福建尤溪梅仙矿床闪锌矿中黄铜矿交生体的交代成因

福建尤溪梅仙块状硫化物矿床中的闪锌矿经５０％ＨＮＯ３浸蚀后发现,微米级的黄铜矿交生体呈乳滴状,棒条状,蠕虫状等沿闪锌矿解理面,双晶面和颗粒边界,裂隙等处分布,并且黄铜矿交生体所占体积均在５％以上,因上闪锌矿中有限的Ｃｕ的溶解度使出溶无法解释黄鲷矿交生体的成因,交生体的结构特征以其与黄铜矿脉的关系暗示其可能是交代成因。而对横切黄铜矿乳滴的电子探针分析中铁含量特征的研究,证实梅仙矿区闪锌矿中的黄铜矿交     

黄河三角洲地质遗迹景观特征与发展趋势

黄河三角洲国家级地质遗迹保护区总面积15．3万hm2,与国内外其他河流三角洲沉积相比,黄河三角洲的沉积环境和沉积模式有其独特之处,主要是黄河三角洲平原在发展演化过程中形成的各种河流沉积地貌景观、微地貌景观和河口地貌景观。研究和保护这些地质地貌遗迹,对了解黄河三角洲的演化过程、发展趋势以及提出合理的保护措施有重要意义。     

倾斜涡度的发展与云南冬季强降水

应用倾斜涡度发展理论,对云南的一次冬季强降水天气进行诊断分析。结果表明：强降水发生在θｅ 陡立密集区内;倾斜涡度发展和条件性对称不稳定是形成强降水的重要因子;大气的弱位势稳定和强斜压性有利于云南冬季强降水的发生。     

利用地基遥感方法监测大气中汽态、液态水含量分布特征的分析

文章根据1992～1994年4～6月间利用北京大学研制的新一代双通道共天线地基微波辐射计在河北省石家庄等地的监测资料,分析了晴空、有云无雨两种天气条件下,大气中积分汽态水、液态水含量的分布特征,两种相态大气含水量的相对分布特点。结果表明,在有云无雨的天气条件下,云中液态水积分含量仅占大气中总水量的1%,说明作为人工增雨资源条件的云中液态水含量仅占大气总水量的一小部分。因此,分析认为,以往通常采用大气中水汽含量评估人工增雨资源条件的方法,存在着不确切性。     

太原大气能见度影响因子分析及能见度预报

利用2017年1月—2019年12月太原地区逐时气象资料,分析了能见度及其主要影响因子的变化特征,并对两次低能见度过程进行深入分析,构建了能见度预报模型并进行检验,结果表明:(1)从空间分布看,太原北部能见度明显高于南部地区。从时间分布看,太原地区平均能见度最大值出现在5月,最小值出现在1月;日间最低值出现在06:00(北京时,下同),冬季略向后推移,最高值出现在15:00前后。(2)2017—2019年太原地区低能见度分别出现93、84、79 d;低能见度发生时,干霾、湿霾发生频率分别为59.27%、40.73%;湿霾发生时,能见度降低更加明显。(3)所选个例中,能见度均随各影响因子有所起伏,干霾、湿霾过程中能见度分别与颗粒物浓度、相对湿度变化一致。(4)采用神经网络方法构建太原地区能见度预报模型,预报模型相关系数为0.81,均方根为4.43 km,平均绝对误差为17.39%,轻微级能见度的TS评分为87%。神经网络方法对太原地区能见度预报具有较高的参考价值。     

淮河流域大气环流型在冬季气温预测中的应用

应用Lamb-Jenkinson大气环流分型方法,根据由1970—2012年NCEP/NCAR逐日海平面气压场计算得到的环流指数,对淮河流域的环流进行分型。分析了冬季主要环流型和气温的分布特征及两者的联系,并以环流指数和主要环流型为预测因子,结合经验正交函数分解(EOF)方法和逐步回归方法,建立了淮河流域冬季气温距平的预测模型。结果表明,淮河流域冬季的主要环流型是东北风型、东风型、反气旋环流型以及东北风、东风配合下的反气旋性环流型,划分的环流型符合实际情况,这些环流型具有显著的年际和年代际变化特征。通过对预测模型进行后报试验和独立预报试验,表明该模型具有一定的预报技巧。     

