Coastal Data Information Program Research Articles

Wind velocity estimates from wave observing platforms

ABSTRACT Near-surface ocean wind measurements are important for weather forecasting, determining surface transports, and estimating air-sea interactions; however, in-situ wind observations are often limited. Previous studies indicate that the equilibrium range of the surface gravity wave spectrum can be used to estimate surface wind velocity. This approach is tested using spectral wave measurements from the Coastal Data Information Program (CDIP) buoy array off Monterey, California. Quality controlled wind vectors inferred from wave spectra are statistically compared to measurements from a nearby National Data Buoy Center (NDBC) buoy, demonstrating strong agreement with the control observations with root mean square errors for speed and direction of 1.8 m/s for all wind speeds and 13.2° for wind speeds greater than 7 m/s. We expand this estimation method to account for biofouling, which causes high-frequency damping of the wave spectrum, and the effects of form factor, which impact the platform’s dynamic response to high-frequency waves. The method produces wind-proxy measurements solely from wave spectra and wave-based drag parametrizations, making it useful for operational integration. This work demonstrates the ability to make robust wind velocity estimates using wave data from multiple sources, increasing the coverage of wind information over the coastal and open ocean.

Coastal Data Information Program: advances in measuring and modeling wave activity, climate, and extremes

ABSTRACT The Coastal Data Information Program (CDIP) provides wave data to the public in near real-time, maintains an operational wave model for the California coast, and is engaged in ocean wave research on a global scale. CDIP’s array of moored wave buoy stations are instrumented with Datawell Waveriders. CDIP’s recent work to improve monitoring capabilities for directional surface wave spectra, surface current, and temperature is described. This includes data quality assurance and control, real-time alerts, telemetry and dissemination information technology infrastructure and methodology, data visualization tools, and mooring and instrumentation innovation. CDIP’s goal is to maximize data reliability, availability, accuracy, and precision. Validation of commonly used wave models – operational, hindcast, and forecast – with CDIP data is automated to provide assessments of relative skills at a variety of coastal locations and wave conditions. Wave heights measured by the buoys typically exceed modeled heights during the most energetic events, such as hurricanes, nor’easters, and bomb cyclones. In a practical validation example, the global wave model used to drive CDIP’s California coastal wave forecasts was recently changed, based on comparisons against buoy data. Forecast performance has improved for swell events, which are a challenge to model accurately in the Southern California Bight.

Dynamic Characterization, Flow Modeling, and Hierarchical Control of an Energy-Harvesting Underwater Kite in Realistic Ocean Conditions

This paper presents a hierarchical control framework for a kite-based marine hydrokinetic (MHK) system, along with a detailed characterization of the dynamic and energetic performance of the system under realistic flow conditions. The underwater kite, which is designed to be deployed off of an offshore floating platform, features a closed-loop controller that executes power-augmenting, cyclic cross-current flight. The robustness of the kite's undersea flight control algorithm is demonstrated in a realistic four-dimensional flow model (which captures both low-and high-frequency spatiotemporal variations in the current) that accounts for turbulence and wave effects, which is coupled with a detailed dynamic model that captures the six-degree-of-freedom kite and floating platform dynamics, in addition to the tether dynamics. Using data obtained by the Coastal Data Information Program (CDIP) 192 Oregon Inlet buoy [1], wave data from the Wave Information Studies Hindcast model [2], and a spectral turbulence model developed at Florida Atlantic University, we demonstrate the robustness of the kite's control system and the sensitivity of both average net power output and peak-to-average power to wave parameters. In common wave conditions, the average and net power output are shown to be highly robust to the peak period and significant wave height. In extreme wave conditions, the peak-to-average power ratio is shown to be highly positively correlated with an effective wave energy density metric, which characterizes the wave energy density presented to the kite system based on a weighted distribution along depth of the kite.

