Evaluation of tropical Pacific observing systems using NCEP and GFDL ocean data assimilation systems
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The TAO/TRITON array is the cornerstone of the tropical Pacific and ENSO observing system. Motivated by the recent rapid decline of the TAO/TRITON array, the potential utility of TAO/TRITON was assessed for ENSO monitoring and prediction. The analysis focused on the period when observations from Argo floats were also available. We coordinated observing system experiments (OSEs) using the global ocean data assimilation system (GODAS) from the National Centers for Environmental Prediction and the ensemble coupled data assimilation (ECDA) from the Geophysical Fluid Dynamics Laboratory for the period 2004–2011. Four OSE simulations were conducted with inclusion of different subsets of in situ profiles: all profiles (XBT, moorings, Argo), all except the moorings, all except the Argo and no profiles. For evaluation of the OSE simulations, we examined the mean bias, standard deviation difference, root-mean-square difference (RMSD) and anomaly correlation against observations and objective analyses. Without assimilation of in situ observations, both GODAS and ECDA had large mean biases and RMSD in all variables. Assimilation of all in situ data significantly reduced mean biases and RMSD in all variables except zonal current at the equator. For GODAS, the mooring data is critical in constraining temperature in the eastern and northwestern tropical Pacific, while for ECDA both the mooring and Argo data is needed in constraining temperature in the western tropical Pacific. The Argo data is critical in constraining temperature in off-equatorial regions for both GODAS and ECDA. For constraining salinity, sea surface height and surface current analysis, the influence of Argo data was more pronounced. In addition, the salinity data from the TRITON buoys played an important role in constraining salinity in the western Pacific. GODAS was more sensitive to withholding Argo data in off-equatorial regions than ECDA because it relied on local observations to correct model biases and there were few XBT profiles in those regions. The results suggest that multiple ocean data assimilation systems should be used to assess sensitivity of ocean analyses to changes in the distribution of ocean observations to get more robust results that can guide the design of future tropical Pacific observing systems.
KeywordsTropical Pacific observing system Ocean data assimilation systems Observing system experiment ENSO monitoring and ENSO forecast Argo data TAo/TRITON data
We would like to thank support from the NOAA Climate Observation Division of Climate Program Office for this study. We also thank two anonymous reviewers, Dr. Zeng-Zhen Hu and Dr. Jieshun Zhu for their constructive comments and suggestions on this paper. The scientific results and conclusions, as well as any view or opinions expressed herein, are those of the author(s) and do not necessarily reflect the views of NWS, NOAA, or the Department of Commerce.
- Behringer DW, Xue Y (2004) Evaluation of the global ocean data assimilation system at NCEP. In: The Pacific Ocean. Eighth symposium on integrated observing and assimilation system for atmosphere, ocean, and land surface, AMS 84th annual meeting, Washington State Convention and Trade Center, Seattle, pp 11–15, 10 Jan 2004Google Scholar
- Behringer DW (2007) The global ocean data assimilation system at NCEP. In: 11th symposium on integrated observing and assimilation systems for atmosphere, oceans, and land surface, AMS 87th annual meetingGoogle Scholar
- Boyer TP et al (2009) World ocean database 2009, chapter 1: introduction. In: Levitus S (ed) NOAA Atlas NESDIS 66. US Government Printing Office, Washington, DC, 216 ppGoogle Scholar
- Conkright ME et al (1999) World ocean database 1998, documentation and quality control version 2.0. National Oceanographic Data Center internal report 14. National Oceanographic Data Center, Silver SpringGoogle Scholar
- Fujii Y, Kamachi M, Nakaegawa T, Yasuda T, Yamanaka G, Toyoda T, Ando K, Matsumoto S (2011) Assimilating ocean observation data for ENSO monitoring and forecasting. In: Hannachi A (ed) Climate variability. INTECH, Rijeka. ISBN: 979-953-307-236-3Google Scholar
- Fujii Y, Cummings J, Xue Y, Schiller A, Lee T, Balmaseda MA, Remy E, Masuda S, Brassington G, Alves O, Cornuelle B, Martin M, Oke P, Smith G, Yang X (2015) Evaluation of the tropical Pacific observing system from the ocean data assimilation perspective. Q J R Meteorol Soc. doi: 10.1002/qj.2579 Google Scholar
- Kumar A, Wang H, Xue Y, Wang W (2014) How much of monthly subsurface temperature variability in equatorial pacific can be recovered by the specification of sea surface temperatures? J Clim 27:1557–1559Google Scholar