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Correcting Climate Model Sea Surface Temperature Simulations with Generative Adversarial Networks:Climatology,Interannual Variability,and Extremes

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Advances in Atmospheric sciences 2024年第7期41卷 1299-1312页

作者： Ya WANG Gang HUANG Baoxiang PAN Pengfei LIN Niklas BOERS Weichen TAO Yutong CHEN BO LIU Haijie LI State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Laboratory for Regional Oceanography and Numerical Modeling Qingdao National Laboratory for Marine Science and TechnologyQingdao 266237China College of Earth and Planetary Sciences University of Chinese Academy of SciencesBeijing 100049China Earth System Modelling School of Engineering and DesignTechnical University of MunichOttobrunn 85521Germany Potsdam Institute for Climate Impact Research Potsdam 14412Germany Department of Mathematics and Global Systems Institute University of ExeterExeter EX44QEUK CMA Earth System Modeling and Prediction Centre(CEMC) Chinese Academy of Meteorological SciencesBeijing 100081China

Climate models are vital for understanding and projecting global climate change and its associated ***,these models suffer from biases that limit their accuracy in historical simulations and the trustworthiness of future *** these challenges requires addressing internal variability,hindering the direct alignment between model simulations and observations,and thwarting conventional supervised learning ***,we employ an unsupervised Cycle-consistent Generative Adversarial Network(CycleGAN),to correct daily Sea Surface Temperature(SST)simulations from the Community Earth System Model 2(CESM2).Our results reveal that the CycleGAN not only corrects climatological biases but also improves the simulation of major dynamic modes including the El Niño-Southern Oscillation(ENSO)and the Indian Ocean Dipole mode,as well as SST ***,it substantially corrects climatological SST biases,decreasing the globally averaged Root-Mean-Square Error(RMSE)by 58%.Intriguingly,the CycleGAN effectively addresses the well-known excessive westward bias in ENSO SST anomalies,a common issue in climate models that traditional methods,like quantile mapping,struggle to ***,it substantially improves the simulation of SST extremes,raising the pattern correlation coefficient(PCC)from 0.56 to 0.88 and lowering the RMSE from 0.5 to *** enhancement is attributed to better representations of interannual,intraseasonal,and synoptic scales *** study offers a novel approach to correct global SST simulations and underscores its effectiveness across different time scales and primary dynamical modes.

关键词： generative adversarial networks model bias deep learning El Niño-Southern Oscillation marine heatwaves

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Cooperative Jamming Resource Allocation Based on Artificial Bee Colony Multi-objective Decomposition

Cooperative Jamming Resource Allocation Based on Artificial ...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Gao Lu Qianqi Dai Jiechen Xia National Key Laboratory of Science and Technology on Test Physics and umerical Mathematics Beijing Institute of Space Long March Vehicle Beijing China Key Laboratory of Advanced Marine Communication and Information Technology Ministry of Industry and Information Technology Harbin Engineering University Harbin China

Electromagnetic countermeasure plays an important role in modern warfare. Cooperative jamming is one of the main means to counter radar network. In order to improve jamming efficiency, a jamming resource allocation algorithm based on artificial bee colony multi-target decomposition is proposed in this paper. The algorithm takes into account the interference effect and cost, and uses the decomposition mechanism to improve the search efficiency. The simulation results show that the allocation solution set obtained by this algorithm has good performance in diversity and spacing.

关键词： Costs Simulation Radar Interference Computational electromagnetics Artificial bee colony algorithm Radar countermeasures

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Intelligent Counter Guidance Regulated by Deep Reinforced Learning

Intelligent Counter Guidance Regulated by Deep Reinforced Le...

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IEEE Metrology for Aerospace

作者： Runle Du Jiaqi Liu Li Zhang Jianhua Li National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing China

ISBN: (数字)9781728166360

ISBN: (纸本)9781728166377

In the game of pursuit and evasion in outer space, it is of utmost importance for the evader to make appropriate maneuver to survive this challenge. In previous publications, the common approach of guidance behavior recognition and counteracting evasion approach is based on model matching or multi-model matching. In that genre, due to the limitation of approximation from model matching and imperfection of state information, it is very difficult for the evader to take optimal maneuver when the pursuer uses unknown tracking algorithms. To solve this problem, in this article, deep neural network and reinforced learning are applied in counteractive maneuver. In the proposed approach, two networks are applied. Guidance recognition network is a pre-trained deep network able to estimate guidance behavior of pursuer vehicle, and the maneuver control network is trained by deep reinforced learning to perform counteract evading maneuver control. Exploring the policy space with Monte Carlo method, the maneuver controller deep neural network evolved to make optimal control acceleration and succeed in the evasion. Digital simulations confirmed that in the game of pursuit and evasion, deep reinforced learning with Monte Carlo method has the ability to guide the evader during the interception with improved chance of survival.

