An experimental comparison of the velocities and energies of focused spilling waves in deep water     

Xu  Yuanyuan  Liang  Shuxiu  Sun  Zhaochen  Xue  Qingren  Bi  Xiaoqi 《Ocean Dynamics》2020,70(7):863-877

Ocean Dynamics - It is important to achieve a better understanding of the wave energy variations occurring as a steep wave evolves towards breaking. Laboratory experiments of focused waves are...  相似文献   

A forecasting model for wave heights based on a long short-term memory neural network     

Song Gao  Juan Huang  Yaru Li  Guiyan Liu  Fan Bi  Zhipeng Bai 《海洋学报(英文版)》2021,40(1):62-69

To explore new operational forecasting methods of waves, a forecasting model for wave heights at three stations in the Bohai Sea has been developed. This model is based on long short-term memory(LSTM) neural network with sea surface wind and wave heights as training samples. The prediction performance of the model is evaluated,and the error analysis shows that when using the same set of numerically predicted sea surface wind as input, the prediction error produced by the proposed LSTM model at Sta. N01 is 20%, 18% and 23% lower than the conventional numerical wave models in terms of the total root mean square error(RMSE), scatter index(SI) and mean absolute error(MAE), respectively. Particularly, for significant wave height in the range of 3–5 m, the prediction accuracy of the LSTM model is improved the most remarkably, with RMSE, SI and MAE all decreasing by 24%. It is also evident that the numbers of hidden neurons, the numbers of buoys used and the time length of training samples all have impact on the prediction accuracy. However, the prediction does not necessary improve with the increase of number of hidden neurons or number of buoys used. The experiment trained by data with the longest time length is found to perform the best overall compared to other experiments with a shorter time length for training. Overall, long short-term memory neural network was proved to be a very promising method for future development and applications in wave forecasting.  相似文献   

大地电场观测中干扰变化的特征分析     

胡小静  毕青  付虹 《地震》2017,37(2):157-166

针对云南省地电场观测中常见的路灯漏电、 雷电及降雨3种典型干扰因素, 分别讨论了干扰变化的形态特征、 功率谱分析结果、 干扰产生的过程和机理以及地电场地架设时的注意事项, 最后阐述了干扰识别的原理和依据, 得到以下认识: 路灯漏电引起的干扰变化以阶跃型周期变化为主要形态, 变化幅度主要受漏电产生的入地电流强度和土壤介质导电性能的影响; 雷电引起的干扰变化以典型的大幅畸变为主要形态, 主要与放电场强和雷区距离有关; 降雨引起的干扰变化以大幅上升或下降为主要形态, 持续过程与降雨量和电极自身性能有较大关系。  相似文献   

An effective method based on dynamic sampling for data assimilation in a global wave model   总被引：3，自引：2，他引：1  

Meng Sun  Xunqiang Yin  Yongzeng Yang  Kejian Wu 《Ocean Dynamics》2017,67(3-4):433-449

The ensemble Kalman filter (EnKF) performs well because that the covariance of background error is varying along time. It provides a dynamic estimate of background error and represents the reasonable statistic characters of background error. However, high computational cost due to model ensemble in EnKF is employed. In this study, two methods referred as static and dynamic sampling methods are proposed to obtain a good performance and reduce the computation cost. Ensemble adjustment Kalman filter (EAKF) method is used in a global surface wave model to examine the performance of EnKF. The 24-h interval difference of simulated significant wave height (SWH) within 1 year is used to compose the static samples for ensemble errors, and these errors are used to construct the ensemble states at each time the observations are available. And then, the same method of updating the model states in the EAKF is applied for the ensemble states constructed by a static sampling method. The dynamic sampling method employs a similar method to construct the ensemble states, but the period of the simulated SWH is changing with time. Here, 7 days before and after the observation time is used as this period. To examine the performance of three schemes, EAKF, static, or dynamic sampling method, observations from satellite Jason-2 in 2014 are assimilated into a global wave model, and observations from satellite Saral are used for validation. The results indicate that the EAKF performs best, while the static sampling method is relatively worse. The dynamic sampling method improves an assimilation effect dramatically compared to the static sampling method, and its overall performance is closed to the EAKF. In low latitudes, the dynamic sampling method has a slight advantage over the EAKF. In the dynamic or static sampling methods, only one wave model is required to run and their computational cost is reduced sharply. According to the performance of these three methods, the dynamic sampling method can treated as an effective alternative of EnKF, which could reduce the computational cost and provide a good performance of data assimilation.  相似文献   

