New Zealand wave climate from satellite observations

Wave data derived from radar altimeters carried on four satellite missions are combined into a wave climatology for New Zealand waters. These data provide extensive observations of wave conditions around New Zealand, where the paucity of measurements has previously hindered definition of the wave climate. The data span the period 1985 to the present with the exception of a 2‐year gap in 1989–91. The spatial distribution of the long‐term mean of significant wave heights (SWH) indicates a strong latitudinal variation in the south‐west Pacific, with values of over 4 m at latitudes of 50–60°S and under 2.5 m towards the tropics. The shadowing of New Zealand is quite marked; a result of the dominant contribution of south‐westerly wave events. The annual range of the mean SWH also varies over the region; within 0.6 m in the north and 1.3 m in the south. A principal component analysis of the monthly anomalies in mean SWH identifies spatial patterns of variation. Some components vary with the local wind more than others suggesting that some anomalies are associated with wind sea and some with swell. Some patterns also appear to vary with the Southern Oscillation Index and can be related to the wind anomalies associated with El Nino events. Frequency distributions of SWH are also determined, and it is noted that in the north of the region the spatial pattern of the high waves differs considerably from the means.     

基于多源融合卫星高度计观测数据的南海海浪有效波高的季节变化研究

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.     

多源卫星高度计海浪资料在中国近海的验证及应用

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%.     

北太平洋海浪场和风场特征分析

利用欧洲中尺度天气预报中心(ECMWF——European Centre for Medium-Range Weather Forecasts)的1979年1月2014年12月逐6 h的ERA-Interim有效波高和10 m风场资料,分析了近36年期间北太平洋海域海浪场和风场的变化特征。结果表明:1)中低纬度的西北太平洋波高有逐年线性递增趋势,大约在0.2~0.6 cm/a,而低纬度的太平洋东北部海域则以-0.4~-0.2 cm/a的趋势减小。2)风速线性变化趋势显著的区域主要集中在太平洋东北部低纬度海域,约以1.0~2.0 cm/(s·a)的速度在增加。而日本岛四周、菲律宾半岛以南等海域大都以-1.0~-0.5 cm/(s·a)的速度减小。3)北太平洋海域波高和风速都具有明显的季节变化特征,两者具有很强的相关性。西风带内有一个个波高超过10 m的风暴圈,其波高受风浪和涌浪的双重作用。这可为航海、海洋工程设计、军事及海洋能开发与利用等方面提供科学依据。     

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.     

星载高级合成孔径雷达波模式算法及其反演数据精度验证

搭载在欧洲环境卫星(ENVISAT)上的高级合成孔径雷达(Advanced Synthetic Aperture Radar,ASAR)二级波模式数据提供了诸多海浪信息包括有效波高、波向、波长和二维海浪谱等,在海浪预报模式中具有重要作用。本文拟利用浮标观测数据对ASAR波模式算法及其反演数据精度进行对比验证。由于SAR卫星在海面的特殊成像机制,不同海况下会有不同的测量结果,通过与美国国家浮标中心(NDBC)的浮标数据对比,显示ASAR有效波高在高海况下低估和在低海况下高估的现象,在中等海况下的测量结果较优。通过研究ASAR数据集中对应的海浪谱,按照能量与方向分布可分为四种类型:单一方向海浪谱(Ⅰ类谱),180°方向模糊海浪谱(Ⅱ类谱),海浪两个方向且能量分布杂乱(Ⅲ类谱),多个传播方向且谱型杂乱海浪谱(Ⅳ类谱)。探究在不同类型下的海浪参数的精度,结果表明在单一波向正常海浪谱情况下,有效波高、波向与浮标数据一致性较好,存在180°方向模糊的对称海浪谱仅有效波高精度较高,谱型杂乱的海浪谱海浪有效波高和波向反演结果均较差。     

Assessment of SARAL/AltiKa Wave Height Measurements Relative to Buoy,Jason-2, and Cryosat-2 Data

