塔里木板块东北缘坡北杂岩体矿物成分和铂族元素特征:对硫化物熔离和构造环境的约束

坡北杂岩体位于塔里木板块东北缘北山裂谷带,主要由橄榄岩相、单辉辉石岩相、二辉岩相、辉长岩相、苏长岩相和辉长苏长岩相组成。坡一岩体中硫化物矿体赋存于超镁铁质岩中,而坡东岩体中硫化物矿体赋存于辉长苏长岩相中。坡一和坡东岩体不同岩相中单斜辉石的MgO和CaO含量、斜长石的An值和SiO_2含量连续变化且呈负相关,说明二者可能是同一原始岩浆分离结晶的产物。根据前人计算的原始岩浆成分,我们利用MELTS软件模拟了坡北杂岩体的分离结晶过程。结果表明矿物结晶顺序为:橄榄石→橄榄石+单斜辉石→橄榄石+单斜辉石+斜长石→单斜辉石+斜长石+斜方辉石,与岩相观察一致。坡北杂岩体原始岩浆经过20%分离结晶达到S饱和而发生早期硫化物熔离,形成坡一岩体中矿体。因此,在利用具有最高Fo值(90.9mol%)的橄榄石成分进行的模拟中,坡一岩体早期结晶的纯橄榄岩中橄榄石成分与分离结晶趋势线一致,而斜长橄榄岩中橄榄石成分低于趋势线,可能形成于早期硫化物熔离之后。随后岩浆中S再一次不饱和,但坡一岩体橄榄单辉辉石岩和辉长岩中橄榄石Fo和Ni含量在分离结晶趋势线之下,同时坡东岩体不含矿岩石中铂族元素总量主要在8.9×10~(-9)～29.0×10~(-9)之间,且相对于Ni和Cu明显亏损,说明在岩浆分离结晶晚期再次发生硫化物熔离,而且可能是地壳混染引起的,并形成了坡东岩体中的硫化物矿体。坡东岩体橄榄二辉岩和橄榄辉长苏长岩中橄榄石Fo值(74.5mol%～81.0mol%)较低,但变化范围较大,且Fo和Ni呈负相关关系,这可能是由于橄榄石和硫化物熔体在不平衡状态下发生成分交换造成的。坡北杂岩体超镁铁质岩石中单斜辉石Ti O2含量为0.21%～0.83%,阳离子中呈四次配位的Al(AlZ)为0.8mol%～7.8mol%,与裂谷环境堆晶岩中单斜辉石成分相似。因此,坡北杂岩体可能形成于和塔里木二叠纪地幔柱活动相关的裂谷环境。然而,超镁铁质岩石全岩Nd同位素指示其来源于亏损地幔,并不是地幔柱物质熔融的直接产物。纯橄榄岩和异剥橄榄岩La/Sm,Sm/Yb和La/Yb比值指示其源区为尖晶石二辉橄榄岩地幔。因此,坡北杂岩体源区应为浅部以尖晶石二辉橄榄岩为主的亏损岩石圈地幔,地幔柱在源区部分熔融过程中提供了大量的热。     

伊犁盆地尼勒克地区中二叠世陆相地层碎屑物源分析及其对西天山构造演化过程的约束

西天山在二叠纪时期的大地构造环境有岛弧成因和大陆裂谷成因两种不同的观点,伊犁盆地尼勒克地区中二叠统陆相红层的研究是解决上述争议的关键之一。该段地层自下而上是一套由冲洪积扇相、河流相、浅湖相和半深湖相组成的湖侵序列。本文综合该套地层的古水流、砾岩砾石成分与砂岩碎屑组分、重矿物组合、碎屑岩地球化学以及石榴子石化学特征等方面的研究,认为尼勒克盆地中二叠统陆相红层的物源复杂多样,包括超镁铁质-镁铁质岩、安山岩、英安岩、流纹岩、矽卡岩、片麻岩、灰岩和碎屑岩等不同岩石类型,记录了西天山造山带的构造剥蚀与再沉积过程。结合下二叠统乌郎组双峰式火山岩以及区域性角度不整合等资料的综合分析,本研究认为尼勒克地区中二叠世盆地形成于造山后伸展的大地构造背景。     

