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Variability and trends of near-surface wind speed over the Tibetan Plateau:The role played by the westerly and Asian monsoon

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Advances in Climate Change Research 2024年第3期15卷 525-536页

作者： Gang-Feng ZHANG Cesar AZORIN-MOLINA Deliang CHEN Tim RMCVICAR Jose AGUIJARRO Kai-Qiang DENG Lorenzo MINOLA Jaeyeon LEE Seok-Woo SON Heng MA Pei-Jun SHI State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal UniversityBeijing 100875China Engineering Center of Desertification and Blown-Sand Control of Ministry of Education Faculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education Beijing Normal UniversityBeijing 100875China Centro de Investigaciones Sobre Desertificaci'on Consejo Superior de Investigaciones Cientı'ficas(CIDECSIC-UV-Generalitat alenciana)ClimateAtmosphere and Ocean Laboratory(Climatoc-Lab)Moncada 46113Spain Regional Climate Group Department of Earth SciencesUniversity of GothenburgGothenburg 40530Sweden CSIRO Environment CanberraACT 2600Australia Australian Research Council Centre of Excellence for Climate Extremes CanberraACT 2600Australia State Meteorological Agency Balearic Islands OfficePalma de Mallorca 07015Spain School of Atmospheric Sciences Sun Yat-sen UniversityZhuhai 519082China Interuniversity Department of Regional and Urban Studies and Planning(DIST) Politecnico and University of TurinTurin 10125Italy School of Earth and Environmental Sciences Seoul National UniversitySeoul 08826South Korea Atmospheric and Oceanic Sciences Program Princeton UniversityPrinceton NJ 08544USA Geophysical Fluid Dynamics Laboratory NOAAPrinceton NJ 08544USA

Near-surface wind speed exerts profound impacts on many environmental issues,while the long-term(≥60 years)trend and multidecadal variability in the wind speed and its underlying causes in global high-elevation and mountainous areas(e.g.,Tibetan Plateau)remain largely ***,by examining homogenized wind speed data from 104 meteorological stations over the Tibetan Plateau for 1961-2020 and ERA5 reanalysis datasets,we investigated the variability and long-term trend in the near-surface wind speed and revealed the role played by the westerly and Asian *** results show that the homogenized annual wind speed displays a decreasing trend(-0.091 m s^(−1)per decade,p<0.05),with the strongest in spring(-0.131 m s^(−1)per decade,p<0.05),and the weakest in autumn(-0.071 m s^(−1)per decade,p<0.05).There is a distinct multidecadal variability of wind speed,which manifested in an prominent increase in 1961-1970,a sustained decrease in 1970-2002,and a consistent increase in *** observed decadal variations are likely linked to large-scale atmospheric circulation,and the correlation analysis unveiled a more important role of westerly and East Asian winter monsoon in modulating near-surface wind changes over the Tibetan *** potential physical processes associated with westerly and Asian monsoon changes are in concordance with wind speed change,in terms of overall weakened horizontal air flow(i.e.,geostrophic wind speed),declined vertical thermal and dynamic momentum transfer(i.e.,atmospheric stratification thermal instability and vertical wind shear),and varied Tibetan Plateau *** indicates that to varying degrees these processes may have contributed to the changes in near-surface wind speed over the Tibetan *** study has implications for wind power production and soil wind erosion prevention in the Tibetan Plateau.

关键词： Tibetan Plateau Wind speed Decadal change Atmospheric circulation Physical processes

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Abrupt emissions reductions during COVID-19 contributed to record summer rainfall in China (vol 13, pg 1, 2022)

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NATURE COMMUNICATIONS 2022年第1期13卷 959页

作者： Yang, Yang Ren, Lili Wu, Mingxuan Wang, Hailong Song, Fengfei Leung, L. Ruby Hao, Xin Li, Jiandong Chen, Lei Li, Huimin Zeng, Liangying Zhou, Yang Wang, Pinya Liao, Hong Wang, Jing Zhou, Zhen-Qiang Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology School of Environmental Science and Engineering Nanjing University of Information Science and Technology Nanjing Jiangsu China. yang.yang@***. Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology School of Environmental Science and Engineering Nanjing University of Information Science and Technology Nanjing Jiangsu China. Atmospheric Sciences and Global Change Division Pacific Northwest National Laboratory Richland WA USA. Atmospheric Sciences and Global Change Division Pacific Northwest National Laboratory Richland WA USA. hailong.wang@pnnl.gov. Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster Ministry of Education Nanjing University for Information Science and Technology Nanjing Jiangsu China. Tianjin Key Laboratory for Oceanic Meteorology Tianjin Institute of Meteorological Science Tianjin China. Department of Atmospheric and Oceanic Sciences and Institute of Atmospheric Sciences Fudan University Shanghai China.

