排序方式： 共有47条查询结果，搜索用时 15 毫秒
31.
黄河冲淡水转向问题的初步探讨 总被引：1，自引：0，他引：1
黄河自1976年改道清水沟流路,向东流入菜州湾以来,至1988年10月其大嘴已向莱州湾淤进18.8km(钱意颖等,1992),在科氏力的作用下,黄河入海口门也已转成东南方向。随着黄河口海区的开发利用,国内有关单位对黄河口海区的水文环境作过多次调查(朱兰部等,1994;张经等,1985;孙秉一等,198;Yang Zuosheng et al.,1989),从这些调査资料中我们发现,黄河入海径流和长江口一样,在洪水期冲淡水也有转向东北方向的特点。本文根据1976年黄河改道以来中国科学院海洋研究所有关单位在黄河口海区进行调查的水文资料和利津水文站的黄河径流观测资料,对黄河冲淡水的转向现象及其成因进行初步的分析研究,此研究对深入了解黄河口的水文环境及河口有机物、溶解质、悬浮体的输运特征有重要意义。 相似文献
32.
基于ICOADS、ERA-Interim 2种资料,对近35 a南海海-气温差空间分布进行比对,并使用经验正交分解及小波分析讨论了该区域海-气温差的时空分布变化特征。结果表明:ICOADS及ERA-Interim资料均可反映南海海-气温差的实际分布,但同一区域内ERA-Interim下的海-气温差数值较ICOADS偏低,且ERA-Interim在近岸特征不明显;南海南北部海-气温差呈跷跷板型变化,4、5月达南负北正峰值,11月达南正北负峰值;夏、秋季南海海-气温差的年际变化呈波动下降趋势,夏季海-气温差在北部湾与南海主体海域间呈跷跷板关系,秋季南沙群岛海域存在明显海-气温差高值区;四个季节南海海-气温差准3 a振荡周期显著,冬、春季还具有准11 a 振荡周期;海-气温差与夏、秋季Ni?o3.4指数呈正相关,冬、春季呈负相关。 相似文献
33.
南海沿海季节性海平面异常变化特征及成因分析 总被引：1，自引：1，他引：0
Based on sea level, air temperature, sea surface temperature(SST), air pressure and wind data during 1980–2014,this paper uses Morlet wavelet transform, Estuarine Coastal Ocean Model(ECOM) and so on to investigate the characteristics and possible causes of seasonal sea level anomalies along the South China Sea(SCS) coast. The research results show that:(1) Seasonal sea level anomalies often occur from January to February and from June to October. The frequency of sea level anomalies is the most in August, showing a growing trend in recent years. In addition, the occurring frequency of negative sea level anomaly accounts for 50% of the total abnormal number.(2) The seasonal sea level anomalies are closely related to ENSO events. The negative anomalies always occurred during the El Ni?o events, while the positive anomalies occurred during the La Ni?a(late El Ni?o) events. In addition, the seasonal sea level oscillation periods of 4–7 a associated with ENSO are the strongest in winter, with the amplitude over 2 cm.(3) Abnormal wind is an important factor to affect the seasonal sea level anomalies in the coastal region of the SCS. Wind-driven sea level height(SSH) is basically consistent with the seasonal sea level anomalies. Moreover, the influence of the tropical cyclone in the coastal region of the SCS is concentrated in summer and autumn, contributing to the seasonal sea level anomalies.(4) Seasonal variations of sea level, SST and air temperature are basically consistent along the coast of the SCS, but the seasonal sea level anomalies have no much correlation with the SST and air temperature. 相似文献
34.
35.
浅水港口潮汐预报准调和方法的改进 总被引：4，自引：1，他引：3
文中提出了浅水港口潮汐预报准调和方法的两个改进方案.一个是在方国洪等(1981)《浅水港口潮汐预报的一个方法》基础上,增加14周/日、16周/日以及与前期潮汐状况有关的浅水准调和项共6项(方案Ⅰ);另一个在是王骥(2001)提出的方案基础上改进的方案,该方案与方案Ⅰ相比,增加了5个准调和项(方案Ⅱ).这两个方案选用相同的57个调和分潮,但分潮的组合及派生出的准调和项有所不同.方案Ⅰ用40项准调和项表示浅水效应,方案Ⅱ则包含长周期、全日、半日周期的准调和项18项.经过大量实测水位资料的分析和预报检验,表明改进后两个方案对浅水港口潮汐的预报精度均较改进前的准调和方法和传统调和法有明显提高,对第一类浅水港(以吴淞港为例),文中所列的8项预报指标都有显著提高,特别是低潮时均方差由26.8min降至15.1min;对第二类浅水港(以成山角为例),高潮时均方差显著减小,由39.6min减至26.7min. 相似文献
36.
