Assessing the fidelity of surface currents from a coastal ocean model and HF radar using drifting buoys in the Middle Atlantic Bight
- First Online:
- Cite this article as:
- Kuang, L., Blumberg, A.F. & Georgas, N. Ocean Dynamics (2012) 62: 1229. doi:10.1007/s10236-012-0556-2
- 222 Views
The rapid expansion of urbanization along the world’s coastal areas requires a more comprehensive and accurate understanding of the coastal ocean. Over the past several decades, numerical ocean circulation models have tried to provide such insight, based on our developing understanding of physical ocean processes. The systematic establishment of coastal ocean observation systems adopting cutting-edge technology, such as high frequency (HF) radar, satellite sensing, and gliders, has put such ocean model predictions to the test, by providing comprehensive observational datasets for the validation of numerical model forecasts. The New York Harbor Observing and Prediction System (NYHOPS) is a comprehensive system for understanding coastal ocean processes on the continental shelf waters of New York and New Jersey. To increase confidence in the system’s ocean circulation predictions in that area, a detailed validation exercise was carried out using HF radar and Lagrangian drifter-derived surface currents from three drifters obtained between March and October 2010. During that period, the root mean square (RMS) differences of both the east–west and north–south currents between NYHOPS and HF radar were approximately 15 cm s−1. Harmonic analysis of NYHOPS and HF radar surface currents shows similar tidal ellipse parameters for the dominant M2 tide, with a mean difference of 2.4 cm s−1 in the semi-major axis and 1.4 cm s−1 in the semi-minor axis and 3° in orientation and 10° in phase. Surface currents derived independently from drifters along their trajectories showed that NYHOPS and HF radar yielded similarly accurate results. RMS errors when compared to currents derived along the trajectory of the three drifters were approximately 10 cm s−1. Overall, the analysis suggests that NYHOPS and HF radar had similar skill in estimating the currents over the continental shelf waters of the Middle Atlantic Bight during this time period. An ensemble-based set of particle tracking simulations using one drifter which was tracked for 11 days showed that the ensemble mean separation generally increases with time in a linear fashion. The separation distance is not dominated by high frequency or short spatial scale wavelengths suggesting that both the NYHOPS and HF radar currents are representing tidal and inertial time scales correctly and resolving some of the smaller scale eddies. The growing ensemble mean separation distance is dominated by errors in the mean flow causing the drifters to slowly diverge from their observed positions. The separation distance for both HF radar and NYHOPS stays below 30 km after 5 days, and the two technologies have similar tracking skill at the 95 % level. For comparison, the ensemble mean distance of a drifter from its initial release location (persistence assumption) is estimated to be greater than 70 km in 5 days.
KeywordsHF radarNYHOPSGNOMECoastal circulation modelDrifterDrifter-derived currentsModel validationModel skillParticle tracking
The modern world is experiencing the greatest human migration in history. The inland rural population is moving to the coast. Now over 50 % of the world’s population lives in coastal areas. In the USA alone, the figure is 80 % (U.S. National Academies 2010). In the largest coastal cities, the 136 port cities around the world that have more than one million inhabitants, there is a population of 400 million people. These urban coastal areas are especially susceptible to disruption from extremes of weather, tectonic forces, and human activity. Having an accurate knowledge of the currents that are found in coastal regions is important for various applications, such as search and rescue operations, coastal ecosystem management (e.g., tracking fish larvae and dispersal of pollutants; Fan et al. 2004; North et al. 2010), and tidal energy quantification and harvesting. Various ocean technologies, including satellite and other remote imaging (Dugan and Piotrowski 2003), high frequency radar (HF radar, Kohut et al. 2006; Parks et al. 2009; Roarty et al. 2010; Gurgel et al. 2011), satellite-tracked drifters (Fratantoni 2001; Poulain 2001), gliders (Rudnick et al. 2004), unmanned underwater vehicles, etc., have been deployed by oceanographers and meteorologists, to improve understanding of the ocean dynamics. Coastal ocean models have also come into their own right, predicting currents and other ocean constituents with considerable skill (e.g., Samelson et al. 2008; Georgas and Blumberg 2010; Gopalakrishnan and Blumberg 2012).
