scholarly journals Measuring surface currents with Surface Velocity Program drifters: the instrument, its data, and some recent results

2009 ◽  
pp. 39-67 ◽  
Author(s):  
Rick Lumpkin ◽  
Mayra Pazos
Keyword(s):  
Surface Velocity ◽  
Surface Currents ◽  
Measuring Surface

High-Frequency Radar Mapping of Surface Currents Using WERA

2007 ◽  
Vol 24 (3) ◽  
pp. 484-503 ◽  
Author(s):  
Lynn K. Shay ◽  
Jorge Martinez-Pedraja ◽  
Thomas M. Cook ◽  
Brian K. Haus ◽  
Robert H. Weisberg
Keyword(s):  
Time Series ◽  
High Frequency ◽  
Tidal Currents ◽  
Tropical Storm ◽  
Surface Velocity ◽  
Surface Currents ◽  
West Florida Shelf ◽  
The West ◽  
Florida Shelf ◽  
East West

Abstract A dual-station high-frequency Wellen Radar (WERA), transmitting at 16.045 MHz, was deployed along the west Florida shelf in phased array mode during the summer of 2003. A 33-day, continuous time series of radial and vector surface current fields was acquired starting on 23 August ending 25 September 2003. Over a 30-min sample interval, WERA mapped coastal ocean currents over an ≈40 km × 80 km footprint with a 1.2-km horizontal resolution. A total of 1628 snapshots of the vector surface currents was acquired, with only 70 samples (4.3%) missing from the vector time series. Comparisons to subsurface measurements from two moored acoustic Doppler current profilers revealed RMS differences of 1 to 5 cm s−1 for both radial and Cartesian current components. Regression analyses indicated slopes close to unity with small biases between surface and subsurface measurements at 4-m depth in the east–west (u) and north–south (υ) components, respectively. Vector correlation coefficients were 0.9 with complex phases of −3° and 5° at EC4 (20-m isobath) and NA2 (25-m isobath) moorings, respectively. Complex surface circulation patterns were observed that included tidal and wind-driven currents over the west Florida shelf. Tidal current amplitudes were 4 to 5 cm s−1 for the diurnal and semidiurnal constituents. Vertical structure of these tidal currents indicated that the semidiurnal components were predominantly barotropic whereas diurnal tidal currents had more of a baroclinic component. Tidal currents were removed from the observed current time series and were compared to the 10-m adjusted winds at a surface mooring. Based on these time series comparisons, regression slopes were 0.02 to 0.03 in the east–west and north–south directions, respectively. During Tropical Storm Henri’s passage on 5 September 2003, cyclonically rotating surface winds forced surface velocities of more than 35 cm s−1 as Henri made landfall north of Tampa Bay, Florida. These results suggest that the WERA measured the surface velocity well under weak to tropical storm wind conditions.

scholarly journals Estimation of Coastal Currents Using a Soft Computing Method: A Case Study in Galway Bay, Ireland

2019 ◽  
Vol 7 (5) ◽  
pp. 157 ◽  
Author(s):  
Lei Ren ◽  
Jianming Miao ◽  
Yulong Li ◽  
Xiangxin Luo ◽  
Junxue Li ◽  
...  
Keyword(s):  
Numerical Model ◽  
Soft Computing ◽  
Initial Conditions ◽  
Numerical Models ◽  
Surface Velocity ◽  
Training Dataset ◽  
Model Parameters ◽  
Surface Currents ◽  
Coastal Currents ◽  
Computing Models

In order to obtain forward states of coastal currents, numerical models are a commonly used approach. However, the accurate definition of initial conditions, boundary conditions and other model parameters are challenging. In this paper, a novel application of a soft computing approach, random forests (RF), was adopted to estimate surface currents for three analysis points in Galway Bay, Ireland. Outputs from a numerical model and observations from a high frequency radar system were used as inputs to develop soft computing models. The input variable structure of soft computing models was examined in detail through sensitivity experiments. High correlation of surface currents between predictions from RF models and radar data indicated that the RF algorithm is a most promising means of generating satisfactory surface currents over a long prediction period. Furthermore, training dataset lengths were examined to investigate influences on prediction accuracy. The largest improvement for zonal and meridional surface velocity components over a 59-h forecasting period was 14% and 37% of root mean square error (RMSE) values separately. Results indicate that the combination of RF models with a numerical model can significantly improve forecasting accuracy for surface currents, especially for the meridional surface velocity component.

