Evaluating high-frequency radar data assimilation impact in coastal ocean operational modelling

Abstract. The impact of the assimilation of HFR (high-frequency radar) observations in a high-resolution regional model is evaluated, focusing on the improvement of the mesoscale dynamics. The study area is the Ibiza Channel, located in the western Mediterranean Sea. The resulting fields are tested against trajectories from 13 drifters. Six different assimilation experiments are compared to a control run (no assimilation). The experiments consist of assimilating (i) sea surface temperature, sea level anomaly, and Argo profiles (generic observation dataset); the generic observation dataset plus (ii) HFR total velocities and (iii) HFR radial velocities. Moreover, for each dataset, two different initialization methods are assessed: (a) restarting directly from the analysis after the assimilation or (b) using an intermediate initialization step applying a strong nudging towards the analysis fields. The experiments assimilating generic observations plus HFR total velocities with the direct restart provide the best results, reducing by 53 % the average separation distance between drifters and virtual particles after the first 48 h of simulation in comparison to the control run. When using the nudging initialization step, the best results are found when assimilating HFR radial velocities with a reduction of the mean separation distance by around 48 %. Results show that the integration of HFR observations in the data assimilation system enhances the prediction of surface currents inside the area covered by both antennas, while not degrading the correction achieved thanks to the assimilation of generic data sources beyond it. The assimilation of radial observations benefits from the smoothing effect associated with the application of the intermediate nudging step.

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Evaluating High-Frequency radar data assimilation impact in coastal ocean operational modelling

10.5194/os-2021-34 ◽

2021 ◽

Author(s):

Jaime Hernandez-Lasheras ◽

Baptiste Mourre ◽

Alejandro Orfila ◽

Alex Santana ◽

Emma Reyes ◽

...

Keyword(s):

High Frequency ◽

Radar Data ◽

Separation Distance ◽

Western Mediterranean ◽

Radial Velocities ◽

Optimal Interpolation ◽

Coverage Area ◽

High Frequency Radar ◽

Western Mediterranean Sea ◽

The Impact

Abstract. The impact of the assimilation of HFR (High-Frequency Radar) observations in a high-resolution regional model is evaluated, focusing on the improvement of the mesoscale dynamics. The study area is the Ibiza Channel, located in the Western Mediterranean Sea. The resulting fields are tested against trajectories from 13 drifters. Six different assimilation experiments are compared to a control run (no assimilation). The experiments consists in assimilating (i) Sea surface temperature, sea level anomaly and Argo profiles (generic observation dataset); the generic observation dataset plus (ii) HFR total velocities and (iii) HFR radial velocities. Moreover, for each dataset two different initialization methods are assessed: a) restarting directly from the analysis after the assimilation or b) using an intermediate initialization step applying a strong nudging towards the analysis fields. The experiments assimilating generic observations plus HFR total velocities with the direct restart provides the best results, improving by 53 % the average separation distance between drifters and virtual particles after the first 48 hours of simulation in comparison to the control run. When using the nudging initialization step, the best results are found when assimilating HFR radial velocities, with a reduction of the mean separation distance by around 48 %. Results show the capability of the Ensemble Optimal Interpolation data-assimilative system to correct surface currents not only inside but also beyond the HFR coverage area. The assimilation of radial observations benefits from the smoothing effect associated with the application of the intermediate nudging step.

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Comparing High Frequency Radar radial and total derived observations capability to correct surface currents using Data Assimilation

10.5194/egusphere-egu21-15588 ◽

2021 ◽

Author(s):

Jaime Hernandez Lasheras ◽

Baptiste Mourre ◽

Alejandro Orfila ◽

Alex Santana ◽

Emma Reyes ◽

...

Keyword(s):

Data Assimilation ◽

High Frequency ◽

Separation Distance ◽

Surface Currents ◽

High Frequency Radar ◽

Sensing Technology ◽

Motion Speed ◽

Series Of Experiments ◽

Surface Drifters ◽

Using Data

High Frequency Radars (HFR) are a mature remote sensing technology which is widely used in ocean observing systems to monitor surface currents in coastal areas. &#160;HFR systems are composed of 2 or more antennas which measure water motion speed along certain bearings, providing radial observations, which are later on postprocessed and mapped to generate orthogonal currents observations (u, v), herein named Totals.Both Radial and Total observations have been used to correct surface currents through data assimilation in numerous works in the past years, but, in our opinion, there is a lack of studies comparing the performance of both types of data. Here we present a series of experiments evaluating the capabilities of HFR to correct surface currents in the Ibiza Channel using data assimilation. We put special interest in assessing the potentialities of whether using radial or total observations and also their capabilities in a real operational context.A Lagrangian assessment using a set of 14 surface drifters deployed in the area allows to evaluate the performance of both kinds of observations, showing how the separation distance between drifting buoys and virtual particles is reduced in both cases.

