集合卡尔曼滤波在流域水文模型流量预报中的应用     

黄小兰  李麒 《成都信息工程学院学报》2009,24(4):383-386

针对流域降雨入渗过程,引入集合卡尔曼滤波(EnKF)理论,视整个边坡流域为一个随机动态系统,将边坡流域流量观测值作为系统的输出,用集合卡尔曼滤波模型来描述系统的状态;结合流域流量计算方法,实现水文模型参数的随机动态估计,在有效获得待估参数的同时还给出估计值的不确定性.通过数值算例表明,集合卡尔曼滤波可以有效地对含噪声的量测数据进行处理,能够跟踪水文模型的动态变化.相对于常用最优化算法,集合卡尔曼滤波同时给出反演结果和先验知识的后验分布,显示出更好的实时性和可靠性.  相似文献   

A comparative analysis of metiers and catch profiles for some French demersal and pelagic fleets     

Marchal  Paul 《ICES Journal of Marine Science》2008,65(4):674-686

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基于模糊理论的时空数据模型及算法解决     

陈珺 《测绘与空间地理信息》2009,32(1)

针对当前时空数据模型中存在的主要问题,本文提出了一种基于模糊理论的时空数据模型.该模型从时空对象演化的角度出发,结合模糊隶属度的概念,力求精确表达对象演化的整个过程及对象之间的相互关系.在此基础上,进一步分析了该模型的数据结构以及算法解决,为时空数据模型的研究提供了新的思路.  相似文献   

Climate change and fluvial flood risk in the UK: more of the same?     

R. L. Wilby  K. J. Beven  N. S. Reynard 《水文研究》2008,22(14):2511-2523

The potential impact of climate change on fluvial flooding is receiving considerable scientific and political interest thanks to evidence from climate model projections and a widely held belief that flood risk may be increasing at European levels. This review compares published work on historical trends in UK rainfall and river flow records with high‐resolution regional climate change projections, and attempts to reconcile apparent differences between the two. Attention is focused on the techniques used for climate change detection and attribution, as well as the potential confounding effects of land‐use change. International and domestic efforts to build adaptive capacity rest on improved quantification of uncertainty in flood risk at very local, catchment and regional scales. This will involve further research to better integrate climate and land‐management interactions, to understand changes in the dependence between different flood generating mechanisms, and to improve the characterization and communication of uncertainty at all stages of analysis. Resources are also needed to ensure that latest, but still uncertain, science is presented in an appropriate form to underpin policy development and is translated into sensible guidance for practitioners. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

土地利用规划环境影响评价中不确定性分析   总被引：2，自引：0，他引：2  

刘晓丽 《山东国土资源》2007,23(9):28-30,33

在分析土地利用规划环境影响评价中的不确定来源、特点及其对决策的影响基础上,提出了降低环境影响评价中不确定性的方法。通过研究认为:土地利用规划环境影响评价中的不确定主要由土地利用规划方案的不确定、环境信息的不确定和环境影响程度的不确定引起的,这些不确定性具有客观性、传递性、累积性,对决策会产生较大的干扰,但是可以通过使用基于情景分析的预测方法、多方协作的方式以及广泛开展公众参与等方法来降低。  相似文献   

集合预报对台风天鹅(2015)远距离暴雨的不确定性研究     

何斌  楼茂园  李海军  范晓红  陆琛莉  潘士雄 《气象》2020,46(1):15-28

2015年8月23—24日期间台风天鹅引发华东中部沿海地区出现暴雨或大暴雨天气。基于欧洲中期天气预报中心的集合预报分析导致此次远距离暴雨预报不确定的关键原因,并利用集合敏感性分析方法研究影响此次暴雨过程的主要天气系统的敏感区域,此外对暴雨发生发展的热动力机制展开探讨,主要结论包括:集合预报对此次台风天鹅引起的远距离暴雨的可预报性明显偏低,仅在暴雨发生前24 h才做出较大调整。在不同起报时次下,当台风路径的系统性偏差最小时,台风降水集合预报也最接近实况,但是进一步的分析表明,台风路径误差与降水量级之间的对应关系并不确定。不同雨量成员组间中低层环流场的对比分析表明:高空槽的预报差异是集合预报不确定的主要原因,高空槽东移加深有利于增加暴雨区的斜压不稳定,也有利于增强对流层低层的水汽输送急流带。500 hPa高度场的敏感性分析表明无论是初始场还是预报场,暴雨区平均降雨量均与高空槽的东移和加深显著相关,且随着预报时次的临近,显著相关区域向低槽下游明显扩大。此外还发现高空槽的东移有利于增强(减弱)暴雨区左(右)侧低层冷空气的强度,使得台风右侧更多暖湿气流向暴雨区输送。  相似文献   

基于CMIP6强迫模拟分析人为气溶胶的气候效应(一)——介绍NUIST模式评估结果          下载免费PDF全文

史湘军  沈沛洁  朱寿鹏  吉璐莹  张海鹏  刘娇娇  陈伯民  李震坤 《大气科学学报》2020,43(3):506-515

为减少不同气候模式评估气溶胶气候效应的差异,第六次耦合模式比较计划(Coupled Model Intercomparison Project Phase 6,CMIP6)直接给定了人为气溶胶强迫数据。因此,有必要基于此强迫数据重新评估气溶胶气候效应。本研究首先将CMIP6给出的描述人为气溶胶强迫的模块引入南京信息工程大学(Nanjing University of Information Science and Technology,NUIST)的地球系统模式(The NUIST Earth System Model,NESM)。之后,利用NESM模式评估地球辐射收支平衡对此人为气溶胶强迫的响应,并分析模式模拟结果的不确定性。评估给出的人为气溶胶有效辐射强迫为-0. 45(±0. 28) W·m~(-2)。其中,气溶胶直接辐射效应为-0. 34(±0. 01) W·m~(-2),与第二次气溶胶比较计划(The second phase of Aerosol Comparisons between Observations and M odels,Aero ComⅡ)的评估结果基本一致;气溶胶对云辐射强迫的影响(包括半直接效应和间接效应)为-0. 10(±0. 30) W·m~(-2),明显受到模式内部变率的干扰,具有较大的不确定性。  相似文献   

