所属系部:  大气物理学（Atmospheric Physics) 同时兼职：大气探测学 (Atomspheric Measurements）

毕业院校:  北京大学(博士)，中国气象科学研究院(硕士)，Concordia University(研究生)，南信大(学士)

主讲课程:  大气科学前沿研究新进展， 中小尺度天气学

研究方向:  中小尺度天气NWP和AI/DL；云雾物理和人工影响天气；气象灾害预警预报

主要研究领域:  中小尺度模拟预报；云降水和播云催化数值模拟；能源电力和航空气象预报技术

研究生招生：大气物理、大气探测和大气环境方向硕士、博士生

研究团队 (点这 >) 精细化区域地球模拟和信息中心简介。 欢迎对云降水、资料同化和AI有抱负的同学加入

成果示范 (点这 >) 访问实时模拟展示 ：庐山云雾降水和播云催化"数值孪生"模拟实验室

教育背景 (Education):  

1993-1995: National Center for Atmospheric Research (NCAR), USA, Post-Doctor

1989-1992: 北京大学 (Beijing University)，大气物理学，博士

1983-1986: 中国气象科学研究院 (CAMS/SMA)，大气物理学，理学硕士

1979-1983: 南京气象学院 （南京信息工程大学, NUIST），大气物理学，理学学士

1997-1999: Concordia University (Canada)，Computer Science, Graduate.

工作经历 (Professional Career):  

2019 － 至今，教授（博导），南京信息工程大学；科技院长，南京信大气象科学技术研究院

1999 － 2019，Project Scientist 3，National Center for Atmospheric Research（NCAR),USA

1995 － 1999，Res.Associate. McGill University, Canada

1986 － 1992，助理研究员，中国气象科学研究院

学术兼职 (Scientific Servce and honors):  

2014 - 2018，海外高层次专家，中国电力科学研究院

2021 - 至今，学术委员会委员，中国气象科学研究院

2021 - 至今，学术委员会委员，中国电工学会电力气象学会

2019 - 至今，学术委员会副主任，中国气象局人工影响天气重点实验室

2019 - 至今，中心主任，精细化区域地球模拟和信息中心，南京信息工程大学

2020 - 至今，科技院长，南京信大气象科学技术研究院

个人专长 (Work Experience and Expertise):  

1．从事云和天气数值模拟研究、模式研发和运用30年。对中小尺度天气、云和降水物理、大气边界层和地表地面层物理、大气湍流和各类强天气现象的摸拟、特别是中小尺度大气资料同化及能源、航空、减灾防灾业务应用，有深入研究。近20年里，主持或作为项目首席科学家与国内10多个国内企事业单位、美国政府、公司及其他国际多个国家政府的合作研发重大气象应用科研项目。目前核心攻关项目包括中国人工影响天气中心合作，发展新一代精细化人工影响天气数值天气模拟和预报技术。

2．作为美国国家大气科学研究中心应用研究实验室（NCAR/RAL）中、小、微尺度数值天气资料同化和预报模式研发和业务应用的首席专家，带领10多个具有博士、硕士学位的科研人员和机软件工程师，研发针对天气较为敏感的各类应用领域的气象预报和资源分析模式系统。领导发展的中、小、微尺度数值天气资料同化和预报模式技术，包括：RTFDDA：公里和次公里实时四维天气资料同化和预报系统；Ensemble-RTFDDA：云解析模式集合四维天气资料同化和和概率预报系统； RTFDDA-LES：甚高分辨率实时四维天气资料同化和大涡模拟（LES）技术； Climate-FDDA：四维资料同化和降尺度分辨率区域和局地天气再分析技术；4D-REKF：新一代无间隙四维天气集合卡曼滤波资料同化和概率预报技术；ANKF和QR-EnCalib：类聚卡曼滤波AI误差订正技术和集合预报概率校准技术。

3．该数值预报模式系统已应用于：8个美国10个地区和部门，美国、韩国和中国风能和太阳能预报和资源评估、飓风预报和模拟、法国海军微气候、以色列空军气象预报、沙特气象局业务气象预报、中东战场气象、美国反恐毒气扩散预报和城市应急、森林防火气象服务、人工影响天气、奥林匹克气象服务及西非天气预报等，广泛应用于100多个国家和地区。

4．作为国家电网公司的海外高层次特聘专家，在中国电力科学研究院创建支撑国家电网公司电力调度、特高压输电线路运行和维护、输电电网规划和新能源功率预报等的电力气象研究中心， 建立电力气象专业服务的实时业务数值天气预报系统，并培养一只电力气象专业研究人才团队。与NCAR和内蒙古气象局合作，为内蒙古电力公司发展集合风功率预报技术和业务预报系统。与中国电力投资公司新能源分公司合作，发展高分辨率精细化数值预报系统和集合风功率预报系统。

5．为深圳市气象局建立了世界一流的大城市微气候再分析数值模式系统和6年气候再分析资料库，快速更新城市精细化数值天气预报系统（RUUPPS）和快速更新城市积涝预报系统（RUUFFS）。这些先进的数值天气模式技术有力的挖掘深圳市多年发展的世界领先的四维天气观测网的使用价值，有效改进深圳市气象局城市气候服务、公众常规气象预报和灾害性天气预警的能力。

