Using Statistical Downscaling to Quantify the GCM-Related Uncertainty in Regional Climate Change Scenarios： A Case Study of Swedish Precipitation

There are a number of sources of uncertainty in regional climate change scenarios. When statistical downscaling is used to obtain regional climate change scenarios, the uncertainty may originate from the uncertainties in the global climate models used, the skill of the statistical model, and the forcing scenarios applied to the global climate model. The uncertainty associated with global climate models can be evaluated by examining the differences in the predictors and in the downscaled climate change scenarios based on a set of different global climate models. When standardized global climate model simulations such as the second phase of the Coupled Model Intercomparison Project （CMIP2） are used, the difference in the downscaled variables mainly reflects differences in the climate models and the natural variability in the simulated climates. It is proposed that the spread of the estimates can be taken as a measure of the uncertainty associated with global climate models. The proposed method is applied to the estimation of global-climate-model-related uncertainty in regional precipitation change scenarios in Sweden. Results from statistical downscaling based on 17 global climate models show that there is an overall increase in annual precipitation all over Sweden although a considerable spread of the changes in the precipitation exists. The general increase can be attributed to the increased large-scale precipitation and the enhanced westerly wind. The estimated uncertainty is nearly independent of region. However, there is a seasonal dependence. The estimates for winter show the highest level of confidence, while the estimates for summer show the least.     

Implementation of the semi-Lagrangian advection scheme on a quasi-uniform overset grid on a sphere

The semi-Lagrangian advection scheme is implemented on a new quasi-uniform overset （Yin-Yang） grid on the sphere. The Yin-Yang grid is a newly developed grid system in spherical geometry with two perpendicularly-oriented latitude-longitude grid components （called Yin and Yang respectively） that overlapp each other, and this effectively avoids the coordinate singularity and the grid convergence near the poles. In this overset grid, the way of transferring data between the Yin and Yang components is the key to maintaining the accuracy and robustness in numerical solutions. A numerical interpolation for boundary data exchange, which maintains the accuracy of the original advection scheme and is computationally efficient, is given in this paper. A standard test of the solid-body advection proposed by Williamson is carried out on the Yin-Yang grid. Numerical results show that the quasi-uniform Yin-Yang grid can get around the problems near the poles, and the numerical accuracy in the original semi-Lagrangian scheme is effectively maintained in the Yin-Yang grid.     

Some phenomena of the interaction between vegetation and a atmosphere on multiple scales

This article studies the response of the distribution pattern and the physiological characteristics of the ecosystem to the spontaneous precipitation and the interaction between vegetation and the atmosphere on multiple scales in arid and semi-arid zones, based on measured data of the ecological physiological parameters in the Ordas Plateau of northern China. The results show that the vegetation biomass and the energy use efficiency of photosynthesis are especially sensitive to the annual precipitation; strong and complex interactions exist between the vegetation and the atmosphere on multiple scales leading to supernormal thermal heterogeneity of the underlying surface, the strong vortex movement and turbulence. This study can facilitate understanding of the land surface processes and the influences of global climate change as well as human activities on the human environment in the arid and semi-arid zones. It also aids in improving the parameterization schemes of turbulent fluxes of a heterogeneous underlying surface for land surface processes in climate models.     

空间数据计算模式分析与应用

随着传感器和其他数据采集技术的不断进步以及对地观测网络的建设和启动,空间数据的高性能处理和分析成为摆在地学工作者面前的瓶颈。本文以此为出发点,按照不同地学领域(陆地、大气、海洋)的空间数据载体的形态的不同,将空间数据划分为反映固态基质信息的陆地空间数据,反映液态基质信息的陆地水文空间数据,反映液态基质信息的海洋流体空间数据和反映气态基质信息的大气流体空间数据四类,并对每类数据的最小单元问题进行了初步的分析。本文详细阐述了地学空间计算的涵义,并根据计算行为模式及计算的侧重点的不同,将地学计算过程分为深度计算过程与主动计算过程(即“数据→特征→知识”的一般计算过程),并就此进行了阐释。以基于特征的遥感信息提取和目标识别工作为例,对上述理论进行了说明和验证。最后对空间数据计算模式相关问题进行了总结,并对以后的研究做了展望。     

华东地区态矢量的研究

态矢量来源于统计物理学,是对连续场进行粗粒化描述的方法。尹祥础等把该方法移植到地震学中用以定量刻画地震活动性的演化,取得较好的结果。作者对华东地区1970年以来发生5级以上12次地震进行了分析,总结震前态矢量的变化情况,发现震前态矢量均有显著变化,为本地区地震趋势预测提供一定的参考价值。     

首都圈数字地震台网地震事件波形的管理与服务

介绍了首都圈数字地震台网地震事件波形数据的管理和服务系统的基本功能及使用方法,该系统利用GMT,SAC作为后台处理软件,通过perl,Unix Shell程序实现首都圈地震事件波形数据的网络发布。     

非一致激励条件下工程场地地震动相干函数的数值模拟--Ⅰ分析原理和方法

本文将随机振动的虚拟激励原理与工程波动理论散射问题的求解方法相结合,建立了开放系统中非一致激励条件下工程场地地震动随机场的数值模拟方法。该方法将随机输入下的波动分析问题转换为多个虚拟激励下的确定性波动分析组合问题,从而可以方便地获得场地波动观测量之间的谱密度矩阵,进而计算给出工程场地的地震动相干函数。本文还用数值模拟的办法对所提出方法的合理性和稳定性进行了探讨。     

长输管道抗震研究的新进展

本文主要从以下4个方面:地震对长输管道的危害、长输管道震害的研究方法、管道抗震分析和管道抗震的措施,介绍了近几年长输管道抗震方面的研究进展,指出了今后长输管道的研究方向。     

某水电站高边坡在地震作用下的稳定性分析

某水电站地处地质构造活动强烈的地带,坝址区边坡BT20高度达130m,其稳定性严重影响了水电枢纽工程的安全.作者利用Msarma法中准静态地震作用原理,通过引入水平地震系数Kc分析在各种烈度地震作用下边坡的稳定性系数、边坡稳定性对地震作用的敏感性,还分析了高边坡BT20蓄水前、后在各种烈度的地震作用下的稳定性系数.通过分析可知,边坡在Ⅷ度地震作用时处于临界平衡状态,地震作用是高边坡BT20稳定的重要影响因素.     

建立回弹现场测强曲线的位置参数法

工程上迫切需要在现场数据较少的情况下,建立高精度和高可靠度的现场测强曲线(经验公式)。本文利用位置参数法,提出了一种回弹法现场测强曲线(经验公式)。此曲线(经验公式)仍运用原有的幂函数形式并保持回归参数不变,通过增加位置参数反映现场试验的个性信息。此曲线(经验公式)融合了所在地区混凝土强度值、回弹值、碳化深度值之间的共性趋势和现场检测得到的反映现场情况的个性信息,而且解决了地区测强曲线(经验公式)不能完全描述现场的实际情况,而现场检测数据一般不能满足制定现场专用测强曲线(经验公式)要求的问题。在建筑结构无损检测中,利用本文提出的测强曲线(经验公式)可以极大地提高检测精度和检测结果的可靠性,使检测结果更加符合施工现场的实际情况。