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Processes controlling the surface temperature signature of the Madden–Julian Oscillation in the thermocline ridge of the Indian Ocean

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Abstract

During boreal winter, there is a prominent maximum of intraseasonal sea-surface temperature (SST) variability associated with the Madden–Julian Oscillation (MJO) along a Thermocline Ridge located in the southwestern Indian Ocean (5°S–10°S, 60°E–90°E; TRIO region). There is an ongoing debate about the relative importance of air-sea heat fluxes and oceanic processes in driving this intraseasonal SST variability. Furthermore, various studies have suggested that interannual variability of the oceanic structure in the TRIO region could modulate the amplitude of the MJO-driven SST response. In this study, we use observations and ocean general circulation model (OGCM) experiments to quantify these two effects over the 1997–2006 period. Observational analysis indicates that Ekman pumping does not contribute significantly (on average) to intraseasonal SST variability. It is, however, difficult to quantify the relative contribution of net heat fluxes and entrainment to SST intraseasonal variability from observations alone. We therefore use a suite of OGCM experiments to isolate the impacts of each process. During 1997–2006, wind stress contributed on average only about 20% of the intraseasonal SST variability (averaged over the TRIO region), while heat fluxes contributed about 70%, with forcing by shortwave radiation (75%) dominating the other flux components (25%). This estimate is consistent with an independent air-sea flux product, which indicates that shortwave radiation contributes 68% of intraseasonal heat flux variability. The time scale of the heat-flux perturbation, in addition to its amplitude, is also important in controlling the intraseasonal SST signature, with longer periods favouring a larger response. There are also strong year-to-year variations in the respective role of heat fluxes and wind stress. Of the five strong cooling events identified in both observations and the model (two in 1999 and one in 2000, 2001 and 2002), intraseasonal-wind stress dominates the SST signature during 2001 and contributes significantly during 2000. Interannual variations of the subsurface thermal structure associated with the Indian Ocean Dipole or El Niño/La Niña events modulate the MJO-driven SST signature only moderately (by up to 30%), mainly by changing the temperature of water entrained into the mixed layer. The primary factor that controls year-to-year changes in the amplitude of TRIO, intraseasonal SST anomalies is hence the characteristics of intraseasonal surface flux perturbations, rather than changes in the underlying oceanic state.

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Notes

  1. We use filtering in Fourier space in this paper. Time series are converted into Fourier coefficients using a Fast Fourier Transform (FFT), and all coefficients corresponding to frequencies that we wish to remove are set to zero before performing an inverse FFT. This approach works efficiently for an infinite time series, but results in spectral leaking of frequencies close to the cutoff frequency. Comparison with other classical filtering approaches with similar cutoff frequencies (digital filtering or a Hanning filter) produced very similar filtered series.

  2. The regression index (30–100 day filtered average TRIO SST) is normalized by its standard deviation, and the regression coefficients are hence expressed in physical units (m s−1 for wind, W m−2 for fluxes and °C for SST). The time series are filtered first, and then only the December-March values are considered to perform the regression.

  3. We remind that the percentage of variability obtained from regression coefficient sum up to 100% when all components of the fluxes are added, but can be negative. Here 68% + 39% = 107% because the sum of the sensible and longwave contributions contribute negatively (−7%) to net heat flux variability.

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Acknowledgments

A. Jayakumar and Praveen Kumar B. thank Council of Scientific and Industrial Research (CSIR), India for Junior/Senior Research Fellowships. Jérôme Vialard and Matthieu Lengaigne are funded by Institut de Recherche pour le Développement (IRD) and made their contributions to this paper while visiting the National Institute of Oceanography (NIO) in Goa, India. This paper is NIO contribution no. 4876, SOEST contribution no. 8058, and IPRC contribution no. 739. Financial support of Space Application Centre (SAC), Ahmedabad, India and Indian National Centre for Ocean Information Services (INCOIS), Hyderabad, India is acknowledged. TMI gridded SST data are produced by Remote Sensing Systems and are available at www.remss.com. The altimeter products were produced by Salto/Duacs and distributed by AVISO with support from CNES. The wind stress data were obtained from CERSAT, at IFREMER, Plouzané (France).

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Authors and Affiliations

  1. Indian Institute of Tropical Meteorology, Pune, India

    A. Jayakumar & C. Gnanaseelan

  2. Laboratoire d’Océanographie Expérimentation et Approches Numériques, LOCEAN, CNRS, UPMC, IRD, Case 100, Université P. et M. Curie, 4, Place Jussieu, 75252, Paris Cedex 05, France

    Jérôme Vialard & M. Lengaigne

  3. National Institute of Oceanography, CSIR, Goa, India

    Jérôme Vialard, M. Lengaigne & B. Praveen Kumar

  4. International Pacific Research Centre, University of Hawaii, Hawaii, USA

    Julian P. McCreary

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  1. A. Jayakumar
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Jayakumar, A., Vialard, J., Lengaigne, M. et al. Processes controlling the surface temperature signature of the Madden–Julian Oscillation in the thermocline ridge of the Indian Ocean. Clim Dyn 37, 2217–2234 (2011). https://doi.org/10.1007/s00382-010-0953-5

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