The validation of HY-2 altimetermeasurements of a significant wave height based on buoy data

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.     

基于漂流浮标的南大洋卫星高度计有效波高研究

随着技术的进步和数据处理方法的完善,经过修正的卫星高度计数据已获得普遍认可.但在南大洋缺少波浪现场数据,卫星高度计在极端恶劣气候条件下获得数据的准确度仍受到一定程度的质疑.中国于2020年第36次南极考察中,在南大洋布放了一套感应耦合漂流浮标,可提供可靠的南大洋现场波浪数据.本文利用该漂流浮标2020年1月27日至9月...     

一种利用浮标站资料改进海浪模式有效波高预报的方法

基于浮标站海浪历史数据,利用回归分析方法建立了海浪数值模式有效波高预报产品的一元二次回归方程订正统计模型。通过2017年7月1日-2018年10月10日期间业务试运行结果发现:订正方程能有效改善有效波高数值预报产品的预报精度,且预报时效越短订正效果越显著。其中,第6~11 h预报时效内的订正前后平均绝对误差值减小0.17~0. 241 m,第6~18 h预报时效内订正前后均方根误差减小幅度为0.103~0. 28 m。这说明应用订正统计模型对海浪模式输出产品进行订正,也是改进海浪模式预报准确率的一种有效途径。     

台湾海峡有效波高的SWAN模式与ERA-Interim数据对比分析

有效波高是描述海浪的关键参数。欧洲中期天气预报中心（ECMWF）提供的ERA-Interim再分析数据提供了全球海浪的有效波高,本文选取该数据在台湾海峡2013年3月份的有效波高结果,分别与浮标观测数据以及海浪数值模式SWAN （Simulating Waves Nearshore）的数值模拟结果相对比,来分析其预报效果。结果显示：在浮标点,ERA-Interim数据和SWAN模拟浪高数据与浮标浪高数据的时间相关系数分别为0.94和0.98,ERA-Interim数据的浪高均值约为浮标的51%,为SWAN模拟数据的70%。在台湾海峡区域,ERA-Interim数据与SWAN模拟浪高之间的空间异常相关系数（ACC）月均值为0.51,时序ACC曲线显示,一般在海峡东北口风初起时刻ACC值最小,在风吹遍海峡并增长的过程中,ACC迅速增加,在风速达到最大值之后,ACC开始下降,但ERA-Interim数据与SWAN数值模拟结果在整个海峡区域的浪高最大值与最小值分布位置基本一致。综合分析,ERA-Interim数据能够反映台湾海峡区域此时间段的有效波高的时空变化趋势,在数值上有明显低估。     

The validation of the significant wave height product of HY-2 altimeter-primary results

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.     

中国HY-2卫星雷达高度计有效波高真实性检验

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-2SWH 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 0.36 m 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 –0.31 m before April2013 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-2SWH data after April, 2013. SWH data provided by HY-2 satellite radar altimeter are useful and acceptable for ocean operational applications.     

A semiempirical algorithm for SAR wave height retrieval and its validation using Envisat ASAR wave mode data

Many synthetic aperture radar(SAR) wave height retrieval algorithms have been developed.However,the wave height retrievals from most existing methods either depend on other input as the first guess or are restricted to the long wave regime.A semiempirical algorithm is presented,which has the objective to estimate the wave height from SAR imagery without any prior knowledge.The proposed novel algorithm was developed based on the theoretical SAR ocean wave imaging mechanism and the empirical relation between two types of wave period.The dependency of the proposed model on radar incident and wave direction was analyzed.For Envisat advanced synthetic aperture radar(ASAR) wave mode data,the model can be reduced to the simple form with two input parameters,i.e.,the cutoff wavelength and peak wavelength of ocean wave,which can be retrieved from SAR imagery without any prior knowledge of wind or wave.Using Envisat ASAR wave mode data and the collocated buoy measurements from NDBC,the semiempirical algorithm is validated and compared with the Envisat ASAR level 2 products.The root-mean-square-error(RMSE) and scatter index(SI) in respect to the in situ measurements are 0.52 m and 19% respectively.Validation results indicate that,for Envisat ASAR wave mode data,the proposed method works well.     

基于浮标资料的中国东部海域最大波高特征分析

利用原国家海洋局2010—2015年的浮标资料,计算渤、黄、东海有效波高和最大波高的线性关系,并通过1992—2011年共20 a的数值模拟有效波高资料计算中国东部海域各月的2.5 m、4 m、6 m以上最大波高频率和最大波高月极值分布。结果发现:中国东部海域由北至南,最大波高与有效波高的比值逐渐增大;最大波高频率和最大波高月极值空间分布均由渤海、黄海至东海逐渐增大,最大波高频率的极值12月最大,4或5月最小,最大波高月极值9月最大,4月最小。其时空分布表明:受不同天气系统影响,夏秋季台风较多,容易出现极值较大的最大波高;秋冬季冷空气较强,虽然最大波高极值相对较小,但大浪持续时间长、频率大、影响范围广。     