关键词： Neural networks Training Acceleration Monte Carlo methods Kinematics Games Space exploration

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Modulation recognition of emitter signals based on SDAE-ODCNN 5

Modulation recognition of emitter signals based on SDAE-ODCN...

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IET International Radar Conference 2020, IET IRC 2020

作者： Wang, Xu Gao, Jingpeng Gao, Lu Wang, Fu College of Information and Communication Engineering Harbin Engineering University Harbin China National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing Institute of Space Long March Vehicle Beijing China

ISBN: (纸本)9781839535635

In order to improve the recognition rate of emitter signals modulation under low signal noise ratio (SNR), an end-to-end method based on the stacked denoising autoencoder (SDAE) - one dimensional convolutional neural network (ODCNN) is proposed in this paper. The SADE-ODCNN is designed in this method and trained through a two-step training. In the SDAE-ODCNN model, the encoder of the SDAE can extract the denoised and compressed features of the received emitter signals. Then the ODCNN can further extract features to realize the recognition. The simulation results show that the average recognition rate of the method can reach 0.94 under 0dB. Thus the proposed method has a good application in the field of emitter signals modulation recognition. © 2020 Institution of Engineering and technology. All rights reserved.

关键词： Modulation

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A unified back-projection correction algorithm for squint SAR based on SPECAN processing

A unified back-projection correction algorithm for squint SA...

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2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019

作者： Wang, Chao Sun, Heng Zhang, Xin-Yu Zhang, Ran National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing China

ISBN: (纸本)9781728123455

The missile-borne or airborne synthetic aperture radar (SAR) usually adopts the squint mode and subaperture to satisfy maneuvering and the real-time processing. A realtime imaging algorithm of squint SAR based on SPECAN processing is presented. It has high computational efficiency in low resolution. A unified back-projection algorithm is proposed to solve the problem of fan-shaped distortion and geometric distortion. Simulation results validate the effectiveness of the proposed method. © 2019 IEEE.

关键词： Computational efficiency

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Intelligent Assignment Strategy for Multi-Target Adversarial Interception

Intelligent Assignment Strategy for Multi-Target Adversarial...

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Chinese Automation Congress (CAC)

作者： Yang Yu Yizhong Fang Han Wu Tuo Han Qinglei Hu School of Automation Science and Electrical Engineering Beihang University Beijing China National Key Laboratory of Science and Technology on Test Physics & Numerical Mathematics Beijing Institute of Space Long March Vehicle Beijing China School of Aeronautic Science and Engineering Beihang University Beijing China Beihang Hangzhou Innovation Institute (Yuhang) Hangzhou China

The multi-missile confront multi-target is a classic target allocation issue in the combat scenario of multiple missiles intercepting multiple maneuvering targets. Traditional algorithms lack environmental assessment model, train quality, and indicator function in the adversarial environment. To this end, this paper aims to propose an intelligent assignment strategy which contains indicator function and evaluation model. Then, an indicator function and an evaluation model considering the miss distance, threat situation, and the number of specified interception targets are introduced into the reinforcement learning algorithm. The local and global reward functions are introduced to improve the training convergence and efficiency in the multi-missile multi-target confrontation scenario. Finally, simulation results are designed to check on advantage of intelligent allocation strategy.

关键词： Training Missiles Analytical models Automation Simulation Reinforcement learning Resource management

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A Triple-layer Frequency Selective Surface with Flat Wide Passband 5

A Triple-layer Frequency Selective Surface with Flat Wide Pa...

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5th IEEE International Conference on Computational Electromagnetics, ICCEM 2019

作者： Cui, Yichun Zhang, Shengjun Wang, Mingliang National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing China

ISBN: (纸本)9781538671115

In this paper, a novel triple-layer band-pass Frequency selective surface (FSS) with wide passband and low insertion loss is proposed. The proposed FSS is composed of three FSS layers and two dielectric substrates which are symmetric vertically. This structure realizes a three-order response and wide stop band with steep falling edge. Equivalent circuit analysis indicates that the three-order response is generated by resonance of FSS layers and coupling between layers, respectively. After optimization, the passband of proposed FSS ranges from 7.728GHz to 12.31GHz, whose fractional bandwidth reaches 44.5% with -0.044dB insertion loss. Meanwhile, this FSS has stable performance for TE polarization under oblique incidence. © 2019 IEEE.

关键词： Frequency selective surfaces

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Perturbation Estimated Incremental Guidance for Exo-Atmospheric Interception

Perturbation Estimated Incremental Guidance for Exo-Atmosphe...

