Climate Dynamics

, Volume 38, Issue 7–8, pp 1521–1543 | Cite as

TropFlux: air-sea fluxes for the global tropical oceans—description and evaluation

  • B. Praveen Kumar
  • J. Vialard
  • M. Lengaigne
  • V. S. N. Murty
  • M. J. McPhaden
Article

Abstract

In this paper, we evaluate several timely, daily air-sea heat flux products (NCEP, NCEP2, ERA-Interim and OAFlux/ISCCP) against observations and present the newly developed TropFlux product. This new product uses bias-corrected ERA-interim and ISCCP data as input parameters to compute air-sea fluxes from the COARE v3.0 algorithm. Wind speed is corrected for mesoscale gustiness. Surface net shortwave radiation is based on corrected ISCCP data. We extend the shortwave radiation time series by using “near real-time” SWR estimated from outgoing longwave radiation. All products reproduce consistent intraseasonal surface net heat flux variations associated with the Madden-Julian Oscillation in the Indian Ocean, but display more disparate interannual heat flux variations associated with El Niño in the eastern Pacific. They also exhibit marked differences in mean values and seasonal cycle. Comparison with global tropical moored buoy array data, I-COADS and fully independent mooring data sets shows that the two NCEP products display lowest correlation to mooring turbulent fluxes and significant biases. ERA-interim data captures well temporal variability, but with significant biases. OAFlux and TropFlux perform best. All products have issues in reproducing observed longwave radiation. Shortwave flux is much better captured by ISCCP data than by any of the re-analyses. Our “near real-time” shortwave radiation performs better than most re-analyses, but tends to underestimate variability over the cold tongues of the Atlantic and Pacific. Compared to independent mooring data, NCEP and NCEP2 net heat fluxes display ~0.78 correlation and >65 W m−2 rms-difference, ERA-I performs better (~0.86 correlation and ~48 W m−2) while OAFlux and TropFlux perform best (~0.9 correlation and ~43 W m−2). TropFlux hence provides a useful option for studying flux variability associated with ocean–atmosphere interactions, oceanic heat budgets and climate fluctuations in the tropics.

Notes

Acknowledgments

The development of TropFlux product is the result of a joint research collaboration between National Institute of Oceanography (Goa, India) and Institute Pierre et Simon Laplace (Paris, France). BPK and VSNM thanks Director, National Institute of Oceanography, India, for his keen interest in this study. The lead author is supported by a Senior Research Fellowship (SRF) from Council of Scientific and Industrial Research (CSIR, Govt. of India) and a 1-year research grant from Institut de Recherche pour le Développement (IRD, France) and did part of this work whilst at Laboratoire d’Océanographie Expérimentation et Approches Numériques (LOCEAN, Paris). JV and ML are funded by Institut de Recherche pour le Développement (IRD) and did this work while visiting National Institute of Oceanography (NIO, India). We sincerely thank the providers of NCEP, NCEP2 re-analyses and OLR data (NOAA/OAR/ESRL PSD, Boulder, Colorado, USA), ERA-Interim (European Centre for Medium Range Weather Forecasting), OAFlux (Woods Hole Oceanographic Institution), ISCCP (International Satellite Cloud Climatology Project), TMI SST (Remote Sensing Systems), Qscat winds (CERSAT-IFREMER), ICOADS (NOAA, USA), TAO-PIRATA-RAMA (PMEL-NOAA) and the OceanSites initiative for various data sets. Meghan Cronin and Dai McClurg (PMEL) provided TPR climatological wind gustiness data. Discussions with Jean-Luc Redelsperger on wind gustiness parameterization provided useful inputs. Constructive comments by two anonymous reviewers greatly helped to improve an earlier version of this manuscript. This is NIO contribution number 4981 and PMEL contribution number 3628.

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Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • B. Praveen Kumar
    • 1
  • J. Vialard
    • 1
    • 2
  • M. Lengaigne
    • 1
    • 2
  • V. S. N. Murty
    • 3
  • M. J. McPhaden
    • 4
  1. 1.Physical Oceanography DivisionNational Institute of Oceanography, Council of Scientific and Industrial Research (CSIR)Dona PaulaIndia
  2. 2.Laboratoire d’Océanographie Expérimentation et Approches NumériquesCNRS, UPMC, IRDParisFrance
  3. 3.National Institute of Oceanography Regional Centre, Council of Scientific and Industrial Research (CSIR)VisakhapatnamIndia
  4. 4.NOAA/Pacific Marine Research LaboratorySeattleUSA

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