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arXiv 2021年

作者： Wang, Wei Wu, Lijun Li, Junjie Aryal, Niraj Jin, Xilian Liu, Yu Fedurin, Mikhail Babzien, Marcus Kupfer, Rotem Palmer, Mark Petrovic, Cedomir Yin, Weiguo Dean, Mark P.M. Robinson, Ian Tao, Jing Zhu, Yimei Condensed Matter Physics and Materials Science Division Brookhaven National Laboratory UptonNY11973 United States State Key Laboratory of Superhard Materials College of Physics Jilin University Changchun130012 China Accelerator Science & Technology Initiative Accelerator Test Facility Brookhaven National Laboratory UptonNY11973 United States London Centre for Nanotechnology University College LondonWC1E 6BT United Kingdom

Identifying and understanding the mechanisms behind strong phonon-phonon scattering in condensed matter systems is critical to maximizing the efficiency of thermoelectric devices. To date, the leading method to address this has been to meticulously survey the full phonon dispersion of the material in order to isolate modes with anomalously large linewidth and temperature-dependence. Here we combine quantitative MeV ultrafast electron diffraction (UED) analysis with Monte Carlo based dynamic diffraction simulation and first-principles calculations to directly unveil the soft, anharmonic lattice distortions of model thermoelectric material SnSe. A small single-crystal sample is photoexcited with ultrafast optical pulses and the soft, anharmonic lattice distortions are isolated using MeV-UED as those associated with long relaxation time and large displacements. We reveal that these modes have interlayer shear strain character, induced mainly by c-axis atomic displacements, resulting in domain formation in the transient state. These findings provide an innovative approach to identify mechanisms for ultralow and anisotropic thermal conductivity and a promising route to optimizing thermoelectric devices. © 2021, CC BY.

关键词： Monte Carlo methods

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Learning to Infer Weather States Using Partial Observations

Journal of Geophysical Research: Machine Learning and Comput...

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Journal of Geophysical Research: Machine Learning and Computation 2025年第1期2卷

作者： Jie Chao Baoxiang Pan Quanliang Chen Shangshang Yang Jingnan Wang Congyi Nai Yue Zheng Xichen Li Huiling Yuan Xi Chen Bo Lu Ziniu Xiao National Key Laboratory of Earth System Numerical Modeling and Application Institute of Atmospheric Physics Chinese Academy of Science Beijing China School of Atmospheric Sciences Chengdu University of Information Technology Chengdu China Key Laboratory of Mesoscale Severe Weather Ministry of Education and School of Atmospheric Sciences Nanjing University Nanjing China College of Computer National University of Defense Technology Hunan China Clustertech LTD Hong Kong China National Climate Center China Meteorological Administration Beijing China

Accurate state estimation of the high-dimensional, chaotic Earth's atmosphere marks a Sisyphean task, yet is indispensable for initiating weather forecasts and gauging climate variability. While much effort is devoted to assimilating observations and forecasts to infer weather states, the inherent low-dimensional statistical structure in atmospheric circulation, shaped by geophysical laws and geographic boundaries, is underutilized as an informative prior for state inference, or as reference for assessing representative of existing observations and planning new ones. We realize these potential by learning climatological distribution from climate reanalysis/simulation, using a deep generative model. For a case study of estimating 2 m temperature spatial patterns, the learned distribution faithfully reproduces climatology statistics. A combination of the learned climatological prior with few station observations yields strong posterior of spatial pattern estimates, which are spatially coherent, faithful and adaptive to observational constraints, and uncertainty-aware. This allows us to evaluate each observation's value in reducing pattern estimation uncertainty, and guide optimal observation network design by pinpointing the most informative sites. Our study showcases how generative models can extract and utilize information produced in the chaotic evolution of climate system. Deep generative model enables accurate spatial interpolation of weather variables from sparse observations The generative model produces spatially coherent and uncertainty-aware estimates, effectively constrained by observational data The approach provides a framework to quantify observation impact on uncertainty reduction, enabling optimization of observation networks Accurate estimation of weather conditions across a large area is crucial but challenging due to the complex and chaotic nature of the atmosphere. Traditional methods rely on combining observations with forecasts, which can be comp

