GFDL - Geophysical Fluid Dynamics Laboratory

Dr. Xiaosong Yang

UCAR, Project Scientist II

Climate Variations and Predictability Group, NOAA/GFDL

Princeton University Forrestal Campus

201 Forrestal Road, Princeton, NJ 08540

Phone: 609-452-5311, Fax: 609-987-5063, Email: Xiaosong.Yang@noaa.gov

Education

  • Ph.D. in Marine and Atmospheric Science, Stony Brook University,  Stony Brook, 2006
  • M.S. in Atmospheric Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, 2000
  • B.S. in Meteorology, Ocean University of Qingdao, China, 1995

Research Interests

  • Coupled model initialization for climate prediction
  • Subseasonal-seasonal-decadal scale climate predictability and variability
  • Climate extremes: Attribution and prediction
  • Eddy-mean flow interactions and storm track dynamics

Submitted manuscripts:

  1. Yang, X., G. A. Vecchi, L. Jia, S. Kapnick, T. L. Delworth,R. G. Gudgel, Seth Underwood, Fanrong Zeng, 2017: On the seasonal prediction of the western United States  El Niño precipitation during the 2015/16 winter, Climate Dynamics, Submitted.

Selected papers on predictability studies

  1.  Jia, L., X. Yang, G. A. Vecchi, R. Gudgel, T. Delworth, S. Fueglistaler, P. Lin, A. Scaife, S. Underwood, S.-J. Lin, 2017: Seasonal Prediction Skill of Northern Extratropical Surface Temperature Driven by the Stratosphere, J. Climate, DOI:10.1175/JCLI-D-16-0475.1
  2.  Jia, Liwei, G. A. Vecchi, X. Yang, R. G. Gudgel, T. L. Delworth, W. F. Stern, K. Paffendorf, S. D. Underwood, and F. Zeng, 2016: The Roles of Radiative Forcing, Sea Surface Temperatures, and Atmospheric and Land Initial Conditions in U.S. Summer Warming Episodes. Journal of Climate, 29(11), DOI:10.1175/JCLI-D-15-0471.1
  3. Yang, X. et al., 2015: Seasonal predictability of extratropical storm tracks in GFDL’s high-resolution climate prediction model, J. Climate, 28, 3592-3611,doi: http://dx.doi.org/10.1175/JCLI-D-14-00517.1
  4. Jia, L., X. Yang,  et al., 2015: Improved Seasonal Prediction of Temperature and Precipitation over Land in a High-resolution GFDL Climate Model, J. Climate, 28, 2044-2062, doi: http://dx.doi.org/10.1175/JCLI-D-14-00112.1.
  5. Yang, X. et al., 2013: A predictable AMO-like pattern in GFDL’s fully-coupled ensemble initialization and decadal forecasting system,  Journal of Climate., 26(2), DOI:10.1175/JCLI-D-12-00231.1 .

Selected papers on data assimilation

  1. DelSole, T., and X. Yang, 2010: State and Parameter Estimation in Stochastic Dynamical Models, Physica D, 239,1781-1788.
  2. Yang, X., and T. DelSole, 2009: Using ensemble Kalman Filter to estimate multiplicative parameters, Tellus A, 61, 601-609.
  3. Yang, X., and T. DelSole, 2009: The diffuse ensemble  filter,  Nonlinear Processes in Geophysics, 16, 475-486

Publication Statistics

Publication list

GFDL’s Bibliography Page

CV