The Middle Atlantic Bight (MAB) is the part of the United States East Coast continental shelf that runs from Cape Cod, Massachusetts to Cape Hatteras, North Carolina. Its coastline is one of the most populous regions in the world. The understanding of currents and circulation in the MAB is of critical importance to the economic and social development in this region. The general circulation pattern has been studied extensively and is well understood. In general, the MAB has water characteristics that are typically lower in temperature and salinity than the adjacent offshore slope water (Brian 2009). Chang et al. (2002) showed that the general circulation in the MAB originates with the mixing of the Gulf of Maine and Scotian Shelf waters to the north as modified by local processes (seasonal heating, cooling, precipitation, and evaporation). This water flows southward over and around Georges Bank and proceeds past Cape Cod into the MAB region (Brian 2009). Physical processes associated with river/estuary systems, coastal bathymetry, and the shelf slope interact with this water mass within the MAB region. The water does not exit the MAB at the shelf break but rather runs along the shelf and exits to the south near Cape Hatteras (Brian 2009). Studies by Rasmussen et al. (2005) showed that the cross shelf transport at the shelf-slope edge (shelf break) is small and supports the notion of large along-shelf transport in the MAB. Between 75 and 90 % of the along-shelf sub-inertial current energy can be attributed to wind-forced motions and freely propagating waves (Noble et al. 1983).
Currents in the MAB are influenced by many processes, including tides, winds, river flows, and coastal and shelf break upwelling and downwelling. Energetic tidal currents have been identified along the US east coast shelf. The M2 tide is the dominant constituent and accounts for 80 % of tide energy in the central MAB. Spatial variability of the tidal currents between the Lower Hudson River and the Delaware Bay is found (Brian 2009). In the MAB, the subtidal flow along shelf is largely driven by winds and propagating free waves (Schulz et al. 2012). On the shelf break, there exists a cross-shelf geostrophic balance associated with a persistent along-shore jet that flows to the southwest (Flagg 1977). The Gulf Stream (Beardsley and Boicourt 1981) also affects the shelf break and outer shelf regions.
The development of land-based HF radar systems over the last several decades has provided a unique ocean observation platform capable of measuring near-surface ocean currents remotely from the shoreline. The HF radar system works on the principle of radio wave backscatter by ocean surface gravity waves in the frequency band 3–30 MHz and is capable of mapping ocean surface currents (~1 m deep) over a synoptic scale of the O (200 km) depending upon the transmitting frequency (Barrick et al. 1977; Paduan and Rosenfeld 1996; Paduan and Graber 1997; Graber et al. 1997). A HF radar network has been deployed for the MAB which provides shelf-wide realizations of surface currents every hour (Roarty et al. 2010). This HF radar observation system consists of more than 20 long-range stations, with locations all along the coast of the Middle Atlantic States.
At the same time, there exists a high fidelity coastal ocean forecast model of the same waters (Georgas and Blumberg 2010). The model is part of the New York Harbor Observing and Prediction System (NYHOPS), providing high spatial resolution predictions of water level, 3D circulation fields (currents, temperature, salinity, density, speed of sound), significant wave height, and period that are archived on an hourly basis for the coastal waters of New Jersey and New York.
In the present study, satellite-tracked drifters (Davis 1985) are used to validate the performance of both HF radar and NYHOPS from both Eulerian and Lagrangian perspectives in the MAB. The region is of interest for its importance as an urban coast and for being a highly productive biological zone. Here, we first comprehensively compare estimates of surface currents over the continental shelf portion of the MAB from the HF radar network data and the NYHOPS model predictions. Then, currents are determined from drifter locations over time along their trajectory and then compared to currents from the HF radar system and NYHOPS. And finally, particle-tracking-based simulations of drifter trajectories based on both the currents from the HF radar network and NYHOPS are compared to the observed drifter paths. Questions on the limit of useful trajectory predictions are then addressed. Limitations in both technologies (climatological boundary condition for NYHOPS and HF radar signal coverage) during the period of this study are also presented.
