Discovery of the Significant Impacts of Swell Propagation on Global Wave Climate Change

This study compared the differences in the wave climate in the South China Sea and North Indian Ocean under these two datasets:ERA-40 wave reanalysis and Mei’s hindcast wave data.In the numerical calculation of regional ocean waves,the wave climate characteristics exhibited significant bias if the influence of external swells(swells from afar)was not fully considered,which may provide an incorrect basis for global climate change analysis.1)The trends of the significant wave height(SWH)obtained from the two datasets showed significant differences,such as those of the Bay of Bengal and the Java Sea in June-July-August.For the past 45 years,SWH from ERA-40(SWH-ERA)exhibited a significant annual increase in low-latitude waters of the North Indian Ocean(0.2-0.6 cm yr^(-1))and South China Sea(0.2-0.8 cm yr^(-1)).2)In the Bay of Bengal,the SWH-ERA in each month was generally 0.5 m higher than the SWH from Mei’s hindcast wave data(SWH-Mei)and can reach 1.0 m higher in some months.3)In the Bay of Bengal,SWH-ERA and SWH-Mei increased significantly at annual rates of 0.13 and 0.27 cm yr^(-1),respectively.This increasing trend was mainly reflected after 1978.SWH-ERA showed a trough in 1975(1.33 m)and a crest in 1992(1.83 m),which were not reflected in SWH-Mei.

Simulation of Deep Water Wave Climate for the Indian Seas

The ocean wave climate has a variety of applications in Naval defence.However,a long-term and reliable wave climate for the Indian Seas(The Arabian Sea and The Bay of Bengal)over a desired grid resolution could not be established so far due to several constraints.In this study,an attempt was made for the simulation of wave climate for the Indian Seas using the third-generation wave model(3g-WAM)developed by WAMDI group.The 3g-WAM as such was implemented at NPOL for research applications.The specific importance of this investigation was that,the model utilized a“mean climatic year of winds”estimated using historical wind measurements following statistical and probabilistic approaches as the winds which were considered for this purpose were widely scattered in space and time.Model computations were carried out only for the deep waters with current refraction.The gridded outputs of various wave parameters were stored at each grid point and the spectral outputs were stored at selected locations.Monthly,seasonal and annual distributions of significant wave parameters were obtained by post-processing some of the model outputs.A qualitative validation of simulated wave height and period parameters were also carried out by comparing with the observed data.The study revealed that the results of the wave climate simulation were quite promising and they can be utilized for various operational and ocean engineering applications.Therefore,this study will be a useful reference/demonstration for conducting such experiments in the areas where wind as well as wave measurements are insufficient.

Long-Term Extreme Wave Characteristics in the Water Adjacent to China Based on ERA5 Reanalysis Data

Extreme waves have a profound impact on coastal infrastructure;thus,understanding the variation law of risky analysis and disaster prevention in coastal zones is necessary.This paper analyzed the spatiotemporal characteristics of extreme wave heights adjacent to China from 1979 to 2018 based on the ERA5 datasets.Nonstationary extreme value analysis is undertaken in eight repre-sentative points to investigate the trends in the values of 50-and 100-year wave heights.Results show that the mean value of extreme waves is the largest in the eastern part of Taiwan Island and the smallest in the Bohai Sea from 1979 to 2018.Only the extreme wave height in the northeastern part of Taiwan Island shows a significant increase trend in the study area.Nonstationary analysis shows remarkable variations in the values of 50-and 100-year significant wave heights in eight points.Considering the annual mean change,E1,E2,S1,and S2 present an increasing trend,while S3 shows a decreasing trend.Most points for the seasonal mean change demon-strate an increasing trend in spring and winter,while other points show a decreasing trend in summer and autumn.Notably,the E1 point growth rate is large in autumn,which is related to the change in typhoon intensity and the northward movement of the typhoon path.

