scholarly journals Improving flow characterisations in complex estuary and coastal waterways using Lagrangian drifter data

2021 ◽  
Author(s):  
Mohammadreza Khanarmuei
Keyword(s):  
Lagrangian Drifter

scholarly journals Lagrangian predictability of high-resolution regional models: the special case of the Gulf of Mexico

2004 ◽  
Vol 11 (1) ◽  
pp. 47-66 ◽  
Author(s):  
P. C. Chu ◽  
L. M. Ivanov ◽  
L. H. Kantha ◽  
T. M. Margolina ◽  
O. V. Melnichenko ◽  
...  
Keyword(s):  
Gulf Of Mexico ◽  
Prediction Error ◽  
Spatial Scales ◽  
Singular Values ◽  
Forecast System ◽  
Gaussian Shape ◽  
University Of Colorado ◽  
Non Gaussian ◽  
The University ◽  
Lagrangian Drifter

Abstract. The Lagrangian prediction skill (model ability to reproduce Lagrangian drifter trajectories) of the nowcast/forecast system developed for the Gulf of Mexico at the University of Colorado at Boulder is examined through comparison with real drifter observations. Model prediction error (MPE), singular values (SVs) and irreversible-skill time (IT) are used as quantitative measures of the examination. Divergent (poloidal) and nondivergent (toroidal) components of the circulation attractor at 50m depth are analyzed and compared with the Lagrangian drifter buoy data using the empirical orthogonal function (EOF) decomposition and the measures, respectively. Irregular (probably, chaotic) dynamics of the circulation attractor reproduced by the nowcast/forecast system is analyzed through Lyapunov dimension, global entropies, toroidal and poloidal kinetic energies. The results allow assuming exponential growth of prediction error on the attractor. On the other hand, the q-th moment of MPE grows by the power law with exponent of 3q/4. The probability density function (PDF) of MPE has a symmetrical but non-Gaussian shape for both the short and long prediction times and for spatial scales ranging from 20km to 300km. The phenomenological model of MPE based on a diffusion-like equation is developed. The PDF of IT is non-symmetric with a long tail stretched towards large ITs. The power decay of the tail was faster than 2 for long prediction times.

scholarly journals Estimating the state of a geophysical system with sparse observations: time delay methods to achieve accurate initial states for prediction

2017 ◽  
Vol 24 (1) ◽  
pp. 9-22 ◽  
Author(s):  
Zhe An ◽  
Daniel Rey ◽  
Jingxin Ye ◽  
Henry D. I. Abarbanel
Keyword(s):  
Time Delays ◽  
Time Series Data ◽  
Chaotic Behavior ◽  
Weather Prediction ◽  
Series Data ◽  
State Variables ◽  
Nonlinear Shallow Water Equations ◽  
Delayed Measurements ◽  
Lagrangian Drifter ◽  
Geophysical System

Abstract. The problem of forecasting the behavior of a complex dynamical system through analysis of observational time-series data becomes difficult when the system expresses chaotic behavior and the measurements are sparse, in both space and/or time. Despite the fact that this situation is quite typical across many fields, including numerical weather prediction, the issue of whether the available observations are "sufficient" for generating successful forecasts is still not well understood. An analysis by Whartenby et al. (2013) found that in the context of the nonlinear shallow water equations on a β plane, standard nudging techniques require observing approximately 70 % of the full set of state variables. Here we examine the same system using a method introduced by Rey et al. (2014a), which generalizes standard nudging methods to utilize time delayed measurements. We show that in certain circumstances, it provides a sizable reduction in the number of observations required to construct accurate estimates and high-quality predictions. In particular, we find that this estimate of 70 % can be reduced to about 33 % using time delays, and even further if Lagrangian drifter locations are also used as measurements.

scholarly journals Surface flow structure of the Gulf Stream from composite imagery and satellite-tracked drifters

1994 ◽  
Vol 1 (1) ◽  
pp. 64-71 ◽  
Author(s):  
C. P. Mullen ◽  
A. D. Kirwan, Jr.
Keyword(s):  
Fractal Dimension ◽  
Flow Structure ◽  
Gulf Stream ◽  
Surface Flow ◽  
Geographic Variability ◽  
Data Set ◽  
Study Region ◽  
Physical Conditions ◽  
The North ◽  
Lagrangian Drifter

