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Initiation,organizational modes and environmental conditions of severe convective wind events during the warm season over North China

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Science China Earth Sciences 2024年第9期67卷 2876-2894页

作者： Yue HUANG Jianhua SUN Yuanchun ZHANG Ruoyun MA Xinlin YANG fuyou tian Key Laboratory of Cloud-Precipitation Physics and Severe Storms(LACS) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China University of the Chinese Academy of Sciences Beijing 100049China Earth System Modeling and Prediction Center China Meteorological AdministrationBeijing 100081China College of Aviation Meteorology Civil Aviation Flight University of ChinaGuanghan 618307China National Meteorological Center China Meteorological AdministrationBeijing 100081China

Based on the significant weather report,CG lightning,composite radar reflectivity,and ERA5 reanalysis data,we first studied the spatiotemporal distribution characteristics of four types(only severe convective wind(SCW);SCW and hail;SCW and short-duration heavy rainfall(SDHR);and SCW,hail,and SDHR)of convective weather events related to SCW during the warm season(May to September)from 2011 to 2018 in North ***,severe convective cases producing SCW were selected to statistically analyze the initiation,decay,lifetime,and organizational characteristics of convective ***,using ERA5 reanalysis data and conventional surface observation data,preconvective soundings were constructed to explore the differences in environmental conditions for initiating convective systems between SCW and *** results indicate that mixed-type of SCW and SDHR events occur more frequently over plains,while other types of convective weather occur more frequently over *** frequency peak of SCW occurs in June,while mixed convective weather peaks in *** initiation time of convective systems is concentrated between 1000 and 1300 BST,with a peak at 1200 *** mountains,the daily peaks of ordinary and significant SCW generally occur at 1700-1800 BST and 1600-1700 BST,respectively,while over plains,the peak of ordinary SCW typically lags behind that of mountains by 1-2 ***,SCW systems are mainly initiated over mountains,with most lifetimes lasting 7–13 *** convective systems produce the most SCW events,followed by trailing-stratiform convective *** convective available potential energy(CAPE),downdraft convective available potential energy,and the temperature difference between 850 and 500 hPa can all distinguish between SCW systems and non-SCW systems occurring over *** to non-SCW convective systems,SCW convective systems over mountains are more likely to occur in environments with less precipitable water,while S

关键词： Severe convective wind Convective systems Initiation Organizational modes Environmental conditions

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Warm-Season Diurnal Variations of Total, Stratiform, Convective, and Extreme Hourly Precipitation over Central and Eastern China

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Advances in Atmospheric Sciences 2019年第2期36卷 143-159页

作者： Yongguang ZHENG Yanduo GONG Jiong CHEN fuyou tian National Meteorological Centre Chinese Academy of Meteorological Sciences Wuhan Institute of Heavy Rain of China Meteorological Administration Heilongjiang Meteorological Office

Diurnal variations in amount, frequency and intensity of warm-season hourly precipitation(HP) at seven levels, which are defined as HP 0.1, 0.5, 1, 5, 10, 20 and 50 mm, are revealed based on no less than 30 years of hourly rain-gauge observations at national stations over central and eastern China(CEC). This study investigates the variations, relationships, differences and similarities of total, stratiform, convective and extreme HP over the entire CEC and various subregions. Results indicate that the variations in the amount and frequency of HP at the seven levels over the entire CEC all display a bimodal feature. For various regions, the variations of total HP mostly feature two peaks, while convective HP mainly occurs in the late afternoon and determines the diurnal variation of total HP intensity. On the basis of the primary peak time periods of HP frequency at all levels over different subregions, the variations can be classified into three main categories: late-afternoon primary peak, nocturnal primary peak, and time-shifting primary peak. However, the variations over some coastal regions like the Liaodong Peninsula, the Shandong Peninsula, and the coastal regions of Guangdong, distinctly differ from those over their corresponding larger regions. Overall, the normalized diurnal variation amplitude of amount and frequency increases with the increasing HP intensity; convective precipitation can be represented by HP 10 mm; and the intensity of HP 50 mm is slightly larger during the nighttime than during the daytime over the entire CEC. In northern China, diurnal variation in HP 5 mm can represent well that in convective precipitation.

