电离层高阶项改正对参考框架实现及测站坐标的影响分析

根据电离层高阶项改正模型,确定了高阶项延迟对不同GPS观测量的影响量。根据IERS协议2010推荐的最新模型,对全球均匀分布的104个IGS基准站数据进行了重新处理,研究了电离层高阶项延迟(二、三阶项)对坐标参考框架实现及测站坐标的影响,量化了不同地磁模型下的高阶项改正影响变化。结果表明,电离层延迟高阶项改正对参考框架原点有较大影响,犣方向的平移可达20mm,犡、犢方向的平移所受的影响相对较小,大部分维持在5mm以下;电离层高阶项延迟会引起测站坐标变化的区域性偏移现象;地磁模型的不同会导致参考框架原点犣方向有着约10mm的变化,在局部区域也会引起显著的测站坐标变化差异。最后对电离层高阶项改正的影响结果进行了分析与讨论。     

Comparison of parameter uncertainty analysis techniques for a TOPMODEL application

Parameter uncertainty in hydrologic modeling is crucial to the flood simulation and forecasting. The Bayesian approach allows one to estimate parameters according to prior expert knowledge as well as observational data about model parameter values. This study assesses the performance of two popular uncertainty analysis (UA) techniques, i.e., generalized likelihood uncertainty estimation (GLUE) and Bayesian method implemented with the Markov chain Monte Carlo sampling algorithm, in evaluating model parameter uncertainty in flood simulations. These two methods were applied to the semi-distributed Topographic hydrologic model (TOPMODEL) that includes five parameters. A case study was carried out for a small humid catchment in the southeastern China. The performance assessment of the GLUE and Bayesian methods were conducted with advanced tools suited for probabilistic simulations of continuous variables such as streamflow. Graphical tools and scalar metrics were used to test several attributes of the simulation quality of selected flood events: deterministic accuracy and the accuracy of 95 % prediction probability uncertainty band (95PPU). Sensitivity analysis was conducted to identify sensitive parameters that largely affect the model output results. Subsequently, the GLUE and Bayesian methods were used to analyze the uncertainty of sensitive parameters and further to produce their posterior distributions. Based on their posterior parameter samples, TOPMODEL’s simulations and the corresponding UA results were conducted. Results show that the form of exponential decline in conductivity and the overland flow routing velocity were sensitive parameters in TOPMODEL in our case. Small changes in these two parameters would lead to large differences in flood simulation results. Results also suggest that, for both UA techniques, most of streamflow observations were bracketed by 95PPU with the containing ratio value larger than 80 %. In comparison, GLUE gave narrower prediction uncertainty bands than the Bayesian method. It was found that the mode estimates of parameter posterior distributions are suitable to result in better performance of deterministic outputs than the 50 % percentiles for both the GLUE and Bayesian analyses. In addition, the simulation results calibrated with Rosenbrock optimization algorithm show a better agreement with the observations than the UA’s 50 % percentiles but slightly worse than the hydrographs from the mode estimates. The results clearly emphasize the importance of using model uncertainty diagnostic approaches in flood simulations.     

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论煤层的加积方式

煤层成因是煤地质学的核心。煤层是一种沉积地层,它遵循沉积学、地层学、岩石学以及矿床学的基本规律,也有其特殊性,其成因并不同于煤的成因。传统煤地质学的核心观点是煤层由泥炭沼泽演化而成,其本质就是成煤物质的垂向加积。通过对煤层垂向和侧向加积的分析对比以及大面积稳定展布的厚煤层低自然伽马多峰现象、层理与条带结构等沉积特征的研究,认为成煤物质是机械沉积的,煤层像大多数沉积岩层一样是侧向加积形成的。对于厚煤层而言,多期侧向加积产生了次生垂向加积,其形成过程不是一个简单的、连续的、线性的垂向累加过程,而是一个复杂的、不连续的、非线性的侧向叠合过程,成煤物质是不连续的、多期多源的,厚煤层中普遍存在的夹矸便是其不连续的证据,同时厚煤层是穿时的。煤层侧向加积与较深水或海相沉积共生,是一个有机连续的整体,符合瓦尔特相律和古生态学原理,符合煤层厚度、形态多变及下伏地层沉积体系多种多样,也符合成煤物质超巨量工业富集、含煤地层灰色灰黑色、煤矿床质量优良的事实。     

Hydrological cycle and water balance estimates for the megadune–lake region of the Badain Jaran Desert,China

