700年以来冲绳海槽西南部粘土矿物来源及其对沉积环境的响应

利用X射线衍射（XRD）技术对冲绳海槽南部HOBAB4-S2站700年以来的黏土矿物组成以及结晶学特征进行了研究和分析,并对该区的沉积特征、物质来源以及黏土矿物所记录的东亚季风的演化历史进行了探讨。研究发现冲绳海槽南部HOBAB4-S2站黏土矿物组合总体是以伊利石（59–77 %,平均含量69 %）和绿泥石（11–17 %,平均含量14 %）为主,而蒙脱石（5–23 %,平均含量12 %）和高岭石含量（2–6 %,平均含量4 %）则相对较低。通过黏土矿物研究对物源进行分析,发现冲绳海槽南部研究站位的黏土矿物中,蒙脱石主要是来自于长江或者东海大陆架的再沉积。伊利石,绿泥石以及高岭石主要来自于台湾河流,尤其是兰阳溪。蒙脱石/（伊利石+绿泥石）比值的大小可以用来指示东亚夏季风的强弱变化。1320 AD以来的黏土矿物组合的变化较好地记录了部分中世纪暖期后期、小冰期以及现代暖期3个时期在百年时间尺度上的气候波动。该指标显示,相对于中世纪暖期后期,东亚季风强度在小冰期（1405–1850 AD）和在现代暖期（1955 AD）均存在明显的减弱,指示该时期台湾东北部-冲绳海槽南部地区处于相对湿润强降雨的气候环境。     

Simulations of the Impact of Lakes on Local and Regional Climate Over the Tibetan Plateau

ABSTRACT

Because of the high elevation and complex topography of the Tibetan Plateau (TP), the role of lakes in the climate system over the Tibetan Plateau is not well understood. For this study, we investigated the impact of lake processes on local and regional climate using the Weather Research and Forecasting (WRF) model, which includes a one-dimensional physically based lake model. The first simulation with the WRF model was performed for the TP over the 2000–2010 period, and the second was carried out during the same period but with the lakes filled with nearby land-use types. Results with the lake simulation show that the model captures the spatial and temporal patterns of annual mean precipitation and temperature well over the TP. Through comparison of the two simulations, we found that the TP lakes mainly cool the near-surface air, inducing a decreasing sensible heat flux for the entire year. Meanwhile, stronger evaporation produced by the lakes is found in the fall. During the summer, the cooling effect of the lakes decreases precipitation in the surrounding area and generates anomalous circulation patterns. In conclusion, the TP lakes cool the near-surface atmosphere most of the time, weaken the sensible heat flux, and strengthen the latent heat flux, resulting in changes in mesoscale precipitation and regional-scale circulation.     

MEEMD-Elman神经网络的电离层TEC预报模型

利用IGS中心提供的不同纬度的电离层TEC值,建立基于改进的集总平均经验模态分解(MEEMD)算法和Elman回归神经网络(ERNN)模型相结合的电离层TEC预报模型。实验结果表明,在低、中、高不同纬度采用本文方法预报5 d电离层TEC的预测值的均方根误差最优可达到0.96 TECu,相对精度最优达到95.4%,精度较EMD-ERNN模型及单一ERNN模型有显著提高。     

伊朗盐湖分布和研究现状

伊朗盐湖广泛分布,具有丰富的盐湖矿产资源和盐湖生物资源。综合文献资料,重点分析了伊朗盐湖的分布、研究热点、研究机构和研究人员等现状。伊朗盐湖主要为乌尔米耶湖、Meyghan湖、Fesendooz湖、马哈尔卢盐沼和Tashk湖;干盐滩为Houze Sultan干盐滩、巴赫泰甘干盐滩、Gaav Khooni干盐滩、纳马克干盐滩、Khur干盐滩和Haj Aligholj干盐滩;伊朗南部沿海盐类资源集中分布;盐沙漠为达什特坎维和达什特鲁。分析得出伊朗盐湖研究领域论文呈整体增长态势,伊朗盐湖主要的研究内容为盐湖生态环境、盐湖地质、水资源以及盐湖生物,涉及科研机构和科研人员最多的研究领域为盐湖微生物。     

Strength of Stacking Technique of Ensemble Learning in Rockburst Prediction with Imbalanced Data: Comparison of Eight Single and Ensemble Models

Rockburst is a common dynamic geological hazard, severely restricting the development and utilization of underground space and resources. As the depth of excavation and mining increases, rockburst tends to occur frequently. Hence, it is necessary to carry out a study on rockburst prediction. Due to the nonlinear relationship between rockburst and its influencing factors, artificial intelligence was introduced. However, the collected data were typically imbalanced. Single algorithms trained by such data have low recognition for minority classes. In order to handle the problem, this paper employed stacking technique of ensemble learning to establish rockburst prediction models. In total, 246 sets of data were collected. In the preprocessing stage, three data mining techniques including principal component analysis, local outlier factor and expectation maximization algorithm were used for dimension reduction, outlier detection and outlier substitution, respectively. Then, the pre-processed data were split into a training set (75%) and a test set (25%) with stratified sampling. Based on the four classical single intelligent algorithms, namely k-nearest neighbors (KNN), support vector machine (SVM), deep neural network (DNN) and recurrent neural network (RNN), four ensemble models (KNN–RNN, SVM–RNN, DNN–RNN and KNN–SVM–DNN–RNN) were built by stacking technique of ensemble learning. The prediction performance of eight models was evaluated, and the differences between single models and ensemble models were analyzed. Additionally, a sensitivity analysis was conducted, revealing the importance of input variables on the models. Finally, the impact of class imbalance on the prediction accuracy and fitting effect of models was quantitatively discussed. The results showed that stacking technique of ensemble learning provides a new and promising way for rockburst prediction, which exhibits unique advantages especially when using imbalanced data.

