Significant Wave Height Data Research Articles

Are Jason-2 significant wave height measurements still useful

Jason-2 was launched on June 20, 2008. The main payload of Jason-2 is a radar altimeter that measures, among other variables, significant wave height (SWH) and surface wind speed. To compliment the 25-year reference altimetry record, Jason-2 left its orbit to its younger sibling Jason-3 which was launched on January 17, 2016 and became operational on October 14, 2016. Jason-2 was then moved to another location on the same orbit till July 2017 when it was moved to a new long-repeat orbit (LRO) for the first geodetic cycle. Then it was moved to an interleaved long repeat orbit (i-LRO) in July 2018 for the second geodetic cycle. Jason-2 continued to provide SWH and wind speed measurements. After more than 10 years in space, a few orbit changes and going through few operational disruptions the question is whether Jason-2 SWH (and wind speed) measurements are useful. The simple answer is that Jason-2 SWH data are as useful as similar data from any other altimeter in space and are as effective in reducing the model random SWH errors through wave data assimilation. It is recommended to keep Jason-2 in orbit and to support the provision of its ocean wave data in near real time for as long period as possible.

Extreme value statistics of wind speed and wave height of the Marmara Sea based on combined radar altimeter data

Both reliable and long-term wind and wave data are necessary for the design of coastal and offshore structures. Due to lack of sufficient in-situ measurement data, modeling data have been used in the limited number of wind and wave climate studies of the Marmara Sea. Satellites equipped with instruments capable of observing marine surface wind and ocean waves like Radar Altimeter can be another source for the long term wind and wave climate of the Marmara Sea. In this study, for the first time, the altimeter wind speed and the significant wave height data from different satellite missions are attempted to use in the climate and extreme value analysis of the Marmara Sea. Altimeter wind speeds and significant wave heights are compared with the in-situ measurements and it is found that while the altimeter wind speed agrees with the measurement data, the significant wave height data should be calibrated. After the calibration of the altimeter data and the inter-calibrations of earlier satellite missions, 27 years of altimeter wind speed and wave height data are obtained to use in extreme value analysis. The wind speed and the significant wave height values corresponding to various return periods are determined as a result of extreme value statistics and those values are compared with the results of the measurements and previous studies. Consistent extreme values computed in the current study indicate that the combined radar altimeter data can be used in the wind and the wave climate calculations and the extreme value analysis of the Marmara Sea.

Validation of Sentinel-3A/3B Satellite Altimetry Wave Heights with Buoy and Jason-3 Data.

The validation of significant wave height (SWH) data measured by the Sentinel-3A/3B SAR Altimeter (SRAL) is essential for the application of the data in ocean wave monitoring, forecasting and wave climate studies. Sentinel-3A/3B SWH data are validated by comparisons with U. S. National Data Buoy Center (NDBC) buoys, using a spatial scale of 25 km and a temporal scale of 30 min, and with Jason-3 data at their crossovers, using a time difference of less than 30 min. The comparisons with NDBC buoy data show that the root-mean-square error (RMSE) of Sentinel-3A SWH is 0.30 m, and that of Sentinel-3B is no more than 0.31 m. The pseudo-Low-Resolution Mode (PLRM) SWH is slightly better than that of the Synthetic Aperture Radar (SAR) mode. The statistical analysis of Sentinel-3A/3B SWH in the bin of 0.5 m wave height shows that the accuracy of Sentinel-3A/3B SWH data decreases with increasing wave height. The analysis of the monthly biases and RMSEs of Sentinel-3A SWH shows that Sentinel-3A SWH are stable and have a slight upward trend with time. The comparisons with Jason-3 data show that SWH of Sentinel-3A and Jason-3 are consistent in the global ocean. Finally, the piecewise calibration functions are given for the calibration of Sentinel-3A/3B SWH. The results of the study show that Sentinel-3A/3B SWH data have high accuracy and remain stable.