6. 近三年，指导团队师生开展了基于AI深度学习气象应用研究，包括卫星云观测3D云雷达发射率反演技术（Wang等2023）、3D辐射传输效应订正技术（Zhou等2022）、对流短临预报技术（Li等2023）、模式预报误差订正技术（Qin等2023）和边界层结构反演技术（Fan等2023）。这些技术为改进卫星、雷达资料同化技术和提升集合同化与预报能力开辟新的路径。

为下述国际学术杂志审阅论文

J. Appl. Meteor. Climate (AMS)

J. of Atmos. Sci. (AMS)

Wea. and Forecast. (AMS）

Mon. Wea. Rev. (AMS) 

JGR-Atmosphere (AGU) 

Advances in Atmos. Sci. (Chinese Academy of Science)

Atmos. Research. (Elsevier)

Wind Energy (Elsevier)

Energy and Buildings (Elsevier)

Atmospheric Research (Elsevier)

Journal of Energy

Journal of Hydrology (AMS)

Atmosphere

Remote Sensing

担任美国自然科学基金项目建议书评审

任美国气象学会“Monthly Weather Review”杂志的编委

担任美国自然科学基金评审

担任中国基金委项目评审

American Meteorological Society 美国 1994 - 成员

American GeophysicalUnion 美国 2009- 成员

European GeophysicalUnion 欧洲 2010- 成员

 

学术荣誉 (Honors and Awards):  

2015: Colorado State Governor CO-LAB Award

2012: Nominated, NCAR Year-2012 best published paper.

   (美国国家大气研究中心：2012年度最佳学术论文奖提名［集合预报和飞行气象应用］)

2011：Winner, NCAR Year-2011 Scientific and Technological Advancement Award for research 

       of the wind power forecasting system for Xcel Energy

   (美国国家大气研究中心2012年度最佳科学技术进步奖 ［风能预报技术研发］)

2006：Nominated, NCAR for Scientific and Technological Advancement Award for development 

       of a multi-scale weather system for the state critical facilities

   (美国国家大气研究中心2012年度最佳科学技术进步奖提名［国家重大设施气象之盾系统研发］)

2005：NASA Aviation Safety Program (NASP) Extraordinary Contribution Award for incorporating 

       and study TAMDAR data in mesoscale NWP

   (美国航天局NASA航空安全计划特殊贡献奖 ［机载气象仪器对气象预报运用］)

2001：Winner, NCAR Year-2001 Scientific and Technological Advancement Award for developing

        the 4-Dimensional Weather (4DWX) system

   (荣获美国国家大气研究中心2001年度最佳科学技术进步奖［发展国家重大试验基地四维天气系统］)

1994：2nd Prize, National Natural Science Council of China for advancements on severe 

       convection modeling study

   (中国国家气象局科学进步 2等奖［强对流数值模式研发和摸拟］)

1993：China Scientific Achievement Award, 2nd Rank for significant progress on the Northern

        China rain enhancement field research

   (中国国家科学进步2等奖［北方层壮云物理和人工降雨潜力研究］)

1992：1st Class Scientific Achievement Award, Natural Science Foundation of China for significant 

      progress on the Northern China rain enhancement field research

   (中国国家气象局科学进步1等奖［北方层壮云物理和人工降雨潜力研究］)

1990：Beijing University Overseas "Guanghua" award for academic achievement on an outstanding 

     paper during Ph.D graduate study

   (北京大学海外“光华”奖［在读博士期间 优秀学术论文奖］)

  

近期科研项目 (Sci. and Tech. R&D Projects):  

2024年 - 2027年, 基金委：多频双偏振雷达和FY-4短波通道云和降水资料同化关键技术研究，PI

2023年 - 2027年, 科技部重大研发：暖云催化技术研究，课题负责人

2020年 - 2024年,乌鲁木齐机场空管工程数值预报系统及应用平台，PI

2020年 - 2021年,飞行高影响天气气象环境仿真系统，PI

2019年 - 2022年, 广泛互联的“天-地-网”气象观测及数据融合技术研究，课题负责人

2019年 - 2021年, 风电场风和功率集合预报技术研究, 首席科学家，主持（PI）

2019年 - 2021年, 西北人影工程建设人影四维资料同化和预报系统，主持（PI）

2019年 - 2021年,河北气象局环境气象中心环境气象数值预报，主持（PI）

2019年 - 2020年, 深圳市气象局FDDA实时天气分析、QPE和积涝预报，主持（PI）

2017年 - 2020年,中国电力投资有限公司风电场功率预报，主持（PI）

1999年 - 2018年,美国重要测试基地气象预报，数值模式研发首席科学家

2006年 - 2017年, PWS TAMDAR and NWP 长期合作项目，主持 （PI）

2009年 - 2016年, Xcel Energy Inc.：风能预报, CO-PI, 数值模式研发课题负责人

2009年 - 2017年, 以色列空军数值天气预报系统(MAGEN), 首席科学家（PI）

2012年－2018年,集合四维资料同化和概率预报和气候再分析。主持（PI）

2013年 - 2019年,中国深圳市气象局：四维资料同化微气候和资源分析；主持（PI）

2018年 - 2019年,内蒙古电力公司风电场功率预报，主持（PI）

2012年 - 2014年,沙特阿拉伯气象局业务数值天气预报系统，首席科学家

2011年 - 2013年,韩国气象局: 风能预报（共3期项目），主持（PI）

2008年 - 2010年, 以色列水文局：季节降雨预报, 主持（PI）

2007年 - 2009年, UCAR西非数值天气预报演示系统, 主持（PI）

发明专利成果:  

