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An Evaluation of Tropical Cyclone Genesis Forecast over the Western North Pacific and the South China Sea from the CMA-TRAMS

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Journal of Tropical Meteorology 2024年第1期30卷 20-28页

作者：李梦婕陈子通戴光丰田群梁卓轩林青张艳霞 Guangzhou Institute of Tropical and Marine Meteorology/guangdong provincial key laboratory of regional numerical weather prediction CMAGuangzhou 510641 China State key laboratory of Severe weather Chinese Academy of Meteorological SciencesBeijing 100081 China guangdong Meteorological Observatory Guangzhou 510641 China

Tropical cyclone(TC) genesis forecasting is essential for daily operational practices during the typhoon season.The updated version of the Tropical regional Atmosphere Model for the South China Sea(CMA-TRAMS) offers forecasters reliable numerical weather prediction(NWP) products with improved configurations and fine resolution. While traditional evaluation of typhoon forecasts has focused on track and intensity, the increasing accuracy of TC genesis forecasts calls for more comprehensive evaluation methods to assess the reliability of these predictions. This study aims to evaluate the effectiveness of the CMA-TRAMS for cyclogenesis forecasts over the western North Pacific and South China Sea. Based on previous research and typhoon observation data over five years, a set of localized, objective criteria has been proposed. The analysis results indicate that the CMA-TRAMS demonstrated superiority in cyclogenesis forecasts, predicting 6 out of 22 TCs with a forecast lead time of up to 144 h. Additionally, over 80% of the total could be predicted 72 h in advance. The model also showed an average TC genesis position error of 218.3 km, comparable to the track errors of operational models according to the annual evaluation. The study also briefly investigated the forecast of Noul(2011). The forecast field of the CMA-TRAMS depicted thermal and dynamical conditions that could trigger typhoon genesis, consistent with the analysis field. The 96-hour forecast field of the CMA-TRAMS displayed a relatively organized threedimensional structure of the typhoon. These results can enhance understanding of the mechanism behind typhoon genesis,fine-tune model configurations and dynamical frameworks, and provide reliable forecasts for forecasters.

关键词： CMA-TRAMS cyclogenesis numerical weather prediction tropical cyclone

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Combinatorial Optimization of Physics Parameterization Schemes for Typhoon Simulation Based on a Simple Genetic Algorithm(SGA)

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Journal of Meteorological Research 2024年第1期38卷 10-26页

作者： Zebin LU Jianjun XU Zhiqiang CHEN Jinyi YANG Jeremy Cheuk-Hin LEUNG Daosheng XU Banglin ZHANG China Meteorological Administration–guangdong Ocean University Joint laboratory for Marine Meteorology South China Sea Institute of Marine MeteorologyGuangdong Ocean UniversityZhanjiang 524088 College of Ocean and Meteorology Guangdong Ocean UniversityZhanjiang 524088 Guangzhou Institute of Tropical and Marine Meteorology/guangdong provincial key laboratory of regional numerical weather prediction China Meteorological AdministrationGuangzhou 510640 Shenzhen Institute of guangdong Ocean University Shenzhen 518120 College of Atmospheric Science Lanzhou UniversityLanzhou 730000

Each physical process in a numerical weather prediction(NWP)system may have many different parameterization schemes.Early studies have shown that the performance of different physical parameterization schemes varies with the weather situation to be simulated.Thus,it is necessary to select a suitable combination of physical parameterization schemes according to the variation of weather systems.However,it is rather difficult to identify an optimal combination among millions of possible parameterization scheme combinations.This study applied a simple genetic algorithm(SGA)to optimizing the combination of parameterization schemes in NWP models for typhoon forecasting.The feasibility of SGA was verified with the simulation of Typhoon Mujigae(2015)by using the weather Research and Forecasting(WRF)model and Typhoon Higos(2020)by using the Coupled Ocean–Atmosphere–Wave–Sediment Transport(COAWST)modeling system.The results show that SGA can efficiently obtain the optimal combination of schemes.For Typhoon Mujigae(2015),the optimal combination can be found from the 1,304,576 possible combinations by running only 488 trials.Similar results can be obtained for Typhoon Higos(2020).Compared to the default combination proposed by the COAWST model system,the optimal combination scheme significantly improves the simulation of typhoon track and intensity.This study provides a feasible way to search for the optimal combinations of physical parameterization schemes in WRF and COAWST for more accurate typhoon simulation.This can help provide references for future development of NWP models,and for analyzing the coordination and adaptability of different physical process parameterization schemes under specific weather backgrounds.

