利用多年卫星测高资料研究南海上层环流季节特征

利用10年高精度卫星测高海面高异常网格资料,联合EGM96稳态海面地形模型,构成南海海域合成海面地形的时间序列,并计算了各个时期的南海表层地转流场. 利用卫星跟踪漂流浮标观测结果与相应时期南海地转流场进行对比验证,结果显示本文结果可以很好地反映南海海域一些中小尺度的环流特征. 根据南海各季节多年平均表层环流场结构,对南海环流周年变化规律和季节特征进行了初步的探讨. 研究结果表明,南海表层环流始终处在不断演变过程之中,在时间和空间上都表现出明显的多尺度特征.     

海洋测量信息处理技术的发展

海洋测量信息处理是海洋测绘的关键技术之一.为此,着重对当前海洋测量信息处理技术的几个研究热点进行了介绍,内容包括海陆基准的统一、海洋遥感图像的精校正、卫星测高和遥感测深技术,并对海洋测量信息处理与多元化表示作了简要的讨论.     

利用TOPEX测高数据确定大洋环流模式

大洋环流对海洋学、大地测量学以及地球物理学等学科具有重要意义.介绍了利用卫星测高确定海面地形和大洋环流的原理与方法,利用6年的TOPEX测高数据计算了平均稳态海面地形模型,并将其与EGM96、CSR以及Levitus(1982)海面地形模型进行了比较,在此基础上对平均大洋环流模式进行了初步的研究.     

基于1993-2014年高度计数据的西北太平洋中尺度涡识别和特征分析

本文利用22年的AVISO卫星高度计融合数据,基于WA涡旋自动识别方法对西北太平洋的中尺度涡进行了识别追踪,并统计分析了研究区域中尺度涡的空间分布特征、运动属性以及季节和年际变化。研究结果表明:22年间共追踪到生命周期超过30 d的气旋涡3 841个,反气旋涡2 836个,气旋涡数量多于反气旋涡。涡旋大部分向西移动,西向传播的涡旋分布在整个研究区域,而东向传播的涡旋则集中在黑潮及其延伸区。涡旋主要存在15°~30°N的纬度带间;分别而言,气旋涡主要分布在研究区域的北部和南部,而反气旋涡主要分布在副热带逆流区。30°~35°N之间的黑潮延伸区具有明显更高的涡动能和涡振幅,与同纬度区域相比这里的涡旋半径也较高。在季节和年际变化上,春季出现的中尺度涡最多,夏季最少;对涡旋的月生成数目与ENSO指数MEI比较发现,西北太平洋涡旋活动变化并不直接与ENSO现象相关。     

Assimilation of altimetry data for nonlinear shallow-water tides: Quarter-diurnal tides of the Northwest European Shelf

Non-linear tidal constituents, such as the overtide M₄ or the compound tide MS₄, are generated by interaction in shallow seas of the much larger astronomically forced “primary” tidal constituents (e.g., M₂, S₂). As such, errors in modeling these “secondary” shallow-water tides might be expected to be caused first of all by errors in modeling the primary constituents. Thus, in the context of data assimilation, observations of primary-constituent harmonic constants can indirectly constrain shallow-water constituents. Here we consider variational data assimilation for primary and secondary tidal constituents as a coupled problem, using a simple linearized perturbation theory for weak interactions of the dominant primary constituents. Variation of the resulting penalty functional leads to weakly non-linear Euler–Lagrange equations, which we show can be solved approximately with a simple two-stage scheme. In the first stage, data for the primary constituents are assimilated into the linear shallow water equations (SWE), and the resulting inverse solutions are used to compute the quadratic interactions in the non-linear SWE that constitute the forcing for the secondary constituents. In the second stage, data for the compound or overtide constituent are assimilated into the linear SWE, using a prior forced by the results of the first stage. We apply this scheme to assimilation of TOPEX/Poseidon and Jason altimetry data on the Northwest European Shelf, comparing results to a large set of shelf and coastal tide gauges. Prior solutions for M₄, MS₄ and MN₄ computed using inverse solutions for M₂, S₂, and N₂ dramatically improve fits to validation tide gauges relative to unconstrained forward solutions. Further assimilation of along-track harmonic constants for these shallow-water constituents reduces RMS differences to below 1 cm on the shelf, approaching the accuracy of the validation tide gauge harmonic constants.     