关键词： diurnal variation total precipitation stratiform precipitation convective precipitation extreme precipitation

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融合物理理解与模糊逻辑的分类强对流客观短期预报系统:(1)系统构成

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气象 2024年第6期50卷 521-531页

作者：田付友郑永光孙建华夏坤杨波坚参扎西赤曲国家气象中心北京100081 中国科学院大气物理研究所云降水物理与强风暴重点实验室北京100029 中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室北京100029 西藏自治区气象台拉萨850000

提供准确的雷暴、短时强降水、雷暴大风和冰雹客观短期预报产品,对提高预报预警的预见期,及早采取有针对性的预防措施有重要意义。基于对四类强对流天气现象物理成因理解,给出了由国家气象中心牵头研发,融合模糊逻辑人工智能方法的分类... 详细信息

提供准确的雷暴、短时强降水、雷暴大风和冰雹客观短期预报产品,对提高预报预警的预见期,及早采取有针对性的预防措施有重要意义。基于对四类强对流天气现象物理成因理解,给出了由国家气象中心牵头研发,融合模糊逻辑人工智能方法的分类强对流客观短期概率预报系统的流程框架和实现方法,详细介绍了该系统的结构特征,以及系统中用于雷暴、短时强降水、雷暴大风和冰雹四类强对流天气预报模型构建的关键预报因子、隶属度函数获取方法和权重因子配置等信息,并在此基础上探讨了物理理解与模糊逻辑人工智能相融合方法具有广泛适用性的本质,可以表征产生特定强对流天气现象的环境配置的多样性和复杂性。

关键词：物理理解模糊逻辑人工智能分类强对流短期预报系统系统构成

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A Review of Research on Warm-Sector Heavy Rainfall in China

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Advances in Atmospheric Sciences 2019年第12期36卷 1299-1307页

作者： Jianhua SUN Yuanchun ZHANG Ruixin LIU Shenming FU fuyou tian Key Laboratory of Cloud-Precipitation Physics and Severe Storms Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science and TechnologyNanjing 210044China Beijing Municipal Weather Forecast Center Beijing 100089China National Meteorological Center China Meteorological AdministrationBeijing 100081China

Warm-sector heavy rainfall (WSHR) events in China have been investigated for many years. Studies have investigated the synoptic weather conditions during WSHR formation, the categories and general features, the triggering mechanism, and structural features of mesoscale convective systems during these rainfall events. The main results of WSHR studies in recent years are summarized in this paper. However, WSHR caused by micro- to mesoscale systems often occurs abruptly and locally, making both numerical model predictions and objective forecasts difficult. Further research is needed in three areas:(1) The mechanisms controlling WSHR events need to be understood to clarify the specific effects of various factors and indicate the influences of these factors under different synoptic background circulations. This would enable an understanding of the mechanisms of formation, maintenance, and organization of the convections in WSHR events.(2) In addition to South China, WSHR events also occur during the concentrated summer precipitation in the Yangtze River-Huaihe River Valley and North China. A high spatial and temporal resolution dataset should be used to analyze the distribution and environmental conditions, and to further compare the differences and similarities of the triggering and maintenance mechanisms of WSHR events in different regions.(3) More studies of the mechanisms are required, as well as improvements to the model initial conditions and physical processes based on multi-source observations, especially the description of the triggering process and the microphysical parameterization. This will improve the numerical prediction of WSHR events.

关键词： warm-sector heavy rainfall synoptic weather conditions triggering mechanism South China

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Cloud services with big data provide a solution for monitoring and tracking sustainable development goals

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Geography and Sustainability 2020年第1期1卷 25-32页

作者： Bingfang Wu fuyou tian Miao Zhang Hongwei Zeng Yuan Zeng State Key Laboratory of Remote Sensing Science Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100101China University of Chinese Academy of Sciences Beijing 10049China

To achieve the Sustainable Development Goals(SDGs),high-quality data are needed to inform the formulation of policies and investment decisions,to monitor progress towards the SDGs and to evaluate the impacts of ***,the data landscape is *** emerging big data and cloud-based services,there are new opportunities for data collection,influencing both official data collection processes and the operation of the programmes they *** paper uses cases and examples to explore the potential of crowdsourcing and public earth observation(EO)data products for monitoring and tracking the *** paper suggests that cloud-based services that integrate crowdsourcing and public EO data products provide cost-effective solutions for monitoring and tracking the SDGs,particularly for low-income *** paper also discusses the challenges of using cloud services and big data for SDG *** and quality control of public EO data is very important;otherwise,the user will be unable to assess the quality of the data or use it with confidence.