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Chinese Automation Congress (CAC)

作者： Yuting Lu Peng Liu Tuo Han Qinglei Hu School of Automation Science and Electrical Engineering Beihang University Beijing China National Key Laboratory of Science and Technology on Test Physics & Numerical Mathematics Beijing Institute of Space Long March Vehicle Beijing China School of Aeronautic Science and Engineering Beihang University Beijing China Beihang Hangzhou Innovation Institute (Yuhang) Hangzhou China

In order to meet the requirement of accurate intercept against the increased target maneuverability and external disturbance, a second-order inertial delay based incremental guidance law (IDIASMG) is proposed for an exo-atmospheric interceptor. Specifically, a three-dimensional guidance model is transformed into an incremental version. As a guidance design benchmark, a conventional sliding mode guidance law (SMG) is presented, and a sliding mode incremental guidance law (ISMG) is designed with gain adaptation. Moreover, a second-order inertial delay filter is utilized to estimate and compensate guidance perturbation including the target maneuver, system uncertainty, and external disturbance. Theoretical analysis shows that the incremental guidance requires smaller gains to ensure smaller system residual than the conventional SMG. Extensive numerical simulations validate the effectiveness and robustness of IDIASMG.

关键词： Solid modeling Uncertainty Adaptive systems Upper bound Navigation Perturbation methods numerical simulation

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Resolved magnetohydrodynamic wave lensing in the solar corona

arXiv

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arXiv 2024年

作者： Zhou, Xinping Shen, Yuandeng Yuan, Ding Keppens, Rony Zhao, Xiaozhou Fu, Libo Tang, Zehao Wang, Jiaoyang Zhou, Chengrui College of Physics and Electronic Engineering Sichuan Normal University Chengdu610068 China Yunnan Observatories Chinese Academy of Sciences Kunming650216 China Shenzhen Key Laboratory of Numerical Prediction for Space Storm Institute of Space Science and Applied Technology Harbin Institute of Technology Guangdong Shenzhen China Key Laboratory of Solar Activity and Space Weather National Space Science Center Chinese Academy of Sciences Beijing China Centre for mathematical Plasma Astrophysics Department of Mathematics KU Leuven Celestijnenlaan 200B LeuvenB-3001 Belgium

Electromagnetic wave lensing, a common physical phenomenon recognized in visible light for centuries, finds extensive applications in manipulating light in optical systems such as telescopes and cameras. Magnetohydrodynamic wave is a common perturbation phenomenon in the corona. By using high spatio-temporal resolution observations from the Solar Dynamics Observatory, here, we report the observation of a magnetohydrodynamic wave lensing in the highly ionized and magnetized coronal plasma, where quasi-periodic wavefronts emanated from a flare converged at a specific point after traversing a coronal hole. The entire process resembles an electromagnetic wave lensing from the source to the focus. Meanwhile, the magnetohydrodynamic wave lensing is well reproduced through a magnetohydrodynamic numerical simulation with full spatio-temporal resolution. We further investigate potential applications for coronal seismology, as the lensing process encodes information on the Alfvén speed, in conjunction with favorable geometric and density variations. Copyright © 2024, The Authors. All rights reserved.

关键词： Electromagnetic waves

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Graph-GIC: A Smart and Parallelized Geomagnetically Induced Current Modelling Algorithm Based on Graph Theory for Space Weather Applications

arXiv

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arXiv 2024年

作者： Chen, Wen Yuan, Ding Feng, Xueshang Poedts, Stefaan Zou, Zhengyang Feng, Song Zhu, Yuxuan Yin, Tong Shenzhen Key Laboratory of Numerical Prediction for Space Storm School of Aerospace Harbin Institute of Technology Guangdong Shenzhen518055 China Key Laboratory of Solar Activity and Space Weather National Space Science Center Chinese Academy of Sciences Beijing China Centre for Mathematical Plasma Astrophysics Department of Mathematics KU Leuven LeuvenB-3001 Belgium State Key Laboratory of Lunar and Planetary Sciences Macau University of Science and Technology China Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Institute of Physics University of Maria Curie-Sklodowska ul. Marii Curie-Sklodowskiej 1 Lublin20-031 Poland

Geomagnetically Induced Current (GIC) refers to the electromagnetic response of the Earth and its conductive modern infrastructures to space weather and would pose a significant threat to high-voltage power grids designed for the alternative current operation. To assess the impact of space weather on the power grid, one needs to calculate the GIC on a national or continental scale. In this study, we developed a smart and parallelized GIC modelling algorithm, Graph GIC. This algorithm deploys a graph representing a power grid in a single-line diagram, in which substations/transformers act as nodes and transmission lines as edges. With these denotations, a power grid and its electric parameters are mathematically represented with an adjacency matrix and an admittance matrix. We used sparse matrix and parallelisation techniques to expedite the intensive computation in cases of large-scale power grids. The Graph GIC was validated with a benchmark grid, applied to the GIC calculation of the 500 kV power grid of Guangdong, China, and conducted preliminary analysis on the grid’s susceptibility to geomagnetic storms. The Graph GIC algorithm has the advantage of an intuitive and highly scalable graph representation of a power grid at any scale. It achieves high-accuracy calculation and a speedup of about 18 times after parallelisation. This algorithm could be applied to assess the impact of space weather on a power grid up to continental scales and could be incorporated into global space weather modelling frameworks. Copyright © 2024, The Authors. All rights reserved.

关键词： Matrix algebra

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