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Seasonal Forecasts of the Summer 2016 Yangtze River Basin Rainfall

Advances in Atmospheric Sciences 2018年第8期35卷 22-30页

作者： Philip E. BETT Adam A. SCAIFE Chaofan LI Chris HEWITT Nicola GOLDING Peiqun ZHANG Nick DUNSTONE Doug M. SMITH Hazel E. THORNTON Riyu LU Hong-Li REN Met Office Hadley Centre FitzRoy Road Exeter EX1 3PB UK College of Engineering Mathematics and Physical Sciences University of Exeter Exeter Devon EX4 4QF UK Center for Monsoon System Research Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 China Laboratory for Climate Studies National Climate Center China Meteorological Administration Beijing 100081 China State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 China

The Yangtze River has been subject to heavy flooding throughout history, and in recent times severe floods such as those in 1998 have resulted in heavy loss of life and livelihoods. Dams along the river help to manage flood waters, and are important sources of electricity for the region. Being able to forecast high-impact events at long lead times therefore has enormous potential benefit. Recent improvements in seasonal forecasting mean that dynamical climate models can start to be used directly for operational services. The teleconnection from E1 Nifio to Yangtze River basin rainfall meant that the strong E1 Nifio in winter 2015/16 provided a valuable opportunity to test the application of a dynamical forecast system. This paper therefore presents a case study of a real-time seasonal forecast for the Yangtze River basin, building on previous work demonstrating the retrospective skill of such a forecast. A simple forecasting methodology is presented, in which the forecast probabilities are derived from the historical relationship between hindcast and observations. Its performance for 2016 is discussed. The heavy rainfall in the May-June-July period was correctly forecast well in advance. August saw anomalously low rainfall, and the forecasts for the June-July-August period correctly showed closer to average levels. The forecasts contributed to the confidence of decision-makers across the Yangtze River basin. Trials of climate services such as this help to promote appropriate use of seasonal forecasts, and highlight areas for future improvements.

关键词： seasonal forecasting flood forecasting Yangtze basin rainfall ENSO hydroelectricity

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Predictable and Unpredictable Components of the Summer East Asia–Pacific Teleconnection Pattern

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Advances in Atmospheric Sciences 2018年第11期35卷 1372-1380页

作者： Xiaozhen LIN Chaofan LI Riyu LU Adam A.SCAIFE State Key Laboratory of Numerical Modelling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China University of Chinese Academy of Sciences Beijing 100029China Center for Monsoon System Research Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Met Oce Hadley Centre FitzRoy RoadExeter EX1 3PBUK College of Engineering Mathematics and Physical SciencesUniversity of ExeterExeterDevon EX4 4QF UK

The East Asia–Pacific(EAP) teleconnection pattern is the dominant mode of circulation variability during boreal summer over the western North Pacific and East Asia, extending from the tropics to high latitudes. However, much of this pattern is absent in multi-model ensemble mean forecasts, characterized by very weak circulation anomalies in the mid and high latitudes. This study focuses on the absence of the EAP pattern in the extratropics, using state-of-the-art coupled seasonal forecast systems. The results indicate that the extratropical circulation is much less predictable, and lies in the large spread among different ensemble members, implying a large contribution from atmospheric internal variability. However,the tropical–mid-latitude teleconnections are also relatively weaker in models than observations, which also contributes to the failure of prediction of the extratropical circulation. Further results indicate that the extratropical EAP pattern varies closely with the anomalous surface temperatures in eastern Russia, which also show low predictability. This unpredictable circulation–surface temperature connection associated with the EAP pattern can also modulate the East Asian rainband.

关键词： EAP pattern circulation seasonal forecast surface temperature eastern Russia

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Skillful Seasonal Forecasts of Summer Surface Air Temperature in Western China by Global Seasonal Forecast system Version 5

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Advances in Atmospheric Sciences 2018年第8期35卷 59-68页

作者： Chaofan LI Riyu LU Philip E. BETT Adam A. SCAIFE Nicola MARTIN Center for Monsoon System Research Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 China State Key Laboratory of Numerical Modelling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 China University of the Chinese Academy of Sciences Beijing 100029 China Met Office Hadley Centre FitzRoy Road Exeter EX1 3PB UK College of Engineering Mathematics and Physical Sciences University of Exeter Exeter Devon EX4 4QF UK

