利用卫星测高资料推求西北太平洋海域的海洋大地水准面

本文根据卫星测高数据和海面动力地形资料，绘制了不相上下北太平洋海域局部大地水准面的精细结构图，对解决卫星测高技术中大地水准面积和海面地形的可分性问题作了初步尝试。     

信息时代地图技术美的研究与实践

通过分析现代地图表现形式及存在的问题，探讨了信息时代地图制图技术美的含义和地图技术美的表现形式。并在技术美创新理念指导下，对利用计算机技术和图形图像处理技术来改进地图符号设计，提高地图表现力进行了一些理论探讨和技术尝试．同时也得到了一些有益的启示。     

Water level observations from unmanned aerial vehicles for improving estimates of surface water–groundwater interaction

Integrated hydrological models are usually calibrated against observations of river discharge and piezometric head in groundwater aquifers. Calibration of such models against spatially distributed observations of river water level can potentially improve their reliability and predictive skill. However, traditional river gauging stations are normally spaced too far apart to capture spatial patterns in the water surface, whereas spaceborne observations have limited spatial and temporal resolution. Unmanned aerial vehicles can retrieve river water level measurements, providing (a) high spatial resolution; (b) spatially continuous profiles along or across the water body, and (c) flexible timing of sampling. A semisynthetic study was conducted to analyse the value of the new unmanned aerial vehicle‐borne datatype for improving hydrological models, in particular estimates of groundwater–surface water (GW–SW) interaction. Mølleåen River (Denmark) and its catchment were simulated using an integrated hydrological model (MIKE 11–MIKE SHE). Calibration against distributed surface water levels using the Differential Evolution Adaptive Metropolis algorithm demonstrated a significant improvement in estimating spatial patterns and time series of GW–SW interaction. After water level calibration, the sharpness of the estimates of GW–SW time series improves by ~50% and root mean square error decreases by ~75% compared with those of a model calibrated against discharge only.     

岩石中的压力影形成的实验观测研究

野外地质观察发现,在大陆地壳变质岩中可以广泛观察到围绕一个大的单晶或者硬质点的两端区域填充低粘度相物质形成的压力影。为了定量研究岩石材料中压力影的形成条件,本文利用高精度Paterson气体介质变形装置,对含有刚性球的圣卡罗橄榄石和洋中脊玄武岩(MORB)的混合物圆柱型样品进行了高温高压扭转变形试验。变形实验前样品的初始熔融均匀分布,比例为φ≈0.05,变形试件尺寸为D8.9mm×L5.5mm,内含8粒直径约1mm的刚性球。扭转变形试验温度为1473K,围压为300MPa,应变率为γ≈1×10~(-4)s~(-1),最大剪切变形为γ≈4。实验结果表明,岩石受到扭转力的作用产生变形之后,当局部剪切应变达到γ≈1时,可以在刚性球周围形成熔融富集带和熔融贫乏带,即压力影构造,围绕刚性球对称分布。由于熔融分布的不均一性,富集带熔融比例上升,最高可以达到φ_(high)=0.1~0.3,熔融贫乏带熔融比例下降,含量为φ_(low)=0.01~0.02。由于刚性球对其周围的压力分布的扰动区域大约为刚性球的尺度范围,因此,在离开刚性球一定距离后,熔融趋于均匀分布。     

Trends in Extreme Mean Sea Level Quantiles from Satellite Altimetry

Satellite altimetry allows the study of sea-level long-term variability on a global and spatially uniform basis. Here quantile regression is applied to derive robust median regression trends of mean sea level as well as trends in extreme quantiles from radar altimetry time series. In contrast with ordinary least squares regression, which only provides an estimate on the rate of change of the mean of data distribution, quantile regression allows the estimation of trends at different quantiles of the data distribution, yielding a more complete picture of long-term variability. Trends derived from basin-wide averaged regional mean sea level time series are robust and similar for all quantiles, indicating that all parts of the data distribution are changing at the same rate. In contrast, trends are not robust and diverge across quantiles in the case of local time series. Trends are under- (over-)estimated in the western (eastern) equatorial Pacific. Furthermore, trends in the lowermost quantile (0.05) are larger than the median trend in the western Pacific, while trends in the uppermost quantile (0.95) are lower than the median trend in the eastern Pacific. These differences in trends in extreme mean sea level quantiles are explained by the exceptional effect of the strong 1997–1998 El Niño–Southern Oscillation (ENSO) event.     

