National Oceanic and
Atmospheric Administration
United States Department of Commerce


 

FY 2012

TropFlux: Air-sea fluxes for the global tropical oceans – Description and evaluation

Praveen Kumar, B., J. Vialard, M. Lengaigne, V.S.N. Murty, and M.J. McPhaden

Climate Dynam., 38(7–8), 1521–1543, doi: 10.1007/s00382-011-1115-0 (2012)


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.



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