Validation of HF Radar Measurements

Chapman, R.D.; Graber, Hans C.

doi:10.5670/oceanog.1997.28

Cited by 77 publications

(32 citation statements)

References 12 publications

(9 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Ohlmann et al (2007) attributed about 5 cm s 21 rmsd to spatial sampling differences in their study case. On the other hand, currents may have larger variability on the midshelf than the inner shelf (e.g., Liu and Weisberg 2005b); the spatial inhomogeneity in currents also contributes to the rmsd between HF radar and ADCP data (e.g., Chapman and Graber 1997). Examining another offshore mooring, C13, the CODAR SeaSonde-ADCP radial comparisons (Fig.…”

Section: ) Codar Seasonde Versus Adcpmentioning

confidence: 98%

“…Two or more radial current maps with overlapping areas may be combined in the least squares sense (Lipa and Barrick 1983) to get velocity vectors using a prescribed geometrical dilution of precision (GDOP; e.g., Chapman et al 1997). During this combining process, the radial errors may be transformed into the velocity errors (e.g., Barth et al 2010), depending on the angle at which the radial currents intersect.…”

Section: Total Velocitymentioning

confidence: 99%

“…With the advancement of ocean-current-measuring technologies, acoustic Doppler current profilers (ADCPs) were then also used to validate HF radar-derived currents (e.g., Graber et al 1997). An early review of HF radar validation is provided by Chapman and Graber (1997). With the increasing number of deployments of HF radars for measuring currents in coastal oceans, validations against a variety of in situ observations have expanded considerably in the last two decades, both for CODAR (e.g., Emery et al 2004;Paduan et al 2006;Ohlmann et al 2007;Cosoli et al 2010;Kohut et al 2012) and WERA (e.g., Shay et al 2007;Savidge et al 2011;Robinson et al 2011).…”

Section: Introductionmentioning

confidence: 98%

See 2 more Smart Citations

Assessment of CODAR SeaSonde and WERA HF Radars in Mapping Surface Currents on the West Florida Shelf*

Liu

Weisberg

Merz

2014

Journal of Atmospheric and Oceanic Technology

View full text Add to dashboard Cite

Concurrently operated on the West Florida shelf for the purpose of observing surface currents are three long-range (4.9 MHz) Coastal Ocean Dynamics Applications Radar (CODAR) SeaSonde and two medianrange (12.7 MHz) Wellen Radar (WERA) high-frequency (HF) radar systems. These HF radars overlook an array of moored acoustic Doppler current profilers (ADCPs), three of which are presently within the radar footprint. Analyzed herein are 3 months of simultaneous observations. Both the SeaSonde and WERA systems generally agree with the ADCPs to within root-mean-square differences (rmsd) for hourly radial velocity components of 5.1-9.2 and 3.8-6.5 cm s 21 for SeaSonde and WERA, respectively, and within rmsd for 36-h low-pass filtered radial velocity components of 2.8-6.0 and 2.2-4.3 cm s 21 for SeaSonde and WERA, respectively. The bearing offset and tidal and subtidal currents of total velocities are also assessed using the ADCP data. Despite differences in a variety of aspects between the direction-finding CODAR SeaSonde (long range, effective depth of 2.4 m, integration time of 4 h, and idealized antenna patterns) and the beamforming WERA (median range, effective depth of 0.9 m, and integration time of 1 h), both HF radar systems demonstrated good surface current mapping capability. The differences between the velocities measured with the HF radar and the ADCP are sufficiently small in this low-energy shelf that much of these rmsd values may be accounted for by the expected measurement differences due to the horizontal, vertical, and temporal sampling differences of the ocean current observing systems used.

show abstract

Section: ) Codar Seasonde Versus Adcpmentioning

confidence: 98%

Section: Total Velocitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

See 1 more Smart Citation

Assessment of CODAR SeaSonde and WERA HF Radars in Mapping Surface Currents on the West Florida Shelf*

Liu

Weisberg

Merz

2014

Journal of Atmospheric and Oceanic Technology

View full text Add to dashboard Cite

show abstract

“…al. [3] as Geometric Dilution Of Precision (GDOP). These uncertainties increase along the baseline between the coastal sites as well as well offshore.…”