兴蒙造山带晚古生代伸展过程:来自二连浩特东北部石炭-二叠系沉积地层的证据

本文选取内蒙古二连浩特东北部本巴图地区,通过对石炭-二叠纪沉积典型地层的剖面测制、锆石U-Pb年代学及Hf同位素分析,查明其充填层序、沉积环境及物质来源,并进一步探讨了兴蒙造山带晚古生代伸展构造的演化过程。来自石炭-二叠纪地层的3个凝灰岩样品中最年轻峰值年龄分别为298Ma、302Ma、303Ma,表明其形成时代为303～298Ma,即晚石炭世-早二叠世,应归属格根敖包组。沉积环境研究揭示石炭-二叠纪沉积地层发育两个从前三角洲相到三角洲前缘相的旋回,其沉积速率估算结果与伸展构造背景下的裂谷盆地沉积速率相似。锆石Hf同位素特征分析表明,从约400Ma到约300Ma,其演化趋势具有新生地壳明显增多的特点,揭示从早中古生代年轻造山带形成到晚古生代伸展作用发生过程中的变化。结合区域地质研究,晚古生代北造山带的沉积演化和伸展作用过程可分为四个阶段:第一阶段为磨拉斯盆地形成,以盆地南缘泥鳅河组为代表;第二阶段为贺根山伸展带发育阶段,形成超基性-基性-酸性的岩浆组合;第三阶段为稳定的陆表海环境,以晚石炭世本巴图和阿木山组的碎屑岩-碳酸盐岩组合为代表;第四阶段是晚石炭世-早二叠世的第二次伸展,发育格根敖包组火山-沉积岩系组成的三角洲沉积,具有陆内裂谷盆地性质。     

几内亚福雷卡里亚YML铁矿区的富铁矿床地质特征及找矿前景探讨

YML铁矿区位于几内亚福雷卡里亚省,富铁矿以条带状赤铁矿和铁角砾岩矿为主。矿区内共发育7条矿体,条带状赤铁矿体6条,铁角砾岩矿体1条。条带状赤铁矿体赋存部位多为向形地段,次级紧密褶皱发育,沿走向和倾向有逐渐变薄和尖灭的趋势;铁角砾岩矿体覆盖于地表,以风化壳的形式出现。矿床类型属复合类型,即海底热液喷气沉积叠加后期构造变质型+风化淋滤型。该区具备铁矿形成和保存的地质条件,且已发现具一定储量、品位较高的条带状赤铁矿和大面积的铁角砾岩分布区,区内铁矿找矿远景较好。     

IPCC AR6报告解读：气候系统对太阳辐射干预响应

IPCC第六次评估报告（AR6）第一工作组报告评估了太阳辐射干预（Solar radiation modification,SRM）对气候系统和碳循环的影响。在大幅度减排基础上,太阳辐射干预有潜力作为应对气候变化的备用措施。目前,对于太阳辐射干预气候影响的评估都是基于模式模拟结果。评估主要结论如下：太阳辐射干预可以在全球和区域尺度上抵消一部分温室气体增加造成的气候变化（高信度);但是太阳辐射干预无法在全球和区域尺度上完全抵消温室气体增加引起的气候变化（几乎确定);有可能通过适当的太阳辐射干预设计,同时实现多个温度变化减缓目标（中等信度);在高强度温室气体排放情景下,如果太阳辐射干预实施后突然终止,并且这种终止长时间持续,将会造成快速的气候变化（高信度);如果在减排和CO₂移除的情况下,太阳辐射干预的实施强度逐渐减小至零,将显著降低太阳辐射干预突然终止产生的快速气候变化风险（中等信度);太阳辐射干预会通过降温作用,促进陆地和海洋对大气CO₂的吸收（中等信度),但是太阳辐射干预无法缓解海洋酸化（高信度);太阳辐射干预对其他生物化学循环影响的不确定性大。由于对云-气溶胶-辐射过程的相互作用和微物理过程认知有限,目前对平流层气溶胶注入、海洋低云亮化、高层卷云变薄等太阳辐射干预方法的冷却潜力和气候效应的认知还有很大的不确定性。     

A CRPS-Based Spatial Technique for the Verification of Ensemble Precipitation Forecasts