Wave–Tide Interaction for a Strongly Modulated Wave Field

Abstract Observations from Coastal Data Information Program (CDIP) moored buoys off the coast of Florida reveal tidally driven wave–current interactions that modify significant wave heights by up to 25% and shift peak periods by up to a second. A case study at Fernandina Beach, Florida, shows surface waves steepening on following tidal currents and becoming less steep on opposing tidal currents, with the largest modulations occurring in the long-period swell band. To better understand tidal modulations as a function of the phase of the tide, we use simplified analytical and numerical solutions to the equations of geometrical optics and conservation of wave action under the assumption of a one-dimensional tide acting as a progressive shallow-water wave. The theoretical frameworks allow us to identify parameters that characterize the magnitude of variation in surface waves due to tidally induced currents and changes in water depth. We compute modulations to the omnidirectional and directional wave spectrum (between 0.05 and 0.15 Hz), as well as characteristic bulk parameters such as significant wave height and peak period. The theory is corroborated using directional wave and surface current observations from the Fernandina Beach CDIP station (located in water of average depth of 16 m). We find that the numerical results reproduce the observed wave modulations due to tidal currents and changes in water depth. Specifically, surface waves traveling in the direction of the tide are strongly modulated, and the relative speeds between the tide and surface waves set the sign and magnitude of these modulations. Given knowledge of tidal currents, water-depth variations, and wave climatology, theoretical and numerical predictions may be used to provide both statistical and instantaneous estimates of wave-height variations due to tides. Because operational forecasts and nowcasts do not routinely include tides or currents, these findings can help to accurately represent nearshore surface wave variability.

Determining Errors in Directional Buoy-Derived Swell Heights via the Joint Analysis of Space-Borne Radars and WaveWatch III Simulations

Characterizing the uncertainties in buoy ocean wave records is critical not only for understanding the limitations of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> wave measurements, but also for interpreting the implied accuracies of the remotely sensed products in which these buoy data are used as validation references. This letter preliminarily assesses the error of long-period swell heights ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Hss</i> ) representing specific directional wave partition energy observed from deep-water buoys moored in the northeast Pacific. We propose a buoy <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Hss</i> error estimation method by combining dual and triple collocation using data derived from buoys, two kinds of space-borne radars and numerical simulations. Compared to traditional methods, the proposed approach can reveal “absolute” errors (with respect to the underlying truth) from buoy <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Hss</i> , accepting and then confirming that swell heights from buoy, satellite and model are all uncertain. This study simultaneously employs ocean swell products derived from synthetic/real aperture radars (Sentinel-1A/B and CFOSAT/SWIM) and WaveWatch III® ocean wave model hindcasts to diagnose the accuracy of the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Hss</i> values observed by buoys of National Data Buoy Center (NDBC) and Coastal Data Information Program (CDIP) during the period from July 2019 to October 2021. We quantify that the NDBC’s 3-m heave-pitch-roll buoy (CDIP’s Waverider buoy) recorded <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Hss</i> have root-mean-square error of 0.17 m (0.12 m), or have about 10.65% (7.06%) uncertainty relative to the mean <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Hss</i> value (approximately 1.6 m). Our findings imply that the reference value uncertainties should be taken into account when understanding direct satellite <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Hss</i> validation against buoy <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> .

Wind-Stress Variations from Deep to Shallow Water during Hurricanes for Air-Sea-Land Interaction Applications

In September 2020 Hurricane Sally impacted two National Data Buoy Center (www.ndbc.noaa.gov) buoys near its track: 42040 in the deep water and 42012 in the shallow. Using pertinent air-sea interaction formulas from the literature, analyses of these buoy data indicate that, under fully rough airflow and wind sea conditions, U* = a Hs2 /Tp3 + b, here U* is the friction velocity, Hs is the significant wave height, and Tp is the peak wave period. It is found that a = 28 and b = 0.12 for the deep water environment, a = 30 and b = 0.26 for the shoaling wave environment, and a = 31 and b = 0.14 for the transitional water-depth environment, respectively. All units are in SI. Verifications and applications of these proposed formulas to estimate storm surge, wind speed, surface currents and seabed scours are presented. Because an extensive network for monitoring waves along the coastlines of the United States by the Coastal Data Information Program (CDIP) (CDIP About (ucsd.edu)), these proposed formulas are particularly useful. In addition, it is demonstrated that the parameter of wave steepness can be used to explain why there are large variations in the drag coefficient and wave-age formulations in the literature.

