袁慧玲

教授、博导

    Email: yuanhl@nju.edu.cn

个人简介

       袁慧玲，bwin必赢教授、博士生导师、中尺度灾害性天气教育部重点实验室副主任。2013年入选江苏省高层次创新创业人才，2021年入选教育部长江学者特聘教授。主要从事中小尺度数值模拟、智能预报、水文气象、陆气相互作用研究。发表学术论文60余篇，参与编著英文专著1部和中文教材1本。目前担任中国气象学会水文气象学委员会副主任委员, SCI期刊Environmental Research Letters和Advances in Atmospheric Sciences编委等职务。获得江苏省科学技术二等奖、国家气象中心气象科技工作成果应用一等奖、江苏省气象学会气象科技成果奖（基础研究奖）一等奖，bwin必赢创新育人奖、魅力导师奖、师德先进团队奖、育教融合奖、“我最喜爱的老师”和“我最喜爱的研究生生涯导师”等荣誉称号。

       1997年获bwin必赢气象学学士学位，2000年获中科院大气物理研究所气象学硕士学位，2005年获美国加州大学尔湾分校土木工程学博士学位。2006-2010年就职于美国国家海洋大气局地球系统研究实验室（NOAA/ESRL），2010年被聘为bwin必赢教授。

教育经历

2003-2005  美国加州大学尔湾分校（UC Irvine）土木环境工程系，博士

2000-2003  美国亚利桑那大学水文与水资源系，博士研究生

1997-2000  中国科学院大气物理研究所，硕士

1993-1997  bwin必赢大气科学系，学士

工作经历

2010-目前    bwin必赢，教授、博导

2007-2010   美国国家海洋大气局地球系统研究实验室（NOAA/ESRL）和科罗拉多大学环境合作研究所（CIRES），
                    研究员(2级)   (Research Scientist Ⅱ)

2006-2007   美国科学院国家研究委员会（NAS/NRC）和国家海洋大气局地球系统研究实验室（NOAA/ESRL），
                    助理研究员   (Research Associate)

研究方向

数值模拟与灾害性天气预报、机器学习与数据科学、水文气象与陆气相互作用

教学经历

研究生课程：高等大气科学概论（英文授课）、水文气象（本硕通选，国际化课程）

本科课程：大气科学概论、大气科学综合实验（上）

重要项目

2024-2027   国家自然科学基金气象联合基金重点项目：面向长三角地区精细化气象保障服务的机器学习算法研究，主持

2021-2024   国家自然科学基金面上项目：土壤湿度初始化对WRF-Hydro模式陆面水文过程模拟的影响，主持

2018-2021   国家重点研发计划课题：暴雨可预报性与对流尺度集合预报方法，主持

2017-2020   国家自然科学基金面上项目：淮河上游流域分布式水文模拟的不确定性研究，主持

2012-2015   国家自然科学基金面上项目：中国夏季定量降水预报的不确定性理论研究，主持

2012-2014   公益性行业（气象）科研专项项目：定量降水预报的系统误差订正关键技术研究，主持

代表论著

Yang, C., H. Yuan*, F. Zhang, M. Xie, Y. Wang, G.-M. Jiang, 2024: Convective initiation nowcasting in South China using physics-augmented random forest models and geostationary satellites. Earth and Space Science, 11, e2024EA003571. https://doi.org/10.1029/2024EA003571

Veiga, S. F., H. Yuan*, 2024: Evaluation of metrics for assessing dipolar climate patterns in climate models. Climate Dynamics, 2024, 1-17. https://doi.org/10.1007/s00382-024-07220-3

Han, X., H. Yuan*, 2024: Impacts of precipitation uncertainty on hydrological ensemble simulations over the Ganjiang River basin. Journal of Hydrology: Regional Studies, 51, 101617. https://doi.org/10.1016/j.ejrh.2023.101617

Yang, S., H. Yuan*, 2023: A customized multi-scale deep learning framework for storm nowcasting. Geophysical Research Letters, 50, e2023GL103979. https://doi.org/10.1029/2023GL103979

Wang, J., Yuan, H.*, Wang, X., Cui, C., & Wang, X. (2023). Impact of thermally forced circulations on the diurnal cycle of summer precipitation over the southeastern Tibetan Plateau. Geophysical Research Letters, 50, e2022GL100951. https://doi.org/10.1029/2022GL100951

