用贝叶斯方法推算设计波高

采用长期概率预报提供波浪要素设计值是海洋工程中不可缺少的内容之一，文中介绍了一种基於贝叶斯原理的新计算方法，它较传统统计方法有明显的优越性，不仅可以通过补充新信息不断修正原有的估算结果，而且可以避免传统方法带来诸多不确定性，文中以北海中部百年一遇设计波高为例进行了计算。     

华南中尺度暴雨数值预报的不确定性与集合预报试验

利用非静力MM5模式,分析了不同积云对流参数化方案对华南暖区暴雨数值预报的不确定性影响,进行了中尺度暴雨模式扰动集合预报试验。不同对流参数化方案的对流凝结加热引起不同的局地温度扰动,通过大气内部的热力动力过程,导致垂直速度的差异,进而影响网格尺度和次网格尺度降水时间、地点和强度。后续降水再通过凝结潜热释放形成新的扰动源。不同积云对流参数化方案还可引起扰动源能量传播方式不同,最终使模拟大气的动力和热力结构有差异。针对物理过程的不确定性,使用两种模式扰动方法构造集合预报扰动模式,第一种方法是随机组合不同积云对流参数化方案和边界层方案,第二种方法是扰动Grell积云对流参数化方案中主要参数振幅。集合预报结果表明,第一种方法的集合预报效果优于第二种方法,仅扰动参数振幅值似乎还不足以反映华南暴雨预报的不确定性。单一的确定性预报在暴雨落区和强度方面的可信度不稳定,集合产品能给华南暴雨过程提供更有用价值的指导预报,具有较高的应用价值。     

Uncertainty in adaptive capacity

The capacity to adapt is a critical element of the process of adaptation: it is the vector of resources that represent the asset base from which adaptation actions can be made. Adaptive capacity can in theory be identified and measured at various scales, from the individual to the nation. The assessment of uncertainty within such measures comes from the contested knowledge domain and theories surrounding the nature of the determinants of adaptive capacity and the human action of adaptation. While generic adaptive capacity at the national level, for example, is often postulated as being dependent on health, governance and political rights, and literacy, and economic well-being, the determinants of these variables at national levels are not widely understood. We outline the nature of this uncertainty for the major elements of adaptive capacity and illustrate these issues with the example of a social vulnerability index for countries in Africa. To cite this article: W.N. Adger, K. Vincent, C. R. Geoscience 337 (2005).     

Uncertainties associated with Ra and Ra measurements in water via a Delayed Coincidence Counter (RaDeCC)

The short-lived radium isotopes, ²²³Ra (T_1/2 = 11.4 days) and ²²⁴Ra (T_1/2 = 3.66 days), have been successfully used as tracers of several environmental processes, e.g., submarine groundwater discharge, coastal mixing processes, and water residence times. In this paper, the uncertainties associated with ²²³Ra and ²²⁴Ra measurements using a Radium Delayed Coincidence Counter are determined on a detailed error propagation basis with a confidence interval of 1σ. From the data analyses of several groups of coastal water samples, the calculated relative uncertainties averaged 12% for the ²²³Ra and 7% for the ²²⁴Ra. These uncertainties can decrease for radium-enriched groundwater samples although asymptotic limits have been found at 7% relative uncertainty for ²²³Ra and 4% for ²²⁴Ra. In this paper, the influence of sampling and measurement parameters on the final radium uncertainties is evaluated in order to provide guidance to optimize these factors and obtain more reliable results.     

Inferred ground motions on Guadeloupe during the 2004 Les Saintes earthquake

Accurate estimates of the ground motions that occurred during damaging earthquakes are a vital part of many aspects of earthquake engineering, such as the study of the size and cause of the uncertainties within earthquake risk assessments. This article compares a number of methods to estimate the ground shaking that occurred on Guadeloupe (French Antilles) during the 21st November 2004 (M _w 6.3) Les Saintes earthquake, with the aim of providing more accurate shaking estimates for the investigation of the sources of uncertainties within loss evaluations, based on damage data from this event. The various techniques make differing use of the available ground-motion recordings of this earthquake and by consequence the estimates obtained by the different approaches are associated with differing uncertainties. Ground motions on the French Antilles are affected by strong local site effects, which have been extensively investigated in previous studies. In this article, use is made of these studies in order to improve the shaking estimates. It is shown that the simple methods neglecting the spatial correlation of earthquake shaking lead to uncertainties similar to those predicted by empirical ground-motion models and that these are uniform across the whole of Guadeloupe. In contrast, methods (such as the ShakeMap approach) that take account of the spatial correlation in motions demonstrate that shaking within roughly 10 km of a recording station (covering a significant portion of the investigated area) can be defined with reasonable accuracy but that motions at more distant points are not well constrained.     

Model and parameter uncertainty in IDF relationships under climate change

Quantifying distributional behavior of extreme events is crucial in hydrologic designs. Intensity Duration Frequency (IDF) relationships are used extensively in engineering especially in urban hydrology, to obtain return level of extreme rainfall event for a specified return period and duration. Major sources of uncertainty in the IDF relationships are due to insufficient quantity and quality of data leading to parameter uncertainty due to the distribution fitted to the data and uncertainty as a result of using multiple GCMs. It is important to study these uncertainties and propagate them to future for accurate assessment of return levels for future. The objective of this study is to quantify the uncertainties arising from parameters of the distribution fitted to data and the multiple GCM models using Bayesian approach. Posterior distribution of parameters is obtained from Bayes rule and the parameters are transformed to obtain return levels for a specified return period. Markov Chain Monte Carlo (MCMC) method using Metropolis Hastings algorithm is used to obtain the posterior distribution of parameters. Twenty six CMIP5 GCMs along with four RCP scenarios are considered for studying the effects of climate change and to obtain projected IDF relationships for the case study of Bangalore city in India. GCM uncertainty due to the use of multiple GCMs is treated using Reliability Ensemble Averaging (REA) technique along with the parameter uncertainty. Scale invariance theory is employed for obtaining short duration return levels from daily data. It is observed that the uncertainty in short duration rainfall return levels is high when compared to the longer durations. Further it is observed that parameter uncertainty is large compared to the model uncertainty.     

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…     

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).