2.1 Data and models
In the present work, three realizations of surface currents from NYHOPS, HF radar, and drifters have been used for comparison purposes. Each will be briefly described.
The specific type of drifter used here is called the self-locating marker datum buoy (SLMDB). It transmits its location via the ARGOS satellite every 30 min. This type of drifter buoy is designed to stay in the ocean surface, follow the near-surface currents at a depth of 1 m, and have minimal windage effects (Davis 1985). A clear picture of the ocean flow patterns from a Lagrangian perspective is thus obtained in near real time.
NYHOPS is a 3D operational forecast model for the New York/New Jersey Harbor Estuary and surrounding waters (Bruno et al. 2006; Georgas et al. 2009; Georgas 2010). The extent of the NYHOPS computational domain covering the MAB is shown in Fig. 1. The domain is discretized on an Arakawa “C” finite-difference grid with 147 × 452 cells, 15,068 of which are designated as water, with a horizontal resolution varying from 25 m (estuary) to 7.5 km (outer shelf). The depth of this region varies from 2 to 200 m at the shelf break where the NYHOPS open boundary is located. NYHOPS is forced at the open ocean lateral boundaries by total water level, waves, climatological temperature and salinity; It is also forced internally with thermodynamic inputs from river, stream, water pollution control plant discharges, and thermal power plant intakes/outfalls. Spatially variable surface boundary conditions for wind and heating and cooling are included. Quadratic friction is applied at the bottom based on internally calculated friction coefficients that include wave boundary layer effects (Grant and Madsen 1979; Georgas et al. 2007; Georgas 2010) and at the free surface through assimilation of surface ice cover friction (Georgas 2012). Several comprehensive skill assessment studies have been carried out (Fan et al. 2006; Georgas et al. 2007; Bhushan et al. 2009; Georgas and Blumberg 2008, 2010; DiLiberto et al. 2011). Currents at depths of 1–5 m (depending on the depth of the surface-most sigma layer in the model) computed by NYHOPS during calendar year 2010 were retrieved from archived data and used in this study.
2.2 Estimation of surface currents from drifters
Deployment history of the SLDMB drifters used in this study
March 11, 2010
March 25, 2010
July 31, 2010
August 4, 2010
October 11, 2010
October 22, 2010
2.3 Assessment metrics
Continuous surface current time series from NYHOPS and HF radar, between March 5, 2010 and April 10, 2010, were used to calculate the tidal amplitude, phase, and current ellipse parameters based on the least-squares harmonic analysis following T_tide by Pawlowicz Rich et al. (2002). Results were compared to observed tidal ellipses from historic current meter data collected in the MAB, tabulated in Moody et al. (1984). This was done to evaluate the ability of each technology to simulate the tidal signal.
2.4 Lagrangian particle tracking
Lagrangian particle tracking models have been created and used in search and rescue planning, predicting distributions of fish larvae, and oil spill fate and transport. With this in mind, assessing the skill of a set of currents in combination with a Lagrangian particle tracking model is very useful and complementary. Here, surface current fields derived by NYHOPS and HF radar are put to the test of reproducing observed Lagrangian trajectories with the use of a particle tracking model. Numerical particles are released at the same initial location and starting time as the observed drifters; their trajectories are then simulated. The separation distance between simulated and observed drifters is analyzed as a metric for assessing estimator performance. In this study, drifter 3 (Fig. 1) is used for the particle tracking analysis given the fact that the data coverage in that region is comparatively better, and currents from both NYHOPS and HF radar are for the most part reasonable, as explained in Section 3.2.