·      一种人工影响天气的作业效果评估办法。ZL 2021 1 0337598.3 

·      基于PSO-GRNN风电场风机缺损风速值填充办法 ZL 2015 1 0443853.7

·      一种风场临近多台风电机测量风速缺损值的组合填充系统 ZL 2014 1 0484067.7

科学论文 (Publications):

      2024

Li Y., Liu* Y., Shi Y., Chen B., Zeng F., Huo Z. and Fan H., 2024: Probablistic convective initiation nowcasting using Himawari-8 AHI with explanable deep learning models. Mon. Wea. Rev., 152 (1), 363-385. DOI: 10.1175/MWR-D-22-0216.1 

Qin, Y., Wang, F., Liu*, Y., Fan H., Zhou Y. and Duan J., 2024: Research on Three-Dimensional Cloud Structure Retrieval and Fusion Technology for the MODIS Instrument. Remote Sensing, 2024, 16 (9), 1561; https://doi.org/10.3390/rs16091561

Yang,J., Huang,S., Zhang Q., Jing,X., Deng, Y., and Liu*, Y., 2024: Impact of ice multiplication on the cloud electrification of a cold-season thunderstorm: a numerical case study. Atmos. Chem. Phys., 24, 5989-6010, 2024.04,  https://doi.org/10.5194/egusphere-2023-2188.

Yan L, Zhou Y, Wu Y, Cai M, Peng C, Song C, Liu S, Liu Y.,2024, FY-4A Measurement of cloud-seeding effect and validation of a catalyst T&D algorithm. Atmosphere. 2024; 15(5):556. https://doi.org/10.3390/atmos15050556

Yuan G., Ding R., Liu*, Y., Zhang L., Xu. H., 2024:  The Effects of Land Use and Land Cover Changes on the Land Surface Temperature Over Northeast China, Advances in Meteorology. Volume 2024, Article ID 3737920, 14 pages, https://doi.org/10.1155/2024/3737920.

2023

Zhou Y., and Liu* Y., Han Wei, 2023: Demonstrating the potential impact of assimilating FY-4 visible radiances on forecasts of cloud and precipitation with a localized particle filter. Mon. Wea. Rev.，151 (5), 1167-1188. DOI：10.1175/MWR-D-22-0133.1

Wang F., Liu* Y., Zhou Y., Sun* R., Duan J., Li Y., Ding Q., Wang H., 2023: Retrieving vertical cloud radar reflectivity from MODIS cloud products with CGAN: An evaluation for different cloud types and latitudes. Remote Sensing, 2023, 15, 816. https://doi.org/ 10.3390/rs15030816.

Huo, Z., Liu* Y., Shi Y., Chen B., Li Y., and Fan H., 2023: An investigation on joint data assimilation of a radar network and ground-based profiling platforms for forecasting convective storms. Mon. Wea. Rev.，151 (8), 2049-2064. DOI:10.1175/MWR-D-22-0332.1

Sun R., Ding Q., Fan X., Ding R., Xu H., Liu Y., Li P., Zhang H. and Li E., 2023: Microclimate Analysis of the High-Impact Weather for the Power Grid Operation in the Jibei Region of China. Energies, 2023, 16 (12), 1-17.

Hua S., Chen* B., Liu* Y., Chen G., Yang Y., Dong X., Zhao Z., Gao Y., Zhou X., Zhong R. and Duan J., 2023: Evaluation of the ice particle simulation of microphysics schemes with aircraft measurements of a stratiform cloud in North China. J. Atmos. Sci., 80 (6), 1635-1656.  DOI:10.1175/JAS-D-22-0155.1。

Shu Z., Zhao T., Chen,Y., Liu,Y., Yang,F., Jiang Y., He,G., Yang,Q., and Zhang, Y., 2023: Terrain effect on atmospheric process in seasonal ozone variation over the Sichuan Basin, Southwest China. Environmental Pollution. 2023.12. 338， https://doi.org/10.1016/j.envpol.2023.122622.

Li Y., Liu* Y., Sun R., Guo F., Xu X., and Xu H, 2023: Convective storm VIL and lightning nowcasting using satellite and weather radar measurements based on multi-task learning models. Advances in Atmospheric Sciences.  40 (5), 887-899. doi: 10.1007/s00376-022-2082-6.

Yuan G., Zhang Y., Li E. and Liu* Y., 2023: Effects of different land use types on soil surface temperature in the Heihe River Basin. Sustainability. 15, 3859. https://doi.org/10.3390/su15043859.

Fan H., Liu* Y., Li Y., Liu Yue., Duan J., Li L., Z. Huo, 2023: A deep learning method for predicting lower troposphere temperature using surface analysis. Atmospheric Research. 283, 1 March 2023. http://doi.org/10.1016/j.atmosres.2022.106542.

Qin Y., Liu* Y., Jiang X., Li Y., Xu H., Shi Y. and Huo Z.,2023: Grid-to-Point Deep-Learning Error Correction for the Surface Weather Forecasts of a Fine-Scale Numerical Weather Prediction System. Atmosphere, 14,145. 9 Jan. 2023. https://doi.org/10.3390/atmos14010145.

