@article{fdi:010092593,
  title = {{S}urface circulation characterization along the middle southern coastal region of {V}ietnam from high-frequency radar and numerical modeling},
  author = {{T}ran, {T}. {H}. and {S}entchev, {A}. and {D}uy, {T}. {T}. and {H}errmann, {M}arine and {O}uillon, {S}ylvain and {N}guyen, {K}. {C}.},
  editor = {},
  language = {{ENG}},
  abstract = {{C}oastal water dynamics along the {V}ietnamese middle southern coast ({VMSC}) region, part of the {S}outh {C}hina {S}ea, are highly complex with large spatiotemporal variability whose drivers are not yet well understood. {F}or the first time, high-resolution surface current data from high-frequency radar ({HFR}) measurements were obtained in this region during the early (transition) phase of the {A}sian summer monsoon. {T}he data were used for comparison with simulation results from a circulation model, {SYMPHONIE}, and ultimately to optimize the wind forcing in the model. {B}oth modeling and {HFR} were able to show the spatial and temporal evolution of the surface circulation, but some discrepancies were found between model and {HFR} data on some days, coinciding with the evolution of the wind. {T}wo methods were used to optimize the wind forcing, namely the ensemble perturbation smoother ({E}n{PS}) and the wind correction method using wind-driven surface currents ({E}k{W}). {B}oth methods achieved a significant reduction (similar to 36 %-40 %) in the error of the surface current velocity fields compared to the measured data. {O}ptimized winds obtained from the two methods were compared with satellite wind data for validation. {T}he results show that both optimization methods performed better in the far field, where topography no longer affects the coastal surface circulation. {T}he optimization results revealed that the surface circulation is driven not only by winds but also by other factors such as intrinsic ocean variability, which is not entirely controlled by boundary conditions. {T}his indicates the potential usefulness of large velocity datasets and other data fusion methods to effectively improve modeling results.},
  keywords = {{VIET} {NAM} ; {CHINE} {DU} {SUD} {MER}},
  booktitle = {},
  journal = {{O}cean {S}cience},
  volume = {21},
  numero = {1},
  pages = {1--18},
  ISSN = {1812-0784},
  year = {2025},
  DOI = {10.5194/os-21-1-2025},
  URL = {https://www.documentation.ird.fr/hor/fdi:010092593},
}