{"title":"外推欧拉洋流以改进海面漂移预报","authors":"T. Tamtare, D. Dumont, C. Chavanne","doi":"10.1080/1755876x.2019.1661564","DOIUrl":null,"url":null,"abstract":"ABSTRACT Predictions of drift trajectories based on four drift models were compared with observations from drifting buoys deployed in 2014 and 2015 in the Estuary and Gulf of St. Lawrence to show the impact of the current vertical shear on the surface drift predictions. Input of ocean currents and winds are obtained from ISMER's 5 km resolution ocean circulation model and from the Canadian Regional Deterministic Prediction System, respectively. The control drift model A considers depth-averaged near-surface currents (0–5 m) provided by the top grid cell of the ocean circulation model. Model B performs a linear extrapolation assuming a constant vertical shear equal to that between the first two cells of the ocean model. Models C and D perform a dynamic extrapolation assuming an Ekman layer with a constant or linearly increasing vertical viscosity, respectively. Model performance is evaluated based on several error metrics. Drift models based on extrapolated surface currents reduce separation distances relative to the control model by 25% (model B), 31% (model C) and 35% (model D) on average, for lead times from 3 h to 72 h. We thus recommend the use of extrapolation methods of near-surface ocean currents for improving surface drift forecasting skills in support of emergency response.","PeriodicalId":50105,"journal":{"name":"Journal of Operational Oceanography","volume":"18 1","pages":"71 - 85"},"PeriodicalIF":1.7000,"publicationDate":"2019-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Extrapolating Eulerian ocean currents for improving surface drift forecasts\",\"authors\":\"T. Tamtare, D. Dumont, C. Chavanne\",\"doi\":\"10.1080/1755876x.2019.1661564\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT Predictions of drift trajectories based on four drift models were compared with observations from drifting buoys deployed in 2014 and 2015 in the Estuary and Gulf of St. Lawrence to show the impact of the current vertical shear on the surface drift predictions. Input of ocean currents and winds are obtained from ISMER's 5 km resolution ocean circulation model and from the Canadian Regional Deterministic Prediction System, respectively. The control drift model A considers depth-averaged near-surface currents (0–5 m) provided by the top grid cell of the ocean circulation model. Model B performs a linear extrapolation assuming a constant vertical shear equal to that between the first two cells of the ocean model. Models C and D perform a dynamic extrapolation assuming an Ekman layer with a constant or linearly increasing vertical viscosity, respectively. Model performance is evaluated based on several error metrics. Drift models based on extrapolated surface currents reduce separation distances relative to the control model by 25% (model B), 31% (model C) and 35% (model D) on average, for lead times from 3 h to 72 h. We thus recommend the use of extrapolation methods of near-surface ocean currents for improving surface drift forecasting skills in support of emergency response.\",\"PeriodicalId\":50105,\"journal\":{\"name\":\"Journal of Operational Oceanography\",\"volume\":\"18 1\",\"pages\":\"71 - 85\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2019-09-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Operational Oceanography\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1080/1755876x.2019.1661564\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"METEOROLOGY & ATMOSPHERIC SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Operational Oceanography","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1080/1755876x.2019.1661564","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
Extrapolating Eulerian ocean currents for improving surface drift forecasts
ABSTRACT Predictions of drift trajectories based on four drift models were compared with observations from drifting buoys deployed in 2014 and 2015 in the Estuary and Gulf of St. Lawrence to show the impact of the current vertical shear on the surface drift predictions. Input of ocean currents and winds are obtained from ISMER's 5 km resolution ocean circulation model and from the Canadian Regional Deterministic Prediction System, respectively. The control drift model A considers depth-averaged near-surface currents (0–5 m) provided by the top grid cell of the ocean circulation model. Model B performs a linear extrapolation assuming a constant vertical shear equal to that between the first two cells of the ocean model. Models C and D perform a dynamic extrapolation assuming an Ekman layer with a constant or linearly increasing vertical viscosity, respectively. Model performance is evaluated based on several error metrics. Drift models based on extrapolated surface currents reduce separation distances relative to the control model by 25% (model B), 31% (model C) and 35% (model D) on average, for lead times from 3 h to 72 h. We thus recommend the use of extrapolation methods of near-surface ocean currents for improving surface drift forecasting skills in support of emergency response.
期刊介绍:
The Journal of Operational Oceanography will publish papers which examine the role of oceanography in contributing to the fields of: Numerical Weather Prediction; Development of Climatologies; Implications of Ocean Change; Ocean and Climate Forecasting; Ocean Observing Technologies; Eutrophication; Climate Assessment; Shoreline Change; Marine and Sea State Prediction; Model Development and Validation; Coastal Flooding; Reducing Public Health Risks; Short-Range Ocean Forecasting; Forces on Structures; Ocean Policy; Protecting and Restoring Ecosystem health; Controlling and Mitigating Natural Hazards; Safe and Efficient Marine Operations