关键词： simple genetic algorithm(SGA) combinatorial optimization typhoon forecast numerical weather prediction(NWP)

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The main strategies for soil pollution apportionment:A review of the numerical methods

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Journal of Environmental Sciences 2024年第2期136卷 95-109页

作者： Bin Shi Jing Meng TieyuWang Qianqian Li Qifan Zhang Guijin Su Research Center for Eco-Environmental Sciences Chinese Academy of SciencesBeijing 100085China University of Chinese Academy of Sciences Beijing 100049China guangdong provincial key laboratory of Marine Disaster prediction and Prevention Shantou UniversityShantou 515063China

Nowadays,a large number of compounds with different physical and chemical properties have been determined in soil.Environmental behaviors and source identification of pollutants in soil are the foundation of soil pollution control.Identification and quantitative analysis of potential pollution sources are the prerequisites for its prevention and control.Many efforts have made to develop methods for identifying the sources of soil pollutants.These efforts have involved the measurement of source and receptor parameters and the analysis of their relationships via numerical statistics methods.We have comprehensively reviewed the progress made in the development of source apportionment methodologies to date and present our synthesis.The numerical methods,such as spatial geostatistics analysis,receptor models,and machine learning methods are addressed in depth.In most cases,however,the effectiveness of any single approach for source apportionment remains limited.Combining multiple methods to address soil quality problems can reduce uncertainty about the sources of soil pollution.This review also constructively highlights the key strategies of combining mathematical models with the assessment of chemical profiles to provide more accurate source attribution.This review intends to provide a comprehensive summary of source apportionment methodologies to help promote further development.

关键词： Soil pollutants Source attribution Methodologies Chemical profiles Mathematical models

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Preliminary Model Study for Forecasting a Hot weather Process in guangdong Province Using CMA-TRAMS

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Atmospheric and Climate Sciences 2024年第1期14卷 101-117页

作者： Wenfan Wang Jiemin Zhan Dehui Chen Zitong Chen Yanxia Zhang Qing Fan Guangfeng Dai Yingying Luo Aifen Ye Department of Applied Mechanics and Engineering Shenzhen Campus of Sun Yat-sen University Shenzhen Guangdong China Guangzhou Institute of Tropical and Marine Meteorology/guangdong provincial key laboratory of regional numerical weather prediction CMA Guangzhou China

In this paper, the CMA-TRAMS tropical high-resolution system was used to forecast a typical hot weather process in guangdong, China with different horizontal resolutions and surface coverage. The results of resolutions of 0.02° and 0.06° were presented with the same surface coverage of the GlobeLand30 V2020, companies with the results of resolution 0.02° with the USGS global surface coverage. The results showed that, on the overall assessment the 2 km model performed better in forecasting 2 m temperature, while the 6 km model was more accurate in predicting 10 m wind speed. In the evaluation of representative stations, the 2 km model performed better in forecasting 2 m temperature and 2 m relative humidity at the coastal stations, and the 2 km model was also better in forecasting 2 m pressure at the representative stations. However, the 6 km model performed better in forecasting 10 m wind speed at the representative stations. Furthermore, the 2 km model, owing to its higher horizontal resolution, presented a more detailed stratification of various meteorological field maps, allowing for a more pronounced simulation of local meteorological element variations. And the use of the surface coverage data of the GlobeLand30 V2020 improved the forecasting of 2 m temperature, and 10 m wind speed compared to the USGS surface coverage data.

