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本文提出一种基于支持向量回归的统计预报方法,通过经验正交分解对原始数据矩阵进行时空分解,提取出空间模态和时间系数。由于海面高度变化具有非线性、大惯性的特点,对时间系数进行小波分析,能有效滤除其中的高频信号,得到表征海面高度变化的低频信号。利用支持向量回归方法对小波分解后的低频信号构建预报模型。最后,进行小波重构,还原时间序列长度,实现未来7天的海面高度预报。通过黑潮附近海域的海面高度预报结果验证,该预报方法的预报效果优于整合滑动平均自回归预报方法。本文通过机器学习的算法实现了海面高度的预报,为海洋预报方法提供了新的思路。 相似文献
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根据临时验潮站观测到的一个月潮位资料通常能够分析得到11个分潮的调和常数。如果用所分析得到的调和常数与邻近站的Sa和Ssa的调和常数以及年平均海面做出潮汐预报,则在这一个月当中的平均海面的日变化将会反映出来,因而,潮位预报精度应该比仅由11个分潮和月平均海面所预报的潮位要高。本文对上述的问题进行论述。 相似文献
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本文分析了1996－1998年逐月太平洋海面距平资料及热带太平洋海面赤道槽、脊及上层海水体积变化资料，清楚地看到20世纪最强的一次EL97／98事件，不仅基本特征明显，而且太平洋海面变化与其有密切的响应关系，受此启发，作者依据1975－2000年间赤道槽、脊、逆流槽及热带太平洋上层海水体积变化的历史资料，经年周期滑动平均数据处理和采用基于均生函数的正交化筛选建模方法，建立了各单预测因子周期外延的ENSO预测模式。结果表明，本预测模式除把单预测因子序列的历史变化趋势反映和预测出来，还揭示了历史上的El Nino事件发生了经滑动平均后的赤道脊或热带太平洋上层海水体积的峰值附近，结束于谷底附近，La Nina则出现在滑动平均后的赤道脊谷底上升至均值期间的一般规律性。根据各单预测因子周期外延曲线的峰、谷变化，预测下一次El Nino事件将于2001年下半年至2002年上半年期间形成。 相似文献
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基于TOPEX/Poseidon资料的南海海面高度场的时空特征分析 总被引：1，自引：0，他引：1
采用经验正交函数(EOF)分解方法，对TOPEX／Poseidon卫星高度计在南海获得的1992年10月到1999年9月约7a的海面高度观测资料进行分析，从而获得南海海面高度距平场典型的空间分布型态及其对应的时间变化特征。结果表明，南海海面高度距平场在空间上主要表现为两种典型的分布结构：(1)由于冬、夏季风反转造成海盆尺度的涡旋结构，这种分布结构对南海海面高度距平场的方差贡献达27．46％；(2)NE—SW即吕宋—越南反相双涡结构，其方差贡献达20．37％。这两个模态都明显反映了季风的反转以及季风结构所造成的影响。同时，对各空间典型场所对应的时间系数序列进行了傅立叶谱分析，结果表明南海海面高度距平场存在多种时间尺度的变化。 相似文献
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南海南部海域海面温度异常的时空分布特征 总被引：1，自引：0，他引：1
基于1982年1月—2006年12月NOAA Optimum Interpolation Sea Surface Temperature（OISST）的逐月平均海面温度（SST）资料,采用经验正交函数分解（EOF）方法分析了南海南部海面温度异常场典型的空间分布形态及其时间变化特征。结果表明,南海南部海域海面温度异常场空间上主要表现为三种典型的分布结构,即以研究区域北部为中心的海盆尺度的单涡结构、东西反相的经向偶极子分布结构和南北反相的纬向偶极子分布结构,这三种分布结构都以2—4年的年际变化周期为主,反映了研究海域海面温度异常与ENSO现象高度相关。此外,研究海域还存在显著的半年和季节内周期变化,这种变化周期主要以南北反相的纬向偶极子分布结构（第三模态）存在,反映了大气动力强迫和热力强迫共同影响的结果。 相似文献
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浙江海面变化的灰色模型分析与预测 总被引：1，自引：0，他引：1
应用灰色模型理论，分析了各影响海面变化因素的影响力度，指出影响浙江海面趋势性变化的主要因素是气温；建立了海面变化的灰色气温模型，其计算值与实测值吻合良好，可根据气温变化趋势预测未来海面变化趋势。若未来百年全球气温再上升１．５－５．５℃，浙江海面将对应上升２４－７８ｃｍ。灰色模型模拟还显示，未来平均高潮位于上升速率明显大于平均低潮位上升速率，潮差将逐渐增大，在相同平均海面升幅的情况下，未来海面上升对 相似文献
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Eight years of sea surface height data derived from the TOPEX/Poseidon altimeter, are analyzed in order to identify long- and a-periodic behavior of the North Atlantic sea level. For easy interpolation, sea surface height data are converted into sea surface topography data using the geoid derived from EGM96 to degree 360. Principal Component Analysis is used to identify the most dominant spatial and temporal variations. In order to separate dominant periodic signals, a yearly and a half-yearly oscillation, as well as alias effects from imperfect ocean tide corrections, are estimated independently by a Harmonic Analysis and subtracted. The residuals are smoothed by a 90-day moving average filter and examined once again by a PCA, which identifies a low-frequency variation with a period of approximately 6-7 years and an amplitude of about 1 dm, as well as a large sea level change of partially more than ±1 dm within only few months. This sea level change can also be seen in yearly and seasonal sea level residuals. Furthermore, the analysis shows a significant sea level change in 1998 occurring almost over the whole North Atlantic, which is not clearly identified by the PCA. Similar results are obtained by analyzing sea surface temperature and sea level pressure data. 相似文献
