scholarly journals Calculating lateral plume spreading with surface Lagrangian drifters

2020 ◽  
Vol 18 (7) ◽  
pp. 346-361
Author(s):  
Georgia Kakoulaki ◽  
Daniel G. MacDonald ◽  
Kelly Cole
Keyword(s):  
Lagrangian Drifters

Analysis of the Large-Scale Dynamics of Surface Waters in the Southern Ocean with the Help of Lagrangian Drifters

2003 ◽  
Vol 13 (6) ◽  
pp. 333-354
Author(s):  
A. I. Danilov ◽  
L. M. Ivanov ◽  
A. V. Klepikov ◽  
T. M. Margolina
Keyword(s):  
Southern Ocean ◽  
Surface Waters ◽  
Large Scale ◽  
Lagrangian Drifters

Mesoscale Activity in the Eastern Mediterranean: Blending Altimetry with in situ observations

2020 ◽  
Author(s):  
Georges Baaklini ◽  
Leila Issa ◽  
Julien Brajard ◽  
Milad Fakhri ◽  
Milena Menna ◽  
...  
Keyword(s):  
Eastern Mediterranean ◽  
Regional Scale ◽  
Surface Velocity ◽  
Surface Dynamics ◽  
Ocean Modelling ◽  
Lagrangian Drifters ◽  
In Situ Observations ◽  
Surface Drifters ◽  
Lebanese Coast

<p>Mesoscale to sub-mesoscale surface dynamics in the ocean is a key parameter, driving, for instance, the dispersion of pollutants emanating from heavily populated coastal areas for example. Estimating the surface velocity can be challenging especially when data is sparse. In [1], the authors developed a near real-time 3D-Var assimilation algorithm that blends in-situ Lagrangian drifters’ positions with altimetry data to improve the estimation of the surface velocity in the Eastern Levantine Mediterranean. The algorithm was tested near the Lebanese coast and in the case of an eddy between Lebanon and Cyprus. The objective of this work is to further validate the algorithm.</p><p>First, a Comparison with Ocean color satellite images shows that eddies’ shapes and location are more consistent after the assimilation of drifter data.Independent in-situ current-meter data provided from the EGYPT campaign are also used to validate the results of the algorithm in terms of velocity intensity and direction. The comparison shows an improvement of the estimated velocity, particularly in terms of direction.</p><p>We also address the question of extending the algorithm to a larger regional scale in the Eastern Levantine Mediterranean, which is subject to a high mesoscale activity but which is less densely observed than the western part.</p><p> </p><p><span>[1] L. Issa, J. Brajard, M. Fakhri, D. Hayes, L. Mortier, P-M. Poulain. </span>Modelling Surface Currents in the Eastern Levantine Mediterranean Using Surface Drifters and Satellite Altimetry. Ocean Modelling, May 2016. Doi: 10.1016/j.ocemod.2016.05.006</p>

Vertical noise coherence measurements in shallow water using Lagrangian drifters

1998 ◽  
Vol 103 (5) ◽  
pp. 2858-2858
Author(s):  
Fancine Desharnais ◽  
Blair R. MacDonald ◽  
Kenneth J. Mah
Keyword(s):  
Shallow Water ◽  
Lagrangian Drifters

scholarly journals Improving the Accuracy of Hydrodynamic Model Predictions Using Lagrangian Calibration

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 575 ◽  
Author(s):  
Neda Mardani ◽  
Kabir Suara ◽  
Helen Fairweather ◽  
Richard Brown ◽  
Adrian McCallum ◽  
...  
Keyword(s):  
Hydrodynamic Model ◽  
Field Measurements ◽  
Hydrodynamic Models ◽  
Lagrangian Drifters ◽  
Lagrangian Velocity ◽  
Model Predictions ◽  
Spatio Temporal ◽  
Lagrangian Data ◽  
Lagrangian Drifter ◽  
Recent Attention

While significant studies have been conducted in Intermittently Closed and Open Lakes and Lagoons (ICOLLs), very few have employed Lagrangian drifters. With recent attention on the use of GPS-tracked Lagrangian drifters to study the hydrodynamics of estuaries, there is a need to assess the potential for calibrating models using Lagrangian drifter data. Here, we calibrated and validated a hydrodynamic model in Currimundi Lake, Australia using both Eulerian and Lagrangian velocity field measurements in an open entrance condition. The results showed that there was a higher level of correlation (R2 = 0.94) between model output and observed velocity data for the Eulerian calibration compared to that of Lagrangian calibration (R2 = 0.56). This lack of correlation between model and Lagrangian data is a result of apparent difficulties in the use of Lagrangian data in Eulerian (fixed-mesh) hydrodynamic models. Furthermore, Eulerian and Lagrangian devices systematically observe different spatio-temporal scales in the flow with larger variability in the Lagrangian data. Despite these, the results show that Lagrangian calibration resulted in optimum Manning coefficients (n = 0.023) equivalent to those observed through Eulerian calibration. Therefore, Lagrangian data has the potential to be used in hydrodynamic model calibration in such aquatic systems.

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