共查询到17条相似文献，搜索用时 250 毫秒
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利用有效波高和风速的3种概率密度函数分布:Rayleigh概率密度函数分布、Weibull概率密度函数分布、Log-Normal密度函数分布,结合TOPEX卫星高度计资料,对台湾岛周边海域的有效波高和风速进行分析比较.结果表明:有效波高的观测资料直方图与Log-Normal概率密度函数分布符合较好;而风速的观测资料直方图与Weibull概率密度函数分布符合较好.台湾岛周边海域的大部分海域以年变化为主,有效波高的平均值在冬季达到最大值,每年12月的平均值最大.每年平均有效波高最大值大多数出现在夏季,春季则是一年中有效波高平均值最小的季节,秋季和冬季则是巨浪出现频率较高的季节.同时,对有效波高平均值的时间序列做傅立叶展开表明,对应周期为1 a变化时的波动能量占每条轨道的波高波动能量的主要分量. 相似文献
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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。 相似文献
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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4 m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1 a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6 m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。 相似文献
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JASON-1与TOPEX/POSEIDON卫星高度计数据在中国海和西北太平洋的一致性分析及印证 总被引：1，自引：0，他引：1
利用JASON-1和TOPEX/POSEIDON卫星高度计在相互校正阶段的观测资料,对两者在中国海和西北太平洋测得的海面风速、有效波高、后向散射截面、海平面高度等参数进行一致性分析;利用j,v模型及主要分潮的调和常数,对中国陆架浅海的JASON-1海平面高度数据进行浅海潮汐修正,使用验潮站月平均水位资料对修正结果加以印证。结果显示,2颗高度计观测的海洋环境参数具有强相关性,JASON-1具备了完成延续TOPEX/POSEIDON数据集这一使命的条件。但是,2套系统对于同一海洋环境参数的观测还是存在不能忽略的差异,对这种差异进行了分析,并给出了修正模型。所使用的浅海潮汐修正方法有效地抑制了中国陆架浅海潮波对海平面高度反演的影响,所使用浅海水域的5个验潮站月平均水位资料与JASON-1高度计经过浅海潮汐修正后的海平面高度的相关系数为0.738,标准偏差为0.096m。通过进一步融合JASON-1和TOPEX/POSEIDON在并行飞行期间的海平面高度数据并与验潮站资料比较显示,两者的相关系数提高到0.83,标准偏差为0.067m。 相似文献
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利用美国NOAA/NCEP环境模拟中心海洋模拟小组近年新开发的一个准业务化的海浪数值模式WAVEWATCH Ⅲ(以下简称WWATCH),以每天4次的NOAA/NCEP再分析风场资料为输入,模拟了1996年的南海海域的海面风浪场,通过分析TOPEX/Poseidon(以下简称T/P)高度计的上升和下降轨道在南海海域的交叉点位置处的风、浪观测资料与NCEP风场和WWATCH模式模拟的有效波高大小,可以看出,NCEP风场基本与T/P高度计的风速观测结果一致,相应的模式模拟的有效波高也基本与卫星高度计的有效波高观测结果相一致,但从空间上看,在计算区域中心附近海域的结果一致性较好,靠近计算边界附近海域的结果相对较差,但这种因边界而影响模拟结果的范围很有限;从时间上看,冬季风期间的结果一致性较好,而夏季风期间的结果偏小的趋势明显,并且这种偏小主要出现在夏季风期间的极小风速值附近。 相似文献
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TOPEX卫星高度计有效波高数据分析与极值统计预报 总被引：3，自引：0，他引：3
利用TOPEX卫生高度计测量的有效波高资料，对中国近海9个海域进行了卫星主度计的C，Ku两波段测量值的比较分析与处理,出合理的有效波高数值。利用三参数Weibull分布，以渤海海域、上海附近海域和南海东部海域的作为特定区进行有效波高的极值统计预报，并进行了统计分析。 相似文献
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海面有效波高(H1/3)是表征海浪的重要参数,随着卫星遥感技术的发展,雷达高度计已成为获取海面有效波高的重要手段,但也只能对卫星星下点轨迹处进行有效观测,远无法满足大范围应用的需求.本研究结合2013年10月HY-2雷达高度计观测的海面有效波高和微波散射计观测的海面风场资料,分别对高、低风速下风浪数据进行拟合,建立了适用于0~40 m/s风速范围内的南海海域风浪关系模型,经模型比对和结果验证,结果表明,基于HY-2卫星数据分析建立的南海海域风浪关系模型是可信的,特别是低风速的风浪模型与实测数据建立的风浪模型具有很好的一致性;根据建立的风浪关系模型,从卫星散射计大面观测的海面风场出发,能推算出风浪条件下海面有效波高的大面信息,数据覆盖远高于卫星高度计的星下点观测,能为分析和预报海浪、风暴潮灾害提供大范围的海面有效波高信息. 相似文献
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全球有效波高和风速的时空变化及相关关系研究 总被引：2，自引：1，他引：1
The climatology of significant wave height（SWH） and sea surface wind speed are matters of concern in the fields of both meteorology and oceanography because they are very important parameters for planning offshore structures and ship routings. The TOPEX/Poseidon altimeter, which collected data for about 13 years from September 1992 to October 2005, has measured SWHs and surface wind speeds over most of the world＇s oceans. In this paper, a study of the global spatiotemporal distributions and variations of SWH and sea surface wind speed was conducted using the TOPEX/Poseidon altimeter data set. The range and characteristics of the variations were analyzed quantitatively for the Pacific, Atlantic, and Indian oceans. Areas of rough waves and strong sea surface winds were localized precisely, and the correlation between SWH and sea surface wind speed analyzed. 相似文献