Aqua MODIS and altimetry satellite data utilization for determining the effective time and area of fishing in South Sulawesi

South Sulawesi is one of the provinces in Indonesia which geographically is a marine-based area with huge potential of marine resources. In sea resources exploration activities are often found obstacles caused by the variability of weather and climate that affect the condition of South Sulawesi waters. Limited availability of weather data in the waters of South Sulawesi Province has caused difficulties in analyzing and identifying conditions in these waters. The use of the MODIS Aqua satellite and Altimetry can be used as a solution in the analysis and identification of water conditions. Aqua MODIS satellite data used in this study is the sea surface temperature (SST) and chlorophyll-a data while the Altimetry satellite data used is significant wave height data. In addition, Niño 3.4 Index are used as supporting data to identify the weather and climate phenomena that occur in the waters of South Sulawesi in this case are El Niño and the Southern Oscillation (ENSO) phenomena. SST and chlorophyll-a data are used as indicators in determining fish catch potential and significant wave height data are used to determine the effective time in fishing activities in the waters of South Sulawesi Province. The results showed that a significant wave peak height in the waters of South Sulawesi occurred in July. The highest chlorophyll-a average occurred in August when the average SST showed the lowest value or when the El Niño event occurred.

Development of a fine-resolution atmosphere-wave-ocean coupled forecasting model for the South China Sea and its adjacent seas

A 72-h fine-resolution atmosphere-wave-ocean coupled forecasting system was developed for the South China Sea and its adjacent seas. The forecasting model domain covers from from 15°S to 45°N in latitude and 99°E to 135°E in longitude including the Bohai Sea, the Yellow Sea, the East China Sea, the South China Sea and the Indonesian seas. To get precise initial conditions for the coupled forecasting model, the forecasting system conducts a 24-h hindcast simulation with data assimilation before forecasting. The Ensemble Adjustment Kalman Filter (EAKF) data assimilation method was adopted for the wave model MASNUM with assimilating Jason-2 significant wave height (SWH) data. The EAKF data assimilation method was also introduced to the ROMS model with assimilating sea surface temperature (SST), mean absolute dynamic topography (MADT) and Argo profiles data. To improve simulation of the structure of temperature and salinity, the vertical mixing scheme of the ocean model was improved by considering the surface wave induced vertical mixing and internal wave induced vertical mixing. The wave and current models were integrated from January 2014 to October 2015 driven by the ECMWF reanalysis 6 hourly mean dataset with data assimilation. Then the coupled atmosphere-wave-ocean forecasting system was carried out 14 months operational running since November 2015. The forecasting outputs include atmospheric forecast products, wave forecast products and ocean forecast products. A series of observation data are used to evaluate the coupled forecasting results, including the wind, SHW, ocean temperature and velocity. The forecasting results are in good agreement with observation data. The prediction practice for more than one year indicates that the coupled forecasting system performs stably and predict relatively accurate, which can support the shipping safety, the fisheries and the oil exploitation.

Accuracy assessment of wave data from altimeter near the coast

This study presents a methodology to verify the notion that wave measurements could be less accurate near the coast when they are provided by altimetry radars (on-board satellites). The methodology is based on comparing significant wave height (Hs) data from the RA-2 altimetry radar on-board ENVISAT satellite (European Space Agency) against points from a Gulf of Cadiz database that were propagated through SMC software (Sistema de Modelado Costero). Nine years of SWELL waves were analysed (2002–2010). The results show a RMSE of only 0.19 m (correlation coefficient of R ≥ 0.96) in deep waters, but this decreases within 10 km of the coastline, reaching a value of 1.12 m (R = 0.16) at 5 km from the coast.

The Condition of Significant Wave Height and Wind Velocity in Makassar Strait during 2017

This study aims to look at the conditions and characteristics of significant wave height and its relationship to wind velocity in the Makassar Strait in 2017. The data used in this study are bathymetry data from GEBCO with a resolution of 30 seconds, significant wave height data (Hs) with a resolution of 0.25 x 0.25 as well as wind velocity and direction with a resolution of 0.25 x 0.25 which are secondary data results from the European Center for Medium-Range Weather Forecasts (ECMWF) with a span of one year in 2017. The method used in this research is an analysis of the energy spectrum of significant wave height using Fast Fourier Transform. In addition, wind velocity and direction are processed by using GrADS software to see the visual conditions. Based on this study, it can be concluded that wind velocity is strongly associated with significant wave height values. This can be seen at each sample point in the Makassar Strait, where when the value of wind velocity is high, the value of significant wave height has the same conditions, and vice versa. The wind velocity value has a maximum value in the Makassar Strait during the east season with a value of more than 4.5 m/s. The highest energy spectrum occurs at point 3 in the Makassar Strait, which is 7303 m2 with a period of 6 months.

