Characterization of Extreme Wave Heights and Relative Risk Ratios for US Coastal Regions
Explore the source record for details and available documents.
Meuris, Brek Joseph [Sandia National Laboratories ↗
SEARCH · Search NASA
Results for “wave height”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Correlation of radar backscattering cross sections with ocean wave height and wind velocity
Ocean surface condition correlation to radar backscattering cross sections and wind velocity from scatterometer data
Krishen, K.↗
Optical wave measurement technique and experimental comparison with conventional wave height probes.
Explore the source record for details and available documents.
Sturm, G. V.↗
Significant Wave Height Comparisons Between TOPEX and Platform Harvest
Two sources of H1/3 estimates were available at Platform harvest; a NOAA buoy and CU depth sensor highrate data.
H1/3 Platform Harvest TOPEX NOAA↗
The Seasonal Cycle of Significant Wave Height in the Ocean: Local vs Remote Forcing
Explore the source record for details and available documents.
Luke Vincent Colosi↗
HERO WEC V1.0 2024 - WEC-Sim Detailed Simulation Runs and Summary Data
This dataset includes results from simulations of NREL's hydraulic and electric reverse osmosis wave energy converter (HEREO WEC). Simulation runs include 135 wave cases that were based on the updated WEC-Sim model, which is linked below. The data represented in this repository is based on an updated WEC-Sim model using laboratory data to tune and refine the original WEC-Sim model for the V1.0 HERO WEC. The 135 wave cases represent waves with the following wave height and wave period ranges: - Significant Wave Height: 0.25 - 3.75m in 0.25m increments - Wave Period: 5 - 13 sec in 1 sec increments Each run was simulated using a Pierson-Moskowitz irregular wave spectrum with a 100 second ramp time, a total simulation time of 3,100 seconds, and a simulation time-step of 0.005s. A reference table has been included to map each multi condition run (MCR) case with each wave condition. Summary data set includes a spreadsheet and image files with matrices that are associated with data from simulation runs. All matrices cover the same significant wave height and wave periods from the simulation runs, in the same increments. The following matrices are included: - Power Abs: The average absorbed power from the WEC (calculated from anchor reaction force and heave velocity) - Power Hyd: The average hydraulic power output at pump (calculated from pump output flow and pressure) - Power - Hyd ROi: The average hydraulic power measured at the RO system inlet (calculated from RO system pressure and flow (pre-accumulator)) - Flow - Pump out: The average flowrate measured at the pump outlet - Flow - Perm: The average permeate (clean water) production - Flow - RO (pre): The average flowrate measured at the inlet of the RO system before the accumulators - Flow - RO (post): The average flowrate measured after the accumulator bank in the RO system - Pressure - RO: The average pressure measured at the inlet of the RO system This data set has been developed by the National Renewable Energy Laboratory, operated by the Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding provided by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Water Power Technologies Office.
16 TIDAL AND WAVE POWER↗
Project GEOS-C
An oceanographic-geodetic satellite, designated Geodynamics Experimental Ocean Satellite-C (GEOS-C), an earth-orbiting spacecraft designed to measure precisely the topography of the ocean surface and the sea state (wave height, wave period, wave propagation direction) is described. Launch operations, spacecraft description, and mission objectives are included along with a brief flight history of the NASA satellite geodesy program. Principal investigations to be performed by the GEOS-C mission are discussed.
Source record↗
Stochastic sea state for SRB studies
Ocean surface characteristics at two locations were studied for a space shuttle solid rocket booster ocean impact and recovery analysis. Probability distributions of wave heights, wave slopes, wave velocities, ocean currents, and 1-kilometer altitude winds were formulated. Procedures for generating ocean wave simulations are described.
Perlmutter, M.↗
Seasat performance evaluation - The first two steps
Seasat, the satellite dedicated to the study of the oceans using microwave sensors, collected a data set containing information on sea surface winds, sea surface temperatures, wave heights, wave directions, internal waves, currents, tides, the marine geoid, and atmospheric water content. The first two steps of the performance evaluation of the satellite have been completed: (1) the engineering assessment and (2) the sensor evaluation. The results are encouraging for the performance of the instruments and the first level of data processing algorithms.
