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Predictability of the 7·20 extreme rainstorm in Zhengzhou in stochastic kinetic-energy backscatter ensembles

Science China Earth Sciences 2024年第7期67卷 2226-2241页

作者： Min YANG Peilong YU Lifeng ZHANG Xiaobing PAN Quanjia ZHONG Yunying LI college of Meteorology and Oceanography National University of Defense TechnologyChangsha 410073China Key Laboratory of High Impact Weather(Special) China Meteorological AdministrationChangsha 410073China Collaborative Innovation Center on Forecast and Evaluation of Meteorological disasters/Key Laboratory of Meteorological disaster Ministry of Education/Joint International Research Laboratory of Climate and Environment ChangeNanjing University of Information Science and TechnologyNanjing 210044China Department of Ocean Science Hong Kong University of Science and TechnologyHong Kong 999077China

The scale-dependent predictability of the devastating 7·20 extreme rainstorm in Zhengzhou,China in 2021.was investigated via ensemble experiments,which were perturbed on different scales using the stochastic kinetic-energy backscatter(SKEB)scheme in the WRF model,with the innermost domain having a 3-km grid *** daily rainfall(RAIN24h)and the cloudburst during 1.00-1.00 LST(RAIN1.)were *** demonstrated that with larger perturbation scales,the ensemble spread for the rainfall maximum widens and rainfall forecasts become closer to the *** ensembles with mesoscale or convective-scale perturbations,RAIN1. loses predictability at scales smaller than 20 km and RAIN24h is predictable for all *** in ensembles with synoptic-scale perturbations,the largest scale of predictability loss extends to 60 km for both RAIN1. and ***,the average positional error in forecasting the heaviest rainfall for RAIN24h(RAIN1.)was 400 km(50-60)*** southerly low-level jet near Zhengzhou was assumed to be directly responsible for the forecast uncertainty of *** rapid intensification in low-level cyclonic vorticity,mid-level divergence,and upward motion concomitant with the jet dynamically facilitated the *** analysis of the divergent,rotational and vertical kinetic spectra and the corresponding error spectra showed that the error kinetic energy at smaller scales grows faster than that at larger scales and saturates more quickly in all ***-scale perturbations not only boost larger-scale error growth but are also conducive to error growth at all scales through a downscale cascade,which indicates that improving the accuracy of larger-scale flow forecast may discernibly contributes to the forecast of cloudburst intensity and position.

关键词： Stochastic kinetic-energy backscatter(SKEB) Extreme rainfall Ensemble forecast Predictability

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Effects of H_2/CO/CH_4 syngas composition variation on the NO_x and CO emission characteristics in a partially-premixed gas turbine combustor

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Science China(Technological Sciences) 2016年第12期59卷 1804-1813页

作者： Lee Min Chul Department of Safety Engineering College of EngineeringFire Disaster Prevention Research CenterIncheon National University

This paper reports the effects of variations in the fuel composition of H_2/CO/CH_4 syngas on the characteristics of NO_x and CO emissions in a partially-premixed gas turbine combustor. Combustion tests were conducted on a full range of fuel compositions by varying each component gas from 0% to 1.0% at heat inputs of 40 and 50 k Wth. Flame temperature, combustor liner temperature, ignition delay time, and flame structure were investigated computationally and experimentally to judge whether they are significant indicators of NO_x and CO formation. The characteristics of and reasons for NO_x and CO emissions were investigated by analyzing the emission mechanisms and relationships among fuel property, equivalence ratio, flame temperature, liner temperature, flame shape. The flame structures were investigated using the following flame visualization methods:(1. time-averaged OH* chemiluminescence and its Abel-deconvolution;(2) direct photography; and(3) instantaneous OH-PLIF. The flame structures were greatly changed by the fuel composition and heat input, and they were subjected to key affecting parameters of the temperatures of the flames and the liners. NO_x and CO emissions also largely varied according to fuel composition and heat input, showing neither linearly nor exponentially clear proportional trends toward the syngas compositions because of the singular conditions. For example, only the 1.0% CO flame at low load emitted lots of CO, whereas complete combustion was observed in other cases. However, the qualitative observations showed that the root causes of NO_x emission behaviors were flame temperature and flame structure, which were directly related to the residence time in the flame. Various sets of practical test results were obtained, and these results could contribute to the optimal selection of the fuel-feeding condition when fuel is changed from natural gas to syngas in order to minimize NO_x and CO emissions with stable combustion.