ASSESSMENT OF SEASONAL VARIABILITY FOR WIND SPEED AND SIGNIFICANT WAVE HEIGHT USING SATELLITE ALTIMETER OVER MALAYSIAN SEAS

Abstract. Malaysia is located in the equatorial region and experienced climate hot, humid and rainy throughout the year. These have brought four monsoon seasons to Malaysia which can be categorised as Northeast monsoon, Southwest monsoon, First-inter monsoon and Second-inter monsoon. Although Malaysia is surrounded by large scale marine resources, the lack of understanding in seasonal variability has affected the spatial and temporal analysis. Thus, this study will highlight the assessment of seasonal variability of wind speed and significant wave height over the Malaysian seas. For more than two decades satellite altimeter data were used to generate a prolonged trend of regional ocean wind speed and significant wave height in order to study the monsoons in Malaysia. A set of wind speed and significant wave height data are compared with the in-situ measurement to validate the accuracy of the wind speed and significant wave height observation using the satellite altimeter. Two selected buoys were using as benchmarks and assessed using the statistical analysis by conducting a root mean square error and a correlation calculation. Seasonal variations assessment is conducted with significance to analyse the monsoon effect towards the wind speed and significant wave height condition. As a result, both ocean parameters present a good value of root mean square error and positive correlation which were 0.7976 (wind speed) and 0.92 (significant wave height), which proves the measurement from satellite altimeter is reliable to use. In addition, the seasonal variation assessment illustrates during the Northeast monsoon, each part of the Malaysian seas experienced with great wind speed and significant wave height.

Extreme wave climate variability in South China Sea

Extreme wave climate variability in the South China Sea (SCS) was investigated using significant wave height (SWH) data simulated by the third generation wave model WAVEWATCH-III (WW-III) for the period 1976–2014. The wind forcing data was using the objective reanalysis wind dataset from the weather research and forecasting (WRF) model. The simulated SWH was well validated by observation data from satellite altimeter and in-situ buoys. A generalized extreme value (GEV) model was applied to analyze the extreme wave climate variability. Monthly significant wave height maxima is used to characterize the seasonal variability. The spatial distributions of positional and scale parameters are achieved. The positional parameter values reach the maximum in winter, while the scale parameter values are greater in summer and autumn due to the impact of typhoon. The regression analysis of harmonic functions was applied to give the annual cycle. Interannual climatology of extreme wave climate from Empirical Orthogonal Function (EOF) decomposition method and spectrum analysis method revealed a dominant 12 months period and a 22 months period, respectively. Results show that El Nino may significantly affect the extreme wave climate variability in the SCS.

Spatial variability of long-term trends of significant wave heights in the Black Sea

This study aims to estimate the spatial variability of the long-term trends of Significant Wave Height (SWH) in the Black Sea. A spectral wave model was used to hindcast 38 years of SWH forced by ECMWF ERA Interim wind fields. Long-term trends were estimated from normalized SWH (NSWH) data, for each month separately, by using two non-parametric methodologies; Line of best fit and the Theil-Sen estimator, and then mapped to show their spatial variability. Maps were generated for both mean SWHs and 95th percentile SWHs, the latter is considered to reflect the trends of the severe sea states. The basin-averaged analysis was also carried out to investigate the general tendency of SWHs in the Black Sea. The significance of the trends was evaluated by using Mann-Kendall test. The annual mean SWH is found to be increasing (up to 1.6%/year) in the eastern part of the Black Sea while the western part has a negative trend (down to −1.2%/year). Long-term analysis of the 95th percentile SWHs revealed steeper trend slopes and higher statistical significance compared to the mean SWH trends, showing that storm SWHs have a higher tendency to increase than the mean SWHs. Statistically significant correlations between climate indices; North Atlantic Oscillation (NAO), Arctic Oscillation (AO), Antarctic Oscillation (AAO), Atlantic Multidecadal Oscillation (AMO), Pacific North American (PNA), East Atlantic (EA), East Atlantic/West Russia (EA/WR), Scandinavia (SCAND), Niño3 and the Black Sea wave fields were identified.

Long-Term Characterization of Sea Conditions in the East China Sea Using Significant Wave Height and Wind Speed

In this study, the statistical characterization of sea conditions in the East China Sea (ECS) is investigated by analyzing a significant wave height and wind speed data at a 6-hour interval for 30 years (1980–2009), which was simulated and computed using the WAVEWATCH III (WW3) model. The monthly variations of these parameters showed that the significant wave height and wind speed have minimum values of 0.73 m and 5.15 m s−1 and 1.73 m and 8.24 m s−1 in the month of May and December, respectively. The annual, seasonal, and monthly mean sea state characterizations showed that the slight sea generally prevailed in the ECS and had nearly the highest occurrence in all seasons and months. Additionally, the moderate sea prevailed in the winter months of December and January, while the smooth (wavelets) sea prevailed in May. Furthermore, the spatial variation of sea states showed that the calm and smooth sea had the largest occurrences in the northern ECS. The slight sea occurred mostly (above 30%) in parts of the ECS and the surrounding locations, while higher occurrences of the rough and very rough seas were distributed in waters between the southwest ECS and the northeast South China Sea (SCS). The occurrences of the phenomenal sea conditions are insignificant and are distributed in the northwest Pacific and its upper region, which includes the Southern Kyushu-Palau Ridge and Ryukyu Trench.