Following the methodology developed by Ullman et al. (2006) for simulating drifters in the MAB, 1,000 numerical particles were released and were allowed to move with currents based on the input current field and diffuse based on a uniform diffusion coefficient, D, of 100 m2 s−1. A sensitivity study of the diffusion coefficient was first performed that involved decreasing and increasing the coefficient by an order of magnitude. The results were that the separation distance between the simulated and real drifter in both cases was indeed much larger than that using 100 m2 s−1. Due to the negligible lee-way of wind effects on SLMDB drifters (Davis 1985), no windage forcing was used in GNOME simulation for both NYHOPS and HF radar particle tracking predictions. The trajectory of drifter 3 was divided into daily release points (“reseeding points”). Five-day GNOME runs were initiated by releasing the particles at each reseeding point, saving the locations of the position hourly. Eight such runs were considered and factored in an ensemble analysis. The accuracy of the drifter trajectory prediction was measured here by the ensemble mean separation distance between the real drifter and the simulated one. That distance was put into perspective by considering the persistence error, that is, the ensemble mean separation distance if one were to assume that each reseeded drifter remained at its release location (Ullman et al. 2006). If the separation distance is less than the persistence error, then the technology (NYHOPS or HF radar) is qualitatively able to reproduce longer term mean flows.
3.1 Comparison between currents from NYHOPS and HF radar
The mean vector currents plotted in Fig. 2a have much in common. They both have the correct mean flow pattern. This mean flow is well known, based on hydrography, drifters, shipboard current profiles, and moored current observations (see Beardsley and Boicourt 1981 for an early summary; also Lentz 2008a, b) as well as numerical modeling over many years (Blumberg and Galperin 1990; Xu and Oey 2011). The mean surface flow is 2 to 12 cm s−1 directed southward on the shelf and offshore. The currents are smallest at the inner shelf and largest at the shelf break (Gong et al. 2010).
Both the HF radar and NYHOPS currents show strong currents flowing out of the eastern end of Long Island Sound in agreement with the currents observations of Gay et al. (2004). Only NYHOPS currents show the well-known flow exiting the NY/NJ Estuary (e.g., Chant et al. 2008). These are similar to those currents determined by Gong et al. (2010).
Calculated tidal ellipses are presented in Fig. 2b. The tidal ellipses are all traced clockwise in time and are generally oriented normal to isobaths (Moody et al. 1984). The tidal ellipses for NYHOPS and HF radar both exhibit the considerable observed spatial variability in amplitude and phase. Figure 2b (upper panel) shows that the tidal ellipses of NYHOPS agree well with observations for all 16 sites. HF radar-derived tidal ellipses are also similar. The difference between the HF radar and observed tidal ellipses is slightly larger at five sites (2, 4, 11, 15, and 16, Fig. 2b). The averaged misfits between observation and NYHOPS are 0.80 cm s−1 for semi-major axis and 0.38 cm s−1 for semi-minor axis and 18° in orientation and 25° in phase. The averaged misfits between observation and HF radar are 2.4 cm s−1 for semi-major axis and 1.4 cm s−1 for semi-minor axis and 22° in orientation and 35° in phase. The average difference between NYHOPS and HF radar is 1.6 cm s−1 for the semi-major axis and 1.1 cm s−1 for the semi-minor axis and 3° for orientation and 10° for phase. It is apparent that NYHOPS and HF radar capture tidal currents correctly.
