Error estimation of buoy, altimeter, and model significant wave height from triple collocation technique

2021 ◽  
Author(s):  
Guillaume Dodet ◽  
Jean-Raymond Bidlot ◽  
Mickaël Accensi ◽  
Mathias Alday ◽  
Saleh Abdalla ◽  
...  
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Wave Model ◽  
Sea State ◽  
Significant Wave ◽  
In Situ Data ◽  
Collocation Technique ◽  
Coastal Risk ◽  
Marine Engineering

<p>Ocean wave information is of major importance for a number of applications including climate studies, safety at sea, marine engineering (offshore and coastal), and coastal risk management. Depending on the scales and regions of interest, several data sources may be considered (e.g. in situ data, VOS observations, altimeter records, numerical wave model), each one with its pros and cons. In order to optimize the use of multiple source wave information (e.g. through assimilation scheme in NWP), the error characteristics of each measurement system need to be investigated and inter-compared. In this study, we use triple collocation technique to estimate the random error variances of significant wave height from in situ, altimeter and model data. The buoy dataset is a selection of ~100 in-situ measuring stations provided by the CMEMS In-Situ Thematic Assembly Center. The altimeter dataset is composed of the ESA Sea State CCI V1.1 L2P product. The model dataset is the result of WW3 Ifremer hindcast run forced with ERA5 winds using the recently updated T475 parameterization. In comparisons to previous studies using similar techniques, the large triple collocation dataset (~450 000 matchups in total) generated for this study provides some new insights on the error variability within in situ stations, satellite missions and upon sea state conditions.Moreover, the results of the triple collocation technique help developing improved calibration of the altimeter missions included in the ESA Sea State CCI V1.1 dataset.</p>

scholarly journals Round Robin Assessment of Radar Altimeter Low Resolution Mode and Delay-Doppler Retracking Algorithms for Significant Wave Height

2020 ◽  
Vol 12 (8) ◽  
pp. 1254 ◽  
Author(s):  
Florian Schlembach ◽  
Marcello Passaro ◽  
Graham D. Quartly ◽  
Andrey Kurekin ◽  
Francesco Nencioli ◽  
...  
Keyword(s):  
Climate Change ◽  
Wave Height ◽  
Significant Wave Height ◽  
Low Resolution ◽  
Spectral Variability ◽  
Sea State ◽  
Significant Wave ◽  
In Situ Data ◽  
Wave Models

Radar altimeters have been measuring ocean significant wave height for more than three decades, with their data used to record the severity of storms, the mixing of surface waters and the potential threats to offshore structures and low-lying land, and to improve operational wave forecasting. Understanding climate change and long-term planning for enhanced storm and flooding hazards are imposing more stringent requirements on the robustness, precision, and accuracy of the estimates than have hitherto been needed. Taking advantage of novel retracking algorithms, particularly developed for the coastal zone, the present work aims at establishing an objective baseline processing chain for wave height retrieval that can be adapted to all satellite missions. In order to determine the best performing retracking algorithm for both Low Resolution Mode and Delay-Doppler altimetry, an objective assessment is conducted in the framework of the European Space Agency Sea State Climate Change Initiative project. All algorithms process the same Level-1 input dataset covering a time-period of up to two years. As a reference for validation, an ERA5-based hindcast wave model as well as an in-situ buoy dataset from the Copernicus Marine Environment Monitoring Service In Situ Thematic Centre database are used. Five different metrics are evaluated: percentage and types of outliers, level of measurement noise, wave spectral variability, comparison against wave models, and comparison against in-situ data. The metrics are evaluated as a function of the distance to the nearest coast and the sea state. The results of the assessment show that all novel retracking algorithms perform better in the majority of the metrics than the baseline algorithms currently used for operational generation of the products. Nevertheless, the performance of the retrackers strongly differ depending on the coastal proximity and the sea state. Some retrackers show high correlations with the wave models and in-situ data but significantly under- or overestimate large-scale spectral variability. We propose a weighting scheme to select the most suitable retrackers for the Sea State Climate Change Initiative programme.

scholarly journals Reliability of Extreme Significant Wave Height Estimation from Satellite Altimetry and In Situ Measurements in the Coastal Zone

2020 ◽  
Vol 8 (12) ◽  
pp. 1039
Author(s):  
Ben Timmermans ◽  
Andrew G. P. Shaw ◽  
Christine Gommenginger
Keyword(s):  
Coastal Zone ◽  
Wave Height ◽  
Satellite Data ◽  
Significant Wave Height ◽  
Wave Climate ◽  
In Situ Measurements ◽  
Altimeter Data ◽  
Sea State ◽  
Significant Wave