Assessment of wave energy resource in the mid-Atlantic based on 37-year numerical hindcast data

This study presents results from an investigation of wave energy resources over the mid-Atlantic by using the significant wave height and mean wave period (T_m) data spanning a 37 year (1980–2016) period and derived from the analysis of wave climate predictions generated by the WAVEWATCH-III wind-wave model. The spatiotemporal variations of the wave energy resource are presented and described. Results showed that wave energy is richest (11.5–14 kW/m) in regions such as West Indies, East of Martinique and Guiana basin in the extreme northwestern mid-Atlantic and are therefore ideal locations for the installation of wave power plants for electrical energy generation. Temporal variation revealed that 1992 was a year of relatively rich wave energy in the mid-Atlantic. Also, a characterization of wave energy showed that the wave energy groups 0 ≤ wp ≤ 5 and 5 ≤ wp ≤ 10, prevailed in the mid-Atlantic. Furthermore, spatial trend analysis of the annual and summer mean wave power showed that stronger trends (0.03–0.1 kW/m/year) in both cases, distribute in the southern mid-Atlantic while stronger trends (0.04–0.085 kW/m/year) dominate the northern mid-Atlantic at winter. Temporal trend analysis for the years and seasons showed that wave power exhibits an insignificant trend of approximately 0.022 kW/m/year in the mid-Atlantic.

Validation of significant wave height retrieval from co-polarization Chinese Gaofen-3 SAR imagery using an improved algorithm

Chinese Gaofen-3 (GF-3) is the first civilian satellite to carry C-band (5.3 GHz) synthetic aperture radar (SAR). During the period of August 2016 to December 2017, 1 523 GF-3 SAR images acquired in quad-polarization (vertical-vertical (VV), horizontal-horizontal (HH), vertical-horizontal (VH), and horizontal-vertical (HV)) mode were recorded, mostly around China’s seas. In our previous study, the root mean square error (RMSE) of significant wave height (SWH) was found to be around 0.58 m when compared with retrieval results from a few GF-3 SAR images in co-polarization (VV and HH) with moored measurements by using an empirical algorithm CSAR_WAVE. We collected a number of sub-scenes from these 1 523 images in the co-polarization channel, which were collocated with wind and SWH data from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis field at a 0.125° grid. Through the collected dataset, an improved empirical wave retrieval algorithm for GF-3 SAR in co-polarization was tuned, herein denoted as CSAR_WAVE2. An additional 92 GF-3 SAR images were implemented in order to validate CSAR_WAVE2 against SWH from altimeter Jason-2, showing an about 0.52 m RMSE of SWH for co-polarization GF-3 SAR. Therefore, we conclude that the proposed empirical algorithm has a good performance for wave retrieval from GF-3 SAR images in co-polarization.

Meteo-Marine Parameters from Sentinel-1 SAR Imagery: Towards Near Real-Time Services for the Baltic Sea

A method for estimating meteo-marine parameters from satellite Synthetic Aperture Radar (SAR) data, intended for near-real-time (NRT) service over the Baltic Sea, is presented and validated. Total significant wave height data are retrieved with an empirical function CWAVE_S1-IW, which combines spectral analysis of Sentinel-1A/B Interferometric Wide swath (IW) subscenes with wind data derived with common C-Band Geophysical Model Functions (GMFs). In total, 15 Sentinel-1A/B scenes (116 acquisitions) over the Baltic Sea were processed for comparison with off-shore sea state measurements (52 collocations) and coastal wind measurements (357 colocations). Sentinel-1 wave height was spatially compared with WAM wave model results (Copernicus Marine Environment Monitoring Service (CMEMS). The comparison of SAR-derived wave heights shows good agreement with measured wave heights correlation r of 0.88 and with WAM model (r = 0.85). The wind speed estimated from SAR images yields good agreement with in situ data (r = 0.91). The study demonstrates that the wave retrievals from Sentinel-1 IW data provide valuable information for operational and statistical monitoring of wave conditions in the Baltic Sea. The data is valuable for model validation and interpretation in regions where, and during periods when, in situ measurements are missing. The Sentinel-1 A/B wave retrievals provide more detailed information about spatial variability of the wave field in the coastal zone compared to in situ measurements, altimetry wave products and model forecast. Thus, SAR data enables estimation of storm locations and areal coverage. Methods shown in the study are implemented in NRT service in German Aerospace Center’s (DLR) ground station Neustrelitz.

