山体遮挡对滇池风生流的影响初探

用二维风生流数值模型模拟滇池湖流运动。滇池在主导风向西南风作用下,假定湖面风场是均匀的,数值模拟的湖流流态与实测湖流结果相差很大。而考虑山体遮挡影响,根据实测湖流期间现有的风情资料,在湖面上构造一非均匀风场,数值模拟结果与实测值基本一致。山体遮挡对滇池风生流的影响是不容忽视的。建议进一步进行湖流和湖面风向、风速监测,并建立过山气流数学模型,深入研究山体遮挡对湖泊风生流的影响。     

地形影响地面运动的观测研究

本文利用矿山爆破,进行了地形对地面运动影响的观测研究.9次爆破的结果表明,山顶处位移和速度的谱曲线的峰区较山前和其它测点的集中,振幅的量值也大,其放大倍率约为3,其中与山体走向平行的水平分量放大得最大,与之垂直的次之,而垂直于地面的最小;山顶测点不同分量上最大位移所对应的周期接近,其对山前的放大量值近于2,也是水平分量大于垂直分量;山顶处地面运动的延续时间取决于爆破的药量和方式,山前等测点延时的放大为3-4倍,也是水平分量大于垂直分量.山顶上地面运动的这种特殊性,是由于入射波所激发的山体共振所引起的.     

金星的地幔对流、岩石圈演化和表面更新

金星在大小、轨道半径等方面与地球非常接近,但现今的观测显示金星在大气、表面温度、重力与地形特征等方面与地球非常不同.对固体金星而言,最显著特征是有火山活动但没有活动的板块构造运动、表面平均大约500±200 Ma的年龄显示金星发生过全球性表面快速更新、重力与地形强相关.本文在简要介绍已有工作的基础上,主要介绍我们基于这些观测特征开展的金星动力学研究,包括现今地幔的对流模式、相变对表面更新的影响、地壳厚度、岩石圈演化与表面更新等研究工作和取得的初步认识.     

基于高铁震源简化桥墩模型激发地震波的数值模拟

高铁列车运行过程中绝大部分时间都是行驶在高架桥上的,高铁列车经过桥梁时,通过与大地耦合的桥墩激发地震波发震过程和平地不完全一样.本文探索高铁列车行驶经过高架桥桥墩,通过桥墩对地下介质激发地震波的机理及过程.为了便于理论分析,文中将高铁列车简化为在高架桥上沿一个方向运动的移动线源,通过每节车厢前后组轮对,对每一个桥墩施加力的作用,而桥墩插入地面几十米深至围岩,与表层土壤和深层围岩双重耦合,由此给出高铁列车通过桥墩激发地震波的震源时间函数.同时,基于广义连续介质力学框架下的修正偶应力理论,推导包含介质特征尺度的弹性波动方程,并应用此弹性波动方程以及构建的高铁震源时间函数,采用优化的交错网格有限差分算法,实现数值模拟,将合成的地震记录与实际地震记录对比分析,其结论将为进一步的基于高铁震源的成像和反演研究提供理论依据.     

Coriolis力作用下的β效应与层结效应的Rossby孤立波

从包含完整Coriolis力的大气运动方程组出发,利用半地转近似导出了β效应、层结效应和地球旋转水平分量f_h共同作用下的非线性Rossby波满足KdV方程以及KdVmKdV方程.结果表明β效应、层结效应和地球旋转水平分量对Rossby的作用.     

俯冲构造vs.地幔柱构造——板块运动驱动力探讨

板块构造是指地球外壳岩石圈块体在地球表面的(水平)运动及其相互作用.自50年前板块构造理论建立以来,对板块运动的动力来源这一问题一直存在争议.早期的观点认为是"自下而上"机制,即板块运动受控于板块之下的地幔对流系统,特别是起源于核幔边界的地幔柱作用于板块底部,促使大陆裂解,并驱动板块运动.而现今较为普遍接受的观点则是"自上而下"机制,即认为板块运动的驱动力主要来源于板块自身的负浮力(即重力大于浮力),板块构造和地幔对流均受控于板块的俯冲作用,因此板块构造又被称为俯冲构造.这一观点得到了众多地质和地球物理观测的支持.进一步研究表明,个别板块增速、减速与单一地幔柱活动在百万年时间尺度具有耦合关系;多个板块内稳定克拉通地区地表隆升、沉积速率与地幔柱相关的岩浆活动在亿年时间尺度存在时空相关性;而全球范围的超大陆聚合、裂解与超级地幔柱活动在二十亿年以来的地质历史时期表现为周期性耦合关系.这些不同时空尺度的耦合现象均表明,板块构造与地幔柱构造在地球演化过程中是紧密联系、相互作用的,地幔柱构造对板块运动产生了不可忽视的影响.因此,需要将板块构造和地幔柱构造这两大地球构造体系加以联合,开展综合分析与研究,才能获得对板块构造和整个地球动力系统运行机制的全面认识.     