Arctic sea ice concentration and thickness data assimilation in the FIO-ESM climate forecast system     

Qi Shu  Fangli Qiao  Jiping Liu  Zhenya Song  Zhiqiang Chen  Jiechen Zhao  Xunqiang Yin  Yajuan Song 《海洋学报(英文版)》2021,40(10):65-75

To improve the Arctic sea ice forecast skill of the First Institute of Oceanography-Earth System Model (FIO-ESM) climate forecast system, satellite-derived sea ice concentration and sea ice thickness from the Pan-Arctic Ice-Ocean Modeling and Assimilation System (PIOMAS) are assimilated into this system, using the method of localized error subspace transform ensemble Kalman ?lter (LESTKF). Five-year (2014–2018) Arctic sea ice assimilation experiments and a 2-month near-real-time forecast in August 2018 were conducted to study the roles of ice data assimilation. Assimilation experiment results show that ice concentration assimilation can help to get better modeled ice concentration and ice extent. All the biases of ice concentration, ice cover, ice volume, and ice thickness can be reduced dramatically through ice concentration and thickness assimilation. The near-real-time forecast results indicate that ice data assimilation can improve the forecast skill significantly in the FIO-ESM climate forecast system. The forecasted Arctic integrated ice edge error is reduced by around 1/3 by sea ice data assimilation. Compared with the six near-real-time Arctic sea ice forecast results from the subseasonal-to-seasonal (S2S) Prediction Project, FIO-ESM climate forecast system with LESTKF ice data assimilation has relatively high Arctic sea ice forecast skill in 2018 summer sea ice forecast. Since sea ice thickness in the PIOMAS is updated in time, it is a good choice for data assimilation to improve sea ice prediction skills in the near-real-time Arctic sea ice seasonal prediction.  相似文献   

Evaluation on surface current observing network of high frequency ground wave radars in the Gulf of Thailand     

Xunqiang Yin  Junqiang Shi  Fangli Qiao 《Ocean Dynamics》2018,68(4-5):575-587

Due to the high cost of ocean observation system, the scientific design of observation network becomes much important. The current network of the high frequency radar system in the Gulf of Thailand has been studied using a three-dimensional coastal ocean model. At first, the observations from current radars have been assimilated into this coastal model and the forecast results have improved due to the data assimilation. But the results also show that further optimization of the observing network is necessary. And then, a series of experiments were carried out to assess the performance of the existing high frequency ground wave radar surface current observation system. The simulated surface current data in three regions were assimilated sequentially using an efficient ensemble Kalman filter data assimilation scheme. The experimental results showed that the coastal surface current observation system plays a positive role in improving the numerical simulation of the currents. Compared with the control experiment without assimilation, the simulation precision of surface and subsurface current had been improved after assimilated the surface currents observed at current networks. However, the improvement for three observing regions was quite different and current observing network in the Gulf of Thailand is not effective and a further optimization is required. Based on these evaluations, a manual scheme has been designed by discarding the redundant and inefficient locations and adding new stations where the performance after data assimilation is still low. For comparison, an objective scheme based on the idea of data assimilation has been obtained. Results show that all the two schemes of observing network perform better than the original network and optimal scheme-based data assimilation is much superior to the manual scheme that based on the evaluation of original observing network in the Gulf of Thailand. The distributions of the optimal network of radars could be a useful guidance for future design of observing system in this region.  相似文献   

Climate and extrema of ocean waves in the East China Sea     

Hailun He  Jinbao Song  Yefei Bai  Yao Xu  Juanjuan Wang  Fan Bi 《中国科学:地球科学(英文版)》2018,61(7):980-994

