The joint design criteria of significant wave heights and wind speeds are quite important for the structural reliability of fixed offshore platforms.However,the design method that regards different ocean environmental...The joint design criteria of significant wave heights and wind speeds are quite important for the structural reliability of fixed offshore platforms.However,the design method that regards different ocean environmental variables as independent is conservative.In the present study,we introduce a bivariate sample consisting of the maximum wave heights and concomitant wind speeds of the threshold by using the peak-over-threshold and declustering methods.After selecting the appropriate bivariate copulas and univariate distributions and blocking the sample into years,the bivariate compound distribution of annual extreme wave heights and concomitant wind speeds is constructed.Two joint design criteria,namely,the joint probability density method and the conditional probability method,are applied to obtain the joint return values of significant wave heights and wind speeds.Results show that(28.5±0.5)m s^(-1)is the frequently obtained wind speed based on the Atlantic dataset,and these joint design values are more appropriate than those calculated by univariate analysis in the fatigue design.展开更多
As wave height is an important parameter in marine climate measurement,its accurate prediction is crucial in ocean engineering.It also plays an important role in marine disaster early warning and ship design,etc.Howev...As wave height is an important parameter in marine climate measurement,its accurate prediction is crucial in ocean engineering.It also plays an important role in marine disaster early warning and ship design,etc.However,challenges in the large demand for computing resources and the improvement of accuracy are currently encountered.To resolve the above mentioned problems,sequence-to-sequence deep learning model(Seq-to-Seq)is applied to intelligently explore the internal law between the continuous wave height data output by the model,so as to realize fast and accurate predictions on wave height data.Simultaneously,ensemble empirical mode decomposition(EEMD)is adopted to reduce the non-stationarity of wave height data and solve the problem of modal aliasing caused by empirical mode decomposition(EMD),and then improves the prediction accuracy.A significant wave height forecast method integrating EEMD with the Seq-to-Seq model(EEMD-Seq-to-Seq)is proposed in this paper,and the prediction models under different time spans are established.Compared with the long short-term memory model,the novel method demonstrates increased continuity for long-term prediction and reduces prediction errors.The experiments of wave height prediction on four buoys show that the EEMD-Seq-to-Seq algorithm effectively improves the prediction accuracy in short-term(3-h,6-h,12-h and 24-h forecast horizon)and long-term(48-h and 72-h forecast horizon)predictions.展开更多
Based on historical wind fields in the Bohai Sea, a sequence of annual extremal wave heights is produced with numerical wave models for deep-water and shallow water. The design wave heights with different return perio...Based on historical wind fields in the Bohai Sea, a sequence of annual extremal wave heights is produced with numerical wave models for deep-water and shallow water. The design wave heights with different return periods for the nearest deep-water point and for the shallow water point are estimated on the basis of P-III type, Weibull distribution, and Gumbel distribution; and the corresponding values for the shallow water point are also estimated based on the HISWA model with the input of design wave heights for the nearest deep-water point. Comparisons between design wave heights for the shallow water point estimated on the basis of both distribution functions are HISWA model show that the results from different distribution functions scatter considerably, and influenced strongly by return periods; however, the results from the HISWA model are convergent, that is, the influence of the design wave heights estimated with different distribution functions for deep water is weakened, and the estimated values decrease for long return periods and increase for short return periods. Therefore, the numerical wave model gives a more stable result in shallow water design wave estimation because of the consideration of the effect of physical processes which occur in shallow water.展开更多
This paper reveals that the long-period statistic distribution of the characteristic heights of deep-water waves assumes the lognormal distribution. Thereafter, the largest wave-height which may occur in the service l...This paper reveals that the long-period statistic distribution of the characteristic heights of deep-water waves assumes the lognormal distribution. Thereafter, the largest wave-height which may occur in the service life of coastal structures is derived in this paper.展开更多
The HY-2 satellite was successfully launched on 16 August 2011. The HY-2 significant wave height (SWH) is validated by the data from the South China Sea (SCS) field experiment, National Data Buoy Center (NDBC/ bu...The HY-2 satellite was successfully launched on 16 August 2011. The HY-2 significant wave height (SWH) is validated by the data from the South China Sea (SCS) field experiment, National Data Buoy Center (NDBC/ buoys and Jason-1/2 altimeters, and is corrected using a linear regression with in-situ measurements. Com- pared with NDBC SWH, the HY-2 SWH show a RMS of 0.36 m, which is similar to Jason- 1 and Jason-2 SWH with the RMS of 0.35 m and 0.37 m respectively; the RMS of corrected HY-2 SWH is 0.27 m, similar to 0.27 m and 0.23 m of corrected Jason-1 and Jason-2 SWH. Therefore the accuracy of HY-2 SWH products is close to that of Jason-1/2 SWH, and the linear regression function derived can improve the accuracy of HY-2 SWH products.展开更多
HY-2 has been launched by China on August 16, 2011 which assembles multi-microwave remote sensing payloads in a body and has the ability of monitoring ocean dynamic environments. The HY-2 satellite data need to be cal...HY-2 has been launched by China on August 16, 2011 which assembles multi-microwave remote sensing payloads in a body and has the ability of monitoring ocean dynamic environments. The HY-2 satellite data need to be calibrated and validated before being put into use. Based on the in-situ buoys from the Nation- al Data Buoy Center (NDBC), Ku-band significant wave heights (SWH, hs) of HY-2 altimeter are validated. Eleven months of HY-2 altimeter Level 2 products data are chose from October 1, 2011 to August 29, 2012. Using NDBC 60 buoys yield 902 collocations for HY-2 by adopting collocation criteria of 30 min for tempo- ral window and 50 km for a spatial window. An overall RMS difference of the SWH between HY-2 and buoy data is 0.297 m. A correlation coefficient between these is 0.964. An ordinary least squares (OLS) regression is performed with the buoy data as an independent variable and the altimeter data as a dependent vari- able. The regression equation of hs is hs (HY-2)=0.891 × hs (NDBC)+0.022. In addition, 2016 collocations are matched with temporal window of 30 rain at the crossing points of HY-2 and Jason-2 orbits. RMS difference of Ku-band SWH between the two data sets is 0.452 m.展开更多
