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Home » NOAA / GSL Staff Directory » Profile

Linlin Pan

GSL Staff Profiles
Title
Research Scientist
Email
linlin.pan@noaa.gov
Phone
303-497-5929
Office Number
2B512
Address
DSRC
325 Broadway
Boulder, CO 80305
Affiliation
CIRES

Professional Profile

Research Scientist

My work is mainly focused on numerical weather model development, verification and support. I participate in enhancing transition of innovations in Numerical Weather Prediction (NWP) to NOAA's operational Unified Forecast System (UFS) with Finite Volume Cubed Sphere (FV3) dynamical core,  as well as strengthening the development and support of the Hurricane Weather Research and Forecasting (HWRF) system. I also contribute to Developmental Testbed Center (DTC) activities in supporting the community.

Research Interests

  • Numerical weather prediction
  • Atmospheric physics and Dynamics
  • Data Assimilation
  • Model development, verification and support
 

Education

  • Ph. D. in Meteorology, University of Hawaii at Manoa, Honolulu, HI
  • M.S. and B. S. in Atmospheric Science, Peking University, Beijing, China

Experience

  • Research Scientist II, GSL at CIRES/CU (Sept. 2018-)
  • Project Scientist II, RAL NCAR, (Aug.. 2016-Aug. 2018)
  • Project Scientist I, RAL NCAR, (Dec. 2009-Aug. 2016)

Professional Activities

  • Member, American Meteorological Society
  • Member, American Geophysical Union
  • Permanent Member, Chinese-American Oceanic and Atmospheric Association

