英国北海区域卫星遥感与船测海面温度场的比较

运用北海研究计划期间（１９８８年９月－１９８９年９月）所采集的海面温度数据与同一期间的ＮＯＡＡ卫星的ＡＶＨＲＲ遥感温度数据，检验由卢瑟福实验提出的ＲＡＬ线性模式反演的海面温度与船测海面温度之间的误差。检验结果表明，误差在０．９℃左右。由此得出结论，ＲＡＬ模式应用于北海这样的小尺度海域并不十分完善（因为这个模式是根据全球大气模式提出的）。因此，有必要利用小尺度海域当地的资料，建立相应的适合于具体海域     

动态水平-海面辐照度测量的新理念

目前海面辐照度的测量,在消除天空光影响的同时,却引入了仪器接收面倾斜的误差。作者经过多年的实践,提出动态水平的理念和一整套技术方法,解决了这一问题。动态水平技术的应用,需应用最新技术的发展,而且必然引起海洋光学测量仪器、特别是海洋光学浮标的一系列变革,对海洋水色遥感具有重要的意义和影响。     

基于MISR多角度光学遥感影像的海面风速估算实验

太阳耀光是来自粗糙海面的直接太阳反射光,其强度与海面粗糙度密切相关,而海面粗糙度主要受海面风场影响。因此,包含太阳耀光信息的光学遥感影像在海洋动力过程和海面风速探测中具有积极意义。本文利用2016年2月到2017年3月期间成像的25幅Terra卫星MISR(Multi-angle Imaging Spectro Radiometer)传感器的多角度遥感影像,分别提取了太阳的高度角和方位角、正视和后视影像的卫星观测角、方位角等信息,校正获得正视和后视影像的太阳耀光辐射强度,进一步反演海表面粗糙度信息,进而计算海面风速。最后利用ECMWF(European Centre for Medium-Range Weather Forecasts)的模式风速数据与反演获得的风速结果进行对比验证。结果表明,两者的相关系数较高(R=0.745),均方根误差和平均绝对偏差值分别为1.514 m·s^-1和1.319 m·s^-1。初步实验结果表明,利用MISR多角度光学遥感影像估算海表面风速是可行性的。     

两种卫星遥感海面温度数据的处理技术

论文首先通过从网上获取AVHRR的2001年海面温度月平均数据和WOA01的海面温度季度平均数据资料,然后利用fortran程序读取数据和初步处理数据,并利用matlab软件和surfer作图工具绘制了两组不同数据的等值线图,最后对图像进行了分析,对比两组海面温度分布图。     

利用卫星高度计风速资料研究海面粗糙度

海面粗糙度对于海洋工程和海洋军事都非常重要，但对海面粗糙度的现场观测资料非常少，这大大制约了我们对海面粗糙度的认识。本文利用TOPEX高度计风速资料，实现了对海面粗糙度的反演。利用1993年和1998年两年的资料，文中对西北太平洋海域的海面粗糙度进行了研究。     

利用卫星观测海面信息反演三维温度场

基于历史观测的温盐剖面资料,采用回归分析方法统计出海面温度异常、海面动力高度异常与温度剖面异常之间的相关关系;然后利用高分辨率的卫星遥感海表面温度(SST)和卫星观测海面高度(SSH)信息重构了三维海洋温度场。在台湾岛周边海域建立了时间分辨率为天、空间分辨率为0.25°×0.25°的三维温度分析场。通过与实测资料的比较分析,文章所构建的分析场能够较好地描述海洋三维温度场的结构特征,能够较为真实地反映海洋的中尺度变化过程。该分析场可以作为海洋数值模式的初始场,也可以作为伪观测同化到海洋数值再分析和预报系统中,进而改善三维温、盐、流的数值再分析和预报。     

海面盐度卫星遥感的大气影响仿真

海面盐度是描述海洋的重要参量之一,基于星载微波辐射计的海面盐度探测也是海洋遥感研究的重要内容.在影响盐度遥感的误差中,大气是重要的影响因素.在辐射传输理论的基础上,仿真计算了大气透射率和上、下行辐射随地面大气温度、压强和辐射计入射角的变化关系,进而得到大气对接收辐射亮温的影响.仿真结果表明,大气对盐度遥感的影响很大,但当地面大气温度和压强精度分别达到2℃和1000 Pa时,可以消除大气的影响.     

台湾海峡及其邻近海域海面温度锋的卫星遥感观测

使用1989~2001年的NOAA AVHRR图像,研究了我国台湾海峡及其邻近海域的海面温度锋.卫星遥感观测表明,该海域海面温度锋终年存在,锋面沿50~100 m等深线分布,西段呈西南西-东北东走向,东段以舌状向北突出,长约470 km.给出了该海域海面温度锋的多年月平均、季平均和年平均特征值.统计结果显示,锋的平均强度、平均最大强度和平均宽度分别为0.147,0.281℃/km和15.15 km.锋的各种特征存在明显的季节和年际变化.锋的不稳定性普遍存在,沿锋面常形成半环状的锋波,使锋面呈半环状波动分布.锋波形成的时间尺度约为1~7 d,锋的波长约为35~133 km,年平均波长为63 km,波幅为25~70 km.锋面的波动向北东北方向传播,并存在锋面整体向北东北的平移现象.     