湖冰厚度遥感反演进展与展望

湖冰是对气候变化十分敏感的冰冻圈水文变量,起到调节区域气候和湖泊生态系统的作用,并作为一种自然资源服务于冰上生产生活。湖冰覆盖和湖冰厚度是研究湖冰过程的关键变量,目前大多数湖冰研究集中在湖冰覆盖领域,湖冰厚度领域由于缺乏实测资料和专门的遥感观测平台还存在诸多空白,大量缺资料地区湖冰厚度仍处于未知状态,亟待方法和数据上的突破与创新。本文综述了近20年国内外湖冰厚度遥感反演领域的进展,介绍了各类反演方法的原理机理及主要优缺点,其中被动微波遥感方法具有良好的时间分辨率但空间分辨率较粗,难以覆盖中小型湖泊;基于SAR影像的主动微波方法空间分辨率较高但物理机制复杂,可靠性有待进一步验证;基于测高雷达的主动微波方法观测时段较长,物理机制明确,易于拓展到无实测资料湖泊,但空间覆盖相对有限;热红外遥感方法时空分辨率较好,但容易受云和湖冰表面积雪的影响,反演精度和可靠性有待提升。在此基础上,本文分析湖冰厚度遥感反演领域面临的主要挑战和发展方向包括：（1）厘清湖冰表面积雪相关的物理过程;（2）实现大范围实测冰厚和遥感资料的集成;（3）实现多源遥感冰厚反演方法的交叉融合。     

Investigating the uncertainty of satellite altimetry products for hydrodynamic modelling

Satellite altimetry products are increasingly used in many hydraulic applications, and recent studies demonstrate their suitability for the calibration of hydraulic models. The study investigates the effect of satellite‐data uncertainty on the calibration of a quasi‐two‐dimensional (quasi‐2D) model of the middle‐lower portion of the Po river (~140 km). We refer to extended (~16 years of observations) ERS and ENVISAT altimetry products (i.e. River and Lake Hydrology data, RLH) to investigate the effect of (i) record length (i.e. number of satellite measurements at a given satellite track) and (ii) data uncertainty (i.e. altimetry measurements errors) on the calibration of the quasi‐2D model. We first present an assessment of ERS and ENVISAT altimetry errors and then perform the investigations in a Monte Carlo framework by generating datasets of synthetic altimetry products. The results of our analysis further emphasize the suitability of satellite data for the calibration of hydraulic models, providing also a quantitative assessment of the effect of the uncertainty of altimetry products. The analysis highlights the higher accuracy of ENVISAT data, which ensures a stable calibration with ~1.5 years of data (Mean Absolute Error, MAE, lower than 0.4 m, ~0.2 m of which results directly from the uncertainty of ENVISAT data). ERS‐based calibrations become stable with longer series (~3.5–5 years of data), and the negative effect of uncertainty in ERS data is higher (i.e. MAE of 0.6–0.9 m, of which 0.4–0.6 m results from the uncertainty of ERS measurements). Copyright © 2015 John Wiley & Sons, Ltd.     