Chinese Haiyang-2(HY-2) satellite is the first Chinese marine dynamic environment satellite. The dual-frequency (Ku and C band) radar altimeter onboard HY-2 has been working effective to provide operational signif...Chinese Haiyang-2(HY-2) satellite is the first Chinese marine dynamic environment satellite. The dual-frequency (Ku and C band) radar altimeter onboard HY-2 has been working effective to provide operational significant wave height (SWH) for more than three years (October 1, 2011 to present).We validated along-track Ku-band SWH data of HY-2 satellite against National Data Buoy Center (NDBC) in-situ measurements over a time period of three years from October 1, 2011 to September 30, 2014, the root mean square error (RMSE) and mean bias of HY-2 SWH is 0.38 m and (-0.13±0.35) m, respectively. We also did cross validation against Jason-2 altimeter SWH data, the RMSE and the mean bias is 0.36m and (-0.22±0.28) m, respectively. In order to compare the statistical results between HY-2 and Jason-2 satellite SWH data, we validated the Jason-2 satellite radar altimeter along-track Ku-band SWH data against NDBC measurements using the same method. The results demonstrate the validation method in this study is scientific and the RMSE and mean bias of Jason-2 SWH data is 0.26 m and (0.00±0.26) m, respectively. We also validated both HY-2 and Jason-2 SWH data every month, the mean bias of Jason-2 SWH data almost equaled to zero all the time, while the mean bias of HY-2 SWH data was no less than -0.31m before April 2013 and dropped to zero after that time. These results indicate that the statistical results for HY-2 altimeter SWH are reliable and HY-2 altimeter along-track SWH data were steady and of high quality in the last three years. The results also indicate that HY-2 SWH data have greatly been improved and have the same accuracy with Jason-2 SWH data after April, 2013. SWH data provided by HY-2 satellite radar altimeter are useful and acceptable for ocean operational applications.展开更多
As an important equipment for sea state remote sensing, high frequency surface wave radar (HFSWR) has received more and more attention. The conventional method for wave height inversion is based on the ratio of the ...As an important equipment for sea state remote sensing, high frequency surface wave radar (HFSWR) has received more and more attention. The conventional method for wave height inversion is based on the ratio of the integration of the second-order spectral continuum to that of the first-order region, where the strong external noise and the incorrect delineation of the first- and second-order Doppler spectral regions due to spectral aliasing are two major sources of errors in the wave height. To account for these factors, two more indices are introduced to the wave height estimation, i.e., the ratio of the maximum power of the second-or- der continuum to that of the Bragg spectral region (RSCB) and the ratio of the power of the second harmonic peak to that of the Bragg peak (RSHB). Both indices also have a strong correlation with the underlying wave height. On the basis of all these indices an empirical model is proposed to estimate the wave height. This method has been used in a three-months long experiment of the ocean state measuring and analyzing ra- dar, type S (OSMAR-S), which is a portable HFSWR with compact cross-loop/monopole receive antennas developed by Wuhan University since 2006. During the experiment in the Taiwan Strait, the significant wave height varied from 0 to 5 m. The significant wave heights estimated by the OSMAR-S correlate well with the data provided by the Oceanweather Inc. for comparison, with a correlation coefficient of 0.74 and a root mean square error (RMSE) of 0.77 m. The proposed method has made an effective improvement to the wave height estimation and thus a further step toward operational use of the OSMAR-S in the wave height extraction.展开更多
The joint distribution of wave heights and periods of individual waves is usually approximated by the joint distribution of apparent wave heights and periods. However there is difference between them. This difference ...The joint distribution of wave heights and periods of individual waves is usually approximated by the joint distribution of apparent wave heights and periods. However there is difference between them. This difference is addressed and the theoretical joint distributions of apparent wave heights and periods due to Longuet-Higgins and Sun are modified to give more reasonable representations of the joint distribution of wave heights and periods of individual waves. The modification has overcome an inherent drawback of these joint PDFs that the mean wave period is infinite. A comparison is made between the modified formulae and the field data of Goda, which shows that the new formulae consist with the measurement better than their original counterparts.展开更多
A joint probability density is derived for wavelengths and wave heights. It is asymmetric and depends only on the spectral bandwidth epsilon defined by Cartwright and Longuet-Higgins (1956). After that a theoretical p...A joint probability density is derived for wavelengths and wave heights. It is asymmetric and depends only on the spectral bandwidth epsilon defined by Cartwright and Longuet-Higgins (1956). After that a theoretical probability density for wave steepness is obtained. It tends to Rayleigh distribution as epsilon --> 0. A comparison between theoretical steepness distribution and laboratory experiment result shows good agreement.展开更多