A statistical analysis of mesoscale eddies in the Bay of Bengal from 22–year altimetry data

本文使用一种基于SLA数据的涡旋识别方法,通过22年的AVISO高度计测高数据对孟加拉湾的中尺度涡特征进行了研究。本文主要分析了孟加拉湾涡旋的地理分布、涡旋极性、涡旋生命周期和传播距离、涡旋产生和消失位置、涡旋传播方向和移动轨迹、涡旋运动特征、涡旋属性的演化以及涡旋活动的季节和年际变化等特性。涡旋主要分布在孟加拉湾西部海域,并且大部分涡旋向西移动。涡旋极性分布显示气旋涡更经常出现在湾的西北部和南部,而反气旋涡主要出现在湾的东部。在22年间,共追踪探测到生命周期超过30天的气旋涡565个、反气旋涡389个;对所有生命周期和传播距离而言都是气旋涡数量居多。所有观测到的涡旋的运动属性分析显示气旋涡的涡旋平均振幅大于反气旋涡;对平均半径和平均移动速度而言,气旋涡和反气旋涡相差不大。而且,涡旋属性演化显示生命周期超过90天的涡旋具有明显的双阶段演化特征,包括一个前50天的涡旋成长阶段和一个50天之后的涡旋消亡阶段。针对涡旋活动的季节变化,气旋涡在春季居多而反气旋涡在夏季较多;长生命周期的涡旋季节分布显示在孟加拉湾涡旋活动具有明显的季节分布特征。涡旋数量的年际变化与EKE变化有一个明显的负相关。     

Variations of Kuroshio geostrophic transport south of Japan estimated from long-term IES observations

Two inverted echo sounders were maintained on coastal and offshore sides of the Kuroshio south of Japan from October 1993 to July 2004. Applying the gravest empirical mode method, we obtained a time series of geostrophic transport. Estimated transports generally agree well with geostrophic transports estimated from hydrography. Their agreement with the hydrographic transports is better than that of transports estimated from satellite altimetry data. The geostrophic transport is expressed as the surface transport per unit depth multiplied by the equivalent depth. The geostrophic transport varies mostly with the surface transport and fractionally with the equivalent depth. Seasonal variation of the geostrophic transport has a minimum in March and a maximum in September, with a range of about one fifth of the total transport.     

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Hydrodynamic Tidal Model of the Persian Gulf Based on Spatially Variable Bed Friction Coefficient

The aim of this study is to develop a two-dimensional hydrodynamic tidal model for the Persian Gulf (PG2017) using 2D-MIKE21 software. The advantages of present study is accounting for the spatial variation of bed friction coefficient besides a precise bathymetry together with a 23-year of combined records of satellite altimetry data. We found that the bed friction coefficient has a significant effect on sea level changes in the region under our modeling consideration. Since the tidal behavior in the northern part of the Qeshm Island is significantly different from the other parts of the Persian Gulf, to present a more accurate hydrodynamic tidal model, the Gulf is divided into two regions where the bed friction coefficient is modeled separately for each region. The root mean square value of the differences between the amplitude of dominant constituents; M2, S2, K1, and O1 derived from the PG2017 model and that of 98 altimetry and coastal tide gauge stations are respectively equal to 1.6, 1.9, 2.8, and 1.3?cm. Moreover, comparing the PG2017 model efficiency with the FES2014, OSU12, EOT11a, DTU10, and Admiralty models shows that the PG2017 model has an improvement of 22.1%, 47.2%, 43.2%, 44.2%, and 57.6% in terms of relative error, respectively.     

Sea Level Prediction in the Yellow Sea From Satellite Altimetry With a Combined Least Squares-Neural Network Approach

Accessible high-quality observation datasets and proper modeling process are critically required to accurately predict sea level rise in coastal areas. This study focuses on developing and validating a combined least squares-neural network approach applicable to the short-term prediction of sea level variations in the Yellow Sea, where the periodic terms and linear trend of sea level change are fitted and extrapolated using the least squares model, while the prediction of the residual terms is performed by several different types of artificial neural networks. The input and output data used are the sea level anomalies (SLA) time series in the Yellow Sea from 1993 to 2016 derived from ERS-1/2, Topex/Poseidon, Jason-1/2, and Envisat satellite altimetry missions. Tests of different neural network architectures and learning algorithms are performed to assess their applicability for predicting the residuals of SLA time series. Different neural networks satisfactorily provide reliable results and the root mean square errors of the predictions from the proposed combined approach are less than 2?cm and correlation coefficients between the observed and predicted SLA are up to 0.87. Results prove the reliability of the combined least squares-neural network approach on the short-term prediction of sea level variability close to the coast.