کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6388628 | 1627927 | 2014 | 15 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Estimating Lagrangian transport blending drifters with HF radar data and models: Results from the TOSCA experiment in the Ligurian Current (North Western Mediterranean Sea)
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موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
زمین شناسی
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چکیده انگلیسی
Lagrangian transport estimates are investigated using results from HF radar, model and drifter data during a dedicated experiment in the Ligurian Current in the Toulon area (North Western Mediterranean Sea). Uncertainty estimates on particle position, D(t), are computed and compared to absolute dispersion, D0(t), that provides an indication of the uncertainty in case of zero prior knowledge. In agreement with previous studies, radar results show that D(t)â1/2D0(t) (i.e. â6Â km after 24Â h). Model results are less reliable, as it can be expected in highly nonlinear coastal flows without local data assimilation. The central result of this paper is that when drifters are promptly deployed in an area of interest, their data can be used to significantly improve transport estimates using the Lagrangian blending algorithm LAVA with velocity fields from models or radar. Uncertainty can be reduced to â1/6D0(t), (i.e. â2Â km after 24Â h) for both radar and model, implying a much reduced search range in case of operational applications. The method is also found to have some forecasting skills with uncertainty â1/2D0(t) during the first â6Â h. Sensitivity tests provide indications on relevant time and space scales of predictability and provide suggestions for appropriate drifter sampling strategies.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Progress in Oceanography - Volume 128, November 2014, Pages 15-29
Journal: Progress in Oceanography - Volume 128, November 2014, Pages 15-29
نویسندگان
Maristella Berta, Lucio Bellomo, Marcello G. Magaldi, Annalisa Griffa, Anne Molcard, Julien Marmain, Mireno Borghini, Vincent Taillandier,