Abstract. A unique set of coutemporaneous satellite-tracked drifters and five-day composite Advanced Very High Resolution Radionmeter (AVHRR) satellite imagery of the North Atlantic has been analyzed to examine the surface flow structure of the Gulf Stream. The study region was divided into two sections, greater than 37° N and less than 37° N, in order to answer the question of geographic variability. Fractal and spectral analyses methods were applied to the data. Fractal analysis of the Lagrangian trajectories showed a fractal dimension of 1.21 + 0.02 with a scaling range of 83 - 343 km. The fractal dimension of the temperature fronts of the composite imagery is similar for the two regions with D = 1.11 + 0.01 over a scaling range of 4 - 44 km. Spectral analysis also reports a fairly consistent value for the spectral slope and its scaling range. Therefore, we conclude there is no geographic variability in the data set. A suitable scaling range for this contemporaneous data set is 80 - 200 km which is consistent with the expected physical conditions in the region. Finally, we address the idea of using five-day composite imagery to infer the surface flow of the Gulf Stream. Close analyses of the composite thermal fronts and the Lagrangian drifter trajectories show that the former is not a good indicator of the latter.

scholarly journals A performance comparison for two lagrangian drifter designs

1989 ◽  
Vol 27 (2) ◽  
pp. 443-456 ◽  
Author(s):  
David L. Mackas ◽  
William R. Crawford ◽  
Pearn P. Niiler
Keyword(s):  
Performance Comparison ◽  
Lagrangian Drifter ◽  
A Performance

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.

scholarly journals A comparison of biogenic iron quotas during a diatom spring bloom using multiple approaches

2012 ◽  
Vol 9 (2) ◽  
pp. 667-687 ◽  
Author(s):  
A. L. King ◽  
S. A. Sañudo-Wilhelmy ◽  
P. W. Boyd ◽  
B. S. Twining ◽  
S. W. Wilhelm ◽  
...  
Keyword(s):  
Single Cell ◽  
Inductively Coupled Plasma ◽  
Spring Bloom ◽  
Biogenic Elements ◽  
Surface Mixed Layer ◽  
Inductively Coupled ◽  
General Decline ◽  
Sampling Protocols ◽  
Lagrangian Drifter ◽  
Radioisotope Uptake

Abstract. Biogenic Fe quotas were determined using three distinct techniques on samples collected concurrently in the subtropical Pacific Ocean east of New Zealand. Fe quotas were measured using radioisotope uptake experiments (24 h incubation), bulk filtration and analysis by inductively-coupled plasma mass spectrometer (ICPMS), and single-cell synchrotron x-ray fluorescence (SXRF) analysis over a sixteen-day period (year days 263 to 278 of 2008) during a quasi-Lagrangian drifter experiment that tracked the evolution of the annual spring diatom bloom within a counter-clockwise open-ocean eddy. Overall, radioisotope uptake-determined Fe quotas (washed with oxalate reagent to remove extracellular Fe) were the lowest (0.5–1.0 mmol Fe:mol P; 4–8 μmol Fe:mol C), followed by single-cell Fe quotas (2.3–7.5 mmol Fe:mol P; 17–57 μmol Fe:mol C), and the highest and most variable quotas were from the bulk filtration ICPMS approach that used the oxalate reagent wash, corrected for lithogenic Fe using Al (0.8–21 mmol Fe:mol P; 4–136 μmol Fe:mol C). During the evolution of the spring bloom within the eddy (year days 263 to 272), the surface mixed layer inventories of particulate biogenic elements (C, N, P, Si) and chlorophyll increased while Fe quotas estimated from all three approaches exhibited a general decline. After the onset of the bloom decline, the drogued buoys exited the eddy center (days 273 to 277). Fe quotas returned to pre-bloom values during this part of the study. Our standardized and coordinated sampling protocols reveal the general observed trend in Fe quotas: ICPMS > SXRF > radioisotope uptake. We discuss the inherent differences between the techniques and argue that each technique has its individual merits and uniquely contributes to the characterization of the oceanic particulate Fe pool.

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