scholarly journals Wind Speed Dependence of Single-Site Wave-Height Retrievals from High-Frequency Radars

2010 ◽  
Vol 27 (8) ◽  
pp. 1381-1394 ◽  
Author(s):  
Brian K. Haus ◽  
Lynn K. Shay ◽  
Paul A. Work ◽  
George Voulgaris ◽  
Rafael J. Ramos ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
High Frequency ◽  
Hf Radar ◽  
Single Site ◽  
Scale Separation ◽  
Peak Energy ◽  
Wave Heights ◽  
Acoustic Doppler Profiler ◽  
Buoy Data

Abstract Wave-height observations derived from single-site high-frequency (HF) radar backscattered Doppler spectra are generally recognized to be less accurate than overlapping radar techniques but can provide significantly larger sampling regions. The larger available wave-sampling region may have important implications for observing system design. Comparison of HF radar–derived wave heights with acoustic Doppler profiler and buoy data revealed that the scale separation between the Bragg scattering waves and the peak energy-containing waves may contribute to errors in the single-site estimates in light-to-moderate winds. A wave-height correction factor was developed that explicitly considers this scale separation and eliminates the trend of increasing errors with increasing wind speed.

scholarly journals Wind Speed Inversion in High Frequency Radar Based on Neural Network

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Yuming Zeng ◽  
Hao Zhou ◽  
Hugh Roarty ◽  
Biyang Wen
Keyword(s):  
Neural Network ◽  
Wind Speed ◽  
High Frequency ◽  
Dynamic Parameter ◽  
Hf Radar ◽  
Data Sets ◽  
High Frequency Radar ◽  
Wide Range ◽  
Radar Echo ◽  
Buoy Data

Wind speed is an important sea surface dynamic parameter which influences a wide variety of oceanic applications. Wave height and wind direction can be extracted from high frequency radar echo spectra with a relatively high accuracy, while the estimation of wind speed is still a challenge. This paper describes an artificial neural network based method to estimate the wind speed in HF radar which can be trained to store the specific but unknown wind-wave relationship by the historical buoy data sets. The method is validated by one-month-long data of SeaSonde radar, the correlation coefficient between the radar estimates and the buoy records is 0.68, and the root mean square error is 1.7 m/s. This method also performs well in a rather wide range of time and space (2 years around and 360 km away). This result shows that the ANN is an efficient tool to help make the wind speed an operational product of the HF radar.

scholarly journals Wave Height Distributions and Rogue Waves in the Eastern Mediterranean

2021 ◽  
Vol 9 (6) ◽  
pp. 660
Author(s):  
Sagi Knobler ◽  
Daniel Bar ◽  
Rotem Cohen ◽  
Dan Liberzon
Keyword(s):  
Wave Height ◽  
Eastern Mediterranean ◽  
Rogue Waves ◽  
Distribution Model ◽  
Storm Events ◽  
Order Model ◽  
Deep Seawater ◽  
Wave Heights ◽  
Storm Characteristics ◽  
Buoy Data

There is a lack of scientific knowledge about the physical sea characteristics of the eastern part of the Mediterranean Sea. The current work offers a comprehensive view of wave fields in southern Israel waters covering a period between January 2017 and June 2018. The analyzed data were collected by a meteorological buoy providing wind and waves parameters. As expected for this area, the strongest storm events occurred throughout October–April. In this paper, we analyze the buoy data following two main objectives—identifying the most appropriate statistical distribution model and examining wave data in search of rogue wave presence. The objectives were accomplished by comparing a number of models suitable for deep seawater waves. The Tayfun—Fedele 3rd order model showed the best agreement with the tail of the empirical wave heights distribution. Examination of different statistical thresholds for the identification of rogue waves resulted in the detection of 99 unique waves, all of relatively low height, except for one wave that reached 12.2 m in height which was detected during a powerful January 2018 storm. Characteristics of the detected rogue waves were examined, revealing the majority of them presenting crest to trough symmetry. This finding calls for a reevaluation of the crest amplitude being equal to or above 1.25 the significant wave height threshold which assumes rogue waves carry most of their energy in the crest.