Lame, D. B.↗
Modeling Whitecaps on Global Scale
Whitecaps play an important role in the surface-atmosphere interactions across the ocean. They are directly linked to the energy dissipation rate during wave breaking and transfer of heat, momentum, and gas/aerosol exchange from the wind to the sea surface. Although the first models of W were dependent only on wind speeds, a large number of diverse models based on wind and sea state which include wave height, wave age, friction velocity, and stability effects have been proposed since then. However, it is recognized that most of the proposed W models have strong systematic (e.g., zonal bias) and random errors when compared against observations. This is partly due to the differences in environmental conditions, measurement techniques, and geographical locations among these studies. But, some of these biases are linked to the inability of the proposed models to capture the variability in W in certain wind/wave regimes. Despite the knowledge of existing biases, W residual relationships from the models with wind and wave fields remain highly uncertain, with residual trends varying between the published studies. Here, we take advantage of the availability of relatively dense observations of W from WindSat microwave satellite retrievals in combination with the University of Miami wave model which was recently incorporated within the NASA GMAO/GEOS system (GEOS-UMWM). We use Windsat W retrievals to assess and constrain the previously published W models and understand the relationships of residuals from models in different wind/wave regimes. We link these unexplained residual variations to additional factors such as swell index, drag coefficient etc and add information to the existing whitecap models. Since Windsat retrievals cover wide range of environmental conditions, it helps to reduce the uncertainties associated with differences in measurement techniques. Regression of wind-wave fields against all Windsat data points (CTL) results in larger residuals for lower wave age and W is overestimated upto ~4% for wave age < 10 and underestimated by upto ~2% as wave age increases. We attest to this bias by considering two approaches. One is to perform regression separately for different stages of wave development such as developing sea, fully developed, and wind sea regimes thereby understanding the sensitivity of regression coefficients to sea state (EXP1). Another is to derive coefficients of W models in EXP1 as a function of additional wind/wave factors such as swell index, drag coefficient, and mean squared slope, deriving more nonlinear W models (EXP2). EXP2 provides reduction in Root Mean Squared Error (RMSE) by 0.1-0.3%. Sea surface drag has a stronger relationship with regression coefficients compared to swell index.These additional factors provide improved parameterizations in different wind and wave age regimes, with smaller unexplained/residual variations in W that has been a major concern in the W community.
Raman, Aishwarya↗
HERO WEC V1.0 - WEC-Sim Detailed Simulation Runs and Summary Data
Data sets from simulation runs include 144 wave cases that were run based on the WEC-Sim model (https://mhkdr.openei.org/submissions/483). The 144 wave cases represent waves with the following wave height and wave period ranges: - Significant Wave Height: 0.25 - 4.0m in 0.25m increments - Wave Period: 5 - 13 sec in 1 sec increments Each run was simulated using a Pierson-Moskowitz irregular wave spectrum with a 200 second ramp time and a total simulation time of 2,200 seconds. Summary data set includes a spreadsheet and image files with matrices that are associated with data from simulation runs. All matrices cover the same significant wave height and wave periods from the sim runs, in the same increments. The following matrices are included: - Mechanical Power Input: Absorbed power calculated using linear input velocity at PTO (power take-off) multiplied by winch tension. - Mechanical Power Output: The hydraulic power calculated at the pump output prior to the pressure relief valve dump. - Feed Pressure: Average pressure at RO (reverse osmosis) input prior to pre-filters - RO Power Input: The hydraulic power calculated at the RO system inlet, accounts for flow loss due to pressure relief valve - Water Production: Average clean water flow at RO output
16 TIDAL AND WAVE POWER↗
Oceanic-wave-measurement system
Barometer mounted on bouy senses wave heights. As wave motion raises and lowers barometer, pressure differential is proportional to wave height. Monitoring circuit samples barometer output every half cycle of wave motion and adds magnitudes of adjacent positive and negative peaks. Resulting output signals, proportional to wave height, are transmitted to central monitoring station.
