气象预警信息一键式发布系统研究与应用

基于WebGIS、HTTP通信、数据库等技术,制定了一键式预警信息发布规范,有效整合了电子显示屏、预警大喇叭、手机等预警发布终端,开发了气象预警信息一键式发布平台,实现了地图综合显示、气象数据叠加、任意预警区域选取、一键式发布预警信息等功能,提高了预警信息发布的可视化水平,保证了多终端预警信息发布的高效性、一致性。该系统的一键式信息发布技术,为气象预警发布开拓了新思路,能够有效提升业务水平和预警发布能力。     

青藏高原晚始新世干旱化事件：改则盆地康托组碳酸盐岩碳氧同位素的记录

改则盆地位于青藏高原腹地,盆地内沉积物记录了高原古环境变化的重要信息。本文对改则盆地康托组碳酸盐岩碳氧同位素进行研究,结果显示改则盆地中-晚始新世的演化分为两个阶段:1中始新世湿润气候下开放湖盆阶段:虽然碳酸盐岩δ~(18)O值在43层处向正值偏移,但整体~(18)O和~(13)C强烈亏损,并且该时期碳酸盐岩δ~(18)O值和δ~(13)C变化相关系数为R~2=0.082。表明该阶段的研究区虽然经历过短期蒸发作用增强或补给水减少,但整体是气候湿润条件下补给水丰富的开放型湖盆。2晚始新世干旱气候下封闭湖盆阶段:经过中新世晚期(63层)气候和湖泊水文状态的过渡,晚始新世~(18)O和~(13)C同位素富集,δ~(18)O值和δ~(13)C值变化相关系数为R~2=0.7762。表明该阶段气候干旱,蒸发作用强烈,湖盆萎缩成为封闭湖盆。综合前人研究,认为青藏高原腹地及北缘、东北缘在晚始新世存在明显的区域性干旱化事件。对比分析青藏高原隆升、全球气候记录、全球海水Sr和大气CO_2记录,认为青藏高原腹地和北部的干旱化事件主要受青藏高原隆升的影响。     

Initiation of large-volume silicic centers in the Yellowstone hotspot track: insights from H<Subscript>2</Subscript>O- and F-rich quartz-hosted rhyolitic melt inclusions in the Arbon Valley Tuff of the Snake River Plain

During the onset of caldera cluster volcanism at a new location in the Snake River Plain (SRP), there is an increase in basalt fluxing into the crust and diverse silicic volcanic products are generated. The SRP contains abundant and compositionally diverse hot, dry, and often low-δ¹⁸O silicic volcanic rocks produced through time during the formation of individual caldera clusters, but more H₂O-rich eruptive products are rare. We report analyses of quartz-hosted melt inclusions from pumice clasts from the upper and lower Arbon Valley Tuff (AVT) to gain insight into the initiation of caldera cluster volcanism. The AVT, a voluminous, caldera-forming rhyolite, represents the commencement of volcanism (10.44 Ma) at the Picabo volcanic field of the Yellowstone hotspot track. This is a normal δ¹⁸O rhyolite consisting of early and late erupted members (lower and upper AVT, respectively) with extremely radiogenic Sr isotopes and unradiogenic Nd isotopes, requiring that ~50 % of the mass of these elements is derived from melts of Archean upper crust. Our data reveal distinctive features of the early erupted lower AVT melt including: variable F concentrations up to 1.4 wt%, homogenous and low Cl concentrations (~0.08 wt%), H₂O contents ranging from 2.3 to 6.4 wt%, CO₂ contents ranging from 79 to 410 ppm, and enrichment of incompatible elements compared to the late erupted AVT, subsequent Picabo rhyolites, SRP rhyolites, and melt inclusions from other metaluminous rhyolites (e.g., Bishop Tuff, Mesa Falls Tuff). We couple melt inclusion data with Ti measurements and cathodoluminescence (CL) imaging of the host quartz phenocrysts to elucidate the petrogenetic evolution of the AVT rhyolitic magma. We observe complex and multistage CL zoning patterns, the most critical being multiple truncations indicative of several dissolution–reprecipitation episodes with bright CL cores (higher Ti) and occasional bright CL rims (higher Ti). We interpret the high H₂O, F, F/Cl, and incompatible trace element concentrations in the context of a model involving melting of Archean crust and mixing of the crustal melt with basaltic differentiates, followed by multiple stages of fractional crystallization, remelting, and melt extraction. This multistage process, which we refer to as distillation, is further supported by the complex CL zoning patterns in quartz. We interpret new Δ¹⁸O(Qz-Mt) isotope measurements, demonstrating a 0.4 ‰ or ~180 °C temperature difference, and strong Sr isotopic and chemical differences between the upper and lower AVT to represent two separate eruptions. Similarities between the AVT and the first caldera-forming eruptions of other caldera clusters in the SRP (Yellowstone, Heise and Bruneau Jarbidge) suggest that the more evolved, lower-temperature, more H₂O-rich rhyolites of the SRP are important in the initiation of a caldera cluster during the onset of plume impingement.     