Record rainfall and severe flooding struck eastern China in the summer of 2020. The extreme summer rainfall occurred during the COVID-19 pandemic, which started in China in early 2020 and spread rapidly across the globe. By disrupting human activities, substantial reductions in anthropogenic emissions of greenhouse gases and aerosols might have affected regional precipitation in many ways. Here, we investigate such connections and show that the abrupt emissions reductions during the pandemic strengthened the summer atmospheric convection over eastern China, resulting in a positive sea level pressure anomaly over northwestern Pacific Ocean. The latter enhanced moisture convergence to eastern China and further intensified rainfall in that region. Modeling experiments show that the reduction in aerosols had a stronger impact on precipitation than the decrease of greenhouse gases did. We conclude that through abrupt emissions reductions, the COVID-19 pandemic contributed importantly to the 2020 extreme summer rainfall in eastern China.

关键词： Atmospheric chemistry

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Synergetic roadmap of carbon neutrality and clean air for China

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Environmental Science and Ecotechnology 2023年第4期16卷 1-25页

作者： Qiang Zhang Zhicong Yin Xi Lu Jicheng Gong Yu Lei Bofeng Cai Cilan Cai Qimin Chai Huopo Chen Hancheng Dai Zhanfeng Dong Guannan Geng Dabo Guan Jianlin Hu Cunrui Huang Jianing Kang Tiantian Li Wei Li Yongsheng Lin Jun Liu Xin Liu Zhu Liu Jinghui Ma Guofeng Shen Dan Tong Xuhui Wang Xuying Wang Zhili Wang Yang Xie Honglei Xu Tao Xue Bing Zhang Da Zhang Shaohui Zhang Shaojun Zhang Xian Zhang Bo Zheng Yixuan Zheng Tong Zhu Jinnan Wang Kebin He Ministry of Education Key Laboratory for Earth System Modelling Department of Earth System ScienceTsinghua UniversityBeijing100084China Key Laboratory of Meteorological Disaster Ministry of Education/Joint International Research Laboratory of Climate and Environment Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)Nanjing University of Information Science&TechnologyNanjing210044China State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing100084China Institute for Carbon Neutrality Tsinghua UniversityBeijing100084China State Key Joint Laboratory for Environment Simulation and Pollution Control College of Environmental Sciences and Engineering and Center for Environment and HealthPeking UniversityBeijing100871China Center of Air Quality Simulation and System Analysis Chinese Academy of Environmental PlanningBeijing100012China Center for Carbon Neutrality Chinese Academy of Environmental PlanningBeijing100012China National Center for Climate Change Strategy and International CooperationBeijing100035China Nansen-Zhu International Research Centre Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing100029China College of Environmental Sciences and Engineering Peking UniversityBeijing100871China Institute of Environmental Policy Management Chinese Academy of Environmental PlanningBeijing100012China Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control School of Environmental Science and EngineeringCollaborative Innovation Center of Atmospheric Environment and Equipment TechnologyNanjing University of Information Science and TechnologyNanjing210044China Vanke School of Public Health Tsinghua UniversityBeijing100084China Center for Energy and Environmental Policy Research Beijing Institute of TechnologyBeijing100081China China CDC Key Laboratory of Environment and Population Health National Institute of En

It is well recognized that carbon dioxide and air pollutants share similar emission sources so that synergetic policies on climate change mitigation and air pollution control can lead to remarkable co-benefits on greenhouse gas reduction,air quality improvement,and improved *** the context of carbon peak,carbon neutrality,and clean air policies,this perspective tracks and analyzes the process of the synergetic governance of air pollution and climate change in China by developing and monitoring 18 *** 18 indicators cover the following five aspects:air pollution and associated weather-climate conditions,progress in structural transition,sources,inks,and mitigation pathway of atmospheric composition,health impacts and benefits of coordinated control,and synergetic governance system and *** tracking the progress in each indicator,this perspective presents the major accomplishment of coordinated control,identifies the emerging challenges toward the synergetic governance,and provides policy recommendations for designing a synergetic roadmap of Carbon Neutrality and Clean Air for China.

