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 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;

Wave climate extremes from the Sea State CCI satellite data

2021 ◽  
Author(s):  
Marta Ramirez ◽  
Melisa Menendez ◽  
Guillaume Dodet
Keyword(s):  
Wave Height ◽  
Satellite Data ◽  
Significant Wave Height ◽  
Regional Analysis ◽  
Wave Climate ◽  
Extratropical Cyclones ◽  
Extreme Waves ◽  
Extreme Wave ◽  
Sea State ◽  
Significant Wave

&lt;p&gt;The knowledge of ocean extreme wave climate is of significant importance for a number of coastal and marine activities (e.g. coastal protection, marine spatial planning, offshore engineering). This study uses the recently released Sea State CCI v1 altimeter product to analyze extreme wave climate conditions at global scale. The dataset comprises 28-years inter-calibrated and denoised significant wave height data from 10 altimeter missions.&lt;/p&gt;&lt;p&gt;First, a regional analysis of the available satellite information of extreme waves associated with both, tropical and extratropical cyclones, is carried out. As tropical cyclones, we analyze two intense events which affected the Florida Peninsula and Caribbean Islands: Wilma (in October 2005) and Irma (in August 2017) hurricanes. As extratropical cyclones, we focused on the extreme waves during the 2013-2014 winter season along the Atlantic European coasts. The extreme waves associated with these events are identified in the satellite dataset and are compared with in situ and high-resolution simulated data. The analysis of the satellite data during the storm tracks and its comparison against other data sources indicate that satellite data can provide added value for the analysis of extreme wave conditions that caused important coastal damages.&lt;/p&gt;&lt;p&gt;After assessing the quality of extreme wave data measured by altimeters from this regional analysis, we explore a method to characterize wave height return values (e.g. 50yr return period significant wave height) from the multi-mission satellite data. The method is validated through comparisons with return values estimated from long-term wave buoy records. The extreme analysis is based on monthly maxima of satellite significant wave height computed over marine areas of varying extensions and centered on a target location (e.g. the wave buoy location for comparison and validation of the method).&amp;#160; The extension of the areas is defined from a seasonal study of the spatial correlation and the error metrics of the satellite data against the selected coastal location. We found a threshold of 0.85 correlation as the isoline to select the satellite data subsample (i.er. larger areas to select satellite maxima are found during winter seasons). Finally, a non-stationary extreme model based on GEV distribution is applied to obtain quantiles of low probability. Outcomes from satellite data are validated against extreme estimates from buoy records.&lt;/p&gt;

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 Wave Climate Change in the North Sea and Baltic Sea

2019 ◽  
Vol 7 (6) ◽  
pp. 166 ◽  
Author(s):  
Antonio Bonaduce ◽  
Joanna Staneva ◽  
Arno Behrens ◽  
Jean-Raymond Bidlot ◽  
Renate Anna Irma Wilcke
Keyword(s):  
Climate Change ◽  
Baltic Sea ◽  
Wave Height ◽  
North Sea ◽  
Significant Wave Height ◽  
Wave Climate ◽  
Significant Wave ◽  
The North ◽  
The North Sea

Wave climate change by the end of the 21st century (2075–2100) was investigated using a regional wave climate projection under the RCP 8.5 scenario. The performance of the historical run (1980–2005) in representing the present wave climate was assessed when compared with in situ (e.g., GTS) and remote sensing (i.e., Jason-1) observations and wave hindcasts (e.g., ERA5-hindcast). Compared with significant wave height observations in different subdomains, errors on the order of 20–30% were observed. A Principal Component (PC) analysis showed that the temporal leading modes obtained from in situ data were well correlated (0.9) with those from the historical run. Despite systematic differences (10%), the general features of the present wave climate were captured by the historical run. In the future climate projection, with respect to the historical run, similar wave climate change patterns were observed when considering both the mean and severe wave conditions, which were generally larger during summer. The range of variation in the projected extremes (±10%) was consistent with those observed in previous studies both at the global and regional spatial scales. The most interesting feature was the projected increase in extreme wind speed, surface Stokes drift speed and significant wave height in the Northeast Atlantic. On the other hand, a decrease was observed in the North Sea and the southern part of the Baltic Sea basin, while increased extreme values occurred in the Gulf of Bothnia during winter.

