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Understanding the Low Predictability of the 2015/16 El Niño Event Based on a Deep Learning Model

Advances in Atmospheric Sciences 2024年第7期41卷 1313-1325页

作者： Tingyu WANG Ping HUANG Xianke YANG Center for Monsoon System Research Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China National space Science Center Chinese Academy of SciencesBeijing 100190China State Key laboratory of space Weather National Space Science CenterChinese Academy of SciencesBeijing 100190China College of Plant Science and Technology Huazhong Agricultural UniversityWuhan 430070China

The 2015/16 El Niño event ranks among the top three of the last 100 years in terms of intensity,but most dynamical models had a relatively low prediction skill for this event before the summer ***,the attribution of this particular event can help us to understand the cause of super El Niño–Southern Oscillation events and how to forecast them *** present study applies attribute methods based on a deep learning model to study the key factors related to the formation of this event.A deep learning model is trained using historical simulations from 21 CMIP6 models to predict the Niño-3.4 *** integrated gradient method is then used to identify the key signals in the North Pacific that determine the evolution of the Niño-3.4 *** crucial signals are then masked in the initial conditions to verify their roles in the *** addition to confirming the key signals inducing the super El Niño event revealed in previous attribution studies,we identify the combined contribution of the tropical North Atlantic and the South Pacific oceans to the evolution and intensity of this event,emphasizing the crucial role of the interactions among them and the North *** approach is also applied to other El Niño events,revealing several new precursor *** study suggests that the deep learning method is useful in attributing the key factors inducing extreme tropical climate events.

关键词： ENSO attribution deep learning ENSO prediction extreme El Niño

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Predicting PM_(2.5) Concentration in the Yangtze River Delta Region Using Climate System Monitoring Indices and Machine Learning

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Journal of Meteorological Research 2024年第2期38卷 249-261页

作者： Jinghui MA Shiquan WAN Shasha XU Chanjuan WANG Danni QIU Shanghai Typhoon Institute Shanghai Meteorological ServiceShanghai 200030 Key laboratory of Polar atmosphere-Ocean-Iice System for Weather and Climate Ministry of EducationDepartment of Atmospheric and Oceanic SciencesFudan UniversityShanghai 200438 Shanghai Key laboratory of Meteorology and Health Shanghai Meteorological ServiceShanghai 200030 Yangzhou Meteorological Office Yangzhou 225001 Department of physics Yangzhou UniversityYangzhou 225003

Changing meteorological conditions during autumn and winter have considerable impact on air quality in the Yangtze River Delta(YRD)*** climatic factors,such as sea surface temperature and sea ice,together with the atmospheric circulation,directly affect meteorological conditions in the YRD region,thereby modulating the variation in atmospheric PM_(2.5) *** study used the evolutionary modeling machine learning technique to investigate the lag relationship between 144 climate system monitoring indices and autumn/winter PM_(2.5) concentration over 0-12 months in the YRD *** calculating the contribution ratios and lagged correlation coefficients of all indices over the previous 12 months,the top 36 indices were selected for model ***,the nine indices that contributed most to the PM_(2.5) concentration in the YRD region,including the decadal oscillation index of the Atlantic Ocean and the consistent warm ocean temperature index of the entire tropical Indian Ocean,were selected for physical mechanism *** evolutionary model was developed to forecast the average PM_(2.5) concentration in major cities of the YRD in autumn and winter,with a correlation coefficient of *** model testing,the correlation coefficient between the predicted and observed PM_(2.5) concentrations was in the range of 0.73-0.83 and the root-mean-square error was in the range of 9.5-11.6μg m-3,indicating high predictive *** model performed exceptionally well in capturing abnormal changes in PM_(2.5) concentration in the YRD region up to 50 days in advance.

关键词： PM_(2.5)concentration machine learning evolutionary modeling seasonal prediction

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Study on the Performance of the GRANDProto300 Particle Detector Array by Simulation

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Research in Astronomy and Astrophysics 2024年第1期24卷 173-177页

作者： Fu-Lin Dai Quan-Bu Gou Xiaoyuan Huang Yi-Qing Guo Key laboratory of Dark Matter and space Astronomy Purple Mountain ObservatoryChinese Academy of SciencesNanjing 210023China School of Astronomy and space Science University of Science and Technology of ChinaHefei 230026China Key laboratory of Particle Astrophysics Institute of High Energy PhysicsChinese Academy of SciencesBeijing 100049China University of Chinese Academy of Sciences Beijing 100049China

The Giant Radio Array for Neutrino Detection(GRAND)is a proposed large-scale observatory designed to detect cosmic rays,gamma-rays,and neutrinos with energies exceeding 100 Pe *** GRANDProto300 experiment is proposed as the early stage of the GRAND project,consisting of a hybrid array of radio antennas and scintillator *** latter,as a mature and traditional detector,is used to cross-check the nature of the candidate events selected from radio *** this study,we developed a simulation software called G4GRANDProto300,based on the Geant4 software package,to optimize the spacing of the scintillator detector array and to investigate its effective *** analysis was conducted at various zenith angles under different detector spacings,including 300,500,600,700,and 900 *** results indicate that,for large zenith angles used to search for cosmic-ray in the GRAND project,the optimized effective area is with a detector spacing of 500 *** G4GRANDProto300 software that we developed could be used to further optimize the layout of the particle detector array in future work.