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The impact of storm-induced coastal trapped waves on the transport of marine debris using high-frequency radar data

2019 IEEE/OES Twelfth Current, Waves and Turbulence Measurement (CWTM) ◽

10.1109/cwtm43797.2019.8955266 ◽

2019 ◽

Author(s):

Kelsey Brunner ◽

Kamazima M. M. Lwiza

Keyword(s):

High Frequency ◽

Radar Data ◽

Marine Debris ◽

Trapped Waves ◽

High Frequency Radar ◽

Coastal Trapped Waves ◽

The Impact

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High Frequency Radar Data Assimilation in the Monterey Bay

Estuarine and Coastal Modeling (2001) ◽

10.1061/40628(268)27 ◽

2002 ◽

Author(s):

I. Shulman ◽

C.-R. Wu ◽

J. D. Paduan ◽

J. K. Lewis ◽

L. K. Rosenfeld ◽

...

Keyword(s):

Data Assimilation ◽

High Frequency ◽

Radar Data ◽

Monterey Bay ◽

High Frequency Radar ◽

Radar Data Assimilation

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Sea Surface Circulation Structures in the Malta-Sicily Channel from Remote Sensing Data

Water ◽

10.3390/w11081589 ◽

2019 ◽

Vol 11 (8) ◽

pp. 1589 ◽

Cited By ~ 1

Author(s):

Reyes Suarez ◽

Cook ◽

Gačić ◽

Paduan ◽

Drago ◽

...

Keyword(s):

High Frequency ◽

Remote Sensing Data ◽

Radar Data ◽

Western Mediterranean ◽

Sea Surface ◽

Kinetic Properties ◽

Dynamic Topography ◽

High Frequency Radar ◽

Surface Circulation ◽

Sicily Channel

The Malta-Sicily Channel is part of the Sicily Channel system where water and thermohaline properties between the Eastern and Western Mediterranean basins take place. Several mesoscales features are detached from the main circulation due to wind and bathymetric forcing. In this paper, surface circulation structures are studied using different remotely sensed datasets: satellite data (absolute dynamic topography, Cross-Calibrated Multi-Platform wind vector analysis, satellite chlorophyll and sea surface temperature) and high frequency radar data. We identified high frequency motions (at short time scales—hours to days), as well as mesoscale structures fundamental for the understanding of the Malta-Sicily Channel circulation dynamics. One of those is the Malta-Sicily Gyre; an anticyclonic structure trapped between the Sicilian and Maltese coasts, which is poorly studied in the literature and often confused with the Malta Channel Crest and the Ionian Shelf Break Vortex. In order to characterize this gyre, we calculated its kinetic properties taking advantage of the fine-scale temporal and spatial resolution of the high frequency radar data, and thus confirming its presence with an updated version of the surface circulation patterns in the area.

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On the Performance of High Frequency Radar in the Western Mediterranean During the Record-Breaking Storm Gloria

Frontiers in Marine Science ◽

10.3389/fmars.2021.645762 ◽

2021 ◽

Vol 8 ◽

Cited By ~ 3

Author(s):

Pablo Lorente ◽

Jue Lin-Ye ◽

Manuel García-León ◽

Emma Reyes ◽

Maria Fernandes ◽

...

