大气重力波触发的Rayleigh－Taylor不稳定性的时空演变

对大气重力波触发的赤道电离层Ｒａｙｌｅｉｇｈ－Ｔａｙｌｏｒ不稳定性的时空演变进行了数值模拟．结果表明,重力波能在Ｆ区底部触发Ｒａｙｌｅｉｇｈ－Ｔａｙｌｏｒ不稳定性,这种等离子体不稳定扰动穿过Ｆ峰,到达Ｆ区顶部,形成等离子体泡结构．等离子体泡出现向西倾斜和分岔等特征．当夜Ｆ区较高时,产生等离子体泡的时间仅１９００ｓ．数值模拟结果证实了重力波触发．Ｒａｙｌｅｉｇｈ－Ｔａｙｌｏｒ不稳定性的理论,解释了大量电离层观测现象．     

不同对流参数化方案试验中凝结加热的特征及对暴雨中尺度模拟结果的影响

使用20 km分辨率的MM5模式,分别选用KUO,GRELL,KAIN-FRITSCH和BETTS-MILLER(以下简称KU,GR,KF和BM)等4种不同对流参数化方案,对1996年8月3~4日石家庄特大暴雨过程作数值模拟试验,分析比较了4个不同试验中网格尺度(显式方案)和次网格尺度(对流参数化方案)凝结加热的水平、垂直分布和时变特征;研究探讨了凝结加热分布及差异对暴雨中尺度模拟结果的可能影响。分析显示,暴雨过程中,4个不同对流参数化方案试验所得到的次网格尺度凝结加热基本都呈单峰特征、加热峰值在对流层中层,但加热层厚度和强度在不同试验间存在差别;4个试验的网格尺度凝结加热的垂直范围表现出较好的一致性,加热重心位于对流层低层,但加热强度仍有所不同;GR和KF及BM试验的总凝结加热率的垂直分布特征主要受其网格尺度凝结加热率特征的影响、加热重心在对流层低层,而KU试验的总凝结加热率的垂直分布特征由其次网格尺度凝结加热率特征所决定、加热重心在对流层中层。研究表明,尽管4个试验在暴雨期间总凝结加热的垂直分布差异并不显著,但对暴雨中尺度模拟的影响却不能忽视。凝结加热的分布特征及演变直接影响与暴雨发生发展密切关联的物理量场的中尺度结构和演变;凝结加热对暴雨中尺度的影响具有连锁性,由加热差异波及局部环流细致结构和强度及其变化的差异,进而影响暴雨发生发展的细致特征。在20 km或更高一些分辨率的条件下,对于描述温带/中纬度暴雨的发展和结构,选用KF方案得到的模拟结果可能更具物理合理性;而KU方案模拟结果容易出现格点气柱的水汽和温度被过量调整的不合理情况。要得到一个可信的中尺度模拟结果,对降水模拟结果进行细化特征的验证、特别是随时间演变特征的验证分析是非常重要的,因为降水的细致演变特征与凝结加热及与之相联系的物理量场的中尺度演变特征密切关联。     

地下水模型的Neumann展开Monte-Carlo随机有限元法

讨论了求解地下水模型(水流模型和水质模型)的Neumann展开Monte-Carlo随机有限元法。从基本的随机变量入手,避免了过程中随机变量的增多问题,给出结点水头(浓度)的均值、方差和水头在某区间的概率计算方法;改进了矩阵求逆的效率,对输入随机变量较多、随机变量变异较大的非稳定地下水问题特别有效。同时选取二维承压地下水水流问题(有解析解)作为例子,进行了随机数值模拟实验。     

Dispersal of arbuscular mycorrhizal fungi and dark septate endophytes by Ctenomys cf. knighti (Rodentia) in the northern Monte Desert of Argentina

In arid and semi-arid environments, root-associated fungi may play a key role in plant communities (e.g., seedling establishment, nutrient acquisition, plant survival and heat tolerance). Several studies have shown the importance of small mammals as consumers and dispersal agents of mycorrhizal fungi spores in tropical and temperate ecosystems. However, little is known about the dispersal of infective propagules of endophytic fungi in arid and semi-arid ecosystems. This study analyzed the potential role of the subterranean rodent Ctenomys cf. knighti as a dispersal agent of root-associated fungi. In order to demonstrate this role, we analyzed: (1) the incidence of colonization of arbuscular mycorrhizae and dark septate endophytes on representative plant species of the Monte Desert; (2) the presence of fungal structures of arbuscular mycorrhizae and dark septate endophytes in C. cf. knighti fecal samples; and (3) the infectivity of the fungal propagules contained in the scat and their growth effects on nine native plant species. Data strongly suggest that this South American subterranean rodent may play a key role as a dispersal agent of arbuscular mycorrhizae and dark septate endophytes fungi in the arid environment of the northern Monte Desert of Argentina.     