预测有效波高的深度学习模型研究

研究基于RNN、LSTM、GRU深度学习模型,针对NOAA浮标数据集中的44013、44014、44017浮标的数据,通过斯皮尔曼相关性分析提高模型预测效果。实验结果表明,在进行相关性分析后,S-RNN、S-LSTM、 S-GRU的预测效果均比原始RNN、LSTM、GRU模型预测效果好。此外,提出一种基于LSTM的LSTM-Attention 波高预测模型,并进行相关实验,量化LSTM-Attention模型的预测效果,实验结果表明LSTM-Attention模型有更好的预测效果。为评估模型的泛化能力,研究还提出了一种采用邻近浮标数据进行学习,预测浮标缺失数据的方 法。实验结果表明,该方法的预测精度可以达到97.93%。本研究为海浪预测提供了新的方法和思路,也为未来深 度学习模型在海浪预测中的应用提供了参考。     

多源卫星高度计有效波高数据融合方法研究

有效波高数据融合可以弥补单颗卫星高度计数据存在的时间和空间分辨率不足的问题,为有效波高的海洋学应用提供更精确的分析资料.对反距离加权法、克里金插值法和逐步订正法等数据融合方法进行了研究,得到了适合于有效波高数据融合的模型和参数,并利用GFO,Jason-1和Envisat高度计获取的我国海域及其邻近海域有效波高数据,对不同融合方法、滤波器窗口和卫星个数等影响融合结果的因素进行了分析,结果表明:(1)融合后的有效波高分布特征与前人多年统计分析结果基本一致;(2)数据较密集时,不同融合方法的结果差别不大;(3)选择的滤波器窗口大小与时间分辨率有关,对于时间分辨率为10d的融合而言,采用2.5°×2.5°~3°×3°大小的滤波器窗口所得到的融合结果最合适;(4)参加融合的卫星个数至少为3颗.     

Extreme significant wave height climate in the Gulf of Guinea

This article investigates spatio-temporal trends for different return periods of extreme significant wave height (SWH) in the Gulf of Guinea (GG), northeastern tropical Atlantic Ocean, based on a 37-year (1980–2016) wave hindcast. High-resolution reanalysis windfield datasets were used to force the spectral wave model WAVEWATCH III. The wave hindcast information was validated using data gathered from the US National Data Buoy Center. The model performance was adequate. In a spatial analysis, the trends were less than 0.3 m decade^?1 in all parts of the GG, and were increasingly positive westwards, extending to the far western part of the GG; trends below 0.01 m decade^?1 dominated in the eastern part and some areas of the northern part of the gulf. Temporal analysis showed that the trends were negative in all cases. Spatio-temporal trends in the return periods for the 99th-percentile wave height were generally weak. Also, trends in the yearly, seasonal and monthly means of extreme SWH all generally increased from east to west in the GG. Furthermore, temporal trend analysis showed that extreme SWH exhibited an increasing trend of 0.0041 m y^–1 throughout the 37-year period; by season, it exhibited a declining trend of ?0.0005 m y^–1 in winter, and an increasing trend of 0.0048 m y^?1 in summer. The observed increasing positive trend of extreme SWH westward in the GG, however, suggests an increasing storminess towards the western part of the gulf, with potential implications for coastal flooding and erosion, and consequences for coastal structures.     

支持向量回归的机器学习方法在海浪预测中的应用

基于支持向量回归(SVR)方法,建立了渤海海域近岸海浪有效波高短期预测模型,并设计了多组风浪信息组合输入方案,开展了有效波高预测敏感性试验。研究发现:综合考虑当前风浪信息作为模型的输入,对3 h和6 h有效波高预测具有较高的预报技巧,但随着预测时效的延长其预测准确性迅速降低;若此时引入未来预测风速信息作为模型输入,则可极大提高对12 h和24 h有效波高的预测能力;此外,若输入信息与预测对象之间不存在显著相关,多个信息的输入对有效波高预测效果提高无显著作用。建立的机器学习模型对小样本数据集具有良好的适应能力,能够有效解决海浪预报中的非线性问题,可为近岸海浪有效波高短期预测提供合理的技术参考。     

一种基于Envisat ASAR波模式数据的有效波高反演算法

The main objective of this paper is to propose a newly developed ocean Significant Wave Height(SWH) retrieval method from Envisat Advanced Synthetic Aperture Radar(ASAR) imagery. A series of wave mode imagery from January, April and May of 2011 are collocated with ERA-Interim reanalysis SWH data. Based on the matched datasets, a simplified empirical relationship between 22 types of SAR imagery parameters and SWH products is developed with the Genetic Algorithms Partial Least-Squares(GA-PLS) model. Two major features of the backscattering coefficient σ_0 and the frequency parameter S_(10) are chosen as the optimal training feature subset of SWH retrieval by using cross validation. In addition, we also present a comparison of the retrieval results of the simplified empirical relationship with the collocated ERA-Interim data. The results show that the assessment index of the correlation coefficient, the bias, the root-mean-square error of cross validation(RMSECV) and the scattering index(SI) are 0.78, 0.07 m, 0.76 m and 0.5, respectively. In addition, the comparison of the retrieved SWH data between our simplifying model and the Jason-2 radar altimeter data is proposed in our study.Moreover, we also make a comparison of the retrieval of SWH data between our developed model and the wellknown CWAVE_ENV model. The results show that satisfying retrieval results are acquired in the low-moderate sea state, but major bias appears in the high sea state, especially for SWH5 m.     