Laurentia crustal motion observed using TOPEX/POSEIDON radar altimetry over land

A new method to estimate the vertical crustal motion from satellite altimetry over land was developed. The method was tested around Hudson Bay, where the observed vertical motion is largely caused by the incomplete glacial isostatic adjustment (GIA) as a result of the Laurentide ice sheet deglaciation since the last glacial maximum (LGM). Decadal (1992–2003) TOPEX/POSEIDON radar altimetry data over land surfaces were used. The results presented here are improved compared to a previous study (Lee, H., Shum, C.K., Kuo, C.Y., Yi, Y., Braun, A., 2008. Application of TOPEX altimetry for solid Earth deformation studies. Terr. Atmos. Ocean. Sci. 19, 37–46. doi:10.3319/TAO.2008.19.1-2.37(SA).) which estimated vertical motion only over relatively flat land surfaces (standard deviation of the height variation <40 cm). In this study, we extended the concept of traditional 1-Hz (one-per-frame) radar altimeter ocean stackfiles to build 10-Hz (10-per-frame) land stackfiles over Hudson Bay land regions, and succeeded in obtaining vertical motion estimates over much rougher surfaces (standard deviation of the height variation <2 m). 90-m C-band Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) is used as a reference surface to select an optimal waveform retracker, to correct surface gradient errors, and to calculate land surface anomalies. Here, we developed an alternative retracker, called the modified threshold retracker, resulting in decadal vertical motion time series over a 1500 km by 1000 km region covering northern Ontario, northeastern Manitoba, and the Great Lakes region which is at the margin of the former Laurentide ice sheet. The average of the estimated uncertainties for the vertical motion is 2.9 mm/year which is comparable to 2.1 mm/year of recent GPS solutions. The estimated vertical motion is compared with other geodetic observations from GPS, tide gauge/altimetry, GRACE, and several GIA models. The data agree best with the laterally varying 3D GIA model, RF3S20 (β = 0.4) whereas the combination of land altimetry solution with other measurements match best with the models RF3S20 (β = 0.0) or RF3S20 (β = 0.2) in terms of mean and standard deviation of the differences. It is anticipated that this innovative technique could potentially be used to provide additional constraints for GIA model improvement, and be applied to other geodynamics studies.     

Application of altimetry data assimilation on mesoscale eddies simulation

Mesoscale eddy plays an important role in the ocean circulation. In order to improve the simulation accuracy of the mesoscale eddies, a three-dimensional variation (3DVAR) data assimilation system called Ocean Variational Analysis System (OVALS) is coupled with a POM model to simulate the mesoscale eddies in the Northwest Pacific Ocean. In this system, the sea surface height anomaly (SSHA) data by satellite altimeters are assimilated and translated into pseudo temperature and salinity (T-S) profile data. Then, these profile data are taken as observation data to be assimilated again and produce the three-dimensional analysis T-S field. According to the characteristics of mesoscale eddy, the most appropriate assimilation parameters are set up and testified in this system. A ten years mesoscale eddies simulation and comparison experiment is made, which includes two schemes: assimilation and non-assimilation. The results of comparison between two schemes and the observation show that the simulation accuracy of the assimilation scheme is much better than that of non-assimilation, which verified that the altimetry data assimilation method can improve the simulation accuracy of the mesoscale dramatically and indicates that it is possible to use this system on the forecast of mesoscale eddies in the future.     

Mapping the sedimentary basins of the Barents and Kara Seas using ERS-1 altimetry-geodetic mission

The continental shelf in the Arctic north of Russia consists of a series of epicontinental seas, which are the offshore continuation of potentially oil and gas basins on land. The geology of all these epicontinental seas is poorly known, due to the remoteness, the extreme climatic conditions and the extensive costs associated with seismic exploration. Radar altimeter sensors thus provide an invaluable tool for studying the geological structures off the coast. The unique ERS-1 contribution comes from its high latitude coverage (81.5 deg south to north), and the space and time density of its measurements (168-day repeat-orbit).The gravity anomaly field is derived from the geoid height measurements by computing the deflections of the vertical in the north-south and east-west directions and transforming these deflections into gravity anomalies. The gravimetry reveals interesting features of the basement of the Barents and Kara Seas which have not been chartered in recent, previous compilation maps of sedimentary thickness in the Arctic Ocean (Jackson and Oakey, 1988; Gramberg and Puscharovski, 1989). We obtain no indication of the SE-NW offshore Baikalian trend described by Fichler et al (1997) using ERS-1 gravimetry. Instead, the data indicate the presence of a north-south trending gravity high associated with the maximum sediment thickness within the South Barents Sea and the North Barents Sea Basins. Further geological studies are needed to interpret the gravimetric data, which directly addresses the problem of understanding the gravity signature of deep, old, sedimentary basins.