How do uncertainties in NCEP R2 and CFSR surface fluxes impact tropical ocean simulations?
- 259 Downloads
NCEP/DOE reanalysis (R2) and Climate Forecast System Reanalysis (CFSR) surface fluxes are widely used by the research community to understand surface flux climate variability, and to drive ocean models as surface forcings. However, large discrepancies exist between these two products, including (1) stronger trade winds in CFSR than in R2 over the tropical Pacific prior 2000; (2) excessive net surface heat fluxes into ocean in CFSR than in R2 with an increase in difference after 2000. The goals of this study are to examine the sensitivity of ocean simulations to discrepancies between CFSR and R2 surface fluxes, and to assess the fidelity of the two products. A set of experiments, where an ocean model was driven by a combination of surface flux components from R2 and CFSR, were carried out. The model simulations were contrasted to identify sensitivity to different component of the surface fluxes in R2 and CFSR. The accuracy of the model simulations was validated against the tropical moorings data, altimetry SSH and SST reanalysis products. Sensitivity of ocean simulations showed that temperature bias difference in the upper 100 m is mostly sensitive to the differences in surface heat fluxes, while depth of 20 °C (D20) bias difference is mainly determined by the discrepancies in momentum fluxes. D20 simulations with CFSR winds agree with observation well in the western equatorial Pacific prior 2000, but have large negative bias similar to those with R2 winds after 2000, partly because easterly winds over the central Pacific were underestimated in both CFSR and R2. On the other hand, the observed temperature variability is well reproduced in the tropical Pacific by simulations with both R2 and CFSR fluxes. Relative to the R2 fluxes, the CFSR fluxes improve simulation of interannual variability in all three tropical oceans to a varying degree. The improvement in the tropical Atlantic is most significant and is largely attributed to differences in surface winds.
KeywordsCFSR NCEP/DOE reanalysis (R2) Surface wind stress/heat flux validation Ocean model Tropical moored buoy data
We thank Dr. Hui Wang and Dr. Jieshun Zhu for their helpful comments on the initial version of the manuscript. We are grateful for comments from two anonymous reviewers, who greatly helped to improve the final version.
- Behringer D, Xue Y (2004) Evaluation of the global ocean data assimilation system at NCEP: the Pacific Ocean. Eighth Symp Integr Obs Assim Syst Atmos Ocean Land SurfGoogle Scholar
- Conkright ME, Levitus S, O’Brien T, Boyer TP, Stephens C (1998) World ocean database 1998 CD-ROM dataset documentation. Natl. Oceanogr. Data Cent. Int. Rep. 14, Natl. Oceanogr. and Atmos. Admin.. Silver Spring, MDGoogle Scholar
- Griffies SM, Schmidt M, Herzfeld M (2009a) Elements of mom4p1. GFDL Ocean Group Tech Rep 6:444Google Scholar
- Griffies SM et al (2009b) Coordinated ocean-ice reference experiments (COREs). Ocean Modell 26:1–46Google Scholar
- IPCC (2007) Climate change 2007: the physical science basis. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Contribution of Working Group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, 996 ppGoogle Scholar
- Jiang C, Cronin MF, Kelly KA, Thompson L (2005) Evaluation of a hybrid satellite-and NWP-based turbulent heat flux product using Tropical Atmosphere–Ocean (TAO) buoys. J Geophys Res 110Google Scholar
- Merrifield MA, Maltrud ME (2011) Regional sea level trends due to a Pacific trade wind intensification. Geophys Res Lett 38Google Scholar
- Valdivieso M et al (2015) An assessment of air–sea heat fluxes from ocean and coupled reanalyses. Clim Dyn 1–26Google Scholar
- Wang C, Xie SP, Carton JA (2004) A global survey of ocean–atmosphere interaction and climate variability. Earth Climate: the Ocean-Atmopshere Interactions, Geophys. Monogr., 147, Amer. Geophys. Union, 1–19Google Scholar
- Xue Y et al (2015) Evaluation of tropical Pacific observing systems using NCEP and GFDL ocean data assimilation systems. Clim Dyn 1–26Google Scholar
- Zhang L, Kumar A, Wang W (2012) Influence of changes in observations on precipitation: a case study for the climate forecast system reanalysis (CFSR). J Geophys Res 117Google Scholar