Generalized likelihood uncertainty estimation (GLUE) using adaptive Markov Chain Monte Carlo sampling

In the last few decades hydrologists have made tremendous progress in using dynamic simulation models for the analysis and understanding of hydrologic systems. However, predictions with these models are often deterministic and as such they focus on the most probable forecast, without an explicit estimate of the associated uncertainty. This uncertainty arises from incomplete process representation, uncertainty in initial conditions, input, output and parameter error. The generalized likelihood uncertainty estimation (GLUE) framework was one of the first attempts to represent prediction uncertainty within the context of Monte Carlo (MC) analysis coupled with Bayesian estimation and propagation of uncertainty. Because of its flexibility, ease of implementation and its suitability for parallel implementation on distributed computer systems, the GLUE method has been used in a wide variety of applications. However, the MC based sampling strategy of the prior parameter space typically utilized in GLUE is not particularly efficient in finding behavioral simulations. This becomes especially problematic for high-dimensional parameter estimation problems, and in the case of complex simulation models that require significant computational time to run and produce the desired output. In this paper we improve the computational efficiency of GLUE by sampling the prior parameter space using an adaptive Markov Chain Monte Carlo scheme (the Shuffled Complex Evolution Metropolis (SCEM-UA) algorithm). Moreover, we propose an alternative strategy to determine the value of the cutoff threshold based on the appropriate coverage of the resulting uncertainty bounds. We demonstrate the superiority of this revised GLUE method with three different conceptual watershed models of increasing complexity, using both synthetic and real-world streamflow data from two catchments with different hydrologic regimes.     

基于元胞自动机民勤绿洲湖区荒漠化演化预测

民勤湖区是民勤绿洲中生态环境最为恶劣的地区,土地荒漠化问题十分突出。以民勤绿洲湖区为例,解译1992年、1998年、2002年和2006年TM卫星影像,分析其荒漠化动态变化情况,利用ArcObjects模块结合地理元胞自动机理论构造荒漠化动态模拟模型,通过对比2006年的预测数据与实际数据,对模型进行参数调整和预测检验。预测结果表明,模型预测的准确性达到90%。最后对2012年该区土地利用状况做出预测,进而对荒漠化的发展趋势进行预测分析。     

A New Method of Significance Testing for Correlation-Coefficient Fields and Its Application

Correlation-coefficient fields are widely used in short-term climate prediction research. The most frequently used significance test method for the correlation-coefficient field was proposed by Livezey, in which the number of significantcorrelation lattice(station) points on the correlation coherence map is used as the statistic. However, the method is based on two assumptions:(1) the spatial distribution of the lattice(station) points is uniform;and(2) there is no correlation between the physical quantities in the correlation-coefficient field. However, in reality, the above two assumptions are not valid.Therefore, we designed a more reasonable method for significance testing of the correlation-coefficient field. Specifically, a new statistic, the significant-correlation area, is introduced to eliminate the inhomogeneity of the grid(station)-point distribution, and an empirical Monte Carlo method is employed to eliminate the spatial correlation of the matrix.Subsequently, the new significance test was used for simultaneous correlation-coefficient fields between intensities of the atmospheric activity center in the Northern Hemisphere and temperature/precipitation in China. The results show that the new method is more reasonable than the Livezey method.     

Numerical simulation of fully saturated porous materials

Fully coupled, porous solid–fluid formulation, implementation and related modeling and simulation issues are presented in this work. To this end, coupled dynamic field equations with u?p?U formulation are used to simulate pore fluid and soil skeleton (elastic–plastic porous solid) responses. Present formulation allows, among other features, for water accelerations to be taken into account. This proves to be useful in modeling dynamic interaction of media of different stiffnesses (as in soil–foundation–structure interaction). Fluid compressibility is also explicitly taken into account, thus allowing excursions into modeling of limited cases of non‐saturated porous media. In addition to these features, present formulation and implementation models in a realistic way the physical damping, which dissipates energy. In particular, the velocity proportional damping is appropriately modeled and simulated by taking into account the interaction of pore fluid and solid skeleton. Similarly, the displacement proportional damping is physically modeled through elastic–plastic processes in soil skeleton. An advanced material model for sand is used in present work and is discussed at some length. Also explored in this paper are the verification and validation issues related to fully coupled modeling and simulations of porous media. Illustrative examples describing the dynamical behavior of porous media (saturated soils) are presented. The verified and validated methods and material models are used to predict the behavior of level and sloping grounds subjected to seismic shaking. Copyright © 2008 John Wiley & Sons, Ltd.     

与高岭石固相平衡的酸性天然地表水中铝的缓冲作用的计算机模拟

基于质量守恒以及电中性条件,采用化学平衡计算法,计算模拟研究了高岭石固相平衡的酸性天然地表水中铝的缓冲作用对ｐＨ值,酸中和容量ＡＮＣ和缓冲强度β的影响,讨论了影响酸性地表水ｐＨ估算的各种因素,如溶解硅酸的浓度,溶解总无机碳的浓度,溶解总氟和总有机碳的浓度及温度等。模型被用于实际水样的分析,所得结果与实验值符合较好,用ＭｏｎｔｅＣａｒｌｏ模拟考察了由于平衡常数的选择以及水化学参数测量误差而带来的不确     

一种生成大周期伪随机数的新算法——改进的混合同余法

为了克服当前所生成的伪随机数周期小、每个随机数仅能出现1次而不能重复的缺点,本文提出了一种生成伪随机数的新方法,称为改进的混合同余法。