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Influences of the NAO on the North Atlantic CO2 Fluxes in Winter and Summer on the Interannual Scale

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Advances in Atmospheric sciences 2019年第11期36卷 1288-1298页

作者： Yujie JING Yangchun LI Yongfu XU Guangzhou FAN State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 China School of Atmospheric Sciences Chengdu University of Information Technology Chengdu 610225 China Laboratory for Regional Oceanography and Numerical Modeling Qingdao National Laboratory for Marine Science and Technology Qingdao 266237 China Department of Atmospheric Chemistry and Environmental Sciences College of Earth Science University of Chinese Academy of Sciences Beijing 100049 China

The differences in the influences of the North Atlantic Oscillation (NAO) on the air–sea CO2 fluxes (fCO2) in the North Atlantic (NA) between different seasons and between different regions are rarely fully investigated. We used observation-based data of fCO2, surface-ocean CO2 partial pressure (pCO2sea), wind speed and sea surface temperature (SST) to analyze the relationship between the NAO and fCO2 of the subtropical and subpolar NA in winter and summer on the interannual time scale. Based on power spectrum estimation, there are significant interannual signs with a 2–6 year cycle in the NAO indexes and area-averaged fCO2 anomalies in winter and summer from 1980 to 2015. Regression analysis with the 2–6 year filtered data shows that on the interannual scale the response of the fCO2 anomalies to the NAO has an obvious meridional wave-train-like pattern in winter, but a zonal distribution in summer. This seasonal difference is because in winter the fCO2 anomalies are mainly controlled by the NAO-driven wind speed anomalies, which have a meridional distribution pattern, while in summer they are dominated by the NAO-driven SST anomalies, which show distinct zonal difference in the subtropical NA. In addition, in the same season, there are different factors controlling the variation of pCO2sea in different regions. In summer, SST is important to the interannual variation of pCO2sea in the subtropical NA, while some biogeochemical variables probably control the pCO2sea variation in the subpolar NA.

关键词： air-sea CO2 flux North Atlantic Oscillation interannual time scale wind speed surface-ocean CO2 partial pressure

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Stability analysis of discrete Boltzmann simulation for supersonic flows: Influencing factors, coupling mechanisms and optimization strategies

arXiv

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arXiv 2025年

作者： Wu, Yanhong Gan, Yanbiao Xu, Aiguo Yang, Bin Hebei Key Laboratory of Trans-Media Aerial Underwater Vehicle North China Institute of Aerospace Engineering Langfang065000 China National Key Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics P. O. Box 8009-26 Beijing100088 China National Key Laboratory of Shock Wave and Detonation Physics Mianyang621999 China HEDPS Center for Applied Physics and Technology College of Engineering Peking University Beijing100871 China State Key Laboratory of Explosion Science and Safety Protection Beijing Institute of Technology Beijing100081 China School of Energy and Safety Engineering Tianjin Chengjian University Tianjin300384 China

Supersonic flow simulations encounter challenges in threefold: trans-scale modeling, numerical stability and complex field analysis, due to their inherent nonlinear, nonequilibrium and multiscale characteristics. The discrete Boltzmann method (DBM) provides a multiscale kinetic modeling framework and a set of analysis tools to capture complex discrete/nonequilibrium states and effects. While the stable numerical scheme plays a fundamental role in DBM simulations, a comprehensive and systematic stability analysis remains lacking. Similar to the lattice Boltzmann method, the complexity lies mainly in the intrinsic coupling between velocity and spatiotemporal discretizations, compared with the traditional computational fluid dynamics. Based on the von Neumann stability analysis, we investigate influences of the following aspects: (i) approaches for determining equilibrium distribution functions and designing discrete velocities, (ii) thermodynamic nonequilibrium (TNE) levels, (iii) spatiotemporal discretization schemes, (iv) initial conditions, and (v) model parameters, on the stability of DBM simulation. key findings include: (i) Among the equilibrium distribution discretization methods considered, the moment-matching approach outperforms expansion- and weighting-coefficient-based methods in the test simulations. (ii) As TNE intensity/Knudsen number increases, the nonlinear behavior of the system is enhanced. Accordingly, the intrinsic nonlinearity embedded in the matching model equation increases, regardless of whether the model is kinetic or macroscopic. In numerical simulations, instabilities induced by fast-changing behaviors, such as shock waves, are often amplified by nonlinear terms in the model equation. Therefore, the higher the nonlinear order of the model, the weaker its capability to handle such rapidly varying modes, and the more demanding the requirements on the numerical scheme. This reflects a common phenomenon. (iii) Although additional viscous dissip