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Eight years of sea surface height data derived from the TOPEX/Poseidon altimeter, are analyzed in order to identify long- and a-periodic behavior of the North Atlantic sea level. For easy interpolation, sea surface height data are converted into sea surface topography data using the geoid derived from EGM96 to degree 360. Principal Component Analysis is used to identify the most dominant spatial and temporal variations. In order to separate dominant periodic signals, a yearly and a half-yearly oscillation, as well as alias effects from imperfect ocean tide corrections, are estimated independently by a Harmonic Analysis and subtracted. The residuals are smoothed by a 90-day moving average filter and examined once again by a PCA, which identifies a low-frequency variation with a period of approximately 6–7 years and an amplitude of about 1 dm, as well as a large sea level change of partially more than ±1 dm within only few months. This sea level change can also be seen in yearly and seasonal sea level residuals. Furthermore, the analysis shows a significant sea level change in 1998 occurring almost over the whole North Atlantic, which is not clearly identified by the PCA. Similar results are obtained by analyzing sea surface temperature and sea level pressure data. 相似文献
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Based on long-term tide gauge observations in the last 60 years, the temporal and spatial variation characteristics of sea level change along the coast of China are analyzed. The results indicate that the sea level along the coast of China has been rising at an increasing rate, with an estimated acceleration of 0.07 mm/a2. The rise rates were 2.4 mm/a, 3.4 mm/a and 3.9 mm/a during 1960–2020, 1980–2020 and 1993–2020, respectively. In the last 40 years, the coastal sea level has risen fastest in the South China Sea and slowest in the Yellow Sea. Seasonal sea levels all show an upward trend but rise faster in winter and spring and slower in autumn. Sea level change along the coast of China has significant periodic oscillations of quasi-2 a, 4 a, 7 a, 11 a, quasi-19 a and 30–50 a, among which the 2–3 a, 11 a, and 30–50 a signals are most remarkable, and the amplitude is approximately 1–2 cm. The coastal sea level in the most recent decade reached its highest value in the last 60 years. The decadal sea level from 2010 to 2019 was approximately 133 mm higher than the average of 1960–1969. Empirical orthogonal function analysis indicates that China’s coastal sea level has been changing in a north-south anti-phase pattern, with Pingtan and Fujian as the demarcation areas. This difference was especially obvious during 1980–1983, 1995–1997 and 2011–2013. The coastal sea level was the highest in 2016, and this extreme sea level event was analyzed to be related mainly to the anomalous wind field and ENSO. 相似文献