Variations of surface air temperature （SAT） are key in affecting the hydrological cycle, ecosystems and agriculture in western China in summer. This study assesses the seasonal forecast skill and reliability of SAT in western China, using the GloSea5 operational forecast system from the UK Met Office. Useful predictions are demonstrated, with considerable skill over most regions of western China. The temporal correlation coefficients of SAT between model predictions and observations axe larger than 0.6, in both northwestern China and the Tibetan Plateau. There are two important sources of skill for these predictions in western China： interannual variation of SST in the western Pacific and the SST trend in the tropical Pacific. The tropical SST change in the recent two decades, with a warming in the western Pacific and cooling in the eastern Pacific, which is reproduced well by the forecast system, provides a large contribution to the skill of SAT in northwestern China. Additionally, the interannual variation of SST in the western Pacific gives rise to the reliable prediction of SAT around the Tibetan Plateau. It modulates convection around the Maritime Continent and further modulates the variation of SAT on the Tibetan Plateau via the surrounding circulation. This process is evident irrespective of detrending both in observations and the model predictions, and acts as a source of skill in predictions for the Tibetan Plateau. The predictability and reliability demonstrated in this study is potentially useful for climate services providing early warning of extreme climate events and could imply useful economic benefits.

关键词： seasonal forecast western China surface air temperature predictability warming trend

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Standard Analysis for Transfer Delay in CTCS-3

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Chinese Journal of Electronics 2017年第5期26卷 1057-1063页

作者： CAO Yuan MA Lianchuan XIAO Shuo ZHANG Xia XU Wei National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University School of Computer Sciences and Technology China University of Mining & Technology National Mobile Communications Research Lab. Southeast University

According to the standard for the GSM for railway(GSM-R) wireless systems in China train control system level 3(CTCS-3),the control data transfer delay should be no larger than 500 ms with greater than99% *** of both non-redundant networks and intercross redundant networks and cases of single Mobile terminals(MTs) and redundant MTs on one train are considered,and the corresponding vehicle-ground communication models,delay models,and fault models are *** simulation results confirm that the transfer delay can meet the standard requirements under all *** particular,the probability is greater than 99.996% for redundant MTs and networks,and the standard of transfer delay in CTCS-3 will be improved inevitably.

关键词： China train control system level 3(CTCS-3) GSM for railway(GSM-R) Data transfer delay Deterministic and stochastic petri net(DSPN)

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Stochastic channel modeling for high-speed railway viaduct scenario at 93.2 GHz 12

Stochastic channel modeling for high-speed railway viaduct s...

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12th European Conference on Antennas and Propagation, EuCAP 2018

作者： Wang, Longhe Ai, Bo Guan, Ke He, Danping Zhong, Zhangdui Tian, Li Dou, Jianwu State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Beijing Engineering Research Center of High-Speed Railway Broadband Mobile Communications Beijing100044 China Wireless Algorithm Department Product R and D system ZTE Corporation Shanghai201210 China

ISBN: (纸本)9781785617911

Nowadays, with the rapid development of the high-speed railway, more and more people prefer to using rail traffic for travel or for commuting due to its convenience and flexibility. Railway scenario becomes an important communication scenario in the 5G era. In order to satisfy the increasing demand for higher transmission capabilities, the railway communication system should be designed to support high data rate demands with seamless connectivity. The channel characteristics of viaduct tunnel scenario are studied and modeled in this paper. More channel characteristics are explored by ray-tracing simulations at 93.2 GHz with 2 GHz bandwidth. The critical channel parameters are extracted, supplied, and incorporated into a 3GPP-like random channel generator. The necessary channel information can be practically implemented so that the link level and system level design of the communication system can be supported in similar scenarios. © Institution of engineering and *** Rights Reserved.

关键词： 5G mobile communication systems

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Message from the Guest Editor-in-Chief

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Global Energy Interconnection 2020年第1期3卷 1-1页

作者： Qili Huang Weisheng Wang the Chinese Academy of Engineering the Academic Committees of the State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources the State Key Laboratory of Power Grid Safety and Energy Conservation and the State Key Laboratory of Coal-based Clean Energy Renewable Energy Research Center of China Electric Power Research Institute(CEPRI) the State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems

At present, a new cycle of energy technology revolution coupled with economic and industrial reforms has come to a historical convergence. Consequently, the international energy supply system and industrial division of labor are being reshaped. The large replacement of fossil energy with clean energy is a critical indication for the evolution in the energy structure from the supply side.

