Kumar Arun

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Kumar
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Arun
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Subject: CFSR × Start date: 2016 × End date: 2016 ×

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  • Preprint
    How do uncertainties in NCEP R2 and CFSR surface fluxes impact tropical ocean simulations?
    ( 2016-12) Wen, Caihong ; Xue, Yan ; Kumar, Arun ; Behringer, David W. ; Yu, Lisan
    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 component 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 100m 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.