scholarly journals Forecasting of Surface Currents via Correcting Wind Stress with Assimilation of High-Frequency Radar Data in a Three-Dimensional Model

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Lei Ren ◽  
Stephen Nash ◽  
Michael Hartnett
Keyword(s):  
Data Assimilation ◽  
High Frequency ◽  
Three Dimensional ◽  
Hf Radar ◽  
Surface Velocity ◽  
Shear Stresses ◽  
Surface Currents ◽  
Dimensional Model ◽  
Three Dimensional Model ◽  
The Impact

This paper details work in assessing the capability of a hydrodynamic model to forecast surface currents and in applying data assimilation techniques to improve model forecasts. A three-dimensional model Environment Fluid Dynamics Code (EFDC) was forced with tidal boundary data and onshore wind data, and so forth. Surface current data from a high-frequency (HF) radar system in Galway Bay were used for model intercomparisons and as a source for data assimilation. The impact of bottom roughness was also investigated. Having developed a “good” water circulation model the authors sought to improve its forecasting ability through correcting wind shear stress boundary conditions. The differences in surface velocity components between HF radar measurements and model output were calculated and used to correct surface shear stresses. Moreover, data assimilation cycle lengths were examined to extend the improvements of surface current’s patterns during forecasting period, especially for north-south velocity component. The influence of data assimilation in model forecasting was assessed using a Data Assimilation Skill Score (DASS). Positive magnitude of DASS indicated that both velocity components were considerably improved during forecasting period. Additionally, the improvements of RMSE for vector direction over domain were significant compared with the “free run.”

scholarly journals Water Surface and Velocity Measurement-River and Flume

2014 ◽  
Vol XL-5 ◽  
pp. 151-156 ◽  
Author(s):  
J. H. Chandler ◽  
E. Ferreira ◽  
R. Wackrow ◽  
K. Shiono
Keyword(s):  
Experimental Work ◽  
Water Surface ◽  
Critical Role ◽  
Extreme Rainfall ◽  
Surface Velocity ◽  
Specific Marker ◽  
Extreme Rainfall Events ◽  
Measuring Surface ◽  
Initial Work ◽  
Close Range

Understanding the flow of water in natural watercourses has become increasingly important as climate change increases the incidence of extreme rainfall events which cause flooding. Vegetation in rivers and streams reduce water conveyance and natural vegetation plays a critical role in flood events which needs to be understood more fully. A funded project at Loughborough University is therefore examining the influence of vegetation upon water flow, requiring measurement of both the 3-D water surface and flow velocities. Experimental work therefore requires the measurement of water surface morphology and velocity (i.e. speed and direction) in a controlled laboratory environment using a flume but also needs to be adaptable to work in a real river.<br><br> Measuring the 3D topographic characteristics and velocity field of a flowing water surface is difficult and the purpose of this paper is to describe recent experimental work to achieve this. After reviewing past work in this area, the use of close range digital photogrammetry for capturing both the 3D water surface and surface velocity is described. The selected approach uses either two or three synchronised digital SLR cameras in combination with PhotoModeler for data processing, a commercial close range photogrammetric package. One critical aspect is the selection and distribution of appropriate floating marker points, which are critical if automated and appropriate measurement methods are to be used. Two distinct targeting approaches are available: either large and distinct specific floating markers or some fine material capable of providing appropriate texture. Initial work described in this paper uses specific marker points, which also provide the potential measuring surface velocity. The paper demonstrates that a high degree of measurement and marking automation is possible in a flume environment, where lighting influences can be highly controlled. When applied to a real river it is apparent that only lower degrees of automation are practicable. The study has demonstrated that although some automation is possible for point measurement, point matching needs to be manually guided in a natural environment where lighting cannot be controlled.

scholarly journals Measuring Surface Velocity of Water Flow by Dense Optical Flow Method

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2320
Author(s):  
Wu ◽  
Zhao ◽  
Gan ◽  
Ma
Keyword(s):  
Optical Flow ◽  
Water Flow ◽  
Video Processing ◽  
Processing Technology ◽  
Surface Velocity ◽  
Flow Method ◽  
Optical Flow Method ◽  
Dense Optical Flow ◽  
Measuring Surface ◽  
Relative Errors

Recent advances in video processing technology have provided a new approach to measuring the surface velocity of water flow (SVWF). However, most of the previous researches using video processing technology depended on tracers for target tracing, requiring spraying tracers in the measurement process. These methods are not convenient for velocity measurement. In this study, a dense optical flow method (Farneback optical flow method) was used to process the water flow video to get the estimated SVWFs. The estimated SVWFs were verified by the actual SVWFs measured by a portable propeller velocimeter. The regression analyses between the estimated SVWFs and the measured SVWFs were conducted. The coefficient of determinations (R2) of the estimated and the measured SVWFs in different test regions are between 0.81 and 0.85. The average relative errors of the estimated and the measured SVWFs in all test regions are no more than 6.5%. The results indicate that the method had a good accuracy in estimating the SVWF and is a feasible and promising approach to analyzing the surface velocity distribution of water flow.