利用卫星高度计风速资料研究海面粗糙度

海面粗糙度对于海洋工程和海洋军事都非常重要,但对海面粗糙度的现场观测资料非常少, 这大大制约了对海面粗糙度的认识。利用 TOPEX 高度计风速资料实现了对海面粗糙度的反演,并利用 1993 年和1998 年两年的资料对西北太平洋海域的海面粗糙度进行了研究。     

利用多年卫星资料分析青岛和茂名附近海域海面风场变化

文章围绕青岛海洋经济开发和茂名海洋气象基础科学综合试验对附近海域基础环境数据的需求,利用多年卫星资料开展了青岛和茂名附近海域海面风场统计分析研究。结果表明:青岛附近海域风向频率和风速频率最大的方向均为北,相对应的平均风速值为3.5m/s;茂名附近海域风向频率最大方向为ENE,风速频率最大方向为NNE,茂名附近海域平均风速值全年均大于青岛附近海域平均风速值,研究成果可为开展海洋气象业务观测和科学试验提供基础数据支持,为"一带一路"海上风能资源开发与利用提供决策支撑。     

Characteristics of Sea Surface Circulation and Eddy Field in the South China Sea Revealed by Satellite Altimetric Data

Temporal and spatial variations of sea surface circulation in the South China Sea were revealed with use of altimetric data provided by TOPEX/POSEIDON from December 1992 to October 1997. The estimated distribution of sea surface dynamic heights from altimetric data coincide well with the results of observation by Soong et al. (1995) and Chu et al. (1998). The RMS variability of sea surface dynamic height, which is obtained after tidal correction based on Yanagi et al. (1997), is high in the central part of the South China Sea, the Gulf of Tongking, the Sunda Shelf and the Gulf of Thailand. The high RMS variability in the Gulf of Tongking, the Sunda Shelf and the Gulf of Thailand is due to set up and set down of sea water by the East Asian monsoon, which is northeasterly during winter and southwesterly during summer. Also, the high RMS variability in the central part of the South China Sea is due to the variations of basin-wide circulation. The circulations are dominant in the central part of the South China Sea during summer and winter, an anticyclonic circulation during summer and a cyclonic circulation during winter. It is suggested that these circulations are controlled by the East Asian monsoon. Hence, there is an interannual variability of the basin-wide circulation associated with the variation of the East Asian monsoon.     

利用卫星资料分析黄海海表温度的年际与年代际变化

海表温度长期变化在一定程度上反映了海域的气候变化信号,卫星遥感资料是获取高时空分辨率水温长期变化的有效手段。基于国家海洋局1982—1999年黄海断面监测器测数据的2 954组水温数据对时空匹配的卫星(NOAA/AVHRR)反演海表温度(SST)进行校验,计算得到卫星反演SST系统偏差为(0.18±1.00)℃。卫星反演的水温空间分布以及长期变化趋势与器测趋势较为一致,可以用来研究海域SST长期变化规律。利用校验后1982-01～2011-08NOAA/AVHRR的SST数据,分析了该时段黄海冬夏季代表月2、8月海表水温的变化规律。结果显示:(1)近30a,黄海冬季水温有2次跃迁:1989—1990年由冷至暖的状态跃迁,2000-2001年出现由暖至冷的状态转变;1990年代冬季水温达最高,相比1880年代,水温升高1.07℃,新世纪水温稍有降低,水温较1990年代下降了0.53℃,温度变化较大区域位于北黄海、山东半岛沿岸,苏北浅滩毗邻海区,该区SST与局地经向风场存在显著正相关,且北极涛动通过影响冬季风间接影响黄海水温变化;(2)夏季海表水温在1994—1995年呈现由冷至暖的状态跃迁,冷、暖期水温相差0.57℃,水温变化较显著的区域为黄东海分界处,其具体变化机制需深入研究。     

Variability of Sea Surface Circulation in the Japan Sea

Composite sea surface dynamic heights (CSSDH) are calculated from both sea surface dynamic heights that are derived from altimetric data of ERS-2 and mean sea surface that is calculated by a numerical model. The CSSDH are consistent with sea surface temperature obtained by satellite and observed water temperature. Assuming the geostrophic balance, sea surface current velocities are calculated. It is found that temporal and spatial variations of sea surface circulation are considerably strong. In order to examine the characteristics of temporal and spatial variation of current pattern, EOF analysis is carried out with use of the CSSDH for 3.5 years. The spatial and temporal variations of mode 1 indicate the strength or weakness of sea surface circulation over the entire Japan Sea associated with seasonal variation of volume transport through the Tsushima Strait. The spatial and temporal variations of mode 2 mostly indicate the temporal variation of the second branch of the Tsushima Warm Current and the East Korean Warm Current. It is suggested that this variation is possibly associated with the seasonal variation of volume transport through the west channel of the Tsushima Strait. Variations of mode 3 indicate the interannual variability in the Yamato Basin.     