关键词： gas turbine combustor NO_x and CO emission synthetic gas OH* chemiluminescence planar laser induced fluorescence

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Enhancing Deep Learning Soil Moisture Forecasting Models by Integrating Physics-based Models

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Advances in Atmospheric Sciences 2024年第7期41卷 1326-1341页

作者： Lu LI Yongjiu DAI Zhongwang WEI Wei SHANGGUAN Nan WEI Yonggen ZHANG Qingliang LI Xian-Xiang LI School of Atmospheric Sciences Sun Yat-sen UniversityGuangzhou 510275China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Guangzhou 510275China Guangdong Province Key Laboratory for Climate Change and Natural disaster Studies Guangzhou 510275China Institute of Surface-Earth System Science School of Earth System ScienceTianjin UniversityTianjin 300072China college of Computer Science and Technology Changchun Normal UniversityChangchun 130123China

Accurate soil moisture(SM)prediction is critical for understanding hydrological ***-based(PB)models exhibit large uncertainties in SM predictions arising from uncertain parameterizations and insufficient representation of land-surface *** addition to PB models,deep learning(DL)models have been widely used in SM predictions ***,few pure DL models have notably high success rates due to lacking physical ***,we developed hybrid models to effectively integrate the outputs of PB models into DL models to improve SM *** this end,we first developed a hybrid model based on the attention mechanism to take advantage of PB models at each forecast time scale(attention model).We further built an ensemble model that combined the advantages of different hybrid schemes(ensemble model).We utilized SM forecasts from the Global Forecast System to enhance the convolutional long short-term memory(ConvLSTM)model for 1.1. days of SM *** performances of the proposed hybrid models were investigated and compared with two existing hybrid *** results showed that the attention model could leverage benefits of PB models and achieved the best predictability of drought events among the different hybrid ***,the ensemble model performed best among all hybrid models at all forecast time scales and different soil *** is highlighted that the ensemble model outperformed the pure DL model over 79.5%of in situ stations for 1.-day *** findings suggest that our proposed hybrid models can adequately exploit the benefits of PB model outputs to aid DL models in making SM predictions.

关键词： soil moisture forecasting hybrid model deep learning ConvLSTM attention mechanism

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Prediction of Extreme Significant Wave Height from Daily Maxima

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China Ocean Engineering 2001年第1期16卷 97-106页

作者：刘德辅李华军温书勤宋艳王树青 disaster {1. Research Institute Ocean University of Qingdao college of Engineering Ocean University of Qingdao

For prediction of the extreme significant wave height in the ocean areas where long term wave data are not available, the empirical method of extrapolating short term data (1.similar to3 years) is used in design practice. In this paper two methods are proposed to predict extreme significant wave height based on short-term daily maxima. According to the daa recorded by the Oceanographic Station of Liaodong Bay at the Bohai Sea, it is supposed that daily maximum wave heights are statistically independent. The data show that daily maximum wave heights obey log-normal distribution, and that the numbers of daily maxima vary from year to year, obeying binomial distribution. Based on these statistical characteristics, the binomial-log-normal compound extremum distribution is derived for prediction of extreme significant wave heights (50 similar to 1.0 years). For examination of its accuracy and validity, the prediction of extreme wave heights is based on 1. years' data at this station, and based on each 3 years' data respectively. The results show that with consideration of confidence intervals, the predicted wave heights based on 3 years' data are very close to those based on 1. years' data. The observed data in some ocean areas in the Atlantic Ocean and the North Sea show it is not correct to assume that daily maximum wave heights are statistically independent; they are subject to Markov chain condition, obeying log-normal distribution. In this paper an analytical method is derived to predict extreme wave heights in these cases. A comparison of the computations shows that the difference between the extreme wave heights based on the assumption that daily maxima are statistically independent and that they are subject to Markov Chain condition is smaller than 1.%.