关键词： High-Resolution numerical Model CMA-TRAMS Model Test Evaluation Surface Coverage numerical Simulation

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Sub-Seasonal Predictability of the Northeast China Cold Vortex in BCC and ECMWF S2S Model Forecasts for 2006–2021

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Journal of Meteorological Research 2024年第3期38卷 453-468页

作者： Yiqiu YU Jie WU Yihe FANG Chunyu ZHAO Zongjian KE Yitong LIN Liaoning provincial Climate Centre Liaoning Provincial Meteorological Administration key Opening laboratory for Northeast China Cold Vortex Research China Meteorological Administration Panjin National Climate Observatory China Meteorological Administration key laboratory for Climate prediction Studies National Climate Centre China Meteorological Administration Jilin provincial Climate Centre Jilin Provincial Meteorological Administration

As an important atmospheric circulation system in the mid–high latitudes of East Asia, the Northeast China cold vortex(NCCV) substantially influences weather and climate in this region. So far, systematic assessment on the performance of numerical prediction of the NCCVs has not been carried out. Based on the Beijing Climate Centre(BCC) and the ECMWF model hindcast and forecast data that participated in the Sub-seasonal to Seasonal(S2S) prediction Project, this study systematically examines the performance of both models in simulating and forecasting the NCCVs at the sub-seasonal timescale. The results demonstrate that the two models can effectively capture the seasonal variations in the intensity, active days, and spatial distribution of NCCVs; however, the duration of NCCVs is shorter and the intensity is weaker in the models than in the observations. Diagnostic analysis shows that the differences in the intensity and location of the East Asian subtropical westerly jet and the wave train pattern from North Atlantic to East Asia may be responsible for the deficient simulation of NCCV events in the S2S models. Nonetheless, in the deterministic forecasts, BCC and ECMWF provide skillful prediction on the anomalous numbers of NCCV days and intensity at a lead time of 4–5(5–6) pentads, and the skill limit of the ensemble mean is 1–2 pentads longer than that of individual members. In the probabilistic forecasts of daily NCCV activities, BCC and ECMWF exhibit a forecasting skill of approximately 7 and 11 days, respectively; both models show seasonal dependency in the simulation performance and forecast skills of NCCV events, with better performance in winter than in summer.The results from this study provide helpful references for further improvement of the S2S prediction of NCCVs.

关键词： Northeast China cold vortex (NCCV) predictability sub-seasonal to seasonal (S2S) prediction deterministic forecast probabilistic forecast

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Spin-polarized pairing induced by the magnetic field in the Bernal bilayer graphene

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Chinese Physics B 2024年第4期33卷 650-654页

作者：黄妍周涛 guangdong Basic Research Center of Excellence for Structure and Fundamental Interactions of Matter Guangdong Provincial Key Laboratory of Quantum Engineering and Quantum MaterialsSchool of PhysicsGuangdong-Hong Kong Joint Laboratory of Quantum Matterand Frontier Research Institute for PhysicsSouth China Normal UniversityGuangzhou 510006China

Recent experimental findings have demonstrated the occurrence of superconductivity in Bernal bilayer graphene when induced by a magnetic field.In this study,we conduct a theoretical investigation of the potential pairing symmetry within this superconducting system.By developing a theoretical model,we primarily calculate the free energy of the system with p+ip-wave parallel spin pairing,p+ip-wave anti-parallel spin pairing and d+i d-wave pairing symmetry.Our results confirm that the magnetic field is indeed essential for generating the superconductivity.We discover that the p+ip-wave parallel spin pairing leads to a lower free energy for the system.The numerical calculations of the energy band structure,zero-energy spectral function and density of states for each of the three pairing symmetries under consideration show a strong consistency with the free energy results.