关键词： Big data Cloud services SDGs Monitoring

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A Synthesizing Land-cover Classification Method Based on Google Earth Engine: A Case Study in Nzhelele and Levhuvu Catchments, South Africa

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Chinese Geographical Science 2020年第3期30卷 397-409页

作者： ZENG Hongwei WU Bingfang WANG Shuai MUSAKWA Walter tian fuyou MASHIMBYE Zama Eric POONA Nitesh SYNDEY Mavengahama State Key Laboratory of Remote Sensing Science Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100101China University of Chinese Academy of Sciences Beijing 100049China State Key Laboratory of Earth Surface Proc-esses and Resource Ecology Faculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China Department of Town and Regional Planning University of JohannesburgJohannesburg 2028South Africa Department of Geography and Envi-ronmental Studies Stellenbosch UniversityStellenbosch 7600South Africa Department of Crop Science Faculty of Natural and Agricultural SciencesNorth West UniversityMmabatho 2745South Africa

This study designed an approach to derive land-cover in the South Africa with insufficient ground samples, and made a case demonstration in Nzhelele and Levhuvu catchments, South Africa. The method was developed based on an integration of Landsat 8, Sentinel-1, and Shuttle Radar Topography Mission(SRTM) Digital Elevation Model(DEM), and the Google Earth Engine(GEE) platform. Random forest classifier with 300 trees is employed as land-cover classification model. In order to overcome the defect of insufficient ground data, the stratified sampling method was used to generate the training and validation samples from the existing land-cover product. Likewise, in order to recognize different land-cover categories, the percentile and monthly median composites were employed to expand input metrics of random forest classifier. Results showed that the overall accuracy of the land-cover of Nzhelele and Levhuvu catchments, South Africa in 2017–2018 reached to 76.43%. Three important results can be drawn from our research. 1) The participation of Sentinel-1 data can slightly improve overall accuracy of land-cover while its contribution on land-cover classification varied with land types. 2) Under-fitting problem was observed in the training of non-dominant land-cover categories using the random sampling, the stratified sampling method is recommended to make sure the classification accuracy of non-dominant classes. 3) When related reflectance bands participated in the training process, individual Normalized Difference Vegetation index(NDVI), Enhanced Vegetation Index(EVI), Soil Adjusted Vegetation Index(SAVI), Normalized Difference Built-up Index(NDBI) have little effect on final land-cover classification result.

关键词： land-cover classification random forest percentile composite Landsat 8 Sentinel-1 Google Earth Engine(GEE)

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Detecting the linkage between arable land use and poverty using machine learning methods at global perspective

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Geography and Sustainability 2022年第1期3卷 7-20页

作者： fuyou tian Bingfang Wu Hongwei Zeng Gary R Watmough Miao Zhang Yurui Li State Key Laboratory of Remote Sensing Science Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100101China University of Chinese Academy of Sciences Beijing 100049China School of Geosciences University of EdinburghEH89XP EdinburghUnited Kingdom Institute of Geographic Sciences and Natural Resources Research Chinese Academy of SciencesBeijing 100101China Key Laboratory of Regional Sustainable Development Modelling Chinese Academy of SciencesBeijing 100101China

Eradicating extreme poverty is one of the UN’s primary sustainable development goals(SDG).Arable land is related to eradicating poverty(SDG1)and hunger(SDG2).However,the linkage between arable land use and poverty reduction is ambiguous and has seldom been investigated *** indicators of agricultural inputs,crop intensification and extensification were used to explore the relationship between arable land use and ***-parametric machine learning methods were used to analyze the linkage between agriculture and poverty at the global scale,including the classification and regression tree(CART)and random forest *** found that the yield gap,fertilizer consumption and potential cropland ratio in protected areas correlated with *** countries usually had a ratio of actual to potential yield less than 0.33 and fertilizer consumption less than 7.31 kg/***,crop extensification,intensification and agricultural inputs were related to poverty at the global level.