关键词： astroparticle physics instrumentation:detectors (ISM:)cosmic rays

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Transverse momentum balance of dijets in Xe+Xe collisions at the LHC

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Nuclear Science and Techniques 2024年第7期35卷 137-146页

作者： Yao Li Shu-Wan Shen Sa Wang Ben-Wei Zhang Key laboratory of Quark&Lepton physics(MOE)and Institute of Particle physics Central China Normal UniversityWuhan430079China College of Science China Three Gorges UniversityYichang443002China Center for Astronomy and space Sciences and Institute of Modern physics China Three Gorges UniversityYichang443002China Guangdong-Hong Kong Joint laboratory of Quantum Matter Guangdong Provincial Key Laboratory of Nuclear ScienceSouthern Nuclear Science Computing CenterSouth China Normal UniversityGuangzhou510006China

We present a theoretical study of the medium modifications of the p_(T)balance (x_(J)) of dijets in Xe+Xe collisions at■.The initial production of dijets was carried out using the POWHEG+PYTHIA8 prescription,which matches the next-toleading-order (NLO) QCD matrix elements with the parton shower (PS) *** SHELL model described the in-medium evolution of nucleus–nucleus collisions using a transport *** theoretical results of the dijet xJin the Xe+Xe collisions exhibit more imbalanced distributions than those in the p+p collisions,consistent with recently reported ATLAS *** utilizing the Interleaved Flavor Neutralisation,an infrared-and-collinear-safe jet flavor algorithm,to identify the flavor of the reconstructed jets,we classify dijets processes into three categories:gluon–gluon (gg),quark–gluon (qg),and quark–quark (qq),and investigated the respective medium modification patterns and fraction changes of the gg,qg,and qq components of the dijet sample in Xe+Xe *** is shown that the increased fraction of qg component at a small x_(J)contributes to the imbalance of the dijet;in particular,the q_(1)g_(2)(quark-jet-leading) dijets experience more significant asymmetric energy loss than the g_(1)q_(2)(gluon-jet-leading) dijets traversing the *** comparing the■of inclusive,■ dijets in Xe+Xe collisions,we observe■.Moreover,ρ_(Xe),P_(b),the ratios of the nuclear modification factors of dijets in Xe+Xe to those in Pb+Pb,were calculated,which indicates that the yield suppression of dijets in Pb+Pb is more pronounced than that in Xe+Xe owing to the larger radius of the lead nucleus.

关键词： Heavy-ion collisions Quark-gluon plasma Jet quenching Transverse momentum balance

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Resolution Enhancement of SOHO/MDI Magnetograms

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Research in Astronomy and Astrophysics 2024年第6期24卷 358-367页

作者： Ying Qin Kai-Fan Ji Hui Liu Xiao-Guang Yu Yunnan Observatories Chinese Academy of SciencesKunming 650011China University of Chinese Academy of Sciences Beijing 100049China Yunnan Key laboratory of Solar physics and space Science Kunming 650216China Key laboratory for the Structure and Evolution of Celestial Objects Chinese Academy of SciencesKunming 650216China

Research on the solar magnetic field and its effects on solar dynamo mechanisms and space weather events has benefited from the continual improvements in instrument resolution and measurement *** augmentation and assimilation of historical observational data timelines also play a significant role in understanding the patterns of solar magnetic field *** the realm of astronomical data processing,super-resolution(SR)reconstruction refers to the process of using a substantial corpus of training data to learn the nonlinear mapping between low-resolution(LR)and high-resolution(HR)images,thereby achieving higherresolution astronomical *** paper is an application study in high-dimensional nonlinear *** learning models were employed to perform SR modeling on SOHO/MDI magnetograms and SDO/HMI magnetograms,thus reliably achieving resolution enhancement of full-disk SOHO/MDI magnetograms and enhancing the image resolution to obtain more detailed *** this study,a data set comprising 9717pairs of data from 2010 April to 2011 February was used as the training set,1332 pairs from 2011 March were used as the validation set and 1034 pairs from 2011 April were used as the test *** data preprocessing,we randomly cropped 128×128 sub-images as the LR cases from the full-disk MDI magnetograms,and the corresponding 512×512 sub-images as HR ones from the HMI full-disk magnetograms for model *** tests conducted have shown that the study successfully produced reliable 4×SR reconstruction of full-disk MDI *** MESR model's results(0.911)were highly correlated with the target HMI magnetographs as indicated by the correlation coefficient ***,the method achieved the best PSNR,SSIM,MAE and RMSE values,indicating that the MESR model can effectively reconstruct magnetograms.