关键词： superconductivity magnetic field induction pairing symmetry Bernal bilayer graphene

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numerical Investigation on Heat Transfer Characteristics of Microencapsulated Phase Change Material Slurry in a Rectangular Minichannel

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Journal of Thermal Science 2024年第2期33卷 564-577页

作者： WANG Zhibin LI Zilong JIA Lisi DING Bin CHEN Ying School of Materials and Energy Guangdong University of TechnologyGuangzhou510006China guangdong provincial key laboratory of Functional Soft Condensed Matter Guangzhou510006China College of New Energy China University of Petroleum(East China)Qingdao266580China

Microencapsulation phase change material slurry(MEPCMS) becomes a potential working fluid for cooling high energy density miniaturized components,thanks to the latent heat absorption of particles in the heat transfer process.In this work,the Discrete Phase Model(DPM) based on the Euler-Lagrangian method is used to numerically investigate the convective heat transfer characteristics of MEPCMS flowing through a rectangular minichannel with constant heat flux.The results show that particles of MEPCMS are mainly subjected to drag force during the flow.Even so,they can migrate from the high-temperature region to the low-temperature region driven by the thermophoretic force,affecting the particle distribution and phase change process.Moreover,the Nux of the MEPCMS fluctuates due to particle phase change with varying specific heat capacities.Specifically,the value increases first,then decreases,and eventually increases again until it approaches the fully developed value of the pure base fluid as the particles gradually melt.Furthermore,the heat transfer performance of the MEPCMS is influenced by the combination of fluid inlet temperature fluid inlet velocity(v),and mass concentration(c_(m)) of MEPCM particles.The result shows that the maximum reduction of the maximum bottom wall temperature difference(ΔT_(w)) is 23.98% at T_(in)=293.15 K,v=0.15 m·s^(-1),c_(m)=10%.

关键词： Microencapsulated Phase Change Material Slurry(MPCMS) Discrete Phase Model(DPM) particle-fluid interaction force minichannel heat sink thermophoresis

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A Neural-network-based Alternative Scheme to Include Nonhydrostatic Processes in an Atmospheric Dynamical Core

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Advances in Atmospheric Sciences 2024年第6期41卷 1083-1099,I0002,I0003页

作者： Yang XIA Bin WANG Lijuan LI Li LIU Jianghao LI Li DONG Shiming XU Yiyuan LI Wenwen XIA Wenyu HUANG Juanjuan LIU Yong WANG Hongbo LIU Ye PU Yujun HE Kun XIA Ministry of Education key laboratory for Earth System Modeling and Department of Earth System ScienceTsinghua UniversityBeijing 100084China State key laboratory of numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Innovation Group 311020008 Southern Marine Science and Engineering Guangdong LaboratoryZhuhai 519000China Shanghai Ecological Forecasting and Remote Sensing Center Shanghai 200030China key laboratory of Earth System Modeling and prediction China Meteorological AdministrationBeijing 100081China College of Ocean Sciences University of Chinese Academy of SciencesBeijing 100049China

Here,a nonhydrostatic alternative scheme(NAS)is proposed for the grey zone where the nonhydrostatic impact on the atmosphere is evident but not large enough to justify the necessity to include an implicit nonhydrostatic solver in an atmospheric dynamical core.The NAS is designed to replace this solver,which can be incorporated into any hydrostatic models so that existing well-developed hydrostatic models can effectively serve for a longer time.Recent advances in machine learning(ML)provide a potential tool for capturing the main complicated nonlinear-nonhydrostatic relationship.In this study,an ML approach called a neural network(NN)was adopted to select leading input features and develop the NAS.The NNs were trained and evaluated with 12-day simulation results of dry baroclinic-wave tests by the weather Research and Forecasting(WRF)model.The forward time difference of the nonhydrostatic tendency was used as the target variable,and the five selected features were the nonhydrostatic tendency at the last time step,and four hydrostatic variables at the current step including geopotential height,pressure in two different forms,and potential temperature,respectively.Finally,a practical NAS was developed with these features and trained layer by layer at a 20-km horizontal resolution,which can accurately reproduce the temporal variation and vertical distribution of the nonhydrostatic tendency.Corrected by the NN-based NAS,the improved hydrostatic solver at different horizontal resolutions can run stably for at least one month and effectively reduce most of the nonhydrostatic errors in terms of system bias,anomaly root-mean-square error,and the error of the wave spatial pattern,which proves the feasibility and superiority of this scheme.