The RMS difference for both the east–west and north–south components of the total surface currents between NYHOPS and HF radar is on the order of 15 cm s−1 for the majority of the MAB shelf region (Fig. 3). The RMS differences are as high as 50 cm s−1 in those areas where surface currents are usually strong, as in Delaware Bay, NY/NJ Estuary, Long Island Sound (Brian 2009; Chant et al. 2008). The normalized RMS difference of the east–west and north–south components of the surface currents between NYHOPS and HF radar by the maximal surface current has a value of 20 %. The normalized RMS difference of the east–west and north–south surface current components has similar distribution as the RMS difference (not shown). The normalized RMS differences are as high as 90 % in those areas with stronger surface currents. The spatially averaged ratio of the RMS difference to the standard deviation of the HF radar currents is 1.5 for both the east–west and north–south components of the surface currents. If the two datasets were in best agreement, one would expect this ratio to be less than unity. The RMS difference of the non-tidal currents between NYHOPS and HF radar is on the order of 12 cm s−1 for the majority of the MAB shelf region (not shown). This analysis implies that the difference between NYHOPS and HF radar is mostly from the non-tidal effects, due to meteorology, buoyant plumes common in the MAB and the influences of the offshore ocean. The difference of the representative depth of each technology is one factor that contributes to the differences between NYHOPS (the first sigma layer depth varies from 1 to 5 m) and HF radar (1 m depth). Consideration of surface shear and Ekman layer can also play a role in the discrepancies. Also, the quality of HF radar signal and its temporal/spatial coverage plays a big role in the accuracy of HF radar observation.
3.2 Comparison of surface currents—NYHOPS, HF radar, and drifters
Mean velocity of east–west (\( \overline u \)) and north–south (\( \overline v \)) near-surface current from drifters, NYHOPS, and HF radar and the mean speed of their mean vector velocity difference (MVVD, as described in the text) for the three drifter tracks in 2010
\( \overline u \) (cm s−1)
\( \overline v \) (cm s−1)
MVVD (cm s−1)
Root mean square difference (RMSD) of sea-surface currents ([u, (E–W)] and [v, (N–S)] component) between NYHOPS, HF radar, and drifters along the three drifter tracks in 2010
RMSD of u (cm s−1)
RMSD of v (cm s−1)
Drifter 1 was in the water for 14 days during March 2010. It was deployed in the northeastern portion of the shelf. It appears from Fig. 4 that both NYHOPS and HF radar are able to reproduce the currents over much of the period. HF radar retrievals were especially good during March 15 to 17 when there was a strong flow to the south due to sustained winds blowing from the northwest at over 10 m s−1. However, the difference between HF radar/NYHOPS and drifter is bigger at times when the wind is strong (Fig. 4). The difference is relatively smaller when the wind is much weaker, especially seen during March 17 to 20. The inertial oscillations shown in the drifter track between March 20 and March 25 are well reproduced by NYHOPS and less well in the HF radar signal. The RMS differences of the NYHOPS and HF radar surface current vs. the drifter are both on the order of 10 cm s−1 (Table 3). This statistic holds for both the east–west (u) and north–south (v) velocity components. Although the magnitude of the mean current was under-predicted by almost 50 % by both NYHOPS and HF radar [vector mean current differences (MVVD) of 5 to 6 cm s−1 for a 11-cm-s−1 mean current], the general westward direction of the mean current observed by the drifter was correctly reproduced by both technologies (Table 2). NYHOPS did better with regard to mean vector direction in all three paths. The differences of mean vector direction between NYHOPS and drifters 1, 2, and 3 are 9°, 10°, and 3°, respectively. However, the differences of mean vector direction between HF radar and drifters 1, 2, and 3 are higher, with their values of 25°, 169°, and 18°, respectively.
The region where drifter 2 was deployed, the entrance to the NY/NJ Estuary, was clearly not a region where the HF radar current was able to derive the currents correctly as shown in the time series of Fig. 5 (Gopalakrishnan 2011). This drifter was a short deployment of 4 days. The observed inertial oscillations were nicely reproduced in the NYHOPS currents for the entire period. The RMS error between the NYHOPS and the drifter currents was approximately 10 cm s−1, while the HF radar’s RMS errors were about double that, with errors sometimes exceeding 50 cm s−1. The NYHOPS vector mean currents were within 4 cm s−1 of the drifter observations.