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

&lt;p&gt;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.&lt;/p&gt;

scholarly journals The Wave Climate of the Southern Ocean

2020 ◽  
Vol 50 (5) ◽  
pp. 1417-1433
Author(s):  
Ian R. Young ◽  
Emmanuel Fontaine ◽  
Qingxiang Liu ◽  
Alexander V. Babanin
Keyword(s):  
Wind Speed ◽  
Southern Ocean ◽  
Wave Height ◽  
Significant Wave Height ◽  
Wave Model ◽  
Wave Climate ◽  
Altimeter Data ◽  
Local Wind ◽  
Significant Wave ◽  
Individual Wave

AbstractThe wave climate of the Southern Ocean is investigated using a combined dataset from 33 years of altimeter data, in situ buoy measurements at five locations, and numerical wave model hindcasts. The analysis defines the seasonal variation in wind speed and significant wave height, as well as wind speed and significant wave height for a 1-in-100-year return period. The buoy data include an individual wave with a trough to crest height of 26.4 m and suggest that waves in excess of 30 m would occur in the region. The extremely long fetches, persistent westerly winds, and procession of low pressure systems that traverse the region generate wave spectra that are unique. These spectra are unimodal but with peak frequencies that propagate much faster than the local wind. This situation results in a unique energy balance in which waves at the spectra peak grow as a result of nonlinear transfer without any input from the local wind.

scholarly journals Global wave height trends and variability from new multi-mission satellite altimeter products, reanalyses and wave buoys

2020 ◽  
Author(s):  
Christine Gommenginger ◽  
Ben Timmermans ◽  
Guillaume Dodet ◽  
Jean-Raymond Bidlot
Keyword(s):  
Climate Change ◽  
Wave Height ◽  
Significant Wave Height ◽  
Temporal Trends ◽  
European Space Agency ◽  
Wave Climate ◽  
Sea State ◽  
Satellite Altimeter ◽  
Ocean Surface Waves ◽  
Significant Wave

&lt;p&gt;Accurate knowledge and understanding of the sea state and its variability is crucial to numerous oceanic and coastal engineering applications, but also to climate change and related impacts including coastal inundation from extreme weather and ice-shelf break-up. The increasing duration of the satellite altimeter record for sea state motivates a range of global analyses, including the examination of changes in ocean climate. For ocean surface waves in particular, the recent development and release of new products providing observations of altimeter-derived significant wave height make long term analyses fairly straightforward.&lt;/p&gt;&lt;p&gt;In this study, significant wave height climatologies and trends over 1992-2017 are intercompared in four recent high-quality global datasets using a consistent methodology. In particular, we make use of products presented by Ribal et al. (2019), and the recently released product developed through the European Space Agency Climate Change Initiative (CCI) for Sea State (Dodet et al. 2020, ESSD, in review). Regional differences in mean climatology are identified and linked to low and high sea states, while temporal trends from the altimetry products, and two reanalysis and hindcast datasets, show general similarity in spatial variation and magnitude but with major differences in equatorial regions and the Indian Ocean. Discrepancies between altimetry products likely arise from differences in calibration and quality control. However, multidecadal observations at buoy stations also highlight issues with wave buoy data, raising questions about their unqualified use, and more fundamentally about uncertainty in all sea state products. We discuss these results in the context of both the current state of knowledge of the changing wave climate, and the on-going development of CCI Sea State altimetry products.&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.

scholarly journals Synergy between satellite observations and model simulations during extreme events

2018 ◽  
Author(s):  
Anne Wiese ◽  
Joanna Staneva ◽  
Johannes Schultz-Stellenfleth ◽  
Arno Behrens ◽  
Luciana Fenoglio-Marc ◽  
...  
Keyword(s):  
Satellite Data ◽  
Extreme Events ◽  
Wave Model ◽  
Coastal Areas ◽  
In Situ Measurements ◽  
Model Simulations ◽  
Significant Wave ◽  
Operational Analysis

Abstract. In this study, the quality of wind and wave data provided by the new Sentinel-3A satellite is evaluated. We focus on coastal areas, where altimeter data are of lower quality than those for the open ocean. The satellite data of Sentinel-3A, Jason-2 and CryoSat-2 are assessed in a comparison with in situ measurements and spectral wave model (WAM) simulations. The sensitivity of the wave model to wind forcing is evaluated using data with different temporal and spatial resolution, such as ERA-Interim and ERA5 reanalyses, ECMWF operational analysis and short-range forecasts, German Weather Service (DWD) forecasts and regional atmospheric model simulations -coastDat. Numerical simulations show that both the wave model forced using the ERA5 reanalyses and that forced using the ECMWF operational analysis/forecast demonstrate the best capability over the whole study period, as well as during extreme events. To further estimate the variance of the significant wave height of ensemble members for different wind forcings, especially during extreme events, an empirical orthogonal function (EOF) analysis is performed. Intercomparisons between remote sensing and in situ observations demonstrate that the overall quality of the former is good over the North Sea and Baltic Sea throughout the study period, although the significant wave heights estimated based on satellite data tend to be greater than the in situ measurements by 7 cm to 26 cm. The quality of all satellite data near the coastal area decreases; however, within 10 km off the coast, Sentinel-3A performs better than the other two satellites. Analyses in which data from satellite tracks are separated in terms of onshore and offshore flights have been carried out. No substantial differences are found when comparing the statistics for onshore and offshore flights. Moreover, no substantial differences are found between satellite tracks under various metocean conditions. Furthermore, the satellite data quality does not depend on the wind direction relative to the flight direction. Thus, the quality of the data obtained by the new Sentinel-3A satellite over coastal areas is improved compared to that of older satellites.

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