基于SVM回归模型的SAR图像有效波高估测

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.     

西北太平洋浪流相互作用对有效波高的影响研究

西北太平洋强流区会对海浪的特征和分布产生显著的影响,尤其是研究台风过程中海流与海浪的相互作用具有重要的研究意义。本文以ROMS海洋模式和SWAN海浪模式为基础,构建了浪流耦合模式系统,对2013年10月6-17日间的台风“丹娜丝”、“百合”、“韦帕”过程中西北太平洋浪流相互作用中海流对有效波高的影响进行了研究。通过对比模式模拟有效波高与浮标观测资料,发现耦合后的有效波高比非耦合结果更接近观测值,耦合模式中海流的存在对有效波高的分布有明显的影响。研究表明,特别是在有效波高峰值处,海流引起的有效波高增大最大可达1 m。海浪浪向及流向的空间分布以及中国近海浮标处浪向与流向的时间序列表明,流向与浪向反向时,海流的影响造成有效波高增大;二者同向时,有效波高减小。海流对有效波高的调整会沿着海浪传播的方向传播相当一段距离。在西北太平洋的海浪场计算中,引入海流的耦合模式计算结果对改善强流区海浪预报具有重要意义,并且海流的模拟精度对于高精度的海浪预报非常重要。     

石岛海域海浪数值模拟及特征分析

本文基于SWAN(Simulating Waves Nearshore)模式研究了2001～2016年石岛海浪有效波高的季节和年际变化特征,评估了不同区域风场对其贡献,并探讨了其与ENSO的关系。结果表明,石岛有效波高受黄海季风系统的影响呈现显著的季节变化:12月份最大, 6月份最小, 1%大波有效波高季节变化不显著。石岛有效波高年际变化信号显著,其与风速年际变化之间的关系存在季节性差异:石岛有效波高和石岛、黄海区域平均风速不同月份的年际异常分别在7、10月份相关性较高,而石岛1%大波有效波高和石岛、黄海区域平均1%大风风速不同月份的年际异常则在8月份左右相关性最高。不同区域风场对石岛有效波高场的影响也呈现了季节性差异:夏季,黄海南部区域风场对石岛海浪的贡献较大,而石岛风场的贡献较小;冬季,石岛风场的贡献较大。ENSO(El Ni?o-Southern Oscillation)事件会对石岛有效波高的年际变化产生一定的影响,但影响比较小。本研究旨在对石岛海浪在季节和年际尺度上的变化特征以及风场等影响因素进行研究,对该海域海浪场进行了详细的认识,对了解该海域海浪有重要意义。     

Modified Weibull distribution for maximum and significant wave height simulation and prediction

Calibration coefficients incorporated in the modified Weibull distribution are more effective for maximum wave height simulation. The parametric relations are derived there from to estimate various wave height statistics including extreme wave heights. The characteristic function of the Weibull distribution is derived. The Weibull distribution is suggested for the newly defined significant wave height simulation by the method of characteristic function. The statistical tools suggested and developed here for predicting the required wave height statistics are validated against the wave data (both deep and shallow) of eastern Arabian Sea comprising rough monsoon conditions also, giving reasonable accuracy.     

基于浮标数据的卫星雷达高度计海浪波高数据评价与校正

卫星雷达高度计是海浪有效波高（significant wave height,SWH）观测的重要手段之一,本文利用时空匹配方法对T/P、Jason-1、Envisat、Jason-2、Cryosat-2和HY-2A共6颗卫星雷达高度计SWH数据与NDBC（National Data Buoy Center,NDBC）浮标SWH数据进行对比验证,并对雷达高度计SWH数据进行校正。全部卫星雷达高度计SWH数据时间跨度为1992年9月25日到2015年9月1日,对比验证NDBC浮标共53个,包括7个大洋浮标。精度评价发现除T/P外,各卫星雷达高度计SWH的RMSE都在0.4~0.5 m之间,经过校正后,RMSE都有显著下降,下降程度最大为13.82%;对于大洋浮标,评价结果RMSE在0.20~0.28 m之间,结果明显优于全部NDBC浮标的精度评价结果;HY-2A卫星雷达高度计SWH在经过校正后数据质量与国外其他5颗卫星雷达高度计SWH数据质量差异较小。     

利用一种改进的算法对中国高分三号同极化SAR图像反演的有效波高的验证

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.     

中国海域有效波高、海表风速长期变化趋势的季节特征

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, of3.38 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 Gulf, 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.