The third track, covering 11 days in the fall of 2010, was located in the deeper waters on the southeast portion of the shelf. The time series shown in Fig. 6 suggest that both the NYHOPS and HF radar currents have periods when they agree well with the drifter currents and periods when they do not. The period between October 15 and 18, with surface winds over 10 m s−1 (Fig. 6), is captured by both the NYHOPS and HF radar currents. The mean vector velocity error was less than 1 cm s−1 for NYHOPS, while it was approximately equal to 9 cm s−1 for the HF radar currents. In general, the computed drifter currents are larger than the two other sets of currents, especially during October 20 to 22 (Fig. 6). During the period October 20 to 22, there is considerable error in both the model and HF radar currents when compared to the drifter-based currents. Based on available reanalysis from larger meteorological and hydrodynamic models that include the deeper ocean, it is hypothesized that the NYHOPS model results were degraded because the shelf break upwelling that existed at that time was not simulated in the model. The NYHOPS model shelf break forcing utilizes monthly temperature and salinity climatology and thus not able to simulate dynamic events originating in waters deeper than the shelf break. The shelf break upwelling event, coincident with frontal winds just offshore of the shelf break in the southern MAB, appears to have intensified the generally southwestward flowing current in the deeper area west of the Hudson canyon where the drifter was. Unrelated to this, the HF radar currents were in error because the coverage for track 3 at locations traveled during October 20 to 22 is relatively low (see the coverage map of HF radar total currents, Fig. 1, insert). This low coverage of the HF radar signal will lead to less accurate surface currents (Lentz 2008a). Considering the average currents, it is apparent that the drifter currents were larger than both the NYHOPS and, especially, HF radar-derived currents.
Overall, RMS errors against the drifter currents were found to be on the order of 10 cm s−1 for both u and v. Mean HF radar currents appear to be generally lower than the ones observed by the drifters. The skill of the HF radar was similar during this period as to that found by Ullman et al. (2006). The RMS errors against the drifter currents when the wind speed is larger than 5 m s−1 were also analyzed and were found on the order of 10 cm s−1 for both NYHOPS and HF radar. The analysis suggests that NYHOPS and HF radar have similar skill in estimating the currents over the NJ shelf.
3.3 Particle tracking results analysis
The ensemble mean separation distances and corresponding upper 95 % confidence intervals from the reseeding GNOME runs are shown in Fig. 7. Ensemble mean separation generally increases with time in a linear fashion. There is some indication that separations increase at a faster rate during the first day of the release, a finding consistent with Ullman et al. (2006). It does not appear that the separation distance is dominated by high frequency time or short spatial scale wavelengths. This suggests that both the NYHOPS and HF radar currents are representing tidal and inertial time scales correctly. The growing separation distance is dominated by errors in the mean flow causing the numerical drifters to slowly diverge from their observed position.
From the separation distance analysis (Fig. 7), NYHOPS performed slightly better in predicting the drifter location than the HF radar in this case. The separation distance for both HF radar and NYHOPS is less than 30 km in 5 days. Persistence is obviously not a good method of predicting the trajectory of a drifter subject to a general circulation current, so its separation over the 5 days grows to almost 70 km. Castellari et al. (2009) showed observation model drifter errors of 35–65 km over 10 days in the Adriatic Sea with a mean flow of around 2–20 cm s−1. The work of Fan et al. (2004) reproduced drifter paths with position error of 30–80 km in a 10-day period in the Gulf of Mexico with mean surface velocities ranging from 10 to 40 cm s−1. The mean surface current along track 3 is 25 cm s−1.