Keyword(s):

High Frequency ◽

Mixed Layer Depth ◽

Three Dimensional ◽

Surface Current ◽

Western Mediterranean ◽

Ocean Model ◽

Transport Processes ◽

Instantaneous Rate ◽

High Frequency Radar ◽

The Impact

Storm Gloria (January 19–24, 2020) hit the NW Mediterranean Sea with heavy rainfall, strong easterly winds, and very high waves, causing structural damages and 13 fatalities. The low-lying Ebro Delta (ED) region was severely inundated, ruining rice fields and seaside promenades. A variety of Copernicus Marine Environment Monitoring Service (CMEMS) modeling and observational products were jointly used to examine the fingerprint of Gloria and the response of the upper oceanic layer. According to the results, Gloria can be interpreted as a high-impact once-in-a-decade metocean event where various historical records were beaten. The 99th percentile of several parameters (wind speed, significant wave height, wave period, and surface current velocity), derived from long-term observational time series, was persistently exceeded. The atmospheric surge, albeit not negligible, exerted a secondary role in ED. The ability of a high-frequency radar deployed in this region (HFR-ED) to characterize the striking features of the storm was quantified from both waves and circulation aspects. Consistent radar current observations were subsequently compared against the 5-day-ahead forecast of CMEMS Iberia-Biscay-Ireland (IBI) regional ocean model to determine, from an Eulerian perspective, the strengths and shortcomings in its predictive capabilities. Time-averaged maps of surface circulation, superimposed with fields of Instantaneous Rate of Separation (IROS), were derived to resolve flow features and identify areas of elevated particles dispersion, respectively. The mean and P99 values of IROS almost doubled the historical statistics in the vicinity of the northern Ebro hemidelta. Although IBI predicted moderately well basic features of the storm-induced circulation, results suggests that coastal transport processes, likely modulated by wave-current interactions, were not fully captured. Furthermore, current estimations from other two radar systems, overlooking immediate choke points like the Ibiza Channel and the Strait of Gibraltar, evidenced Gloria’s remote-effect in the anomalous circulation patterns observed, that altered the usual water exchanges between adjacent sub-basins. Finally, three-dimensional outcomes from IBI were used to elucidate the impact of this moving storm at different depth levels. Data analyses illustrated that Gloria caused a large increase in kinetic energy and a significant deepening of the mixed layer depth.

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Inversion of Wave-number Spectrum from Simulated Bistatic High-frequency Radar Data

JOURNAL OF ELECTRONICS INFORMATION TECHNOLOGY ◽

10.3724/sp.j.1146.2011.00193 ◽

2011 ◽

Vol 33 (10) ◽

pp. 2477-2482

Author(s):

Huan He ◽

Heng-yu Ke ◽

Xian-rong Wan ◽

Fang-zhi Geng

Keyword(s):

High Frequency ◽

Radar Data ◽

Wave Number ◽

High Frequency Radar

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Predictability of Deep Convection in Idealized and Operational Forecasts: Effects of Radar Data Assimilation, Orography, and Synoptic Weather Regime

Monthly Weather Review ◽

10.1175/mwr-d-19-0045.1 ◽

2019 ◽

Vol 148 (1) ◽

pp. 63-81 ◽

Cited By ~ 10

Author(s):

Kevin Bachmann ◽

Christian Keil ◽

George C. Craig ◽

Martin Weissmann ◽

Christian A. Welzbacher

Keyword(s):

Data Assimilation ◽

Deep Convection ◽

Radar Data ◽

Ensemble Prediction ◽

Small Scale ◽

Model Errors ◽

Ensemble Prediction System ◽

Beneficial Impact ◽

The Impact ◽

Radar Data Assimilation

Abstract We investigate the practical predictability limits of deep convection in a state-of-the-art, high-resolution, limited-area ensemble prediction system. A combination of sophisticated predictability measures, namely, believable and decorrelation scale, are applied to determine the predictable scales of short-term forecasts in a hierarchy of model configurations. First, we consider an idealized perfect model setup that includes both small-scale and synoptic-scale perturbations. We find increased predictability in the presence of orography and a strongly beneficial impact of radar data assimilation, which extends the forecast horizon by up to 6 h. Second, we examine realistic COSMO-KENDA simulations, including assimilation of radar and conventional data and a representation of model errors, for a convectively active two-week summer period over Germany. The results confirm increased predictability in orographic regions. We find that both latent heat nudging and ensemble Kalman filter assimilation of radar data lead to increased forecast skill, but the impact is smaller than in the idealized experiments. This highlights the need to assimilate spatially and temporally dense data, but also indicates room for further improvement. Finally, the examination of operational COSMO-DE-EPS ensemble forecasts for three summer periods confirms the beneficial impact of orography in a statistical sense and also reveals increased predictability in weather regimes controlled by synoptic forcing, as defined by the convective adjustment time scale.

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