CDIP observations of recent extreme wave conditions on U.S. coasts

The Coastal Data Information Program (CDIP) maintains wave gauge stations for continuous coverage, with precision instruments and dedicated telemetry and dissemination infrastructure. Decades of this persistent, quality-controlled wave monitoring effort has provided the data required to generate metrics for wave climate at coastal locations across the United States and identify and characterize extreme wave events. During the extremely active 2020 North Atlantic hurricane season, the CDIP East Coast array recorded significantly elevated wave conditions generated by no fewer than 15 named storms. In California, meanwhile, long-term monitoring stations have measured new all-time maximum wave heights during recent storm events. Complete quality-controlled directional spectra and displacement data sets, as well as sea surface temperature and surface current data from the wave buoys, are publicly available at http://cdip.ucsd.edu.

Morphological response of variable river discharge and wave forcing at a bar-built estuary

Observations of morphological evolution at Carmel River State Beach, Carmel, CA, USA, were made during two winter periods where the estuary underwent transitions from closed to open states episodically during each observation period. However, each winter was climatologically distinct: the first (Dec 2016–May 2017) was a high river discharge year (several events >200 m3/s) with westerly offshore waves and the second (Dec 2017–May 2018) was a low river discharge year with northwesterly offshore waves. The morphological response of the beach was measured using Structure-from-Motion from both aircraft and unmanned aerial vehicles (UAVs) and shows two distinct seasonal trends. The first (in 2016–2017) indicates rapid (hours) and frequent (days-weeks) migration of the river breach channel across the span of the beach. The second (in 2017–2018) indicates no migration of the initial breach channel, despite multiple breach events. Analysis of the offshore wave energy using the Coastal Data Information Program (CDIP) hindcast model results indicate a stronger longshore wave radiation stress during the migratory breach year. In addition, discharge rates during this year were more than three times stronger than the non-migratory year, indicating a stronger offshore jet from the breach site. These observations support the hypothesis that migration requires both a strong river discharge and a longshore wave radiation stress component.

The Role of Stakeholders in Creating Societal Value From Coastal and Ocean Observations

The importance of stakeholder engagement in ocean observation and in particular the realization of economic and societal benefits is discussed, introducing a number of overarching principles such as the convergence on common goals, effective communication, co-production of information and knowledge and the need for innovation. A series of case studies examine the role of coordinating frameworks such as the US’s Interagency Ocean Observing System (IOOS®), and the European Ocean Observing System (EOOS), public-private partnerships such as Project Azul and the Coastal Data Information Program (CDIP) and finally the role of the “third” or voluntary sector. The paper explores the value that stakeholder engagement can bring as well as making recommendations for the future.

Data Mining Pt. Reyes Buoy for Rare Wave Groups

This paper addresses the existence of rare wave groups by examining time series data from the Pt. Reyes buoy. The buoy is operated by the Coastal Data Information Program (CDIP), University of California San Diego. The definition of rare wave groups, as defined by Kim and Troesch, used in this paper differs from the more commonly used wave group definition based on threshold crossings. With the time series data from the Pt. Reyes buoy, these rare wave groups are shown to be a naturally occurring phenomenon. The essential features of the data are examined, as well as the analysis methods and findings. By sifting through 17 years of wave elevation data from the Pt. Reyes buoy, this preliminary work addresses not only the question to what extent rare wave groups exist in nature but also what their probability of occurrence is.

