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↗
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The Seasonal Cycle of Significant Wave Height in the Ocean: Local vs Remote Forcing
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Luke Vincent Colosi↗
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↗
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.↗
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.↗
Tilt Modulation Distortions in Wave Topography Measured by a Scanning Radar Altimeter
Work continues on estimating tilt modulation distortions in the wave topography measured by a scanning radar altimeter. To quantify this effect, a two-dimensional simulation has been performed in the cross-track plane only which assumed that sinusoidal waves of constant wavelength propagate in the cross-track direction (and are infinitely long-crested in the along-track direction). The initial results reported earlier for a Gaussian surface scattering model indicated that when the highest reasonable value of mss is used in the simulation (the Plant limit of 0.08), the nadir values of the ratio of the apparent to actual wave height are the same as for the omnidirectional scattering case. But as the off-nadir angle increased, the apparent wave height increased and became larger than the actual wave height by about 10 degrees off-nadir. And the shorter the wavelength, the larger the apparent wave height increase. This represented a systematic over-estimate of the wave amplitude for waves propagating in the cross-track direction. For lower values of mss the situation worsened. The simulation has been improved by incorporating actual variations of backscattered power with incidence angle measured by the SRA instead of the Gaussian model. The resulting distortion was about half that originally reported. The 3-dimensional simulation to model waves propagating at various azimuthal angles relative to the cross-track plane is still in progress. The results of this model will be verified by comparing them with Scanning Radar Altimeter (SRA) data and optimum correction procedures will be developed. An assessment of the improved 2-dimensional model indicates that the distortion will generally be small in the data taken during the Southern Ocean Waves Experiment (SOWEX) presently be analyzed. But tilt modulation effects are of great concern for SRA data collected during the 1998 hurricane season since the minimum aircraft altitude was 1.5 km and it frequently flew higher. For a given wave length and steepness, the effect increases with increasing aircraft altitude, and is larger for waves propagating in the cross-track direction, which was generally the situation during the hurricane flights.
Walsh, Edward J.↗
Seasat-A - An ocean observation satellite
Mission details, onboard equipment, and measurements to be taken are described for the Seasat-A global ocean monitoring satellite. The satellite is designed for mapping the global ocean geoid, charting ice fields and leads, precision measurement of sea surface topography, global monitoring of wave height and wave directional spectra, surface winds and wind direction, current patterns, and ocean temperature. Data handling subsystems, a compressed pulse radar altimeter, coherent synthetic aperture imaging radar, microwave wind scatterometer, scanning visible/IR radiometer, scanning multispectral (5 freq) microwave radiometer mounted on the satellite are described briefly.
Williams, F. L.↗
The Seasat commercial demonstration program
The background and development of the Seasat commercial demonstration program are reviewed and the Seasat spacecraft and its sensors (altimeter, wind field scatterometer, synthetic aperture radar, and scanning multichannel microwave radiometer) are described. The satellite data distribution system allows for selected sets of data, reformatted or tailored to specific needs and geographical regions, to be available to commercial users. Products include sea level and upper atmospheric pressure, sea surface temperature, marine winds, significant wave heights, primary wave direction and period, and spectral wave data. The results of a set of retrospective case studies performed for the commercial demonstration program are described. These are in areas of application such as marine weather and ocean condition forecasting, offshore resource exploration and development, commercial fishing, and marine transportation.
Mccandless, S. W.↗
Wave attenuation in the marginal ice zone during LIMEX
The effect of ice cover on ocean-wave attenuation is investigated for waves under flexure in the marginal ice zone (MIZ) with SAR image spectra and the results of models. Directional wavenumber spectra are taken from the SAR image data, and the wave-attenuation rate is evaluated with SAR image spectra and by means of the model by Liu and Mollo-Christensen (1988). Eddy viscosity is described by means of dimensional analysis as a function of ice roughness and wave-induced velocity, and comparisons are made with the remotely sensed data. The model corrects the open-water model by introducing the effects of a continuous ice sheet, and turbulent eddy viscosity is shown to depend on ice thickness, floe sizes, significant wave height, and wave period. SAR and wave-buoy data support the trends described in the model results, and a characteristic rollover is noted in the model and experimental wave-attenuation rates at high wavenumbers.
