土层剪切波速测试中的不确定性对场地地震动参数的影响分析——以Ⅲ类场地为例

本文选取山东地区2个Ⅲ类场地的工程地质勘探及土层剪切波速等资料,将土层厚度按5个深度段,每个分段给出了4个土层剪切波速的改变量,通过改变不同深度段土层剪切波速,建立了19种土层地震反应分析模型,分析了不同深度段,不同概率水平下土层剪切波速的变化对场地地震动参数的影响。研究表明,不同深度段土层剪切波速的变化对场地地震动参数的影响有差异。具体表现为,土层剪切波速的改变在1—10m、11—40m和地震输入界面处三个深度段对地震动加速度峰值影响较大;其中,41—70m和71—100m两个深度段剪切波速的改变对地震动加速度峰值影响小;在土层深度1—10m时,剪切波速降低,峰值变大,剪切波速的改变与峰值的改变呈负相关;在其它深度段,剪切波速降低,峰值变小,剪切波速的改变与峰值的改变呈正相关。剪切波速的改变在1—10m和11—40m两个深度段对地震加速度反应谱影响较大;在41—70m、71—100m和地震输入界面三个深度段对地震加速度反应谱影响很小。     

中国未来极端气温变化的概率预估及其不确定性

本文基于第五次耦合模式比较计划的23个全球气候模式所提供的最高气温与最低气温在RCP4.5情景下的逐日格点资料,根据模式对5个极端气温指数的模拟能力,使用秩加权方法研究了中国未来极端气温变化的概率预估及其不确定性。结果表明,21世纪中期（2046—2065年）中国区域平均最高气温和平均最低气温的增加幅度相对于历史时期（1986—2005年）可能超过2.0℃（概率>66%),增加的大值区主要位于青藏高原南部。暖夜指数在中国大部分地区增加超过15%,西南和东南部沿海是增加的大值区,增幅超过20%。霜冻日数在全国范围内减少,减少的大值区位于青藏高原周围,减少日数超过了20 d。热浪指数在整个中国区域可能增加10 d以上,大值区位于西藏西南部,可达30 d。不确定性的结果表明,除热浪指数的可信度较低外,其余指数都有较高的可信度。到21世纪末期（2081—2100年),中国区域极端气温增加幅度超过前期,平均最高气温和平均最低气温很可能增加超过2.0℃（概率>90%),大值区除中国西部地区外,还扩展到了东北和青藏高原西南地区。中国大部分地区的暖夜指数增加超过15%,西南和南部沿海可能超过25%。大部分地区的霜冻日数减少20 d,青藏高原周围减少超过40 d。热浪指数在中国范围内增加20 d,青藏高原西南部增加40 d以上。除霜冻指数的信噪比略比21世纪中期大外,其余指数的信噪比与中期基本一致。     

Why Is the Climate Forcing of Sulfate Aerosols So Uncertain?

l. IntroductionAlthough the aerosol has been recognized as an important factor which has innuence onthe past, present and future climate for a long time, it still has much uncertainty in assessingits climate forcing. The direct radiative forcing of sulfate aerosols has been estimated rangingfrom --0.3 W/ m2 to --0.9 W/ m2 in recent publications (Charlson et al., l992, Kiehl andBriegleb l993; Taylor and Penner 1994, Boucher and Anderson l995, Kieh1 and Rodhe l995;Chuang et al., l997, Penne…     

Optimal estimation of irrigation schedule – An example of quantifying human interferences to hydrologic processes

Reliable records of water use for irrigation are often lacking. This presents a difficulty for a qualified water use and water availability assessment. Quantification of the hydrologic cycle processes in regions of intensive agricultural practice requires irrigation as an input to hydrologic models. This paper presents a coupled forward-inverse framework to estimate irrigation schedule using remote-sensed data and data assimilation and optimization techniques. Irrigation schedule is treated as an unknown input to a hydro-agronomic simulation model. Remote-sensed data is used to assess actual crop evapotranspiration, which is used as the “observation” of the computed crop evapotranspiration from the simulation model. To handle the impact of model and observation error and the unknown biased error with irrigation inputs, a coupled forward-inverse approach is proposed, implemented and tested. The coupled approach is realized by an integrated ensemble Kalman filter (EnKF) and genetic algorithm (GA). The result from a case study demonstrates that the forward and inverse procedures in the coupled framework are complementary to each other. Further analysis is provided on the impact of model and observation errors on the non-uniqueness problem with inverse modeling and on the exactness of irrigation estimates.     

Taking the uncertainty in climate-change vulnerability assessment seriously

Climate-change vulnerability assessment has become a frequently employed tool, with the purpose of informing policy-makers attempting to adapt to global change conditions. However, we suggest that there are three reasons to suspect that vulnerability assessment often promises more certainty, and more useful results, than it can deliver. First, the complexity of the system it purports to describe is greater than that described by other types of assessment. Second, it is difficult, if not impossible, to obtain data to test proposed interactions between different vulnerability drivers. Third, the time scale of analysis is too long to be able to make robust projections about future adaptive capacity. We analyze the results from a stakeholder workshop in a European vulnerability assessment, and find evidence to support these arguments. To cite this article: A. Patt et al., C. R. Geoscience 337 (2005).     