Characterizing the wave energy resource of the US Pacific Northwest

The substantial wave energy resource of the US Pacific Northwest (i.e. off the coasts of Washington, Oregon and N. California) is assessed and characterized. Archived spectral records from ten wave measurement buoys operated and maintained by the National Data Buoy Center and the Coastal Data Information Program form the basis of this investigation. Because an ocean wave energy converter must reliably convert the energetic resource and survive operational risks, a comprehensive characterization of the expected range of sea states is essential. Six quantities were calculated to characterize each hourly sea state: omnidirectional wave power, significant wave height, energy period, spectral width, direction of the maximum directionally resolved wave power and directionality coefficient. The temporal variability of these characteristic quantities is depicted at different scales and is seen to be considerable. The mean wave power during the winter months was found to be up to 7 times that of the summer mean. Winter energy flux also tends to have a longer energy period, a narrower spectral width, and a reduced directional spread, when compared to summer months. Locations closer to shore, where the mean water depth is less than 50 m, tended to exhibit lower omnidirectional wave power, but were more uniform directionally. Cumulative distributions of both occurrence and contribution to total energy are presented, over each of the six quantities characterizing the resource. It is clear that the sea states occurring most often are not necessarily those that contribute most to the total incident wave energy. The sea states with the greatest contribution to energy have significant wave heights between 2 and 5 m and energy periods between 8 and 12 s. Sea states with the greatest significant wave heights (e.g.>7 m) contribute little to the annual energy, but are critically important when considering reliability and survivability of ocean wave energy converters.

Changes in ocean infrasonic energy density and vector intensity with changes in wind and ocean surface wave conditions as measured by a freely drifting vector sensor

During an experiment in 1.3-km-deep water in the Southern California Bight, the wind speed decreased from about 7 to 1 m/s over a 10-h period, and then increased to 9 m/s over the next 8-h period. Measurements made by a neutrally buoyant, freely drifting vector sensor at 920-m depth show that the corresponding changes in the potential and kinetic energy density levels of the infrasonic sound field have a frequency-dependent delay. The levels in a 0.1-Hz-wide bin at 3 Hz respond to wind-speed changes with approximately a 2-h delay, and the delay in response increases with decreasing frequency at a rate of about 1 h per hertz down to 1 Hz. The corresponding evolution in directionality of the active and reactive acoustic intensity vectors in these same frequency bins and their relationship to the surrounding bathymetry will be presented. The directional spectra of the ocean surface wave field during the experiment were reconstructed using back-refraction modeling with wave data from shore stations and offshore platforms archived by the Coastal Data Information Program to obtain estimates of the temporal variability of the nonlinear wave-wave interactions generating the ocean infrasound. [Work supported by ONR.]

Ambient noise measurements in the acoustic beach monitoring experiment.

During the spring of 1994 (April–June) the Marine Physical Laboratory/SIO conducted the acoustic beach monitoring (ABM) pilot experiment at Camp Pendelton, CA. One component of the experiment was concerned with measurement of ambient noise up to 40 kHz, at distances up to several kilometers offshore. An array of three modified SSQ 57B sonobuoys were moored at distances from 1.5 to 3.5 km offshore. The surf zone was instrumented with pressure gauges and a current meter, and a comprehensive meteorological station was set up on the beach. A directional microphone on the beach was used to monitor the surf noise. Supporting oceanographic and meteorological data was available from the SIO coastal data information program. Near-shore acoustic spectra are characterized by two broad peaks in the ranges of 100–500 Hz and 1–7 kHz, respectively. The higher frequency peak rapidly attenuates offshore, while the lower frequency peak is essentially unattenuated over ranges of several kilometers. In contrast to deep water, the correlation of surf zone ambient noise with the local wind is poor since the shoaling waves may be dominated by swell from distant storms. Short term averages of acoustic power correlate very well with the amplitude modulation (groupiness) of the incident waves. [Work supported by ONR.]