[A-CG40] Earth System Observation Impacts on Climate and Ocean Predictions

[ACG40-P08] High frequency radar error classification and prediction based on K-means methods

*Zhaoyi Wang^1,3, Marie Drevilion², Pierre De Mey-Frémaux⁴, Elisabeth Remy², Nadia Ayoub⁴, Dakui Wang³, Bruno Levier² (1.Tianjin Key Laboratory for Marine Environmental Research and Service, School of Marine Science and Technology, Tianjin University, 2.Mercator Ocean International, 3.Key Laboratory of Research on Marine Hazards Forecasting, National Marine Environmental Forecasting Cente, 4.Laboratory of Space Geophysical and Oceanographic Studies)

Keywords:HF radar, ocean current, the Bay of Biscay, K-means, error estimate

The K-means classification algorithm based on an improvedEuclidean Distance calculation method that does not take missing values into account was used to characterize the HF radar and numerically simulated 24h low-frequency filtered currents in the south-eastern Bay of Biscay (study area) and to estimate error between observation and simulation. The results for the study area show predominantly eastward (northward) currents over the Spanish (French) continental shelf/slope in winter and more variable currents in the west and south-west in summer. The model classification results for circulation characteristics are in relatively good agreement with HF radar results, especially for currents on the Spanish (French) shelf/slope. In addition, the probabilistic relationship between observed and modeled currents was explored, obtaining the probability of occurrence of modeled current groups when each group of observed currents occurs. Finally, predictions of model and observed current errors were made based on the classification results, and it was found that the predictions based on the classification of all data had the smallest errors, with a 17% improvement over the unclassified control experiment. This study will provide the basis for subsequent model error testing, forecast product improvement and data assimilation.