Liu, Antony K.↗
Predictive Sea State Estimation for Automated Ride Control and Handling - PSSEARCH
PSSEARCH provides predictive sea state estimation, coupled with closed-loop feedback control for automated ride control. It enables a manned or unmanned watercraft to determine the 3D map and sea state conditions in its vicinity in real time. Adaptive path-planning/ replanning software and a control surface management system will then use this information to choose the best settings and heading relative to the seas for the watercraft. PSSEARCH looks ahead and anticipates potential impact of waves on the boat and is used in a tight control loop to adjust trim tabs, course, and throttle settings. The software uses sensory inputs including IMU (Inertial Measurement Unit), stereo, radar, etc. to determine the sea state and wave conditions (wave height, frequency, wave direction) in the vicinity of a rapidly moving boat. This information can then be used to plot a safe path through the oncoming waves. The main issues in determining a safe path for sea surface navigation are: (1) deriving a 3D map of the surrounding environment, (2) extracting hazards and sea state surface state from the imaging sensors/map, and (3) planning a path and control surface settings that avoid the hazards, accomplish the mission navigation goals, and mitigate crew injuries from excessive heave, pitch, and roll accelerations while taking into account the dynamics of the sea surface state. The first part is solved using a wide baseline stereo system, where 3D structure is determined from two calibrated pairs of visual imagers. Once the 3D map is derived, anything above the sea surface is classified as a potential hazard and a surface analysis gives a static snapshot of the waves. Dynamics of the wave features are obtained from a frequency analysis of motion vectors derived from the orientation of the waves during a sequence of inputs. Fusion of the dynamic wave patterns with the 3D maps and the IMU outputs is used for efficient safe path planning.
Huntsberger, Terrance L.↗
Managing and Servicing Physical Oceanographic Data at a NASA Distributed Active Archive Center
The NASA Earth Science Data Information Systems Project funds and operates 12 Distributed Active Archive Center(s) (DAAC) throughout the United States. Of these 12 centers, the Physical Oceanography DAAC (PO.DAAC) is committed to providing long term archival, distribution and stewardship for NASA physical oceanographic data, primarily derived from space-born satellite systems, but also including a growing set of recent and future in situ observations from the SPURS-1 and SPURS-2 campaigns. Notable NASA missions supported include: Seasat, TOPEX/Poseidon, NSCAT, QuikSCAT, ISS-RapidScat, Jason-1, Jason-2/OSTM, GRACE, Aquarius, GHRSST, and MODIS. The following interagency and international missions are also supported by PO.DAAC: AVHRR, Coriolis, DMSP, MetOp-A, MetOp-B, Oceansat-2. The PO.DAAC currently holds 525 datasets in public distribution, spanning the following observational parameters: sea surface temperature, sea surface salinity, ocean color, ocean surface currents, ocean surface wind speed, ocean surface wind direction, sea surface height, significant wave height, ocean water mass/thickness, and sea ice age. A hundred of these datasets are available in near-real-time. Datasets are distributed through a variety of open-source access protocols including FTP, OPeNDAP, and THREDDS. FTP will soon be phased out in favor of a recently introduced HTTPS PO.DAAC Drive interface that supports WebDAV and interoperable machine-to-machine communication. OPeNDAP supports remote data/metadata query, subset, and download. THREDDS provides the features of OPeNDAP with the additional feature of temporal aggregation. PO.DAAC also offers proprietary tools and services to further enhance the data discovery, visualization and analysis experience, including but not limited to: State of the Ocean, Web Services (data/metadata discovery and extraction), HiTIDE Level-2 subsetter, Live Access Server (LAS), Webification (w10nsci), and Rich Site Summary (RSS) Datacasting. To assist with provenance of datasets, PO.DAAC has implemented DOIs for the data it distributes so that they can be properly cited. There is a user forum and helpdesk that contains data recipes and via which users can get guidance. In summary, this presentation aims to provide a general overview of PO.DAAC’s web portal and data holdings along with a set of illustrative examples leading prospective data users into the practical utility of its tools and services.
Moroni, David F.↗