A new method for estimating significant wave height(SWH) from advanced synthetic aperture radar(ASAR) wave mode data based on a support vector machine(SVM) regression model is presented. The model is established...A new method for estimating significant wave height(SWH) from advanced synthetic aperture radar(ASAR) wave mode data based on a support vector machine(SVM) regression model is presented. The model is established based on a nonlinear relationship between σ0, the variance of the normalized SAR image, SAR image spectrum spectral decomposition parameters and ocean wave SWH. The feature parameters of the SAR images are the input parameters of the SVM regression model, and the SWH provided by the European Centre for Medium-range Weather Forecasts(ECMWF) is the output parameter. On the basis of ASAR matching data set, a particle swarm optimization(PSO) algorithm is used to optimize the input kernel parameters of the SVM regression model and to establish the SVM model. The SWH estimation results yielded by this model are compared with the ECMWF reanalysis data and the buoy data. The RMSE values of the SWH are 0.34 and 0.48 m, and the correlation coefficient is 0.94 and 0.81, respectively. The results show that the SVM regression model is an effective method for estimating the SWH from the SAR data. The advantage of this model is that SAR data may serve as an independent data source for retrieving the SWH, which can avoid the complicated solution process associated with wave spectra.展开更多
Based on the maximum entropy principle, a probability density function (PDF) is derived for the distribution of wave heights in a random wave field, without any more hypothesis. The present PDF, being a non-Rayleigh f...Based on the maximum entropy principle, a probability density function (PDF) is derived for the distribution of wave heights in a random wave field, without any more hypothesis. The present PDF, being a non-Rayleigh form, involves two parameters: the average wave height H— and the state parameter γ. The role of γ in the distribution of wave heights is examined. It is found that γ may be a certain measure of sea state. A least square method for determining γ from measured data is proposed. In virtue of the method, the values of γ are determined for three sea states from the data measured in the East China Sea. The present PDF is compared with the well known Rayleigh PDF of wave height and it is shown that it much better fits the data than the Rayleigh PDF. It is expected that the present PDF would fit some other wave variables, since its derivation is not restricted only to the wave height.展开更多
Long-term variations in a sea surface wind speed (WS) and a significant wave height (SWH) are associated with the global climate change, the prevention and mitigation of natural disasters, and an ocean resource ex...Long-term variations in a sea surface wind speed (WS) and a significant wave height (SWH) are associated with the global climate change, the prevention and mitigation of natural disasters, and an ocean resource exploitation, and other activities. The seasonal characteristics of the long-term trends in China's seas WS and SWH are determined based on 24 a (1988-2011) cross-calibrated, multi-platform (CCMP) wind data and 24 a hindcast wave data obtained with the WAVEWATCH-III (WW3) wave model forced by CCMP wind data. The results show the following. (1) For the past 24 a, the China's WS and SWH exhibit a significant increasing trend as a whole, of 3.38 cm/(s.a) in the WS, 1.3 cm/a in the SWH. (2) As a whole, the increasing trend of the China's seas WS and SWH is strongest in March-April-May (MAM) and December-January-February (DJF), followed by June-July-August (JJA), and smallest in September-October-November (SON). (3) The areal extent of significant increases in the WS was largest in MAM, while the area decreased in JJA and DJF; the smallest area was apparent in SON. In contrast to the WS, almost all of China's seas exhibited a significant increase in SWH in MAM and DJF; the range was slightly smaller in JJA and SON. The WS and SWH in the Bohai Sea, the Yellow Sea, East China Sea, the Tsushima Strait, the Taiwan Strait, the northern South China Sea, the Beibu Gull and the Gulf of Thailand exhibited a significant increase in all seasons. (4) The variations in China's seas SWH and WS depended on the season. The areas with a strong increase usually appeared in DJF.展开更多
A method is presented to extrapolate a time series of wave data to extreme wave heights. The 15-year time series of deepwater wave data collected for 34 min every hour from 1988 to 2002 in the South Pacific Ocean, Aus...A method is presented to extrapolate a time series of wave data to extreme wave heights. The 15-year time series of deepwater wave data collected for 34 min every hour from 1988 to 2002 in the South Pacific Ocean, Australia, is analyzed to generate a set of storm peak wave heights by use of the Peaks-Over-Threshold method. The probability distribution is calculated by grouping the observod storm peak wave heights into a number of wave height classes and assigning a probability to each wave height class. The observed probability distribution is then fitted to eight different probability distribution functions and found to be fitted best by the Weibull distribution (a = 1.17), nearly best by the FT-Ⅰ, quite well by the exponential, and poorly by the lognormal function based on the criterion of the sum of squares of the errors, SSE (H). The effect of the threshold wave height on the estimated extreme wave height is also studied and is found insignificant in this study. The 95 % prediction intervals of the best-fit FT-Ⅰ , exponential and Weibull functions are also derived.展开更多
The seasonal variability of the significant wave height(SWH) in the South China Sea(SCS) is investigated using the most up-to-date gridded daily altimeter data for the period of September 2009 to August 2015. The ...The seasonal variability of the significant wave height(SWH) in the South China Sea(SCS) is investigated using the most up-to-date gridded daily altimeter data for the period of September 2009 to August 2015. The results indicate that the SWH shows a uniform seasonal variation in the whole SCS, with its maxima occurring in December/January and minima in May. Throughout the year, the SWH in the SCS is the largest around Luzon Strait(LS) and then gradually decreases southward across the basin. The surface wind speed has a similar seasonal variation, but with different spatial distributions in most months of the year. Further analysis indicates that the observed SWH variations are dominated by swell. The wind sea height, however, is much smaller. It is the the largest in two regions southwest of Taiwan Island and southeast of Vietnam Coast during the northeasterly monsoon, while the largest in the central/southern SCS during the southwesterly monsoon. The extreme wave condition also experiences a significant seasonal variation. In most regions of the northern and central SCS, the maxima of the 99 th percentile SWH that are larger than the SWH theoretically calculated with the wind speed for the fully developed seas mainly appear in August–November, closely related to strong tropical cyclone activities.Compared with previous studies, it is also implied that the wave climate in the Pacific Ocean plays an important role in the wave climate variations in the SCS.展开更多
