西太平洋海域卫星测高重力异常反演与精度评估

联合T/P、ERS1/GM、ERS1/ERM、ERS2/ERM、GEOSAT/ERM、GEOSAT/GM等多源卫星测高数据,基于逆Vening-Meinesz公式和EGM2008模型,采用移去-恢复方法和快速傅里叶变换算法构建了中国西太平洋海域(0°~40°N,105°E~145°E)1'×1'重力异常模型,选取两个不同特征区域航线,将构建的重力异常模型、EGM2008重力异常模型、美国Scripps海洋研究所重力异常与船测重力数据进行比较分析。结果表明,构建的重力异常模型与船测重力总体趋势变化较为一致、与船测重力比较均方根差为4.16m Gal,总体精度与EGM2008模型重力异常、美国Scripps海洋研究所重力异常相当,反演精度和分辨率达到国际领先水平。     

利用多代卫星测高数据计算中国近海及邻域重力异常

为提高海洋重力场数据的精度和空间分辨率,联合Jason-1/2、T/P、Envisat、ERS-1/2、Geosat等多代卫星测高数据计算中国近海及邻域(0°~42°N,100°~140°E)2′×2′重力异常。对卫星测高数据分别进行共线处理和自交叉点平差,并以T/P卫星测高数据为基准进行多星数据联合平差,有效削弱了卫星测高数据的时变影响和不协调性;利用逆Vening-Meinesz公式计算重力异常,与船测重力相比,均方根误差为5.4 mgal。结果表明,通过引入高精度的卫星测高数据,结合多项平差处理手段,提高了海洋重力异常的计算精度。     

利用卫星测高资料确定全球海洋重力场

详细描述了卫星测高数据的平滑处理、高斯低通滤波、交叉点剩余垂线偏差计算、网格化方法以及根据逆的威宁·曼尼兹公式利用 1DFFT技术反演海域重力异常的解算过程 ,介绍一种确定正常轨道地面轨迹交叉点位置的简便方法 ,导出了海面地形对垂线偏差影响的改正公式以及剩余网格垂线偏差模型值的计算公式。所确定的全球 82°S～ 82°N ,0°～ 36 0°海域 30′× 30′网格平均重力异常与船测平均重力异常比较表明 ,精度达到± 4 .1～± 4 .7毫伽。     

利用多代卫星测高数据计算海洋重力场

联合Jason-1/2、T/P、Envisat、ERS-1/2、Geosat等多代卫星测高数据计算中国近海及邻域（0°~42°N,100°~140°E）2′×2′重力异常。对卫星测高数据分别进行共线处理和自交叉点平差,并以T/P卫星测高数据为基准进行多星数据联合平差,有效削弱了卫星测高数据的时变影响和不协调性;利用逆Vening-Meinesz公式计算重力异常,与船测重力相比,均方根误差为5.4mGal。结果表明,通过引入高精度的卫星测高数据,结合多项平差处理手段,提高了海洋重力异常的计算精度。     

联合多代卫星测高数据建立中国近海垂线偏差模型

联合T/P数据、T/P新轨道数据、ERS2数据、GFO数据、Geosat GM数据和ERS-1/168数据,用测高卫星记录点的位置信息直接计算沿轨大地水准面的方向导数,在交叉点处联合方位角推求垂线偏差,然后利用Shepard插值法得到了中国近海2′×2′格网分辨率子午圈和卯酉圈垂线偏差模型。将其与2′×2′分辨率的CLS_SHOW 99垂线偏差模型比较,在子午圈分量上的RMS为0.87,″在卯酉圈分量上的RMS为1.45″。     

垂线偏差反演重力异常中央区效应计算模型

为提高卫星测高反演重力场中央区效应的计算精度,以逆Vening-Meinesz公式为例,推导了包含4个网格的矩形中央区效应计算模型;基于"非奇异变换"思想,推导了中央区垂线偏差展开为泰勒级数式和二次多项式的非奇异变换法计算模型一和模型二。结果表明:矩形中央区积分法得到了与非奇异变换法模型一完全相同的中央区效应计算模型。设计了基于EGM2008模型数据的仿真计算,计算结果表明:该公式计算的重力异常中央区效应与将中央区视为圆域的传统方法算得的结果差值最大能够达到数个毫伽;与形式更为复杂的非奇异变换法算得的结果基本一致,说明在中央区效应计算中,使用矩形域中央区模型更为合理。     