关键词： Carbon neutrality Clean air Synergetic roadmap

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Influence of Riboflavin on the Corrosion of X80 Pipeline Steel by Sulfate Reducing Bacteria

SSRN

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SSRN 2023年

作者： Fu, Lei Lin, Li Yan, Shisen Luo, Yunrong Zhang, Yingqian Lai, Sheng Wang, Zhengguo Tan, Mingxing School of Mechanical Engineering Sichuan University of Science & Engineering Zigong643000 China Failure Mechanics and Engineering Disaster Prevention Key Lab of Sichuan Province Sichuan University Chengdu610065 China Key Laboratory of Deep Earth Science and Engineering Sichuan University Ministry of Education Chengdu610065 China School of Material Science and Engineering Sichuan University of Science & Engineering Zigong643000 China Vanadium and Titanium Resource Comprehensive Utilization Key Laboratory of Sichuan Province Panzhihua617000 China Sichuan Provincial Key Lab of Process Equipment and Control Zigong643000 China School of Civil Engineering Sichuan University of Science & Engineering Zigong643000 China

Sulfate reducing bacteria (SRB) are facultative anaerobic, and the electron transfer process of their growth and metabolic activities is as follows: the electrons released from the metal surface pass through the cell wall into the cell by extracellular electron transfer, and the electron shuttle to the body plays the role of electron transfer between cells and metals. In this study, the effect of riboflavin (RF) as an electron shuttle on SRB corrosion of X80 pipeline steel was analyzed. The results showed that the addition of 10 ppm RF to the SRB medium did not significantly change the type of corrosion products, but resulted in an enlarged corrosion pit area and an increased pit depth. The corrosion weight loss rate of the SRB + 10 ppm RF system is about 3 times that of the SRB system, and the corrosion current density of the polarization curve is about 38% higher than that of the SRB system. Therefore, RF can transfer the electrons released by iron oxidation to the cytoplasm by means of electron transfer across the cell wall, thereby accelerating the corrosion of X80 steel. This further proves that the electronic medium RF can accelerate the microbial influenced corrosion (MIC) caused by SRB. © 2023, The Authors. All rights reserved.

关键词： Electron transport properties

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Artificial intelligence for geoscience:Progress,challenges,and perspectives

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The Innovation 2024年第5期5卷 136-160,135页

作者： Tianjie Zhao Sheng Wang Chaojun Ouyang Min Chen Chenying Liu Jin Zhang Long Yu Fei Wang Yong Xie Jun Li Fang Wang Sabine Grunwald Bryan MWong Fan Zhang Zhen Qian Yongjun Xu Chengqing Yu Wei Han Tao Sun Zezhi Shao Tangwen Qian Zhao Chen Jiangyuan Zeng Huai Zhang Husi Letu Bing Zhang Li Wang Lei Luo Chong Shi Hongjun Su Hongsheng Zhang Shuai Yin Ni Huang Wei Zhao Nan Li Chaolei Zheng Yang Zhou Changping Huang Defeng Feng Qingsong Xu Yan Wu Danfeng Hong Zhenyu Wang Yinyi Lin Tangtang Zhang Prashant Kumar Antonio Plaza Jocelyn Chanussot Jiabao Zhang Jiancheng Shi Lizhe Wang Aerospace Information Research Institute Chinese Academy of SciencesBeijing 100094China School of Computer Science China University of GeosciencesWuhan 430078China State Key Laboratory of Mountain Hazards and Engineering Resilience Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610299China Key Laboratory of Virtual Geographic Environment(Ministry of Education of PRC) Nanjing Normal UniversityNanjing 210023China Data Science in Earth Observation Technical University of Munich80333 MunichGermany The National Key Laboratory of Water Disaster Prevention Yangtze Institute for Conservation and DevelopmentHohai UniversityNanjing 210098China Institute of Computing Technology Chinese Academy of SciencesBeijing 100190China School of Geographical Sciences Nanjing University of Information Science and TechnologyNanjing 210044China State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of SciencesNanjing 210008China Soil Water and Ecosystem Sciences DepartmentUniversity of FloridaPO Box 110290GainesvilleFLUSA Materials Science Engineering Program Cooperating Faculty Member in the Department of Chemistry and Department of Physics Astronomy University of CaliforniaCaliforniaRiversideCA 92521USA Institute of Remote Sensing and Geographical Information System School of Earth and Space SciencesPeking UniversityBeijing 100871China Key Laboratory of Computational Geodynamics University of Chinese Academy of SciencesBeijing 100049China International Research Center of Big Data for Sustainable Development Goals Beijing 100094China College of Geography and Remote Sensing Hohai UniversityNanjing 211100China Department of Geography The University of Hong KongHong Kong 999077SARChina Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Nanjing 210044China School of Environmental Science and Engineering Nanjing University of Information Science&TechnologyNanjing 210044China Collaborative Inno