张依鸣，刘玉宝*，王昊亮，孙荣富、樊小伟，2023: GSI-3DVAR背景场误差协方差水平相关特征尺度对地面气象站资料同化适应性研究。气象科学 , 43 (3), 370-383。DOI:10.12306/2022jms.0020

2022

Wang H., Yuan S., Liu* Y., Li Y., 2022:  Comparison of the WRF-FDDA-Based Radar Reflectivity and Lightning Data Assimilation for Short-Term Precipitation and Lightning Forecasts of Severe Convection.. Remote Sens. 2022, 14, 5980. https://doi.org/10.3390/ rs14235980.

Zhou* Y., Liu* Y., Huo Z. and Li Y., 2022: Preliminary evaluation of FY-4A visible radiance data assimilation by the WRF/DART-RTTOV system for a tropical storm case. Geosci. Model Dev., 15, 7397–7420, 2022 https://doi.org/10.5194/gmd-15-7397-2022.

Lu Z., Han* Y., Liu* Y., Liu S., Liu Z., Tang Y., and Jing W., 2022:  An improvement of wind gust estimate (WGE) method for squall lines. Geomatics, Natural Hazards and Risk.13 (1), 993-1013, DOI: 10.1080/19475705.2022.2064773.

Wen W., Liu* Y., Sun R., and Liu Yue, 2022:  Research on Anomaly Detection of Wind Farm SCADA Wind Speed Data.  Energies, 2022, 15, 5869. https://doi.org/10.3390/en15165869

Wang H., Liu* Y., Duan J., Shi Y., Lou X. and Li J., 2022:  Assimilation of Radar Reflectivity Using A Time-Lagged Ensemble Based Ensemble Kalman Filter With “Cloud-Dependent” Background Error Covariances. JGR- Atmosphere. 127 (10),  https://doi.org/10.1029/2021JD036207

Yuan G., Tang W. , Zuo T., Li E., Zhang L., Liu* Y., 2022: Impacts of afforestation on land surface temperature in different regions of China. Agricultural and Forest Meteorology.18 (2022) 108901. https://doi.org/10.1016/j.agrformet.2022.108901. 

Sun, H.; Wang, H.; Yang, J.; Zeng, Y.; Zhang, Q.; Liu, Y.; Gu, J.; Huang, S. , 2022: Improving Forecast of Severe Oceanic Mesoscale Convective Systems Using FY-4A Lightning Data Assimilation with WRF-FDDA. Remote Sensing, 2022,14,1965. https:// doi.org/10.3390/rs14091965 

Yang J., Liu E., Liu* Y. , Lin Y.,  Jin X., 2022:   Impact of vertical wind shear on summer orographic clouds over Tian Shan Mountians: A case study based on radar observation and  numerical simulation.  Remote Sensing, 2022, 14, 1583. https://doi.org/10.3390/ rs14071583 .

Shi J.; Liu* Y., Li Y., Liu Yue., Roux G., Shi L., Fan X.,2022: Wind Speed Forecasts of a Mesoscale Ensemble for Large-Scale Wind Farms in Northern China: Downscaling Effect of Global Model Forecasts. Energies 2022,15,896. https://doi.org/ 10.3390/en15030896.

Shu Z., Zhao T., Liu Y., Zhang L., Ma X., Kuang X., Li Y., Huo Z., Ding Q., Sun X., Shen L., 2022: Impact of deep basin terrain on PM2.5 distribution and its seasonality over the Sichuan Basin, Southwest China. Environmental Pollution. 300, 118933-118944. https://doi.org/10.1016/j.envpol.2022.118944.

Wang, H.; Liu*, Y.; Liu, Y.; Cao, Y.; Liang, H.; Hu, H.; Liang, J.; Tu, M.，2022: Assimilation of GNSS PWV with NCAR-RTFDDA to Improve Prediction of a Landfall Typhoon. Remote Sens.2022,14,178. https:// doi.org/10.3390/rs14010178。

袁锦涵, 周永波, 刘玉宝*, 段婧, 王新, 2022. 云滴谱分布对FY-4A/AGRI水云光学厚度与有效粒子半径反演的影响研究[J], 光学学报, 42(6), 2022.3. doi:10.3788/AOS202242.0628004 

熊一帆，丁秋冀，舒卓智，刘玉宝*，赵天良, 2022: 基于数值模拟与资料同化探究长三角地区冬 季 PM2.5 污染过程的气象影响. 环境科学学报(J), 42(4),293-303. DOI:10.13671/j.hjkxxb.2022.0004

He G.; Yuan G.; Liu* Y.; Jiang Y.; Liu Y.; Shu Z.; Ma X.; Li Y., Huo Z.，2022: The Effects of Topography and Urban Agglomeration on the Sea Breeze Evolution over the Pearl River Delta Region. Atmosphere 2022, 13, 39. https://doi.org/10.3390/atmos13010039

2021

Shu  Z., Liu* Y., Zhao T., et al., 2021: Long-term variations in aerosol optical properties, types, and radiative forcing in the Sichuan Basin, Southwest China,Science of the Total Environment ,  https://doi.org/10.1016/j.scitotenv.2021.151490

Li Y., Liu* Y., Chen Y., Chen B., Zhang X., Wang W., Shu Z. and Huo Z., 2021: Characteristics of deep convective systems and initiation during warm seasons over China and its vicinity. Remote Sens. , 13, 4289. https://doi.org/10.3390/ rs13214289.

