Networking Observation and Applications of Chinese Ocean Satellites

This paper presents the networking observation capabilities of Chinese ocean satellites and their diverse applications in ocean disaster prevention,ecological monitoring,and resource development.Since the inaugural launch in 2002,China has achieved substantial advancements in ocean satellite technology,forming an observation system composed of the HY-1,HY-2,and HY-3 series satellites.These satellites are integral to global ocean environmental monitoring due to their high resolution,extensive coverage,and frequent observations.Looking forward,China aims to further enhance and expand its ocean satellite capabilities through ongoing projects to support global environmental protection and sustainable development.

Wave forecast in the Atlantic Ocean using a double-stage ConvLSTM network

海浪预报对海上运输安全至关重要.本研究提出了一种涵盖物理信息的深度学习模型Double-stage ConvLSTM(D-ConvLSTM)以改进大西洋的海浪预报.将D-ConvLSTM模型与海浪持续性预测和原始ConvLSTM模型的预测技巧进行对比.结果表明,预测误差随着预测时长的增加而增加.D-ConvLSTM模型在预测准确度方面优于前二者,且第三天预测的均方根误差低于0.4 m,距平相关系数约在0.8.此外,当使用IFS预测风替代再分析风时,能够产生相似的预测效果.这表明D-ConvLSTM模型的预测能力能够与ECMWF-WAM模式相当,且更节省计算资源和时间.

Initial evaluations of a Gulf of Mexico/Caribbean ocean forecast system in the context of the Deepwater Horizon disaster

In response to the Deepwater Horizon （DwH） oil spill event in 2010, the Naval Oceanographic Office deployed a nowcast-forecast system covering the Gulf of Mexico and adjacent Caribbean Sea that was designated Americas Seas, or AMSEAS, which is documented in this manuscript. The DwH disaster provided a challenge to the application of available ocean-forecast capabilities, and also generated a historically large observational dataset. AMSEAS was evaluated by four complementary efforts, each with somewhat different aims and approaches： a university research consortium within an Integrated Ocean Observing System （IOOS） testbed; a petroleum industry consortium, the Gulf of Mexico 3-D Operational Ocean Forecast System Pilot Prediction Project （GOMEX-PPP）; a British Petroleum （BP） funded project at the Northern Gulf Institute in response to the oil spill; and the Navy itself. Validation metrics are presented in these different projects for water temperature and salinity profiles, sea surface wind, sea surface temperature, sea surface height, and volume transport, for different forecast time scales. The validation found certain geographic and time biases/errors, and small but systematic improvements relative to earlier regional and global modeling efforts. On the basis of these positive AMSEAS validation studies, an oil spill transport simulation was conducted using archived AMSEAS nowcasts to examine transport into the estuaries east of the Mississippi River. This effort captured the influences of Hurricane Alex and a non-tropical cyclone off the Louisiana coast, both of which pushed oil into the western Mississippi Sound, illustrating the importance of the atmospheric influence on oil spills such as DwH.

Development of a fine-resolution atmosphere-wave-ocean coupled forecasting model for the South China Sea and its adjacent seas

A 72-h fine-resolution atmosphere-wave-ocean coupled forecasting system was developed for the South China Sea and its adjacent seas. The forecasting model domain covers from from 15°S to 45°N in latitude and 99°E to135°E in longitude including the Bohai Sea, the Yellow Sea, the East China Sea, the South China Sea and the Indonesian seas. To get precise initial conditions for the coupled forecasting model, the forecasting system conducts a 24-h hindcast simulation with data assimilation before forecasting. The Ensemble Adjustment Kalman Filter(EAKF) data assimilation method was adopted for the wave model MASNUM with assimilating Jason-2 significant wave height(SWH) data. The EAKF data assimilation method was also introduced to the ROMS model with assimilating sea surface temperature(SST), mean absolute dynamic topography(MADT) and Argo profiles data. To improve simulation of the structure of temperature and salinity, the vertical mixing scheme of the ocean model was improved by considering the surface wave induced vertical mixing and internal wave induced vertical mixing. The wave and current models were integrated from January 2014 to October 2015 driven by the ECMWF reanalysis 6 hourly mean dataset with data assimilation. Then the coupled atmosphere-wave-ocean forecasting system was carried out 14 months operational running since November 2015. The forecasting outputs include atmospheric forecast products, wave forecast products and ocean forecast products. A series of observation data are used to evaluate the coupled forecasting results, including the wind, SHW, ocean temperature and velocity.The forecasting results are in good agreement with observation data. The prediction practice for more than one year indicates that the coupled forecasting system performs stably and predict relatively accurate, which can support the shipping safety, the fisheries and the oil exploitation.