SARAL/AltiKa GDR-T are analyzed to assess the quality of the significant wave height (SWH) measurements. SARAL along-track SWH plots reveal cases of erroneous data, more or less isolated, not detected by the quality flags. The anomalies are often correlated with strong attenuation of the Ka-band backscatter coefficient, sensitive to clouds and rain. A quality test based on the 1 Hz standard deviation is proposed to detect such anomalies. From buoy comparison, it is shown that SARAL SWH is more accurate than Jason-2, particularly at low SWH, and globally does not require any correction. Results are better with open ocean than with coastal buoys. The scatter and the number of outliers are much larger for coastal buoys. SARAL is then compared with Jason-2 and Cryosat-2. The altimeter data are extracted from the global altimeter SWH Ifremer data base, including specific corrections to calibrate the various altimeters. The comparison confirms the high quality of SARAL SWH. The 1 Hz standard deviation is much less than for Jason-2 and Cryosat-2, particularly at low SWH. Furthermore, results show that the corrections applied to Jason-2 and to Cryosat-2, in the data base, are efficient, improving the global agreement between the three altimeters.     

利用TOPEX卫星高度计资料分析台湾岛周边海域巨浪和大风特征

卫星高度计实现了对全球性或区域性的海洋参量的实时监测,TOPEX卫星高度计提供了迄今为止时间序列最长、数据质量最高的全球海面风速和有效波高的同步观测资料。利用TOPEX卫星高度计资料,分析了有效波高4m以上的巨浪在台湾岛周边海域的时空分布特征,结果表明台湾岛周边海域巨浪的分布具有明显的季节特征。每年平均有效波高最大值大多数出现在夏季,春季是1a中有效波高最小的季节,而秋季和冬季是巨浪出现频率最高的季节。波高大于6m的巨浪大都出现在台湾岛东部及东北部海域,在南部海域出现较少。     

Long-term trend analysis of wave characteristics in the Bohai Sea based on interpolated ERA5 wave reanalysis from 1950 to 2020

Reasonably understanding of the long-term wave characteristics is very crucial for the ocean engineering. A feedforward neural network is operated for interpolating ERA5 wave reanalysis in this study, which embodies a detailed record from 1950 onwards. The spatiotemporal variability of wave parameters in the Bohai Sea, especially the significant wave height (SWH), is presented in terms of combined wave, wind wave and swell by employing the 71 years (1950–2020) of interpolated ERA5 reanalysis. Annual mean SWH decreases at ?0.12 cm/a estimated by Theil-Sen estimator and 95th percentile SWH reflecting serve sea states decreases at ?0.20 cm/a. Inter-seasonal analysis shows SWH of wind wave has steeper decreasing trend with higher slopes than that of swell, especially in summer and winter, showing the major decrease may attribute to the weakening of monsoon. The inner Bohai Sea reveals a general decreasing trend while the intersection connecting with the Yellow Sea has the lower significance derived by Mann-Kendall test. Meanwhile, 95th percentile SWH decreases at a higher rate while with a lower significance in comparison with the mean state. The frequencies of mean wave directions in sub-sector are statistically calculated to find the seasonal prevailing directions. Generally, the dominant directions in summer and winter are south and north. A similar variation concerning to SWH, the trend of the mean wave period is provided, which also shows a decrease for decades.     

SARAL/AltiKa Wind and Wave Products: Monitoring,Validation and Assimilation

SARAL/AltiKa surface wind speed (WS) and significant wave height (SWH) measurements are monitored and validated against operational European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric and wave model results in addition to available in-situ observations to access their suitability for various applications, especially SWH data assimilation. The quality of SWH is very high while that of WS is very good except for an underestimation of high wind speeds. The impact of assimilating SWH in the ECMWF Integrated Forecast System was assessed using several numerical experiments. The results show positive impact. Operational assimilation of SWH at ECMWF model is part of the forthcoming model change.     

An assessment of global ocean wave energy resources over the last 45 a

Against the background of the current world facing an energy crisis,and human beings puzzled by the problems of environment and resources,developing clean energy sources becomes the inevitable choice to deal with a climate change and an energy shortage.A global ocean wave energy resource was reanalyzed by using ERA-40 wave reanalysis data 1957–2002 from European Centre for Medium-Range Weather Forecasts(ECMWF).An effective significant wave height is defined in the development of wave energy resources(short as effective SWH),and the total potential of wave energy is exploratively calculated.Synthetically considering a wave energy density,a wave energy level probability,the frequency of the effective SWH,the stability and long-term trend of wave energy density,a swell index and a wave energy storage,global ocean wave energy resources were reanalyzed and regionalized,providing reference to the development of wave energy resources such as wave power plant location,seawater desalination,heating,pumping.     

