A Coupled Ice-Ocean Model in the Pan-Arctic and North Atlantic Ocean: Simulation of Seasonal Cycles

A coupled ice-ocean model is configured for the pan-Arctic and northern North Atlantic Ocean with a 27.5 km resolution. The model is driven by the daily atmospheric climatology averaged from the 40-year NCEP reanalysis (1958–1997). The ocean model is the Princeton Ocean Model (POM), while the sea ice model is based on a full thermodynamical and dynamical model with plastic-viscous rheology. A sea ice model with multiple categories of thickness is utilized. A systematic model-data comparison was conducted. This model reasonably reproduces seasonal cycles of both the sea ice and the ocean. Climatological sea ice areas derived from historical data are used to validate the ice model performance. The simulated sea ice cover reaches a maximum of 14 × 10⁶ km² in winter and a minimum of 6.7 × 10⁶ km² in summer. This is close to the 95-year climatology with a maximum of 13.3 × 10⁶ km² in winter and a minimum of 7 × 10⁶ km² in summer. The simulated general circulation in the Arctic Ocean, the GIN (Greenland, Iceland, and Norwegian) seas, and northern North Atlantic Ocean are qualitatively consistent with historical mapping. It is found that the low winter salinity or freshwater in the Canada Basin tends to converge due to the strong anticyclonic atmospheric circulation that drives the anticyclonic ocean surface current, while low summer salinity or freshwater tends to spread inside the Arctic and exports out of the Arctic due to the relaxing wind field. It is also found that the warm, saline Atlantic Water has little seasonal variation, based on both simulation and observations. Seasonal cycles of temperature and salinity at several representative locations reveals regional features that characterize different water mass properties.     

边界层湍流参数化改进对雾的模拟影响

为了提高边界层参数化在我国复杂下垫面上的描述能力,改善边界层能量和物质输送计算和检验其数值模拟效果,本文选取WRF三维模式,采用基于我国不同下垫面上的边界层观测资料改进的新MYNN（Mellor-Yamada-Nakanishi-Niino）参数化方案对2009年3月17日黄海海雾以及2011年12月4日华北地区两次大雾过程进行模拟检验,探讨边界层参数化方案对雾和边界层结构模拟的影响。参照卫星云图和探空资料,边界层内云水混合比垂直积分的水平分布的模拟能力明显提高,反映了改进的MYNN方案能够更好地模拟出两次雾过程的发生、移动和雾区空间分布,更精确的云水混合比和温度的垂直分布能更好地给出雾区的垂直结构和稳定层结,同时可改善雾区低层位温以及比湿垂直分布的模拟。     

海藻中植物生长素组成的初步研究

海藻样品在经过提取、分离和纯化等前处理步骤后，以薄层色谱（TLC）法定性检测了16种海藻中的植物生长素（IAA）以及提取和分离纯化的效果。结果表明，大部分海藻样品经过提取、脱色、萃取、柱层析纯化过程后都发现含有IAA的显色斑点而其它生长素的显色斑点很少。这些结果说明了16种海藻样品中都含有IAA以及定性检测方法的准确性和前处理方法的必要性。     

广西大厂拉么锌铜多金属矿床成矿规律与找矿潜力分析

拉么锌铜矿床是大厂锡矿田中矿带的主要矿床。本文通过对矿山工作以及前人资料的分析研究,总结了矿床地层、岩浆岩、构造、围岩蚀变等因素在控矿、成矿上的规律,认为矿体具有一定空间分布规律,并依据这些规律,在研究区范围内对于寻找新的矽卡岩型矿体与陡倾斜脉状矿有着较大找矿潜力,提出了矿床成因类型应属岩浆热液型矿床。     

http://www.sciencedirect.com/science/article/pii/S1674987112000254

The applications of intelligent techniques have increased exponentially in recent days to study most of the non-linear parameters.In particular,the behavior of earth resembles the non-linearity applications.An efficient tool is needed for the interpretation of geophysical parameters to study the subsurface of the earth.Artificial Neural Networks(ANN) perform certain tasks if the structure of the network is modified accordingly for the purpose it has been used.The three most robust networks were taken and comparatively analyzed for their performance to choose the appropriate network.The single-layer feed-forward neural network with the back propagation algorithm is chosen as one of the well-suited networks after comparing the results.Initially,certain synthetic data sets of all three-layer curves have been taken for training the network,and the network is validated by the Held datasets collected from Tuticorin Coastal Region(78°7′30″E and 8°48′45″N),Tamil Nadu.India.The interpretation has been done successfully using the corresponding learning algorithm in the present study.With proper training of back propagation networks,it tends to give the resistivity and thickness of the subsurface layer model of the field resistivity data concerning the synthetic data trained earlier in the appropriate network.The network is trained with more Vertical Electrical Sounding(VES) data,and this trained network is demonstrated by the field data.Groundwater table depth also has been modeled.     