关键词： neural network nonhydrostatic alternative scheme atmospheric model dynamical core

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Investigation of Maxima Assumptions in Modelling Tropical Cyclone- Induced Hazards in the South China Sea

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China Ocean Engineering 2024年第3期38卷 491-504页

作者： WEN Ze-guo WANG Fu-ming WAN Jing YANG Fan School of Civil Engineering Sun Yat-sen University&Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)Zhuhai 519082China guangdong Academy of Safety Science and Technology Guangzhou 510060China guangdong key laboratory of Oceanic Civil Engineering Guangzhou 510275China Advanced Energy Science and Technology guangdong laboratory(Yangjiang Offshore Wind Energy laboratory) Yangjiang 529500China

The present study aims to examine the suitability of two commonly used assumptions that simplify modelling metoceanconditions for designing offshore wind turbines in the South China Sea (SCS). The first assumption assumes thatjoint N-year extreme wind and wave events can be independently estimated and subsequently combined. The secondone assumes peak wind and waves can be modelled as occurring simultaneously during a tropical cyclone (TC) event.To better understand the potential TC activity, a set of 10000 years synthetic TC events are generated. The wind fieldmodel and the Mike 21 spectral wave model are employed to model the TC-induced hazards. Subsequently, theeffect of the assumptions is evaluated by analyzing the peak structural response of both monopile and semisubmersibleoffshore wind turbines during TC events. The results demonstrate that the examined assumptions are generally accurate.By assessing the implications of these assumptions, valuable insights are obtained, which can inform andimprove the modelling of TC-induced hazards in the SCS region.

关键词： tropical cyclone numerical wave modelling hazards offshore wind turbines structural response

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A novel box-counting method for quantitative fractal analysis of threedimensional pore characteristics in sandstone

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International Journal of Mining Science and Technology 2024年第4期34卷 479-489页

作者： Huiqing Liu Heping Xie Fei Wu Cunbao Li Renbo Gao State key laboratory of Coal Mine Disaster Dynamics and Control Chongqing UniversityChongqing 400030China School of Resources and Safety Engineering Chongqing UniversityChongqing 400030China guangdong provincial key laboratory of Deep Earth Sciences and Geothermal Energy Exploitation and Utilization Shenzhen UniversityShenzhen 518060China Shenzhen key laboratory of Deep Underground Engineering Sciences and Green Energy College of Civil and Transportation EngineeringShenzhen UniversityShenzhen 518060China

Fractal theory offers a powerful tool for the precise description and quantification of the complex pore structures in reservoir rocks,crucial for understanding the storage and migration characteristics of media within these rocks.Faced with the challenge of calculating the three-dimensional fractal dimensions of rock porosity,this study proposes an innovative computational process that directly calculates the three-dimensional fractal dimensions from a geometric perspective.By employing a composite denoising approach that integrates Fourier transform(FT)and wavelet transform(WT),coupled with multimodal pore extraction techniques such as threshold segmentation,top-hat transformation,and membrane enhancement,we successfully crafted accurate digital rock models.The improved box-counting method was then applied to analyze the voxel data of these digital rocks,accurately calculating the fractal dimensions of the rock pore distribution.Further numerical simulations of permeability experiments were conducted to explore the physical correlations between the rock pore fractal dimensions,porosity,and absolute permeability.The results reveal that rocks with higher fractal dimensions exhibit more complex pore connectivity pathways and a wider,more uneven pore distribution,suggesting that the ideal rock samples should possess lower fractal dimensions and higher effective porosity rates to achieve optimal fluid transmission properties.The methodology and conclusions of this study provide new tools and insights for the quantitative analysis of complex pores in rocks and contribute to the exploration of the fractal transport properties of media within rocks.

关键词： 3D fractal analysis Fractal dimension Rock pore structure Box-counting method Permeability simulation Computational geosciences

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