关键词： daily maxima compound extremum distribution Markov chain

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沙尘暴中多物理场的结构和耦合特征

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Acta Mechanica Sinica 2024年第3期40卷 28-39页

作者：张欢 Center for Particle-laden Turbulence Lanzhou UniversityLanzhou730000China Key Laboratory of Mechanics on disaster and Environment in Western China Attached to the Ministry of Education of China Lanzhou UniversityLanzhou730000China Department of Mechanics and Engineering Science College of Civil Engineering and MechanicsLanzhou UniversityLanzhou730000China

沙尘暴是典型的分散两相大气湍流,其中沙尘颗粒高度带电.虽然在单相高雷诺数湍流中已经确认存在超大尺度运动(very-large-scale motions,VLSMs),但在沙尘暴中,尤其是涉及湍动电场方面的研究还相对较少.在本文中,利用大气表面层内现场观... 详细信息

沙尘暴是典型的分散两相大气湍流,其中沙尘颗粒高度带电.虽然在单相高雷诺数湍流中已经确认存在超大尺度运动(very-large-scale motions,VLSMs),但在沙尘暴中,尤其是涉及湍动电场方面的研究还相对较少.在本文中,利用大气表面层内现场观测数据,我们证明沙尘暴的风速、直径小于1.微米的沙尘颗粒浓度(PM1.沙尘浓度)和电场存在大致相同大小的VLSMs.此外,我们发现这些多物理场在VLSMs尺度上具有最大的线性耦合,线性相干谱在0.5–0.8之间.通过传递熵分析,我们进一步证明风速和PM1.沙尘浓度在波数k_(1.=0.002 m^(-1.处具有最大的非线性耦合,而PM1.沙尘浓度和电场在k_(1.=0.1. m^(-1.处具有最大的非线性耦合,这表明风场-粉尘和粉尘-静电相互作用之间存在不同的非线性耦合行为.我们的研究结果揭示了沙尘暴中多物理场的结构和耦合特征,从而为理解复杂的分散两相湍流流动提供了关键信息.

关键词： Very-large-scale motions Electric fields Particle-laden flow Dust storms

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Interhemispheric atmospheric mass oscillation and its relation to interannual variations of the Asian monsoon in boreal summer

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Science China Earth Sciences 2010年第9期53卷 1343-1350页

作者： LU ChuHan, GUAN ZhaoYong & CAI JiaXi Key Laboratory of Meteorological disaster of Ministry of Education and {1. of Atmospheric Sciences, Nanjing University of Information Science & Technology, Nanjing 21.044, China 1. Key Laboratory of Meteorological disaster of Ministry of Education and {1. of Atmospheric Sciences Nanjing University of Information Science & Technology Nanjing 210044 China

Using NCEP/NCAR reanalysis and precipitation records of Chinese stations, we have investigated the relationship of interhemispheric oscillation of air mass (IHO) with global lower-level circulation and monsoon anomalies in boreal summer. Our results show that the summer IHO explains a greater portion of variance in the abnormal distribution of atmospheric mass over 30°S-60°N as well as the Antarctic. The IHO strongly correlates to the variations of sea level pressure (SLP) in these regions. It is shown that IHO has some influences on both atmospheric mass transports and water vapor fluxes over 30°S-60°N in association with three anomalous cyclonic circulations over land areas of the eastern hemisphere, which is in close relation to the changes in summer monsoon intensity in eastern Asia and western Africa. Composites of summer rainfall anomalies in China for high and low IHO-index years indicate that the eastern Asian summer monsoon is more intense, with positive precipitation anomaly centers in northern and northeastern parts of China, as opposed to the negative center over the mid-lower reaches of the Yangtze River (MLRYR) in stronger IHO years. In weak IHO years, a feeble summer monsoon appears in eastern Asia, leading to positive center of precipitation anomalies displaced into the MLRYR. Furthermore, a teleconnection in wind fields between the western African and eastern Asian monsoon regions was observed in the middle and higher troposphere in the scenario of IHO. The anomalous cyclonic (anticyclonic) circulations along the path of this Africa-East Asia teleconnection were found to be just over the diabatic heating (cooling) centers, suggesting that diabatic forcings are responsible for the formation of this Africa-East Asia teleconnection.