湖泊富营养化响应与流域优化调控决策的模型研究进展

湖泊富营养化是全球水环境领域面临的长期挑战,富营养化响应与流域优化决策模型是制定经济和高效调控方案的关键.然而已有的模型研究综述主要集中于模型开发、案例应用、敏感性分析、不确定性分析等单一方面,而缺少针对非线性响应、生态系统长期演变等最新湖泊治理挑战的研究总结.本文对数据驱动的统计模型、因果驱动的机理模型和决策导向的优化模型进行了综述.其中,统计模型包含经典统计、贝叶斯统计和机器学习模型,常用于建立响应关系、时间序列特征分析以及预报预警;机理模型包含流域的水文与污染物输移模拟以及湖泊的水文、水动力、水质、水生态等过程的模拟,用于不同时空尺度的变化过程模拟,其中复杂机理模型的敏感性分析、参数校验、模型不确定性等需要较高的计算成本;优化模型结合机理模型形成“模拟优化”体系,在不确定性条件下衍生出随机、区间优化等多种方法,通过并行计算、简化与替代模型可一定程度上解决计算时间成本的瓶颈.本文识别了湖泊治理面临的挑战,包括:①如何定量表征外源输入的非线性叠加和湖泊氮、磷、藻变化的非均匀性?②如何提高优化调控决策和水质目标的关联与精准性?③如何揭示湖泊生态系统的长期变化轨迹与驱动因素?最后,本文针对这些挑战提出研究展望,主要包括:①基于多源数据融合与机器学习算法以提升湖泊的短期水质预测精度;②以生物量为基础的机理模型与行为驱动的个体模型的升尺度或降尺度耦合以表达多种尺度的物质交互过程;③机器学习算法与机理模型的直接耦合或数据同化以降低模拟误差;④时空尺度各异的多介质模拟模型融合以实现精准和动态的优化调控.     

波动方程反演的全局优化方法研究

复杂介质波动方程反演是地球物理研究中的重要问题,通常表述为特定目标函数最优化,难点是多参数、非线性和不适定性.局部和全局优化方法都不能实现快速全局优化.本文概述了地震波勘探反演问题的理论基础和研究进展,阐述了反演中优化问题的解决方法和面临的困难,并提出了一种确定性全局优化的新方法.通过在优化参数空间识别并划分局部优化解及其附近区域,只需有限次参数空间划分过程就能发现所有局部解（集合）;基于复杂目标函数多尺度结构分析,提出多尺度参数空间分区优化方法的研究方向.该方法收敛速度快,优化结果不依赖初始解的选取,是对非线性全局优化问题的一个新探索.     

高密度电法在山体稳定性评价中的应用

山体中不稳定滑坡体的存在是影响人类生产生活安全的一大隐患。物探方法是山体稳定性评价中的重要测量手段,被用于探查具有松散表象的山体内部,测量与山体不稳定性相关的参数和数据。详细阐述了高密度电法在山西某矿西侧山体稳定性评价中的应用过程,该方法为山体稳定性定量计算提供了比较准确的数据,为物探方法在此类评价中的应用推广提供了具有说服力的实例。     

丽江7.0级地震重力前兆模式研究<

为了研究1996年丽江MＳ7.0地震前地震孕育过程或前兆表现，利用滇西地震实验场内高精度重复重力观测数据，结合地质调查和地球物理推断结果，并考虑到观测数据和模型粗差， 采用稳健或抗差-贝叶斯最小二乘算法和多断层位错模型，首次初步反演获得了研究区主要活动断裂滑动的时间变化分布．结果表明，1990～1997年断层运动的时间变化，较好地反映了1996年丽江MＳ7.0地震孕育过程．其主要前兆模式图象具有主震余震型特征，遵循地壳内部密度和地壳形变耦合运动模式（简称DD耦合运动模式）．      