Measurements of significant wave height from satellite altimeter missions are finding increasing application in investigations of wave climate, sea state variability and trends, in particular as the means to mitigate the general sparsity of in situ measurements. However, many questions remain over the suitability of altimeter data for the representation of extreme sea states and applications in the coastal zone. In this paper, the limitations of altimeter data to estimate coastal Hs extremes (<10 km from shore) are investigated using the European Space Agency Sea State Climate Change Initiative L2P altimeter data v1.1 product recently released. This Sea State CCI product provides near complete global coverage and a continuous record of 28 years. It is used here together with in situ data from moored wave buoys at six sites around the coast of the United States. The limitations of estimating extreme values based on satellite data are quantified and linked to several factors including the impact of data corruption nearshore, the influence of coastline morphology and local wave climate dynamics, and the spatio-temporal sampling achieved by altimeters. The factors combine to lead to considerable underestimation of estimated Hs 10-yr return levels. Sensitivity to these factors is evaluated at specific sites, leading to recommendations about the use of satellite data to estimate extremes and their temporal evolution in coastal environments.

scholarly journals SIGNIFICANT WAVE HEIGHT DETERMINED FROM SEQUENCE OF X-BAND RADAR IMAGES USING TEAGER-HUANG TRANSFORM

2015 ◽  
Vol XL-7/W3 ◽  
pp. 1265-1268 ◽  
Author(s):  
M. R. Mortazavi ◽  
C. J. Huang ◽  
L. C. Wu
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Energy Operator ◽  
Radar Data ◽  
Significant Wave ◽  
Radar Images ◽  
In Situ Data ◽  
Mode Decomposition ◽  
X Band

This work introduces a nonlinear and data-dependant method for extracting the significant wave height from a sequence of X-band radar images, which is based on the Teager-Huang Transform (THH). The THH comprises two parts, which are empirical mode decomposition (EMD) and application of the Teager-Kaiser energy operator (TKEO). EMD is applied to decompose the images into various decompositions, which are narrow-banded and have mono-components; TKEO separates the aforementioned narrow-banded components into their amplitude and frequency. The standard deviation of the separated amplitude is related to <i>Hs</i> , and, the relation is obtained by calibrating radar data with in situ data (buoy). The separated frequencies reveal the orientation and intensity of data, which are directly related to the direction of the waves. For validation, the method was applied to sequences of radar images that were obtained from the west coast of Taiwan. The results obtained using the method indicate that THH can be used specifically to estimate <i>Hs</i> with a root mean square error (RMSE) of 0.34 m. Furthermore, the developed method can efficiently measure the direction of waves at each specific point in an image.

scholarly journals Reliability of Extreme Significant Wave Height Estimation from Satellite Altimetry and In Situ Measurements in the Coastal Zone

2021 ◽  
Author(s):  
Ben Timmermans ◽  
Andrew Shaw ◽  
Chrsitine Gommenginger
Keyword(s):  
Coastal Zone ◽  
Wave Height ◽  
Satellite Data ◽  
Significant Wave Height ◽  
Wave Climate ◽  
In Situ Measurements ◽  
Altimeter Data ◽  
Sea State ◽  
Significant Wave

&lt;p&gt;Measurements of significant wave height from satellite altimeter missions are finding increasing application in investigations of wave climate, sea state variability and trends, in particular as the means to mitigate the general sparsity of in situ measurements. However, many questions remain over the suitability of altimeter data for the representation of extreme sea states and in particular applications that examine extremes in the coastal zone. In this paper, the limitations of altimeter data to estimate coastal Hs extremes (&lt;10 km from shore) are investigated using the European Space Agency Sea State Climate Change Initiative (CCI) L2P altimeter data v1.1 product recently released. This Sea State CCI product provides near complete global coverage and a continuous record of 28 years. It is used here together with in situ data from moored wave buoys at a number of sites around the coast of the United States. The limitations of estimating extreme values based on satellite data are quantified and linked to several factors including the impact of data corruption nearshore, the influence of coastline morphology and local wave climate dynamics and the spatio-temporal sampling achieved by altimeters. The factors combine to lead to considerable underestimation of estimated Hs 10-yr return levels. Sensitivity to these factors is evaluated at specific sites, leading to recommendations about the use of satellite data to estimate extremes and their temporal evolution in coastal environments.&lt;/p&gt;

scholarly journals Estimation of Significant Wave Heights from ASCAT Scatterometer Data via Deep Learning Network

