Hindcasting and Forecasting of Surface Flow Fields through Assimilating High Frequency Remotely Sensing Radar Data

Ren, Lei; Hartnett, Michael

doi:10.3390/rs9090932

Cited by 6 publications

(3 citation statements)

References 42 publications

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“…Bandwidth of both radars is 500 kHz. The data are transmitted directly to a central data management platform located at National University of Ireland, Galway [21].…”

Section: Codar Systemmentioning

confidence: 99%

The Effect of Wind Forcing on Modeling Coastal Circulation at a Marine Renewable Test Site

2017

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Abstract:The hydrodynamic circulation in estuaries is primarily driven by tides, river inflows and surface winds. While tidal and river data can be quite easily obtained for input to hydrodynamic models, sourcing accurate surface wind data is problematic. Inaccurate wind data can lead to inaccuracies in the surface currents computed by three-dimensional hydrodynamic models. In this research, a high-resolution wind model was coupled with a three-dimensional hydrodynamic model of Galway Bay, a semi-enclosed estuary on the west coast of Ireland, to investigate the effect of wind forcing on model accuracy. Two wind-forcing conditions were investigated: (1) using wind data measured onshore on the NUI Galway campus (NUIG) and (2) using offshore wind data provided by a high resolution wind model (HR). A scenario with no wind forcing (NW) was also assessed. The onshore wind data varied with time but the speed and direction were applied across the full model domain. The modeled offshore wind fields varied with both time and space. The effect of wind forcing on modeled hydrodynamics was assessed via comparison of modeled surface currents with surface current measurements obtained from a High-Frequency (HF) radar Coastal Ocean Dynamics Applications Radar (CODAR) observation system. Results indicated that winds were most significant in simulating the north-south surface velocity component. The model using high resolution temporally-and spatially-varying wind data achieved better agreement with the CODAR surface currents than the model using the onshore wind measurements and the model without any wind forcing.

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“…Bandwidth of both radars is 500 kHz. The data are transmitted directly to a central data management platform located at National University of Ireland, Galway [21].…”

Section: Codar Systemmentioning

confidence: 99%

The Effect of Wind Forcing on Modeling Coastal Circulation at a Marine Renewable Test Site

2017

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“…(Barrick and Lipa, 1986;Laws et al, 2010;Lai et al, 2017;Tian et al, 2019) 할 것으로 사료된다 (Lee et al, 2008;Röhrs et al, 2015). 용되고 있다 (Wyatt, 2012;Abascal et al, 2017;Ren and Hartnett et al, 2017;Zhang et al, 2020). (…”

Section: 제주 남부 해수면 관측레이더 구축mentioning

confidence: 99%

Current Status and Future Plans for Surface Current Observation by HF Radar in the Southern Jeju

Jung¹,

Kim²,

Kwon³

et al. 2022

J Korean Soc Coast Ocean Eng

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The southern strait of Jeju is a divergence point of the Tsushima Warm Current (TWC), and it is the starting point of the thermohaline circulation in the waters of the Korean Peninsula, affecting the size and frequency of marine disasters such as typhoons and tsunamis, and has a very important oceanographic impact, such as becoming a source of harmful organisms and radioactively contaminated water. Therefore, for an immediate response to these maritime disasters, real-time ocean observation is required. However, compared to other straits, in the case of southern Jeju, such wide area marine observations are insufficient. Therefore, in this study, surface current field of the southern strait of Jeju was calculated using High-Frequency radar (HF radar). the large surface current field is calculated, and post-processing and data improvement are carried out through APM (Antenna Pattern Measurement) and FOL (First Order Line), and comparative analysis is conducted using actual data. As a result, the correlation shows improvement of 0.4~0.7 and RMSE of about 1~19 cm/s. These high-frequency radar observation results will help solve domestic issues such as response to typhoons, verification of numerical models, utilization of wide area wave data, and ocean search and rescue in the future through the establishment of an open data network.

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“…Haines et al implemented a QC method using non-velocity metrics of the signal quality and solutions to address the challenge of the coexistence of high and low currents [21]. Ren et al applied a nudging data assimilation algorithm to incorporate real-time HFR current measurements into a numerical model, which improved the predictive capability of the numerical model [22]. Cosoli et al developed a real-time and offline QC methodology based on the determination of Doppler line SNR values that contribute to hourly radial current at each range-bearing pair for the SeaSonde [23,24].…”

Section: Introductionmentioning

confidence: 99%

Quality Control for Ocean Current Measurement Using High-Frequency Direction-Finding Radar

He,

Zhou,

Tian

et al. 2023

Remote Sensing

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High-frequency radars (HFRs) are important for remote sensing of the marine environment due to their ability to provide real-time, wide-coverage, and high-resolution measurements of the ocean surface current, wave height, and wind speed. However, due to the intricate multidimensional processing demands (e.g., time, Doppler, and space) for internal data and effective suppression of external noise, conducting quality control (QC) on radar-measured data is of great importance. In this paper, we first present a comprehensive quality evaluation model for both radial current and synthesized vector current obtained by direction-finding (DF) HFRs. In the proposed model, the quality factor (QF) is calculated for each current cell to evaluate its reliability. The QF for the radial current depends on the signal-to-noise ratio (SNR) and DF factor of the first-order Bragg peak region in the range–Doppler (RD) spectrum, and the QF for the synthesized vector current can be calculated using an error propagation model based on geometric dilution of precision (GDOP). A QC method is then proposed for processing HFR-derived surface current data via the following steps: (1) signal preprocessing is performed to minimize the effect of unwanted external signals such as radio frequency interference and ionospheric clutter; (2) radial currents with low QFs and outliers are removed; (3) the vector currents with low QFs are also removed before spatial smoothing and interpolation. The proposed QC method is validated using a one-month-long dataset collected by the Ocean State Monitoring and Analyzing Radar, model S (OSMAR-S). The improvement in the current quality is proven to be significant. Using the buoy data as ground truth, after applying QC, the correlation coefficients (CCs) of the radial current, synthesized current speed, and synthesized current direction are increased by 4.33~102.91%, 1.04~90.74%, and 1.20~62.67%, respectively, and the root mean square errors (RMSEs) are decreased by 2.51~49.65%, 7.86~27.22%, and 1.68~28.99%, respectively. The proposed QC method has now been incorporated into the operational software (RemoteSiteConsole v1.0.0.65) of OSMAR-S.

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Hindcasting and Forecasting of Surface Flow Fields through Assimilating High Frequency Remotely Sensing Radar Data

Cited by 6 publications

References 42 publications

The Effect of Wind Forcing on Modeling Coastal Circulation at a Marine Renewable Test Site

The Effect of Wind Forcing on Modeling Coastal Circulation at a Marine Renewable Test Site

Current Status and Future Plans for Surface Current Observation by HF Radar in the Southern Jeju

Quality Control for Ocean Current Measurement Using High-Frequency Direction-Finding Radar

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