Assessing Performance of Tomo-SAR and Backscattering Coefficient for Hemi-Boreal Forest Aboveground Biomass Estimation

Tomo-SAR technique has been used for hemi-boreal forest height and further forest biomass estimation through allometric equation. Backscattering coefficient especially in longer wavelength (L- or P-band) is thought as a useful parameter for hemi-boreal forest biomass retrieval. The aim of this paper is to assess the performance of vertical backscattering power and backscattering coefficient for hemi-boreal forest aboveground biomass (AGB) estimation with airborne P-band data. The test site locates in southern Sweden called Remningstorp test site, and the in-situ forest AGB ranges from 14 t/ha to 245 t/ha at stand level. Multi-baseline P-band Pol-InSAR data in repeat-path mode collected during March and May in 2007 at Remningstorp test site was used. We found that the correlation coefficient (R) between backscattering coefficient of P-band HH polarization and the in-situ forest biomass reached 0.87. The R for P-band VV backscattering power at 5 m is 0.71 and 10 m is 0.72. Backscattering coefficient in HH polarization and vertical backscattering power at 5 m and 10 m were applied to construct a model for hemi-boreal forest AGB estimation by backward step-wise regression and cross-validation approach. The results showed that the estimated forest AGB ranges from 19 to 240 t/ha, and the constructed model obtained a higher R and smaller RMSE, the value of R is 0.91, RMSE is 30.43 t/ha at Remningstorp test site.     

Recursive algorithm for fast GNSS orbit fitting

Gaussian elimination is an efficient and numerically stable algorithm for estimating parameters and their precision. However, before estimating the parameters, it is often prudent to perform statistical tests to achieve the best fitting model. We use Gaussian elimination to select the best fitting model among candidate models. A succinct relationship between the weighted sum of squared residuals and the previous one is revealed by a volume formula. For quick parameter estimation and determination of weighted sum of squared residuals, a recursive elimination algorithm is proposed in the context of Gaussian elimination. In order to improve the model selection efficiency, the parameter estimation and the determination of the weighted sum of squared residuals are carried out in parallel using the proposed recursive elimination algorithm in which the improvement at each recursive stage is judged by the Bayesian information criterion. Ultimately, the computational complexity and numerical stability of the recursive elimination proposed are briefly discussed, and a GNSS orbit interpolation example is used to verify the results. It shows that the proposed recursive elimination algorithm inherits the numerical stability of the Gaussian elimination, and this algorithm can be used to examine the gain from the newly introduced parameter, dynamically assess the fitting model, and fix the optimal model efficiently. The optimal fitting model with the lowest information is very close to the real situation verified by checkpoints.     

A new method for specular and diffuse pseudorange multipath error extraction using wavelet analysis

Multipath remains one of the major challenges in Global Navigation Satellite System (GNSS) positioning because it is considered the dominant source of ranging errors, which can be classified into specular and diffuse types. We present a new method using wavelets to extract the pseudorange multipath in the time domain and breaking it down into the two components. The main idea is an analysis-reconstruction approach based on application of both continuous wavelet transform (CWT) and discrete wavelet transform (DWT). The proposed procedure involves the use of L1 code-minus-carrier (CMC) observable where higher-frequency terms are isolated as residuals. CMC residuals are analyzed by applying the CWT, and we propose the scalogram as a technique for discerning time–frequency variations of the multipath signal. Unlike Fourier transform, the potential of the CWT scalogram for examining the non-stationary and multifrequency nature of the multipath is confirmed as it simultaneously allows fine detection and time localization of the most representative frequencies of the signal. This interpretation of the CWT scalogram is relevant when choosing the levels of reconstruction with DWT, allowing accurate time domain extraction of both the specular and diffuse multipath. The performance and robustness of the method and its boundary applicability are assessed. The experiment was carried out using a receiver of Campania GNSS Network. The results are given in which specular multipath error is achieved using DWT level 7 approximation component and diffuse multipath error is achieved using DWT level 6 denoised detail component.     