Huo Z., Liu* Y., …,  2021: Hydrometeor and Latent Heat Nudging for Radar Reflectivity Assimilation: Response to the Model States and Uncertainties. Remote Sensing. https://doi.org/10.3390/rs13193821.

Pan, L., Liu Y., …,  2021:  Seasonal variation of the surface wind forcast performance of the high-resolution WRF-RTFDDA system over China. Atmo. Res. 259. https://doi.org/10.1016/j.atmosres.2021.105673

Zhou, Y., Liu* Y. , C. Liu, 2021: A machine learning-based method to account for 3D Short-wave radiative effects in 1D satellite observation operators. J. Quant. Spec. & Rad. Trans., 275,  https://doi.org/10.1016/j.jqsrt.2021.107891.

Shu, Z., Liu Y. , T, Zhao ..., 2021: Elevated 3D structure of PM2.5 and impact of complex terrain-forcing circulation on heavy haze pollution over Sichuan Basin, China. Atom. Chem. and Phys.; 21, 9253–9268, 2021 https://doi.org/10.5194/acp-21-9253-2021.  

Lu, Z, Y. Han. Liu Y.,  2021:  Improving the Ramer scheme for diagnosis of freezing rain in China. Atmo. Res. 259. https://doi.org/10.1016/j.atmosres.2021.105520

李扬, 刘玉宝*, 许小峰, 2021: 基于深度学习改进数值天气预报模式和预报的研究及挑战. 气象科技进展, 11, 103 – 112. (2021.3). DOI:10.3969/j.issn.2095-1973.2021.03.012.

刘玉宝*，丁秋冀，史月琴，方春刚，段婧,  楼小凤，李萍，霍朝阳，周永波，王昊亮，景晓琴，王新，陈添宇，陈宝君，李集明, 2021: 云解析人工影响天气数值模式的建立、初步试验和展望. 气象科技进展, 11, (2021.9). 

Yuan，G., L. Zhang, Y. Liu, 2021: Impacts of soil moisture and atmospheric moisture transport on the T precipitation in two typical regions of China. Atmos. Res., 247 (2021) 105151.

2020

Zhao, X., J. Zhu, L. Cheng, Y. Liu, Y. Liu, 2020:  An Observing System Simulation Experiment to Assess the Potential Impact of a Virtual Mobile Communication Tower-based Observation Network on Weather Forecasting Accuracy in China. Part 1: Weather Stations with a Typical Mobile Tower Height of 40 m. Adv. Atmos. Sci. 37, 617–633 (2020). https://doi.org/10.1007/s00376-020-9058-1.

Kosovic, B.,... Y. Liu, …,  2020: A Comprehensive Wind Power Forecasting System Integrating Artificial Intelligence and Numerical Weather Prediction. Energies, 13, 1372; doi:10.3390/en13061372.

Liu，Y., Y. Liu, et al. , 2020: Simulation of Flow Fields in Complex Terrain with WRF-LES: Sensitivity Assessment of Different PBL Treatments. Journal of Appl. Met. Clim., 59, 1841-1501.

2019

Huang，Y., Y. Liu*, Yue Liu, and J. C. Knievel, 2019: Budget analyses of a record-breaking rainfall event in the coastal metropolitan city of Guangzhou, China. Journal of Geophysical Research - Atmosphere, 124, 1-16.

Wei，X.，Y. Liu, Y. Liu, and L. Li, 2019: Numerical study of a local PM2.5 pollution event under the typhoon Neoguri (1408) background over a coastal metropolitan city, Shenzhen, China. Physics and Chemistry of the Earth, 110, 99-108.

Du, J., H. Sun, Y. Cao, Y. Liu*, L.Pan and Yue Liu, 2019: Ensemble interpolation of missing wind turbine nacelle wind speed data in wind farms based on robust particle swarm optimized generalized regression neural network. International Journal of Green Energy, 16, 1210-1219 .

2018

Huang, Y., Y. Liu*, Yue Liu, H. Li, and J. C. Knievel, 2018: Mechanisms for a Record‐Breaking Rainfall in the Coastal Metropolitan City of Guangzhou, China: Observation Analysis and Nested Very Large Eddy Simulation with WRF model. Journal of Geophysical Research - Atmosphere, 123, 1-22.

Wang, H., Y. Liu*, W. Y. Y. Cheng, T. Zhao, M. Xu, Yue. Liu,, A. O. Fierro, 2018: Continuous Assimilation of Lightning Data Using Time-Lagged Ensembles for a Convection-Allowing Numerical Weather Prediction Model. Journal of Geophysical Research - Atmosphere, 123, 9652-9673.

刘郁珏，苗世光，胡 非，刘玉宝, 2018: 冬奥会小海坨山赛区边界层风场大涡模拟研究. 高原学报, 37, 1388-1401.

Pan, L., Y. Liu, J. C. Knievel, L. Delle Monache, and G. Roux, 2018: Evaluations of WRF Sensitivities in Surface Simulations with an Ensemble Prediction System. Atmosphere, 9, 106.

