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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Volume 11, issue 11
Atmos. Meas. Tech., 11, 6091-6106, 2018
https://doi.org/10.5194/amt-11-6091-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Atmos. Meas. Tech., 11, 6091-6106, 2018
https://doi.org/10.5194/amt-11-6091-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 09 Nov 2018

Research article | 09 Nov 2018

Evaluation of OAFlux datasets based on in situ air–sea flux tower observations over Yongxing Island in 2016

Fenghua Zhou1,2, Rongwang Zhang1, Rui Shi1, Ju Chen1, Yunkai He1, Dongxiao Wang1, and Qiang Xie3,4 Fenghua Zhou et al.
  • 1State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510300, China
  • 2University of Chinese Academy of Sciences, Beijing 100049, China
  • 3Institute of Deep-sea Science and Engineering, Chinese Academy of Sciences, Sanya 572000, China
  • 4Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China

Abstract. The Yongxing air–sea flux tower (YXASFT), which was specially designed for air–sea boundary layer observations, was constructed on Yongxing Island in the South China Sea (SCS). Surface bulk variable measurements were collected during a 1-year period from 1 February 2016 to 31 January 2017. The sensible heat flux (SHF) and latent heat flux (LHF) were further derived via the Coupled Ocean–Atmosphere Response Experiment version 3.0 (COARE3.0). This study employed the YXASFT in situ observations to evaluate the Woods Hole Oceanographic Institute (WHOI) Objectively Analyzed Air–Sea Fluxes (OAFlux) reanalysis data products.

First, the reliability of COARE3.0 data in the SCS was validated using direct turbulent heat flux measurements via an eddy covariance flux (ECF) system. The LHF data derived from COARE3.0 are highly consistent with the ECF with a coefficient of determination (R2) of 0.78. Second, the overall reliabilities of the bulk OAFlux variables were diminished in the order of Ta (air temperature), U(wind speed), Qa (air humidity) and Ts (sea surface temperature) based on a combination of R2 values and biases. OAFlux overestimates (underestimates) U (Qa) throughout the year and provides better estimates for winter and spring than in the summer–autumn period, which seems to be highly correlated with the monsoon climate in the SCS. The lowest R2 is between the OAFlux-estimated and YXASFT-observed Ts, indicating that Ts is the least reliable dataset and should thus be used with considerable caution. In terms of the heat fluxes, OAFlux considerably overestimates LHF with an ocean heat loss bias of 52wm−2 in the spring, and the seasonal OAFlux LHF performance is consistent with U and Qa. The OAFlux-estimated SHF appears to be a poor representative, with enormous overestimations in the spring and winter, while its performance is much better during the summer–autumn period. Third, analysis reveals that the biases in Qa are the most dominant factor on the LHF biases in the spring and winter, and that the biases in both Qa and U are responsible for controlling the biases in LHF during the summer–autumn period. The biases in Ts are responsible for controlling the SHF biases, and the effects of biases in Ts on the biases in SHF during the spring and winter are much greater than that in the summer–autumn period.

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In this work, successive air–sea heat flux-related data were acquired over the course of a year (01/02/2016–31/01/2017) at the YXASFT on Yongxing Island. Then, seasonal comparisons were conducted for the daily mean surface bulk variables and heat fluxes between the WHOI OAFlux products and YXASFT observations. The conclusions in this paper will provide useful reference for researchers on how to select the appropriate OAFlux datasets in different seasons over the South China Sea.
In this work, successive air–sea heat flux-related data were acquired over the course of a year...
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