Modeling and Sizing of an Undersea Energy Storage System

This paper presents modeling and sizing of an undersea energy storage system (USS). The USS, which is placed at the seabed, consists of a concrete sphere, a reversible pump-turbine unit, a permanent magnet synchronous machine, and a steel pipe through which water flows into/out of the sphere from/to the deep ocean. A novel mathematical model is derived to describe the governing equations of the USS operation. It is assumed that the USS operates in parallel with a direct-drive wave energy converter (DDWEC) and a novel sizing algorithm is developed to obtain the required USS capacity/size for regulating the DDWEC output power fluctuations during a designated period of time. In order to determine the DDWEC output power profile, wave spectrums are required. Real significant wave height and dominant wave period data, which are measured and collected by a buoy station in the Gulf of Maine, are used to generate wave profiles based on the modified two-parameter Pierson-Moskowitz spectrum. Eventually, Monte Carlo simulations with a thousand generated wave profiles are carried out to determine the optimal size of the USS for all possible scenarios. Furthermore, through promising results obtained from hardware-in-the-loop studies, the effective role of the USS in regulating the wave energy converter output power fluctuations is demonstrated.

A global high-resolution ocean wave model improved by assimilating the satellite altimeter significant wave height

This study examines the effects of data assimilation using Significant Wave Height (SWH) from three satellite altimeters, notably the Jason-2, Jason-3 and SAtellite with ARgos and ALtiKa (SARAL), orbiting in space and incorporating the data into a global high-resolution ocean wave model. The third-generation wave model, WAVEWATCH III (WW3), was adopted for numerical simulation and its spatial resolution was refined to 0.2°. Data assimilation is carried out using the Optimal Interpolation (OI) scheme to demonstrate the feasibility and the benefits of simultaneously assimilating the along-track SWH data from multi-satellite altimeters into a global ocean wave model. Higher resolution global ocean wave models can advantageously account for the swell propagation from deep ocean waters without open boundary conditions, as well as simulate smaller scale wind waves from the coastal zones conveniently, effectively and in tandem. The Root Mean Square (RMS) of non-assimilation experiment is 0.54 m, which is smaller than the previous coarse resolution global wave modelling. Minor improvement is found when only one 10-min frequency, SWH data from the Jason-2 altimeter was assimilated into the global ocean wave model. However, the RMS against buoy observations is highly reduced (i.e. approximately 0.42 m) when the SWH data from three satellite altimeters (i.e. Jason-2, Jason-3 and SARAL) are simultaneously assimilated into the global high-resolution ocean wave model and in return, led to significant model improvement. This study can also provide some implications for wave predictions in global oceans.

Assessment of extreme wind and waves in the Colombian Caribbean Sea for offshore applications

Interest in Colombia’s offshore industry has increased over the past years. Therefore a detailed characterization of extreme wind and waves, in terms of return periods, numbers of events and its duration during the annual cycle, is needed. Two sets of high-resolution data are used in the statistical extreme value analysis (EVA). The significant wave height data (0.125°, 6h) are from the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim reanalysis available for the past 35 years (1979–2014). Surface winds (0.25°, 6h) from the Cross-Calibrated Multi-Platform Ocean Surface Wind Vector Analyses (CCMP) of NASA/GSFC/NOAA (NASA/Goddard Space Flight Center/National Oceanic and Atmospheric Administration) are available for the past 24 years (1987–2011). Three well-known methods are applied to the data: the Block Maxima (BM), the Peak-Over-Threshold (POT) and the Method of Independent Storm (MIS). Several probabilistic models (Gumbel, Generalized Extreme Value, Weibull and Pareto) are evaluated for the BM and different threshold values for the POT and MIS. The results show that waves can reach up to 3.8m and winds can be as strong as 31m/s when considering the 50–100-year return periods. However, the wave model could underestimate values by up to one meter; hence, there is a probability of higher values in the region. Seasonally, most extreme events occur during the dry season (December–March) and during the Mid-Summer-Drought (MDS) or Veranillo months (June–July). Local conditions, including the reinforcement of the Caribbean Low Level Jet (CLLJ) and the occurrence of cold atmospheric fronts, are important drivers of extreme metoceanic variability. The total number of extreme wind events varied spatially and temporally from 15 to 65 and the mean duration from 15 to 25h. A total number of extreme wave events ranging from <10 to 80 were computed during the annual cycle in the areas of interest, with a mean duration of less than 40h.

