卫星估计降水量产品的优化处理及分区检验

经检验发现,由国家卫星气象中心反演并投入业务使用的GMS-5卫星红外估计降水量产品性能在我国存在一定的区域差异。利用实测雨量对卫星估计降水量产品进行优化处理,结果显示优化后的卫星估计降水量在全国各气候分区都有不同程度的改善。     

基于小波变换和数学形态学的潮沟提取方法研究

潮沟是潮滩的主要地貌类型之一,潮沟信息的检测对湿地生态环境的监测和保护有着重要意义。本文以长江口九段沙下沙北部发育比较复杂的潮沟为研究对象,使用2016年1月26日Landsat8全色波段数据,采用了一种融合小波变换、最大类间方差法和数学形态学的方法对潮沟边缘信息进行了检测。小波变换中通过减小高层小波系数,达到弱化潮滩灰度变化的目的;通过增大低层小波系数,达到增强潮沟信息的目的;利用数学形态学和图像之间的几何(加减乘)运算,完成潮沟的提取;最后,分别在原始数据和检测结果相应的位置取样进行精度验证,样方潮沟面积一致性精度平均为92.1%。     

Adaptive Observer Based Backstepping Controller Design for Dynamic Ship Positioning

Modified adaptive observer based backstepping control system for dynamic positioning of ship is proposed. As an improvement, the adaptive observer takes the first-order wave frequency model and the bias term which represent the slowly varying environmental disturbances and the unmodeled dynamics. Thus, the wave-frequency motions are filtered out, and only the reconstructed low-frequency motions are sent as inputs of the controller. Furthermore, as the ship dynamics parameters are unknown, the adaptive estimation law is designed for both the unknown ship dynamics and the unmeasured state variables. Based on the estimated states and parameters, backstepping controller considering the integral action is designed. Global exponential stability (GES) for the total system is proved using Lyapunov direct method. Simulation results show a good performance of the observer and control system.     

1958-2016年呼伦贝尔草原新巴尔虎右旗气温和降水变化特征

气候变化是影响草原区植被与环境状况的重要因素。利用呼伦贝尔草原新巴尔虎右旗1958-2016年的气温和降水数据资料,采用线性倾向估计法、累积距平分析法、M-K检验法和Morlet小波分析等方法,从不同时间序列上,对该地区近59年的气候变化趋势、极端气候以及突变现象进行分析。结果表明：年平均气温以0.354℃/10a的速率上升,上升趋势显著;四季平均气温均呈现增温趋势,其中春季增温趋势最大;1985-1986年发生了由低温到高温的突变;研究区年平均气温存在11 a的强显著周期。研究区年降水量整体以8.68 mm/10a的速率呈下降趋势,变化趋势不显著;降水集中在夏季（6-8月）,占全年降水量的72.9%,7月降水量最大,有效降水日数最多;1961-1962年和1981-1982年降水发生突变;极端降水指标中日最大降水量、连续5 d最大降水量、强降水量、极强降水量、强降水比率、连续无雨日数、零降水量日数均呈现递减趋势,仅降水强度呈递增趋势,变化趋势均不显著;Morlet小波分析表明研究区年降水量存在52 a的强显著周期。新巴尔虎右旗近59 a气候总体呈现干旱化趋势。     

Spatial constrained inverse rock physics modelling

Predicting reservoir parameters, such as porosity, lithology, and saturations, from geophysical parameters is a problem with non‐unique solutions. The variance in solutions can be extensive, especially for saturation and lithology. However, the reservoir parameters will typically vary smoothly within certain zones—in vertical and horizontal directions. In this work, we integrate spatial correlations in the predicted parameters to constrain the range of predicted solutions from a particular type of inverse rock physics modelling method. Our analysis is based on well‐log data from the Glitne field, where vertical correlations with depth are expected. It was found that the reservoir parameters with the shortest depth correlation (lithology and saturation) provided the strongest constraint to the set of solutions. In addition, due to the interdependence between the reservoir parameters, constraining the predictions by the spatial correlation of one parameter also reduced the number of predictions of the other two parameters. Moreover, the use of additional constraints such as measured log data at specific depth locations can further narrow the range of solutions.     

一种基于丹麦法的改进型双步M估计

针对抗差估计方法初值与临界值选取不当的问题,提出一种以L1-范估计的平差值作为初值、以改进的丹麦法权函数作为第一步抗差阶段权函数的双步M估计,该方法既具有较强的抗差性,又具有最小二乘的最优性。试验表明,该方法估计结果与无粗差时的LS估计结果基本一致,抗差效果明显优于传统抗差估计方法与其他两步抗差估计。     

Joint parameter estimation from magnetic resonance and vertical electric soundings using a multi‐objective genetic algorithm

