Wave steepness retrieved from scatterometer data in a genetic algorithm

Wave steepness is an important characteristic of a high sea state, and is widely applied on wave propagations at ports, ships, offshore platforms, and CO2 circulation in the ocean. Obtaining wave steepness is a difficult task that depends heavily on theoretical research on wavelength distribution and direct observations. Development of remote-sensing techniques provides new opportunities to study wave steepness. At present, two formulas are proposed to estimate wave steepness from QuikSCAT and ERS-1/2 scatterometer data. We found that wave steepness retrieving is not affected by radar band, and polarization method, and that relationship of wave steepness with radar backscattering cross section is similar to that with wind. Therefore, we adopted and modified a genetic algorithm for relating wave steepness with radar backscattering cross section. Results show that the root-mean-square error of the wave steepness retrieved is 0.005 in two cases from ERS-1/2 scatterometer data and from QuikSCAT scatterometer data.     

Comprehensive Marine Observing Experiment Based on High-Altitude Large Unmanned Aerial Vehicle(South China Sea Experiment2020 of the “Petrel Project”)

In collaboration with 12 other institutions, the Meteorological Observation Center of the China Meteorological Administration undertook a comprehensive marine observation experiment in the South China Sea using the Yilong-10 high-altitude large unmanned aerial vehicle(UAV). The Yilong-10 UAV carried a self-developed dropsonde system and a millimeter-wave cloud radar system. In addition, a solar-powered unmanned surface vessel and two drifting buoys were used. The experiment was further supported by an intelligent, reciprocating horizontal drifting radiosonde system that was deployed from the Sansha Meteorological Observing Station, with the intent of producing a stereoscopic observation over the South China Sea. Comprehensive three-dimensional observations were collected using the system from 31 July to2 August, 2020. This information was used to investigate the formation and development processes of Typhoon Sinlaku(2020). The data contain measurements of 21 oceanic and meteorological parameters acquired by the five devices, along with video footage from the UAV. The data proved very helpful in determining the actual location and intensity of Typhoon Sinlaku(2020). The experiment demonstrates the feasibility of using a high-altitude, large UAV to fill in the gaps between operational meteorological observations of marine areas and typhoons near China, and marks a milestone for the use of such data for analyzing the structure and impact of a typhoon in the South China Sea. It also demonstrates the potential for establishing operational UAV meteorological observing systems in the future, and the assimilation of such data into numerical weather prediction models.     

Effects of Drag Coefficients on Surface Heat Flux during Typhoon Kalmaegi (2014)

The lack of in situ observations and the uncertainties of the drag coefficient at high wind speeds result in limited understanding of heat flux through the air-sea interface and thus inaccurate estimation of typhoon intensity in numerical models. In this study, buoy observations and numerical simulations from an air-sea coupled model are used to assess the surface heat flux changes and impacts of the drag coefficient parameterization schemes on its simulations during the passage of Typhoon Kalmaegi (2014). Three drag coefficient schemes, which make the drag coefficient increase, level off, and decrease, respectively, are considered. The air-sea coupled model captured both trajectory and intensity changes better than the atmosphere-only model, though with relatively weaker sea surface cooling (SSC) compared to that captured by buoy observations, which led to relatively higher heat flux and thus a stronger typhoon. Different from previous studies, for a moderate typhoon, the coupled simulation with the increasing drag coefficient scheme outputted an intensity most consistent with the observation because of the strongest SSC, reasonable ratio of latent and sensible heat exchange coefficients, and an obvious reduction in the overestimated surface heat flux among all experiments. Results from sensitivity experiments showed that surface heat flux was significantly determined by the drag coefficient-induced SSC rather than the resulting wind speed changes. Only when SSC differs indistinctively (<0.4°C) between the coupled simulations, heat flux showed a weak positive correlation with the drag coefficient-impacted 10-m wind speed. The drag coefficient also played an important role in decreasing heat flux even a long time after the passage of Kalmaegi because of the continuous upwelling from deeper ocean layers driven by the impacted momentum flux through the air-sea interface.     

2006年夏季福建近海台风风暴潮特征分析

根据2006年夏季福建沿岸4个海洋观测站和福建近海5个潜标水位观测站的水位观测资料,分析了在4个热带气旋影响下的福建近海风暴潮特征．结果表明：福建沿岸海域的台风风暴潮大小不完全取决于台风强弱,与大风半径关系密切．若台风大风区覆盖整个台湾海峡,福建沿岸海域增水都较大,比如0604号强热带风暴“碧利斯”的大风区较大,由其引起厦门海洋观测站的最大增水高度达114em．0608号超强台风“桑美”和0609号强热带风暴“宝霞”双台风的大风区都比较小,由其引起的各测站增水相对也较小,增水高度最大的厦门海洋观测站只有52em．比较福建近海潜标水位观测站及其附近的海洋观测站采用11点（11h）滑动平均后的最大增水可知,福建近海潜标观测站台风增水高度（22～46cm）比沿岸海洋观测站的台风增水高度（62—73em）小40％左右．这表明台风增水有个向岸堆积的过程,即测站离岸越远,台风增水高度就越小．位于热带气旋（0605号台风“格关”）行进路径右侧的测站增水较大（平潭海洋观测站极值增水高度为49em,崇武海洋观测站极值增水高度为55em）,位于热带风暴行进路径左侧的测站增水较小（东山海洋观测站极值增水高度为45cm）．通过对0604号强热带风暴“碧利斯”引起的各测站增水滤除高频振荡后,福建沿岸海洋观测站最大增水高度从大到小依次为崇武站（74orfl）、平潭站（73em）、厦门站（68om）、东山站（62cm）,可见距离热带风暴中心越近（距离热带风暴中心从近到远依次为平潭、崇武、厦门、东山海洋观测站）,增水高度越大,反之,增水高度越小．台湾海峡地形和福建沿岸海域地形容易出现双（多）增水峰现象．通过对各测站台风增水时间序列进行最大熵谱分析可知,热带气旋容易引起福建沿岸和近海各测站台风增水出现周期为12．0h的振荡．     

