塔里木盆地东部地区构造特征及其演化

在综合地震、测井、地质等各类资料的基础上,系统分析了塔东地区的构造特征及断裂系统。塔里木盆地是一个典型的多期叠合的复合型盆地,塔东地区主要经历了四个构造演化阶段:基底形成阶段(前震旦纪)、残余古隆起形成阶段(前侏罗纪)、陆内坳陷盆地阶段(侏罗-白垩纪)、内克拉通盆地阶段(新生代)。塔东地区断裂系统的发育具有分组性、分期性的特点,北东向断裂体系形成较早(加里东-印支期),北西向和近南北向断裂体系形成较晚(印支-喜山期)。受断裂系统控制,塔东地区在垂向上可划分为前震旦系基底、古生界、中生界和新生界四大构造层,其中古生界与中新生界构造层在形成、演化上具有巨大的差异性,构造格局截然不同。在明确了构造格局与断裂系统的形成演化的基础上,进一步划分了塔东地区的三级构造单元,从而很好的指导了该区油气勘探工作的深入进展。     

临清坳陷晚古生代煤成气储层沉积学特征

临清坳陷晚古生代地层是胜利油田勘探的重要层位,研究其煤成气储层特征对该区油气资源勘探和能源接替有重要意义。以沉积学、岩石学和地层学为主要研究手段,在总结该区晚古生代沉积体系及沉积相基础上,分析了山西组和石盒子组等地层中的砂岩储层物性特征。研究发现:该区主要存在四大沉积体系,即潮坪沉积体系、障壁-泻湖沉积体系、河控浅水三角洲沉积体系及河流-湖泊复合沉积体系,其中,三角洲分流河道砂体、大型河流、湖泊及湖泊三角洲沉积砂体成为煤成气的有利储层;这些储层的岩石类型主要有长石砂岩、石英砂岩、岩屑砂岩及硬砂岩等,且石英砂岩以奎山段较发育,长石石英砂岩多发育于山西组。      

古土壤干湿特征指示晚古生代气候演化

古土壤是地质历史时期气候变化的重要记录者,通过古土壤记录的信息,可以定性和定量重建深时古环境和古气候,为认识地质历史时期的各种地质事件提供依据。前人大多对特定区域展开古土壤研究,对全球性古土壤数据的整理和古气候、古环境研究相对较少。基于古土壤的干湿情况对古气候环境的指示作用,我们按照植物根迹、根系结构与根化石、黏土矿物以及古土壤的结构构造等依据,将前人报道的古生代(410～255 Ma)古土壤分为干旱古土壤和湿润古土壤两种类型。将古土壤干湿特征与其他气候敏感性沉积物进行对照,显示为干旱古土壤分布与钙质结核以及蒸发岩等指示干旱气候带的敏感性沉积物分布一致,湿润古土壤分布与高岭石、煤以及铝土矿等指示湿润气候带的敏感性沉积物分布一致。干旱古土壤大都分布在晚古生代中低纬度干旱地区;湿润古土壤大都分布在晚古生代赤道附近及中纬度湿润地区。通过以上分析认为,古土壤干湿特征可以作为一个新的气候敏感指标指示古气候环境,进而作为划分气候带的有力依据。     

氟碳钙铈矿结构中晶体缺陷的高分辨电镜研究

用高分辨电子显微术（ＨＲＥＭ）研究了氟碳钙铈矿（ＢＳ）晶体结构中的无序堆垛和体衍交生现象，结果表明该矿物的衍生多晶体是由钙－铈氟碳酸盐矿物中不同组分的氟碳铈矿（Ｂ）和直氟碳钙铈矿（Ｓ）结构单元层沿ｃ方向无序堆垛而成。高分辨结构象揭示出氟碳钙铈矿衍生多晶体的微结构特征。讨论了氟碳钙铈矿结构中的堆垛层错等晶体缺陷现象。     

