Lili LEI

Professor


lililei@nju.edu.cn

Education
 2011Ph.D. Pennsylvania State University, Meteorology
 2006M.S. Nanjing University, Meteorology
 2004B.S. Nanjing University, Atmospheric Sciences
Work Experience
 2016 - presentProfessor, School of Atmospheric Sciences, Nanjing University
 2014 - 2016Research Scientist, CIRES Climate Diagnostics Center, University of Colorado, and Physical Sciences Division, NOAA/Earth System Research Laboratory
 2011 - 2014Postdoctoral Fellow, Advanced Study Program, National Center for Atmospheric Research
 2006 - 2011Graduate Research Assistant, Pennsylvania State University, Department of Meteorology
Research Interests

   Data assimilation, particularly ensemble-based techniques
   Numerical weather prediction and climate modeling
   Predictability
   Mesoscale dynamics

Teaching Interests

   Data assimilation
   Atmospheric dynamics

Selected Publications
 1.Lei, L., J. S. Whitaker, and C. H. Bishop, 2018: Improving assimilation of radiance observations by implementing model space localization in an ensemble Kalman filter. J. Adv. Model. Earth Syst., 10, 3221-3233, https://doi.org/10.1029/2018MS001468.
 2.Lei, L., and J. S. Whitaker, 2017: Evaluating the trade-offs between ensemble size and ensemble resolution. J. Adv. Model. Earth Syst., 9, 781-789.
 3.Lei, L., J. L. Anderson, and J. S. Whitaker, 2016: Localizing the impact of satellite radiance observations using a global group ensemble filter. J. Adv. Model. Earth Syst., 8, 719-734. https://doi.org/10.1002/2016MS0000627.
 4.Lei, L., and J. S. Whitaker, 2016: A four-dimensional incremental analysis update for the ensemble Kalman filter. Mon. Wea. Rev., 144, 2605-2621. http://dx.doi.org/10.1175/MWR-D-15-0246.1.
 5.Lei, L., and J. S. Whitaker, 2015: Model space localization is not always better than observation space localization for assimilation of satellite radiances. Mon. Wea. Rev., 143, 3948-3955, https://doi.org/10.1175/MWR-D-14-00413.1.
 6.Lei, L., J. L. Anderson and G. S. Romine, 2015: Empirical localization functions for ensemble Kalman filter data assimilation in regions with and without precipitation. Mon. Wea. Rev., 143, 3664-3679, https://doi.org/10.1175/MWR-D-14-00415.1.
 7.Lei, L., and J. L. Anderson, 2014: Impacts of frequent assimilation of surface pressure observations on atmospheric analyses. Mon. Wea. Rev., 142, 4477–4483, https://doi.org/10.1175/MWR-D-14-00097.1
 8.Lei, L., and J. L. Anderson, 2014: Empirical localization of observations for serial ensemble Kalman filter data assimilation in an atmospheric general circulation model. Mon. Wea. Rev., 142, 1835-1851, https://doi.org/10.1175/MWR-D-13-00288.1.
 9.Lei, L., and J. Anderson, 2014: Comparisons of empirical localization techniques for ensemble Kalman filters in a simple atmospheric general circulation model. Mon. Wea. Rev., 142, 739-754, https://doi.org/10.1175/MWR-D-13-00152.1.
 10.Lei, L., D. R. Stauffer, and A. Deng, 2012: A hybrid nudging-ensemble Kalman filter approach to data assimilation. Part II: application in a shallow-water model. Tellus, 64A, 18485, http://dx.doi.org/10.3402/tellusa.v64i0.18485.
Awards, Honors, Positions and Services
 2018Kamide Lecture, Asia Oceania Geosciences Society (AOGS)
 2016Tepin Professor, Jiangsu Province
 2015Deng Feng Scholar Program B, Nanjing University
 2006Anne C. Wilson Graduate Fellowship, Pennsylvania State University
 2004Zhu Binghai Scholarship, Nanjing University
 2003First Prize in People's Scholarship, Nanjing University
 2002First Prize in People's Scholarship, Nanjing University
 2001First Prize in Mathematical Contest in Modeling of China;
First Prize in People's Scholarship, Nanjing University
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    Nanjing, Jiangsu Province, 210023