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印度尼西亚海域潮波的数值研究 总被引：1，自引：1，他引：0
基于ROMS模式构建了模拟区域为(15.52°S-7.13°N,110.39°~134.15°E)水平分辨率为2′的潮波数值模式,分别模拟了印尼海域M2、S2、K1、O1四个主要分潮。模拟结果与29个卫星高度计交叠点上的调和常数进行比较,符合较好。M2分潮的振幅均方根差为3.4cm,迟角均方根差为5.9°;S2分潮的振幅均方根差为1.7cm,迟角均方根差为6.3°;K1分潮振幅均方根差为1.1cm,迟角均方根差为5.8°;O1分潮振幅均方根差为1.2cm,迟角均方根差为4.4°。M2、S2、K1、O1分潮向量均方根差分别为3.8cm、2.4cm、1.9cm和1.3cm,模拟结果的相对偏差在10%左右。根据计算结果分析了印尼海域的潮汐特征及潮能传播规律,结果显示:爪哇海以外的印尼海域主要为不规则半日潮区;全日潮潮能主要由太平洋传入印尼海域,而半日潮潮能则是从印度洋传入印尼海域。 相似文献
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台湾以东黑潮的低频变化及机制研究 总被引：1，自引：0，他引：1
本文基于AVISO（Archiving, Validation and Interpretation of Satellite Oceanographic data）1993-2015年间的海表面绝对动力高度数据,研究了台湾以东黑潮的低频变化特征,并探讨了影响其变化的机制。结果表明,台湾以东多年平均的黑潮流幅值约为136 km,表层流量值约为7.75×104 m2/s,对应的标准差分别为28 km和2.14×104 m2/s。台湾以东黑潮不仅具有显著的季节变化特征,还具有显著的年际变化特征。功率谱分析结果表明,台湾以东黑潮表层流量具有1 a和2.8 a的显著周期。空间上,台湾东南部黑潮的年际变化幅度比东北部强烈。相关性及合成分析结果表明,台湾以东黑潮的年际变化与PTO（Philippines-Taiwan Oscillation）之间存在显著的相关性。PTO年际震荡所导致的副热带逆流区反气旋式涡旋与气旋式涡旋的相对强度是影响台湾以东黑潮年际变化的主要动力因素。 相似文献
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选取岱海湖流域3个国家一般气象站60年的气象资料,采用Penman-Monteith模型计算出岱海湖流域的参考蒸散量和干湿指数,表征岱海湖流域地表干湿状况。岱海湖流域地表多年平均干湿指数为0.42,属于气候半干旱区。20世纪60、70、90年代湿润指数距平为正距平,气候偏半湿润状态;20世纪80年代后期和21世纪初期（2000—2009年）为负距平,气候偏干旱化。干湿指数主要受降水量、潜在蒸散量、相对湿度、日照时数影响,这些气象因子共同作用影响岱海湖流域气候干湿状况,其中降水量是最主要的影响因子。研究结果可以更好地认识区域气候条件及未来变化方向,为岱海湖的生态评价提供科学参考。 相似文献
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滨海核电厂运行时会有少量的放射性核素通过液态途径进入海洋环境中,在掌握其海域水动力环境的基础上,开展放射性核素迁移研究具有重要意义。基于某核电站近岸海域的水下地形和水文条件,通过潮位、流速、流向的率定,构建水动力环境模型,模拟研究区的潮流运动过程和特征,为放射性核素迁移扩散提供基本流场背景。以核素131I为例,采用恒定速率1Bq/L活度浓度持续排放,用实测两个半月潮模拟核素迁移过程,分析放射性核素131I在该海域的时间和空间分布规律。结果表明:1)随着时间推移,核素逐渐向外海域扩散,但扩散速度较慢;随着距离增大,海域中核素活度浓度呈几何倍数快速下降;厂址东北方向岸边核素活度浓度较高,在一个月后逐步达到稳定,约比排放活度浓度低两个数量级。2)涨潮时核素活度浓度范围较小,落潮时核素活度浓度范围快速扩大,相同核素活度浓度面积为涨潮时的2~3倍。3)排放初期,各处核素活度浓度均随时间迅速增加,随后趋于稳定;不同位置的活度浓度随着潮汐交替涨落,不断波动,涨潮时活度浓度较低,落潮时活度浓度较高;不同位置的平均活度浓度随着潮汐交替涨落,不断波动,大潮期间活度浓度较高,小潮期间活度浓度快速降低。 相似文献
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Based on an empirical orthogonal function (EOF) analysis of the monthly NCEP Optimum Interpolation Sea Surface Temperature (OISST) data in the South China Sea (SCS) after removing the climatological mean and trends of SST, over the period of January 1982 to October 2003, the corresponding TCF correlates best with the Dipole Mode Index (DMI), Niño1+2, Niño3.4, Niño3, and Niño4 indices with time lags of 10, 3, 6, 5, and 6 months, respectively. Thus, a statistical hindcasts in the prediction model are based on a canonical correlation analysis (CCA) model using the above indices as predictors spanning from 1993/1994 to 2003/2004 with a 1–12 month lead time after the canonical variants are calculated, using data from the training periods from January 1982 to December1992. The forecast model is successful and steady when the lead times are 1–12 months. The SCS warm event in 1998 was successfully predicted with lead times from 1–12 months irrespective of the strength or time extent. The prediction ability for SSTA is lower during weak ENSO years, in which other local factors should be also considered as local effects play a relatively important role in these years. We designed the two forecast models: one using both DMI and Niño indices and the other using only Niño indices without DMI, and compared the forecast accuracies of the two cases. The spatial distributions of forecast accuracies show different confidence areas. By turning off the DMI, the forecast accuracy is lower in the coastal areas off the Philippines in the SCS, suggesting some teleconnection may occur with the Indian Ocean in this area. The highest forecast accuracies occur when the forecast interval is five months long without using the DMI, while using both of Niño indices and DMI, the highest accuracies occur when the forecast interval time is eight months, suggesting that the Niño indices dominate the interannual variability of SST anomalies in the SCS. Meanwhile the forecast accuracy is evaluated over an independent test period of more than 11 years (1993/94 to October 2004) by comparing the model performance with a simple prediction strategy involving the persistence of sea surface temperature anomalies over a 1–12 month lead time (the persisted prediction). Predictions based on the CCA model show a significant improvement over the persisted prediction, especially with an increased lead time (longer than 3 months). The forecast model performs steadily and the forecast accuracy, i.e., the correlation coefficients between the observed and predicted SSTA in the SCS are about 0.5 in most middle and southern SCS areas, when the thresholds are greater than the 95% confidence level. For all 1 to 12 month lead time forecasts, the root mean square errors have a standard deviation of about 0.2. The seasonal differences in the prediction performance for the 1–12 month lead time are also examined. 相似文献