关于积云增雨和实施方案的探讨

在综合雷雨云式的积云降水特点和归纳观测及理论结果的基础上,用数值模拟研究了阵雨形成机制,发现雷雨云式的积云结构类似于雹云,也存在着水平风“零域”和成雨“穴道”,大粒子群向这里集中并累积,然后再下泻成阵雨。据此提出了积云人工增雨的动力学根据和设计实施方案的要领,并给出了积云人工增雨作业部位、时机的概念模型。     

大型湖库滨岸带蓝藻水华堆积风险评估——以巢湖为例

淡水湖库富营养化与蓝藻水华是全球性的突出水环境问题,尤其是滨岸带严重蓝藻水华堆积甚至造成了水体黑臭、威胁饮用水安全等严重危害,科学评估滨岸带蓝藻水华堆积风险、精准识别蓝藻水华易堆积区域是水环境管理与研究中亟待解决的关键科学问题.本研究以我国长江中下游的大型浅水富营养化湖泊巢湖为研究对象,依托流域水文与湖泊水动力模拟、遥...     

The effects of intermediate principle stress on the mechanical behavior of transversely isotropic rocks: Insights from DEM simulations

The discrete element method (DEM) is used to study the response of anisotropic rocks under true triaxial testing. Numerical samples of seven different bedding orientations (β = 0^o, 15^o, 30^o, 45^o, 60^o, 75^o, and 90^o) are created. Six series of test simulations (σ₃ = 0, 10, 30, 50, 70, and 100 MPa) are conducted on each sample, with five different σ₂ values, varied from σ₃ to σ₁. The effects of anisotropy and intermediate stress on the peak strength, brittle-ductile transition, and degree of anisotropy are subsequently explained through underlying micromechanics. Results show a “fan-shaped” variation of the peak strength with σ₂, displaying an ascending-then-descending trend. An increasing brittleness with σ₂ is observed at lower confining pressures for all, but medium anisotropy angles. For higher confining pressures, increasing ductility with σ₂ is seen for every anisotropy angle. A U-shaped variation of peak strength with anisotropy angles is noted that flattens under high intermediate stress. Hence, for numerical models of Posidonia shale under normalized σ₂ higher than 0.76, the anisotropy effect is found to be negligible. Micromechanical analyses reveal that the stress asymmetry, suppression of weak plane action as well as the localization and coalescence of microcracks in the intact rock matrix, due to σ₂, are the contributors towards the obtained trends. Since existing failure criteria do not weigh in these features in geotechnical assessments, this paper helps future studies by providing a deeper understanding of these effects and a comprehensive data set for the analyses of anisotropic rocks under polyaxial stress conditions.     

Towards optimal observational array for dealing with challenges of El Niño-Southern Oscillation predictions due to diversities of El Niño

This paper investigates the optimal observational array for improving the initialization of El Niño-Southern Oscillation predictions by exploring the sensitive areas for target observations of two types of El Niño predictions. The sensitive areas are identified by calculating the optimally growing errors (OGEs) of the Zebiak–Cane model, as corrected by the optimal forcing vector that is determined by assimilating the observed sea surface temperature anomalies (SSTAs). It is found that although the OGEs have similar structures for different start months of predictions, the regions covered by much large errors for the SSTA component tend to locate at different zonal positions and depends on the start months. Furthermore, these regions are also in difference between two types of El Niño events. The regions covered by large errors of OGEs represent the sensitive areas for target observations. Considering the dependence of the sensitive areas on related El Niño types and the start months of predictions, the present study propose a quantitative frequency method to determine the sensitive areas for target observations associated with two types of El Niño predictions, which is expected to be applicable for both types of El Niño predictions with different start months. As a result, the sensitive areas that describe the array of target observations are presented with a reversal triangle-like shape locating in the eastern Pacific, specifically the area of 120°W–85°W, 0°S–11°S, and an extension to the west along the equator and then gathering at the 180° longitude and the western boundary. “Hindcast” experiments demonstrated that such observational array is very useful in distinguishing two types of El Niño and superior to the TAO/TRITON array. It is therefore suggested that the observational array provided in the present study is towards the optimal one and the original TAO/TRITON array should be further optimized when applied to predictions of the diversities of El Niño events.