4 Discussion and conclusions
In the present study, surface currents predicted by the NYHOPS hydrodynamic model, estimated by HF radar retrievals, and observed by drifters are compared. Harmonic analysis of NYHOPS and HF radar surface currents shows similar M2 tidal ellipse parameters in the MAB, with differences of 2.4 cm s−1 in semi-major and 1.4 cm s−1 in semi-minor and 3° in orientation and 10° in phase. The comparison of tidal ellipses from NYHOPS and HF radar against observations shows that both NYHOPS and HF radar perform well and have similar skill in tidal current estimation. The presented analysis revealed that, in the open waters of the MAB, differences between HF radar and NYHOPS are mostly due to non-tidal effects, including meteorological forcing and buoyant plumes, which appear to be true.
NYHOPS and HF radar have a RMSD of 15 cm s−1 in the majority of the Middle Atlantic Bight. Differences are largest in the regions with strong surface currents, which include the New York Harbor area of the Hudson River plume, New Jersey coast, Delaware Bay, Long Island Sound, and the northern portion of the MAB shelf near Cape Cod. Away from coastal influences, in the open shelf water of the MAB, the presented RMSD analysis of non-tidal currents reveals that the biggest contributor to the apparent differences in the total current from the two technologies is due to inconsistent representation of the non-tidal effects. The normalized RMSD for the E–W and N–S current component against maximal tidal currents both have a value of about 20 % for the majority of the MAB. The variations in the depth of current estimations by the two technologies may contribute to those apparent differences and require further investigation.
From the current vector plot comparisons, both NYHOPS and HF radar appear generally reasonable in predicting the transient surface currents derived from the drifters along their trajectory. Both technologies have similar skill for the whole period, with RMS errors on the order of 10 cm s−1. The HF radar currents were not accurate for drifter 2 which was in shallower waters adjacent to the NY Harbor mouth. Apparently, the HF radar’s radial coverage was relatively low which often yields erroneous currents using the standard least-square methods employed here. It appears that NYHOPS was slightly better in reproducing mean current vectors (magnitude and directions) in this investigation. But it also lacked dynamic offshore temperature and salinity boundary conditions that appear to be important to the transient currents near the shelf break.
Particle tracking studies also reveal that both NYHOPS and HF radar yield very similar predictions and their separation distance from the observed drifter track was within 30 km after 5 days. For the case shown, the skill of the HF radar network in predicting drifter locations was slightly worse than that of NYHOPS. The inclusion of horizontal diffusion in the particle tracking model improved the predictions, and sensitivity tests verified that the 100-m2-s−1 value given in literature (Ullman et al. 2006) is reasonable for the MAB. Based on the time period investigated here, it is recommended that both the NYHOPS and HF radar surface currents can be used alternatively for search and rescue simulations in the MAB with duration less than about 5 days. Both technologies produced simulated trajectories with separation distance less than 30 km before 5 days.
From the results of the present study, we find that both HF radar and NYHOPS have similar skills in terms of their capability for estimating and predicting near-surface currents. Based on NOAA guidelines on operational model skill (NOAA 2003), an RMS difference value of 17 cm s−1 is considered acceptable for operational use. NYHOPS and HF radar performance depends on the capture of tidal currents and non-tidal currents. The two technologies perform better when tide is dominant and may perform less well (with mixed success) during events when non-tidal effects are more dominant. Additional comparisons like those provided in this study for other time periods are suggested, as more recent drifter data become available and the technologies mature further. Validations of the model and HF radar currents against current meter observations should also be conducted. Also, new methods of extracting information from drifters for improving or validating models are encouraged and needed.
This paper is made possible with the help from Dr. Josh Kohut of Rutgers University who kindly provided the hourly HF radar surface currents and answered so many questions we had. Thanks also to Dr. Arthur Allen of the US Coastal Guard and to Dr. Eoin Howlett of Applied Science of Associates for providing the SLMDB drifter data. We also thank Ms. Caitlin O’ Connor of NOAA for providing technical advice with the GNOME software. This work was supported by NOAA, under Grant: NA11NOS0120038, “Phased Deployment and Operation of Mid-Atlantic Regional Coastal Observing System (MARCOOS)” administered through Rutgers University.