scholarly journals Evaluation of in-situ wind speed and wave height measurements against reanalysis data for the Greek Seas

2017 ◽  
pp. 486 ◽  
Author(s):  
DAFNI SIFNIOTI ◽  
TAKVOR SOUKISSIAN ◽  
SERAFEIM POULOS ◽  
PANAGIOTIS NASTOS ◽  
MARIA HATZAKI
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
Reanalysis Data ◽  
Error Statistics ◽  
Evaluation Of Performance ◽  
Assimilation Process ◽  
Temporal And Spatial ◽  
Wave Hindcasting ◽  
Buoy Data

ERA-Interim, ECMWF’s reanalysis product, includes wave and atmospheric characteristics, with high temporal and spatial scale, providing more information on the marine state. Even though their assimilation process has been validated and verified in numerous studies, their performance in more local scales is still under examination. This research focuses on the evaluation of performance of ERA-Interim reanalysis datasets in the Greek Seas for wind and wave characteristics in comparison to POSEIDON buoy data. The results prove fair to good correlation for wave height (r = 0.67-0.94) and wind speed (r= 0.71-0.83) and different error statistics per sub-region. The upper 10% analysis shows an underestimate of 10-15% for wind speed and wave height from ERA-Interim in relation to the buoy measurements. The ERA-Interim and the buoy monthly means and standard deviations are also presented and discussed according to seasonal patterns. The results of the study are compared to other researches of wave hindcasting and wind reanalysis data for the Greek Seas and globally. It is shown that ERA-Interim products could be regarded as representative for the Greek Seas, although their application should be made with caution regarding the assessment of extreme conditions (i.e. given in analyses of upper percentiles) and especially at nearshore locations due to complex coastline configuration enhanced by the great number of islands.

Measured Metocean Characteristics of Gulf of Mexico Hurricanes

2015 ◽  
Author(s):  
George Z. Forristall ◽  
Jason McConochie
Keyword(s):  
Gulf Of Mexico ◽  
Wave Height ◽  
Storm Track ◽  
Significant Wave ◽  
Wind Speeds ◽  
Hurricane Wind ◽  
Wave Parameters ◽  
Wave Heights ◽  
Significant Wave Heights ◽  
Buoy Data

A wealth of Gulf of Mexico hurricane wind and wave data has been measured in recent years. We have constructed a database that combines HURDAT storm track information with NDBC buoy data for the years 1978–2010. HURDAT contains 141 storms for that period of which 67 had measured significant wave heights greater than 5 m. Industry measurements in Hurricanes Camille, Lili, Ivan, Katrina, Rita, Gustav and Ike have been added to the buoy data. We have used this data base to study the relationships between wind and wave parameters in hurricanes. Specifically, we have calculated regressions and equal probability contours for significant wave height and peak spectral periods, first and second moment periods, wave height and Jonswap gamma values, wind speeds and wave heights, and wave and wind directions. All of these calculations have been done for azimuthal quadrants of the storm and radial distances near and far from the storm center.

Error Estimation of Buoy, Satellite, and Model Wave Height Data

2007 ◽  
Vol 24 (9) ◽  
pp. 1665-1677 ◽  
Author(s):  
Peter A. E. M. Janssen ◽  
Saleh Abdalla ◽  
Hans Hersbach ◽  
Jean-Raymond Bidlot
Keyword(s):  
Collocation Method ◽  
Wave Height ◽  
Wave Model ◽  
Weather Forecasts ◽  
Model Wave ◽  
Analysis Scheme ◽  
Wave Heights ◽  
Forecasting System ◽  
Buoy Data ◽  
Height Data