Recent Advances in Predictability Studies in China （1999-2002）   总被引：10，自引：2，他引：8  

MU Mu  DUAN Wansuo  CHOU Jifan 《大气科学进展》2004,21(3):437-443

Since the last International Union of Geodesy and Geophysics (IUGG) General Assembly (1999), the predictability studies in China have made further progress during the period of 1999-2002. Firstly, three predictability sub-problems in numerical weather and climate prediction are classified, which are concerned with the maximum predictability time, the maximum prediction error, and the maximum allowable initial error, and then they are reduced into three nonlinear optimization problems. Secondly, the concepts of the nonlinear singular vector (NSV) and conditional nonlinear optimal perturbation (CNOP) are proposed,which have been utilized to study the predictability of numerical weather and climate prediction. The results suggest that the nonlinear characteristics of the motions of atmosphere and oceans can be revealedby NSV and CNOP. Thirdly, attention has also been paid to the relations between the predictability and spatial-temporal scale, and between the model predictability and the machine precision, of which the investigations disclose the importance of the spatial-temporal scale and machine precision in the study of predictability. Also the cell-to-cell mapping is adopted to analyze globally the predictability of climate,which could provide a new subject to the research workers. Furthermore, the predictability of the summer rainfall in China is investigated by using the method of correlation coefficients. The results demonstrate that the predictability of summer rainfall is different in different areas of China. Analysis of variance, which is one of the statistical methods applicable to the study of predictability, is also used to study the potential predictability of monthly mean temperature in China, of which the conclusion is that the monthly mean temperature over China is potentially predictable at a statistical significance level of 0.10. In addition,in the analysis of the predictability of the T106 objective analysis/forecasting field, the variance and the correlation coefficient are calculated to explore the distribution characteristics of the mean-square errors.Finally, the predictability of short-term climate prediction is investigated by using statistical methods or numerical simulation methods. It is demonstrated that the predictability of short-term climate in China depends not only on the region of China being investigated, but also on the time scale and the atmospheric internal dynamical process.  相似文献   

Investigation of Uncertainties of Establishment Schemes in Dynamic Global Vegetation Models简     

SONG Xiang  ZENG Xiaodong 《大气科学进展》2014,31(1):85-94

In Dynamic Global Vegetation Models （DGVMs）, the establishment of woody vegetation refers to flowering, fertiliza- tion, seed production, germination, and the growth of tree seedlings. It determines not only the population densities but also other important ecosystem structural variables. In current DGVMs, establishments of woody plant functional types （PFTs） are assumed to be either the same in the same grid cell, or largely stochastic. We investigated the uncertainties in the competition of establishment among coexisting woody PFTs from three aspects： the dependence of PFT establishments on vegetation states; background establishment; and relative establishment potentials of different PFTs. Sensitivity experi- ments showed that the dependence of establishment rate on the fractional coverage of a PFT favored the dominant PFT by increasing its share in establishment. While a small background establishment rate had little impact on equilibrium states of the ecosystem, it did change the timescale required for the establishment of alien species in pre-existing forest due to their disadvantage in seed competition during the early stage of invasion. Meanwhile, establishment purely fiom background （the scheme commonly used in current DGVMs） led to inconsistent behavior in response to the change in PFT specification （e.g., number of PFTs and their specification）. Furthermore, the results also indicated that trade-off between irtdividual growth and reproduction/colonization has significant influences on the competition of establishment. Hence, further development of es- tablishment parameterization in DGVMs is essential in reducing the uncertainties in simulations of both ecosystem structures and successions.  相似文献   

Risk mitigation and the social cost of carbon     

《Global Environmental Change》2014

The social cost of carbon – i.e., the marginal present-value cost imposed by greenhouse gas emissions – is determined by a complex interaction between factual assumptions, modeling methods, and value judgments. Among the most crucial factors is society's willingness to tolerate potentially catastrophic environmental risks. To explore this issue, the present analysis employs a stochastic climate–economy model that accounts for uncertainties in baseline economic growth, baseline emissions, greenhouse gas mitigation costs, carbon cycling, climate sensitivity, and climate change damages. In this model, preferences are specified to reflect the high degree of risk aversion revealed by private investment decisions, signaled by the large observed gap between the average rates of return paid by safe and risky financial instruments. In contrast, most climate–economy models assume much lower risk aversion. Given high risk aversion, the analysis finds that investment in climate stabilization yields especially large net benefits by forestalling low-probability threats to long-run human well-being. Accordingly, the social cost of carbon attains the markedly high value of $25,700 per metric ton of carbon dioxide in a baseline scenario in which emissions are unregulated. This value falls to just $4 per ton as the stringency of control measures is successively increased. These results cast doubt on the idea that the social cost of carbon takes on a uniquely defined, objective value that is independent of policy decisions. This does not, however, rule out the use of carbon prices to achieve the benefits of climate stabilization using least-cost mitigation measures.  相似文献