西北太平洋波候与大气涛动的联系

利用ECMWF 1958-2001年44 a的ERA-40海浪再分析资料计算了西北太平洋海域(0°~45°N,99°~160°E)月平均有效波高(SWH)、平均周期(T)与北太平洋模态指数(NPI)、太平洋年代际振荡(PDO)和多变量ENSO指数(MEI)等大气涛动之间的时间和空间的相关性,重点探讨了NPI对北半球西太平洋波候(SWH和T)的影响。结果表明:NPI、PDO和MEI均与SWH和T有显著的相关性;NPI与SWH和T呈现正相关性,NPI超前SWH和T半年左右正相关最强,最强的相关海域位于日本和菲律宾以东洋面;NPI还存在3~5 a、8~9 a和13~15 a的年际和年代际周期变化; NPI高指数且PDO负位相或MEI负位相均使得SWH和T 增大; MEI冷位相且叠加PDO负位相时也利于SWH和T增大。NPI影响西北太平洋波候的可能机制是:NPI处于低(高)指数时,阿留申低压加深(减弱)且位置偏东(西),北太平洋西风带海面风速急流出现(消失),太平洋副热带东北信风大值区东移(西移),西北太平洋海域信风减弱(加强),西北太平洋海域有效波高和平均周期随之减小(增大)。中、东太平洋西向传播的涌浪对西北太平洋海域波侯有重要影响。     

大西洋波高分布及变化规律研究

使用Topex／Poseidon卫星高度计1992年10月到1998年12月连续75个月，230个重复周期的有效波高资料对南北大西洋的波侯进行了研究，统计分析了大西洋有效波高的累年累年各月和累年各季的空间分布特征和时间变化规律。结果表明大西洋波高呈现中间低、南北高的马鞍形空间分布特征和明显季节变化的规律，与大西洋的气候分布特征和变化规律具有良好的响应关系。     

1988—2009年中国海波候、风候统计分析

利用高精度、高时空分辨率、长时间序列的CCMP(Cross-Calibrated,Multi-Platform)风场,驱动国际先进的第三代海浪模式WAVEWATCH-Ⅲ(WW3),得到中国海1988年1月～2009年12月的海浪场。对中国海的波候(风候)进行精细化的统计分析,分析了海表风场和浪场的季节特征、极值风速与极值波高、风力等级频率和浪级频率、海表风速和波高的逐年变化趋势,结果显示:(1)中国海的海浪场与海表风场具有较好的一致性,尤其是在DJF(December,January,February)期间;海表风速和波高在MAM(March,April,May)期间为全年最低,在DJF期间达到全年最大;MAM和JJA(June,July,August)期间,中国海大部分海域的波周期在3～5.5s,SON(September,October,November)和DJF期间为4.5～6.5s。(2)中国海极值风速、极值波高的大值区分布于渤海中部海域、琉球群岛附近海域和台湾以东广阔洋面、台湾海峡、东沙群岛附近海域、北部湾海域、中沙群岛南部海域。(3)吕宋海峡在MAM、SON、DJF期间均为6级以上大风和4m以上大浪的相对高频海域,JJA期间,6级以上大风的高频海域位于中国南半岛东南部海域,4m以上大浪主要出现在10°N以北。(4)在近22a期间,中国海大部分海域的海表风速、有效波高呈显著性逐年线性递增趋势,风速递增趋势约0.06～0.15m.s-1.a-1,波高递增趋势约0.005～0.03m.a-1。     

黄海海浪天气时间尺度变化的数值模拟研究

利用第三代海浪数值模式(SWAN)系统研究了黄海海浪有效波高的天气时间尺度变化的时空分布特征和相关动力学过程。结果表明黄海海浪有效波高的天气变化强度(S_W)具有显著的时间变化特征和空间分布特征。其多年平均值在黄海的中东部存在由南向北延伸的高值区,同时向两侧近海区域逐渐减小。S_W在冬季最大,夏季最小。从11月到翌年5月,S_W月气候态平均值的空间分布与其年平均值的空间分布类似;从6月到同年10月,S_W的月气候态平均值在黄海与东海的分界处存在较强的由黄海到东海的空间梯度。进一步分析表明黄海海域的S_W以风浪占主,涌浪的贡献远小于风浪贡献。数值实验表明,黄海海浪有效波高的天气时间尺度变化主要是由大于天气变化周期的海面风强迫通过四波非线性相互作用产生的。     