关键词： magnetic fields techniques:image processing virtual observatory tools Sun:magnetic fields

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Distribution and Formation Causes of PM_(2.5) and O_(3) Double High Pollution Events in China during 2013–20

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Advances in Atmospheric Sciences 2024年第6期41卷 1235-1250,I0004-I0021页

作者： Zhixuan TONG Yingying YAN Shaofei KONG Jintai LIN Nan CHEN Bo ZHU Jing MA Tianliang ZHAO Shihua QI Department of Atmospheric Science School of Environmental SciencesChina University of GeosciencesWuhan 430074China State Key laboratory of Atmospheric Boundary Layer physics and Atmospheric Chemistry Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Research Centre for Complex Air Pollution of Hubei Province Wuhan 430074China laboratory for Climate and Ocean–atmosphere Studies Department of Atmospheric and Oceanic SciencesSchool of PhysicsPeking UniversityBeijing 100871China Eco-Environmental Monitoring Centre of Hubei Province Wuhan 430074China Key laboratory of Atmospheric Chemistry China Meteorological AdministrationBeijing 100081China School of Atmospheric physics Nanjing University of Information Science and TechnologyNanjing 210044China State Key laboratory of Biogeology and Environmental Geology China University of GeosciencesWuhan 430074China

Fine particulate matter(PM_(2.5))and ozone(O_(3))double high pollution(DHP)events have occurred frequently over China in recent years,but their causes are not completely *** this study,the spatiotemporal distribution of DHP events in China during 2013–20 is *** synoptic types affecting DHP events are identified with the Lamb–Jenkinson circulation classification *** meteorological and chemical causes of DHP events controlled by the main synoptic types are further *** show that DHP events(1655 in total for China during 2013–20)mainly occur over the North China Plain,Yangtze River Delta,Pearl River Delta,Sichuan Basin,and Central *** occurrence frequency increases by 5.1%during 2013–15,and then decreases by 56.1%during 2015–*** main circulation types of DHP events are“cyclone”and“anticyclone”,accounting for over 40%of all DHP events over five main polluted regions in China,followed by southerly or easterly flat airflow types,like“southeast”,“southwest”,and“east”.Compared with non-DHP events,DHP events are characterized by static or weak wind,high temperature(20.9℃ versus 23.1℃)and low humidity(70.0%versus 64.9%).The diurnal cycles of meteorological conditions cause PM_(2.5)(0300–1200 LST,Local Standard Time=UTC+8 hours)and O_(3)(1500–2100 LST)to exceed the national standards at different periods of the DHP *** pollutant conversion indices further indicate the rapid secondary conversions during DHP events,and thus the concentrations of NO_(2),SO_(2) and volatile organic compounds decrease by 13.1%,4.7%and 4.4%,*** results of this study can be informative for future decisions on the management of DHP events.

关键词： double high pollution events PM_(2.5) ozone spatiotemporal distribution meteorological causes chemical composition characteristics

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Synthesis of covalent organic framework materials and their application in the field of sensing

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Nano Research 2024年第1期17卷 162-195页

作者： Weiyu Zhang Shiwei Liu Qihua Sun Ning Tian Zhaofeng Wu Xinjiang Key laboratory of Solid-State physics and Devices Urumqi 830046China School of physics Science and Technology Xinjiang UniversityUrumqi 830046China

Covalent organic frameworks(COFs)are an emerging type of porous crystalline polymers formed by combining strong covalent bonds with organic building *** to their large surface area,high intrinsic pore space,good crystallization properties,high stability,and designability of the resultant units,COFs are widely studied and used in the fields of gas adsorption,drug transport,energy storage,photoelectric catalysis,electrochemistry,and *** recent years,the rapid development of the Internet of Things and people’s yearning for a better life have put forward higher and more requirements for sensors,which are the core components of the Internet of ***,this paper reviews the recent progress of COFs in synthesis methods and sensing applications,especially in the last five *** paper first introduces structure,properties,and synthesis methods of COFs and discusses advantages and disadvantages of different synthesis ***,the research progress of COFs in different sensing fields,such as metal ion sensors,gas sensors,biomedical sensors,humidity sensors,and pH sensors,is introduced *** and prospects are also presented in order to provide a reference for researchers concerned with COFs and sensors.