一种改进的电离层层析成像算法

针对电离层层析成像算法中确定相位积分常数以及合理选择迭代初值等关键问题,本文提出一种联合使用差分多普勒相位和差分多普勒频率数据的新算法,将相位积分常数的计算以及迭代初值的确定与图像的重建过程统一起来．该算法克服了单独计算相位积分常数的困难,初值的选择也较为合理,数值模拟反演与对实测数据反演的结果证明,本文提出的算法对电离层ＣＴ重建更为合理有效．     

Snow water equivalent estimation in the Mallero basin using snow gauge data and MODIS images and fieldwork validation

Snow accumulation and ablation rule the temporal dynamics of water availability in mountain areas and cold regions. In these environments, the evaluation of the snow water amount is a key issue. The spatial distribution of snow water equivalent (SWE) over a mountain basin at the end of the snow accumulation season is estimated using a minimal statistical model (SWE‐SEM). This uses systematic observations such as ground measurements collected at snow gauges and snow‐covered area (SCA) data retrieved by remote sensors, here MODIS. Firstly, SWE‐SEM calculates local SWE estimates at snow gauges, then the spatial distribution of SWE over a certain area using an interpolation method; linear regressions of the first two order moments of SWE with altitude. The interpolation has been made by both confining and unconfining the spatial domain by SCA. SWE‐SEM is applied to the Mallero basin (northern Italy) for calculating the snow water equivalent at the end of the winter season for 6 years (2001–2007). For 2007, SWE‐SEM estimates are validated through fieldwork measurements collected during an ‘ad hoc’ campaign on March 31, 2007. Snow‐surveyed measurements are used to check SCA, snow density and SWE estimates. Copyright © 2009 John Wiley & Sons, Ltd.     

Topographic signatures of progressive glacial landscape transformation

The Pleistocene glaciations left a distinct topographic footprint in mountain ranges worldwide. The geometric signature of glacial topography has been quantified in various ways, but the temporal development of landscape metrics has not been traced in a landscape evolution model so far. However, such information is needed to interpret the degree of glacial imprint in terms of the integrated signal of temporal and spatial variations in erosion as a function of glacial occupation time. We apply a surface process model for cold-climate conditions to an initially fluvial mountain range. By exploring evolving topographic patterns in model time series, we determine locations where topographic changes reach a maximum and where the initial landscape persists. The signal of glacial erosion, expressed by the overdeepening of valleys and the steepening of valley flanks, develops first at the glacier front and migrates upstream with ongoing glacial erosion. This leads to an increase of mean channel slope and its variance. Above steep flanks and head-walls, however, the observed mean channel slope remains similar to the mean channel slope of the initial fluvial topography. This leads to a characteristic turning point in the channel slope–elevation distribution above the equilibrium line altitude, where a transition from increasing to decreasing channel slope with elevation occurs. We identify this turning point and a high channel slope variance as diagnostic features to quantify glacial imprint. Such features are abundant in glacially imprinted mid-latitude mountain ranges such as the Eastern Alps. By analysing differently glaciated parts of the mountain range, we observe a decreasing clarity of this diagnostic morphometric property with decreasing glacial occupation. However, catchments of the unglaciated eastern fringe of the Alps also feature turning points in their channel slope–elevation distributions, but in contrast to the glaciated domain, the variance of channel slope is small at all elevation levels.     

基于印模法的地面磁电阻率数据三维非线性共轭梯度反演

本文提出了能提高异常体分辨能力,同时得到绝对电导率的地面磁电阻率数据三维反演方法.磁电阻率响应用准直流的低频磁场代替;数值模拟由频率域电场满足的Helmholtz方程出发,采用三维交错网格有限差分法;长直导线源作为发射源,其中源的计算包含在背景场中;结合地面磁电阻率数据各分量的特点,选择y分量进行反演研究;反演采用三维非线性共轭梯度反演技术,为了提高异常体的深度分辨能力,进行迭代重构反演;用印模法对初始模型进行重构,采用的是辅模型在浅部,元模型在深部的组合方式.从合成数据和实际数据的反演结果可以得到以下的认识:(1)由频率域麦克斯韦方程组出发,低频磁场数据反演可以直接得到电导率,而不是相对电导率之比;(2)采用印模法组合初始模型,进行迭代重构反演,可以提高地面磁电阻率数据反演对异常体的分辨能力,确定埋深位置,同时不会丧失对于浅部异常体的分辨能力;(3)在结合印模法的地面磁电阻率数据三维反演中,深部异常体的分辨能力受地表不均匀导电体影响较小;(4)确定印模深度可以采用上一次重构反演结束时的模型变化量,通过相邻两次重构反演结束时的模型变化量之差来确定迭代重构是否终止.因为静磁场与重力场在数学上的相似性,本文的反演方法可以被运用到重力场等位场的地面数据的反演中.     