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地下水中半挥发性有机污染物痕量分析的5个问题探讨 总被引：1，自引：1，他引：0
针对地下水中有机氯农药、多氯联苯和多环芳烃等半挥发性有机污染物的痕量分析,从实验室分析测试人员的角度,探讨了提高定量分析准确度的三个问题:分级绘制标准曲线、注重标准溶液配制细节、避免假阳性与假阴性.从实验室管理人员的角度探讨了提高实验室竞争力的两个问题:提高服务质量和降低分析成本.本文对这几个重要但往往易被忽视的问题进行逐一分析,并探讨了分级绘制标准曲线的方法、配制标准溶液应考虑的要点、避免假阳性与假阴性的措施,以及提高服务质量和降低成本的因素. 相似文献
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Based on an empirical orthogonal function (EOF) analysis of the monthly NCEP Optimum Interpolation Sea Surface Temperature (OISST) data in the South China Sea (SCS) after removing the climatological mean and trends of SST,over the period of January 1982 to October 2003,the corresponding TCF correlates best with the Dipole Mode Index (DMI),Nio1+2,Nio3.4,Nio3,and Nio4 indices with time lags of 10,3,6,5,and 6 months,respectively.Thus,a statistical hindcasts in the prediction model are based on a canonical correlation analysis (CCA) model using the above indices as predictors spanning from 1993/1994 to 2003/2004 with a 1-12 month lead time after the canonical variants are calculated,using data from the training periods from January 1982 to December1992.The forecast model is successful and steady when the lead times are 1-12 months.The SCS warm event in 1998 was successfully predicted with lead times from 1-12 months irrespective of the strength or time extent.The prediction ability for SSTA is lower during weak ENSO years,in which other local factors should be also considered as local effects play a relatively important role in these years.We designed the two forecast models:one using both DMI and Nio indices and the other using only Nio indices without DMI,and compared the forecast accuracies of the two cases.The spatial distributions of forecast accuracies show different confidence areas.By turning off the DMI,the forecast accuracy is lower in the coastal areas off the Philippines in the SCS,suggesting some teleconnection may occur with the Indian Ocean in this area.The highest forecast accuracies occur when the forecast interval is five months long without using the DMI,while using both of Nio indices and DMI,the highest accuracies occur when the forecast interval time is eight months,suggesting that the Nio indices dominate the interannual variability of SST anomalies in the SCS.Meanwhile the forecast accuracy is evaluated over an independent test period of more than 11 years (1993/94 to October 2004) by comparing the model performance with a simple prediction strategy involving the persistence of sea surface temperature anomalies over a 1-12 month lead time (the persisted prediction).Predictions based on the CCA model show a significant improvement over the persisted prediction,especially with an increased lead time (longer than 3 months).The forecast model performs steadily and the forecast accuracy,i.e.,the correlation coefficients between the observed and predicted SSTA in the SCS are about 0.5 in most middle and southern SCS areas,when the thresholds are greater than the 95% confidence level.For all 1 to 12 month lead time forecasts,the root mean square errors have a standard deviation of about 0.2.The seasonal differences in the prediction performance for the 1-12 month lead time are also examined. 相似文献
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为了研究黑潮跨过200m等深线对东海入侵的年际变化特征,本文基于ROMS(Regional Ocean Modeling System)海洋模式,对西北太平洋海域进行了高分辨率的数值模拟,模式水平分辨率高达4km,该分辨率可以很好地分辨黑潮以东区域的中尺度涡旋等过程。模式首先进行了6年的气候态模拟,然后进行了1993到2015年的后报模拟。模式很好地再现了东海陆架已知的环流结构,模拟出的对马海峡和台湾海峡的年平均流量和观测结果也比较一致。基于模式结果,利用旋转经验正交函数(REOF)的方法,对黑潮跨过200m等深线流量的年际变化进行分析。REOF的主要模态表明,黑潮跨过200m等深线对东海陆架的入侵主要发生台湾东北,并且入侵主要集中在黑潮次表层水中。主要模态的时间系数表明,黑潮入侵东海陆架的年平均流量存在一个8年的变化周期。相关性分析表明,黑潮入侵东海陆架的年际变化和太平洋年代际振荡PDO(Pacific Decadal Oscillation)指标具有显著的负相关,其相关系数达–0.63。该相关可以通过如下过程解释:PDO会导致东太平洋风应力涡度异常,由Sverdrup关系可知向赤道的体积输运也会相应地产生异常,根据质量守恒,向赤道体积输运的异常必然通过西边界流-黑潮的异常来平衡,从而导致黑潮入侵东海陆架强烈的年际变化。 相似文献