关键词： covalent organic framework materials structural design and synthesis sensing application gas sensors

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Inversion of O_(2) 1.27 μm nightglow emissions: A climatological analysis using satellite Limb-Viewed spectra and Harmonic analysis method

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Earth and Planetary physics 2024年第4期8卷 632-640页

作者： YiYi Sui YaJun Zhu QiuYu Chen MaoSheng He JiYao Xu State Key laboratory of space Weather National Space Science CenterChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100190China Key laboratory of Solar Activity and space Weather National Space Science CenterChinese Academy of SciencesBeijing 100190China Hainan National Field Science Observation and Research Observatory for space Weather National Space Science CenterChinese Academy of SciencesBeijing 100190China

This study employs a linear inversion algorithm to retrieve volume emission rates(VERs)of molecular O_(2) nightglow at 1.27μm,utilizing Limb-Viewed spectra obtained from the SCanning Imaging Absorption spectroMeter for Atmospheric for CHartographY(SCIAMACHY)payload on board the Envisat *** retrieved results are compared with VERs data from the SABER payload on the Thermosphere Ionosphere Mesosphere Energetics and Dynamics(TIMED)satellite,exhibiting *** will help to facilitate accurate revelation of spatial distribution and periodic variation in O_(2) *** are extracted monthly within the altitude range of 75-110 km from 2002 to 2012,yielding a climatology of spatial and temporal *** meridional structure exhibits two maxima,at the equator and at 45°*** August and October,the VERs exhibit a meridional bimodal structure,with the weaker one above the equator and the stronger one above 45°*** April,the VERs reach their annual ***,harmonic analysis reveals significant temporal variations on different *** emission shows characteristics of annual and semi-annual variation,and a non-linear long-term trend associated with solar cycle activity.

关键词： VERs O_(2)1.27μm nightglow SCIAMACHY

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Recent Progress in space Science and Applications on Chinese space Station in 2022–2024

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空间科学学报 2024年第4期44卷 607-621页

作者： GU Yidong GAO Ming ZHAO Guangheng WANG Qiang LYU Congmin ZHONG Hongen LIU Guoning Key laboratory of space Utilization Technology and Engineering Center for Space UtilizationChinese Academy of SciencesBeijing 100094

Chinese space Station(CSS)has been fully deployed by the end of 2022,and the facility has entered into the application and development *** has conducted scientific research projects in various fields,such as space life science and biotechnology,space materials science,microgravity fundamental physics,fluid physics,combustion science,space new technologies,and *** this review,we introduce the progress of CSS development and provide an overview of the research conducted in Chinese space Station and the recent scientific findings in several typical research *** compelling findings mainly concern the rapid solidification of ultra-high temperature alloy melts,dynamics of fluid transport in space,gravity scaling law of boiling heat transfer,vibration fluidization phenomenon of particulate matter,cold atom interferometer technology under high microgravity and related equivalence principle testing,the full life cycle of rice under microgravity and so ***,the planned scientific research and corresponding prospects of Chinese space station in the next few years are presented.

关键词： Chinese space Station(CSS) space material science Micro-gravity fluid physics Fundamental physics space life sciences and biotechnology

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Advancements in machine learning for material design and process optimization in the field of additive manufacturing

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China Foundry 2024年第2期21卷 101-115页

作者： Hao-ran Zhou Hao Yang Huai-qian Li Ying-chun Ma Sen Yu Jian shi Jing-chang Cheng Peng Gao Bo Yu Zhi-quan Miao Yan-peng Wei National Key laboratory of Advanced Casting Technologies Shenyang Research Institute of Foundry Co.Ltd.CAMShenyang 110022China Department of Mechanical Engineering Tsinghua UniversityBeijing 100084China Key laboratory of space physics Beijing 100076China School of Materials Science and Engineering Nanyang Technological University639798Singapore

Additive manufacturing technology is highly regarded due to its advantages,such as high precision and the ability to address complex geometric ***,the development of additive manufacturing process is constrained by issues like unclear fundamental principles,complex experimental cycles,and high *** learning,as a novel artificial intelligence technology,has the potential to deeply engage in the development of additive manufacturing process,assisting engineers in learning and developing new *** paper provides a comprehensive overview of the research and applications of machine learning in the field of additive manufacturing,particularly in model design and process ***,it introduces the background and significance of machine learning-assisted design in additive manufacturing *** then further delves into the application of machine learning in additive manufacturing,focusing on model design and process ***,it concludes by summarizing and forecasting the development trends of machine learning technology in the field of additive manufacturing.

关键词： additive manufacturing machine learning material design process optimization intersection of disciplines embedded machine learning

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