基于决策树算法的江苏省不同区域短时强降水预报研究

采用2000—2019年13个地级市气象站地面观测站点观测资料以及ERA5再分析资料,基于机器学习中的经典的C4.5算法对江苏省不同区域是否出现短时强降水建立气象要素预报模型。结果表明：基于C4.5算法的决策树预测模型能够较为直观准确的对江苏省不同区域是否发生短时强降水进行预测,并且该决策树模型具有较高的泛化能力。决策树模型利用各区域总样本的前15 a数据样本进行自学习,学习准确率在淮北地区为89.70%,在江淮之间地区为87.89%,在长江以南地区为87.88%,利用各区域剩余5 a样本对该决策树模型的泛化能力进行测试,测试准确率在淮北地区为85.73%,在江淮之间地区为83.39%,在长江以南地区为93.92%。     

High Pressure Response of Rutile Polymorphs and Its Significance for Indicating the Subduction Depth of Continental Crust

α-PbO2-type TiO2 （TiO2-Ⅱ） is an important index mineral for ultrahigh-pressure metamorphism. After the discovery of a natural high-pressure phase of titanium oxide with α-PbO2- structure in omphacite from coesite-bearing eclogite at Shima in the Dabie Mountains, China, a nanoscale （〈2 nm） α-PbO2-type TiO2 has been identified through electron diffraction and high-resolution transmission electron microscopy in coesite-bearing jadeite quartzite at Shuanghe in the Dabie Mountains. The crystal structure is orthorhombic with lattice parameters a = 4.58×10-1 nm, b = 5.42×10-1 nm, c = 4.96×10-1 nm and space group Pbcn. The analysis results reveal that ruffle {011}R twin interface is a basic structural unit of α-PbO2-type TiO2. Nucleation of α-PbO2-type TiO2 lamellae is caused by the displacement of one half of the titanium cations within the {011}R twin slab. This displacement reduces the Ti-O-Ti distance and is favored by high pressure. The identification of α- PbO2-type TiO2 in coesite-bearing jadeite quartzite from Shuanghe, Dabie Mountains, provides a new and powerful evidence of ultrahigh-pressure metamorphism at 4--7 GPa, 850℃-900℃, and implies a burial of continental crustal rocks to 130-200 kilometers depth or deeper. The α-PbO2-type TiO2 may be a useful indicator of the pressure and temperature in the diamond stability field.     

济宁煤田济北矿区构造展布规律分析

通过对济宁北矿区区域构造特征以及区内各井田地质资料的统计研究分析,系统总结了该矿区断层构造的发育特征和展布组合规律。研究发现：在区域上,研究区构造以断裂为主,且规模和强度较大,褶皱强度小,均为宽缓褶皱。矿区内的主要断裂有两组,一组为SN向的区域性断裂,构成井田边界,另一组为由其附生的NE向断裂,使其开采地质条件复杂化。区内NE向褶皱发育,多呈背、向斜相间分布。     

Exploration of optimal time steps for daily precipitation bias correction: a case study using a single grid of RCM on the River Exe in southwest England

ABSTRACT

Bias correction is a necessary post-processing procedure in order to use regional climate model (RCM)-simulated local climate variables as the input data for hydrological models due to systematic errors of RCMs. Most of the present bias-correction methods adjust statistical properties between observed and simulated data based on a predefined duration (e.g. a month or a season). However, there is a lack of analysis of the optimal period for bias correction. This study attempted to address the question whether there is an optimal number for bias-correction groups (i.e. optimal bias-correction period). To explore this we used a catchment in southwest England with the regional climate model HadRM3 precipitation data. The proposed methodology used only one grid of RCM in the Exe catchment, one emissions scenario (A1B) and one member (Q0) among 11 members of HadRM3. We tried 13 different bias-correction periods from 3-day to 360-day (i.e. the whole of one year) correction using the quantile mapping method. After the bias correction a low pass filter was used to remove the high frequencies (i.e. noise) followed by estimating Akaike’s information criterion. For the case study catchment with the regional climate model HadRM3 precipitation, the results showed that a bias-correction period of about 8 days is the best. We hope this preliminary study on the optimum number bias-correction period for daily RCM precipitation will stimulate more research to improve the methodology with different climatic conditions. Future efforts on several unsolved problems have been suggested, such as how strong the filter should be and the impact of the number of bias correction groups on river flow simulations.

Editor M.C. Acreman Associate editor S. Kanae