A new compound distribution model for extreme wave heights of typhoon-affected sea areas is proposed on the basis of the maximum-entropy principle. The new model is formed by nesting a discrete distribution in a conti...A new compound distribution model for extreme wave heights of typhoon-affected sea areas is proposed on the basis of the maximum-entropy principle. The new model is formed by nesting a discrete distribution in a continuous one, having eight parameters which can be determined in terms of observed data of typhoon occurrence-frequency and extreme wave heights by numerically solving two sets of equations derived in this paper. The model is examined by using it to predict the N-year return-period wave height at two hydrology stations in the Yellow Sea, and the predicted results are compared with those predicted by use of some other compound distribution models. Examinations and comparisons show that the model has some advantages for predicting the N-year return-period wave height in typhoon-affected sea areas.展开更多
This paper concerns the calculation of wave height exceedance probabilities for nonlinear irregular waves in transitional water depths, and a Transformed Rayleigh method is first proposed for carrying out the calculat...This paper concerns the calculation of wave height exceedance probabilities for nonlinear irregular waves in transitional water depths, and a Transformed Rayleigh method is first proposed for carrying out the calculation. In the proposed Transformed Rayleigh method, the transformation model is chosen to be a monotonic exponential function, calibrated such that the first three moments of the transformed model match the moments of the true process. The proposed new method has been applied for calculating the wave height exceedance probabilities of a sea state with the surface elevation data measured at the Poseidon platform. It is demonstrated in this case that the proposed new method can offer better predictions than those by using the conventional Rayleigh wave height distribution model. The proposed new method has been further applied for calculating the total horizontal loads on a generic jacket, and its accuracy has once again been substantiated. The research findings gained from this study demonstrate that the proposed Transformed Rayleigh model can be utilized as a promising alternative to the well-established nonlinear wave height distribution models.展开更多
In using the PGCEVD (Poisson-Gumbel Compound Extreme Value Distribution) model to calculate return values of typhoon wave height, the quantitative selection of the threshold has blocked its application. By analyzing...In using the PGCEVD (Poisson-Gumbel Compound Extreme Value Distribution) model to calculate return values of typhoon wave height, the quantitative selection of the threshold has blocked its application. By analyzing the principle of the threshold selection of PGCEVD model and in combination of the change point statistical methods, this paper proposes a new method for quantitative calculation of the threshold in PGCEVD model. Eleven samples from five engineering points in several coastal waters of Guangdong and Hainan, China, are calculated and analyzed by using PGCEVD model and the traditional Pearson type III distribution (P-III) model, respectively. By comparing the results of the two models, it is shown that the new method of selecting the optimal threshold is feasible. PGCEVD model has more stable results than that of P-III model and can be used for the return wave height in every direction.展开更多
The analysis and design of offshore structures necessitates the consideration of wave loads. Realistic modeling of wave loads is particularly important to ensure reliable performance of these structures. Among the ava...The analysis and design of offshore structures necessitates the consideration of wave loads. Realistic modeling of wave loads is particularly important to ensure reliable performance of these structures. Among the available methods for the modeling of the extreme significant wave height on a statistical basis, the peak over threshold method has attracted most attention. This method employs Poisson process to character- ize time-varying properties in the parameters of an extreme value distribution. In this paper, the peak over threshold method is reviewed and extended to account for subjectivity in the modeling. The freedom in selecting the threshold and the time span to separate extremes from the original time series data is incorpo- rated as imprecision in the model. This leads to an extension from random variables to random sets in the probabilistic model for the extreme significant wave height. The extended model is also applied to different periods of the sampled data to evaluate the significance of the climatic conditions on the uncertainties of the parameters.展开更多
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-polarizatio...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 CSARWAVE. 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 CSARWAVE2. An additional 92 GF-3 SAR images were implemented in order to validate CSARWAVE2 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.展开更多
基金the National Natural Science Foundation of China(No.52171284)。
文摘The joint design criteria of significant wave heights and wind speeds are quite important for the structural reliability of fixed offshore platforms.However,the design method that regards different ocean environmental variables as independent is conservative.In the present study,we introduce a bivariate sample consisting of the maximum wave heights and concomitant wind speeds of the threshold by using the peak-over-threshold and declustering methods.After selecting the appropriate bivariate copulas and univariate distributions and blocking the sample into years,the bivariate compound distribution of annual extreme wave heights and concomitant wind speeds is constructed.Two joint design criteria,namely,the joint probability density method and the conditional probability method,are applied to obtain the joint return values of significant wave heights and wind speeds.Results show that(28.5±0.5)m s^(-1)is the frequently obtained wind speed based on the Atlantic dataset,and these joint design values are more appropriate than those calculated by univariate analysis in the fatigue design.
