4.6 Article

Modelling surface drifting of buoys during a rapidly-moving weather front in the Gulf of Finland, Baltic Sea

期刊

ESTUARINE COASTAL AND SHELF SCIENCE
卷 70, 期 4, 页码 567-576

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ACADEMIC PRESS LTD ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ecss.2006.06.010

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Lagrangian current measurement; surface drifters; surface currents; modelling; atmospheric forcing; Baltic Sea

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The Gulf of Finland is an elongated estuary located in the north-eastern extremity of the Baltic Sea. This semi-enclosed sea-area is subject to heavy sea traffic, and is one of the main risk areas for oil accidents in the Baltic. The continuous development and validation of operational particle drift and oil-spill forecasting systems is thus seen to be essential for this sea-area. Here, the results of a three-day drift experiment in May 2003 are discussed. The field studies were performed using GPS-positioned surface floating buoys. The aim of this paper is to evaluate how well models can reproduce the drift of these buoys. Model simulations, both in forecast and hindcast modes. were carried out by three different 3D hydrodynamic models, the results of which are evaluated by comparing the calculated drifts with observations. These models were forced by HIRLAM (High Resolution Limited Area Model) and ECMWF (European Centre for Medium-Range Weather Forecasts) meteorological forecast fields. The simulated drift of the buoys showed a good agreement with observations even when, during the study period, a rapidly-changing wind situation was observed to affect the investigation area; in this situation the winds turned about 100 degrees in half an hour. In such a case it is a very complicated task to forecast the drifters' routes: there is a need to regularly update the meteorological forcing fields and to use these regularly-updated fields throughout the simulations. It is furthermore recommended that forecasts should be made using several circulation models and several meteorological forecasts, in order to get an overview of the accuracy of the forecasted drifts and related differences in between the forecasts. (c) 2006 Elsevier Ltd. All rights reserved.

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