Yang, Y., H. Yuan*, W. Chen, 2023. Convection-permitting ensemble forecasts of a double rainbelt event in South China during the pre-summer rainy season. Atmospheric Research, 284, 106599. https://doi.org/10.1016/j.atmosres.2022.106599

Xu, F., H. Yuan*, L. Lin, W. Chen, 2023: Convective-scale ensemble forecasts of the heavy precipitation of typhoon Lekima (2019) in Zhejiang Province. Atmospheric Research, 283, 106543. https://doi.org/10.1016/j.atmosres.2022.106543

Liu, L., H. Yuan*, Y. Deng, J. Ren, Y. Bai, C. Cui, 2023: Effects of aerosols on the forecasting of Mei-yu frontal storms over the Yangtze–Huai River Valley. Atmospheric Research, 283, 106535.https://doi.org/10.1016/j.atmosres.2022.106535

Yang, S., H. Yuan*, L. Dong, 2022: Offshore wind resource assessment by characterizing weather regimes based on self-organizing map. Environmental Research Letters, 17, 124009. https://doi.org/10.1088/1748-9326/aca2c2

Lin, L., H. Yuan*, X. Bao, W. Chen, S. Zhang, F. Xu, 2022: Evaluation of the raindrop size distribution representation of microphysics schemes in typhoon Lekima using disdrometer network observations. Atmospheric Research, 278, 106346. https://doi.org/10.1016/j.atmosres.2022.106346

Chen, W., H. Yuan*, 2022: Onshore convection associated with the easterly wave over the South China Sea: A case study. Atmospheric Research, 268, 105979. https://doi.org/10.1016/j.atmosres.2021.105979

Sandro F. Veiga, H. Yuan*, 2022: The response of the East Asian summer rainfall to more extreme El Niño events in future climate scenarios. Atmospheric Research, 268, 105983. https://doi.org/10.1016/j.atmosres.2021.105983

Sandro F. Veiga, H. Yuan*, 2021: Performance-based projection of precipitation extremes over China based on CMIP5/6 models using integrated quadratic distance. Weather and Climate Extremes, 34, 100398. https://doi.org/10.1016/j.wace.2021.100398

Wu, B., S. Oncley, H. Yuan*, F. Chen, 2020: Ground heat flux determination based on near-surface soil hydro-thermodynamics. Journal of Hydrology, 591, 125578. https://doi.org/10.1016/j.jhydrol.2020.125578

Chen, Y, H. Yuan*, Y. Yang, and R. Sun, 2020: Sub-daily soil moisture estimate using dynamic Bayesian model averaging. Journal of Hydrology, 590, 125455. https://doi.org/10.1016/j.jhydrol.2020.125445

Chen, F., H. Yuan*, R. Sun*, C. Yang, 2020: Streamflow simulations using error correction ensembles of satellite precipitation products over the Huaihe River basin. Journal of Hydrology, 589, 125179. https://doi.org/10.1016/j.jhydrol.2020.125179

Chen, Y, and H. Yuan*, 2020:Evaluation of nine sub-daily soil moisture model products over China using high-resolution in situ observations. Journal of Hydrology, 588, 125054. https://doi.org/10.1016/j.jhydrol.2020.125054

Yang, C., H. Yuan*, X. Su, 2020: Bias correction of ensemble precipitation forecasts in the improvement of summer streamflow prediction skill. Journal of Hydrology, 588, 124955. https://doi.org/10.1016/j.jhydrol.2020.124955

Chen, Y., Yuan, H.*, and Gao, S., 2019: A high-resolution simulation of roll convection over the Yellow Sea during a cold air outbreak. Journal of Geophysical Research: Atmospheres, 124, 10608-10625. https://doi.org/10.1029/2019JD030968

Yang, Y., H. Yuan*, and W. Yu, 2018: Uncertainties of 3D Soil Hydraulic Parameters in Streamflow Simulations using a Distributed Hydrological Model System. Journal of Hydrology, 567, 12-24. https://doi.org/10.1016/j.jhydrol.2018.09.042

Sun, R., H. Yuan*, and Y. Yang, 2018. Using multiple satellite-gauge merged precipitation products ensemble for hydrologic uncertainty analysis over the Huaihe River basin. Journal of Hydrology, 566, 406-420.https://doi.org/10.1016/j.jhydrol.2018.09.024

Chen, X., H. Yuan*, and M. Xue, 2018: Spatial spread-skill relationship in terms of agreement scales for precipitation forecasts in a convection-allowing ensemble. Quarterly Journal of the Royal Meteorological Society, 144, 85-98.https://doi.org/10.1002/qj.3186