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Paul A. Hwang Steven M. Bratos William J. Teague David W. Wang Gregg A. Jacobs Donald T. Resio 《Journal of Oceanography》1999,55(2):307-325
Wind speed and wave height measured by satellite altimeters represent a good data source to the study of global and regional
wind and wave conditions. In this paper, the TOPEX altimeter wind and wave measurements in the Yellow and East China Seas
are analyzed. The results provide a glimpse on the statistical properties and the spatial distributions of the regional wind
and wave conditions. These data are excellent for use in the validation and verification of numerical simulations on global
and regional scales. The altimeter measurements are compared with model output of temporal statistics and spatial distributions.
The results show that the model simulations are in good agreement with TOPEX measurements in terms of the local mean and standard
deviation of the variables (wave height and wind speed). For the comparison of spatial distributions, the quality of agreement
between numerical simulations and altimeter measurements varies significantly from cycle to cycle of altimeter passes. In
many cases, trends in the spatial distributions of wave heights and wind speeds between simulations and measurements are opposite.
The statistics of biases, rms differences, linear regression coefficients and correlation coefficients are presented. A rather
large percentage (∼50%) of cases show poor agreement based on a combination of low correlation, large rms difference or bias,
and poor regression coefficient. There are indications that wave age is a factor affecting the performance of wave modeling
skills. Generally speaking, the error statistics in the wave field is correlated to the corresponding error statistics in
the wind field under the condition of active wind-wave generation. The error statistics between the wave field and the wind
field become less correlated for large wave ages.
This revised version was published online in August 2006 with corrections to the Cover Date. 相似文献
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1988-2010年中国海域波浪能资源模拟及优势区域划分 总被引：7，自引：2，他引：5
基于国际先进的第三代海浪数值模式WAVEWATCH -Ⅲ,以CCMP风场为驱动场,模拟得到中国海域域1988年1月-2010年12月的海浪场。从提高波浪能资源利用效率的角度出发,定义了波浪能资源开发的有效时间,综合考虑波浪能流密度的大小、资源开发有效时间出现的频率、能流密度的稳定性(变异系数)、SWH和能流密度的变化趋势、资源的总储量和有效储量等方面,对中国海域域的波浪能资源进行评估。研究发现:(1)南海北部四季皆为能流密度的大值区,各个季节基本都在8 kW/m以上,秋冬两季更是高达20 kW/m以上。(2)东海和南海大部分海域的波浪能资源开发有效时间出现频率较高。(3)能流密度的稳定性在1月最好,4月和10月次之,7月最差;南海能流密度的稳定性好于其余海域,其中又以南海北部海域的稳定性最好。(4)中国海域域大部分海域单位面积的波浪能总储量在2×104 kW·h/m以上,高值中心分布于南海北部海域,有效储量的分布特征与总储量基本一致。(5)我国大部分海域的SWH和波浪能流密度呈显著的逐年线性递增趋势,SWH的递增趋势为0.5~2.5 cm/a,能流密度的递增趋势为0.05~0.55 kW/(m·a)。(6)我国大部分海域蕴藏着较为丰富的波浪能资源,其中南海北部、台湾以东洋面及琉球群岛附近海域为波浪能资源的优势区域。 相似文献
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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. 相似文献
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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 总被引：2，自引：0，他引：2
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. 相似文献
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1988—2009年中国海波候、风候统计分析 总被引：3，自引：0，他引：3
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。 相似文献
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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%. 相似文献