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Using results from coupled climate model simulations of the 8.2 ka climate event that produced a cold period over Greenland in agreement with the reconstructed cooling from ice cores, we investigate the typical pattern of climate anomalies (fingerprint) to provide a framework for the interpretation of global proxy data for the 8.2 ka climate event. For this purpose we developed an analysis method that isolates the forced temperature response and provides information on spatial variations in magnitude, timing and duration that characterise the detectable climate event in proxy archives. Our analysis shows that delays in the temperature response to the freshwater forcing are present, mostly in the order of decades (30 a over central Greenland). The North Atlantic Ocean initially cools in response to the freshwater perturbation, followed in certain parts by a warm response. This delay, occurring more than 200 a after the freshwater pulse, hints at an overshoot in the recovery from the freshwater perturbation. The South Atlantic and the Southern Ocean show a warm response reflecting the bipolar seesaw effect. The duration of the simulated event varies for different areas, and the highest probability of recording the event in proxy archives is in the North Atlantic Ocean area north of 40° N. Our results may facilitate the interpretation of proxy archives recording the 8.2 ka event, as they show that timing and duration cannot be assumed to correspond with the timing and duration of the event as recorded in Greenland ice cores. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
64.
A new magnitude category disaggregation approach for temporal high‐resolution rainfall intensities
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Simulation of quick runoff components such as surface runoff and associated soil erosion requires temporal high‐resolution rainfall intensities. However, these data are often not available because such measurements are costly and time consuming. Current rainfall disaggregation methods have shortcomings, especially in generating the distribution of storm events. The objectives of this study were to improve point rainfall disaggregation using a new magnitude category rainfall disaggregation approach. The procedure is introduced using a coupled disaggregation approach (Hyetos and cascade) for multisite rainfall disaggregation. The new procedure was tested with ten long‐term precipitation data sets of central Germany using summer and winter precipitation to determine seasonal variability. Results showed that dividing the rainfall amount into four daily rainfall magnitude categories (1–10, 11–25, 26–50, >50 mm) improves the simulation of high rainfall intensity (convective rainfall). The Hyetos model category approach (HyetosCat) with seasonal variation performs representative to observed hourly rainfall compared with without categories on each month. The mean absolute percentage accuracy of standard deviation for hourly rainfall is 89.7% in winter and 95.6% in summer. The proposed magnitude category method applied with the coupled HyetosCat–cascade approach reproduces successfully the statistical behaviour of local 10‐min rainfall intensities in terms of intermittency as well as variability. The root mean square error performance statistics for disaggregated 10‐min rainfall depth ranges from 0.20 to 2.38 mm for summer and from 0.12 to 2.82 mm for the winter season in all categories. The coupled stochastic approach preserves the statistical self‐similarity and intermittency at each magnitude category with a relatively low computational burden. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
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Slope stability optimization, in the presence of a band of a weak layer between two strong layers, is accounted for in complicated geotechnical problems. Classical optimization algorithms are not suitable for solving such problems as they need a proper preliminary solution to converge to a valid result. Therefore, it is necessary to find a proper algorithm which is capable of finding the best global solution. Recently a lot of metaheuristic algorithms have been proposed which are able to evade local minima effectively. In this study four evolutionary algorithms, including well‐known and recent ones, such as genetic algorithm, differential evolution, evolutionary strategy and biogeography‐based optimization (BBO), are applied in slope stability analysis and their efficiencies are explored by three benchmark case studies. Result show BBO is the most efficient among these evolutionary algorithms and other proposed algorithms applied to this problem. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
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根据重力梯度观测各分量的方差及协方差信息,提出了利用GOCE梯度数据计算径向重力梯度的优化方法。首先给出了径向重力梯度的计算方法,并深入分析了误差传播规律,通过建立相应的条件极值问题,给出了计算径向重力梯度最优组合因子的方法;通过模拟数据验证了本文所提出的优化因子的优越性。实际数据计算表明:相对于传统方法,采用优化组合因子可使反演所得引力位模型的累积大地水准面精度在250阶时提高约2 cm。由于径向重力梯度不仅可以用于地球引力场模型的求解,也可直接应用于地球物理问题的讨论,因此本文所提出的优化方法也可对部分地球动力学问题的讨论提供方便。 相似文献
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The bus route map is a diagram that aims to convey necessary information for map readers to find an appropriate way of moving from an origin to a destination. Design of bus route map is a complicated and time-consuming task that requires careful consideration of readability and aesthetics. This paper proposes a new computational method for designing bus route maps. The method helps us to reduce six types of undesirable elements in bus route maps, i.e., gap, shift, crossing, overlap, misalignment, and acute bend. The method consists of two phases: line layout phase determines the relative order of bus routes on each road segment and map layout phase calculates the actual position of bus routes drawn on a map. This paper applies the method to the design of bus route maps of Chiba City, Japan. The result supports the effectiveness of the method as well as reveals open topics for future research. 相似文献
68.
基于灵敏度分析的海洋油气资源BP神经网络预测模型的优化 总被引:2,自引:2,他引:0
作者针对BP神经网络结构设计中存在的问题,提出利用灵敏度分析方法对BP神经网络预测模型进行优化。通过BP算法与参数灵敏度分析的结合,寻找网络输入属性与输出属性之间的影响因子;在保证精度的前提下优选网络输入属性,简化网络结构,以增强网络的泛化能力,减少人为主观因素对网络设计的影响。最后以海洋油气资源预测为例,结合实测资料建立BP神经网络预测模型并进行了优化及预测精度评价,表明优化后的模型既能有效提高油气资源预测结果的稳定性,又不损失预测精度。 相似文献
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Ran Wei Alan T. Murray 《International journal of geographical information science》2016,30(3):432-450
Location siting is an important part of service provision, with much potential to impact operational efficiency, safety, security, system reliability, etc. A class of location models seeks to optimize coverage of demand for service that is continuously distributed across space. Decision-making and planning contexts include police/fire resource allocation for a community, siting cellular towers to support cell phone signal transmission, locating emergency warning sirens to alert the public of severe weather and other related dangers, and many others as well. When facilities can be sited anywhere in continuous space to provide coverage to an entire region, this is a very computationally challenging problem to solve because potential demand for service is everywhere and there are an infinite number of potential facility sites to consider. This article develops a new parallel solution approach for this location coverage optimization problem through an iterative bounding scheme on multi-core architectures. The developed approach is applied to site emergency warning sirens in Dublin, Ohio, and fire stations in Elk Grove, California. Results demonstrate the effectiveness and efficiency of the proposed approach, enabling real-time analysis and planning. This work illustrates that the integration of cyberinfrastructure can significantly improve computational efficiency in solving challenging spatial optimization problems, fitting the themes of this special issue: cyberinfrastructure, GIS, and spatial optimization. 相似文献