh


In this study, the subsurface temperature variability in the Tropical Indian Ocean (TIO) is examined in the Climate Forecast System version 2 (CFSv2) coupled model. The observations and reanalysis show a north–south dominant mode of variability in the TIO subsurface temperature during September–November, the season when the dominant east–west surface mode (Indian Ocean Dipole; IOD) peaks. The nature of the north–south dipole in TIO subsurface temperature is successfully captured by CFSv2. The observations however indicate that this subsurface mode, in general, persists for the next two seasons with stronger signals during December–February, whereas such tenacity is not seen in the model, instead rapid decay of the mode is seen in the model. It is found that the misrepresentation of both equatorial surface wind anomalies and associated Ekman transport as well as the Ekman pumping in the model have close association with the early weakening of the mode in CFSv2. The surface easterlies are generally modulated by the presence of twin anticyclones on both sides of the equator. The model captured these anticyclones with weaker than observed intensity and the northern anticyclone is confined over much smaller region than observed. Association of the subsurface mode with El Niño Southern Oscillation (ENSO) and IOD is further examined in this study. The anomalously prolonged decay phase of El Niño in CFSv2 is found only during the El Niño, IOD co-occurrence years, which was not reported before. This paves way for addressing an important modeling issue which is common in many coupled climate models including CFSv2. The analysis suggests the possible role of coupled air–sea interaction over the TIO on the El Niño cycle in the Pacific. It is also found that the misrepresentation of subsurface variability in CFSv2 during December–February is closely associated with the rapid decay of El Niño forced TIO warming.



We thank the Director, ESSO-IITM and Ministry of Earth Sciences (MoES), Government of India for support. The comments from two anonymous reviewers helped us to improve the manuscript considerably. We thank M. K. Roxy for providing the CFSv2 free run data. ORAS4 data is downloaded from ERA40 and ERA-Interim data are downloaded from ECMWF website. The ARGO gridded data is available from Asia-Pacific data-research center (APDRC) (


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Copyright information

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

Authors and Affiliations

  1. 1.Indian Institute of Tropical MeteorologyPuneIndia
  2. 2.Department of Atmospheric and Space SciencesSavitribai Phule Pune UniversityPuneIndia

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