基金The Project Supported by Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)under contract No.SML2020SP007the National Natural Science Foundation of China under contract Nos 42192562 and 62072249.
文摘As wave height is an important parameter in marine climate measurement,its accurate prediction is crucial in ocean engineering.It also plays an important role in marine disaster early warning and ship design,etc.However,challenges in the large demand for computing resources and the improvement of accuracy are currently encountered.To resolve the above mentioned problems,sequence-to-sequence deep learning model(Seq-to-Seq)is applied to intelligently explore the internal law between the continuous wave height data output by the model,so as to realize fast and accurate predictions on wave height data.Simultaneously,ensemble empirical mode decomposition(EEMD)is adopted to reduce the non-stationarity of wave height data and solve the problem of modal aliasing caused by empirical mode decomposition(EMD),and then improves the prediction accuracy.A significant wave height forecast method integrating EEMD with the Seq-to-Seq model(EEMD-Seq-to-Seq)is proposed in this paper,and the prediction models under different time spans are established.Compared with the long short-term memory model,the novel method demonstrates increased continuity for long-term prediction and reduces prediction errors.The experiments of wave height prediction on four buoys show that the EEMD-Seq-to-Seq algorithm effectively improves the prediction accuracy in short-term(3-h,6-h,12-h and 24-h forecast horizon)and long-term(48-h and 72-h forecast horizon)predictions.
基金This work was financially supported by the National Natural Science Foundation of China(Grant No.49776282)
文摘Based on historical wind fields in the Bohai Sea, a sequence of annual extremal wave heights is produced with numerical wave models for deep-water and shallow water. The design wave heights with different return periods for the nearest deep-water point and for the shallow water point are estimated on the basis of P-III type, Weibull distribution, and Gumbel distribution; and the corresponding values for the shallow water point are also estimated based on the HISWA model with the input of design wave heights for the nearest deep-water point. Comparisons between design wave heights for the shallow water point estimated on the basis of both distribution functions are HISWA model show that the results from different distribution functions scatter considerably, and influenced strongly by return periods; however, the results from the HISWA model are convergent, that is, the influence of the design wave heights estimated with different distribution functions for deep water is weakened, and the estimated values decrease for long return periods and increase for short return periods. Therefore, the numerical wave model gives a more stable result in shallow water design wave estimation because of the consideration of the effect of physical processes which occur in shallow water.
文摘This paper reveals that the long-period statistic distribution of the characteristic heights of deep-water waves assumes the lognormal distribution. Thereafter, the largest wave-height which may occur in the service life of coastal structures is derived in this paper.
基金The Marine Public Welfare Project of China under contract No.201105032the National High-Tech Project of China undercontract No.2008AA09A403the fund of State Administration for Science,Technology and Industry for National Defense
文摘The HY-2 satellite was successfully launched on 16 August 2011. The HY-2 significant wave height (SWH) is validated by the data from the South China Sea (SCS) field experiment, National Data Buoy Center (NDBC/ buoys and Jason-1/2 altimeters, and is corrected using a linear regression with in-situ measurements. Com- pared with NDBC SWH, the HY-2 SWH show a RMS of 0.36 m, which is similar to Jason- 1 and Jason-2 SWH with the RMS of 0.35 m and 0.37 m respectively; the RMS of corrected HY-2 SWH is 0.27 m, similar to 0.27 m and 0.23 m of corrected Jason-1 and Jason-2 SWH. Therefore the accuracy of HY-2 SWH products is close to that of Jason-1/2 SWH, and the linear regression function derived can improve the accuracy of HY-2 SWH products.