使用卫星测高、海表温度以及中国沿海台站水位等数据,分析研究了ENSO对中国近海海平面影响的区域特征。结果表明:（1）赤道东太平洋海表温度与我国近海海平面存在显著的遥相关关系。相关系数自北至南呈梯度递增,分为3个影响明显的区域,分别是渤、黄海、东海和南海海域。南海海平面异常与赤道东太平洋区域的海表温度异常相关性最强,大部分区域的相关系数超过了0.6;东海海域海平面异常与赤道东太平洋海表温度的遥相关系数弱于南海,强于渤、黄海,大部分海域的遥相关系数超过了0.4;渤、黄海海域海平面异常与赤道东太平洋海表温度的遥相关系数最弱,但是大部分海域的遥相关系数超过了0.3,通过了显著性检验。（2）中国沿海海平面的季节变化与ENSO有明显的相关关系,且影响范围具有明显的区域特征,以长江口和台湾海峡为分界线分为长江口以北、长江口到台湾海峡以及台湾海峡以南3个区域。海平面的年振幅在厄尔尼诺年均出现偏低的现象,并且年振幅的极小值均出现在厄尔尼诺年。另外,海平面的年振幅对厄尔尼诺事件的响应与其强弱有关,在强厄尔尼诺事件中,响应区域和幅度较大,弱事件中,响应区域和幅度偏小。（3）南海、东海和渤、黄海这3个区域沿海的海平面变化均存在4~7 a的显著振荡周期,说明这3个区域的海平面均受ENSO的影响。其中,南海7 a周期的振荡幅度最大,约为1.5 cm;东海7 a周期的振荡幅度次之,约为1.3 cm;渤、黄海6 a周期的振荡幅度最小,不到1 cm。 相似文献
37.
38.
Using the International Comprehensive Ocean-Atmosphere Data Set(ICOADS) and ERA-Interim data, spatial distributions of air-sea temperature difference(ASTD) in the South China Sea(SCS) for the past 35 years are compared,and variations of spatial and temporal distributions of ASTD in this region are addressed using empirical orthogonal function decomposition and wavelet analysis methods. The results indicate that both ICOADS and ERA-Interim data can reflect actual distribution characteristics of ASTD in the SCS, but values of ASTD from the ERA-Interim data are smaller than those of the ICOADS data in the same region. In addition, the ASTD characteristics from the ERA-Interim data are not obvious inshore. A seesaw-type, north-south distribution of ASTD is dominant in the SCS; i.e., a positive peak in the south is associated with a negative peak in the north in November, and a negative peak in the south is accompanied by a positive peak in the north during April and May. Interannual ASTD variations in summer or autumn are decreasing. There is a seesaw-type distribution of ASTD between Beibu Bay and most of the SCS in summer, and the center of large values is in the Nansha Islands area in autumn. The ASTD in the SCS has a strong quasi-3a oscillation period in all seasons, and a quasi-11 a period in winter and spring. The ASTD is positively correlated with the Nio3.4 index in summer and autumn but negatively correlated in spring and winter. 相似文献
39.
环渤海沿岸海表温度资料的均一性检验与订正 总被引：2，自引：1，他引：1
本文对环渤海沿岸具有代表性且资料完整的6个海洋观测站的月均海表温度(SST)序列作均一性检验和订正。我国海洋观测站密集度低,难以选择参考序列,本文首先采用不依赖参考序列的惩罚最大F检验(PMFT)方法对SST序列检验,利用详尽的元数据对检验结果进行确认,再对不连续点订正,该方法适用于元数据详尽的海洋观测站。对于元数据不详尽的观测站,使用惩罚最大T检验(PMT)方法,选取与海洋台站距离近且相关显著的气象观测站的均一化地面气温序列来制作参考序列,对SST序列进行检验和订正。结果表明,环渤海地区SST序列都存在一定非均一性,观测站较大距离迁移和观测系统变更(从人工观测到自动化观测)是造成非均一性的重要原因。订正后的环渤海地区年平均SST增温趋势更加明显。本文使用不同方法来检验SST序列的均一性,该思路对沿海其他海区观测站SST均一性检验和订正有一定参考价值和应用前景,可为沿海气候变化研究提供科学准确的第一手资料。 相似文献
40.
东海沿海季节性海平面异常成因 总被引：1，自引：0，他引：1
Based on the analysis of sea level, air temperature, sea surface temperature(SST), air pressure and wind data during 1980–2013, the causes of seasonal sea level anomalies in the coastal region of the East China Sea(ECS) are investigated. The research results show:(1) sea level along the coastal region of the ECS takes on strong seasonal variation. The annual range is 30–45 cm, larger in the north than in the south. From north to south, the phase of sea level changes from 140° to 231°, with a difference of nearly 3 months.(2) Monthly mean sea level(MSL)anomalies often occur from August to next February along the coast region of the ECS. The number of sea level anomalies is at most from January to February and from August to October, showing a growing trend in recent years.(3) Anomalous wind field is an important factor to affect the sea level variation in the coastal region of the ECS. Monthly MSL anomaly is closely related to wind field anomaly and air pressure field anomaly. Wind-driven current is essentially consistent with sea surface height. In August 2012, the sea surface heights at the coastal stations driven by wind field have contributed 50%–80% of MSL anomalies.(4) The annual variations for sea level,SST and air temperature along the coastal region of the ECS are mainly caused by solar radiation with a period of12 months. But the correlation coefficients of sea level anomalies with SST anomalies and air temperature anomalies are all less than 0.1.(5) Seasonal sea level variations contain the long-term trends and all kinds of periodic changes. Sea level oscillations vary in different seasons in the coastal region of the ECS. In winter and spring, the oscillation of 4–7 a related to El Ni?o is stronger and its amplitude exceeds 2 cm. In summer and autumn, the oscillations of 2–3 a and quasi 9 a are most significant, and their amplitudes also exceed 2 cm. The height of sea level is lifted up when the different oscillations superposed. On the other hand, the height of sea level is fallen down. 相似文献