Huang, Y., Y. Liu*, M. Xu, Yue. Liu, L. Pan, H. Wang, W. Y.Y. Cheng, Y. Jiang, H. Lan, H. Yang, X. Wei, R. Zong, Ch. Cao, and S. Jin, 2018: Forecasting severe convective storms with WRF-based RTFDDA radar data assimilation in Guangdong, China. Atmospheric Research, 209, 131-143.

Wang. H, Y. Liu*, T. Zhao, M. Xu, Y.W. Liu, F. Guo, W.Y.Y.Cheng, S. Feng, E.R. Mansell, A.O. Fierro, 2018: Incorporating geostationary lightning data into a radar reflectivity based hydrometeor retrieval method: An observing system simulation experiment. Atmospheric Research, 209, 1-13.

2017

Li, L., Y. Jiang, W. Zhang, D. Wang, Y. Liu, L. Pan, Y. Liu, 2017: Using Four-Dimensional Data Assimilation technique: establishment of data set and preliminary applications. Journal of Tropical Meteorology, 33, 874-883.

王昊亮, 刘玉宝, 赵天良, 郭凤霞, 冯双磊, 王勃, 2017: 基于数值天气模式及其模式输出的 闪电预报研究进展. 地球科学进展, 32, 44-55.

Knievel, J. C., Y. Liu, T. M. Hopson, J. S. Shaw, S. F. Halvorson, H. H. Fisher, G. Roux, R.-S. Sheu, L. Pan, W. Wu, J. P. Hacker, E. Vernon, F. W. Gallagher III, and J. C. Pace, 2017: Mesoscale Ensemble Weather Prediction at U.S. Army Dugway Proving Ground, Utah. Weather and Forecasting, 32, 2195-2216.

Wang, H., Y. Liu, W. Y. Y. Cheng, T. Zhao, M. Xu, Yue. Liu, S. Shen, K. M. Calhoun, and A. O. Fierro, 2017: Improving Lightning and Precipitation Prediction of Severe Convection Using Lightning Data Assimilation With NCAR WRF-RTFDDA. Journal of Geophysical Research - Atmosphere, 122, 12296–12316.

Cheng, W.Y.Y., Y. Liu, A. Bourgeois, Y. Wu, S.E. Haupt, 2017: Short-term wind forecast of a data assimilation/weather forecasting system with wind turbine anemometer measurement assimilation. Renewable Energy, 107, 340-351.

Rostkier-Edelstein,D., P. Kunin, T. M. Hopson, Y. Liu and A. Givati, 2016: Statistical downscaling of seasonal precipitation in Israel. Journal of Climate, 36, 590–606.

Zhang, Y., Y. Liu, and Thomas Nipen, 2016: Evaluation of the Impacts of Assimilating the TAMDAR Data on 12/4 km Grid WRF-Based RTFDDA Simulations over the CONUS. Advances in Meteorology, 2016, 1-13.

杜杰，彭玲霞、刘玉宝, 2015: 风 电场风机测量风速缺损值的组合填充模型. 电力自动化设备, 9, 125-129.

Keller, T. L., S. B. Trier, W.D. Hall, R.D. Sharman, M. Xu, and Y. Liu, 2015: Lee Waves Associated with a Commercial Jetliner Accident at Denver International Airport. Journal of Applied Meteorology and Climatology, 54, 1373-1392.

Fernando H.J., … Y. Liu …, 2015: THE MATERHORN: Unraveling the Intricacies of Mountain Weather. Bulletin of American Meteorological Society, 131, 1945-1967.

Pan, L., Y. Liu, Y. Liu, L. Li, Y. Jiang, W. Cheng, and G. Roux, 2015: Impact of four-dimensional data assimilation (FDDA) on urban climate analysis.  Journal of Advances in Modeling Earth Systems, 7, 1997–2011.

Rostkier-Edelstein, D., P. Kunin, T. Hopson, Y. Liu  and A. Givati,, 2015: Statistical downscaling of seasonal precipitation in Israel. International. Journal of Climatology., 36, 590-606.

Zhang, Y., Y. Liu, P. A. Kucera, B. H. Alharbi, L. Pan, and A. Ghulam, 2015: Dust modeling over Saudi Arabia using WRF-Chem: March 2009 severe dust case. Atmospheric Environment, 119, 118-130.

Wyszogrodzki, A, Y. Liu, N. Jacobs, P. Childs, Y. Zhang, G. Roux and T. Warner, 2013: Analysis of the surface temperature and wind forecast errors of the NCAR-AirDat operational CONUS 4-km WRF forecasting system. Meteorology and Atmospheric Physics, 122, 125-143.

Rostkier-Edelstein, D., Y. Liu, W. Wu, P. Kunin, M. Ge and A. Givati, 2013: Towards a high-resolution climatography of seasonal precipitation over Israel. International. Journal of Climatology, 34, 1964-1979.

Cheng, W., Y. Liu, Y.W. Liu, Y. Zhang, W.P. Mahoney, and T. T. Warner, 2013: The impact of model physics on numerical wind forecasts. Renewable Energy, 55, 347-356.

