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Climate effects of nuclear war in china

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Journal of Environmental sciences 1993年第2期5卷 230-240页

作者： cao hongxingchinese academy of meteorological sciences, beijing 100081, chinaWang Yongzhong Lin Yunmeibeijing Institute of Meteorology, beijing 100081, china Chinese academy of meteorological sciences Beijing 100081 China. China

By utilizing simulations of climatic respponse to nuclear smoke, which were made by the Lawrence Livermore National Laboratory, USA, climate change in china induced by a large-scale nuclear war is analysed. Remarkable climate change in china following nuclear smoke injections is found. The surface air temperature decreases dramatically around all china, surface cooling is 13 ℃ averaging over whole china in July and maximum cooling is 23. 4 ℃ , 3 ℃ cooling in January and maximum 8℃ for the 150 Tg smoke injection (equivalent to the base-line nuclear war). However, the change in temperature is unhomogeneous, implying that the rise in temperature happens over some parts of china. An averaging precipitation decrease in many of months of the experimental year. The precipitation defect is dependent on a scale of nuclear war, the deduction is 1.8mm/day averaging over china in July in the 150 Tg smoke injection, and 0.1 mm/d in January. Nevertheless, the precipitation enhancement in a few months over some regions is found. This dramatic climate change brings catastrophe to agriculture, ecology, as well as socio-economics.

关键词： nuclear winter climate simulation precipitation change.

The least-square method in complex number domain

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Progress in Natural Science:Materials International 2006年第3期16卷 307-312页

作者： GU Xiangqian, KANG Hongwen and cao Hongxing (State Key Laboratory of Severe Weather, Chinese academy of meteorological sciences, beijing 100081, china) State Key Laboratory of Severe Weather Chinese Academy of Meteorological Sciences Beijing 100081 China

The classical least-square method was extended from the real number into the complex number domain, which is called the complex least-square method. The mathematical derivation and its applications show that the complex least-square method is different from one that the real number and the imaginary number are separately calculated with the classical least-square, by which the actual least-square estimation cannot be obtained in practice. Applications of this new method to an arbitrarily given series and to the precipitation in rainy season at 160 meteorological stations in china mainland show advantages of this method over other conventional statistical models.

关键词： complex least square Fourier transformation forecast in rainy season.

umerical tests of efficiency of the retrospective time integration scheme in the self-memory model

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Progress in Natural Science:Materials International 2004年第9期 89-92页

作者： GU Xiangqian 1*, YOU Xingtian 2, ZHU He 2 and cao Hongxing 1(1. Chinese academy of meteorological sciences, beijing 100081, china 2. Training Center of china meteorological Administration, beijing 100081, china)

A set of numerical tests was carried out to compare the retrospective time integral scheme in a self memory model, whose dynamic kernel is the barotropical quasi geostrophic model, with the ordinary centered difference scheme in the barotropical quasi geostrophic model. The Rossby Haurwitz wave function was taken as the initial fields for both schemes. The results show that in comparison with the ordinary centered difference scheme, the retrospective time integral scheme reduces by 2 orders of magnitude the forecast error, and the forecast error increases very little with lengthening of the time step. Therefore, the retrospective time integral scheme has advantages of improving the forecast accuracy, extending the predictable duration and reducing the computation amount.

关键词： numerical tests self-memory model retrospective time integral scheme.

Numerical simulation analysis of wind field above pavement surface in different landforms by computational fluid dynamics approach

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Journal of Traffic and Transportation Engineering(English Edition) 2024年第3期11卷 559-573页

作者： Jian Ouyang Zhao Jiang Leiyu Ye Jing Li Peng cao School of Civil Engineering and Architecture Hainan UniversityHaikou 570000China School of Transportation and Logistics Dalian University of TechnologyDalian 116024China Hexagon Manufacturing Intelligence(Qingdao)Co. Ltd.Qingdao 266000China china Tower Co. Ltd.Dalian BranchDalian 116024China Faculty of Architecture Civil and Transportation EngineeringBeijing University of TechnologyBeijing 100124China

The temperature and moisture of the pavement structure can be greatly influenced by the wind speed above pavement *** wind speed above pavement surface not only is dominated by the wind speed of atmosphere,but also it is highly related to the landform and buildings around ***,currently there are no studies about the wind field above pavement surface in consideration of the effect of the landform and buildings.A simulation method,which is combined with geographic information system(GIS),wind data from meteorological observatory and computational fluid dynamics(CFD)software,is employed to study the effect of the landform and the wind speed of atmosphere on the wind field above pavement *** cases are studied,including an urban road,a coastal road and a mountainous ***,the wind field distribution above road surface in different wind directions was studied in our *** indicate that the wind field above pavement surface can be greatly affected by the landforms,buildings and wind *** simulation method can provide reliable results for the wind field above pavement *** maximum relative errors between simulated and measured wind speed can be less than 20%in the analysis of the three *** is recommended that the CFD simulation method is a good tool to accurately know the wind field above pavement surface.