基金The Special Funds of State Oceanic Administration for Marine Commonweal Research under contract Nos 201105032-1and 201305032the Special Project of State Oceanic Administration of Poles Environmental Investigation and Assessment under contract No.CHINARE2012-02-04the European Space Agency (ESA)-Minister of Science and Technology of the Peoples Republic of China (MOST) Dragon 3 Cooperation Programme under contract No.10466
文摘HY-2 has been launched by China on August 16, 2011 which assembles multi-microwave remote sensing payloads in a body and has the ability of monitoring ocean dynamic environments. The HY-2 satellite data need to be calibrated and validated before being put into use. Based on the in-situ buoys from the Nation- al Data Buoy Center (NDBC), Ku-band significant wave heights (SWH, hs) of HY-2 altimeter are validated. Eleven months of HY-2 altimeter Level 2 products data are chose from October 1, 2011 to August 29, 2012. Using NDBC 60 buoys yield 902 collocations for HY-2 by adopting collocation criteria of 30 min for tempo- ral window and 50 km for a spatial window. An overall RMS difference of the SWH between HY-2 and buoy data is 0.297 m. A correlation coefficient between these is 0.964. An ordinary least squares (OLS) regression is performed with the buoy data as an independent variable and the altimeter data as a dependent vari- able. The regression equation of hs is hs (HY-2)=0.891 × hs (NDBC)+0.022. In addition, 2016 collocations are matched with temporal window of 30 rain at the crossing points of HY-2 and Jason-2 orbits. RMS difference of Ku-band SWH between the two data sets is 0.452 m.
基金The Public Science and Technology Research Funds Projects of Ocean under contract Nos 201105032,201305032 and 201005030the National High Technology Research and Development Program(863 Program)of China under contract No.2013AA09A505+2 种基金Global Change and Air-Sea Interaction Project of China under contract No.GASI-03-03-01-01the International Science&Technology Cooperation Program of China under contract No.2011DFA22260the Open funds of State Key Laboratory of Satellite Ocean Environment Dynamics under contract No.SOED1411
文摘Chinese Haiyang-2(HY-2) satellite is the first Chinese marine dynamic environment satellite. The dual-frequency (Ku and C band) radar altimeter onboard HY-2 has been working effective to provide operational significant wave height (SWH) for more than three years (October 1, 2011 to present).We validated along-track Ku-band SWH data of HY-2 satellite against National Data Buoy Center (NDBC) in-situ measurements over a time period of three years from October 1, 2011 to September 30, 2014, the root mean square error (RMSE) and mean bias of HY-2 SWH is 0.38 m and (-0.13±0.35) m, respectively. We also did cross validation against Jason-2 altimeter SWH data, the RMSE and the mean bias is 0.36m and (-0.22±0.28) m, respectively. In order to compare the statistical results between HY-2 and Jason-2 satellite SWH data, we validated the Jason-2 satellite radar altimeter along-track Ku-band SWH data against NDBC measurements using the same method. The results demonstrate the validation method in this study is scientific and the RMSE and mean bias of Jason-2 SWH data is 0.26 m and (0.00±0.26) m, respectively. We also validated both HY-2 and Jason-2 SWH data every month, the mean bias of Jason-2 SWH data almost equaled to zero all the time, while the mean bias of HY-2 SWH data was no less than -0.31m before April 2013 and dropped to zero after that time. These results indicate that the statistical results for HY-2 altimeter SWH are reliable and HY-2 altimeter along-track SWH data were steady and of high quality in the last three years. The results also indicate that HY-2 SWH data have greatly been improved and have the same accuracy with Jason-2 SWH data after April, 2013. SWH data provided by HY-2 satellite radar altimeter are useful and acceptable for ocean operational applications.
基金The National Natural Science Foundation of China under contract No.61371198the National Special Program for Key Scientific Instrument and Equipment Development of China under contract No.2013YQ160793the Natural Science Foundation of Jiangsu Province of China under contract No.BK2012199
文摘As an important equipment for sea state remote sensing, high frequency surface wave radar (HFSWR) has received more and more attention. The conventional method for wave height inversion is based on the ratio of the integration of the second-order spectral continuum to that of the first-order region, where the strong external noise and the incorrect delineation of the first- and second-order Doppler spectral regions due to spectral aliasing are two major sources of errors in the wave height. To account for these factors, two more indices are introduced to the wave height estimation, i.e., the ratio of the maximum power of the second-or- der continuum to that of the Bragg spectral region (RSCB) and the ratio of the power of the second harmonic peak to that of the Bragg peak (RSHB). Both indices also have a strong correlation with the underlying wave height. On the basis of all these indices an empirical model is proposed to estimate the wave height. This method has been used in a three-months long experiment of the ocean state measuring and analyzing ra- dar, type S (OSMAR-S), which is a portable HFSWR with compact cross-loop/monopole receive antennas developed by Wuhan University since 2006. During the experiment in the Taiwan Strait, the significant wave height varied from 0 to 5 m. The significant wave heights estimated by the OSMAR-S correlate well with the data provided by the Oceanweather Inc. for comparison, with a correlation coefficient of 0.74 and a root mean square error (RMSE) of 0.77 m. The proposed method has made an effective improvement to the wave height estimation and thus a further step toward operational use of the OSMAR-S in the wave height extraction.
文摘The joint distribution of wave heights and periods of individual waves is usually approximated by the joint distribution of apparent wave heights and periods. However there is difference between them. This difference is addressed and the theoretical joint distributions of apparent wave heights and periods due to Longuet-Higgins and Sun are modified to give more reasonable representations of the joint distribution of wave heights and periods of individual waves. The modification has overcome an inherent drawback of these joint PDFs that the mean wave period is infinite. A comparison is made between the modified formulae and the field data of Goda, which shows that the new formulae consist with the measurement better than their original counterparts.