Verification of an operational ocean circulation-surface wave coupled forecasting system for the China＇s seas

An operational ocean circulation-surface wave coupled forecasting system for the seas off China and adjacent areas（OCFS-C） is developed based on parallelized circulation and wave models. It has been in operation since November 1, 2007. In this paper we comprehensively present the simulation and verification of the system, whose distinguishing feature is that the wave-induced mixing is coupled in the circulation model. In particular, with nested technique the resolution in the China＇s seas has been updated to（1/24）° from the global model with（1/2）°resolution. Besides, daily remote sensing sea surface temperature（SST） data have been assimilated into the model to generate a hot restart field for OCFS-C. Moreover, inter-comparisons between forecasting and independent observational data are performed to evaluate the effectiveness of OCFS-C in upper-ocean quantities predictions, including SST, mixed layer depth（MLD） and subsurface temperature. Except in conventional statistical metrics, non-dimensional skill scores（SS） is also used to evaluate forecast skill. Observations from buoys and Argo profiles are used for lead time and real time validations, which give a large SS value（more than 0.90）. Besides, prediction skill for the seasonal variation of SST is confirmed. Comparisons of subsurface temperatures with Argo profiles data indicate that OCFS-C has low skill in predicting subsurface temperatures between 100 m and 150 m. Nevertheless, inter-comparisons of MLD reveal that the MLD from model is shallower than that from Argo profiles by about 12 m, i.e., OCFS-C is successful and steady in MLD predictions. Validation of 1-d, 2-d and 3-d forecasting SST shows that our operational ocean circulation-surface wave coupled forecasting model has reasonable accuracy in the upper ocean.

Forecast and Analysis of the Main Indicators for the Development of Ocean Fishery in China during the Twelfth Five-Year Plan Period

The ocean fishery is an important part of the marine economy and an important source of human food.The leaders at all levels attach great importance to the development and utilization of ocean fishery resources.Using the regression analysis method,we forecast the main indicators for the development of ocean fishery during the Twelfth Five-Year Plan period.Through the study,it is found that in 2015,the value added of ocean fishery in China is expected to exceed 360 billion yuan,and the output of marine products will exceed 30 million tons.The marine products make stable contribution to the marine economy and the residents'nutrient composition,conducive to maintaining the stable supply of the market and meeting the residents'daily needs for marine products.

Study on short－range numerical forecasting of ocean current in the East China Sea－Ⅲ Three－dimensional baroclinic anomaly forecasting model And its application

A three-dimensional baroclinic numerical forecasting model for anomaly current field is developed forapplication in the Bohai Sea and the upper layer of the Huanghai Sea and the East China Sea. All the dynamical variables, including temperature and salinity, can be calculated predictively by using the model. The results of the numerical weather prediction are used as input fields,and various dynamic and thermodynamic boundary conditions areadopted. So, the model can be used as an operational numerical forecasting model for current fields. In this paper,the structure of the model is presented in detail, various tests for the performance of the model are made, and thedependence of the model on some parameters is discussed. The results of the numerical simulation using historicaldata and experimental forecasting tests are also presented.

A Spatiotemporal Interactive Processing Bias Correction Method for Operational Ocean Wave Forecasts

Numerical models and correct predictions are important for marine forecasting,but the forecasting results are often unable to satisfy the requirements of operational wave forecasting.Because bias between the predictions of numerical models and the actual sea state has been observed,predictions can only be released after correction by forecasters.This paper proposes a spati-otemporal interactive processing bias correction method to correct numerical prediction fields applied to the production and release of operational ocean wave forecasting products.The proposed method combines the advantages of numerical models and Forecast Discussion;specifically,it integrates subjective and objective information to achieve interactive spatiotemporal correc-tions for numerical prediction.The method corrects the single-time numerical prediction field in space by spatial interpolation and sub-zone numerical analyses using numerical model grid data in combination with real-time observations and the artificial judg-ment of forecasters to achieve numerical prediction accuracy.The difference between the original numerical prediction field and the spatial correction field is interpolated to an adjacent time series by successive correction analysis,thereby achieving highly efficient correction for multi-time forecasting fields.In this paper,the significant wave height forecasts from the European Centre for Medium-Range Weather Forecasts are used as background field for forecasting correction and analysis.Results indicate that the proposed method has good application potential for the bias correction of numerical predictions under different sea states.The method takes into account spatial correlations for the numerical prediction field and the time series development of the numerical model to correct numerical predictions efficiently.