Abstract Triple collocation is a powerful method to estimate the rms error in each of three collocated datasets, provided the errors are not correlated. Wave height analyses from the operational European Centre for Medium-Range Weather Forecasts (ECMWF) wave forecasting system over a 4-yr period are compared with independent buoy data and dependent European Remote Sensing Satellite-2 (ERS-2) altimeter wave height data, which have been used in the wave analysis. To apply the triple-collocation method, a fourth, independent dataset is obtained from a wave model hindcast without assimilation of altimeter wave observations. The seasonal dependence of the respective errors is discussed and, while in agreement with the properties of the analysis scheme, the wave height analysis is found to have the smallest error. In this comparison the altimeter wave height data have been obtained from an average over N individual observations. By comparing model wave height with the altimeter superobservations for different values of N, alternative estimates of altimeter and model error are obtained. There is only agreement with the estimates from the triple collocation when the correlation between individual altimeter observations is taken into account. The collocation method is also applied to estimate the error in Environmental Satellite (ENVISAT), ERS-2 altimeter, buoy, model first-guess, and analyzed wave heights. It is shown that there is a high correlation between ENVISAT and ERS-2 wave height error, while the quality of ENVISAT altimeter wave height is high.

scholarly journals Validation of Jason-1 and Envisat Remotely Sensed Wave Heights

2009 ◽  
Vol 26 (1) ◽  
pp. 123-134 ◽  
Author(s):  
Tom H. Durrant ◽  
Diana J. M. Greenslade ◽  
Ian Simmonds
Keyword(s):  
Wave Height ◽  
Systematic Difference ◽  
Environmental Data ◽  
Altimeter Data ◽  
Wave State ◽  
Common Reference ◽  
State Dependent ◽  
Linear Correction ◽  
Wave Heights ◽  
Buoy Data

Abstract Satellite altimetry provides an immensely valuable source of operational significant wave height (Hs) data. Currently, altimeters on board Jason-1 and Envisat provide global Hs observations, available within 3–5 h of real time. In this work, Hs data from these altimeters are validated against in situ buoy data from the National Data Buoy Center (NDBC) and Marine Environmental Data Service (MEDS) buoy networks. Data cover a period of three years for Envisat and more than four years for Jason-1. Collocation criteria of 50 km and 30 min yield 3452 and 2157 collocations for Jason-1 and Envisat, respectively. Jason-1 is found to be in no need of correction, performing well throughout the range of wave heights, although it is notably noisier than Envisat. An overall RMS difference between Jason-1 and buoy data of 0.227 m is found. Envisat has a tendency to overestimate low Hs and underestimate high Hs. A linear correction reduces the RMS difference by 7%, from 0.219 to 0.203 m. In addition to wave height–dependent biases in the altimeter Hs estimate, a wave state–dependent bias is also identified, with steep (smooth) waves producing a negative (positive) bias relative to buoys. A systematic difference in the Hs being reported by MEDS and NDBC buoy networks is also noted. Using the altimeter data as a common reference, it is estimated that MEDS buoys are underestimating Hs relative to NDBC buoys by about 10%.

scholarly journals Accuracy of altimeter data in inner and coastal seas

2018 ◽  
Author(s):  
Luigi Cavaleri ◽  
Luciana Bertotti ◽  
Paolo Pezzutto
Keyword(s):  
Wind Speed ◽  
High Frequency ◽  
Adriatic Sea ◽  
Wave Model ◽  
Altimeter Data ◽  
Northern Adriatic Sea ◽  
Large Wave ◽  
Northern Adriatic ◽  
Wave Heights ◽  
One Year

Abstract. We carry out an inter comparison among four different altimeters, Cryosat, Jason2, Jason3, Sentinel-3. This is done checking the altimeter data versus the same wind and wave model results of a given area, the Mediterranean Sea, for one year period. The four datasets are consistent for wind speed, but they show substantial differences for wave heights. The verification of a Sentinel-3 pass close to coast in the Northern Adriatic Sea shows irregular spiky large wave height values close to coast. The problem worsens using high frequency altimeter data.

scholarly journals Accuracy of altimeter data in inner and coastal seas

Ocean Science ◽  
2019 ◽  
Vol 15 (2) ◽  
pp. 227-233 ◽  
Author(s):  
Luigi Cavaleri ◽  
Luciana Bertotti ◽  
Paolo Pezzutto
Keyword(s):  
Wind Speed ◽  
High Frequency ◽  
Adriatic Sea ◽  
Wave Model ◽  
Altimeter Data ◽  
Data Sets ◽  
Northern Adriatic Sea ◽  
Large Wave ◽  
Northern Adriatic ◽  
Wave Heights