关键词： interhemispheric oscillation Asian monsoon precipitation China boreal summer

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Enhanced detection of freeze‒thaw induced landslides in Zhidoi county(Tibetan Plateau,China)with Google Earth Engine and image fusion

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Advances in Climate Change Research 2024年第3期15卷 476-489页

作者： Jia-Hui YANG Yan-Chen GAO Lang JIA Wen-Juan WANG Qing-Bai WU Francis ZVOMUYA Miles DYCK Hai-Long HE college of Natural Resources and Environment Northwest A&F UniversityYangling 712100China State Key Laboratory of Frozen Soil Engineering Northwest Institute of Eco-Environment and ResourcesChinese Academy of SciencesLanzhou 730000China Department of Soil Science University of Manitob1Winnipeg MB R3T 2N2Canada Department of Renewable Resources University of Albert1Edmonton AB T6G 2H1Canad

Freeze‒thaw induced landslides(FTILs)in grasslands on the Tibetan Plateau are a geological disaster leading to soil *** landslides reduce biodiversity and intensify landscape fragmentation,which in turn are strengthen by the persistent climate change and increased anthropogenic ***,conventional techniques for mapping FTILs on a regional scale are impractical due to their labor-intensive,costly,and time-consuming *** study focuses on improving FTILs detection by implementing image fusion-based Google Earth Engine(GEE)and a random forest *** of multiple data sources,including texture features,index features,spectral features,slope,and vertical‒vertical polarization data,allow automatic detection of the spatial distribution characteristics of FTILs in Zhidoi county,which is located within the Qinghai‒Tibet Engineering Corridor(QTEC).We employed statistical techniques to elucidate the mechanisms influencing FTILs *** enhanced method identifies two schemes that achieve high accuracy using a smaller training sample(scheme A:94.1.;scheme D:94.5%)compared to other methods(scheme B:50.0%;scheme C:95.8%).This methodology is effective in generating accurate results using only~1.%of the training sample size necessitated by other *** spatial distribution patterns of FTILs generated for 2021.are similar to those obtained using various other training sample sources,with a primary concentration observed along the central region traversed by the *** results highlight the slope as the most crucial feature in the fusion images,accounting for 93%of FTILs occurring on gentle slopes ranging from 0°to 1.°.This study provides a theoretical framework and technological reference for the identification,monitoring,{1. and control of FTILs in *** developments hold the potential to benefit the management of grassland ecosystem,reduce economic losses,and promote grassland sustainability.

关键词： Permafrost degradation Random forest Thaw slump Spatial distribution Tibetan Plateau

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New method to identify optimal discontinuity set number of rock tunnel excavation face orientation based on Fisher mixed evaluation

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Underground Space 2024年第4期17卷 300-319页

作者： Keshen Zhang Wei Wu Min Zhang Yongsheng Liu Yong Huang Baolin Chen college of Civil Engineering Tongji UniversityShanghai 200092China Key Laboratory of Geotechnical and Underground Engineering of Ministry of Education Tongji UniversityShanghai 200092China State Key Laboratory of disaster Reduction in Civil Engineering Tongji UniversityShanghai 200092China Shudao Investment Group Co.Ltd Chengdu 610095China China Railway Tunnel Group Co.Ltd Guangzhou 511466China China Railway First Survey and Design Institute Group Co.Ltd Xi’an 710043China Zhejiang Institute of Communications Co.Ltd Hangzhou 310012China

Discontinuity is critical for strength,deformability,and permeability of rock *** information is one of the essential discontinuity characteristics and is usually accessed by orientation *** methods of identifying optimal discontinuity set numbers are usually achieved by clustering validity indexes,which mainly relies on the aggregation and dispersion of clusters and leads to the inaccuracy and instability of *** paper proposes a new method of Fisher mixed evaluation(FME)to identify optimal group numbers of rock mass discontinuity *** FME,orientation distribution is regarded as the superposition of Fisher mixed *** grouping results are identified by considering the fitting accuracy of Fisher mixed distributions,the probability monopoly and central location significance of independent Fisher centers.A Halley-Expectation-Maximization(EM)algorithm is derived to achieve an automatic fitting of Fisher mixed *** real rock discontinuity models combined with three orientation clustering algorithms are adopted for discontinuity *** clustering validity indexes are used to automatically identify optimal group numbers for *** results show that FME is more accurate and robust than the other clustering validity indexes in optimal discontinuity group number identification for different rock models and orientation clustering algorithms.