联合多卫星测高数据确定中国近海及其邻域垂线偏差

联合T/P数据、T/P新轨道数据、Jason-1数据、Jason-1新轨道数据、Jason-2数据、Geosat/GM数据、Geosat/ERM数据、Envisat RA-2数据、ERS-1/ERM和ERS-2/ERM数据,基于EGM2008重力场模型,用相邻测高点大地水准面高度的一次差分求沿轨垂线偏差,然后基于最小二乘原理,采用求最小范数逆的方法,直接解算中国近海及其邻域(0°～42°N,102°～138°E)2′×2′分辨率网格点垂线偏差子午分量和卯酉分量。计算结果与EGM2008模型垂线偏差相比,子午分量的RMS为0.91″,卯酉分量的RMS为0.27″。     

GM测高数据反演中国近海及邻域精细重力场

综合对比4种波形重跟踪算法,选择改进阈值法处理Jason-1GM数据,联合波形重跟踪后的Geosat和ERS-1GM数据,沿轨2Hz重采样以提高数据空间分辨率。通过数据质量控制剔除粗差数据,考虑海表面地形的影响,基于移去-恢复法和维宁-曼齐兹公式反演了中国近海及邻近海域(0°~45°N,100°~140°E)1′×1′的精细重力场。船测数据检核表明反演结果在开阔海域精度约4mGal,近岸浅水区约10mGal,均优于DTU10和V21.1模型。     

利用卫星测高垂线偏差计算其他重力场元的特性分析

利用卫星测高技术确定海洋重力场,垂线偏差数据作为导出观测量在实际工作中被普遍采用。利用物理大地测量边值问题的定义以及扰动位在球面边界条件下的解,给出了由垂线偏差计算大地水准面高、重力异常和扰动重力的公式。分析了不同积分计算公式在重力场阶谱表达形式下对垂线偏差误差的抑制作用,也分析了不同积分核函数的变化特性,得出基本结论:在利用卫星测高数据求解海洋重力场时,当以格网化海面垂线偏差数据计算重力场参数时,求解的大地水准面高的有效性和稳定性优于重力异常和扰动重力。     

用T/P测高数据反求海域重力异常

本文以反Stokes公式为数学模型,应用由T/P测高数据计算的大地水准面高反演了海洋平均重力异常,并与船测平均重力异常和OSU91A位模型计算的平均重力异常进行了比以分析,得出了一些有益的结论。     

南海海底地形的卫星测高数据反演

深入讨论了重力异常与海深的关系 ,在考虑地壳均衡补偿效应影响的基础上 ,推导了由重力异常用FFT技术计算海深的模型。最后 ,利用推导的模型联合测高卫星数据和海洋重力资料反演了中国南海 2 5′× 2 5′海底地形     

卫星和模式数据分析的南海中尺度涡的统计特征

为了进一步了解南海中尺度涡的统计特征,利用OFES数据资料和最新的AVISO卫星资料,采用速度矢量涡旋识别方法和空间距离搜索法,对南海中尺度涡的特征加以统计分析。结果表明,南海海域是中尺度涡的多发区,尤其是在南海北部靠近吕宋海峡的区域存在较多的中尺度涡,这些中尺度涡的运动方向都是自东向西;同时在南海的西边界流区也存在较多的中尺度涡,它们的运动轨迹则是与局地的表层流的方向有很大的关系,有很多是自南向北运动。同时西北太平洋的西边界流处也有大量的Rossby波以中尺度涡的形式传来。     

On the Influence of Sea Surface Height Variability on Satellite Altimeter Derived Gravity

The effect of sea surface height (SSH) variability is one of the primary factors that limit the accuracy and resolution of altimeter-derived gravity values. We propose a method to estimate the influence of variation of the sea surface height on the accuracy of satellite-derived gravity by simulation technique, with a case study around Indonesian waters. Wederived an Indonesian marine gravity map using the Geosat-geodetic mission (GM). Since most of the area studied is located around coastal and shallow areas, the measurement of SSH of this area is less accurate. To obtain a distribution of SSH variability over the study area, Topex/Poseidon (T/P) data were first processed and assessed. Processing 52 cycles of the Topex/Poseidon data, the root mean square (RMS) of SSH variability for each cycle was found to vary from 1 to 179 cm. Further, for the purpose of estimating the accuracy of altimeter-derived gravity, we derived several levels of Gaussian noise, computed simulation data by adding the Gaussian noise to Geosat data, and determined simulated gravity maps. Based on the distribution of RMS values from T/P data and standard deviation (STD) differences between the simulated and the original gravity maps, we estimated the accuracy of the gravity map. Around Indonesian waters, the accuracy of the gravity map influenced by SSH variation was estimated to be within the range 0.8~93 mgal.     

