镁同位素地球化学研究进展

镁有3个稳定同位素:24Mg、25Mg和26Mg.已有数据表明,自然界Mg同位素组成的变化在陨石中较大.δ26Mg值在-0.71‰～11.92‰之间(相对于DSM3标准),而地球岩石中Mg同位素组成的变化较小,如地幔橄榄岩的δ26Mg变化范围为-3.01‰-1.03‰,沉积碳酸盐岩的δ26Mg变化范围为-4.84‰～-1.09‰,黄土的δ26Mg为-0.60‰.目前,大多数实验室均采用MC-ICP-MS方法来获得高精度的Mg同位素数据.原有Mg同位素国际标准SRM980由于具有不均一性应该废弃,应使用新的DSM3标准.Mg同位素地球化学的研究主要集中在太阳系星云形成过程、记录亏损地幔和地幔交代作用、揭示地质历史时期海水的Mg同位素组成演化、估算大陆风化通量等方面.我国开展的Mg同位素研究还非常少,且尚处于建立Mg同位素分析方法的研究阶段.随着技术的不断发展以及Mg同位素分馏机理的深入研究,Mg同位素的地质应用前景将日趋广泛.     

基于模糊理论的抗差Kalman滤波算法

动态导航与定位的质量取决于对动态载体扰动和观测异常扰动的认知和控制质量。在实践中,观测向量及其动态模型信息均可能存在异常,此时若仍利用标准Kalman滤波,则状态滤波解将极不可靠。在标准Kalman滤波原理的基础上,结合模糊控制理论,提出了一种基于模糊理论的抗差Kalman滤波算法。该方法是依据滤波处理后的数据残差,利用模糊理论构造等价权,从而有效控制粗差对导航解的影响,并用算例验证了该方法的可行性和有效性。     

基于数字剖面的河流阶地与新构造运动研究 ——以内蒙古西拉木伦河河流阶地为例

野外调查发现在内蒙古东部西拉木伦河流域存在12级阶地序列。利用数字剖面野外系统对该河流阶地剖面的记录完成全程数字化采集,并进行数字剖面桌面系统厚度自动计算和剖面图、柱状图自动生成,发现该阶地序列中T7、T8、T9保存完好,而时代最为古老的T12 根据基座玄武岩形成于上新世—早更新世的年龄,其形成时代应为上新世—早更新世。通过计算新构造运动抬升速率,将其形成、演化过程划分为6个阶段。数据表明,自中新世以来,该地区新构造运动存在一定的周期性,在总体上新构造运动的强度逐渐趋于缓和。     

大兴安岭新林镇岩体的同位素特征及其地质意义

新林镇岩体位于大兴安岭北部,主要由花岗闪长岩、石英二长岩、二长花岗岩、碱长花岗岩组成,局部见到细粒辉长岩和闪长岩包体。岩石地球化学和岩石学特征表明,该杂岩体属于高钾钙碱性I型花岗岩。两个花岗闪长岩的锆石LA-ICP-MS U-Pb定年结果分别为(132±3)Ma和(131±3)Ma,属于早白垩世岩浆活动的产物。样品的Sr-Nd同位素组成比较均一,而Hf同位素特征变化较大,其εHf(t)变化介于1.32~8.32之间,Hf模式年龄与Nd模式年龄一致,表明花岗质岩浆主要起源于元古代增生的地壳物质,在岩石形成过程中有地幔组分的贡献。岩体的同位素特征将额尔古纳地块地壳增生时间限定在新元古代,而兴安地块地壳增生发生在新元古代—显生宙,暗示它们具有不同的地壳演化过程。     

南华北盆地阜阳区块古生代地震层序划分及地震相研究

阜阳区块位于南华北盆地的周口坳陷东部,面积约11000km^2,占坳陷面积的三分之一;该盆地按照中、新生界构造特征将其划分为六凹四凸;随着油气勘探的深入和地质研究的深化,笔者利用该区地震剖面进行地震层序研究与划分,并进一步进行了沉积相的研究,为该区古生代的油气勘探提供科学依据。     

Wind tunnel experiments of air flow patterns over nabkhas modeled after those from the Hotan River basin,Xinjiang,China(Ⅱ):vegetated