太平洋波高熵的分布变化规律研究

使用1992年IO月到1998年12月连续共75个月、230个重复周期的Topex／Poseidon卫星高度计有效波高资料，对南、北太平洋波高熵的空间分布特征和时间变化规律进行了研究。统计分析了太平洋波高熵的多年的空间分布特征和多年各月的时间变化规律。结果表明，太平洋波高熵呈现出中间低、南北高的马鞍形空间分布特征和明显季节变化的规律，与太平洋的平均有效波高和气候分布特征和变化规律相一致。给出了南北太平洋模拟波高熵的计算公式及计算稳定性检验。     

基于现场观测数据的HY-2A卫星有效波高校正研究

Significant wave height(SWH) can be computed from the returning waveform of radar altimeter, this parameter is only raw estimates if it does not calibrate. But accurate calibration is important for all applications, especially for climate studies. HY-2a altimeter has been operational since April 2012 and its products are available to the scientific community. In this work, SWH data from HY-2A altimeters are calibrated against in situ buoy data from the National Data Buoy Center(NDBC), Distinguished from previous calibration studies which generally regarded buoy data as "truth", the work of calibration for HY-2A altimeter wave data against in situ buoys was applied a more sophisticated statistical technique—the total least squares(TLS) method which can take into account errors in both variables. We present calibration results for HY-2A radar altimeter measurement of wave height against NDBC buoys. In addition, cross-calibration for HY-2A and Jason-2 wave data are talked over and the result is given.     

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.     

Increasing wave heights and extreme value projections: The wave climate of the U.S. Pacific Northwest

Deep-water wave buoy data offshore from the U.S. Pacific Northwest (Oregon and Washington) document that the annual averages of deep-water significant wave heights (SWHs) have increased at a rate of approximately 0.015 m/yr since the mid-1970s, while averages of the five highest SWHs per year have increased at the appreciably greater rate of 0.071 m/yr. Histograms of the hourly-measured SWHs more fully document this shift toward higher values over the decades, demonstrating that both the relatively low waves of the summer and the highest SWHs generated by winter storms have increased. Wave heights associated with higher percentiles in the SWH cumulative distribution function are shown to be increasing at progressively faster rates than those associated with lower percentiles. This property is demonstrated to be a direct result of the probability distributions for annual wave climates having lognormal- or Weibull-like forms in that a moderate increase in the mean SWH produces significantly greater increases in the tail of the distribution. Both the linear regressions of increasing annual averages and the evolving probability distribution of the SWH climate, demonstrating the non-stationarity of the Pacific Northwest wave climate, translate into substantial increases in extreme value projections, important in coastal engineering design and in quantifying coastal hazards. Buoy data have been analyzed to assess this response in the wave climate by employing various time-dependent extreme value models that directly compute the progressive increases in the 25- to 100-year projections. The results depend somewhat on the assumptions made in the statistical procedures, on the numbers of storm-generated SWHs included, and on the threshold value for inclusion in the analyses, but the results are consistent with the linear regressions of annual averages and the observed shifts in the histograms.     

基于WW3模式的一次台风浪过程中掠海飞行器的击水概率分析

以CCMP风场驱动WW3海浪模式,对发生在2010年9月的台风“圆规”所致的台风浪进行数值模拟,并就台风浪对整个中国海击水概率的影响进行计算,为提高掠海飞行器的生存能力提供参考。结果表明:(1)以CCMP风场作为WW3模式的驱动场,可以较好地模拟台风影响下的海浪场,模拟的海浪数据接近海浪浮标观测数据。(2)击水概率场与海浪场的分布特征整体上保持了较好的一致性,高值区主要分布于传统的危险半圆。(3)当飞行器飞行高度为10 m时,大浪区的击水概率在20%以上,高值中心可达35%以上,台风尾迹处的击水概率为15%~20%,其余大部分海域为10%~15%;当飞行高度为15 m时,击水概率较飞行高度为10 m时明显降低,台风大浪区的击水概率为5%~15%,其余大部分海域在5%以内。