In a paper published on the Journal of Climate, Chiodi (University of Washington) and Harrison (PMEL) analyze the value of wind stress information from the TAO/TRITON array, which has been deployed for over two decades.
Researchers examined how TAO/TRITON data can contribute to better understanding of El Niño Southern Oscillation (ENSO) sea surface temperatures. Their results show that TAO/TRITON buoy wind observations can be used on their own to simulate with accurate detail the development of ENSO sea surface temperatures.
Accurate knowledge of the winds across the entire equatorial Pacific basin is critical to our ability to understand the development and growth of sea surface temperatures during ENSO events, which can affect temperature and precipitation in the U.S. and worldwide.
This study was supported by the CPO Ocean Observation and Monitoring Division.
Read the paper: Chiodi, A.M. and D.E. Harrison (2017). Simulating ENSO SSTAs from TAO/TRITON Winds: The Impacts of 20 Years of Buoy Observations in the Pacific Waveguide and Comparison with Reanalysis Products. Journal of Climate, 30, 1041–1059. doi: 10.1175/JCLI-D-15-0865.1.
The fundamental importance of near-equatorial zonal wind stress in the evolution of the tropical Pacific Ocean’s seasonal cycle and El Niño–Southern Oscillation (ENSO) events is well known. It has been two decades since the TAO/TRITON buoy array was deployed, in part to provide accurate surface wind observations across the Pacific waveguide. It is timely to revisit the impact of TAO/TRITON winds on our ability to simulate and thereby understand the evolution of sea surface temperature (SST) in this region. This work shows that forced ocean model simulations of SST anomalies (SSTAs) during the periods with a reasonably high buoy data return rate can reproduce the major elements of SSTA variability during ENSO events using a wind stress field computed from TAO/TRITON observations only. This demonstrates that the buoy array usefully fulfills its waveguide-wind-measurement purpose. Comparison of several reanalysis wind fields commonly used in recent ENSO studies with the TAO/TRITON observations reveals substantial biases in the reanalyses that cause substantial errors in the variability and trends of the reanalysis-forced SST simulations. In particular, the negative trend in ERA-Interim is much larger and the NCEP–NCAR Reanalysis-1 and NCEP–DOE Reanalysis-2 variability much less than seen in the TAO/TRITON wind observations. There are also mean biases. Thus, even with the TAO/TRITON observations available for assimilation into these wind products, there remain oceanically important differences. The reanalyses would be much more useful for ENSO and tropical Pacific climate change study if they would more effectively assimilate the TAO/TRITON observations.
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