This paper describes a strategy for merging daily precipitation information from gauge observations, satellite estimates (SEs), and numerical predictions at the global scale. The strategy is designed to remove syste...This paper describes a strategy for merging daily precipitation information from gauge observations, satellite estimates (SEs), and numerical predictions at the global scale. The strategy is designed to remove systemic bias and random error from each individual daily precipitation source to produce a better gridded global daily precipitation product through three steps. First, a cumulative distribution function matching procedure is performed to remove systemic bias over gauge-located land areas. Then, the overall biases in SEs and model predictions (MPs) over ocean areas are corrected using a rescaled strategy based on monthly precipitation. Third, an optimal interpolation (OI)-based merging scheme (referred as the HL-OI scheme) is used to combine unbiased gahge observations, SEs, and MPs to reduce random error from each source and to produce a gauge--satellite-model merged daily precipitation analysis, called BMEP-d (Beijing Climate Center Merged Estimation of Precipitation with daily resolution), with complete global coverage. The BMEP-d data from a four-year period (2011- 14) demonstrate the ability of the merging strategy to provide global daily precipitation of substantially improved quality. Benefiting from the advantages of the HL-OI scheme for quantitative error estimates, the better source data can obtain more weights during the merging processes. The BMEP-d data exhibit higher consistency with satellite and gauge source data at middle and low latitudes, and with model source data at high latitudes. Overall, independent validations against GPCP-1DD (GPCP one-degree daily) show that the consistencies between B MEP-d and GPCP-1DD are higher than those of each source dataset in terms of spatial pattern, temporal variability, probability distribution, and statistical precipitation events.展开更多
Envelope inversion(El)is an efficient tool to mitigate the nonlinearity of conventional full waveform inversion(FWI)by utilizing the ultralow-frequency component in the seismic data.However,the performance of envelope...Envelope inversion(El)is an efficient tool to mitigate the nonlinearity of conventional full waveform inversion(FWI)by utilizing the ultralow-frequency component in the seismic data.However,the performance of envelope inversion depends on the frequency component and initial model to some extent.To improve the convergence ability and avoid the local minima issue,we propose a convolution-based envelope inversion method to update the low-wavenumber component of the velocity model.Besides,the multi-scale inversion strategy(MCEI)is also incorporated to improve the inversion accuracy while guaranteeing the global convergence.The success of this method relies on modifying the original envelope data to expand the overlap region between observed and modeled envelope data,which in turn expands the global minimum basin of misfit function.The accurate low-wavenumber component of the velocity model provided by MCEI can be used as the migration model or an initial model for conventional FWI.The numerical tests on simple layer model and complex BP 2004 model verify that the proposed method is more robust than El even when the initial model is coarse and the frequency component of data is high.展开更多
The development of modern cities has brought about tremendous changes in the climate environment.Faced with complex climate conditions,research on multi-scale climate change in cities is of great significance.The urba...The development of modern cities has brought about tremendous changes in the climate environment.Faced with complex climate conditions,research on multi-scale climate change in cities is of great significance.The urban environmental climate maps and the application of climate atlas tool in Stuttgart,Germany were studied,and the multi-scale application of urban environmental climate maps in Stuttgart,Germany was summarized through the analysis of the pre-planning,current construction situation,and landscape reconstruction of the German"Stuttgart 21"plan case.Besides,other important measures to cope with climate change in German were proposed,and finally multi-scale practical strategies to cope with urban climate and environment were summarized to provide ideas and methods for improving China’s future urban climate environment.展开更多
The paper first analyzes the achievement of BOE's merging case and substantiates its success, then focuses on the strategy analysis of merger of the BOE, including the guidelines, merging way, strategic overall arran...The paper first analyzes the achievement of BOE's merging case and substantiates its success, then focuses on the strategy analysis of merger of the BOE, including the guidelines, merging way, strategic overall arrangement, culture conformity, financial guarantee etc., in a bid to offer valuable experience and reference function for the Chinese enterprises.展开更多
汽车行业智能化和网联化的发展使车辆轨迹能够实现精细化控制,为改进城市交叉口交通信号控制方法提供了新思路。本文提出一种基于非冲突合流策略的灵活信号控制方法,将同时容纳直行和左转来车的合流相位定义为非冲突相位,在双环相位结...汽车行业智能化和网联化的发展使车辆轨迹能够实现精细化控制,为改进城市交叉口交通信号控制方法提供了新思路。本文提出一种基于非冲突合流策略的灵活信号控制方法,将同时容纳直行和左转来车的合流相位定义为非冲突相位,在双环相位结构基础上融入合流策略,形成一种具备12个动作空间的双环合流信号相位结构。在优化相位结构基础上,进一步提出改进的强化学习算法求解信号配时,以车辆到达情况为输入,当前状态下车辆等待时间最小为目标,充分考虑双环结构下相位切换的实际规律,学习当前状态下的最优相位控制策略。在SUMO(Simulation of Urban Mobility)仿真中根据算例需求生成场景数据,对比传统双环结构和双环合流相位结构在感应控制和改进强化学习算法下的不同控制策略的性能指标,分析网联车渗透率对控制效果的影响。结果显示:基于非冲突合流策略和改进强化学习算法能够在提升相位切换灵活性的基础上生成更加符合现实规律的相位配时方案;在不同交通流量条件,尤其是高流量和交通量分布不均衡的场景下,相较于双环相位结构和感应控制方法降低约37%的车均延误,提升了信号控制方案实际运行效果。展开更多