基金National Natural Foundation of China.(No.49676277)
文摘A joint probability density is derived for wavelengths and wave heights. It is asymmetric and depends only on the spectral bandwidth epsilon defined by Cartwright and Longuet-Higgins (1956). After that a theoretical probability density for wave steepness is obtained. It tends to Rayleigh distribution as epsilon --> 0. A comparison between theoretical steepness distribution and laboratory experiment result shows good agreement.
基金The National Key Research and Development Program of China under contract Nos 2016YFA0600102 and2016YFC1401007the National Natural Science Youth Foundation of China under contract No.61501130the Natural Science Foundation of China under contract No.41406207
文摘A new method for estimating significant wave height(SWH) from advanced synthetic aperture radar(ASAR) wave mode data based on a support vector machine(SVM) regression model is presented. The model is established based on a nonlinear relationship between σ0, the variance of the normalized SAR image, SAR image spectrum spectral decomposition parameters and ocean wave SWH. The feature parameters of the SAR images are the input parameters of the SVM regression model, and the SWH provided by the European Centre for Medium-range Weather Forecasts(ECMWF) is the output parameter. On the basis of ASAR matching data set, a particle swarm optimization(PSO) algorithm is used to optimize the input kernel parameters of the SVM regression model and to establish the SVM model. The SWH estimation results yielded by this model are compared with the ECMWF reanalysis data and the buoy data. The RMSE values of the SWH are 0.34 and 0.48 m, and the correlation coefficient is 0.94 and 0.81, respectively. The results show that the SVM regression model is an effective method for estimating the SWH from the SAR data. The advantage of this model is that SAR data may serve as an independent data source for retrieving the SWH, which can avoid the complicated solution process associated with wave spectra.
文摘Based on the maximum entropy principle, a probability density function (PDF) is derived for the distribution of wave heights in a random wave field, without any more hypothesis. The present PDF, being a non-Rayleigh form, involves two parameters: the average wave height H— and the state parameter γ. The role of γ in the distribution of wave heights is examined. It is found that γ may be a certain measure of sea state. A least square method for determining γ from measured data is proposed. In virtue of the method, the values of γ are determined for three sea states from the data measured in the East China Sea. The present PDF is compared with the well known Rayleigh PDF of wave height and it is shown that it much better fits the data than the Rayleigh PDF. It is expected that the present PDF would fit some other wave variables, since its derivation is not restricted only to the wave height.
基金The National Basic Research Program of China under contract Nos 2015CB453200,2013CB956200,2012CB957803 and2010CB950400the National Natural Science Foundation of China under contract Nos 41275086 and 41475070
文摘Long-term variations in a sea surface wind speed (WS) and a significant wave height (SWH) are associated with the global climate change, the prevention and mitigation of natural disasters, and an ocean resource exploitation, and other activities. The seasonal characteristics of the long-term trends in China's seas WS and SWH are determined based on 24 a (1988-2011) cross-calibrated, multi-platform (CCMP) wind data and 24 a hindcast wave data obtained with the WAVEWATCH-III (WW3) wave model forced by CCMP wind data. The results show the following. (1) For the past 24 a, the China's WS and SWH exhibit a significant increasing trend as a whole, of 3.38 cm/(s.a) in the WS, 1.3 cm/a in the SWH. (2) As a whole, the increasing trend of the China's seas WS and SWH is strongest in March-April-May (MAM) and December-January-February (DJF), followed by June-July-August (JJA), and smallest in September-October-November (SON). (3) The areal extent of significant increases in the WS was largest in MAM, while the area decreased in JJA and DJF; the smallest area was apparent in SON. In contrast to the WS, almost all of China's seas exhibited a significant increase in SWH in MAM and DJF; the range was slightly smaller in JJA and SON. The WS and SWH in the Bohai Sea, the Yellow Sea, East China Sea, the Tsushima Strait, the Taiwan Strait, the northern South China Sea, the Beibu Gull and the Gulf of Thailand exhibited a significant increase in all seasons. (4) The variations in China's seas SWH and WS depended on the season. The areas with a strong increase usually appeared in DJF.
文摘A method is presented to extrapolate a time series of wave data to extreme wave heights. The 15-year time series of deepwater wave data collected for 34 min every hour from 1988 to 2002 in the South Pacific Ocean, Australia, is analyzed to generate a set of storm peak wave heights by use of the Peaks-Over-Threshold method. The probability distribution is calculated by grouping the observod storm peak wave heights into a number of wave height classes and assigning a probability to each wave height class. The observed probability distribution is then fitted to eight different probability distribution functions and found to be fitted best by the Weibull distribution (a = 1.17), nearly best by the FT-Ⅰ, quite well by the exponential, and poorly by the lognormal function based on the criterion of the sum of squares of the errors, SSE (H). The effect of the threshold wave height on the estimated extreme wave height is also studied and is found insignificant in this study. The 95 % prediction intervals of the best-fit FT-Ⅰ , exponential and Weibull functions are also derived.
