Academic Journal
High frequency radar error classification and prediction based on K-means methods
| العنوان: | High frequency radar error classification and prediction based on K-means methods |
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| المؤلفون: | Wang, Zhaoyi, Drevillon, Marie, de Mey-Frémaux, Pierre, Remy, Elisabeth, Ayoub, Nadia, K, Wang, Dakui, Levier, Bruno |
| المساهمون: | Tianjin University (TJU), National Marine Environmental Forecasting Center (NMEFC), Mercator Océan International (MOi), Institut de Recherche pour le Développement (IRD)-Service Hydrographique et Océanographique de la Marine (SHOM), Ministère de la défense (1936-.)-Ministère de la défense (1936-.)-United Kingdom Met Office Exeter -Nansen Environmental and Remote Sensing Center Bergen (NERSC)-National Research Council of Italy, Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Centre National de la Recherche Scientifique (CNRS) |
| المصدر: | ISSN: 2296-7745 ; Frontiers in Marine Science ; https://hal.science/hal-04767229 ; Frontiers in Marine Science, 2024, 11, pp.1448427. ⟨10.3389/fmars.2024.1448427⟩ ; https://www.frontiersin.org/journals/marine-science/articles/10.3389/fmars.2024.1448427/full. |
| بيانات النشر: | HAL CCSD Frontiers Media |
| سنة النشر: | 2024 |
| المجموعة: | Université Toulouse III - Paul Sabatier: HAL-UPS |
| مصطلحات موضوعية: | High frequency radar, K-means Clustering, Ocean current, Bay of Biscay, error estimate, [SDU.STU.OC]Sciences of the Universe [physics]/Earth Sciences/Oceanography, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [SDE.IE]Environmental Sciences/Environmental Engineering |
| الوصف: | International audience ; This study aims to characterize the high frequency radar and numerically simulated low-frequency filtered currents in the south-eastern Bay of Biscay (study area) using a K-means classification algorithm based on an improved Euclidean Distance calculation method that does not take missing values. The errors between observations and simulations was estimated and predicted based on this classification method. Results indicate that 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 provides a foundation for subsequent model error testing, forecast product improvement and data assimilation. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| DOI: | 10.3389/fmars.2024.1448427 |
| الاتاحة: | https://hal.science/hal-04767229 https://hal.science/hal-04767229v1/document https://hal.science/hal-04767229v1/file/ZhaoyiWang_fmars2024.pdf https://doi.org/10.3389/fmars.2024.1448427 |
| Rights: | info:eu-repo/semantics/OpenAccess |
| رقم الانضمام: | edsbas.4E5B7E6 |
| قاعدة البيانات: | BASE |
| DOI: | 10.3389/fmars.2024.1448427 |
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