APPLICATION OF MAXIMUM ENTROPY PRINCIPLE METHOD TO THE STUDY OF WAVE CLIMATE STATISTICAL CHARACTERISTICS

The Maximum Entropy Principle (MEP) method is elaborated, and thecorresponding probability density evaluation method for the random fluctuation system is introduced,the goal of the article is to find the best fitting method for the wave climate statisticaldistribution. For the first time, a kind of new maximum entropy probability distribution (MEPdistribution) expression is deduced in accordance with the second order moment of a random process.Different from all the fitting methods in the past, the MEP distribution can describe theprobability distribution of any random fluctuation system conveniently and reasonably. If themoments of the random signal is limited to the second order, that is, the ratio of theroot-mean-square value to the mean value of the random variable is obtained from the random sample,the corresponding MEP distribution can be computed according to the deduced expression in thisessay. The concept of the wave climate is introduced here, and the MEP distribution is applied tofit the probability density distributions of the significant wave height and spectral peak period.Take the Mexico Gulf as an example, three stations at different locations, depths and wind wavestrengths are chosen in the half-closed gulf, the significant wave height and spectral peak perioddistributions at each station are fitted with the MEP distribution, the Weibull distribution and theLog-normal distribution respectively, the fitted results are compared with the field observations,the results show that the MEP distribution is the best fitting method, and the Weibull distributionis the worst one when applied to the significant wave height and spectral peak period distributionsat different locations, water depths and wind wave strengths in the Gulf. The conclusion shows thefeasibility and reasonability of fitting wave climate statistical distributions with the deduced MEPdistributions in this essay, and furthermore proves the great potential of MEP method to the studyof wave statistical properties.

Nonstationary fuzzy forecasting of wind and wave climate in very long-term scales

Global climate change may have serious impact on human activities in coastal and other areas.Climate change may affect the degree of storminess and,hence,change the wind-driven ocean wave climate.This may affect the risks associated with maritime activities such as shipping and offshore oil and gas.So,there is a recognized need to understand better how climate change will affect such processes.Typically,such understanding comes from future projections of the wind and wave climate from numerical climate models and from the stochastic modelling of such projections.This work investigates the applicability of a recently proposed nonstationary fuzzy modelling to wind and wave climatic simulations.According to this,fuzzy inference models(FIS)are coupled with nonstationary time series modelling,providing us with less biased climatic estimates.Two long-term datasets for an area in the North Atlantic Ocean are used in the present study,namely NORA10(57 years)and ExWaCli(30 years in the present and 30 years in the future).Two distinct experiments have been performed to simulate future values of the time series in a climatic scale.The assessment of the simulations by means of the actual values kept for comparison purposes gives very good results.

Wave Energy Resource Availability Assessment in the Philippines Based on 30-Year Hindcast Data

With the goal of evaluating the wave and wave energy conditions in the Philippines,the simulated wave nearshore(SWAN)model was used to estimate the wavefield using 30 years of cross-calibrated multi-platform(CCMP)wind field data(1987-2016).The spatiotemporal patterns of annual and monthly averaged significant wave heights and wave energy in the Philippines were analyzed based on the simulated data.Results showed that they had similar values;in particular,significant wave heights and wave energy were smaller in the south and southwest and higher in the north and northeast.A total of 12 representative points along the Philippine coast were selected to draw wave and wave energy roses.A directional analysis showed that the dominant wave was in the north north-east(NNE),northeast(NE),and east north-east(ENE)directions.Wave energy was mainly distributed in regions with an energy period between 1 and 10 s and significant wave heights between 0 and 4 m.To better utilize wave energy data in the Philippines,this paper studied the available and rich area of wave energy and analyzed the annual and monthly variability index of wave energy in the country.Moreover,the available significant wave heights of wave energy conversion devices(WECs)were set as 0.5-4 m,and the maximum annual average available wave energy occurred in the eastern Philippine Sea area,reaching 13 kW m^(-1).For the safety of WECs,extreme typhoon-induced wave conditions must be considered.Furthermore,the results showed that the maximum significant wave height and mean period over the 50-year return period reached 18 m and 15 s,respectively.

The Assessment of Ocean Wave Energy Along the Coasts of Taiwan

The wave energy resource around the coasts of Taiwan is investigated with wave buoy data covering a 3-year period （2007-2009）. Eleven study sites within the region bounded by the 21.5^°N-25.5°N latitudes and 118°E-122°E longitudes are selected for analysis. The monthly moving-average filter is used to obtain the low-frequency trend based on the available hourly data. After quantifying the wave power and annual wave energy, the substantial resource is the result of Penghu buoy station, which is at the northeastern side of Penghu Island in the Taiwan Strait. it is investigated that the Penghu sea area is determined to be the optimal place for wave energy production according to its abundant resource of northeasterly monsoon waves, sheltering of the Taiwan Island, operation and maintenance in terms of seasonal conditions, and constructability of wave power devices.

