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Discussion papers | Copyright
https://doi.org/10.5194/amt-2017-456
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 01 Feb 2018

Research article | 01 Feb 2018

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This discussion paper is a preprint. A revision of the manuscript is under review for the journal Atmospheric Measurement Techniques (AMT).

Evaluation of OAFlux datasets based on in situ air-sea flux tower observations over the Yongxing Islands in 2016

Fenghua Zhou1, Rongwang Zhang1, Rui Shi1, Ju Chen1, Yunkai He1, Lili Zeng1, Dongxiao Wang1, and Qiang Xie2,3 Fenghua Zhou et al.
  • 1State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510300, China
  • 2Institute of Deep-sea Science and Engineering, Chinese Academy of Sciences, Sanya 572000, China
  • 3Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qiangdao, 266237, China

Abstract. The high-quality Yongxing air-sea flux tower (YXASFT), which was specially designed for air-sea boundary layer flux-related observations, was constructed on Yongxing Island in the South China Sea (SCS). Surface bulk variable measurements were collected during a one-year period from 2016/02/01 to 2017/01/31. 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) using those variables. This study employed the YXASFT in situ observations to evaluate the Woods Hole Oceanographic Institute (WHOI) OAFlux reanalysis data products in the SCS. The study period was divided into the spring, summer_autumn and winter periods to conduct seasonal comparisons for each variable.

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 measurements with a coefficient of determination (R2) of 0.78. Second, to conduct seasonal comparisons, the overall reliabilities of the bulk OAFlux variables diminish in order from Ta, U, Qa to Ts based on a combination of R2 values and biases. OAFlux overestimates (underestimates) U (Qa) throughout the year and provides better estimates of both variables in the 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 value is observed between the OAFlux-estimated and YXASFT-observed Ts, indicating that Ts is the least reliable product 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 52w/m2 (73% of the observed mean) in the spring, and the seasonal OAFlux LHF performance is consistent with U and Qa. The OAFlux-estimated SHF appears to be poorly representative with enormous overestimations in the spring and winter, while its performance is much better during the summer_autumn period. Third, an 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 (2016/02/01–2017/01/31) at the YXASFT in the Yongxing Islands. 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 reseracher on how to select the oppropriate 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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