On the Influence of Sea Surface Height Variability on Satellite Altimeter Derived Gravity

The effect of sea surface height (SSH) variability is one of the primary factors that limit the accuracy and resolution of altimeter-derived gravity values. We propose a method to estimate the influence of variation of the sea surface height on the accuracy of satellite-derived gravity by simulation technique, with a case study around Indonesian waters. Wederived an Indonesian marine gravity map using the Geosat-geodetic mission (GM). Since most of the area studied is located around coastal and shallow areas, the measurement of SSH of this area is less accurate. To obtain a distribution of SSH variability over the study area, Topex/Poseidon (T/P) data were first processed and assessed. Processing 52 cycles of the Topex/Poseidon data, the root mean square (RMS) of SSH variability for each cycle was found to vary from 1 to 179 cm. Further, for the purpose of estimating the accuracy of altimeter-derived gravity, we derived several levels of Gaussian noise, computed simulation data by adding the Gaussian noise to Geosat data, and determined simulated gravity maps. Based on the distribution of RMS values from T/P data and standard deviation (STD) differences between the simulated and the original gravity maps, we estimated the accuracy of the gravity map. Around Indonesian waters, the accuracy of the gravity map influenced by SSH variation was estimated to be within the range 0.8~93 mgal.     

利用卫星高度计资料进行多年一遇极值波高推算的方法研究

根据卫星高度计资料的特点 ,在对 3个海洋站的海浪极值推算中引用发展了尾部分布增强法 (Tail Distribution Method) ,并且与 3个海洋站实测资料推算结果相比较 ,结果良好。以此为基础对西北太平洋进行多年一遇极值推算 ,其多年一遇的极值分布与风场的分布是一致的 ,主要呈纬向带状分布特征 :从 35°N～ 55°N,1 4 5°E～ 1 80°E的长方形海域 ,长时间受到季风的作用并且海域开阔 ,所以它的百年一遇波高可以达到 1 3m以上 ;而在赤道无风带控制下的海域 ,它的百年一遇波高一般为 7m左右。     

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.     

南海上层海洋温度垂向结构的反演

南海上层海洋温度垂向结构对海洋气候研究及海洋防灾减灾具有重要意义,然而由于现场观测数据有限,很难获取高时空分辨率的网格化数据。基于2007–2021年的Argo剖面数据、海面高度异常数据和月平均气候态数据,评估了两层动力模型和多层回归模型在南海海区反演海洋温度结构的性能。两层动力模型反演得到的26℃（D26）与20℃（D20）等温线深度的均方根误差分别13.25 m和21.12 m,多层回归模型的D26、D20均方根误差分别11.55 m和14.32 m。通过对比2种模型的结果：多层回归模型在时间与空间上反演结果性能更佳。2种模型反演的南海上层海洋热含量空间分布较为一致,均能应用于台风“威马逊”的强度评估;然而,在南海特殊的强内潮的背景下,2种模型得到的D20性能都有所降低。     

多类资料计算南海重力垂直梯度的方法比较

重力垂直梯度在解决和解释地球表层地质和地球物理问题中的作用日益明显,因而获得其模型和分布是非常必要的。利用测高卫星可以得到空间大范围高精度、高分辨率的垂线偏差、重力异常以及大地水准面数据,利用测高重力资料和地球重力场模型,采用不同方法分别计算了南海海域重力垂直梯度,并对它们进行了比较。     

Assimilation of TOPEX/POSEIDON Altimeter Data with a Reduced Gravity Model of the Japan Sea

Sea level data measured by TOPEX/POSEIDON over the Japan Sea from 1993 to 1994 is analyzed by assimilation using an approximate Kalman filter with a 1.5 layer (reduced-gravity) shallow water model. The study aims to extract signals associated with the first baroclinic mode and to determine the extent of its significance. The assimilation dramatically improves the model south of the Polar Front where as much as 20 cm² of the observed sea level variance can be accounted for. In comparison, little variability in the northern cold water region is found consistent with the model dynamics, possibly due to significant differences in stratification.