Parks, K., Y.-H. Wan, G. Wiener and Y. Liu, 2012   Wind Energy Forecasting: A Collaboration of the National Center for Atmospheric Research (NCAR) and Xcel Energy. 美国国家再生能源实验室（NREL） DE-AC36-08GO28308., 1-246.

Mahoney, W.P, K. Parks, G. Wiener, Y. Liu, W. Myers, J. Sun, L-D. Monache, T. Hopson, D. Johnson and S.E. Haupt, 2012: A Wind Power Forecasting System to Optimize Grid Integration. IEEE Transactiion on Sustainable Energy, 10, 670-682.

Givati, A., B. Lynn, Y. Liu, A. Rimmer, 2012: Using the WRF Model in an Operational Streamflow Forecast System for the Jordan River. Journal of Applied Meteorology and Climatology, 51, 285-199.

Wu, W., Y. Liu, M. Ge, D. Rostkier-Edelstein, G. Descobes, P. Kunin, T. Warner, S. Swerdlin, A. Givati, T. Hopson, D. Yates, 2012: Statistical downscaling of climate forecast system seasonal predictions for the Southeastern Mediterranean. Atmospheric Research, 118, 346–356 .

Delle Monache, L., T. Nipen, Y. Liu, G. Roux, and R. Stull, 2011: Kalman Filter and Analog Schemes to Postprocess Numerical Weather Predictions. Monthly Weather Review, 139, 3554-3570.

Liu, Y., T. Warner, Y.W. Liu, C. Vincent, W. Wu, B. Mahoney, S. Swerdlin, K. Parks, J. Boehnert, 2011: Simultaneous nested modeling from the synoptic scale to the LES scale for wind energy applications. Journal of Wind Engineering and Industrial Aerodynamics, 99, 308-319.

Frehlich, R., R. Sharman, F. Vanderberg, W. Yu, Y. Liu, and J. Knievel, 2010: Estimates of Cn2 from Numerical Weather Prediction Model Output and Comparison with Thermosonde Data. Journal of Applied Meteorology and Climatology, 49, 1742-1755.

Steiner,M., R. Bateman, D. Megenhardt, Y. Liu, M. Xu, and J. Krozel, 2010: Translation of Ensemble Weather Forecasts into Probabilistic Air Traffic Capacity Impact. Air Traffic Control Quarterly, 18, 229-254.

Hahmann, A. N., D. Rostkier-Edelstein, T. T. Warner, F. Vandenberghe, Y. Liu, R. Babarsky, S. P. Swerdlin, 2009: A dynamical downscaling system for the Generation of Mesoscale Climatographies. Journal of Applied Meteorology and Climatology, 49, 954–972.

Hahmann A., D. Rostkier-Edelstein, T. Waner, Y. Liu, F. Vandenberghe, and S. Swerdlin, 2008: Toward a climate downscaling for the Eastern Mediterranean at high-resolution. Advances in Geosciences, 12, 159-164.

Liu, Y., T.T. Warner, J. F. Bowers, L. P. Carson, F. Chen, C. A. Clough, C. A. Davis, C. H. Egeland, S. Halvorson, T.W. Huck Jr., L. Lachapelle, R.E. Malone, D. L. Rife, R.-S. Sheu, S. P. Swerdlin, and D.S. Weingarten, 2008: The Operational Mesogamma-Scale Analysis and Forecast System of the U.S. Army Test and Evaluation Command. Part I: Overview of the Modeling System, the Forecast Products, and How the Products Are Used. Journal of Applied Meteorology and Climatology, 47, 1077-1092.

Liu, Y., T. T. Warner, E. G. Astling, J. F. Bowers, C. A. Davis, S. F. Halvorson, D. L. Rife, R.-S. Sheu, S. P. Swerdlin, and M. Xu, 2008: The Operational Mesogamma-Scale Analysis and Forecast System of the U.S. Army Test and Evaluation Command. Part II: Interrange Comparison of the Accuracy of Model Analyses and Forecasts. Journal of Applied Meteorology and Climatology, 47, 1093-1104.

Sharman, R., Y. Liu, R.-S. Sheu,  D. L. Rife, T. T. Warner,  J. F. Bowers, and E. Ellison, 2008: The Operational Mesogamma-Scale Analysis and Forecast System of the U.S. Army Test and Evaluation Command. Part III: Forecasting with Secondary-Applications Models. Journal of Applied Meteorology and Climatology, 47, 1105 – 1116.

Grossman-Clarke, S., Y. Liu, J. Zehnder,  and J. Fast, 2008: Simulations of the Urban Planetary Boundary Layer in an Arid Metropolitan Area. Journal of Applied Meteorology and Climatology, 47, 752-768.

Tie, X., S. Madronich, G. Li, Z. Ying, R. Zhang, A. Garcia, J. Lee-Taylor and Y. Liu, 2007: Characterizations of chemical oxidants in Mexico City: A regional chemical dynamical model (WRF-CHEM). Atmospheric Environment, 41, 1989-2008.

Bowers, J. F., Y. Liu, J. Hacker. S. Swerdlin, T. Betacnourt and E. Astling, 2007: An Operational Mesoscale Ensemble-Based Forecast System Using HPC Resources. IEEE HPCMP-UGC 2007, 1-5.

Warner, T., …, Y. Liu, …, 2007: The Pentagon Shield Field Program: Toward Critical Infrastructure Protection. Bulletin of American Meteorological Society, 88, 167-176.

