共查询到19条相似文献，搜索用时 93 毫秒
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水位在忽略观测误差的前提下,可分解为潮位和余水位,后者具有较强的空间相关性以及非平稳特征,是影响水位预报精度的主要因素。港口工程、航运计划编制等方面对实时高精度水位预报具有重要需求,这对余水位预报模型构建提出了更高要求。另外,利用高精度余水位预报模型可减少验潮站布设数量。针对余水位短期预测模型精度不高的现状,本文对余水位进行集合经验模态(EEMD)分解,获得余水位在时间序列上的本征模函数(IMF);使用快速傅立叶变换(FFT)分析各本征模函数的频谱特征;再利用BP神经网络对各个本征模函数进行训练,预测了未来6 h、12 h、24 h的余水位值。对哥伦比亚河下游河口处的3组典型验潮站的余水位数据的预测结果表明,在未来6 h、12 h内的余水位的预测精度达到厘米级,在24 h内接近厘米级,证明了该组合模型在余水位短期预测方面的可行性。 相似文献
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深度基准面是海图水深的起算面,其精度直接影响着真实水深的精度.《海道测量规范》中对深度基准的求解方法进行了规定,但是未对其求解精度进行要求.因此本文采用我国10个验潮站19a间水位观测数据,分析了各站点不同水位观测时长求解的平均海面精度和深度基准精度,实验结果表明,对于港航区域重要长期验潮站,海图深度基准的设定应该采用基于多年平均海面的深度基准结果:对于短期验潮站来说,基于多年平均海面、年平均海面和转测邻近长期站平均海面三者得到的月深度基准精度大概在5-20cm,且三者之间差别不大. 相似文献
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This paper attempts to assess the use of Global Navigation Satellite System (GNSS) as an accurate, reliable, and easy tool for sea level measurement. The GNSS technique was incorporated into a float based tide gauge system. A prototype of such an instrument was developed based on principles of conventional tide gauges, where high frequency noise is reduced mechanically. The ability of the GNSS based tide gauge (GTG) to monitor sea levels was tested in several experiments. The performance of the GTG was compared to that of a traditional tide gauge. The method of data analysis and data comparison between the GPS measurements and the tide gauge data is presented. The results show that the GTG is equal in performance to the traditional float operated tide gauge. It seems that the GTG is capable of delivering the same level of accuracy (1 cm), and its results are as reliable as its competitor, the traditional float tide gauge. The suggested instrument can be easily integrated into the array of permanent GNSS stations and assist in absolute measurements of sea level changes, caused by global warming and the greenhouse effect, for example. 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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利用中国沿岸验潮站GNSS和邻近地区陆态网络GNSS基准站观测数据,结合卫星高度计和验潮站海平面观测数据分析了中国沿海验潮站及其邻近地区陆地垂直运动特征。中国沿海海平面观测以及验潮站和陆态网GNSS基准站观测结果显示,中国沿海省区市及沿海验潮站陆地垂直运动总体表现为：辽宁至江苏沿海上升、上海至福建泉州沿海沉降、福建厦门至广西沿海升降交替的格局,局部滨海平原地区如华北平原天津南部、河北平原的沧县则表现出显著的沉降特征。验潮站陆地的抬升与沉降是沿海相对海平面变化的重要组成部分,准确掌握验潮站及其邻近区域的陆地垂直运动特征,可为沿海相对海平面变化分析、海平面变化影响评估以及未来海平面上升预测提供依据。 相似文献
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南海北部沿岸海域潮汐的调和分析 总被引：1，自引：0，他引：1
采用t_tide潮汐分析工具对南海北部的5个验潮站2009年全年的逐时潮高资料进行调和分析,计算出各站的调和常数,评估调和常数的准确性、稳定性,并总结了广东沿岸海域潮汐特征.利用对2009年逐时潮高的调和分析结果对2010年全年的潮高进行预测,将各站预测结果与同时间的实测数据进行全年和分季节进行比较,对预测结果与实测数据的残差进行统计分析.通过对残差的散点分布、概率分布、置信区间等统计结果进行分析,检验预测结果的准确性、稳定性和可靠性.结果表明：广东沿岸海域潮汐是以M2分潮为主,K1、O1、S2为次结合的潮汐机制,采用t_tide潮汐分析工具对南海北部潮高的预测结果与实测数据拟合较好,相位预测准确,潮高预测除在时间序列尾部（年尾）有些许较大的误差外,t_tide工具在南海北部潮汐预报中具有较高的准确性和稳定性.预测残差的整体服从正态分布,残差均值小于10-2m量级,方差最大为0.229 4,最小为0.173 2,95%置信区间长度小于10-2.各站季节分析主要分潮的离散度小于0.04的结果充分证明不同季节的分析区别不明显,3个月资料与整年资料的调和分析结果几乎一致,与所选取的季节资料几乎无关.虽然在预测值中,有极个别的残差将近1 m,但并不足以影响到预测的准确性. 相似文献
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Arctic absolute sea level variations were analyzed based on multi-mission satellite altimetry data and tide gauge observations for the period of 1993–2018. The range of linear absolute sea level trends were found ?2.00 mm/a to 6.88 mm/a excluding the central Arctic, positive trend rates were predominantly located in shallow water and coastal areas, and negative rates were located in high-latitude areas and Baffin Bay. Satellite-derived results show that the average secular absolute sea level trend was (2.53±0.42) mm/a in the Arctic region. Large differences were presented between satellite-derived and tide gauge results, which are mainly due to low satellite data coverage, uncertainties in tidal height processing and vertical land movement (VLM). The VLM rates at 11 global navigation satellite system stations around the Arctic Ocean were analyzed, among which 6 stations were tide gauge co-located, the results indicate that the absolute sea level trends after VLM corrected were of the same magnitude as satellite altimetry results. Accurately calculating VLM is the primary uncertainty in interpreting tide gauge measurements such that differences between tide gauge and satellite altimetry data are attributable generally to VLM. 相似文献
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