Study on short-range numerical forecasting of ocean current in the East China Sea——Ⅰ Basic problems of ocean current forecasting and structure of the models

Ocean current forecasting is still in explorative stage of study. In the study, we face some problems that have not been met before. The solving of these problems has become fundamental premise for realizing the ocean current forecasting. In the present paper are discussed in depth the physical essence for such basic problems as the predictability of ocean current, the predictable currents, the dynamical basis for studying respectively the tidal current and circulation, the necessity of boundary model, the models on regions with different scales and their link. The foundations and plans to solve the problems are demonstrated. Finally a set of operational numerical forecasting system for ocean current is proposed.

人工智能海浪预报的发展与挑战

海浪是海洋中最为重要的现象之一,快速准确的海浪预报对于保障海上生产、生活安全具有重要意义。该文回顾了海浪预报方法的发展历程,包括传统统计预报、数值模式预报以及目前快速发展的人工智能预报。基于人工智能的海浪预报模型表现出计算速度快、预报精度自适应优化等优势,已经开始从研究阶段逐步应用于实际海浪预报业务之中,但同时该方法也存在预报要素有限、极端海况预报值偏低以及预报泛化能力弱的局限。该文根据人工智能海浪预报的特点,提出了人工智能海浪预报目前亟需解决的观测数据高效利用、先验知识引入、人工智能模型安全性与泛化能力提升等关键科学技术问题。

美国海军全球业务预报系统进展

美国海军一直致力于开发更加精确的预报系统,其全球海洋环境预报系统近10年取得了长足的进步。全球大气预报系统更新为NAVGEM 2.0,分辨率得到进一步提升。海洋数据同化系统更新到改进型合成海洋剖面系统版本2,新增了同化海表面流场功能。全球海洋预报系统更新到3.5版本,提高了水平分辨率,新增了潮汐和引入新版本海冰模式。新开发了全球海气耦合预报系统,能够较好地预测大气海洋状况延伸期的变化。美国海军在业务预报系统方面的持续更新和提高,进一步保障其部队在海上的航行安全,为作战提供更好的海洋环境支持。

基于PredRNN++模型对南海中尺度涡旋的预测研究

基于26年的海表面高度异常、海表面风速异常、海表面温度异常资料,利用时空序列预测模型PredRNN++,本文预报1~28d时效的南海中尺度涡旋轨迹和南海西部偶极子活动。结果表明,PredRNN++模型能从整体上考虑整个南海区域时空演变特征和环境风场、温度场的作用,在短期(1~2周)、中期(3~4周)预报上具有良好的性能。该模型具备一定预报涡旋产生、消亡的能力,且能将涡旋轨迹4周预报误差控制在42.1km,对于生命时长小于100d的涡旋生命中期的位置、振幅预报误差小。此外模型在8—11月份的月平均、4天平均下的任意时间点和任意预报时效下均能较好地追踪到偶极子结构的演变、强度变化,偶极子涡旋相关属性预报误差最小且存在年际、类型差异,2017年涡旋1~4周振幅位置、预报、半径误差最小,分别为40~60km、3~5cm、20~40km,且气旋涡位置预报效果优于反气旋涡。

基于FIO-COM的复杂海洋环境下的声传播效应研究

海洋声学预报系统将海浪-潮流-环流耦合的海洋模型FIO-COM(Coupled Ocean Model)与水下声场传播模型协同连接。在此基础上,本文利用海表面高度异常数据识别和预测海洋中尺度结构的位置和演变,并生成相应的中尺度海洋环境下的声学参数,可用于分析各种包含海洋中尺度结构在内的复杂海洋环境下的声传播效应。利用该系统计算并分析了冲绳海槽、黑潮锋面和北太平洋冷涡等实际海洋环境下的声传播效应,研究结果表明:相对于水体声速场的结构变化,冲绳海槽地形对声传播的影响更为显著,海槽外侧的声源在穿越海槽传播时,大部分声能量陷落在海槽底部,很难到达海槽对面;不考虑地形的影响,黑潮锋表面较高的水温能够导致近海面水域声能量减弱,相对于距离无关水体环境,声传播损失增大约5~10 dB;北太平洋冷涡使得声能量提前汇聚,进而改变汇聚区的宽度、强度和位置。