关键词： Message from the Guest Editor-in-Chief

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走向智能机床

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engineering 2019年第4期 186-210页

作者：陈吉红胡鹏程周会成杨建中谢杰君蒋亚坤高志强张成磊 National Numerical Control System Engineering Research Center Huazhong University of Science and Technology

随着现代信息技术特别是新一代人工智能技术的发展,智能机床技术迎来了新的发展机遇。本文在中国工程院定义的智能制造三个范式的基础上,系统地阐述了智能机床的概念、内涵、特征和体系架构。揭示了机床从手动机床演化到智能机床的三个... 详细信息

随着现代信息技术特别是新一代人工智能技术的发展,智能机床技术迎来了新的发展机遇。本文在中国工程院定义的智能制造三个范式的基础上,系统地阐述了智能机床的概念、内涵、特征和体系架构。揭示了机床从手动机床演化到智能机床的三个阶段(数控机床、互联网+机床以及智能机床),详细分析了智能机床的自主感知与连接、自主学习与建模、自主优化与决策和自主控制与执行这四项智能化控制的实现原理,提出了智能机床通过数据学习形成并积累知识的本质特征,独创发明了指令域分析方法、物理和大数据混合建模技术、i代码和双码联控等关键使能技术。基于以上研究,研制了智能数控系统和智能机床工业样机。通过基于Cyber NC和双码联控的加工质量优化、基于大数据建模的工艺参数优化和基于深度学习的机床进给系统建模及误差补偿这三个智能化技术应用案例的实践,验证了新一代人工智能技术与制造技术的深度融合,是机床实现从"互联网+机床"向"智能+机床"演化的便捷有效途径。

关键词：智能制造智能机床智能数控系统新一代人工智能

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TransMut: a program to predict HLA-I peptide binding and optimize mutated peptides for vaccine design by the Transformer-derived self-attention model

Research Square

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research Square 2021年

作者： Chu, Yanyi Zhang, Yan Wang, Qiankun Zhang, Lingfeng Wang, Xuhong Wang, Yanjing Wang, Jianmin Jiang, Xue Salahub, Dennis Russell Xiong, Yi Wei, Dong-Qing State Key Laboratory of Microbial Metabolism Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances Joint International Research Laboratory of Metabolic & Developmental Sciences School of Life Sciences and Biotechnology Shanghai Jiao Tong University Shanghai200030 China Department of Chemistry CMS - Centre for Molecular Simulation IQST - Institute for Quantum Science and Technology University of Calgary 2500 University Drive NW CalgaryABT2N 1N4 Canada Department of Clinical Oncology The University of Hong Kong-Shenzhen Hospital Shenzhen China School of Electrical Engineering and Computer Science University of Ottawa 75 Laurier Ave. OttawaONK1N 6N5 Canada The Ministry of Education Key Laboratory of System control and information processing Department of Automation School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200030 China Integrative Biotechnology & Translational Medicine Yonsei University Incheon21983 Korea Republic of Peng Cheng Laboratory Vanke Cloud City Phase I Building 8 Xili Street Nanshan District Guangdong Shenzhen518055 China

Computational prediction of the interaction between human leukocyte antigen (HLA) and peptide (pHLA) can speed up epitope screening and vaccine design. Here, we develop the TransMut framework composed of TransPHLA for pHLA binding prediction and AOMP for mutated peptide optimization, which can be generalized to any binding and mutation task of biomolecules. Firstly, TransPHLA is developed by using a Transformer-derived self-attention model to predict pHLA binding, which is significantly superior to 11 previous methods on pHLA binding prediction, neoantigen and human papilloma virus vaccine identification. For vaccine design, the AOMP program is then developed to automatically optimize mutated peptides to search for mutant peptides with higher affinity to the target HLA and with high homology to the source peptide. Among 3660 non-binding pHLAs, 3630 were successfully mutated. Of these, 94% were verified by the IEDB recommended method, and 88% have homology higher than 80% to the source peptide. © 2021, CC BY.