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带周期项的海平面变化灰色分析模型及广西海平面变化分析 总被引：7，自引：0，他引：7
提出了一种带周期项的海平面变化灰色分析模型.该模型保持了GM(1,1)模型能较好反应海平面变化趋势的优点,不仅能求出海平面变化速率,还能方便求出海平面变化的加速度,同时,该模型能较好的模拟海平面变化中的周期现象,从而克服了GM(1,1)不能预报周期性显著的月平均海面的缺点,并提高了预报精度.模型用于广西沿岸海平面变化分析,结果表明北海、涸洲、白龙尾3站的相对海平面上升速率分别为1.67、2.51、0.89mm/a;石头埠相对海平面呈下降趋势,下降速率为0.5～1.0mm/a;广西沿岸绝对海平面上升速率为2.0mm/a.和线性趋势项与周期项叠加的海平面分析模型相比,两者模拟精度相当. 相似文献
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1 .IntroductionTheglobalairtemperatureroseabout 0 .5～ 0 .6°Coverthepast 2 0thcentury ,andtheglobalmeansealevelincreasedbyabout2 0cmduringtheperiod .Theregionalmeansealevelriseswiththerisingglobalmeansealevel.Zuoetal.( 1 997)indicatedthatthemeanrisingrateofabsolutemeansealevelalongtheChinacoastontheassumptionofunifiedisostaticdatumis 2mm a .Woodworth( 1 999)analyzedsealevelspanning 1 76 8tothepresentinLiverpool,andobtainedaseculartrendforheperiodupto 1 880of0 .39± 0 .1 7mm a ,andatrendfort… 相似文献
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本文通过对中国沿海25个观测站水位资料的分析,初步探讨了中国沿海1980-2012年增减水的变化特征及与海平面变化的关系。结果表明:（1）中国沿海增减水的季节变化特征明显,相邻站由于受到的气象状况相同,其沿海增减水变化的过程相近,但是变化幅度存在较大差异。从空间分布看,沿海增减水的变化幅度呈现中间大南北小的区域特征,自长江口至广东沿海,增减水的年变化幅度最大,年变幅平均为5.0~7.5 cm;南海周边及北部湾沿海,增减水的年变化幅度次之,年变幅平均为4.0~5.5 cm;自渤海至黄海沿海,增减水的年变化幅度较小,年变幅平均为3.3~3.5 cm。（2）从时间变化看,1980-2012年中国沿海年平均增减水长期基本没有趋势性变化,但明显存在2至5年的周期性变化信号,该信号的震荡幅度为0.1 cm。经过高频滤波后,对沿海月平均增减水序列与Niño3.4指数进行相关性分析,相关系数为-0.5,该相关系数通过了显著性检验,说明中国沿海的增减水变化与ENSO事件呈现负相关关系。（3）中国沿海增减水的长期变化及空间分布特征均与海平面变化不同。1980-2012年,中国沿海海平面的上升速率为2.9 mm/a,而增减水长期基本无趋势性变化;另外,其季节变化与海平面的季节变化从时间和区域上均不存在一致性。（4）但是,短期海平面的变化与增减水有关,并且增减水对短期海平面的贡献根据其具体情况而定,增水幅度大且持续时间长的过程对短期海平面有抬升作用,其贡献率最大可达65%;反之,减水幅度大且持续时间长的过程则对短期海平面有降低的作用。 相似文献
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The long-term variation and seasonal variation of sea level have a notable effect on the calculation of engineering water level. Such an effect is first analyzed in this paper. The maximal amplitude of inter-annual anomaly of monthly mean sea level along the China coast is larger than 60 cm. Both the storm surge disaster and cold wave disaster are seasonal disasters in various regions, so the water level corresponding to the 1% of the cumulative frequency in the cumulative frequency curve of hourly water level data for different seasons in various sea areas is different from design water level, for example, the difference between them reaches maximum in June, July and August for northern sea area, and maximum in September, October and November for Southern China Sea. The hourly water level data of 19 gauge stations along the China coast are analyzed. Firstly, the annual mean sea level for every station is obtained; secondly, linear chan ging rates of annual mean sea level are obtained with the stochasti 相似文献
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