关键词： Supersonic flow

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A Novel Deceptive Jamming Method Via Frequency Diverse Array

A Novel Deceptive Jamming Method Via Frequency Diverse Array

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Wei Mao Hui Wang Shunsheng Zhang Xiangrong Liu National Key Laboratory of Science and Technology Test Physics and Numerical Mathematics Beijing China Research Institute of Electronic Science and Technology University of Electronic Science and Technology of China Chengdu China

Different from traditional single-element and phased-array antennas, frequency diverse array (FDA) uses a slight frequency offset across the elements to produce angle-, range- and even time-dependent transmit beampattern, which provides promising potentials to develop new jamming techniques on synthetic aperture radar (SAR) imaging. In this paper, we propose a novel deception jamming method against SAR imaging, which uses FDA to quickly generate false targets. Moreover, the position of the false target is controlled by the jammer, and the number of false targets is determined by the number of FDA elements. The proposed methods are validated by extensive simulation results with range-Doppler imaging algorithm.

关键词： Jamming Synthetic aperture radar Imaging Azimuth Interference Radar imaging

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science and Prediction of Heavy Rainfall over China:Research Progress since the Reform and Opening-Up of New China

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Journal of Meteorological Research 2020年第3期34卷 427-459页

作者： Yali LUO Jisong SUN Ying LI Rudi XIA Yu DU Shuai YANG Yuanchun ZHANG Jing CHEN Kan DAI Xueshun SHEN Haoming CHEN Feifan ZHOU Yimin LIU Shenming FU Mengwen WU Tiangui XIAO Yangruixue CHEN Huiqi LI Mingxin LI State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesChina Meteorological AdministrationBeijing 100081 Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science&TechnologyNanjing 210044 School of Atmospheric Sciences and Guangdong Province Key Laboratory for Climate Change and Natural Disaster StudiesSun Yat-sen UniversityGuangzhou 519082 Key Laboratory of Cloud–Precipitation Physics and Severe Storms Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029 National Meteorological Center China Meteorological AdministrationBeijing 100081 State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029 Zhejiang Institute of Meteorological Sciences Zhejiang Meteorological BureauHangzhou 310008 School of Atmospheric Sciences Chengdu University of Information TechnologyChengdu 610225 Institute of Heavy Rain China Meteorological AdministrationWuhan 43020510 Institute of Tropical and Marine MeteorologyChina Meteorological Administration Guangzhou 510640 Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Zhuhai 519082 University of Chinese Academy of Sciences Beijing 100049 CAS Center for Excellence in Tibetan Plateau Earth Sciences Chinese Academy of Sciences(CAS)Beijing 100101

This paper reviews the major progress on development of the science and prediction of heavy rainfall over China since the beginning of the reform and opening-up of new China(roughly between 1980 and 2019).The progress of research on the physical mechanisms of heavy rainfall over China is summarized from three perspectives:1)the relevant synoptic weather systems,2)heavy rainfall in major sub-regions of China,and 3)heavy rainfall induced by *** development and application of forecasting techniques for heavy rainfall are summarized in terms of numerical weather prediction techniques and objective forecasting *** aided by the rapid progress in meteorological observing technology and substantial improvement in electronic computing,studies of heavy rainfall in China have advanced to investigating the evolution of heavy-rain-producing storms and observational analysis of the cloud microphysical features.A deeper and more systematic understanding of the synoptic systems of importance to the production of heavy rainfall has also been *** forecast of heavy rainfall in China has changed from subjective weather event forecasts to a combination of both subjective and objective quantitative precipitation forecasts,and is now advancing toward probabilistic quantitative precipitation forecasts with the provision of forecast uncertainty information.