A Low-Cost Method for Measuring Surface Currents and Modeling Drifting Objects

2011 ◽  
Vol 60 (3) ◽  
pp. 980-989 ◽  
Author(s):  
Huang-Chen Lee ◽  
Chun-Yu Lin ◽  
Chun-Han Lin ◽  
Sheng-Wen Hsu ◽  
Chung-Ta King
Keyword(s):  
Low Cost ◽  
Surface Currents ◽  
Measuring Surface

scholarly journals Development of Aerial Space Time Volume Velocimetry for Measuring Surface Velocity Vector Distribution from UAV

2018 ◽  
Vol 40 ◽  
pp. 06011 ◽  
Author(s):  
Issei Tsuji ◽  
Kojiro Tani ◽  
Ichiro Fujita ◽  
Yuichi Notoya
Keyword(s):  
Flow Direction ◽  
Video Camera ◽  
Space Time ◽  
Surface Velocity ◽  
Measuring Surface ◽  
Snowmelt Flood ◽  
Vector Distribution ◽  
Aerial Vehicle ◽  
Static Images ◽  
Volumetric Texture

Due to the remarkable development of unmanned aerial vehicle (UAV) in recent years, its application in river engineering increases widely mainly for the measurement of ground topography such as by the technique Structure from Motion (SfM) using a series of high-resolution static images. However, although UAV usually installed a high density video camera, the use of the movie is limited just for watching and observing the geometrical feature of the ground. In the light of such a present status, the authors have developed an aerial space-time image velocimetry (STIV) technique to measure streamwise river surface velocity distributions. However, as STIV is insensitive to the change of flow direction, the aerial space-time volume velocimetry (STVV) technique, which is an extension of STIV, was developed in this research. STVV examines the change of volumetric texture within a space-time volume (STV) instead of examining the change of image intensity on a line segment as in STIV. The performance of STVV was investigated during the measurement of snowmelt flood of the Shinano River by comparing it with those obtained by the other techniques such as STIV, LSPIV and ADCP. It was made clear the aerial STVV has a great advantage over the existing image-based techniques.

scholarly journals Measurement Characteristics of Near-Surface Currents from Ultra-Thin Drifters, Drogued Drifters, and HF Radar

2018 ◽  
Vol 10 (10) ◽  
pp. 1633 ◽  
Author(s):  
Steven Morey ◽  
Nicolas Wienders ◽  
Dmitry Dukhovskoy ◽  
Mark Bourassa
Keyword(s):  
High Frequency ◽  
Measurement Techniques ◽  
Hf Radar ◽  
Stokes Drift ◽  
Surface Velocity ◽  
Surface Currents ◽  
Material Transport ◽  
Surface Shear ◽  
Near Surface ◽  
Radar Velocity

Concurrent measurements by satellite tracked drifters of different hull and drogue configurations and coastal high-frequency radar reveal substantial differences in estimates of the near-surface velocity. These measurements are important for understanding and predicting material transport on the ocean surface as well as the vertical structure of the near-surface currents. These near-surface current observations were obtained during a field experiment in the northern Gulf of Mexico intended to test a new ultra-thin drifter design. During the experiment, thirty small cylindrical drifters with 5 cm height, twenty-eight similar drifters with 10 cm hull height, and fourteen drifters with 91 cm tall drogues centered at 100 cm depth were deployed within the footprint of coastal High-Frequency (HF) radar. Comparison of collocated velocity measurements reveals systematic differences in surface velocity estimates obtained from the different measurement techniques, as well as provides information on properties of the drifter behavior and near-surface shear. Results show that the HF radar velocity estimates had magnitudes significantly lower than the 5 cm and 10 cm drifter velocity of approximately 45% and 35%, respectively. The HF radar velocity magnitudes were similar to the drogued drifter velocity. Analysis of wave directional spectra measurements reveals that surface Stokes drift accounts for much of the velocity difference between the drogued drifters and the thin surface drifters except during times of wave breaking.

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