Frequency analysis of nonstationary annual maximum flood series using the time‐varying two‐component mixture distributions

The most popular practice for analysing nonstationarity of flood series is to use a fixed single‐type probability distribution incorporated with the time‐varying moments. However, the type of probability distribution could be both complex because of distinct flood populations and time‐varying under changing environments. To allow the investigation of this complex nature, the time‐varying two‐component mixture distributions (TTMD) method is proposed in this study by considering the time variations of not only the moments of its component distributions but also the weighting coefficients. Having identified the existence of mixed flood populations based on circular statistics, the proposed TTMD was applied to model the annual maximum flood series of two stations in the Weihe River basin, with the model parameters calibrated by the meta‐heuristic maximum likelihood method. The performance of TTMD was evaluated by different diagnostic plots and indexes and compared with stationary single‐type distributions, stationary mixture distributions and time‐varying single‐type distributions. The results highlighted the advantages of TTMD with physically‐based covariates for both stations. Besides, the optimal TTMD models were considered to be capable of settling the issue of nonstationarity and capturing the mixed flood populations satisfactorily. Copyright © 2016 John Wiley & Sons, Ltd.     

Generation of continuous surface soil moisture dataset using combined optical and thermal infrared images

Surface soil moisture (SSM) is a critical variable for understanding water and energy flux between the atmosphere and the Earth's surface. An easy to apply algorithm for deriving SSM time series that primarily uses temporal parameters derived from simulated and in situ datasets has recently been reported. This algorithm must be assessed for different biophysical and atmospheric conditions by using actual geostationary satellite images. In this study, two currently available coarse‐scale SSM datasets (microwave and reanalysis product) and aggregated in situ SSM measurements were implemented to calibrate the time‐invariable coefficients of the SSM retrieval algorithm for conditions in which conventional observations are rare. These coefficients were subsequently used to obtain SSM time series directly from Meteosat Second Generation (MSG) images over the study area of a well‐organized soil moisture network named REMEDHUS in Spain. The results show a high degree of consistency between the estimated and actual SSM time series values when using the three SSM dataset‐calibrated time‐invariable coefficients to retrieve SSM, with coefficients of determination (R²) varying from 0.304 to 0.534 and root mean square errors ranging from 0.020 m³/m³ to 0.029 m³/m³. Further evaluation with different land use types results in acceptable debiased root mean square errors between 0.021 m³/m³ and 0.048 m³/m³ when comparing the estimated MSG pixel‐scale SSM with in situ measurements. These results indicate that the investigated method is practical for deriving time‐invariable coefficients when using publicly accessed coarse‐scale SSM datasets, which is beneficial for generating continuous SSM dataset at the MSG pixel scale.     

利用双线偏振雷达分析人工防雹作业效果

以北京市平谷区2011年6月11日防雹作业为例,利用双线偏振雷达资料,选取与作业区条件十分接近的云块为对比区,根据回波移动方向和速度,跟踪分析在不同高度上防雹作业前后云体宏观结构特征和粒子相态等微物理变化过程。作业后云体所呈现特征为:1作业区的云顶高度、强回波中心高度迅速下降,对比区变化不明显;2作业区水平反射率Zh减小,差分反射率Zdr、零相关系数ρhv增大,单位差分传播相移Kdp小范围内波动,对比区Zh、Zdr、Kdp变化不明显;ρhv增大;3作业区对流减弱,高层较大冰雹粒子、大雨滴下沉明显,最终以霰粒子为主;而对比区域则对流仍然旺盛,冰雹粒子有增多趋势。以上特征表明防雹作业可有效抑制冰雹胚胎成长为冰雹的过程,通过偏振雷达观测参量可对防雹作业效果进行较好的验证。     

华北陆块晋冀Al- Fe- Au- Pb- Zn- Ag- Cu- 煤成矿带主要地质成矿特征及潜力分析

华北陆块晋冀成矿带是我国重要的金属和能源矿产资源基地,近年来新的找矿进展和预测成果不断涌现,使之成为我国重点找矿地区之一,需要对其开展系统的成矿区划和部署研究工作。本文以新的研究成果和找矿突破为基础,通过综合分析,在该地区划分新的重要成矿部署区带,厘定边界并将其命名为"华北陆块晋冀Al-Fe-Au-Pb-Zn-Ag-Cu-煤成矿带"。结合区域成矿地质背景的综合研究,在区内划分了10个成矿亚带,初步建立了Al-Fe-Au-Pb-Zn-Ag-Cu-煤成矿带成矿谱系,其成矿作用具有多期次发育和多系统控制的特点,在时间演化上表现为多旋回性、继承性、新生性和叠加性特点,主要成矿期有前寒武纪,寒武纪-晚二叠世,晚三叠世-晚白垩世和新生代,其中晚侏罗-早白垩世是内生金属矿床成矿大爆发期。该带产出的矿床类型复杂多样,与岩浆有关成矿作用有岩浆岩型、斑岩型、矽卡岩型、海(陆)相火山岩型、岩浆热液型和石英脉型,变质成矿作用有沉积变质型、绿岩建造型,层控成因矿床有碳酸盐岩中热液型,沉积成矿作用有海(陆)相沉积型、砂矿型、风化壳型矿床等。结合区域找矿进展和潜力评价最新成果,认为本区铝土矿、铁、金、锰、钼、铜、铅锌、煤矿潜力巨大,为下一步勘查部署的主攻矿种,同时在本区划分了26个重点远景区,对研究区下一步矿产勘查部署工作有一定指导意义。     

机动期间的GEO卫星钟差确定方法

分析了多种精密卫星钟差的插值方法,构建了GEO卫星机动模型,并结合插值方法,确定机动期间的GEO卫星钟差,并将结果与i GMAS最终产品进行了比较和分析。结果表明,三次样条插值是用于确定机动期间的GEO卫星钟差的最优方法,其结果精度可达0.01~0.38 ns。     

利用GNSS干涉信号振荡幅度反演土壤湿度

根据干涉效应和GNSS接收机信噪比估计方法,推导了利用GNSS干涉信号幅度进行土壤湿度反演的模型,建模过程考虑了天线增益、土壤介电常数和噪声的影响。提出了使用AMPD算法从含有噪声的归一化干涉功率曲线中提取干涉峰值与谷值,进而反演了土壤介电常数与土壤湿度的方法,并对其进行了仿真。结果表明,利用提取出来的干涉谷值进行反演性能比峰值好,相对稳定准确的卫星仰角范围为5°~25°,湿度大于0.06cm~3/cm~3时反演结果更为准确,标准差在0.01cm~3/cm~3左右波动。     

顾及周期项误差和起点偏差修正的北斗卫星钟差预报

根据北斗卫星导航系统星载原子钟自身的物理特性,采用武汉大学IGS数据中心发布的2016年1月1日至2016年11月1日共306天的事后钟差产品进行谱分析。分析结果表明:北斗卫星导航系统的3类卫星钟都存在一定的周期特性;其中GEO和IGSO卫星钟的主周期相对较为明显;GEO卫星钟的主周期依次为12、24、8和6h;IGSO的主周期为24、12、8和6h;而MEO的3个主周期为12.9、6.4和24h。依据各类原子钟的周期特性,同时对各天之间钟差的起始点偏差进行修正,并利用修正模型对北斗卫星钟差进行预报和精度分析。试验结果表明,改进的预报模型能显著提升北斗卫星的钟差预报精度,北斗卫星钟差24h、12h、6h的平均预报精度分别能达到6.55ns、3.17ns和1.76ns。