     

Research progress of TiO2 photocathodic protection to metals in marine environment

Corrosion protection has become an important issue as the amount of infrastructure construction in marine environment increased.Photocathodic protection is a promising method to reduce the corrosion of metals,and titanium dioxide(TiO_2) is the most widely used photoanode.This review summarizes the progress in TiO_2 photo gene rated protection in recent years.Different types of semiconductors,including sulfides,metals,metal oxide s,polymers,and other materials,are used to design and modify TiO_2.The strategy to dramatically improve the efficiency of photoactivity is proposed,and the mechanism is investigated in detail.Characterization methods are also introduced,including morphology testing,light absorption,photoelectrochemistry,and protected metal observation.This review aims to provide a comprehensive overview of Ti02 development and guide photocathodic protection.     

矢量瓦片并行构建与分布式存储模型研究

矢量瓦片体积小、生成效率高、支持动态交互,较传统栅格瓦片有诸多优势,是下一代互联网地图服务研究的重点。为了解决当前矢量瓦片研究中处理速度慢,扩展性差等问题,本文利用并行计算框架Spark进行矢量瓦片快速构建,通过自定义转换函数,将原始矢量数据GeoJson转换成mvt瓦片集;对于生成的矢量瓦片集,本文基于分布式内存文件系统Alluxio设计一个瓦片存储模型-VectorTileStore,模型以键值对进行数据存储,瓦片元数据占据前八个键值对,单个瓦片占据一个键值对,在数据写入的同时,基于键构建一个哈希索引,用于快速访问,模型兼容海量瓦片的组织存储,具有很强的扩展性。通过实验结果表明,本文提出的矢量瓦片并行构建算法较单机构建算法运行时间平均减少49.6%,分布式存储模型VectorTileStore较传统方案更适合海量矢量瓦片存储,存取时间效率更高。     

一种削弱信噪混叠的EMD降噪方法

针对经验模态分解(empirical mode decomposition,EMD)降噪过程中存在信号与噪声模态混叠及直接将分界本征模态函数(intrinsic mode function,IMF)分量归入高频噪声造成真实信号被“湮没”等问题,提出一种改进的EMD降噪方法。该方法将经EMD得到的第2个IMF分量至分界IMF分量进行重构,对重构信号进行下一次EMD,获取其中的“真实”信号,多次重复此操作,最后将所有获得的低频信号累加,从而达到降噪的目的。利用2种模拟数据和1种GPS实测高程数据进行实验,模拟数据与实测数据采用不同的评价指标评价降噪效果,结果表明,改进的EMD方法较传统EMD方法降噪效果更佳,验证了该方法的可靠性。     

Preface to the Special Issue on the 14th International Conference on Mesoscale Convective Systems and High-Impact Weather

<正>A mesoscale convective system (MCS) is an organized cluster of thunderstorms known to be the most important convective mode in causing disastrous high-impact weather, such as heavy rainfall, hail, damaging winds, and tornadoes. The small spatial scale and fast temporal evolution of MCSs make their observation and prediction very challenging. East Asia is home to the world’s most prominent monsoon, setting the stage for various severe convective weather events. MCSs and their associated ...     

闽西南地区一次高架雷暴中尺度特征分析

利用常规观测资料、ERA5再分析资料、闪电定位仪资料、福建龙岩双偏振多普勒天气雷达资料,分析了2020年春季闽西南地区的一次强对流过程。结果表明,此次过程发生在地面锋线北侧冷区内,属于典型的高架雷暴过程,产生的灾害性天气包括冰雹、短时强降水、高山站雷雨大风。500 hPa冷平流、850 hPa暖湿平流、925 hPa闽西南地区的假相当位温高能舌为高架雷暴的发生发展提供了有利的环境条件。探空显示逆温层深厚且逆温层顶温度高,暖湿气流沿着锋面被强迫抬升,至逆温层之上饱和假相当位温随高度递减,存在显著的条件不稳定,对流得到快速发展。雷达分析表明,本次高架雷暴冰雹回波自低层快速倾斜向上发展,具有发展快、强度强、降雹时间长的特征。其双偏振参数演变特征与基于地面抬升的雷暴基本一致,降雹阶段表现为CC谷、Z_DR接近零、K_DP小于零。降雹前回波单体中存在强Z_DR和K_DP柱,可以作为冰雹预报的参考,提前量达到半小时。