2021 ◽  
Vol 13 (2) ◽  
pp. 195
Author(s):  
He Wang ◽  
Jingsong Yang ◽  
Jianhua Zhu ◽  
Lin Ren ◽  
Yahao Liu ◽  
...  
Keyword(s):  
Deep Learning ◽  
Wave Height ◽  
Significant Wave Height ◽  
Incidence Angle ◽  
Ocean Waves ◽  
Global Scale ◽  
Learning Technology ◽  
Sea State ◽  
Significant Wave ◽  
Wave Heights

Sea state estimation from wide-swath and frequent-revisit scatterometers, which are providing ocean winds in the routine, is an attractive challenge. In this study, state-of-the-art deep learning technology is successfully adopted to develop an algorithm for deriving significant wave height from Advanced Scatterometer (ASCAT) aboard MetOp-A. By collocating three years (2016–2018) of ASCAT measurements and WaveWatch III sea state hindcasts at a global scale, huge amount data points (>8 million) were employed to train the multi-hidden-layer deep learning model, which has been established to map the inputs of thirteen sea state related ASCAT observables into the wave heights. The ASCAT significant wave height estimates were validated against hindcast dataset independent on training, showing good consistency in terms of root mean square error of 0.5 m under moderate sea condition (1.0–5.0 m). Additionally, reasonable agreement is also found between ASCAT derived wave heights and buoy observations from National Data Buoy Center for the proposed algorithm. Results are further discussed with respect to sea state maturity, radar incidence angle along with the limitations of the model. Our work demonstrates the capability of scatterometers for monitoring sea state, thus would advance the use of scatterometers, which were originally designed for winds, in studies of ocean waves.

Sea State Estimation Based on Ship Motions Measurements and Data Fusion

2013 ◽  
Author(s):  
Céline Drouet ◽  
Nicolas Cellier ◽  
Jérémie Raymond ◽  
Denis Martigny
Keyword(s):  
Data Fusion ◽  
State Estimation ◽  
Wave Height ◽  
Significant Wave Height ◽  
Wave Spectrum ◽  
Ocean Waves ◽  
Ship Motions ◽  
Sea State ◽  
Significant Wave ◽  
X Band

In-service monitoring can help to increase safety of ships especially regarding the fatigue assessment. For this purpose, it is compulsory to know the environmental conditions encountered: wind, but also the full directional wave spectrum. During the EU TULCS project, a full scale measurements campaign has been conducted onboard the CMA-CGM 13200 TEU container ship Rigoletto. She has been instrumented to measure deformation of the ship as well as the sea state encountered during its trip. This paper will focus on the sea state estimation. Three systems have been installed to estimate the sea state encountered by the Rigoletto: An X-band radar from Ocean Waves with WAMOS® system and two altimetric wave radars from RADAC®. Nevertheless, the measured significant wave height can be disturbed by several external elements like bow waves, sprays, sea surface ripples, etc… Furthermore, ship motions are also measured and can provide another estimation of the significant wave height using a specific algorithm developed by DCNS Research for the TULCS project. As all those estimations are inherently different, it is necessary to make a fusion of those data to provide a single estimation (“best estimate”) of the significant wave height. This paper will present the data fusion process developed for TULCS and show some first validation results.

Effect of Uni- and Bi-Directional Coupling of Ocean-Met Interaction on Significant Wave Height and Local Wind

2017 ◽  
Author(s):  
Adil Rasheed ◽  
Jakob Kristoffer Süld ◽  
Mandar Tabib
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Surface Wind ◽  
Wave Model ◽  
Ocean Surface ◽  
Observation Data ◽  
Local Wind ◽  
Near Surface ◽  
Significant Wave ◽  
Bidirectional Coupling

Accurate prediction of near surface wind and wave height are important for many offshore activities like fishing, boating, surfing, installation and maintenance of marine structures. The current work investigates the use of different methodologies to make accurate predictions of significant wave height and local wind. The methodology consists of coupling an atmospheric code HARMONIE and a wave model WAM. Two different kinds of coupling methodologies: unidirectional and bidirectional coupling are tested. While in Unidirectional coupling only the effects of atmosphere on ocean surface are taken into account, in bidirectional coupling the effects of ocean surface on the atmosphere are also accounted for. The predicted values of wave height and local wind at 10m above the ocean surface using both the methodologies are compared against observation data. The results show that during windy conditions, a bidirectional coupling methodology has better prediction capability.

scholarly journals Evaluation of Sentinel-3A Wave Height Observations Near the Coast of Southwest England

