岩浆混合作用——来自甘肃北山的野外证据

在 1∶2 5万马鬃山幅区调填图和方法研究工作中 ,通过观察到的一些与岩浆混合模式相关的现象 ,指出暗色微粒镁铁质包体是岩浆混合作用的有利证据 ,讨论了与花岗岩侵入体相关的镁铁质小岩体混合成因的可能性 ,认为岩浆混合作用在造山带岩浆活动中是一种极为普遍的现象。     

On the oceanic impact of a data-assimilation method in a coupled ocean-land-atmosphere model

 Based on the Kalman filter theory, a new data-assimilation method has been used to improve the 3-D oceanic temperature field of the Center for Ocean-Land-Atmosphere Studies (COLA) coupled general circulation model. This method is applied to assimilate surface and subsurface temperature of in situ measurements from the Pilot Research Moored Array in the Tropical Atlantic project (PIRATA). The assimilation of the PIRATA data produces an improved representation of the thermal state of the ocean and allows a better estimation of other oceanographic quantities, like meridional heat fluxes and zonal currents. The present paper focuses on the tropical Atlantic and, in particular, it contains new reconstructed temperature profiles. One-month forecast experiments during 1999 were performed and the impact of the assimilation is discussed. Received: 24 April 2001 / Accepted: 8 March 2002     

Use of Fuzzy Membership Input Layers to Combine Subjective Geological Knowledge and Empirical Data in a Neural Network Method for Mineral-Potential Mapping

Use of GIS layers, in which the cell values represent fuzzy membership variables, is an effective method of combining subjective geological knowledge with empirical data in a neural network approach to mineral-prospectivity mapping. In this study, multilayer perceptron (MLP), neural networks are used to combine up to 17 regional exploration variables to predict the potential for orogenic gold deposits in the form of prospectivity maps in the Archean Kalgoorlie Terrane of Western Australia. Two types of fuzzy membership layers are used. In the first type of layer, the statistical relationships between known gold deposits and variables in the GIS thematic layer are used to determine fuzzy membership values. For example, GIS layers depicting solid geology and rock-type combinations of categorical data at the nearest lithological boundary for each cell are converted to fuzzy membership layers representing favorable lithologies and favorable lithological boundaries, respectively. This type of fuzzy-membership input is a useful alternative to the 1-of-N coding used for categorical inputs, particularly if there are a large number of classes. Rheological contrast at lithological boundaries is modeled using a second type of fuzzy membership layer, in which the assignment of fuzzy membership value, although based on geological field data, is subjective. The methods used here could be applied to a large range of subjective data (e.g., favorability of tectonic environment, host stratigraphy, or reactivation along major faults) currently used in regional exploration programs, but which normally would not be included as inputs in an empirical neural network approach.     

在数值预报中应用卫星反演资料的质量控制研究

资料变分同化作为提高数值预报准确率的有效手段之一，受到了越来越多的关注。如何将分辨率较高的卫星资料应用到数值预报中，弥补常规观测网时空分辨率的不足，成为数值天气预报的重要课题。以1996年6月28-29日发生在江淮流域的暴雨过程为例，依据其中尺度场和能量场特征，分别以低云量、急流、湿静力能为标准设计了三套质量控制方案。将质量控制后的反演湿度场变分同化并应用到中尺度MM5模式中，结果表明：经质量控制后，可以明显地改善降水区域及降水量的预报；对降水预报，特别是强降水天气过程的预报，该质量控制方案具有普遍意义。     

GPS折射角资料的变分同化试验

越来越多的新型观测资料为数值天气预报水平的进一步提高提供了许多新的机会。在各种新型的观测资料中,GPS(全球定位卫星系统)折射角资料无疑是非常重要的。GPS折射角资料具有分辨率高、全天候探测、覆盖全球等优点,实现对GPS折射角资料的变分同化,将具有非常重要的意义。文中介绍了如何获得及同化GPS折射角资料的原理。对GPS折射角资料的变分同化可以分为两种:间接同化和直接同化,文中对这两种方法都作了具体介绍。在变分同化的最小化过程中,计算效率无疑是最重要的,而优化步长的计算又直接关系到算法效率的成败。根据最小化算法的特点,通过数学推导,得出一种适合于各种最小化算法的计算优化步长的自适应方法。最后,还利用1995年10月11日的GPS折射角资料进行了数值试验,结果表明了变分同化方法和计算优化步长方法的有效性。     