Full waveform inversion using oriented time‐domain imaging method for vertical transverse isotropic media

Full waveform inversion for reflection events is limited by its linearised update requirements given by a process equivalent to migration. Unless the background velocity model is reasonably accurate, the resulting gradient can have an inaccurate update direction leading the inversion to converge what we refer to as local minima of the objective function. In our approach, we consider mild lateral variation in the model and, thus, use a gradient given by the oriented time‐domain imaging method. Specifically, we apply the oriented time‐domain imaging on the data residual to obtain the geometrical features of the velocity perturbation. After updating the model in the time domain, we convert the perturbation from the time domain to depth using the average velocity. Considering density is constant, we can expand the conventional 1D impedance inversion method to two‐dimensional or three‐dimensional velocity inversion within the process of full waveform inversion. This method is not only capable of inverting for velocity, but it is also capable of retrieving anisotropic parameters relying on linearised representations of the reflection response. To eliminate the crosstalk artifacts between different parameters, we utilise what we consider being an optimal parametrisation for this step. To do so, we extend the prestack time‐domain migration image in incident angle dimension to incorporate angular dependence needed by the multiparameter inversion. For simple models, this approach provides an efficient and stable way to do full waveform inversion or modified seismic inversion and makes the anisotropic inversion more practicable. The proposed method still needs kinematically accurate initial models since it only recovers the high‐wavenumber part as conventional full waveform inversion method does. Results on synthetic data of isotropic and anisotropic cases illustrate the benefits and limitations of this method.     

Sensitivity of the Weather Research and Forecasting (WRF) model to downscaling ratios and storm types in rainfall simulation

Accurate information of rainfall is needed for sustainable water management and more reliable flood forecasting. The advances in mesoscale numerical weather modelling and modern computing technologies make it possible to provide rainfall simulations and forecasts at increasingly higher resolutions in space and time. However, being one of the most difficult variables to be modelled, the quality of the rainfall products from the numerical weather model remains unsatisfactory for hydrological applications. In this study, the sensitivity of the Weather Research and Forecasting (WRF) model is investigated using different domain settings and various storm types to improve the model performance of rainfall simulation. Eight 24‐h storm events are selected from the Brue catchment, southwest England, with different spatial and temporal distributions of the rainfall intensity. Five domain configuration scenarios designed with gradually changing downscaling ratios are used to run the WRF model with the ECMWF 40‐year reanalysis data for the periods of the eight events. A two‐dimensional verification scheme is proposed to evaluate the amounts and distributions of simulated rainfall in both spatial and temporal dimensions. The verification scheme consists of both categorical and continuous indices for a first‐level assessment and a more quantitative evaluation of the simulated rainfall. The results reveal a general improvement of the model performance as we downscale from the outermost to the innermost domain. Moderate downscaling ratios of 1:7, 1:5 and 1:3 are found to perform better with the WRF model in giving more reasonable results than smaller ratios. For the sensitivity study on different storm types, the model shows the best performance in reproducing the storm events with spatial and temporal evenness of the observed rainfall, whereas the type of events with highly concentrated rainfall in space and time are found to be the trickiest case for WRF to handle. Finally, the efficiencies of several variability indices are verified in categorising the storm events on the basis of the two‐dimensional rainfall evenness, which could provide a more quantitative way for the event classification that facilitates further studies. It is important that similar studies with various storm events are carried out in other catchments with different geographic and climatic conditions, so that more general error patterns can be found and further improvements can be made to the rainfall products from mesoscale numerical weather models. Copyright © 2011 John Wiley & Sons, Ltd.     