关键词： heavy rainfall reform and opening-up of new China physical mechanisms forecasting techniques

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A Physical Layer key Generation method with Reliable Negotiation

A Physical Layer Key Generation method with Reliable Negotia...

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Signal, Information and Data Processing (ICSIDP), IEEE International Conference on

作者： Yuchen Wang Xuanli Wu Zhicong Xu Wei Wu Hu Li Ran Zhang School of Electronics and Information Engineering Harbin Institude of Technology Harbin China National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing China

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

There is a risk of information leakage in the process of wireless communication. The introduction of key generation in the physical layer can effectively improve the security of wireless communication. This paper proposes a new physical layer key generation method in the TDD (time division duplex) communication system. Assume that the uplink and downlink channels are reciprocal. Through LDPC (Low Density Parity Check)channel coding and negotiation algorithm, the inconsistency rate of key generation between Alice and Bob is reduced. Simulation and analysis results show that the method improves the key generation rate and reduces the key inconsistency rate.

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Direct vegetation response to CO 2 rise is critical in projecting seasonal soil moisture droughts in mainland China

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Journal of Hydrology 2025年 661卷

作者： Sisi Chen Xing Yuan Peng Ji Shanshui Yuan Chunhui Lu The National Key Laboratory of Water Disaster Prevention Hohai University Nanjing China Key Laboratory of Hydrometeorological Disaster Mechanism and Warning of Ministry of Water Resources Nanjing University of Information Science and Technology Nanjing China College of Hydrology and Water Resources Hohai University Nanjing China State Key Laboratory of Earth System Numerical Modeling and Application Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China Yangtze Institute for Conservation and Development Hohai University Nanjing China

China is a hotspot of vegetation change, accounting for one fourth of the global total vegetation growth. Yet the influence of vegetation change on the future changes of soil moisture drought is two-fold as the response of vegetation physiology (e.g., physiological effects of CO 2 ) and structure (e.g., leaf area index (LAI)) to CO 2 rise can either mitigate or exacerbate soil moisture droughts. Here we investigate the net impact of these two factors and their relative importance against the climate change, based on a series of high-resolution land surface simulations. It is found that the direct vegetation response to CO 2 rise—encompassing both physiological effects and changes in LAI—will reduce the drought frequency by 15 % in South China but exacerbate the drought severity by 47 % in North China at the 3.0 °C warming level, compared to the reference period (1971–2000). Such an inverse north–south spatial pattern is closely related to the spatial varying impact of vegetation greening, which enhances evapotranspiration and intensifies drought in the water-limited regions (e.g., North China) but has limited effect on evapotranspiration in the energy-limited regions (e.g., South China). Meanwhile, the physiological effects of CO 2 mainly mitigate the drought and show small spatial variations. The national mean contribution of climate change, LAI change and CO 2 physiological effects to future drought changes are 49 ∼ 54 %, 19 ∼ 27 % and 22 ∼ 28 %, respectively. And the relative importance of ecological factors would increase to >50 % when focusing on the difference among different warming levels. This study highlights the importance of direct vegetation response to CO 2 rise in drought projections.