Liu, Y., F. Chen, T. Warner and J. Basara, 2006: Verification of a Mesoscale Data-Assimilation and Forecasting System for the Oklahoma City Area during the Joint Urban 2003 Field Project. Journal of Applied Meteorology and Climatology, 45, 912-929.

Grossman-Clarke, S., J. Zehnder, W. Stefanov, Y. Liu and M. Zoldak, 2005: Urban Modifications in a Mesoscale Meteorological Model and the Effects on Near-Surface Variables in an Arid Metropolitan Region. Journal of Applied Meteorology, 44, 1281-1297.

Rife L. D., C. A. Davis, Y. Liu and T. Warner, 2004: Predictability of Low-Level Winds by Mesoscale Meteorological Models. Monthly Weather Review, 132, 2553-2569.

Yau, M.K., Y. Liu, D.-L. Zhang and Y. Chen, 2004: A Multiscale Numerical Study of Hurricane Andrew (1992). Part VI: Small-Scale Inner-Core Structures and Wind Streaks. Monthly Weather Review, 132, 2553-2569.

Zhang, D.-L., Y. Liu and M. K. Yau, 2002: A Multiscale Numerical Study of Hurricane Andrew (1992). Part V: Inner-Core Thermodynamics. Monthly Weather Review, 130, 2745-2763.

Zhang, D.-L., Y. Liu and M. K. Yau, 2001: A Multiscale Numerical Study of Hurricane Andrew (1992). Part IV: Unbalanced Flow. Monthly Weather Review, 129, 97-107.

Zhang, D.-L., Y. Liu and M. K. Yau, 2000: A Multiscale Numerical Study of Hurricane Andrew (1992). Part III: Dynamically Induced Vertical Motion. Monthly Weather Review, 128, 3772-3788.

Zhang, D.-L., Y. Liu and M. K. Yau, 1999: Surface Winds at Landfall of Hurricane Andrew (1992)—A Reply. Monthly Weather Review, 127, 1711-1721.

Liu, Y., D.-L. Zhang and M. K. Yau, 1999: A Multiscale Numerical Study of Hurricane Andrew (1992). Part II: Kinematics and Inner-Core Structures. Monthly Weather Review, 127, 2597-2616.

Liu, Y., D.-L. Zhang and M. K. Yau, 1997: A Multiscale Numerical Study of Hurricane Andrew ( 1992). Part I: Explicit Simulation and Verification. Monthly Weather Review, 125, 3073-3093.

Kuo, Y.-H., R. J. Reed, and Y. Liu, 1996: The ERICA IOP 5 Storm. Part III: Mesoscale Cyclogenesis and precipitation Parameterization. Monthly Weather Review, 124, 1409-1434.

刘玉宝，胡志晋、周秀骥、葛润生, 1995: 中尺度山脉对流群的动力和微物理数值模拟. 气象学报, 53, 157-167.

刘玉宝，周秀骥、胡志晋, 1994: 强对流风暴数值模拟及其未来预报的若干问题. 应用气象学报, 4, 418-427.

Liu, Y., X. Zhou and Z. Hu, 1993: A Three-dimensional Elastic Nested-grid Meso (beia-gamma) scale atmospheric model - Part I: Model Description. Journal of Meteorology Review, 7, 257-272.

Liu, Y., X. Zhou and Z. Hu, 1993: A Three-dimensional Elastic Nested-grid Meso (beia-gamma) scale atmospheric model - Part II: Model Validation. Journal of Meteorology Review, 7, 469-485.

刘玉宝，胡志晋, 1993: 卷云数值模式和对流卷云数值模拟. 气象学报, 51, 148-158.

刘玉宝，周秀骥, 胡志晋, 1993: 三维弹性套网格中尺度(β-γ)大气模式的检验和实例研究. 气象学报, 51, 369-380.

游来光，李炎辉，刘玉宝, 1992: 自然云中冰晶生成的核化过程及雪晶对过冷云滴的撞冻. 气象学报, 50, 232-238.

刘玉宝，游来光, 1990: 北疆冬季降水的中小尺度结构与人工增水作业潜力和自然条件探讨. 应用气象学报, 1, 113-122.

刘玉宝，游来光，胡志晋, 1988: 新疆准葛尔盆地冬季系统性降水研究。II.理论探讨. 气象科学研究院院刊, 3, 36-45.

刘玉宝，胡志晋，游来光, 1988: 新疆准葛尔盆地冬季系统性降水研究。I.降水模型. 气象科学研究院院刊, 3, 159-168

 

团队名称：精细化区域地球模拟和信息中心 （PREMIC）

团队介绍：团队成员：教授3人，副教授2人，青年人才讲师4人，科研助理3人
学生团队：博士研究生3人，硕士研究生11人，本科生：8人
研究内容：中微尺度数值资料同化和预报模式技术和模式输出智能释用技术，及其在灾害性天气预报、人工影响天气、新能源、航空气象、电网气象灾害、城市积涝和山洪暴发灾害、空气质量灾害和有毒气体传输扩散应急决策辅助等方面的应用。
目前合作单位：中国气象科学研究院人影中心，中国电力科学研究研院、内蒙古电力集团、内蒙古气象局、深圳市气象局、河北省气象局、南京信大气象科学研究院等。