Abstract. We carry out an inter-comparison of four different altimeters: Cryosat, Jason-2, Jason-3, and Sentinel-3. This inter-comparison is undertaken by checking the altimeter data against the wind and wave model results of a given area, the Mediterranean Sea, for a 1-year period. The four data sets are consistent for wind speed, but they show substantial differences with respect to wave heights. The verification of a Sentinel-3 pass close to the coast in the northern Adriatic Sea shows irregular, spiky, large, wave height values close to the coast. This problem worsens when using high-frequency altimeter data.

Wave Probabilities Consistent with Official Tropical Cyclone Forecasts

2016 ◽  
Vol 31 (6) ◽  
pp. 2035-2045 ◽  
Author(s):  
Charles R. Sampson ◽  
James A. Hansen ◽  
Paul A. Wittmann ◽  
John A. Knaff ◽  
Andrea Schumacher
Keyword(s):  
Surface Wave ◽  
Wind Speed ◽  
Tropical Cyclone ◽  
Wave Height ◽  
Significant Wave Height ◽  
Wave Model ◽  
Significant Wave ◽  
Wave Heights ◽  
Significant Wave Heights ◽  
Ocean Surface Wave

Abstract Development of a 12-ft-seas significant wave height ensemble consistent with the official tropical cyclone intensity, track, and wind structure forecasts and their errors from the operational U.S. tropical cyclone forecast centers is described. To generate the significant wave height ensemble, a Monte Carlo wind speed probability algorithm that produces forecast ensemble members is used. These forecast ensemble members, each created from the official forecast and randomly sampled errors from historical official forecast errors, are then created immediately after the official forecast is completed. Of 1000 forecast ensemble members produced by the wind speed algorithm, 128 of them are selected and processed to produce wind input for an ocean surface wave model. The wave model is then run once per realization to produce 128 possible forecasts of significant wave height. Probabilities of significant wave height at critical thresholds can then be computed from the ocean surface wave model–generated significant wave heights. Evaluations of the ensemble are provided in terms of maximum significant wave height and radius of 12-ft significant wave height—two parameters of interest to both U.S. Navy meteorologists and U.S. Navy operators. Ensemble mean errors and biases of maximum significant wave height and radius of 12-ft significant wave height are found to be similar to those of a deterministic version of the same algorithm. Ensemble spreads capture most verifying maximum and radii of 12-ft significant wave heights.

Toward Real-Time, Remote Observations of the Coastal Wind Resource Using High-Frequency Radar

2013 ◽  
Vol 47 (4) ◽  
pp. 206-217 ◽  
Author(s):  
Anthony Kirincich
Keyword(s):  
Wind Speed ◽  
High Frequency ◽  
Transfer Functions ◽  
Surface Wind ◽  
The United States ◽  
Coastal Ocean ◽  
Error Rates ◽  
Hf Radar ◽  
Variable Surface

AbstractThere is now a large installed base of high-frequency (HF) coastal ocean radars in the United States able to measure surface currents on an operational basis. However, these instruments also have the potential to provide estimates of the spatially variable surface wind field over distances ranging from 10 to 200 km offshore. This study investigates the ability of direction-finding HF radars to recover spatial maps of wind speed and direction from the dominant first-order region radar returns using empirical models. Observations of radar backscatter from the Martha’s Vineyard Coastal Observatory HF radar system were compared to wind observations from an offshore tower, finding significant correlations between wind speed and the backscatter power for a range of angles between the wind and radar loop directions. Models for the directional spreading of wind waves were analyzed in comparison to data-based results, finding potentially significant differences between the model and data-based spreading relationships. Using empirical fits, radar-based estimates of wind speed and direction at the location of the in situ wind sensor had error rates of 2 m/s and 60°, which decreased with hourly averaging. Attempts to extrapolate the results to the larger domain illustrated that spatially dependent transfer functions for wind speed and direction appear possible for large coastal ocean domains based on a small number of temporary, or potentially mobile, in situ wind sensors.

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