This paper examines the results of wind tunnel experiments on models of nabkha, based on those studied in the Hotan River basin. Semi-spherical and conical models of nabkhas were constructed at a ratio of 40:1 in light of the on-site observation. Artificial vegetation of simulated Tamarix spp. was put on top of each model. Parameters of the shape, including height, width, and diameter of vegetated semi-spherical and conical nabkha, were measured in the Hotan River basin. Wind tunnel experiments on the semi-spherical and conical nabkha used clean air devoid of additional sediments at five different wind speeds (6–14 m/s) to study the influence of vegetation on airflow patterns. Results of the experiments indicate that vegetation at the top of the nabkhas enhances the surface roughness of the sand mounds, retards airflow over the sand mounds, reduces airflow energy, eliminates erosional pits occurring on the top surface of non-vegetated sand mounds and enhances the range of influence of the vortex that forms on the leeward slope. Vegetation changes the airflow pattern upwind and downwind of the sand mound and reduces the transport of sand away from the nabkha. This entrapment of sediment by the vegetation plays an important role in sustaining the nabkha landscape of the study area. The existence of vegetation makes fine materials in wind-sand flow to possibly deposit, and promotes nabkha formation. The imitative flow patterns of different morphological nabkhas have also been verified by on-site observation in the river basin. __________ Translated from Journal of Desert Research, 2007, 27(1): 15–19 [译自: 中国沙漠]     

从地缘关系视角解析“一带一路”的行动路径

“一带一路”倡议是人类历史上最伟大的全球治理工程,开辟了政治地理学研究的新纪元,为地缘关系研究提供了大舞台。地理学是从时间、空间和自然—社会系统三个维度理解陆地表层过程的科学,对地缘关系研究具有独特的功能和作用。因此,从地理学视角研究地缘关系具有其他学科无法比拟的优势。“一带一路”是当前最具挑战的科学和政策命题,从地缘关系视角研究“一带一路”,需要加强四个方面的结合：① 在科学思维上,需要还原论与系统论思维相结合;② 在科学数据建设上,需要社会人文与自然环境数据相结合;③ 在科学问题选择上,需要社会过程、人文过程、政治过程和自然过程相结合;④ 在研究方法上,需要经验方法、实证方法、系统方法与大数据研究方法相结合。中国地理学者应兼顾政治地理学科建设、地缘关系的学科交叉研究和“一带一路”全球实践开展研究。     

不同水汽环境条件下云凝结核浓度对热带气旋发展影响的数值研究

利用WRF模式模拟在清洁海洋大气和污染大气环境下,气溶胶的云凝结核浓度(Cloud Condensation Nuclei, CCN)对热带气旋的强度变化影响。在污染环境下,云凝结核浓度增多,台风区域云水混合物浓度增大,眼墙附近上升运动减小,而台风外围螺旋雨带对流发展,从而抑制低层入流,台风强度减弱,外围尺度增大。在不同环境场水汽条件下,通过热、动力结构和云微物理量的对比分析,结果表明:环境场水汽条件对台风的发展起到至关重要的作用。当环境场水汽条件较干时,CCN浓度对台风发展影响作用不明显,台风发展缓慢。而在充足水汽条件下,CCN浓度对热带气旋发展有明显的影响。本文结果表明,在考虑污染情形下台风变化,需要综合考虑环境场水汽条件。     

Improved Weather Radar Echo Extrapolation Through Wind Speed Data Fusion Using a New Spatiotemporal Neural Network Model

Weather radar echo extrapolation plays a crucial role in weather forecasting. However, traditional weather radar echo extrapolation methods are not very accurate and do not make full use of historical data. Deep learning algorithms based on Recurrent Neural Networks also have the problem of accumulating errors. Moreover, it is difficult to obtain higher accuracy by relying on a single historical radar echo observation. Therefore, in this study, we constructed the Fusion GRU module, which leverages a cascade structure to effectively combine radar echo data and mean wind data. We also designed the Top Connection so that the model can capture the global spatial relationship to construct constraints on the predictions. Based on the Jiangsu Province dataset, we compared some models. The results show that our proposed model, Cascade Fusion Spatiotemporal Network (CFSN), improved the critical success index (CSI) by 10.7% over the baseline at the threshold of 30 dBZ. Ablation experiments further validated the effectiveness of our model. Similarly, the CSI of the complete CFSN was 0.004 higher than the suboptimal solution without the cross-attention module at the threshold of 30 dBZ.