Wind-wave hindcast in the Yellow Sea and the Bohai Sea from the year 1988 to 2002

We performed long-term wind-wave hindcast in the Yellow Sea and the Bohai Sea from the year 1988 to 2002, and then analyzed the regional wave climate. Comparisons between model results and satellite data are generally consistent on monthly mean significant wave height. Then we discuss the temporal and spatial characteristics of the climatological monthly mean significant wave heights and mean wave periods. The climatologically spatial patterns are observed as increasing from northwest to southeast and from offshore to deep-water area for both significant wave height and mean wave period, and the patterns are highly related to the wind forcing and local topography. Seasonal variations of wave parameters are also significant. Furthermore, we compute the extreme values of wind and significant wave height using statistical methods. Results reveal the spatial patterns of N-year return significant wave height in the Yellow Sea and the Bohai Sea, and we discuss the relationship between extreme values of significant wave height and wind forcing.

Climatology of Wind-Seas and Swells in the China Seas from Wave Hindcast

The wind-sea and swell climates in the China Seas are investigated by using the 27-yr Integrated Ocean Waves for Geophysical and other Applications(IOWAGA)hindcast data.A comparison is made between the significant wave height from the IOWAGA hindcasts and that from a jointly calibrated altimetry dataset,showing the good performance of the IOWAGA hindcasts in the China Seas.A simple but practical method of diagnosing whether the sea state is wind-sea-dominant or swell-dominant is proposed based on spectral partitioning.Different from the characteristics of wind-seas and swells in the open ocean,the wave fields in the enclosed seas such as the China Seas are predominated by wind-sea events in respect of both frequencies of occurrences and energy weights,due to the island sheltering and limited fetches.The energy weights of wind-seas in a given location is usually more significant than the occurrence probability of wind-sea-dominated events,as the wave energy is higher in the wind-sea events than in the swell events on average and extreme wave heights are mostly related to wind-seas.The most energetic swells in the China Seas(and other enclosed seas)are‘local swells’,having just propagated out of their generation areas.However,the swells coming from the West Pacific also play an important role in the wave climate of the China Seas,which can only be revealed by partitioning different swell systems in the wave spectra as the energy of them is significantly less than the‘local swells’.

Validation and application of multi-source altimeter wave data in China＇s offshore areas

Studies of offshore wave climate based on satellite altimeter significant wave height（SWH） have widespread application value. This study used a calibrated multi-altimeter SWH dataset to investigate the wave climate characteristics in the offshore areas of China. First, the SWH measurements from 28 buoys located in China＇s coastal seas were compared with an Ifremer calibrated altimeter SWH dataset. Although the altimeter dataset tended to slightly overestimate SWH, it was in good agreement with the in situ data in general. The correlation coefficient was 0.97 and the root-mean-square（RMS） of differences was 0.30 m. The validation results showed a slight difference in different areas. The correlation coefficient was the maximum（0.97） and the RMS difference was the minimum（0.28 m） in the area from the East China Sea to the north of the South China Sea.The correlation coefficient of approximately 0.95 was relatively low in the seas off the Changjiang（Yangtze River） Estuary. The RMS difference was the maximum（0.32 m） in the seas off the Changjiang Estuary and was0.30 m in the Bohai Sea and the Yellow Sea. Based on the above evidence, it is confirmed that the multialtimeter wave data are reliable in China＇s offshore areas. Then, the characteristics of the wave field, including the frequency of huge waves and the multi-year return SWH in China＇s offshore seas were analyzed using the23-year altimeter wave dataset. The 23-year mean SWH generally ranged from 0.6-2.2 m. The greatest SWH appeared in the southeast of the China East Sea, the Taiwan Strait and the northeast of the South China Sea.Obvious seasonal variation of SWH was found in most areas; SWH was greater in winter and autumn than in summer and spring. Extreme waves greater than 4 m in height mainly occurred in the following areas： the southeast of the East China Sea, the south of the Ryukyu Islands, the east of Taiwan-Luzon Island, and the Dongsha Islands extending to the Zhongsha Islands, and the frequency of extreme waves was 3%-6%. Extreme waves occurred most frequently in autumn and rarely in spring. The 100-year return wave height was greatest from the northwest Pacific seas extending to southeast of the Ryukyu Islands（9-12 m）, and the northeast of the South China Sea and the East China Sea had the second largest wave heights（7-11 m）. For inshore areas, the100-year return wave height was the greatest in the waters off the east coast of Guangdong Province and the south coast of Zhejiang Province（7-8 m）, whereas it was at a minimum in the area from the Changjiang Estuary to the Bohai Sea（4-6 m）. An investigation of sampling effects indicates that when using the 1°×1°grid dataset, although the combination of nine altimeters obviously enhanced the time and space coverage of sampling, the accuracy of statistical results, particularly extreme values obtained from the dataset, still suffered from undersampling problems because the time sampling percent in each 1°×1°grid cell was always less than33%.