This paper explores the evolution of geoscientific inquiry,tracing the progression from traditional physics-based models to modern data-driven approaches facilitated by significant advancements in artificial intelligence(AI)and data collection *** models,which are grounded in physical and numerical frameworks,provide robust explanations by explicitly reconstructing underlying physical ***,their limitations in comprehensively capturing Earth’s complexities and uncertainties pose challenges in optimization and real-world *** contrast,contemporary data-driven models,particularly those utilizing machine learning(ML)and deep learning(DL),leverage extensive geoscience data to glean insights without requiring exhaustive theoretical *** techniques have shown promise in addressing Earth science-related ***,challenges such as data scarcity,computational demands,data privacy concerns,and the“black-box”nature of AI models hinder their seamless integration into *** integration of physics-based and data-driven methodologies into hybrid models presents an alternative *** models,which incorporate domain knowledge to guide AI methodologies,demonstrate enhanced efficiency and performance with reduced training data *** review provides a comprehensive overview of geoscientific research paradigms,emphasizing untapped opportunities at the intersection of advanced AI techniques and *** examines major methodologies,showcases advances in large-scale models,and discusses the challenges and prospects that will shape the future landscape of AI in *** paper outlines a dynamic field ripe with possibilities,poised to unlock new understandings of Earth’s complexities and further advance geoscience exploration.

关键词： Earth utilizing landscape

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Large potential of strengthening the land carbon sink in China through anthropogenic interventions

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Science Bulletin 2024年第16期69卷 2622-2631页

作者： Xu Yue Hao Zhou Yang Cao Hong Liao Xiaofei Lu Zhen Yu Wenping Yuan Zhu Liu Yadong Lei Stephen Sitch Jürgen Knauer Huijun Wang Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment TechnologySchool of Environmental Science and EngineeringNanjing University of Information Science&Technology(NUIST)Nanjing 210044China College of Meteorology and Oceanography National University of Defense TechnologyChangsha 410073China Jiangsu Nanjing Environmental Monitoring Center Nanjing 210013China Key Laboratory of Agrometeorology of Jiangsu Province Institute of EcologySchool of Applied MeteorologyNUISTNanjing 210044China Institute of Carbon Neutrality Sino-French Institute for Earth System ScienceCollege of Urban and Environmental SciencesPeking UniversityBeijing 100871China Department of Earth System Science Tsinghua UniversityBeijing 100084China State Key Laboratory of Severe Weather and Key Laboratory of Atmospheric Chemistry of CMA Chinese Academy of Meteorological SciencesBeijing 100081China College of Life and Environmental Sciences University of ExeterExeter EX44RJUK Hawkesbury Institute for the Environment Western Sydney UniversityPenrith 2751Australia Key Laboratory of Meteorological Disaster Ministry of EducationJoint International Research Laboratory of Climate and Environment ChangeCollaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNUISTNanjing 210044China

The terrestrial ecosystem in China mitigates 21%-45%of the national contemporary fossil fuel CO_(2) emissions every *** and strengthening the land carbon sink is essential for reaching China’s target of carbon ***,this sink is subject to large uncertainties due to the joint impacts of climate change,air pollution,and human ***,we explore the potential of strengthening land carbon sink in China through anthropogenic interventions,including forestation,ozone reduction,and litter removal,taking advantage of a well-validated dynamic vegetation model and meteorological forcings from 16 climate *** anthropogenic interventions,considering Shared Socioeconomic Pathways(SSP)scenarios,the land sink is projected to be 0.26-0.56 Pg C a^(-1) at 2060,to which climate change contributes 0.06-0.13 Pg C a^(-1) and CO_(2) fertilization contributes 0.08-0.44 Pg C a^(-1) with the stronger effects for higher emission *** anthropogenic interventions,under a close-to-neutral emission scenario(SSP1-2.6),the land sink becomes 0.47-0.57 Pg C a^(-1) at 2060,including the contributions of 0.12 Pg C a^(-1) by conservative forestation,0.07 Pg C a^(-1) by ozone pollution control,and 0.06-0.16 Pg C a^(-1) by 20%litter removal over planted *** sink can mitigate 90%-110% of the residue anthropogenic carbon emissions in 2060,providing a solid foundation for the carbon neutrality in China.