Estimating the confidence of earthquake damage scenarios: examples from a logic tree approach

Earthquake loss estimation is now becoming an important tool in mitigation planning, where the loss modeling usually is based on a parameterized mathematical representation of the damage problem. In parallel with the development and improvement of such models, the question of sensitivity to parameters that carry uncertainties becomes increasingly important. We have to this end applied the capacity spectrum method (CSM) as described in FEMA HAZUS-MH. Multi-hazard Loss Estimation Methodology, Earthquake Model, Advanced Engineering Building Module. Federal Emergency Management Agency, United States (2003), and investigated the effects of selected parameters. The results demonstrate that loss scenarios may easily vary by as much as a factor of two because of simple parameter variations. Of particular importance for the uncertainty is the construction quality of the structure. These results represent a warning against simple acceptance of unbounded damage scenarios and strongly support the development of computational methods in which parameter uncertainties are propagated through the computations to facilitate confidence bounds for the damage scenarios.     

Unleashing expert judgment in assessment

Assessment evaluates accumulated knowledge and its limits. It informs and ideally empowers decisions and actions on complex, contested issues with persistent uncertainties. Applying rigorous expert judgment is an important dimension of assessment. Here we evaluate advances and challenges in approaches to expert judgment in the Intergovernmental Panel on Climate Change's Fifth Assessment Report (IPCC AR5). We find that revised guidance for author teams improved the development of balanced judgments on scientific evidence across disciplines. In particular, expert judgments underpinning conclusions are more extensively, transparently, and consistently communicated: degree-of-certainty terms are more abundant in AR5 policymaker summaries; wider ranges of possible outcomes are presented with greater inclusion of lower-certainty, decision-relevant findings; and expert judgments supporting conclusions are more comparable across working groups. But challenges in developing and communicating assessment conclusions persist, especially for findings with substantial uncertainties and for subjective aspects of judgments. Based on our evaluations and AR5 lessons learned, we propose a simpler, more rigorous framework for developing and communicating expert judgments in environmental assessment. We also describe practices for reducing expert-judgment biases, for advancing integration of evidence and expert judgment, and for addressing subjective dimensions of expert opinion directly and proactively.     

集合预报的现状和前景

综合论述了近年来已在国际上引起高度重视的新一代动力随机预报方法 ——— 集合预报。 随着计算机技术的迅猛发展和由于大气初值和数值模式中物理过程存在着不确定性的事实, 这一方法无疑代表了数值天气预报未来演变发展的方向。 未来的天气预报产品预计将从“决定论”的预报转变为“随机论”的预报来正确地表达气象科学中这一所谓“可预报性问题”, 以便更好地为用户服务。 文中扼要地叙述了集合预报的概念、基本问题及其最新的研究动态和发展, 包括(1)如何建立和评估一个集合预报系统;(2)如何正确地表征大气初值和模式物理过程的不确定性与随机性;(3)如何从集合预报中提炼有用的预报信息和合理地解释、检验集合预报的产品, 特别是概率预报。 除了直接在天气预报上的应用, 还提到集合预报在气象观测和资料同化方面应用的动态, 以引起有关研究人员的注意。     

Probabilistic seismic hazard: a review of the seismological frame of reference with examples from Norway

A probabilistic seismic hazard analysis (PSHA) utilizes, in the conventional Cornell–McGuire approach, a quantitative model of the earthquake activity implying major simplifications which are important to assess in terms of their contributions to uncertainty. The goal is one of the basic principles in science, namely to establish a minimum parameter model that depicts nature with the optimum representativity (Occam's razor). All too often, underlying seismological issues remain obscure in PSHA analyses. On the basis of a specific analysis conducted in Norway we highlight how a combined seismicity analysis using both modern network data and historical data can be utilized in order to provide realistic insights into location precision and to establish magnitude homogeneity. All of this is aimed at improving the reliability of the seismic source models (i.e. the activity parameters), and to improve, without over-interpretation the earthquake catalog data, the spatial differentiation of the seismogenic zones.     

Reliability analysis of three-dimensional dynamic slope stability and earthquake-induced permanent displacement

Different models were developed for evaluating the probabilistic three-dimensional (3D) stability analysis of earth slopes and embankments under earthquake loading using both the safety factor and the displacement criteria of slope failure. In the 3D analysis, the critical and total slope widths become two new and important parameters.The probabilistic models evaluate the probability of failure under seismic loading considering the different sources of uncertainties involved in the problem, i.e. uncertainties stemming from the discrepancies between laboratory-measured and in-situ values of shear strength parameters, randomness of earthquake occurrence, and earthquake-induced acceleration. The models also takes into consideration the spatial variabilities and correlations of soil properties.Five probabilistic models of earthquake-induced displacement were developed based on the non-exceedance of a limited value criterion. Moreover, a probabilistic model for dynamic slope stability analysis was developed based on 3D dynamic safety factor.These models are formulated and incorporated within a computer program (PTDDSSA).A sensitivity analysis was conducted on the different parameters involved in the developed models by applying those models to a well-known landslides (Selset landslide) under different levels of seismic hazard.The parametric study was conducted to evaluate the effect of different input parameters on the resulting critical failure width, 3D dynamic safety factor, earthquake-induced displacement and the probability of failure. Input parameters include: average values and coefficients of variations of water table, cohesion and angle of friction for effective stress analysis, scales of fluctuations in both distance and time, hypocentral distance, earthquake magnitude, earthquake strong shaking period, etc.The hypocentral distance and earthquake magnitude were found to have major influence on the earthquake-induced displacement, probability of failure (i.e. probability of allowable displacement exceedance), and dynamic 2D and 3D safety factors.