Evaluation of Air–Sea Flux Products Based on Observations in the Northern South China Sea

Quantifying the time and space scale variability in air–sea fluxes is challenging. This study adopts tower-based in situ observations in the northern South China Sea (SCS) to evaluate widely used reanalysis and CO2 flux products. For heat and momentum fluxes, three reanalysis products were considered: the fifth-generation European Centre for Medium-Range Weather Forecast reanalysis (ERA5), the NCEP Climate Forecast System Version 2 reanalysis (CFSv2), and third-generation Japanese Meteorological Agency reanalysis (JRA55). Comparisons of surface state variables show that these three reanalysis products generally agree well with observations on both the daily and monthly scales. On the daily scale, the correlation coefficients between observations and ERA5 exceed 0.93 for wind, air temperature, relative humidity, and longwave radiation. On the monthly scale, seasonal variations in wind, air temperature, and relative humidity are well captured. Nevertheless, the three reanalysis products all overestimate (underestimate) the latent (sensible) heat flux, with a root mean square error above 90.50 (33.35) W/m2. For momentum fluxes, the three reanalysis datasets tend to underestimate 0.07∼0.08 N/m2 with a high correlation coefficient above 0.71. In terms of CO2 fluxes, the Multi-observation Carbon Assimilation System (MCAS), Surface Ocean CO2 Atlas (SOCAT), and Global ObservatioN-based system for monitoring Greenhouse GAs (GONGGA) inversion CO2 flux datasets were evaluated. SOCAT performs best with a correlation coefficient of 0.75, and GONGGA follows with 0.64, while MCAS demonstrates the lowest performance with a value of 0.36. In addition, the spatial patterns of the monthly mean surface CO2 flux in the northern SCS illustrate significant discrepancies between MCAS, SOCAT, and GONGGA. These results can provide valuable insights for reducing uncertainties in air–sea flux products over coastal areas in the future.