关键词： Carbon sink Forestation Ozone Litter removal

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The mechanical mechanism and plastic hinge behavior of novel precast prestressed steel reinforced concrete composite frames with PVA fiber-reinforced ECC cast-in-place joints subjected to monotonic load

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Structures 2025年 79卷

作者： Jing Ji Xuan Chu Liangqin Jiang Zhanbin Zhang Xiaomeng Hou Pengguang Qi Heilongjiang Key Lab of Disaster Prevention Mitigation and Protection Engineering Northeast Petroleum University Daqing 163319 China Heilongjiang Provincial Key Laboratory of Thermal Utilization and Disaster Reduction of New Energy in Cold Regions Northeast Petroleum University Daqing 163319 China Key Laboratory of Structural Disaster and Control of the Ministry of Education Harbin Institute of Technology Harbin 150040 China

In this paper, a novel type of precast prestressed steel reinforced concrete composite frames with PVA fiber-reinforced engineering cementitious composites (PVA-ECC) cast-in-place joints (PSCEFs) is systematically proposed. It consists of precast prestressed steel reinforced concrete beams (PSRCBs), precast small-diameter concrete-filled steel tube gradient strength composite columns (SGCCs), and PVA-ECC cast-in-place joints. To investigate the stress mechanism of the PSCEFs under monotonic loading, refined three-dimensional finite element models of 15 PSCEFs and 2 precast prestressed steel reinforced concrete composite frames with ordinary concrete cast-in-place joints (PSCCFs) are established based on the nonlinear constitutive models of several materials and the geometric nonlinearity of structures. The rationality of the modeling method is well verified by referring to existing tests. The effects of different parameters on the ultimate bearing capacity, ductility, and initial stiffness for PSCEFs are studied, and the results indicate that the stirrup characteristic value ( λ v ) and axial compression ratio ( n ) of SGCCs have a remarkable impact on the ultimate bearing capacity of PSCEFs. The displacement ductility coefficients of PSCEFs are mainly above 4.0, and the initial stiffness is about 15 % higher than that of PSCCFs, so PSCEFs have better ductility and suitable deformation resistance. By comparing the collapse resistance and failure modes for typical specimens of PSCEFs and PSCCFs, it is discovered that the joints poured with PVA-ECC can effectively control the range of plastic strain distribution in the frames. The yield lengths of shaped steel, steel reinforcement, and concrete in PSCEFs are reduced by approximately 5–20 % compared to those of PSCCFs. The failure characteristics and plastic hinges law of PSCEFs are systematically summarized, and the plastic hinge length prediction models with an error of less than 10 % are proposed by introducing seve

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Essential Stressing State Features of Laterally Loaded Masonry Wall Panels Revealed from Experimental Displacements

Research Square

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Research Square 2021年

作者： Liu, Bai Li, Rui Zhang, Yu Zhou, Guangchun Key Lab of Structures Dynamic Behavior and Control of China Ministry of Education Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology School of Civil Engineering Harbin Institute of Technology Harbin150090 China Urban and Engineering Disaster Prevention Laboratory Institute of Engineering Mechanics China Earthquake Administration Harbin150086 China

This study reveals the essential and general working features of laterally loaded masonry (LLM) wall panels from their experimental displacements by applying structural stressing state theory. Firstly, the generalized work of force is proposed to express the stressing state mode and its characteristic parameter. Then, the Mann-Kendall criterion is applied to detect the mutation point in the curve of the characteristic parameter with the load increase. Correspondingly, it is verified that the evolution of the stressing state mode also embodies the mutation feature. The stressing state mutation feature is inherent and common as the embodiment of the natural law from quantitative change to qualitative change of a system. The stressing state mutation feature reveals the starting point of structural failure process, which could update the existing definition of structural failure load. Further, the elastoplastic branch (EPB) point is revealed referring to the updated failure load, which might be directly taken as the design load with the rational margin of safety. In a sense, this paper presents a new way to address the classic issue of structural load-bearing capacity uncertainty and to update the existing design codes of LLM wall panels. © 2021, CC BY.