胶州湾国家海洋公园沿岸地区土地利用预测研究

元胞自动机-马尔科夫耦合模型(CA-Markov模型)作为土地利用变化(LUCC)的一种研究手段,具有马尔科夫模型精确地模拟LUCC未来变化情况,同时还具有元胞自动机模型模拟复杂系统空间变化的能力。本研究运用CA-Markov模型,以分区预测为原则,对胶州湾国家海洋公园沿岸地区过去十年的土地利用构成及变化进行分析,同时对研究区未来三十年的土地利用变化进行中期预测和长期预测。结果表明:胶州湾国家海洋公园沿岸地区建设用地面积在过去十年增大,而在未来三十年将不断减小;模型的预测精度将随预测时长的增加而下降,需要根据其他因素对模拟结果进行一定程度的修正;未来土地利用方式的转变将为国家级海洋公园的生态保护和海洋生态文明建设起到积极推动作用。

基于GODAE Ocean View标准的全球海洋环流预报系统评估

基于USGODAE的现场漂流浮标观测数据,利用GODAE Ocean View框架下的IVTT Class4标准,评估了国家海洋环境预报中心业务化中等分辨率版本全球海洋环流预报系统的海表温度预报技巧。结果表明:该系统的海表温度预报均方根误差范围在0.65~0.73℃左右,在国际7个业务化系统中,预报精度处于中等水平。无论相对于延续性预报场或气候态预报场,其技巧评分皆为正值,说明该系统对海表温度的预报性能优于自身延续性预报和气候态场预报。

海洋大数据分析预报技术研发

为了使海洋大数据分析预报技术满足海洋深度开发和海洋保护的需求,文章对海洋大数据分析预报面临的问题展开分析,包括低质性问题、碎片化问题和隐匿性问题。结合问题研发海洋大数据挖掘与预测技术、表层海洋动力环境要素大数据分析技术、海洋动力环境要素三维结构大数据分析技术,让海洋大数据技术得到更好的发展,为海洋强国和生态文明建设提供有力支持。

Sensitivity of the Arctic sea ice concentration forecasts to different atmospheric forcing: a case study

A regional Arctic configuration of the Massachusetts Institute of Technology general circulation model （MIT-gcm） is used as the coupled ice-ocean model for forecasting sea ice conditions in the Arctic Ocean at the Na-tional Marine Environmental Forecasting Center of China （NMEFC）, and the numerical weather prediction from the National Center for Environmental Prediction Global Forecast System （NCEP GFS） is used as the atmospheric forcing. To improve the sea ice forecasting, a recently developed Polar Weather Research and Forecasting model （Polar WRF） model prediction is also tested as the atmospheric forcing. Their forecasting performances are evaluated with two different satellite-derived sea ice concentration products as initializa-tions： （1） the Special Sensor Microwave Imager/Sounder （SSMIS） and （2） the Advanced Microwave Scanning Radiometer for EOS （AMSR-E）. Three synoptic cases, which represent the typical atmospheric circulations over the Arctic Ocean in summer 2010, are selected to carry out the Arctic sea ice numerical forecasting experiments. The evaluations suggest that the forecasts of sea ice concentrations using the Polar WRF atmo-spheric forcing show some improvements as compared with that of the NCEP GFS.

Application of the nonlinear time series prediction method of genetic algorithm for forecasting surface wind of point station in the South China Sea with scatterometer observations

The present work reports the development of nonlinear time series prediction method of genetic algorithm（GA） with singular spectrum analysis（SSA） for forecasting the surface wind of a point station in the South China Sea（SCS） with scatterometer observations.Before the nonlinear technique GA is used for forecasting the time series of surface wind,the SSA is applied to reduce the noise.The surface wind speed and surface wind components from scatterometer observations at three locations in the SCS have been used to develop and test the technique.The predictions have been compared with persistence forecasts in terms of root mean square error.The predicted surface wind with GA and SSA made up to four days（longer for some point station） in advance have been found to be significantly superior to those made by persistence model.This method can serve as a cost-effective alternate prediction technique for forecasting surface wind of a point station in the SCS basin.

Application of the HY-1 satellite to sea ice monitoring and forecasting

The HY-1A satellite is the first oceanic satellite of China. During the winter of 2002-2003, the data of the HY-1A were applied to the sea ice monitoring and forecasting for the Bohai Sea of China for the first time. The sea ice retrieval system of the HY-1 A has been constructed. It receives 1B data from the satellite, outputs sea ice images and provides digital products of ice concentration, ice thickness and ice edge, which can be used as important information for sea ice monitoring and the initial fields of the numeric sea ice forecast and as one of the reference data for the sea ice forecasting verification. The sea ice retrieval system of the satellite is described, including its processes, methods and parameters. The retrieving results and their application to the sea ice monitoring and forecasting for the Bohai Sea are also discussed.