岩质高边坡稳定性支持向量机预测方法研究

提出一种基于支持向量机的岩质边坡稳定性预测方法。该方法地很好的表达了岩质边坡稳定性与其影响因素之间的非线性映射关系,并应用该方法建立了相应的模型。预测结果表明,利用该方法进行岩质边坡稳定性预测是可行的、有效的。     

任意荷载下欠固结地基的非线性一维固结

根据Gibson得到的固相坐标z下的非线性固结控制方程,运用Laplace变换求解了在任意荷载作用下的单层饱水欠固结地基一维非线性变形问题;通过Laplace逆变换,求得单层饱水欠固结地基在任意荷载作用下的一维非线性固结解。结合单层地基在几种常见荷载作用下固结变形的算例,对解进行了探讨,揭示了任意变荷载作用下单层饱和软粘土欠固结地基一维非线性固结的特性,得到了一些可用于指导工程实践的有益结论。     

地质异常的奇异性度量与隐伏源致矿异常识别

以个旧锡多金属矿床为例,研究了致矿地质异常的非线性特征.从异常地质事件和成矿作用的奇异性出发,定量分析了地质异常的奇异性、不连续性、非平稳性、混沌性、自相似性、临界性等非线性特征.在此基础上,详细介绍了局部奇异性分析原理和方法,论述了奇异性指数对隐伏源异常的识别能力.结果表明,奇异性分析方法在个旧地区水系沉积物地球化学数据处理和隐伏源地球化学异常识别和圈定应用中是有效的.分析结果一定程度上消除了隐伏源深度的影响,所圈定的局部地球化学异常不仅在个旧东区较好地对应了已发现的大型锡矿床的分布,而且在其他低缓地球化学异常区也圈定了多处局部异常,为进一步开展锡矿勘查提供了重要靶区.奇异性理论和方法有望为深部矿产预测、隐伏矿预测、覆盖区矿产预测等特殊环境开展矿产预测提供了新的实用性理论和方法技术.      

硅酸盐固溶体矿物中组分的韵律型空间分布及形成过程中的时-空自组织

本文根据熔体聚合模型和正规溶液模型,建立了非平衡条件下,在二组分硅酸盐熔体固结过程中的非平衡非理想界面反应的非线性动力学模型:对上式进行数值模拟表明,当W/RT<-2时,有三重态,并通过建立界面状态(组成)的质量守恒方程,合理地说明了硅酸盐固溶体矿物韵律结构形成的可能机理之一,寻找界面反应三重态是研究固溶体矿物韵律结构的一条相当普遍的途径。     

水汽场初值调整及其对华南降水预报贡献的研究

该文利用GMS多通道气象卫星资料推导得到的降水资料估算出的加热率, 作为非绝热的非线性正规模初始化过程中的非绝热强迫项, 进行风压场的初值调整, 再采用一个与模式中的对流参数化方案相反的逆运算方案, 进行水汽场的初值调整.以保证初始时刻按模式的物理参数化方案计算得到的加热率与由卫星推导的加热率一致. 这一方法在非绝热的非线性正规模初值化的框架中, 使初始时刻的水汽场得到调整.既实现了传统的初始化目标, 又提高了模式对降水的短时预报效果.对华南的两个个例的试验结果表明该文的方法是有效的.     

飑线的非线性重力波行波解模型

本文提出了一个飑线的非线性重力波行波解模型,并将该模型与实际飑线作了比较,结果表明,该模型可反映出飑线的主要特征.     

A New Strategy for Solving a Class of Constrained Nonlinear Optimization Problems Related to Weather and Climate Predictability

There are three common types of predictability problems in weather and climate, which each involve different constrained nonlinear optimization problems: the lower bound of maximum predictable time, the upper bound of maximum prediction error, and the lower bound of maximum allowable initial error and parameter error. Highly efficient algorithms have been developed to solve the second optimization problem. And this optimization problem can be used in realistic models for weather and climate to study the upper bound of the maximum prediction error. Although a filtering strategy has been adopted to solve the other two problems, direct solutions are very time-consuming even for a very simple model, which therefore limits the applicability of these two predictability problems in realistic models. In this paper, a new strategy is designed to solve these problems, involving the use of the existing highly efficient algorithms for the second predictability problem in particular. Furthermore, a series of comparisons between the older filtering strategy and the new method are performed. It is demonstrated that the new strategy not only outputs the same results as the old one, but is also more computationally efficient. This would suggest that it is possible to study the predictability problems associated with these two nonlinear optimization problems in realistic forecast models of weather or climate.     