东天山卡瓦布拉克前寒武纪地块填图方法思考——以大黑山幅1:25万区调为例

东天山卡瓦布拉克地区前寒武纪地块为古克拉通构造区,物质构成非常复杂。以大陆层圈构造为理论基础,运用形变地层学和变质构造解析方法为主的岩石地层调查方法,在东天山大黑山地区的1:25万区调中重新选择技术路线和工作方法,提高了区内中深变质岩系研究程度及构造-岩石地层单位划分和填图精度。     

海洋次表层叶绿素最大值的特征因子及其影响因素

在多数情况下,海水中叶绿素垂直分布是不均匀的。次表层叶绿素最大值是其中较为常见的一种形式,普遍存在于大洋及沿岸海域。次表层叶绿素最大值层(SCML)的深度、厚度与强度是表征海洋次表层叶绿素最大值(SCM)现象的主要特征因子,受海洋水文环境、营养盐分布以及浮游植物种类等因素共同影响,在不同季节不同海区的分布有较大差异。总体上,相对近海,大洋中SCML特征因子的季节变化较小,SCML深度较大,厚度较大,强度较小。寡营养盐海区SCML深度及强度的影响因素研究已有较明确结论,SCML深度主要受物理因素(光照条件及水体混合程度)影响,而强度则受物理、生物因素(光照条件、水体混合程度或浮游动物摄食等)共同影响。近海富营养盐海区,SCML特征因子的影响因素研究较为薄弱。长时间序列、高分辨率观测站在相应海区的建立,对推进海洋SCM,尤其是近海SCM的研究有重要意义。卫星观测、现场观测和数学模型相结合,定量研究SCML特征因子与各物理、生物、化学因子的普适性关系,是进一步研究SCML特征因子的重要方向之一。     

大厂泥盆纪地层控矿规律及找矿意义

大厂矿田主要矿体的产出均受泥盆纪地层限制,通过对泥盆纪地层控矿规律的研究,并综合其他控矿因素,对今后在该区的找矿工作具有重要的指导意义。     

广西大厂矿区脉岩的地球化学特征及其构造和成矿意义

位于丹池成矿带的大厂锡矿是我国著名的超大型锡多金属矿田和重要的锡矿产出地。大厂矿区的花岗斑岩和(石英)闪长玢岩脉岩,位于主要矿床的两侧,成群成带分布。花岗斑岩和闪长玢岩是在燕山晚期黑云母花岗岩之后同期或充填时间前后相差不大形成的。花岗斑岩和闪长玢岩均穿过矿体,与围岩的接触带内包含围岩角砾和矿化。花岗斑岩的SiO2、Al2O3、CaO和MgO含量较高,K2O+Na2O含量较低。岩石的氧化度较低,暗示成岩部位较深,属相对还原的成岩环境,其侵位固结前经过充分的演化分异,对成矿有利;闪长玢岩具有碱、铝、钛、镁、铁含量都较高的特点,岩石的氧化度较高。脉岩来源于地壳的重熔;脉岩沿南北向断裂充填形成,侵入时间晚于成矿期;矿床分带特征与脉岩的成岩环境一致;脉岩中丰富的主成矿元素和微量元素及其变化趋势,表明其提供了成矿物质或者其所充填的断裂曾是矿液运移通道,在成矿后才被充填,脉岩本身也为成矿物质提供了来源;石英闪长玢岩具有埃达克质岩特征,可能是由底侵的玄武质下地壳熔融形成,推测有底侵的玄武质下地壳熔融形成的岩浆参与岩脉旁侧多金属矿床的成矿。     

南京秋季辐射雾与平流雾边界层气象要素特征比较

利用南京市200 m气象铁塔的梯度观测资料、L波段探空雷达以及常规气象资料,对南京地区2010年两次秋季大雾天气过程进行了对比分析.结果表明:①两次大雾天气分别为典型的辐射雾和平流雾.②在两类大雾的发展过程中,对流层低层都存在较厚的逆温层,其中辐射雾存在多层辐射逆温和下沉逆温,而平流雾仅存在一层由暖平流形成的强逆温;边界层内辐射雾的贴地逆温强度明显强于平流雾,另外两次过程中均存在上层逆温.③雾的发展与地面气温的演变均有较好的对应关系:均是在地面气温出现突降、贴地逆温强度突增之后,边界层相对湿度随之显著上升,雾增强发展;辐射雾的雾顶高度远高于平流雾.④边界层风速呈现明显的峰值变化,且这种风速的脉动与雾的发展有一定的对应关系:当各层风速出现陡降后,雾增强发展,而后随着湍流的加强,雾趋于消散.