《南岭成矿带成矿规律图》研编创新点及其找矿意义

由中国地质科学院矿产资源所编制出版的《南岭成矿带成矿规律图（1∶80万）》,是迄今为止矿种最全、资料最新、信息量最大的全面反映我国南岭勘查成果与成矿规律的区带级别（Ⅲ级成矿单元）成矿规律图。该图件研编实现了4大创新点：① 涵盖了南岭已发现的2903处独立矿产地,包括能源、金属、非金属和水气矿产等4大类的76个矿种,实现了南岭成矿带矿种与矿产地的全覆盖;② 归并了地质底图的地层并淡化显示,突出华南岩体、隐伏岩体的特色,使得不同构造—建造层地质单元的分布格局一目了然;③ 实现了矿产地、规模、类型、时代、成矿系列五位一体的综合图例设计,矿产地表达更简洁、直观;④ 综合成矿系列图、表、成矿体系图、剖面图等,以区域规律图编制的新思路和新方法,更集中反映和彰显南岭成矿带最新科研成果。该图件的研编有助于直观展示南岭成矿带矿产的时空分布格局,深入总结成矿规律,科学圈定重要找矿远景区,对于全面指导南岭的地质找矿工作具有重要的意义。     

可解释性长短期记忆模型用于预测湖泊总磷浓度变化

对湖泊总磷的变化预测和来源识别对水资源调度和流域生态治理有着重要的意义,然而复杂的生化反应和水动力条件导致的非平稳性给湖泊总磷浓度的准确预测带来极大的困难。为克服这一挑战,本文引入了基于加权回归的季节趋势分解(seasonal and trend decomposition using Loess,STL)技术和夏普利加法(SHapley additive exPlanations,SHAP)结合长短期记忆网络(long short-term memory neural network,LSTM)和门控循环单元(gated recurrent unit,GRU)构建了一个可解释的预测框架,以增强对湖泊总磷浓度演变的预测并提高其可解释性。研究表明:(1)在骆马湖总磷浓度的预测中,该框架拥有较好的预报精度(R²=0.878),优于LSTM和卷积长短期记忆模型(convolutional neural networks and long short term memory network,CNN-LSTM)。当预测时间步长增加到8 h时,该框架有效提高了总磷浓度的预测精度,平均相对误差和均方根误差分别降低了47.1%和33.3%。从预测趋势来看,骆马湖在汛期的总磷平均浓度为0.158 mg/L,相较于非汛期的平均浓度,增加了202.1%。(2)运河来水是骆马湖总磷浓度最重要的影响因素,贡献权重为60.0%,并且不同断面(三湾、三场)的污染源受水动力、气象等因素的影响存在显著的时空差异。本文凸显了神经网络模型在预警水体污染方面的可实施性,并且为提高传统神经网络的学习能力和可解释性的开发与验证提供了重要方向。     

“海棠”台风远距离强降水分析

对2005年"海棠"台风倒槽造成河南特大暴雨过程的湿位涡分析结果表明:倾斜涡度发展是暴雨产生和加强的重要机制之一,暴雨产生在eθ线陡立密集区内,湿位涡在这次暴雨过程中边界层内925hPa具有MPV1>0、MPV2<0的特征,此次暴雨产生在正的MPV1中心附近,有利的地形条件在一定程度上增加了降水量。     

西藏墨竹工卡县邦铺钼(铜)矿床辉钼矿稀土—微量元素特征及对成矿流体性质的指示

文章以西藏墨竹工卡县邦铺钼(铜)矿床辉钼矿为研究对象,采用高精度电感耦合等离子质谱( ICPMS)对辉钼矿进行了稀土和微量元素测试.测试结果显示辉钼矿具有轻稀土富集的右倾配分模式,轻重稀土内部分馏明显.辉钼矿稀土元素不同程度地出现铕负异常和铈负异常现象,分析得出其铕负异常可能是继承了成矿流体自身铕亏损的特征,而铈负异常...     

低密度钻井液DMZ的开发与应用

钻井液是钻探施工的血液,低密度无固相钻井液ＤＭＺ,能有效解决小口径绳索取心钻探中出现的钻杆内结泥皮、岩粉携带能力差、失水量高等问题。     

去除EOS/MODIS 1B数据中"弯弓"效应的方法

分析了中分辨率成像光谱仪EOS／MODIS的扫描方式,在此基础上研究了EOS／MODIS1B数据集“弯弓”效应的成因。对EOS／MODIS1B数据02级产品HDF文件的格式进行了探讨,并以250m分辨率资料为例,在2002年7月13日10时的MODIS资料中选取鄱阳湖以北部分地区,读取其数据进行插值、Lambert投影、重采样等处理,从而消除了影响资料使用的“弯弓”效应,同时也完成了对EOS／MODIS数据的几何校正,取得了一定的效果,为EOS／MODIS遥感资料在今后得以广泛应用作了有益的尝试。     