关键词： Rock mass discontinuity Orientation grouping Fisher mixed distribution 3D point cloud Stereo photogrammetry

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A novel CGBoost deep learning algorithm for coseismic landslide susceptibility prediction

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Geoscience Frontiers 2024年第2期15卷 349-365页

作者： Qiyuan Yang Xianmin Wang Jing Yin Aiheng Du Aomei Zhang Lizhe Wang Haixiang Guo Dongdong Li Hubei Subsurface Multi-scale Imaging Key Laboratory School of Geophysics and GeomaticsChina University of GeosciencesWuhan 430074China State Key Laboratory of Biogeology and Environmental Geology China University of GeosciencesWuhan 430074China Key Laboratory of Geological and Evaluation of Ministry of Education China University of GeosciencesWuhan 430074China Laboratory of Natural disaster Risk {1. and Emergency Management School of Economics and ManagementChina University of GeosciencesWuhan 430074China college of Electronic Science and Engineering National University of Defense TechnologyChangsha 410073China

The accurate prediction of landslide susceptibility shortly after a violent earthquake is quite vital to the emergency rescue in the 72-h‘‘golden window”.However,the limited quantity of interpreted landslides shortly after a massive earthquake makes landslide susceptibility prediction become a *** address this gap,this work suggests an integrated method of Crossing Graph attention network and xgBoost(CGBoost).This method contains three branches,which extract the interrelations among pixels within a slope unit,the interrelations among various slope units,and the relevance between influencing factors and landslide probability,respectively,and obtain rich and discriminative features by an adaptive fusion ***,the difficulty of susceptibility modeling under a small number of coseismic landslides can be *** a basic module of CGBoost,the proposed Crossing graph attention network(Crossgat)could characterize the spatial heterogeneity within and among slope units to reduce the false alarm in the susceptibility ***,the rainfall dynamic factors are utilized as prediction indices to improve the susceptibility performance,and the prediction index set is established by terrain,geology,human activity,environment,meteorology,and earthquake *** is applied to predict landslide susceptibility in the Gorkha meizoseismal area.3.43%of coseismic landslides are randomly selected,of which 70%are used for training,and the others for *** the testing set,the values of Overall Accuracy,Precision,Recall,F1.score,and Kappa coefficient of CGBoost attain 0.9800,0.9577,0.9999,0.9784,and 0.9598,*** by all the coseismic landslides,CGBoost outperforms the current major landslide susceptibility assessment *** suggested CGBoost can be also applied to landslide susceptibility prediction in new earthquakes in the future.

关键词： Coseismic landslide Landslide susceptibility prediction Graph neural network Deep learning

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Analysis of meso-inhomogeneous deformation on a metal material surface under low-cycle fatigue

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Acta Mechanica Solida Sinica 2017年第6期30卷 557-572页

作者： Gui-Long Liu Ke-Shi Zhang Xian-Ci Zhong Jiann Woody Ju college of Civil Engineering and Architecture Guangxi University Key Lab of Disaster Prevention and Structural Safety Guangxi Key Lab disaster {1. and Engineering Safety Nanning 530004 China college of Mathematics and Information Science Guangxi University Nanning 530004 China Department of Civil and Environmental Engineering University of California Los Angeles CA 90095-1593 USA

A polycrystalline Voronoi aggregation with a free surface is applied as the representative volume element（RVE）of the nickel-based GH41.9 *** the plastic deformation mechanism at the grain level and the Bauschinger effect,a crystal plasticity model reflecting the nonlinear kinematic hardening of crystal slipping system is *** microscopic inhomogeneous deformation during cyclic loading is calculated through numerical simulation of crystal *** deformation inhomogeneity on the free surface of the RVE under cyclic loading is described respectively by using the following parameters：standard deviation of the longitudinal strain in macro tensile direction,statistical average of first principal strains,and standard deviation of longitudinal *** relationship between the fatigue cycle number and the evolution of inhomogeneous deformation of the material’s free surface is *** research finds that：（1.The inhomogeneous deformation of the material free surface is significantly higher than that of the RVE inside;（2）the increases of the characterization parameters of inhomogeneous deformation on the free surface with cycles reflect the local maximum deformation of the RVE growing during cyclic loading;（3）these parameters can be used as criteria to assess and predict the low-cycle fatigue life rationally.

关键词： Inhomogeneous deformation Surface Grain-level Crystal plasticity Low-cycle fatigue Life prediction

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