Holmes, J. F.↗
Synthetic aperture radar imaging of ocean waves - Comparison with wave measurements
Synthetic aperture radar images of ocean waves were obtained in conjunction with reference wave data near Marineland, Florida, December 14, 1975. Each of the various types of measurements were processed into a form that allowed direct comparisons with the others. Maxima of radar spectra occurred at the same frequencies as the maxima of reference wave height spectra. In a comparison of a radar spectrum with observed spectra of wave height, wave orbital velocity, and surface slope the high-frequency portion of the radar spectrum lay near and between the wave height and the orbital velocity spectra but differed significantly from the surface slope spectrum. The radar-derived mean directions and model-fitted directional spreads of wave energy were close to the values from a directional wave buoy and indicated the accuracy of radar measurements of wave direction. However, a directional plot of a radar spectrum near shore at the frequency of the maximum showed a sharper peak than such a plot of a fitted spectrum derived from reference data.
Mcleish, W.↗
Open-Loop Control of Adjustable Tuned Mass Dampers for Floating Wind Turbine Platforms: Preprint
Floating offshore wind turbines have several advantages over their land-based counterparts, including access to stronger, more consistent winds and proximity to population centers. However, increased costs from the platform have been a challenge inhibiting their widespread adoption. New damping technologies with tunable target frequencies and damping ratios promise a greater degree of control over platform motions, allowing hulls to be designed smaller and reducing the overall cost of the turbines. In this work, a control strategy is proposed for these adjustable tuned mass dampers (TMDs). A frequency-domain model of the system is developed, from which response amplitude operators (RAOs) for the platform's rigid-body modes can be obtained for different natural frequencies and damping ratios of the dampers. Using these RAOs, and JONSWAP spectrums of operational and extreme sea states, the performance of the various damper settings are compared by evaluating the standard deviation of a rigid-body motion of interest (platform pitch or heave). By finding the optimal damper setting for a range of representative design load cases (DLCs), a lookup function is made to return the damper target frequency given the peak period of the sea state. To determine the current sea state, we propose a simple estimator that uses wave measurements (e.g., from a measurement buoy) to determine the peak period and significant wave height. The significant wave height is determined using the statistics of the past 100 seconds of wave elevation information and the peak period is computed using a frequency locked loop. Initial results show that we can use these estimated values to control the TMD natural frequency with an open loop controller. The controlled system is tested in a range of environmental conditions determined by the International Electrotechnical Commission design load cases (DLCs), which include normal and extreme wind and wave models. In these tests, we compare the performance of 4 cases: (1) no TMD, (2) a constant TMD based on the worst case DLC, (3) a controlled TMD based on known wind and wave environments, and (4) a real-time controlled TMD using estimated wind and wave environments. The effect of hull-based TMD control is also compared to changes in traditional wind turbine control via blade pitch.
control↗
Correlated environmental corrections in TOPEX/POSEIDON, with a note on ionospheric accuracy
Estimates of the effectiveness of an altimetric correction, and interpretation of sea level variability as a response to atmospheric forcing, both depend upon assuming that residual errors in altimetric corrections are uncorrelated among themselves and with residual sea level, or knowing the correlations. Not surprisingly, many corrections are highly correlated since they involve atmospheric properties and the ocean surface's response to them. The full corrections (including their geographically varying time mean values), show correlations between electromagnetic bias (mostly the height of wind waves) and either atmospheric pressure or water vapor of -40%, and between atmospheric pressure and water vapor of 28%. In the more commonly used collinear differences (after removal of the geographically varying time mean), atmospheric pressure and wave height show a -30% correlation, atmospheric pressure and water vapor a -10% correlation, both pressure and water vapor a 7% correlation with residual sea level, and a bit surprisingly, ionospheric electron content and wave height a 15% correlation. Only the ocean tide is totally uncorrelated with other corrections or residual sea level. The effectiveness of three ionospheric corrections (TOPEX dual-frequency, a smoothed version of the TOPEX dual-frequency, and Doppler orbitography and radiopositioning integrated by satellite (DORIS) is also evaluated in terms of their reduction in variance of residual sea level. Smooth (90-200 km along-track) versions of the dual-frequency altimeter ionosphere perform best both globally and within 20 deg in latitude from the equator. The noise variance in the 1/s TOPEX inospheric samples is approximately (11 mm) squared, about the same as noise in the DORIS-based correction; however, the latter has its error over scales of order 10(exp 3) km. Within 20 deg of the equator, the DORIS-based correction adds (14 mm) squared to the residual sea level variance.