Section: A Hf Radar Surface Current Processingmentioning

confidence: 99%

The Mid-Atlantic Regional Coastal Ocean Observing System: Serving coast guard needs in the mid-atlantic bight

Kohut

Roarty

Licthenwalner

et al. 2008

2008 IEEE/OES US/EU-Baltic International Symposium

View full text Add to dashboard Cite

and an array of meteorological stations will feed 4 operational numerical modeling systems. The HF radar network provides near realtime surface current observations along 1000 km of coastline with varying coverage from the coast out to the shelf break. The primary goal is to operate the regional system in a coordinated way to guarantee the delivery of quality ocean current and wave data. In this paper we present MARCOOS with an emphasis on the HF Radar network. Particular attention is placed on the setup, operation, and application of the network. Quality control metrics based on comparisons with Coast Guard deployed surface drifters (SLDMBs) have a specific focus to quantifying the uncertainty in the HF radar surface current estimates as applied to search and rescue observations. These metrics will be used to ensure that quality data is going to the Coast Guard and that this information is properly incorporated into existing search planning tools.

show abstract

“…21,16 The GDOP uncertainty increases with the distance from the HF radar stations and reaches a maximum along the periphery of the HF radar data footprint, and along the baseline (line connecting the HF radar stations). In order to improve the HF radar data quality, the present study used a GDOP uncertainty threshold value of less than 1.5cm s −1 , and the maximum radial and total current magnitudes were limited to 1.5m s −1 .…”

Section: Ocean Observations Hf Radar Observationsmentioning

confidence: 99%

Assimilation of HF radar-derived surface currents on tidal-timescales

Gopalakrishnan

Blumberg

2012

Journal of Operational Oceanography

View full text Add to dashboard Cite

A surface current observation system based on high-frequency (HF) radar has been developed for Raritan Bay and the coastal waters of New York and New Jersey. An HF radar network provides synoptic surface current maps in near-real-time that can be optimally combined with ocean circulation models using data assimilation (DA) framework to obtain the best possible estimate of a three-dimensional ocean state. A nudging or Newtonian damping scheme has been developed to assimilate HF radar data into an estuarine and coastal ocean circulation model. This model, with an extensive embedded real-time observational network, is called the New York Harbour Observing and Prediction System (NYHOPS). A nudging parameter is introduced into the equations of motion which affects the model dynamics. The data is imparted to neighbouring (threedimensional) grid points via model dynamics. The impact of HF radar DA is analysed by computing the DA skill score (DA skill ) based on the mean-square-error (mse). The DA skill is computed by comparing non-assimilated and assimilated model solutions with in-situ observations of three-dimensional currents, temperature and salinity, which have not been included in the assimilation. A positive DA skill (0∼1) represents an improvement in the model performance by assimilation. HF radar data covering Raritan Bay and the New York Bight (NYB) Apex were assimilated into the NYHOPS model in the model hindcast cycle (−24h to 0h) on a daily forecast basis for a period of 40 days. The DA skill is assessed with respect to the NYHOPS model hindcasts (daily model solutions from −24h to 0h) as well as the first day forecasts (daily model solutions from 0h to 24h). HF radar DA improved the NYHOPS model performance during both the hindcast and forecast periods. The model skill metrics for the near-surface layers in the inner-NJ shelf region shows a hindcast DA skill of 24% (14%) and forecast DA skill of 18% (7%) for horizontal velocities u: east-west component (v: north-south component), and a hindcast DA skill of 33% (38%) and forecast DA skill of 25% (30%) for temperature (salinity). The nudging scheme is robust and efficient for the HF radar DA into the NYHOPS operational forecast model. The NYHOPS-HF radar DA system is capable of importing in the observations and produce useful hindcasts/forecasts with minimum computational expense.76

show abstract

Validation of HF Radar Measurements

Cited by 77 publications

References 12 publications

Assessment of CODAR SeaSonde and WERA HF Radars in Mapping Surface Currents on the West Florida Shelf*

Assessment of CODAR SeaSonde and WERA HF Radars in Mapping Surface Currents on the West Florida Shelf*

The Mid-Atlantic Regional Coastal Ocean Observing System: Serving coast guard needs in the mid-atlantic bight

Assimilation of HF radar-derived surface currents on tidal-timescales

Contact Info

Product

Resources

About