Application of HF radar currents to oil spill modelling

In this work, the benefits of high-frequency (HF) radar currents for oil spill modeling and trajectory analysis of floating objects are analyzed. The HF radar performance is evaluated by means of comparison between a drifter buoy trajectory and the one simulated using a Lagrangian trajectory model. A methodology to optimize the transport model performance and to calculate the search area of the predicted positions is proposed. This method is applied to data collected during the Galicia HF Radar Experience. This experiment was carried out to explore the capabilities of this technology for operational monitoring along the Spanish coast. Two long-range HF radar stations were installed and operated between November 2005 and February 2006 on the Galician coast. In addition, a drifter buoy was released inside the coverage area of the radar. The HF radar currents, as well as numerical wind data were used to simulate the buoy trajectory using the TESEO oil spill transport model. In order to evaluate the contribution of HF radar currents to trajectory analysis, two simulation alternatives were carried out. In the first one, wind data were used to simulate the motion of the buoy. In the second alternative, surface currents from the HF radar were also taken into account. For each alternative, the model was calibrated by means of the global optimization algorithm SCEM-UA (Shuffled Complex Evolution Metropolis) in order to obtain the probability density function of the model parameters. The buoy trajectory was computed for 24 h intervals using a Monte Carlo approach based on the results provided in the calibration process. A bivariate kernel estimator was applied to determine the 95% confidence areas. The analysis performed showed that simulated trajectories integrating HF radar currents are more accurate than those obtained considering only wind numerical data. After a 24 h period, the error in the final simulated position improves using HF radar currents. Averaging the information from all the simulated daily periods, the mean search and rescue area calculated using HF radar currents, is reduced by approximately a 62% in comparison with the search area calculated without these data. These results show the positive contribution of HF radar currents for trajectory analysis, and demonstrate that these data combined with atmospheric forecast models, are of value for trajectory analysis of oil spills or floating objects.     

两种ASCAT 散射计风产品的比较及评估

基于浮标和步进频率微波辐射计(SFMR,Stepped-Frequency Microwave Radiometer)数据对NASA JPL(Jet Propulsion Laboratory)和RSS(Remote Sensing Systems)公司分别发布的已广泛应用于全球海面风场观测的ASCAT(Advanced SCATterometer)散射计风产品进行了比较和分析。结果表明,两者风速在中低风速(15 m/s)时基本一致;高风速(15 m/s)时RSS风速整体高于JPL风速。通过浮标数据对比,风速15 m/s时两者风速精度一致;风速15 m/s时两者风速RMS相当,但JPL和RSS风速分别低估和高估。利用SFMR数据检验表明RSS风速与SFMR风速一致性更好。两者风向精度在低风速(5 m/s)时较低,但随风速增加而提高并趋于稳定。该研究结果对相关科研人员的ASCAT散射计风产品选择具有重要的指导意义。     

自动校准技术在温盐传感器的应用

本文介绍了自动校准的温度和盐度测量技术，该技术应用在海洋863项目中水质监测浮标的温盐传感器中，自动校准技术可使传器稳定性，准确芳得到很大提高，对应用到海洋领域进行长期观测的传感器具有重要意义。     

湛江港浮标污损生物生态研究

１９９１年在湛江港进行浮标污损生物调查。该海区污损生物的种类组成共９３种，附着厚度２１—７１ｍｍ，湿重３．１０—７２．５３ｋｇ／ｍ２，覆盖面积９８％─１００％。优势种为网纹藤壶Ｂａｌａｎｕｓｒｅｔｉｃｕｌａｔｕｓ、变化短齿蛤Ｂｒａｃｈｉｄｏｎｔｅｓｖａｒｉａｂｉｌｉｓ、刺巨藤壶Ｍｅｇａｂａｌａｎｕｓｖｏｌｃａｎｏ、钟巨藤壶Ｍｅｇａｂａｌａｎｕｓｌｉｎｔｉｎｎａｂｕｌｕｍｔｉｎｔｉｎｎａｂｕｌｕｍ和翡翠贻贝Ｐｅｒｎａｖｉｒｉｄｉｓ。位于不同位置的浮标，其污损生物群落组成和生物量不同，同一浮标的不同部位（体侧，底部，尾外侧，尾管内）的污损生物也有一定差别。     

赤潮监测和预报的构想

在对赤潮监测要素和方法进行分析的基础上，构思了几各监测和预报赤潮的方式，并建议以水质浮标和剖面监测系统为主要方式开展研制工作。     

极地漂流浮标技术的最新进展

阐述了 J- CAD型漂流浮标的结构、特点 ,各类传感器的性能、电子设备的功能及使用情况。它结构紧凑、价格便宜、功能强大 ,是 2 1世纪初开发的世界上第一个用于观测冰下海洋水文要素的漂流浮标。