关键词： Fracture mechanics

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A change-point detection method for detecting and locating the abrupt changes in distributions of damage-sensitive features of SHM data, with application to structural condition assessment

arXiv

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arXiv 2021年

作者： Lei, Xinyi Chen, Zhichng Li, Hui Wei, Shiyin Key Lab of Intelligent Disaster Mitigation The Ministry of Industry and Information Technology Harbin Institute of Technology Harbin150090 China Key Lab of Structures Dynamic Behavior and Control The Ministry of Education Harbin Institute of Technology Harbin150090 China School of Civil Engineering Harbin Institute of Technology Harbin150090 China

Diagnosing the changes of structural behaviors using monitoring data is an important objective of structural health monitoring (SHM). The changes in structural behaviors are usually manifested as the feature changes in monitored structural responses;thus, developing effective methods for automatically detecting such changes is of considerable significance. Existing methods for change detection in SHM are mainly used for scalar or vector data, thus incapable of detecting the changes of the features represented by complex data, e.g., the probability density functions (PDFs). Detecting the abrupt changes occurred in the distributions (represented by PDFs) associated with the damage-sensitive features extracted from SHM data are usually of crucial interest for structural condition assessment;however, the SHM community still lacks effective diagnostic tools for detecting such changes. In this study, a change-point detection method is developed in the functional data-analytic framework for PDF-valued sequence, and it is leveraged to diagnose the distributional information break encountered in structural condition assessment. A major challenge in PDF-valued data modeling or analysis is that the PDFs are special functional data subjecting to nonlinear constraints. To tackle this issue, the PDFs are embedded into the Bayes space, and the associated change-point model is constructed by using the linear structure of the Bayes space;then, a hypothesis testing procedure is presented for distributional change-point detection based on the isomorphic mapping between the Bayes space and a functional linear space. Comprehensive simulation studies are conducted to validate the effectiveness of the proposed method as well as demonstrate its superiority over the competing method. Finally, an application to real SHM data illustrates its practical utility in structural condition assessment. Copyright © 2021, The Authors. All rights reserved.

关键词： Probability density function

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Functional outlier detection for density-valued data with application to robustify distribution to distribution regression

arXiv

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arXiv 2021年

作者： Lei, Xinyi Chen, Zhicheng Li, Hui Key Lab of Intelligent Disaster Mitigation of the Ministry of Industry and Information Technology Harbin Institute of Technology Harbin150090 China Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education Harbin Institute of Technology Harbin150090 China School of Civil Engineering Harbin Institute of Technology Harbin150090 China

Distributional data analysis, concerned with statistical analysis and modeling for data objects consisting of random probability density functions (PDFs) in the framework of functional data analysis (FDA), has received considerable interest in recent years. However, many important aspects remain unexplored, such as outlier detection and robustness. Existing functional outlier detection methods are mainly used for ordinary functional data and usually perform poorly when applied to PDFs. To fill this gap, this study focuses on PDF-valued outlier detection, as well as its application in robust distributional regression. Similar to ordinary functional data, detecting the shape outlier masked by the "curve net’’ formed by the bulk of the PDFs is the major challenge in PDF-outlier detection. To this end, we propose a tree-structured transformation system for feature extraction as well as converting the shape outliers to easily detectable magnitude outliers, relevant outlier detectors are designed for the specific transformed data. A multiple detection strategy is also proposed to account for detection uncertainties and to combine different detectors to form a more reliable detection tool. Moreover, we propose a distributional-regression-based approach for detecting the abnormal associations of PDF-valued two-tuples. As a specific application, the proposed outlier detection methods are applied to robustify a distribution-to-distribution regression method, and we develop a robust estimator for the regression operator by downweighting the detected outliers. The proposed methods are validated and evaluated by extensive simulation studies or real data applications. Relevant comparative studies demonstrate the superiority of the developed outlier detection method with other competitors in distributional outlier detection. © 2021, CC BY.

关键词： Statistics

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