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Estimating Lagrangian transport blending drifters with HF radar data and models: Results from the TOSCA experiment in the Ligurian Current (North Western Mediterranean Sea)

Articolo
Data di Pubblicazione:
2014
Abstract:
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, D-0(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) approximate to 1/2D(0)(t) (i.e. approximate to 6 km after 24 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 approximate to 1/6D(0)(t), (i.e. approximate to 2 km after 24 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 approximate to 1/2D(0)(t) during the first 7, approximate to 6 h. Sensitivity tests provide indications on relevant time and space scales of predictability and provide suggestions for appropriate drifter sampling strategies. (C) 2014 Elsevier Ltd. All rights reserved.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
HF radars; Lagrangian transport; North-western Mediterranean Sea
Elenco autori:
Berta, Maristella; Griffa, Annalisa; Magaldi, MARCELLO GATIMU
Autori di Ateneo:
BERTA MARISTELLA
MAGALDI MARCELLO GATIMU
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/259913
Pubblicato in:
PROGRESS IN OCEANOGRAPHY
Journal
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http://www.sciencedirect.com/science/article/pii/S007966111400127X
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