Evaluation of the Diurnal Warming of Sea Surface Temperature Using Satellite-Derived Marine Meteorological Data

In order to produce a high-quality sea surface temperature (SST) data set, the daily amplitude of SST (ΔSST) should be accurately known. The purpose of this study was to evaluate the diurnal variation of sea surface temperature in a simple manner. The authors first simulated ΔSST with a one-dimensional numerical model using buoy-observed meteorological data and satellite-derived solar radiation data. When insolation is strong, the model-simulated 1-m-depth ΔSST becomes much smaller than the in situ value as wind speed decreases. By forcibly mixing the sea surface layer, the model ΔSST becomes closer to the in situ value. It can be considered that part of this difference is due to the turbulence induced by the buoy hull. Then, on the assumption that the model results were reliable, the authors derived a regression equation to evaluate ΔSST at the skin and 1-m depth from daily mean wind speed (U) and daily peak solar radiation (PS). ΔSST is approximately proportional to In(U) and (PS)², and the skin ΔSST estimated by the equation is not inconsistent with in situ observation results reported in past studies. The authors prepared maps of PS and U using only satellite data, and demonstrated the ΔSST evaluation over a wide area. The result showed that some wide patchy areas where the skin ΔSST exceeds 3.0 K can appear in the tropics and the mid-latitudes in summer. This revised version was published online in July 2006 with corrections to the Cover Date.     

Validation of Daily Amplitude of Sea Surface Temperature Evaluated with a Parametric Model Using Satellite Data

The authors have verified a regression model for the evaluation of the daily amplitude of sea surface temperature (ΔSST) proposed by Kawai and Kawamura (2002). The authors investigated the accuracy of satellite data used for the evaluation and showed that ΔSST error caused by satellite data error is less than ±0.7 K. The evaluated ΔSSTs were compared with in situ values. Its root-mean-square error is about 0.3 K or less, except for a coastal region, and it has a bias of more than +0.1 K in the tropics. This bias can be removed by considering latent heat flux. This revised version was published online in July 2006 with corrections to the Cover Date.     

Spatial and Temporal Scale Variations of Sea Surface Temperature in the East Sea Using NOAA/AVHRR Data

Sea surface temperature fields in the East Sea are composed of various spatial structures such as eddies, fronts, filaments, turbulent-like features and other mesoscale variations associated with the oceanic circulations of the East Sea. These complex SST structures have many spatial scales and evole with time. Semi-monthly averaged SST distributions based on extensive satellite observations of SSTs from 1990 through 1995 were constructed to examine the characteristics of their spatial and temporal scale variations by using statistical methods of multi-dimensional autocorrelation functions and spectral analysis. Two-dimensional autocorrelation functions in the central part of the East Sea revealed that most of the spatial SST structures are anisotropic in the shape of ellipsoids with minor axes of about 90–290 km and major axes of 100–400 km. Two dimensional spatial scale analysis demonstrated a consistent pattern of seasonal variation that the scales appear small in winter and spring, increase gradually to summer, and then decrease again until the spring of the next year. These structures also show great spatial inhomogeneity and rapid temporal change on time scales as short as a semi-month in some cases. The slopes in spectral energy density spectra of SSTs show characteristics quite similar to horizontal and geostrophic turbulence. Temporal spectra at each latitude are demonstrated by predominant peaks of one and two cycles per year in all regions of the East Sea, implying that SSTs present very strong annual and semi-annual variations. This revised version was published online in August 2006 with corrections to the Cover Date.     

基于SODA数据集的南海海表面盐度分布特征与长期变化趋势分析

盐度是南海物理环境的重要组成部分之一,盐度的变化对南海的水动力环境有重要影响。利用1972-2010年的SODA数据集的5.01 m层月平均数据,分析南海海域海表面盐度的时空分布特征,采用基于最小二乘法的线性拟合分析南海海表面盐度的长期变化趋势。结果表明南海海域的海表面盐度在39 a间90%以上区域均呈现盐度下降趋势,整个海域SSS则以每年0.005 88 psu的速率下降,春季SSS下降速率最大为0.006 4 psu/a,夏季SSS下降速率在四季中最小为0.005 19 psu/a。     

HY-1卫星海温反演的误差分析

分别利用GTS船舶报海温数据和NOAA卫星海温数据分析了HY-1卫星海温反演误差。结果显示,对于GTS海温数据,RMS为1.26℃;对于NOAA卫星海温数据,RMS为0.94℃。影响HY-1卫星海温反演精度的主要因素为大气中的水汽吸收和云覆盖。另外,对HY-1卫星海温反演中的大气校正和云检测技术的改进进行了探讨。