基于神经网络的时间域直升机电磁数据电导率深度成像

采用G-S变换以及高斯数值积分法,形成了时间域直升机的航空电磁响应正演样本集,分析了飞机测量过程中吊舱高度变化对电磁响应的影响,并将吊舱高度的变化等效成电导率为零的假层厚度的变化,以去除高度计等的影响.以假层半空间模型为基础,研究了基于人工神经网络的电导率深度成像算法,通过分析两个三层模型的电导率深度成像结果得出,神经网络方法计算时间域航空电磁探测的视电导率精度较高,特别是对高阻层的视电导率计算.     

利用远震接收函数研究黄海周边地区的地壳上地幔结构

利用宽频带流动台站(YSBSN)记录的远震波形数据和远震接收函数方法,反演了黄海东、西两侧地壳上地幔的S波速度结构.结果表明,莫霍面深度在30~38 km之间变化,位于中方一侧的JNN台下方地壳厚度最大,可以归因于华北板块和扬子板块的碰撞;韩方一侧的地壳厚度自北向南逐渐变厚,但仍然难以厘定朝鲜半岛南部潜在碰撞带的位置,这些问题的解决需要更大范围的流动台站观测.由于部分台站位于巨厚的沉积层和多孔的火山岩之上,与浅部构造的相关性使得接收函数表现出较大振幅的混响,从而影响了来自深部结构的转换震相.     

厦门电离层垂测站建设及初步结果

本文介绍了厦门电离层垂直探测站的建设及初步结果.该站选用了加拿大生产的数字测高仪,利用折合偶极天线作为发射和接收天线,采用气象信息专业网和internet网络的两种传输方式,实现了数据实时传输和远程控制.利用试验观测期间获得的2007年8月份首批电离层垂直探测数据,分析发现了厦门地区电离层f_oF2的一些基本特征：白天f_oF2最大值一般出现在地方时14~16点,最大值约5~15 MHz,有较强逐日变化;夜间f_oF2约4MHz左右,逐日变化较小.与最新国际电离层参考模式IRI2007进行了初步对比,发现IRI2007可较好的预报出f_oF2的月中值,但对逐日变化较强的厦门地区电离层f_oF2预报能力较弱.     

基于时-空ETAS模型给出的川滇地区背景地震活动和强震潜在危险区

利用基于时-空传染型余震序列（Epidemic Type Aftershock Sequence, 简称ETAS）模型的随机除丛法,重新审视了2008年5月12日汶川M_S8.0地震前可能存在的长期地震活动异常,研究了川滇地区背景地震活动特征,并评估了当前的强震危险状态.对川滇地区1970年以来的M_L3.0以上的背景地震和丛集地震活动的研究结果表明,该地区地震丛集特征明显、时空分布很不均匀、地震序列常有前震事件.直接将概率值作为地震计数的权重,对地震丛集率空间分布图像分析表明,汶川M_S8.0地震前,龙门山断裂带中南段存在着长期、大范围的地震丛集率低值区,震前该段处于应力闭锁状态.对川滇地区地震丛集率低值区内背景地震与全部地震的累积次数、b值和新定义的Δb等统计参量的分析表明,龙日坝与龙门山断裂带具有地震活动的关联性,川滇地区当前的强震潜在危险区可能是巧家地区和汶川M_S8.0地震破裂尚未穿越的龙门山断裂带南段.此外,还发现b值倾向于反映局部应力场变化,而Δb能较为敏感地给出更大范围应力场的相对变化.     

2014年新疆于田MS7.3地震序列的深度测定

An Ms7. 3 earthquake occurred on February 12, 2014 in Yutian County, Xinjiang Uygur Autonomous Region, which was followed by a series of aftershocks. This paper calculates the depth of the Ms7. 3 earthquake sequence by using the deterministic approach with the seismic phase data from the catalog database of the China Earthquake Networks Center, combined with original seismic wave records from the Digital Seismic Network Center of the Earthquake Administration of Xinjiang Uygur Autonomous Region.     

基于COSMIC掩星数据分析全球NmF2周年和半年变化特征

使用COSMIC掩星提供的NmF2数据,利用傅里叶分析方法,研究全球F2层峰值电子密度的周年和半年分布特征,分析2010年LT12：00 14：00 NmF2周年和半年变化幅度及2008-2011年年平均值变化.结果显示,电离层NmF2周年和半年变化幅度在中高纬地区相对较大;在赤道和低纬地区相对较小,且NmF2以半年变化为主.太阳活动增强期间,NmF2年平均值增大.     

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     

Application of diffracted wave analysis to time‐lapse seismic data for CO2 leakage detection

Time‐lapse seismic analysis is utilized in CO₂ geosequestration to verify the CO₂ containment within a reservoir. A major risk associated with geosequestration is a possible leakage of CO₂ from the storage formation into overlaying formations. To mitigate this risk, the deployment of carbon capture and storage projects requires fast and reliable detection of relatively small volumes of CO₂ outside the storage formation. To do this, it is necessary to predict typical seepage scenarios and improve subsurface seepage detection methods. In this work we present a technique for CO₂ monitoring based on the detection of diffracted waves in time‐lapse seismic data. In the case of CO₂ seepage, the migrating plume might form small secondary accumulations that would produce diffracted, rather than reflected waves. From time‐lapse data analysis, we are able to separate the diffracted waves from the predominant reflections in order to image the small CO₂ plumes. To explore possibilities to detect relatively small amounts of CO₂, we performed synthetic time‐lapse seismic modelling based on the Cooperative Research Centre for Greenhouse Gas Technologies (CO2CRC) Otway project data. The detection method is based on defining the CO₂ location by measuring the coherency of the signal along diffraction offset‐traveltime curves. The technique is applied to a time‐lapse stacked section using a stacking velocity to construct offset‐traveltime curves. Given the amount of noise found in the surface seismic data, the predicted minimum detectable amount of CO₂ is 1000–2000 tonnes. This method was also applied to real data obtained from a time‐lapse seismic physical model. The use of diffractions rather than reflections for monitoring small amounts of CO₂ can enhance the capability of subsurface monitoring in CO₂ geosequestration projects.     

Sensitivity of the surface temperature to changes in total solar irradiance calculated with the WRF model

The temperature sensitivity of the WRF model to changes in Total Solar Irradiance (TSI). The simulations were performed for a region centered over the North Atlantic Ocean, including portions of Eastern North America, Western Europe and Northwest Africa. Four simulations were run with different TSI values. Also, a fifth simulation was performed in which we varied the initial atmospheric conditions, in order to compare the effect on the temperature of both, changes in the TSI and initial atmospheric conditions. Comparing temperature monthly averages we found that changes in TSI and in the initial conditions have a measurable impact on temperature in the region of study. The sensitivity of the model using non-dimensional parameters was also estimated. The numerical experiments show some features that might allow to distinguish between the effects on the temperature due to changes in TSI from those caused by initial conditions. However, TSI changes are of the same order of magnitude than those of disturbances in the initial conditions. We also found that the mean monthly values of temperature over the full grid, did not present significant variations due to changes of either initial conditions or TSI.