Education
2015 Ph.D. Climate Dynamics, University of Texas at Austin
Dissertation title: Multivariate land snow data assimilation in the Northern Hemisphere: Development, evaluation and uncertainty quantification of the extensible data assimilation system.
Advisor: Dr. Zong-Liang Yang
2010 B.S. Atmospheric Sciences, Nanjing University
Research Experiences
2018–present Postdoctoral Research Associate, Princeton University/GFDL
2015–2018 Postdoctoral Research Associate, University of Washington
2020
Zhang, Y.-F., M. Bushuk, M. Winton, B. Hurlin, X. Yang, T. Delworth, and L. Jia (2020), Assimilation of satellite-retrieved sea ice concentration and new prospects for September predictions of Arctic sea ice, J. Clim, in press, doi: 10.1175/JCLI-D-20-0469.1.
Lu, F., M. J. Harrison, A. Rosati, T. L. Delworth, X. Yang, W. F. Cooke, C. McHugh, N. C. Johnson, L. Jia, M. Bushuk, Y.-F. Zhang, and A. Adcroft (2020), GFDL’s SPEAR seasonal prediction system: ocean data assimilation (ODA), ocean tendency adjustment (OTA) and coupled initialization, J. Adv. Model, doi: 10.1029/2020MS002149.
Lin, P., J. Wei, Z.-L. Yang, R. E. Dickinson, Y.-F. Zhang, and L. Zhao (2020), Assimilating multi-satellite snow data in ungauged Eurasia improves the Asian monsoon seasonal forecasts, Environ. Res. Lett., 15, 064033, doi:10.1088/1748-9326/ab80ef.
2019
Bian, Q., Z Xu, L. Zhao, Y.-F. Zhang, H. Zheng, C. Shi, S. Zhang, C. Xie, and Z.-L. Yang (2019), Evaluation and intercomparison of multiple snow water equivalent products over the Tibetan Plateau, J. Hydrometeorol., 20 (10), 2043–2055, doi:10.1175/JHM-D-19-0011.1.
2018
Zhang, Y.-F., C. M. Bitz, J. L. Anderson, N. Collins, J. Hendricks, T. J. Hoar, K. Raeder, and F. Massonnet (2018), Insights on sea ice data assimilation from perfect model observing system simulation experiments, J. Clim., 31, 5911–5926, doi:10.1175/JCLI-D-17-0904.1.
2016
Lin, P., J. Wei, Z.-L. Yang, Y.-F. Zhang, and K. Zhang (2016), Snow data assimilation-constrained land initialization improves seasonal temperature prediction, Geophys. Res. Lett., 43, 11,423–11,432, doi:10.1002/2016GL070966.
Zhang, Y. -F. and Z. -L Yang (2016), Estimating uncertainties in the newly developed multi-source land snow data assimilation system, J. Geophys. Res. –Atmos., 121, 8254–8268, doi:10.1002/2015JD024248.
Zhang Y.-J., P. M. Cristiano, Y.-F. Zhang, P. I. Campanello, Z.-H. Tan, Y.-P. Zhang, K.-F. Cao, G. Goldstein (2016), Carbon economy of subtropical forests, In: Tropical Tree Physiology, Springer.
Toure, A. M., M. Rodell, Z.-L. Yang, H. Beaudoing, E. Kim, Y.-F. Zhang, and Y. Kown (2016), Evaluation of the snow simulations from the Community Land Model, version 4 (CLM4). J. Hydrometeor., 17, 153–170, doi:10.1175/JHM-D-14-0165.1.
2014
Zhang Y.-F., T. J. Hoar, Z.-L. Yang, J. L. Anderson, A. M. Toure, and M. Rodell (2014), Assimilation of MODIS snow cover through the data assimilation research testbed and the Community Land Model Version 4, J. Geophys. Res.–Atmos., 119, 7091–7103, doi:10.1002/2013JD021329.
Yin, L., R. Fu, Y.-F. Zhang, P. A. Arias, D. N. Fernando, W. Li, K. Fernandes, and A. R. Bowerman (2014), What controls the interannual variation of the wet season onsets over the Amazon?, J. Geophys. Res. –Atmos., 119, 2314–2328,doi:10.1002/2013JD021349.