Wave climate plays an important role in the air-sea interaction over marginal seas. Extreme wave height provides fundamental information for various ocean engineering practices, such as hazard mitigation, coastal structure design, and risk assessment. In this paper, we implement a third generation wave model and conduct a high-resolution wave hindcast over the East China Sea to reconstruct a 15-year wave field from 1988 to 2002 for derivation of monthly mean wave parameters and analysis of extreme wave conditions. The numerical results of the wave field are validated through comparison with satellite altimetry measurements, low-resolution reanalysis, and the ocean wave buoy record. The monthly averaged wave height and wave period show seasonal variation and refined spatial patterns of surface waves in the East China Sea. The climatological significant wave height and mean wave period decrease from the open ocean in the southeast toward the continental area in the northwest, with the pattern generally following the bathymetry. Extreme analysis on the significant wave height at the buoy station indicates the hindcast data underestimate the extreme values relative to the observations. The spatial pattern of extreme wave height shows single peak emerges at the southwest of Ryukyu Island although a wind forcing with multi-core structure at the extreme is applied.  相似文献   

蓝藻光合氮同化的特征与分子调控机理研究进展     

杨小龙  刘莉华  毕永红  王洵  董薇  邓自发  王寿兵 《湖泊科学》2023,35(3):766-779

水华蓝藻的生物学特性及其竞争优势、蓝藻水华的形成与维持机制等科学问题,一直是国内外研究的热点。氮素是诱发蓝藻水华暴发的重要营养盐,蓝藻对氮素的同化与其光合作用密切偶联。然而,水体中氮素存在多种形态,不同形态氮素对蓝藻生长和水华发生的影响具有显著差异。因此,了解蓝藻光合作用特征及其同化不同形态氮素的机制和策略,对深入理解蓝藻水华的发生机理具有重要意义。本文在蓝藻的光能捕获与激发能转移、光合电子传递、碳浓缩机制及CO₂同化等光合作用过程及其特征综述的基础上,对蓝藻摄取、同化5种主要氮素形态(NO₃^-、NO₂^-、NH₄⁺、尿素和N₂)的分子机制及其特征进行了解读,总结了蓝藻细胞光合碳、氮同化的耦合关系及调控机制;并指出了该领域的未来发展方向,以推动该方向的深入研究。  相似文献   

地质雷达属性分析在浙江良渚莫角山红烧土层探测中的应用     

毕亚杰  田钢 《江苏地质》2020,44(4):442-446

应用地质雷达划分地层的主要依据是地层介质的电性差异，介质间的电性差异越大，地层界面越容易分辨。但在实际雷达探测中，某些介质虽然具有不同的电性参数，但会产生相同或相似的异常信号，这为地层划分工作带来困难。根据钻孔土芯测量出不同地层的电性参数，获取地质雷达探测的前提条件，对良渚遗址群莫角山红烧土遗址进行雷达数据采集，经预处理后分别进行常规数据处理和纹理属性提取分析，对比发现属性分析在地层划分上比常规处理方法更有优势。  相似文献   

热带东印度洋海表温度持续性的秋季障碍          下载免费PDF全文

郭品文  杨丽萍  唐碧 《大气科学学报》2010,33(1):1-6

利用全球海表海温资料(GISST)和NCEP/NCAR再分析风场、海平面气压场资料,研究了热带东印度洋海表温度持续性的季节差异,发现东印度洋海温持续性存在"秋季障碍"现象。进一步分析了东印度洋"秋季障碍"后冬季海温与中东太平洋海温、海平面气压及850hPa风场的关系,并讨论了热带印度洋—太平洋地区海气系统的季节变化与东印度洋"秋季障碍"的关系,结果表明,秋季热带印度洋—太平洋地区海气系统由以印度洋季风环流为主导转向以太平洋海气系统为主导,太平洋海气系统处于急剧加强期,增强的太平洋海气系统对东印度洋海温持续性"秋季障碍"起着重要的作用。  相似文献