Honors and Awards

  • 2017  - NCAR Scientific and Technical Advancement Awards 

Publications

  • Du, J., H. Sun, Y. Cao, Y. Liu, L. Pan, Y. 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(14), 1-10. DOI: 10.1080/15435075.2019.1671396
  • 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; doi:10.3390/atmos9030106.
  • Huang, Y., Y. Liu, M. Xu, Y. Liu, L. Pan, H. Wang, W. Y. Y. Cheng, Y. Jiang, H. Lan, H. Yang, X. Wei, R. Zong, C. Cao, 2018: Forecasting severe convective storms with WRF-based RTFDDA radar data assimilation in Guangdong, China, Atmospheric Research, 209, 131-143, https://doi.org/10.1016/j.atmosres.2018.03.010
  • 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. 
  • 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, 2016: Mesoscale Ensemble Weather Prediction at U.S. Army Dugway Proving Ground, Utah, Weather and Forecasts, 30, 2195-2216.
  • 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, doi:10.1002/2015MS000487.
  • Du, J., L. Peng, Y. Liu, L. Pan, L. Wang, Y. Cao, 2015:  Combined interpolation model for wind speed measurement missing of wind farm. Electric Power Automation Equipment, 9, 125-129.
  • Zhang Y., Y. Liu, P. A. Kucera, B. H. Alharbi, L. Pan, A. Ghulam, 2015: Dust modeling over Saudi Arabia using WRF-Chem: March 2009 severe dust case. Atmospheric Environment, 119, 118-130. doi:10.1016/j.atmosenv.2015.08.032.
  • Pan L.,  S.-H. Chen, D. Cayan, M.-Y. Lin, Q. Hart, M.-H., Zhang, Y. Liu, and J. Wang, 2011: Influences of climate change on California and Nevada regions revealed by a High-resolution dynamical downscaling study, Climate Dynamics, 37, 2005-2020, DOI 10.1007/s00382-010-0961-5.
  • Grotjahn, R., L. Pan, and J. Tribbia, 2011: Sources of CAM3 vorticity bias during northern winter from diagnostic study of the vorticity bias equation. Climate Dynamics, 36, 2051-2075, DOI 10.1007/s00382-011-0998-0.
  • Grotjahn, R., L. Pan, and J. Tribbia, 2011: CAM3 bias over the Arctic region during northern winter studied with a linear stationary model. Climate Dynamics, 37, 631-645. DOI 10.1007/s00382-011-1033-1.
  • Pan L., R. Grotjahn, and J. Tribbia, 2010: Sources of CAM3 temperature bias during northern winter from diagnostic study of the temperature bias equation, Climate Dynamics, 35, 1411-1427, DOI 10.1007/200382-009-0608-6.
  • Pan L., and T. Li, 2008: Interactions between tropical ISO and midlatitude low-frequency flow, Climate Dynamics, 31, 375-388, DOI: 10.1007/s00382-007-0272-7.
  • Pan L., 2007: Synoptic eddy feedback and air-sea interaction in the North Atlantic region, Climate Dynamics, 27, 647-659, DOI : 10.1007/s00382-007-0256-7.
  • Watanabe, M., F.-F. Jin, and L. Pan, 2006: Accelerated iterative method for solving steady solutions of linearized atmospheric models, J. Atmos. Sci., 63, 3366-3382.
  • Pan, L., F.-F. Jin, and M. Watanabe, 2006: Dynamics of synoptic eddy and low-frequency flow (SELF) feedback, Part III. baroclinic model results. J. Atmos. Sci., 63, 1709-1725.
  • Jin, F.-F., L. Pan, and M. Watanabe, 2006: Dynamics of synoptic eddy and low-frequency flow (SELF) feedback, Part I: a linear closure, J. Atmos. Sci., 63, 1677-1694.
  • Jin, F.-F., L. Pan, and M. Watanabe, 2006: Dynamics of synoptic eddy and low-frequency flow (SELF) feedback, Part II: A theory for low-frequency modes, J. Atmos. Sci., 63, 1695-1708.
  • Pan, L., and F.-F. Jin, 2005: Note on ”Deriving seasonal variation in the Arctic Oscillation”, Bull. Ameri. Meteor. Soc., 86, 1541-1542.
  • Pan, L., and F.-F. Jin, 2005: Seasonality of synoptic eddy feedback and the AO/NAO, Geophys. Res. Lett., 32, L21708, doi:10.1029/2005GL024133.
  • Pan, L., 2005: Observed positive feedback between the NAO and the North Atlantic SSTA tripole, Geophys. Res. Lett., 32, L06707, doi:10.1029/2005GL022427.
  • Wang, Q., K. Suhre, P. Krummel, S. Siems, L. Pan, T. S. Bates, J. E. Johnson, D. H. Lenschow, B. J. Heubert., G. L. Kok, R. D. Schillawski, A. S. Prevot, and S. Businger, 1999: Characteristics of marine boundary layers during two Lagrangian measurement periods 1. General conditions and mean characteristics, J. Geophys. Res., 104, 21751-21765. 
  • Wang, Q., D. H. Lenschow, L. Pan, R. D. Schillawski, G. L. Kok, R. D. Schillawski, A. S. Prevot, K. Lauren, L. M. Russell, A. R. Bandy, D. C. Thornto, and K. Suhre, 1999: Characteristics of marine boundary layers during two Lagrangian measurement periods 2. Turbulence structure, J. Geophys. Res., 104, 21767-21784.
  • Pan, L., J. Chen, 1997: The simulation of "cold Island Effect" over Oasis at Night, Chinese Journal of Atmospheric Sciences, 21(1), 1-9. 
  • Pan, L., J. Chen, H. Zhang, and A. Zhang, 1996: A one-dimensional model of the coupling between land surface and atmosphere and its application to inner Mongolia grassland, Chinese Journal of Atmospheric Sciences, 20(2), 195-206.
  • Pan, L., Chen, J., Zhang, H. and Zhang, A., 1996: Coupling between Land Surface and Atmosphere in Inner Mongolia Grassland, Scientia Atmospherica Sinica, 20(4), 367-377.
  • Liu, B., and L. Pan, 1993: Application of trajectory plume model under complicated meteorological conditions, Bulletin of science and technology, 2, 359-363.