关键词： Peptides

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Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic (vol 11, 5172, 2020)

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NATURE COMMUNICATIONS 2020年第1期11卷 5172页

作者： Liu, Zhu Ciais, Philippe Deng, Zhu Lei, Ruixue Davis, Steven J. Feng, Sha Zheng, Bo Cui, Duo Dou, Xinyu Zhu, Biqing Guo, Rui Ke, Piyu Sun, Taochun Lu, Chenxi He, Pan Wang, Yuan Yue, Xu Wang, Yilong Lei, Yadong Zhou, Hao Cai, Zhaonan Wu, Yuhui Guo, Runtao Han, Tingxuan Xue, Jinjun Boucher, Olivier Boucher, Eulalie Chevallier, Frederic Tanaka, Katsumasa Wei, Yiming Zhong, Haiwang Kang, Chongqing Zhang, Ning Chen, Bin Xi, Fengming Liu, Miaomiao Breon, Francois-Marie Lu, Yonglong Zhang, Qiang Guan, Dabo Gong, Peng Kammen, Daniel M. He, Kebin Schellnhuber, Hans Joachim Department of Earth System Science Tsinghua University Beijing China. zhuliu@***. Laboratoire des Sciences du Climat et de l'Environnement LSCE CEA CNRS UVSQ Centre d'Etudes Orme de Merisiers Gif-sur-Yvette France. Department of Earth System Science Tsinghua University Beijing China. Department of Meteorology and Atmospheric Science The Pennsylvania State University University Park PA USA. Department of Earth System Science University of California Irvine 3232 Croul Hall Irvine CA USA. Division of Geological and Planetary Sciences California Institute of Technology Pasadena CA USA. Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment Technology School of Environmental Science and Engineering Nanjing University of Information Science & Technology Nanjing China. Key Laboratory of Land Surface Pattern and Simulation Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China. Climate Change Research Center Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China. Key Laboratory of Middle Atmosphere and Global Environment Observation Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China. School of Environment Tsinghua University Beijing China. School of Mathematical School Tsinghua University Beijing China. Department of Mathematical Sciences Tsinghua University Beijing China. Center of Hubei Cooperative Innovation for Emissions Trading System Wuhan China. Institut Pierre-Simon Laplace Sorbonne Université / CNRS Paris France. Université Paris Dauphine Place du Maréchal de Lattre de Tassigny 75016 Paris France. Center for Energy and Environmental Policy Research Beijing Institute of Technology Beijing China. Department of Electrical Engineering the State Key Lab of Control and Simulation of Power Systems and Generation Equipment Institute for National Governance and G

A Correction to this paper has been published: https://***/10.1038/s41467-020-20254-5

关键词： Climate sciences Atmospheric science Environmental sciences Environmental social sciences

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Photo-Based Monitoring of Particulate Matter in the Campus: A New Strategy for Student Health

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IOP Conference Series: Earth and Environmental Science 2020年第1期555卷

作者： Yonghui Zhang Ke Gu Zhifang Xia Junfei Qiao Faculty of Information Technology Beijing University of Technology 100124 Beijing China Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education 100124 Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System 100124 Beijing China Beijing Artificial Intelligence Institute 100124 Beijing China State Information Center 100045 Beijing China

It is imperative for the students' future health to ensure the students in good physical levels. Recent years have witnessed the increasingly serious harm to student health caused by the continually growing concentration of Particulate Matters (PMs). Consequently, the task of preventing and controlling PM concentrations in the campus is eagerly required. A well-designed model for the monitoring of PM (as the basis for PM prevention and control) has posed a big challenge. Prior works have revealed that photo-based methods are available for the monitoring of PM. Towards validating the effectiveness of existing methods for PM monitoring in the campus, we construct a novel dataset that involves 1,500 photos collected in the Beijing University of Technology. Results confirm that stated-of-the-art methods are far from ideal for the monitoring of PM in the campus. To solve the aforesaid issue, this paper further proposes a novel photo-based PM monitoring model by using the weighted average method solved by LASSO regression to fuse the above methods' outputs tested to infer the PM values. Results demonstrate the superiority of our proposed model as compared to state-of-the-art methods on the large-scale AQPDBJUT dataset.

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