Optimization and Parametrical Investigation to Assess the Reconstitution of Different Types of Indian Sand Using Portable Travelling Pluviator

By using the air pluviation technique, it is aimed to achieve the desired relative density with uniform void ratio throughout the specimen in order to maintain the homogeneity and to avoid the spatial variability. Further, in order to achieve the maximum deposition intensity, a systematic optimization study has been carried out rigorously in a test tank to determine the diameter of the orifice to be employed for the sieve plates of different porosity and the number of sieve plates to be installed in the diffuser sieve sets. The study has been conducted with four different patterns of sieves with different porosity to achieve a wide range of relative densities for four different uniformly graded Indian sands. The dynamic penetrometer which is considered to be one of the cost effective instruments has been efficiently used to determine the soil resistance at various locations of the test tank for every given height of fall in order to check the uniformity of placement density throughout the sand bed. The study reveals that the sand beds of different relative densities could be achieved using different patterns of diffuser sieves at optimum sand flow rate without compromising the uniformity. The effect of height of fall as well as porosity of diffuser sieves on the relative density of different sands has been studied in detail. The deposition intensity and the relative density obtained from the present study are compared with the values available in the literature.     

Assessment and Prediction of Liquefaction Potential Using Different Artificial Neural Network Models: A Case Study

Soil liquefaction as a transformation of granular material from solid to liquid state is a type of ground failure commonly associated with moderate to large earthquakes and refers to the loss of strength in saturated, cohesionless soils due to the build-up of pore water pressures and reduction of the effective stress during dynamic loading. In this paper, assessment and prediction of liquefaction potential of soils subjected to earthquake using two different artificial neural network models based on mechanical and geotechnical related parameters (model A) and earthquake related parameters (model B) have been proposed. In model A the depth, unit weight, SPT-N value, shear wave velocity, soil type and fine contents and in model B the depth, stress reduction factor, cyclic stress ratio, cyclic resistance ratio, pore pressure, total and effective vertical stress were considered as network inputs. Among the numerous tested models, the 6-4-4-2-1 structure correspond to model A and 7-5-4-6-1 for model B due to minimum network root mean square errors were selected as optimized network architecture models in this study. The performance of the network models were controlled approved and evaluated using several statistical criteria, regression analysis as well as detailed comparison with known accepted procedures. The results represented that the model A satisfied almost all the employed criteria and showed better performance than model B. The sensitivity analysis in this study showed that depth, shear wave velocity and SPT-N value for model A and cyclic resistance ratio, cyclic stress ratio and effective vertical stress for model B are the three most effective parameters on liquefaction potential analysis. Moreover, the calculated absolute error for model A represented better performance than model B. The reasonable agreement of network output in comparison with the results from previously accepted methods indicate satisfactory network performance for prediction of liquefaction potential analysis.     

东海表层沉积物碎屑矿物组合分布特征及其物源环境指示

为进一步明确东海陆架区的沉积物物源及水动力环境,对研究区表层沉积物的碎屑矿物进行了鉴定分析。研究区共鉴定出49种重矿物、8种轻矿物。根据碎屑矿物的组合分布结合矿物形态特征,将东海陆架区划分为三个矿物区,内陆架矿物区、外陆架矿物区及虎皮礁矿物区。内陆架矿物区,动力分选是影响碎屑矿物分布的主要因素,物质来源相对单一,碎屑矿物主要来源于现代长江物质,闽浙沿岸近岸河流的输入,人类活动也对该区的矿物组成产生一定的影响;外陆架矿物区,重矿物分布的主控因素是长期的分选作用,主要是长江物质经后期改造形成,现代长江物质可从内陆架中北部扩散至124.5°E左右,此外外陆架东南部地形的变化也对碎屑矿物的分布起到一定控制作用;虎皮礁矿物区,有来自黄河、长江、火山物质的多重影响,且水动力环境相对复杂。