Magnetic resonance sounding (MRS) has increasingly become an important method in hydrogeophysics because it allows for estimations of essential hydraulic properties such as porosity and hydraulic conductivity. A resistivity model is required for magnetic resonance sounding modelling and inversion. Therefore, joint interpretation or inversion is favourable to reduce the ambiguities that arise in separate magnetic resonance sounding and vertical electrical sounding (VES) inversions. A new method is suggested for the joint inversion of magnetic resonance sounding and vertical electrical sounding data. A one‐dimensional blocky model with varying layer thicknesses is used for the subsurface discretization. Instead of conventional derivative‐based inversion schemes that are strongly dependent on initial models, a global multi‐objective optimization scheme (a genetic algorithm [GA] in this case) is preferred to examine a set of possible solutions in a predefined search space. Multi‐objective joint optimization avoids the domination of one objective over the other without applying a weighting scheme. The outcome is a group of non‐dominated optimal solutions referred to as the Pareto‐optimal set. Tests conducted using synthetic data show that the multi‐objective joint optimization approximates the joint model parameters within the experimental error level and illustrates the range of trade‐off solutions, which is useful for understanding the consistency and conflicts between two models and objectives. Overall, the Levenberg‐Marquardt inversion of field data measured during a survey on a North Sea island presents similar solutions. However, the multi‐objective genetic algorithm method presents an efficient method for exploring the search space by producing a set of non‐dominated solutions. Borehole data were used to provide a verification of the inversion outcomes and indicate that the suggested genetic algorithm method is complementary for derivative‐based inversions.     

Development and validation of nonlinear computational models of dispersed structures under strong earthquake excitation

Structural health monitoring of large multispan flexible bridges is particularly important because of their important role in civil infrastructure and transportation systems. In this study, the response of the Yokohama Bay Bridge (YBB), a three‐span cable‐stayed bridge, to the 2011 Great East Japan Earthquake is used to perform multi‐input multi‐output system identification studies. The extensive multicomponent measurements are also used to develop and validate data‐driven nonlinear mathematical models that can predict the response of YBB to various earthquake records and can accurately estimate its damping characteristics when the system is driven into the nonlinear response range. A combination of least‐square (parametric) and neural network (nonparametric) approaches is used to develop the mathematical models, along with time‐marching techniques for dynamic response calculations. It is shown that the nonlinear mathematical models perform better than the equivalent linear models, both for response prediction and damping estimation. The importance of having an accurate approach for quantifying the damping due to the variety of nonlinear features in the YBB response is shown. This study demonstrates the significance of constructing robust mathematical models that can capture the correct physics of the underlying system and that can be used for computational purposes to augment experimental studies. Given the lack of suitable data sets for full‐scale structures under extreme loads, the availability of the long‐duration measurements from the 2011 Great East Japan Earthquake and its many strong aftershocks provides an excellent opportunity to perform the analyses presented in this study. Copyright © 2013 John Wiley & Sons, Ltd.     

Development of an operational rainfall data quality-control scheme based on radar-raingauge co-kriging analysis

Abstract

Automatic raingauge data often serve as an important input to hydrological and weather warning operations. They are not only fundamental in quantitative rainfall analysis, but also act as the ground truth in warning operation and forecast validation. Quality control is required before the data can be used quantitatively due to systematic and random errors. Extremely large random errors and unreasonably small or false zero values can hamper effective monitoring of heavy rain. Yet both are difficult to detect in real-time by objective means. In an attempt to address these problems, a rainfall data quality-control scheme based on radar-raingauge co-kriging analysis was developed. The important threshold values required in the data quality control of 60-min raingauge rainfall were determined from a detailed analysis of the distributions of rainfall residuals defined as the arithmetic difference and the logarithm of the ratio between a raingauge measurement and its co-kriging estimate. The scheme has been developed and is in real-time use in Hong Kong, a coastal city of about 1100 km² area with more than 150 raingauges installed. Geographically, it is located in the subtropics and dominated by heavy convective rainfall in the summer. As a basis of the quality-control scheme, the co-kriging rainfall analysis was shown through a verification exercise to be superior to those obtained by the Barnes analysis and ordinary kriging of raingauge data. The performance of the quality-control algorithm was assessed using selected cases and controlled tests, and was found to be satisfactory, with a high error detection rate for the two targeted types of error. Limitations and operational issues identified during a real-time trial of the quality-control scheme are also discussed.

Citation Yeung, H.Y., Man, C., Chan, S.T., and Seed, A., 2014. Development of an operational rainfall data quality-control scheme based on radar-raingauge co-kriging analysis. Hydrological Sciences Journal, 59 (7), 1285–1299. http://dx.doi.org/10.1080/02626667.2013.839873     

Long-term diagnostics of precipitation estimates and the development of radar hardware monitoring within a radar product data quality management system

Abstract

Quality is key to ensuring that the potential offered by weather radar networks is realized. To achieve optimum quality, a comprehensive radar data quality management system, designed to monitor the end-to-end radar data processing chain and evaluate product quality, is being developed at the UK Met Office. Three contrasting elements of this system are described: monitoring of key radar hardware performance indicators; generation of long-term integrations of radar products; and monitoring of radar reflectivity factor using synthesized observations from numerical weather prediction model fields. Examples of each component are presented and ways in which the different types of monitoring information have been used to both identify issues with the radar product data quality and help formulate solutions are given.

Editor Z.W. Kundzewicz; Guest editor R.J. Moore

Citation Harrison, D., Georgiou, S., Gaussiat, N., and Curtis, A., 2013. Long-term diagnostics of precipitation estimates and the development of radar hardware monitoring within a radar product data quality management system. Hydrological Sciences Journal, 59 (7), 1327–1342. http://dx.doi.org/10.1080/02626667.2013.841316