The hydrology and water balance of megadunes and lakes have been investigated in the Badain Jaran Desert of China. Field observations and analyses of sand layer water content, field capacity, secondary salt content, and grain size reveal 3 types of important natural phenomenon: (a) vegetation bands on the leeward slope of the megadunes reflect the hydrological regime within the sandy vadose zone; (b) seepage, wet sand deposits, and secondary salt deposits indicate the pattern of water movement within the sandy vadose zone; (c) zones of groundwater seeps and descending springs around the lakes reflect the influence of the local topography on the hydrological regime of the megadunes. The seepage exposed on the sloping surface of the megadunes and gravity water contained within the sand layer confirm the occurrence of preferential flow within the vadose zone of the megadunes. Alternating layers of coarse and fine sand create the conditions for the formation of preferential flows. The preferential flows promote movement of water within the sand layer water that leads to deep penetration of water within the megadunes and ultimately to the recharging of groundwater and lake water. Our results indicate that a positive water balance promotes recharge of the megadunes, which depends on the high permeability of the megadune material, the shallow depth of the surface sand layer affected by evaporation, the occurrence of rainfall events exceeding 15 mm, and the sparse vegetation cover. Water balance estimates indicate that the annual water storage of the megadunes is about 7.5 mm, accounting for only 8% of annual precipitation; however, the shallow groundwater per unit area under the megadunes receives only 3.6% of annual precipitation, but it is still able to maintain a dynamic balance of the lake water. From a water budget perspective, the annual water storage in the megadunes is sufficient to serve as a recharge source for lake water, thereby enabling the long‐term persistence of the lakes. Overall, our findings demonstrate that precipitation is a significant component of the hydrological cycle in arid deserts.     

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.     

K 近邻非参数回归概率预报技术及其应用

针对参数回归技术制作概率预报存在拟合好、但预报结果不稳定的现象, 提出了用K近邻非参数回归技术制作概率预报的新途径。K 近邻非参数回归技术包括历史样本数据库、近邻子集生成和优化以及预报量估计4 个主要部分。利用该技术进行了单要素概率预报(主要包括云量和降水)和多维联合概率预报(降水、总云量、风速和气温)试验, 并对试验结果进行了检验。实例研究结果表明:该文所给出的计算方案预报稳定性好, 准确率较高,具有良好的业务应用价值。     

Study on cut-off low-pressure systems with floods over Northeast Asia

Summary The cut-off lows (COLs) during the period from June to August 1998 leading to the record flood in Northeast Asia, especially in Northeast China, has been investigated in this paper. The results are as follows: the blocking highs benefited significantly the formation and maintenance of COLs over Northeast China; an obvious frontogenesis zone existed in Northeast China and it implies that baroclinity played an important role in the initiation of COLs, especially in middle and upper troposphere; the maxima of the potential vorticity anomaly were located in the upper troposphere, then extended downwards to the middle and the lower troposphere. The pronounced interaction between systems in upper-middle and low troposphere can be revealed; the moisture supply was from South China, and even from East China Sea and South China Sea. The strong southerly current transported very rich moisture to Northeast China. The maximum of the convergence of moisture flux was below 850 hPa. Obvious interaction between the middle and lower latitude systems was found in the study. Also, the summer monsoon showed significant impacts on the sustained heavy rainfalls related with the COLs over Northeast China; the upward motion could be caused by the lifting of the large scale dynamic forcing and there was no obvious releasing of latent heating in the upper-middle troposphere. The cold dome in the COLs was quite different both from the warm core in tropical cyclone and from the weaker warm core in Meiyu (Baiu) front low. The calculation of vorticity budget shows that both the horizontal advection term and horizontal divergence term contributed importantly to the maintenance and the strengthening of positive relative vorticity. Finally, the complex dynamical characteristics regarding the COLs are discussed and further investigation is proposed.     

基于投影变换的线阵旋转扫描相机标定方法

针对线阵旋转扫描相机标定数据难以获取及模型解算不稳定的问题,提出了一种基于投影变换的线阵旋转扫描相机标定方法。首先构建了一种新的线阵旋转扫描相机成像模型,该模型可以根据相机旋转平台参数、线阵旋转扫描相机成像平面与其切平面的位置关系将旋转扫描图像投影为框幅式图像;然后根据构建出的成像模型,采用直接线性变换法和非线性优化方法进行相机标定和参数优化。试验结果表明,此方法简单易行,具有较高的精度。     

沙澧河流域两场大暴雨过程的对比分析

利用常规观测资料、自动站资料和NCEP1°×1°再分析资料对2007年7月5日和14日沙澧河流域两场大暴雨过程进行了诊断对比分析.结果表明:不同影响系统下产生的大暴雨过程其动力机制有所差异.垂直螺旋度计算结果显示:两次过程700hPa等压面上正垂直螺旋度中心的移向和强度变化与降水落区及趋势变化有很好的对应关系,暴雨区出现在正垂直螺旋度中心移动的前方,对流域大暴雨的落区有一定的指示意义.5日呈现中低层正、高层负的垂直螺旋度配置,动力条件更有利于大暴雨的发生.湿位涡演变分析发现,5日中低层既存在对流不稳定,又存在对称不稳定,有利于垂直对流和倾斜对流发生,造成流域大暴雨.14日中低层大气处于对流稳定状态,但边界层和中层存在对流不稳定,同时中层还存在较强的对称不稳定,垂直涡度得到较大增长,导致上升运动的加强和水汽的垂直输送,有利于降水增幅.