关键词： Wind field above pavement surface Computational fluid dynamics Landforms Geographic information system Simulation

Factors Influencing the Spatial Variability of Air Temperature Urban Heat Island Intensity in Chinese Cities

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Advances in Atmospheric sciences 2024年第5期41卷 817-829页

作者： Heng LYU Wei WANG Keer ZHANG Chang cao Wei XIAO Xuhui LEE Key Laboratory of meteorological Disaster Ministry of Education(KLME)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)/Key Laboratory of Ecosystem Carbon Source and SinkChina Meteorological Administration(ECSS-CMA)/Jiangsu Key Laboratory of Agricultural MeteorologyNanjing University of Information Science&TechnologyNanjing 210044China Key Laboratory of Urban Meteorology China Meteorological AdministrationBeijing 100089China School of the Environment Yale UniversityNew HavenCT 06511USA

Few studies have investigated the spatial patterns of the air temperature urban heat island(AUHI)and its controlling *** this study,the data generated by an urban climate model were used to investigate the spatial variations of the AUHI across china and the underlying climate and ecological drivers.A total of 355 urban clusters were *** performed an attribution analysis of the AUHI to elucidate the mechanisms underlying its *** results show that the midday AUHI is negatively correlated with climate wetness(humid:0.34 K;semi-humid:0.50 K;semi-arid:0.73 K).The annual mean midnight AUHI does not show discernible spatial patterns,but is generally stronger than the midday *** urban–rural difference in convection efficiency is the largest contributor to the midday AUHI in the humid(0.32±0.09 K)and the semi-arid(0.36±0.11 K)climate *** release of anthropogenic heat from urban land is the dominant contributor to the midnight AUHI in all three climate *** rural vegetation density is the most important driver of the daytime and nighttime AUHI spatial variations.A spatial covariance analysis revealed that this vegetation influence is manifested mainly through its regulation of heat storage in rural land.

关键词： air temperature urban heat island spatial variations biophysical drivers Chinese cities climate model

Improved forecasting via physics-guided machine learning as exemplified using“21·7”extreme rainfall event in Henan

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Science china Earth sciences 2024年第5期67卷 1652-1674页

作者： Qi ZHONG Zhicha ZHANG Xiuping YAO Shaoyu HOU Shenming FU Yong cao Linguo JING china meteorological Administration Training Center Beijing 100081China State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesBeijing 100081China Zhejiang meteorological Observatory Hangzhou 310017China Hebei Provincial Weather Modification Center Shijiazhuang 050020China Institute of Atmospheric Physics Chinese Academy of SciencesBeijing 100029China National meteorological Center Beijing 100081China School of Computer Science Chengdu University of Information TechnologyChengdu 610225China

As a natural disaster,extreme precipitation is among the most destructive and influential,but predicting its occurrence and evolution accurately is very challenging because of its rarity and *** the example of the“21·7”extreme precipitation event(17–21 July 2021)in Henan Province,this study explores the potential of using physics-guided machine learning to improve the accuracy of forecasting the intensity and location of extreme *** physics-guided ways of embedding physical features,fusing physical model forecasts and revised loss function are used,i.e.,(1)analyzing the anomalous circulation and thermodynamical factors,(2)analyzing the multi-model forecast bias and the associated underlying reasons for it,and(3)using professional forecasting knowledge to design the loss function,and the corresponding results are used as input for machine learning to improve the forecasting *** results indicate that by learning the relationship between anomalous physical features and heavy precipitation,the forecasting of precipitation intensity is improved significantly,but the location is rarely adjusted and more false alarms *** reasons for this are as *** anomalous features used here mainly contain information about large-scale systems and factors which are consistent with the model precipitation deviation;moreover,the samples of extreme precipitation are sparse and so the algorithm used here is ***,by combining“good and different”multi models with machine learning,the advantages of each model are extracted and then the location of the precipitation center in the forecast is improved ***,by combining the appropriate anomalous features with multi-model fusion,an integrated improvement of the forecast of the rainfall intensity and location is ***,this study is a novel exploration to improve the refined forecasting of heavy precipitation with extreme intensity and high variability,

关键词： Extreme precipitation event Refined assessment Anomalous physical features Multi-model fusion Machine learning

Very Short-Term Forecasting of Distributed PV Power Using GSTANN

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CSEE Journal of Power and Energy Systems 2024年第4期10卷 1491-1501页