Validation of the Significant Wave Height Product of HY-2 Altimeter

HY-2 was launched by China on August 2011, which has provided continuous wave height measurements to monitor ocean dynamic environments for more than 5 years. Before using these data, however, the measurements need to be validated. Based on the in situ buoy data from the National Data Buoy Center (NDBC) and the Jason-2 altimeter data, the HY-2 Ku-band significant wave height (SWH) measurements were validated. The comparisons showed that a linear regression with NDBC measurements can be used to improve the accuracy of the HY-2 SWH measurements. Compared with the NDBC SWH data, the validation results of the HY-2 SWH data show an RMS (root mean square) of 0.33 m, which is similar to that of the Jason-1 and Jason-2 data; the RMS of the HY-2 SWH is 0.30 m, which, corrected via linear regression, is similar to that of the corrected Jason-1 and Jason-2 data (0.27 m and 0.23 m, respectively). Therefore, the accuracy of the HY-2 SWH products is close to that of the Jason-1/2 SWH data.

An Empirical Algorithm for Wave Retrieval from Co-Polarization X-Band SAR Imagery

In this study, we proposed an empirical algorithm for significant wave height (SWH) retrieval from TerraSAR-X/TanDEM (TS-X/TD-X) X-band synthetic aperture radar (SAR) co-polarization (vertical-vertical (VV) and horizontal-horizontal (HH)) images. As the existing empirical algorithm at X-band, i.e., XWAVE, is applied for wave retrieval from HH-polarization TS-X/TD-X image, polarization ratio (PR) has to be used for inverting wind speed, which is treated as an input in XWAVE. Wind speed encounters saturation in tropical cyclone. In our work, wind speed is replaced by normalized radar cross section (NRCS) to avoiding using SAR-derived wind speed, which does not work in high winds, and the empirical algorithm can be conveniently implemented without converting NRCS in HH-polarization to NRCS in VV-polarization by using X-band PR. A total of 120 TS-X/TD-X images, 60 in VV-polarization and 60 in HH-polarization, with homogenous wave patterns, and the coincide significant wave height data from European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis field at a 0.125° grid were collected as a dataset for tuning the algorithm. The range of SWH is from 0 to 7 m. We then applied the algorithm to 24 VV and 21 HH additional SAR images to extract SWH at locations of 30 National Oceanic and Atmospheric Administration (NOAA) National Data Buoy Center (NDBC) buoys. It is found that the algorithm performs well with a SWH stander deviation (STD) of about 0.5 m for both VV and HH polarization TS-X/TD-X images. For large wave validation (SWH 6–7 m), we applied the empirical algorithm to a tropical cyclone Sandy TD-X image acquired in 2012, and obtained good result with a SWH STD of 0.3 m. We concluded that the proposed empirical algorithm works for wave retrieval from TS-X/TD-X image in co-polarization without external sea surface wind information.

Regional frequency analysis of extreme waves in a coastal area

This study analysed the wave data from several locations in a coastal region to identify the areas with comparable wave height statistics and to estimate regional extreme significant wave heights of designated return periods. The regional frequency analysis algorithm executed in this work utilised the significant wave height data from 35 sites (35°–45°N, -6.5°–-11.0°W) in a coastal grid (0.25° × 0.25°) off Portugal in the North Atlantic Ocean, extracted from 44 years HIPOCAS hindcast wave database. Regional frequency analysis algorithms based on L-moments identified the discordant sites (discordant site statistics are substantially diffused from the group of sites statistics), assisted in the formation of homogeneous regions by cluster analyses (data vectors include site characteristics and site statistics) and consequently selected appropriate regional frequency distributions by Z goodness-of-fit test statistic at 90% level of significance to estimate regional extreme significant wave height quantiles of designated return periods. The regional frequency analysis algorithm recognised in certain cases, neighbouring sites as members of diverse regions, revealing that geographical proximity of sites are not ascertaining factors to form homogeneous regions. At-site analyses along with regional frequency analysis enabled to apprehend the precision of the regional extreme quantile as genuine feature of its at-site extreme quantiles.