Zlotnicki, V.↗
Simultaneous Ocean Wave Measurements by the Jason and Topex Satellites, With Buoy and Model Comparisons
The verification phase of the Jason-1 satellite altimeter mission presents a unique opportunity for comparing near-simultaneous, independent satellite measurements. We here examine simultaneous significant wave height measurements by the Jason-1 and Topex/Poseidon altimeters. These data are also compared with in-situ measurements from deep-ocean buoys and with predicted wave heights from the Wave Watch 111 operational model. The rms difference between Jason and Topex wave heights is 21 cm, and this can be further lowered by application of median filters to reduce high-frequency noise. This noise is slightly larger in the Jason dataset, amounting to about 7 cm rms for frequencies above 0.05 Hz, which is the frequency at which the coherence between Topex and Jason measurements drops to zero. The probability density function for Jason shows a dearth of small waves relative to Topex. Buoy comparisons confirm that this problem lies with the Jason measurements. The buoy comparisons confirm previous reports that Topex wave heights are roughly 5% smaller than buoy measurements for waves between 2 and 5m; Jason heights in general are 2.7% smaller than Topex. Spurious dips in the Topex density function for 3- and 6-meter waves, a problem that has existed since the beginning of the mission, can be solved by waveform retracking..
Ray, Richard D.↗
Bathymetric Effects on a Tropical Cyclone Wave Field at Landfall
On 26 August 1998, the NASA Scanning Radar Altimeter (SRA) flew aboard one of the WP-3D hurricane research aircraft to document the sea surface directional wave spectrum in the region between Charleston, SC and Cape Hatteras, NC, as Bonnie, a large Category 3 hurricane, was making landfall near Wilmington, NC. Two days earlier, the SRA had documented the wave field spatial variation in open water when Hurricane Bonnie was 400 km east of Abaco Island, Bahamas. Bonnie was similar in size during the two flights, but the maximum speed in the NOAA Hurricane Research Division surface wind analysis was 15% lower prior to landfall (39 m/s) than it had been in the open ocean (46 m/s). This was compensated for by its faster movement prior to landfall (9.5 m/s) than when it was encountered in the open ocean (5 m/s). The slower movement matched the group velocity of waves of 65 m length, so waves at the peak of the spectrum outdistanced the storm as soon as they were generated. The higher translation speed prior to landfall matched the group velocity of waves of 230 m length, significantly increasing the effective fetch and duration of waves near the peak of the spectrum which propagated in the direction of the storm track. The open ocean wave height variation indicated that Hurricane Bonnie would have produced waves of 11 m significant wave height on the shore northeast of Wilmington had it not been for the continental shelf. The bathymetry distributed the steepening and breaking process across the shelf so that the wavelength and wave height were reduced gradually as the shore was approached. The wave height 5 km from shore was about 4 m.
Wright, C. W.↗
Simultaneous Ocean Wave Measurements by the JASON and TOPEX Satellites, With Buoy and Model Comparisons
The verification phase of the Jason-1 satellite altimeter mission presents a unique opportunity for comparing near-simultaneous, independent satellite measurements. We here examine simultaneous significant wave height measurements by the Jason-1 and Topex/Poseidon altimeters. These data are also compared with in-situ measurements from deep-ocean buoys and with predicted wave heights from the WaveWatch 111 operational model. The rms difference between Jason and Topex wave heights is 28 cm, and this can be lowered by half through improved outlier editing and filtering of high-frequency noise. Noise is slightly larger in the Jason dataset, exceeding Topex by about 7 cm rms at frequencies above 0.05 Hz, which is the frequency at which the coherence between Topex and Jason measurements drops to zero. Jason wave heights are more prone to outliers, especially during periods of moderate to high backscatter. Buoy comparisons confirm previous reports that Topex wave heights are roughly 5% smaller than buoy measurements for waves between 2 and 5m; Jason heights in general are 3% smaller than Topex. Spurious dips in the Topex density function for 3- and 6-meter waves, a problem that has existed since the beginning of the mission, can be solved by waveform retracking.
Ray, R. D.↗