用非线性最优化方法研究El Nio可预报性的进展与前瞻

综述用非线性优化方法研究厄尔尼诺(El Ni~no)南方涛动(ENSO)事件可预报性的进展。针对ENSO可预报性研究中的热点问题———“前期征兆”、“春季可预报性障碍”,以及如何量化研究ENSO可预报性和ENSO的不对称性问题,作者在近年来的工作中先后用理论模式和中等复杂程度ENSO模式研究了ENSO可预报性的动力学,揭示了ENSO的若干重要非线性特征。主要结果如下:(1)条件非线性最优扰动(CNOP)(局部CNOP)比线性奇异向量更易发展成ENSO事件,扮演了ENSO的最优前期征兆。这些ENSO事件关于气候平均态是不对称的。理论分析表明,非线性温度平流过程是造成这种不对称性的重要原因。1980~2002年的海洋再分析资料验证了上述理论结果。(2)ENSO事件CNOP型初始误差的发展有明显的季节依赖性,该误差导致了ENSO事件最显著的春季可预报性障碍(SPB)现象。ENSO事件SPB的发生不仅依赖于气候平均态,而且依赖于ENSO事件本身及其初始误差模态,是三者综合作用的结果。(3)建立了关于ENSO可预报性的最大可预报时间下界、最大预报误差上界和最大允许初始误差下界的三类可预报性问题,分别从三个方面揭示了ENSO事件的春季可预报性障碍现象,比较有效地量化了其可预报性。(4)通过CNOP方法,揭示了非线性温度平流在年代际尺度ENSO不对称性研究中的重要作用,解释了ENSO不对称性的年代际变化,基于所用ENSO模式给出了ENSO不对称性年代际变化的机制。最后,展望了非线性优化方法在ENSO可预报性中应用的前景,并期望该方法能拓展到ENSO第二类可预报性问题的研究中。     

Review of the Study of Nonlinear Atmospheric Dynamics in China （1999-2002）

Researches on nonlinear atmospheric dynamics in China (1999-2002) are briefly surveyed. This review includes the major achievements in the following branches of nonlinear dynamics: nonlinear stability theory,nonlinear blocking dynamics, 3D spiral structure in the atmosphere, traveling wave solution of the nonlinear evolution equation, numerical predictability in a chaotic system, and global analysis of climate dynamics.Some applications of nonlinear methods such as hierarchy structure of climate and scaling invariance, the spatial-temporal series predictive method, the nonlinear inverse problem, and a new difference scheme with multi-time levels are also introduced.     

Ensemble retrieval of atmospheric temperature profiles from AIRS

ABSTRACT Satellite-based observations provide great opportunities for improving weather forecasting. Physical retrieval of atmo spheric profiles from satellite observations is sensitive to the uncertainty of the first guess and other factors. In order to improve the accuracy of the physical retrieval, an ensemble methodology was developed with an emphasis on perturbing the first guess. In the methodology, a normal probability density function （PDF） is used to select the optimal profile from the ensemble retrievals. The ensemble retrieval algorithm contains four steps： （1） regression retrieval for original first guess; （2） perturbation of the original first guess to generate new first guesses （ensemble first guesses）; （3） using the ensemble first guesses and nonlinear iterative physical retrieval to generate ensemble physical results; and （4） the final optimal profile is selected from the ensemble physical results by using PDE Temperature eigenvectors （EVs） were used to generate the pertur- bation and generate the ensemble first guess. Compared with the regular temperature profile retrievals from the Atmospheric InfraRed Sounder （AIRS）, the ensemble retrievals RMSE of temperature profiles selected by the PDF was reduced between 150 and 320 hPa and below 400 hPa, with a maximum improvement of 0.3 K at 400 hPa. The bias was also reduced in many layers, with a maximum improvement of 0.69 K at 460 hPa. The combined optimal （CombOpt） profile and a mean optimal （MeanOpt） profile of all ensemble physical results were improved below 150 hPa. The MeanOpt profile was better than the CombOpt profile, and was regarded as the final optimal （FinOpt） profile. This study lays the foundation for improving temperature retrievals from hyper-spectral infrared radiance measurements.