作者： Tiechui Yao Jue Wang Yangang Wang Pei Zhang Haizhou cao Xuebin Chi Min Shi Computer Network Information Center of the Chinese academy of sciences Beijing 100190China University of Chinese academy of sciences Beijing 100190China School of Electrical Engineering Beijing Jiaotong UniversityBeijing 100044China State Grid Hebei Electric Power Co. Ltd.Shijiazhuang 050000China

Photovoltaic(PV)power forecasting is essential for secure operation of a power *** prediction of PV power can improve new energy consumption capacity,help power system planning,promote development of smart grids,and ultimately support construction of smart energy ***,different from centralized PV power forecasts,three critical challenges are encountered in distributed PV power forecasting:1)lack of on-site meteorological observation,2)leveraging extraneous data to enhance forecasting performance,3)spatial-temporal modelling methods of meteorological information around the distributed PV *** address these issues,we propose a Graph Spatial-Temporal Attention Neural Network(GSTANN)to predict the very short-term power of distributed ***,we use satellite remote sensing data covering a specific geographical area to supplement meteorological information for all PV ***,we apply the graph convolution block to model the non-Euclidean local and global spatial dependence and design an attention mechanism to simultaneously derive temporal and spatial ***,we propose a data fusion module to solve the time misalignment between satellite remote sensing data and surrounding measured on-site data and design a power approximation block to map the conversion from solar irradiance to PV *** conducted with real-world case study datasets demonstrate that the prediction performance of GSTANN outperforms five state-of-the-art baselines.

关键词： Distributed photovoltaic power forecasting graph convolutional networks satellite images spatial-temporal attention

Influences of Earth Incidence Angle on FY-3/MWRI SST Retrieval and Evaluation of Reprocessed SST

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Journal of Tropical Meteorology 2024年第3期30卷 230-240页

作者： ZHANG Miao CHEN Lin XU Na cao Guang-zhen Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites National Satellite Meteorological CenterChina Meteorological AdministrationBeijing 100081 China Innovation Center for FengYun meteorological Satellite(FYSIC) Beijing 100081 China

Sea surface temperature(SST)is a crucial physical parameter in meteorology and *** study demonstrates that the influence of earth incidence angle(EIA)on the SST retrieved from the microwave radiation imager(MWRI)onboard FengYun-3(FY-3)meteorological satellites should not be *** with algorithms that do not consider the influence of EIA in the regression,those that integrate the EIA into the regression can enhance the accuracy of SST ***,based on the recalibrated Level 1B data from the FY-3/MWRI,a long-term SST dataset was reprocessed by employing the algorithm that integrates the EIA into the *** reprocessed SST data,including FY-3B/MWRI SST during 2010-2019,FY-3C/MWRI SST during 2013-2019,and FY-3D/MWRI SST during 2018-2020,were compared with the in-situ SST and the SST dataset from the Operational Sea Surface Temperature and Ice Analysis(OSTIA).The results show that the FY-3/MWRI SST data were consistent with both the in-situ SST and the OSTIA SST *** with the Copernicus Climate Change Service V2.0 SST,the absolute deviation of the reprocessed SST,with a quality flag of 50,was less than 1.5℃.The root mean square errors of the FY-3/MWRI orbital,daily,and monthly SSTs,with a quality flag of 50,were approximately 0.82℃,0.69℃,and 0.37℃,*** primary discrepancies between the FY-3/MWRI SST and the OSTIA SST were found mainly in the regions of the western boundary current and the Antarctic Circumpolar ***,this reprocessed SST product is recommended for El Niño and La Niña events monitoring.

关键词： FengYun-3 satellites sea surface temperature microwave radiation imager earth incidence angle reprocessing

THEORETICAL ANALYSES AND NUMERICAL EXPERIMENTS FOR TWO-DIMENSIONAL WIND RETRIEVALS FROM SINGLE-DOPPLER DATA

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Journal of Hydrodynamics 2010年第2期22卷 185-195页

作者： HUANG Si-xun cao Xiao-qun DU Hua-dong ZHONG Ji-qin Institute of Meteorology PLA University of Science and Technology Nanjing 211101 China National University of Defense Technolog Changsha 410073 China Institute of Urban Meteorology China Meteorological Administration Beijing 100089 China

Based on variational adjoint methods,theoretical analyses and numerical experiments are performed for retrievals of two-dimensional winds and related parameters from single-Doppler radar data in polar *** the method,the reflectivity conservation equation is used as the governing equation and the mass continuity equation as a weak *** the same time,the stable functional of regularization and background field are also introduced in the cost *** on the ideal experiments with artificial data,real two-dimensional wind fields are retrieved with low-altitude data from the Nanjing Doppler Radar Station,and the results are encouraging and promising.

关键词： single-Doppler retrievals adjoint methods regularization methods two-dimensional wind