关键词： Arable land use Poverty Machine learning Yield gap Random forest

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Challenges and opportunities in remote sensing-based crop monitoring: a review

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National Science Review 2023年第4期10卷 203-219页

作者： Bingfang Wu Miao Zhang Hongwei Zeng fuyou tian Andries B Potgieter Xingli Qin Nana Yan Sheng Chang Yan Zhao Qinghan Dong Vijendra Boken Dmitry Plotnikov Huadong Guo Fangming Wu Hang Zhao Bart Deronde Laurent Tits Evgeny Loupian State Key Laboratory of Remote Sensing Science Aerospace Information Research Institute Chinese Academy of Sciences School of Resources and Environment University of Chinese Academy of Sciences Executive Committee of Group on Earth Observations Global Agricultural Monitoring (GEOGLAM) Queensland Alliance for Agriculture and Food Innovation The University of Queensland Department of Remote Sensing Flemish Institute of Technological Research Department of Geography and Earth Science University of Nebraska-Kearney Department of Satellite Monitoring Technologies Space Research Institute of Russian Academy of Sciences

Building a more resilient food system for sustainable development and reducing uncertainty in global food markets both require concurrent and near-real-time and reliable crop information for decision ***-driven crop monitoring has become a main method to derive crop information at local, regional,and global scales by revealing the spatial and temporal dimensions of crop growth status and ***, there is a lack of quantitative, objective, and robust methods to ensure the reliability of crop information, which reduces the applicability of crop monitoring and leads to uncertain and undesirable consequences. In this paper, we review recent progress in crop monitoring and identify the challenges and opportunities in future efforts. We find that satellite-derived metrics do not fully capture determinants of crop production and do not quantitatively interpret crop growth status; the later can be advanced by integrating effective satellite-derived metrics and new onboard sensors. We have identified that ground data accessibility and the negative effects of knowledge-based analyses are two essential issues in crop monitoring that reduce the applicability of crop monitoring for decisions on food security. Crowdsourcing is one solution to overcome the restrictions of ground-truth data accessibility. We argue that user participation in the complete process of crop monitoring could improve the reliability of crop *** users to obtain crop information from multiple sources could prevent unconscious ***, there is a need to avoid conflicts of interest in publishing publicly available crop information.

关键词： crop monitoring crop condition crop production Ground data Remote Sensing

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学党史跟党走干事业献青春

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城市公共交通 2021年第12期282卷 10-11页

作者：田富友哈尔滨交通集团公共交通有限公司

今年是中国共产党建党100周年,是国企改革三年行动关键之年,在市委、市政府和集团公司的领导下,哈尔滨公交公司团结带领全体员工,面对后疫情时代严峻的企业外部环境,解放思想,转变观念,克服困难,直面挑战,在危机中育新机,于变局中开新局... 详细信息

今年是中国共产党建党100周年,是国企改革三年行动关键之年,在市委、市政府和集团公司的领导下,哈尔滨公交公司团结带领全体员工,面对后疫情时代严峻的企业外部环境,解放思想,转变观念,克服困难,直面挑战,在危机中育新机,于变局中开新局,结合党史学习教育,开展服务质量提升年专项行动、我为群众办实事实践活动、“四强四提四创”活动、“转作风、强服务、树形象”活动、整治“假把式、软把式、歪把式”不良作风专项整治行动。

关键词：国企改革企业外部环境公交公司服务质量提升解放思想转变观念不良作风

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共青团做好青年思想政治工作的几点体会

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城市公共交通 2019年第11期 7-8页

作者：田富友哈尔滨交通集团公共交通有限公司

新时代共青团思想政治工作要以习近平新时代中国特色社会主义思想为指引,团结带领广大青年坚定不移跟党走,积极投身实现中华民族伟大复兴的宏伟事业,不辜负党的期望、人民的期待、民族的重托。1努力做好青年政治思想引导工作共青团组织... 详细信息

新时代共青团思想政治工作要以习近平新时代中国特色社会主义思想为指引,团结带领广大青年坚定不移跟党走,积极投身实现中华民族伟大复兴的宏伟事业,不辜负党的期望、人民的期待、民族的重托。1努力做好青年政治思想引导工作共青团组织对团员青年实施正确的思想引导是团组织的基本任务,是团组织思想性、政治性的集中体现。大力开展好青年政治思想引导工作是党对共青团组织的基本要求,必须站在党的事业薪火相传的高度予以重视。

关键词：习近平新时代中国特色社会主义思想共青团组织青年思想政治工作共青团思想政治工作思想引导几点体会团员青年薪火相传

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