气候系统可预报性的全局研究

胞映射方法是对非线性系统进行全局分析的强有力工具。文中基于一个最大简化的地－气耦合模式,引入胞映射全局分析方法,对气候系统的可预报性进行了全局的研究。气候系统存在最大可预报期限,对于超过逐日预报可预报期限后的预报,用胞映射思想证明了平均值的可预报性,并得到了定量的结果。研究表明,耦合机制具有延长可预报期限的作用,观测精度的提高亦可延长可预报期限     

Weak ENSO Asymmetry Due to Weak Nonlinear Air–Sea Interaction in CMIP5 Climate Models

State-of-the-art climate models have long-standing intrinsic biases that limit their simulation and projection capabilities.Significantly weak ENSO asymmetry and weakly nonlinear air–sea interaction over the tropical Pacific was found in CMIP5(Coupled Model Intercomparison Project, Phase 5) climate models compared with observation. The results suggest that a weak nonlinear air–sea interaction may play a role in the weak ENSO asymmetry. Moreover, a weak nonlinearity in air–sea interaction in the models may be associated with the biases in the mean climate—the cold biases in the equatorial central Pacific. The excessive cold tongue bias pushes the deep convection far west to the western Pacific warm pool region and suppresses its development in the central equatorial Pacific. The deep convection has difficulties in further moving to the eastern equatorial Pacific, especially during extreme El Ni o events, which confines the westerly wind anomaly to the western Pacific. This weakens the eastern Pacific El Ni o events, especially the extreme El Ni o events, and thus leads to the weakened ENSO asymmetry in climate models. An accurate mean state structure(especially a realistic cold tongue and deep convection) is critical to reproducing ENSO events in climate models. Our evaluation also revealed that ENSO statistics in CMIP5 climate models are slightly improved compared with those of CMIP3. The weak ENSO asymmetry in CMIP5 is closer to the observation. It is more evident in CMIP5 that strong ENSO activities are usually accompanied by strong ENSO asymmetry, and the diversity of ENSO amplitude is reduced.     

Past,present and future climatic forcing due to greenhouse gases

An advanced one-dimensional radiative-convective model (RCM) is used to estimate the past, present and fu-ture climatic forcings induced by greenhouse gases of anthropogenic origin, such as CO2, CH4, N2O and CFCs, in this paper. The results show that the decadal climatic forcing for the last decade is one-order bigger than that prior to the year 1900, and in the case of no control on the emission of the greenhouse gases the climatic forcing for the year 2100 will be almost 4 times as much as now.     

Land surface temperature shaped by urban fractions in megacity region

The influence of spatial scales on surface fluxes is an interesting but not fully investigated question. This paper presents an analysis on the influence of spatial scales on surface fluxes in the north Tibetan Plateau based on eddy covariance (EC) and large aperture scintillometer (LAS) data at site Nagqu/BJ, combined with the land surface temperature (LST) and normalized difference vegetation index (NDVI) of moderate-resolution imaging spectroradiometer (MODIS). The analysis shows that sensible heat fluxes calculated with LAS data (H_LAS) agree reasonably well with sensible heat fluxes calculated with EC data (H_EC) in the rain and dry seasons. The difference in their footprints due to the wind direction is an important reason for the differences in H_EC and H_LAS. The H_LAS are statistically more consistent with H_EC when their footprints overlap than when their footprints do not. A detailed analysis on H_EC and H_LAS changes with net radiation and wind direction in rain and dry season indicates that the spatial heterogeneity in net radiation created by clouds contributes greatly to the differences in H_EC and H_LAS in short-term variations. A significant relationship between the difference in footprint-weighted averages of LST and difference in H_EC and H_LAS suggests that the spatial heterogeneity in LST at two spatial scales is a reason for the differences in H_EC and H_LAS and that LST has a positive correlation with the differences in H_EC and H_LAS. A significant relationship between the footprint-weighted averages of NDVI and the ratio of sensible heat fluxes at two spatial scales to net radiation (H/Rn) in the rain season supports the analysis that the spatial heterogeneity in canopy at two spatial scales is another reason for differences in H_EC and H_LAS and that canopy has a negative correlation with (H/Rn). An analysis on the influence of the difference in aerodynamic roughness lengths at two spatial scales on sensible heat fluxes shows that the influence is greater in the dry season and smaller in the rain season because the ratio of z_{0m_LAS} to z_{0m_EC} is big in the dry season and is close to 1.0 in the rain season. This study on spatial scales on surface fluxes in the Tibetan Plateau will be helpful in analyzing and understanding its influence on climate.