Han, H., J. Liu*, H. Yuan*, et al., 2018: Impacts of synoptic weather patterns and their persistency on free tropospheric carbon monoxide concentrations and outflow in eastern China. Journal of Geophysical Research: Atmospheres, 123, 7024–7046. https://doi.org/10.1029/2017JD028172

Sun, R., H. Yuan*, and X. Liu, 2017. Effect of heteroscedasticity treatment in residual error models on model calibration and prediction uncertainty estimation. Journal of Hydrology, 554, 680-692. https://doi.org/10.1016/j.jhydrol.2017.09.041

Yuan, H., Sun, M. and Wang, Y., 2016: Assessment of the benefits of the Chinese Public Weather Service. Meteorological Applications, 23, 132–139. https://doi.org/10.1002/met.1539

Sun, R., H. Yuan*, X. Liu, and X. Jiang, 2016: Evaluation of the latest satellite-gauge precipitation products and their hydrologic applications over the Huaihe River basin. Journal of Hydrology, 536, 302-319. https://doi.org/10.1016/j.jhydrol.2016.02.054

Li, S., Y. Wang, H. Yuan*, J. Song, and X. Xu, 2016: Ensemble mean forecast skill and applications with the T213 ensemble prediction system. Advances in Atmospheric Sciences, 33, 1297–1305. https://doi.org/10.1007/s00376-016-6155-2

Jiang, X., H. Yuan*, M. Xue, X. Chen, X. Tan, 2014: Analysis of a heavy rainfall event over Beijing during 21-22 July 2012 based on high resolution model analyses and forecasts. Journal of Meteorological Research, 28, 199-212. https://doi.org/10.1007/s13351-014-3139-y

Su, X., H. Yuan*, Y. Zhu, Y., Y. Luo, and Y. Wang, 2014: Evaluation of TIGGE ensemble predictions of Northern Hemisphere summer precipitation during 2008-2012.Journal of Geophysical Research: Atmospheres, 119, 7292-7310. https://doi.org/10.1002/2014JD021733

Chang, H.-L., H. Yuan*, and P.-L. Lin, 2012: Short-range (0-12h) PQPFs from time-lagged multimodel ensembles using LAPS. Monthly Weather Review, 140, 1496-1516. https://doi.org/10.1175/MWR-D-11-00085.1

Tang, J., H. Yuan*, Y. Wang, and J. Fei, 2012: The use of shear gradient vorticity in tropical cyclone heavy precipitation prediction: A high-resolution numerical case study. Journal of Tropical Meteorology, 18(4), 403-411.  https://doi.org/10.16555/j.1006-8775.2012.04.001

Yuan, H.*, C. Lu, J. A. McGinley, P. J. Schultz, B. Jamison, L. Wharton, and C. J. Anderson, 2009: Evaluation of short-range quantitative precipitation forecasts from a time-lagged multimodel ensemble. Weather and Forecasting, 24, 18-38. https://doi.org/10.1175/2008WAF2007053.1

Yuan, H.*, J. A. McGinley, P. J. Schultz, C. J. Anderson, and C. Lu, 2008: Short-range precipitation forecasts from time-lagged multimodel ensembles during the HMT-West-2006 campaign. Journal of Hydrometeorology, 9, 477-491. https://doi.org/10.1175/2007JHM879.1

Yuan, H.*, S. L. Mullen, X. Gao, S. Sorooshian, J. Du, and H. H. Juang, 2007: Short-range probabilistic quantitative precipitation forecasts over the southwest United States by the RSM ensemble system. Monthly Weather Review,135, 1685–1698. https://doi.org/10.1175/MWR3373.1

Yuan, H.*, X. Gao, S. L. Mullen, S. Sorooshian, J. Du, and H. H. Juang, 2007: Calibration of probabilistic quantitative precipitation forecasts with an artificial neural network. Weather and Forecasting, 22,1287–1303. https://doi.org/10.1175/2007WAF2006114.1

Yuan, H.*, S. L. Mullen, X. Gao, S. Sorooshian, J. Du, and H. H. Juang, 2005: Verification of probabilistic quantitative precipitation forecasts over the southwest United States during winter 2002/03 by the RSM ensemble system. Monthly Weather Review,133, 279-294. https://doi.org/10.1175/MWR-2858.1