Traditional precipitation skill scores are affected by the well-known“double penalty”problem caused by the slight spatial or temporal mismatches between forecasts and observations. The fuzzy (neighborhood) method has been proposed for deterministic simulations and shown some ability to solve this problem. The increasing resolution of ensemble forecasts of precipitation means that they now have similar problems as deterministic forecasts. We developed an ensemble precipitation verification skill score, i.e., the Spatial Continuous Ranked Probability Score (SCRPS), and used it to extend spatial verification from deterministic into ensemble forecasts. The SCRPS is a spatial technique based on the Continuous Ranked Probability Score (CRPS) and the fuzzy method. A fast binomial random variation generator was used to obtain random indexes based on the climatological mean observed frequency, which were then used in the reference score to calculate the skill score of the SCRPS. The verification results obtained using daily forecast products from the ECMWF ensemble forecasts and quantitative precipitation estimation products from the OPERA datasets during June-August 2018 shows that the spatial score is not affected by the number of ensemble forecast members and that a consistent assessment can be obtained. The score can reflect the performance of ensemble forecasts in modeling precipitation and thus can be widely used.     

The Digital Belt and Road program in support of regional sustainability

The Belt and Road initiative has a significant focus on infrastructure, trade, and economic development across a vast region, and it also provides significant opportunities for sustainable development. The combined pressure of climate variability, intensified use of resources, and the fragility of ecosystems make it very challenging, however, to achieve future sustainability. To develop the path in a sustainable way, it is important to have a comprehensive understanding of these issues across nations and evaluate them in a scientific and well-informed approach. In this context, the Digital Belt and Road (DBAR) program was initiated as an international venture to share expertise, knowledge, technologies, and data to demonstrate the role of Earth observation science and technology and big Earth data applications to support large-scale development. In this paper, we identify pressing challenges, present the research priorities and foci of the DBAR program, and propose solutions where big Earth data can make significant contributions. This paper calls for further joint actions and collaboration to build a digital silk road in support of sustainable development at national, regional and global levels.     

Geometric-constrained multi-view image matching method based on semi-global optimization

Targeting at a reliable image matching of multiple remote sensing images for the generation of digital surface models, this paper presents a geometric-constrained multi-view image matching method, based on an energy minimization framework. By employing a geometrical constraint, the cost value of the energy function was calculated from multiple images, and the cost value was aggregated in an image space using a semi-global optimization approach. A homography transform parameter calculation method is proposed for fast calculation of projection pixel on each image when calculating cost values. It is based on the known interior orientation parameters, exterior orientation parameters, and a given elevation value. For an efficient and reliable processing of multiple remote sensing images, the proposed matching method was performed via a coarse-to-fine strategy through image pyramid. Three sets of airborne remote sensing images were used to evaluate the performance of the proposed method. Results reveal that the multi-view image matching can improve matching reliability. Moreover, the experimental results show that the proposed method performs better than traditional methods.     

Super-resolution enhancement of UAV images based on fractional calculus and POCS

Abstract

A super-resolution enhancement algorithm was proposed based on the combination of fractional calculus and Projection onto Convex Sets (POCS) for unmanned aerial vehicles (UAVs) images. The representative problems of UAV images including motion blur, fisheye effect distortion, overexposed, and so on can be improved by the proposed algorithm. The fractional calculus operator is used to enhance the high-resolution and low-resolution reference frames for POCS. The affine transformation parameters between low-resolution images and reference frame are calculated by Scale Invariant Feature Transform (SIFT) for matching. The point spread function of POCS is simulated by a fractional integral filter instead of Gaussian filter for more clarity of texture and detail. The objective indices and subjective effect are compared between the proposed and other methods. The experimental results indicate that the proposed method outperforms other algorithms in most cases, especially in the structure and detail clarity of the reconstructed images.     

Modelling coastal land use change by incorporating spatial autocorrelation into cellular automata models

This paper presents a spatial autoregressive (SAR) method-based cellular automata (termed SAR-CA) model to simulate coastal land use change, by incorporating spatial autocorrelation into transition rules. The model captures the spatial relationships between explained and explanatory variables and then integrates them into CA transition rules. A conventional CA model (LogCA) based on logistic regression (LR) was studied as a comparison. These two CA models were applied to simulate urban land use change of coastal regions in Ningbo of China from 2000 to 2015. Compared to the LR method, the SAR model yielded smaller accumulated residuals that showed a random distribution in fitting the CA transition rules. The better-fitting SAR model performed well in simulating urban land use change and scored an overall accuracy of 85.3%, improving on the LogCA model by 3.6%. Landscape metrics showed that the pattern generated by the SAR-CA model has less difference with the observed pattern.