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Development of Climate and Earth System Models in China: Past Achievements and New CMIP6 Results

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Journal of Meteorological Research 2020年第1期34卷 1-19页

作者： Tianjun ZHOU Ziming CHEN Liwei ZOU Xiaolong CHEN Yongqiang YU Bin WANG Qing BAO Ying BAO Jian CAO Bian HE Shuai HU Lijuan LI Jian LI Yanluan LIN Libin MA Fangli QIAO Xinyao RONG Zhenya SONG Yanli TANG Bo WU Tongwen WU Xiaoge XIN He ZHANG Minghua ZHANG State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics(LASG) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029 College of Earth and Planetary Sciences University of Chinese Academy of SciencesBeijing 100049 First Institute of Oceanography Ministry of Natural ResourcesQingdao 266061 School of Atmospheric Science Nanjing University of Information Science&TechnologyNanjing 210044 Chinese Academy of Meteorological Sciences China Meteorological AdministrationBeijing 100081 Tsinghua University Beijing 100084 National Climate Center China Meteorological AdministrationBeijing 100081 International Center for Climate and Environment Sciences Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029

The Earth–Climate System Model(ECSM)is an important platform for multi-disciplinary and multi-sphere integration research,and its development is at the frontier of international geosciences,especially in the field of global *** research and development(R&D)of ECSM in China began in the 1980 s and have achieved great *** China,ECSMs are now mainly developed at the Chinese Academy of sciences,ministries,and *** a brief review of the development history of Chinese ECSMs,this paper summarized the technical characteristics of nine Chinese ECSMs participating in the Coupled Model Intercomparison Project Phase 6 and preliminarily assessed the basic performances of four Chinese models in simulating the global climate and the climate in East *** projected changes of global precipitation and surface air temperature and the associated relationship with the equilibrium climate sensitivity under four shared socioeconomic path scenarios were also ***,combined with the international situation,from the perspective of further improvement,eight directions were proposed for the future development of Chinese ECSMs.

关键词： Earth–Climate System Model(ECSM) Chinese models Coupled Model Intercomparison Project Phase 6(CMIP6) model performance climate prediction and projection outlook

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numerical investigation of Richtmyer–Meshkov instability in shock-driven light square bubble via magnetohydrodynamics

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Computers & Fluids 2025年 299卷

作者： Sheng-Bo Zhang Satyvir Singh Manuel Torrilhon Huan-Hao Zhang Zhi-Hua Chen Chun Zheng National Key Laboratory of Transient Physics Nanjing University of Science and Technology Xiaolingwei 200 210094 Nanjing China Applied and Computational Mathematics RWTH Aachen University Schinkelstrasse 2 52062 Aachen Germany Department of Mathematics Graphic Era Deemed to be University Dehradun Uttarakhand India National Graduate College for Engineers Southern University of Science and Technology Xueyuan Avenue 1008 518055 Shenzhen China School of Energy and Power Engineering Nanjing University of Science and Technology Xiaolingwei 200 210094 Nanjing China

This study presents a numerical investigation of magnetohydrodynamics (MHD) instability in a shock-driven light square bubble, examining the complex interactions at the interface between shocked fluids in the presence of a magnetic field. By incorporating magnetic fields, the dynamics of such instabilities become even more complex, leading to novel behavior in terms of vorticity deposition, mixing, and interface morphology. For numerical simulation, an unsteady compressible ideal magnetohydrodynamics equations in two-dimensional space is solved with the corner transport upwind ＋ constrained transport schemes while preserving the magnetic field’s divergence-free condition. The numerical results show good agreement with the available hydrodynamics experimental data and magnetohydrodynamics calculations. The research results demonstrate that the transverse magnetic field plays a crucial role in the development of MHD-RMI in a light square bubble driven by a planar shock wave. It significantly affects the flow field structure, leading to changes in interface morphology, shock wave structure, vortices and enstrophy. The baroclinic torque induced by magnetic tension at the interface counteracts the torque from velocity shear, thereby inhibiting the roll of Kelvin–Helmholtz vortex. A comprehensive analysis of some physical quantities, including magnetic energy, magnetic strength, and magnetic tension on the square bubble, is presented. MHD-RMI has been found to be a highly effective mechanism for enhancing the magnetic field, thereby improving the suppression of flow instability. Finally, a detailed analysis of the impact of the magnetic field on the time evolution of the interface features is conducted.

关键词： Richtmyer–Meshkov instability MHD Shock wave Light gas interface

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