龙门山地区泥盆纪碳酸盐与硅质碎屑的混积相与混积机理

碳酸盐与陆源碎屑的混合沉积研究至今尚未引起足够重视。文献屈指可数。扬子西经缘龙门山地区盆纪发育了了这类良好的混合沉积。作者根据实际材料，首次从这一思路出发，识别该区泥盆纪Ｅｍｓｉａｎ期到Ｇｉｖｅｔｉａｎ早期的混积相四种，混积亚相约１４种，阐明了其优势混积作用；根据混积作用特征、沉积背景关系，划分出两大混积类型，即泥质背景下的混积１型和砂灰质背景下的混积Ⅱ型；对混积作用机理进行了探讨；并指出不同级次     

略阳─石泉边界地质体特征

略阳─石泉构造带是一板块缝合带，经历了长期复杂的演化历史。现由不同时期、不同构造体制下的断裂构造系统，裹挟不同构造演化阶段的各类建造─蛇绿混杂岩、陆缘楔状体，岛孤岩浆岩及外来岩块等，共同组成了分隔秦岭、扬子地块的一个特殊边界地质体。     

Assimilating data into open ocean tidal models

The problem of deriving tidal fields from observations by reason of incompleteness and imperfectness of every data set practically available has an infinitely large number of allowable solutions fitting the data within measurement errors and hence can be treated as ill-posed. Therefore, interpolating the data always relies on some a priori assumptions concerning the tides, which provide a rule of sampling or, in other words, a regularization of the ill-posed problem. Data assimilation procedures used in large scale tide modeling are viewed in a common mathematical framework as such regularizations. It is shown that they all (basis functions expansion, parameter estimation, nudging, objective analysis, general inversion, and extended general inversion), including those (objective analysis and general inversion) originally formulated in stochastic terms, may be considered as utilizations of one of the three general methods suggested by the theory of ill-posed problems. The problem of grid refinement critical for inverse methods and nudging is discussed.     

A hybrid method for size characterization of coarse subsurface fluvial sediments

This paper introduces and evaluates a novel method for ascertaining the grain‐size distribution of subsurface sediments that involves profoundly less sampling effort than standard methods. It is based on hybrid sampling principles previously applied to the construction of synthetic surface grain‐size distributions. The method is developed from an empirical demonstration of the approximate similarity of surface and subsurface grain‐size distributions when compared over a common range of sizes. Subsurface hybrid models are found to provide good facsimiles of grain‐size distributions de?ned using standard criteria and to yield distribution percentiles with millimetre accuracy. The technique is presented as an expedient alternative to standard methods for large, perennial gravel‐bed rivers. As this is a new technique, prudent application is advised in lieu of further investigation. Copyright © 2004 John Wiley & Sons, Ltd.     

扩展卡尔曼滤波数据同化试验--基于Lorenz(1960)系统的研究

本文采用Lorenz(1960)系统，在只考虑初始误差及观测误差而不考虑模式误差的情况下，利用扩展卡尔曼滤波(Extended Kalman Filter)数据同化方法进行了数值模拟试验。数值试验的结果表明：扩展卡尔曼滤波数据同化方法对系统状态的估计有较好的改善作用，能有效的抑制估计误差的增长；加大观测频率，可以进一步改善数据同化的效果，使估计误差进一步减小；由于模式误差的存在，系统的不稳定能量会不断的累积，出现了估计误差的异常增长和计算的不连续现象，在模式预报方程中的均值演变方程加人二阶偏差纠错项，对控制估计误差的异常增长，进一步改善数据同化的效果有较明显作用。