基金supported by the National Natural Science Foundation of China (Grant Nos. 41275076, 41305057, 41175066, 41175086, and 40905046)the Beijing Natural Science Foundation (Grant No. 8144046)+1 种基金the National High Technology Research and Development Program of China (Grant Nos. 2009AA122005 and 2009BAC51B03)the National Basic Research Program of China (Grant No. 2010CB 951902)
文摘This paper describes a strategy for merging daily precipitation information from gauge observations, satellite estimates (SEs), and numerical predictions at the global scale. The strategy is designed to remove systemic bias and random error from each individual daily precipitation source to produce a better gridded global daily precipitation product through three steps. First, a cumulative distribution function matching procedure is performed to remove systemic bias over gauge-located land areas. Then, the overall biases in SEs and model predictions (MPs) over ocean areas are corrected using a rescaled strategy based on monthly precipitation. Third, an optimal interpolation (OI)-based merging scheme (referred as the HL-OI scheme) is used to combine unbiased gahge observations, SEs, and MPs to reduce random error from each source and to produce a gauge--satellite-model merged daily precipitation analysis, called BMEP-d (Beijing Climate Center Merged Estimation of Precipitation with daily resolution), with complete global coverage. The BMEP-d data from a four-year period (2011- 14) demonstrate the ability of the merging strategy to provide global daily precipitation of substantially improved quality. Benefiting from the advantages of the HL-OI scheme for quantitative error estimates, the better source data can obtain more weights during the merging processes. The BMEP-d data exhibit higher consistency with satellite and gauge source data at middle and low latitudes, and with model source data at high latitudes. Overall, independent validations against GPCP-1DD (GPCP one-degree daily) show that the consistencies between B MEP-d and GPCP-1DD are higher than those of each source dataset in terms of spatial pattern, temporal variability, probability distribution, and statistical precipitation events.
基金supported by the National Science Foundation(Grant No.41104069,41274124)National“973 Project”(Grant No.2014CB239006)+1 种基金National Oil and Gas Project(Grant No.2016ZX05014001,2016ZX05002)supported by Tai Shan Science Foundation for the Excellent Youth Scholars.
文摘Envelope inversion(El)is an efficient tool to mitigate the nonlinearity of conventional full waveform inversion(FWI)by utilizing the ultralow-frequency component in the seismic data.However,the performance of envelope inversion depends on the frequency component and initial model to some extent.To improve the convergence ability and avoid the local minima issue,we propose a convolution-based envelope inversion method to update the low-wavenumber component of the velocity model.Besides,the multi-scale inversion strategy(MCEI)is also incorporated to improve the inversion accuracy while guaranteeing the global convergence.The success of this method relies on modifying the original envelope data to expand the overlap region between observed and modeled envelope data,which in turn expands the global minimum basin of misfit function.The accurate low-wavenumber component of the velocity model provided by MCEI can be used as the migration model or an initial model for conventional FWI.The numerical tests on simple layer model and complex BP 2004 model verify that the proposed method is more robust than El even when the initial model is coarse and the frequency component of data is high.
基金Sponsored by General Project of Natural Science Foundation of Beijing City(8202017)。
文摘The development of modern cities has brought about tremendous changes in the climate environment.Faced with complex climate conditions,research on multi-scale climate change in cities is of great significance.The urban environmental climate maps and the application of climate atlas tool in Stuttgart,Germany were studied,and the multi-scale application of urban environmental climate maps in Stuttgart,Germany was summarized through the analysis of the pre-planning,current construction situation,and landscape reconstruction of the German"Stuttgart 21"plan case.Besides,other important measures to cope with climate change in German were proposed,and finally multi-scale practical strategies to cope with urban climate and environment were summarized to provide ideas and methods for improving China’s future urban climate environment.
文摘The paper first analyzes the achievement of BOE's merging case and substantiates its success, then focuses on the strategy analysis of merger of the BOE, including the guidelines, merging way, strategic overall arrangement, culture conformity, financial guarantee etc., in a bid to offer valuable experience and reference function for the Chinese enterprises.
文摘汽车行业智能化和网联化的发展使车辆轨迹能够实现精细化控制,为改进城市交叉口交通信号控制方法提供了新思路。本文提出一种基于非冲突合流策略的灵活信号控制方法,将同时容纳直行和左转来车的合流相位定义为非冲突相位,在双环相位结构基础上融入合流策略,形成一种具备12个动作空间的双环合流信号相位结构。在优化相位结构基础上,进一步提出改进的强化学习算法求解信号配时,以车辆到达情况为输入,当前状态下车辆等待时间最小为目标,充分考虑双环结构下相位切换的实际规律,学习当前状态下的最优相位控制策略。在SUMO(Simulation of Urban Mobility)仿真中根据算例需求生成场景数据,对比传统双环结构和双环合流相位结构在感应控制和改进强化学习算法下的不同控制策略的性能指标,分析网联车渗透率对控制效果的影响。结果显示:基于非冲突合流策略和改进强化学习算法能够在提升相位切换灵活性的基础上生成更加符合现实规律的相位配时方案;在不同交通流量条件,尤其是高流量和交通量分布不均衡的场景下,相较于双环相位结构和感应控制方法降低约37%的车均延误,提升了信号控制方案实际运行效果。