基于POCS方法指数阈值模型的不规则地震数据重建(英文)

不规则地震数据会对地震多道处理技术的正确运行造成不良影响,降低地震资料的处理质量。本文将广泛用于图形图像重建的凸集投影方法应用到地震数据重建领域,实现规则样不规则道缺失数据的插值重建。对于整道缺失地震数据,将POCS迭代重建过程由时间域转移到频率域实现,避免每次迭代都对时间做正反Fourier变换,节约了计算量。在迭代过程中,阈值参数的选择方式对重建效率有重要影响。本文设计了两种阈值集合模型进行重建试验,试验结果表明:在相同重建效果下,指数型阈值集合模型可以有效减少迭代次数,提高重建效率。此外,分析了POCS重建方法的抗噪性能和抗假频性能。最后,理论模型和实际资料处理效果验证了本文重建方法的正确性和有效性。     

时间域航空电磁2.5维非线性共轭梯度反演

对于时间域航空电磁法二维和三维反演来说,最大的困难在于有效的算法和大的计算量需求.本文利用非线性共轭梯度法实现了时间域航空电磁法2.5维反演方法,着重解决了迭代反演过程中灵敏度矩阵计算、最佳迭代步长计算、初始模型选取等问题.在正演计算中,我们采用有限元法求解拉式傅氏域中的电磁场偏微分方程,再通过逆拉氏和逆傅氏变换高精度数值算法得到时间域电磁响应.在灵敏度矩阵计算中,采用了基于拉式傅氏双变换的伴随方程法,时间消耗只需计算两次正演,从而节约了大量计算时间.对于最佳步长计算,二次插值向后追踪法能够保证反演迭代的稳定性.设计两个理论模型,检验反演算法的有效性,并讨论了选择不同初始模型对反演结果的影响.模型算例表明:非线性共轭梯度方法应用于时间域航空电磁2.5维反演中稳定可靠,反演结果能够有效地反映地下真实电性结构.当选择的初始模型电阻率值与真实背景电阻率值接近时,能得到较好的反演结果,当初始模型电阻率远大于或远小于真实背景电阻率值时反演效果就会变差.     

位场曲化平积分方程的迭代解

提出了位场曲化平的新方法. 给定观测曲面S上的位场、S对下方水平面P的相对高程,确定P上的位场. 利用由P向上延拓到S的积分式,建立这两个面上位场及相对高程三者所满足的方程,它是第一类Fredholm积分方程. 用Fourier逆变换式把这一空间域积分式化为波数域积分式,再由指数函数的Taylor展开进一步化为级数式. 积分方程的解采用逐次逼近法迭代计算,即用S上的位场观测值作为P上位场的初始迭代值,用导出的级数式求得S上的位场计算值、由S上的位场观测值与计算值之差校正P上的位场,多次迭代,直到满足迭代终止准则. 我们还给出该积分方程的波数域迭代计算方法. 模型算例表明,重力异常曲化平的均方差和磁异常曲化平的均方差分别为0.0008 mGal和0.0019 nT,在主频为2.26 GHz的笔记本电脑运行,2048×2048数据量,计算时间是975 s. 野外磁场实际资料处理也证实这种方法的有效性.     

Exploring the effect of data assimilation by WRF‐3DVar for numerical rainfall prediction with different types of storm events

The mesoscale Numerical Weather Prediction (NWP) model is gaining popularity among the hydrometeorological community in providing high‐resolution rainfall forecasts at the catchment scale. Although the performance of the model has been verified in capturing the physical processes of severe storm events, the modelling accuracy is negatively affected by significant errors in the initial conditions used to drive the model. Several meteorological investigations have shown that the assimilation of real‐time observations, especially the radar data can help improve the accuracy of the rainfall predictions given by mesoscale NWP models. The aim of this study is to investigate the effect of data assimilation for hydrological applications at the catchment scale. Radar reflectivity together with surface and upper‐air meteorological observations is assimilated into the Weather Research and Forecasting (WRF) model using the three‐dimensional variational data‐assimilation technique. Improvement of the rainfall accumulation and its temporal variation after data assimilation is examined for four storm events in the Brue catchment (135.2 km²) located in southwest England. The storm events are selected with different rainfall distributions in space and time. It is found that the rainfall improvement is most obvious for the events with one‐dimensional evenness in either space or time. The effect of data assimilation is even more significant in the innermost domain which has the finest spatial resolution. However, for the events with two‐dimensional unevenness of rainfall, i.e. the rainfall is concentrated in a small area and in a short time period, the effect of data assimilation is not ideal. WRF fails in capturing the whole process of the highly convective storm with densely concentrated rainfall in a small area and a short time period. A shortened assimilation time interval together with more efficient utilisation of the weather radar data might help improve the effectiveness of data assimilation in such cases. Copyright © 2012 John Wiley & Sons, Ltd.