2019 ◽  
Vol 11 (24) ◽  
pp. 2998 ◽  
Author(s):  
Francesco Nencioli ◽  
Graham D. Quartly
Keyword(s):  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Wave Height ◽  
Significant Wave Height ◽  
Mean Square ◽  
Significant Wave ◽  
In Situ Observations ◽  
Regression Slopes

Due to the smaller ground footprint and higher spatial resolution of the Synthetic Aperture Radar (SAR) mode, altimeter observations from the Sentinel-3 satellites are expected to be overall more accurate in coastal areas than conventional nadir altimetry. The performance of Sentinel-3A in the coastal region of southwest England was assessed by comparing SAR mode observations of significant wave height against those of Pseudo Low Resolution Mode (PLRM). Sentinel-3A observations were evaluated against in-situ observations from a network of 17 coastal wave buoys, which provided continuous time-series of hourly values of significant wave height, period and direction. As the buoys are evenly distributed along the coast of southwest England, they are representative of a broad range of morphological configurations and swell conditions against which to assess Sentinel-3 SAR observations. The analysis indicates that SAR observations outperform PLRM within 15 km from the coast. Within that region, regression slopes between SAR and buoy observations are close to the 1:1 relation, and the average root mean square error between the two is 0.46 ± 0.14 m. On the other hand, regression slopes for PLRM observations rapidly deviate from the 1:1 relation, while the average root mean square error increases to 0.84 ± 0.45 m. The analysis did not identify any dependence of the bias between SAR and in-situ observation on the swell period or direction. The validation is based on a synergistic approach which combines satellite and in-situ observations with innovative use of numerical wave model output to help inform the choice of comparison regions. Such an approach could be successfully applied in future studies to assess the performance of SAR observations over other combinations of coastal regions and altimeters.

scholarly journals Capability of Jason-2 Subwaveform Retrackers for Significant Wave Height in the Calm Semi-Enclosed Celebes Sea

2020 ◽  
Vol 12 (20) ◽  
pp. 3367
Author(s):  
Kaoru Ichikawa ◽  
Xi-Feng Wang ◽  
Hitoshi Tamura
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Leading Edge ◽  
Sea State ◽  
Significant Wave ◽  
Contamination Sources ◽  
The Pacific ◽  
Unique System ◽  
Calm Water ◽  
Good Agreement

Satellite altimetry is a unique system that provides repeated observations of significant wave height (SWH) globally, but its measurements could be contaminated by lands, slicks, or calm water with smooth surface. In this study, capability of subwaveform retrackers against 20 Hz Jason-2 measurements is examined in the calm Celebes Sea. Distances between contamination sources and Jason-2 observation points can be determined using sequentially assembled adjacent waveforms (radargram). When no contamination sources are present within a Jason-2 footprint, subwaveform retrackers are in excellent agreement with the Sensor Geophysical Data Records (SGDR) MLE4 retracker that uses full-length waveforms, except that Adaptive Leading Edge Subwaveform (ALES) retracker has a positive bias in a calm sea state (SWH < 1 m), which is not unusual in the Celebes Sea. Meanwhile, when contamination sources exist within 4.5 km from Jason-2 observation points, SGDR occasionally estimates unrealistically large SWH values, although they could be partly eliminated by sigma0 filters. These datasets are then compared with WAVEWATCH III model, resulting in good agreement. The agreement becomes worse if swells from the Pacific is excluded in the model, suggesting constant presence of swells despite the semi-enclosed nature. In addition, outliers are found related with locally-confined SWH events, which could be inadequately represented in the model.

Uncertainty of Ocean Wave Hindcasts Due to Wind Modeling

1995 ◽  
Vol 117 (4) ◽  
pp. 294-297 ◽  
Author(s):  
J. C. Teixeira ◽  
M. P. Abreu ◽  
C. Guedes Soares
Keyword(s):  
Wind Speed ◽  
Relative Error ◽  
Wave Height ◽  
Significant Wave Height ◽  
Second Generation ◽  
Wave Model ◽  
Ocean Wave ◽  
Wind Fields ◽  
Significant Wave ◽  
Wind Input

Two wind models were developed and their results were compared with data gathered during the Wangara experiment, so as to characterize their uncertainty. One of the models was adopted to generate the wind fields used as input to a second generation wave model. The relative error in the wind speed was considered in order to assess the uncertainties of the predictions or the significant wave height. Different time steps for the wind input were also used to determine their effect on the predicted significant wave height.

Sign in / Sign up

Export Citation Format

Share Document