基金The Shandong Provincial Natural Science Foundation under contract Nos ZR2015DQ006 and ZR2014DQ005the National Natural Science Foundation of China under contract Nos 41506008 and 41476002the China Postdoctoral Science Foundation under contract No.2015M570609
文摘The seasonal variability of the significant wave height(SWH) in the South China Sea(SCS) is investigated using the most up-to-date gridded daily altimeter data for the period of September 2009 to August 2015. The results indicate that the SWH shows a uniform seasonal variation in the whole SCS, with its maxima occurring in December/January and minima in May. Throughout the year, the SWH in the SCS is the largest around Luzon Strait(LS) and then gradually decreases southward across the basin. The surface wind speed has a similar seasonal variation, but with different spatial distributions in most months of the year. Further analysis indicates that the observed SWH variations are dominated by swell. The wind sea height, however, is much smaller. It is the the largest in two regions southwest of Taiwan Island and southeast of Vietnam Coast during the northeasterly monsoon, while the largest in the central/southern SCS during the southwesterly monsoon. The extreme wave condition also experiences a significant seasonal variation. In most regions of the northern and central SCS, the maxima of the 99 th percentile SWH that are larger than the SWH theoretically calculated with the wind speed for the fully developed seas mainly appear in August–November, closely related to strong tropical cyclone activities.Compared with previous studies, it is also implied that the wave climate in the Pacific Ocean plays an important role in the wave climate variations in the SCS.
基金supported by the Open Fund of the Key Laboratory of Research on Marine Hazards Forecasting (Grant No.LOMF1101)the Shanghai Typhoon Research Fund (Grant No. 2009ST05)the National Natural Science Foundation of China(Grant No. 40776006)
文摘A new compound distribution model for extreme wave heights of typhoon-affected sea areas is proposed on the basis of the maximum-entropy principle. The new model is formed by nesting a discrete distribution in a continuous one, having eight parameters which can be determined in terms of observed data of typhoon occurrence-frequency and extreme wave heights by numerically solving two sets of equations derived in this paper. The model is examined by using it to predict the N-year return-period wave height at two hydrology stations in the Yellow Sea, and the predicted results are compared with those predicted by use of some other compound distribution models. Examinations and comparisons show that the model has some advantages for predicting the N-year return-period wave height in typhoon-affected sea areas.
基金financially supported by the Chinese State Key Laboratory of Ocean Engineering,Shanghai Jiao Tong University(Grant No.GKZD010038)
文摘This paper concerns the calculation of wave height exceedance probabilities for nonlinear irregular waves in transitional water depths, and a Transformed Rayleigh method is first proposed for carrying out the calculation. In the proposed Transformed Rayleigh method, the transformation model is chosen to be a monotonic exponential function, calibrated such that the first three moments of the transformed model match the moments of the true process. The proposed new method has been applied for calculating the wave height exceedance probabilities of a sea state with the surface elevation data measured at the Poseidon platform. It is demonstrated in this case that the proposed new method can offer better predictions than those by using the conventional Rayleigh wave height distribution model. The proposed new method has been further applied for calculating the total horizontal loads on a generic jacket, and its accuracy has once again been substantiated. The research findings gained from this study demonstrate that the proposed Transformed Rayleigh model can be utilized as a promising alternative to the well-established nonlinear wave height distribution models.
基金supported by the National Natural Science Foundation of China(Grant No.10902039)the Major Project Research of the Ministry of Railways of the People's Republic of China(Grant No.2010-201)
文摘In using the PGCEVD (Poisson-Gumbel Compound Extreme Value Distribution) model to calculate return values of typhoon wave height, the quantitative selection of the threshold has blocked its application. By analyzing the principle of the threshold selection of PGCEVD model and in combination of the change point statistical methods, this paper proposes a new method for quantitative calculation of the threshold in PGCEVD model. Eleven samples from five engineering points in several coastal waters of Guangdong and Hainan, China, are calculated and analyzed by using PGCEVD model and the traditional Pearson type III distribution (P-III) model, respectively. By comparing the results of the two models, it is shown that the new method of selecting the optimal threshold is feasible. PGCEVD model has more stable results than that of P-III model and can be used for the return wave height in every direction.
基金The Singapore Ministry of Education AcRF Project under contract NTU ref:RF20/10
文摘The analysis and design of offshore structures necessitates the consideration of wave loads. Realistic modeling of wave loads is particularly important to ensure reliable performance of these structures. Among the available methods for the modeling of the extreme significant wave height on a statistical basis, the peak over threshold method has attracted most attention. This method employs Poisson process to character- ize time-varying properties in the parameters of an extreme value distribution. In this paper, the peak over threshold method is reviewed and extended to account for subjectivity in the modeling. The freedom in selecting the threshold and the time span to separate extremes from the original time series data is incorpo- rated as imprecision in the model. This leads to an extension from random variables to random sets in the probabilistic model for the extreme significant wave height. The extended model is also applied to different periods of the sampled data to evaluate the significance of the climatic conditions on the uncertainties of the parameters.
基金The National Key Research and Development Program of China under contract Nos 2016YFC1401905 and2017YFA0604901the National Natural Science Foundation of China under contract Nos 41776183,41676014,41606024 and 41506033the National Social Science Foundation of China under contract No.15ZDB170
文摘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 CSARWAVE. 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 CSARWAVE2. An additional 92 GF-3 SAR images were implemented in order to validate CSARWAVE2 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.