Feng received his Ph.D. in Earth Sciences from the University of Southern California in 2021 and did his postdoc training at NCAR.

Feng's research interests fall in the application of Earth system modeling and data assimilation, model-data comparison, as well as machine learning, to better understand the Earth system and validate Earth system models. In addition, Feng enjoys and has made lots of efforts on scientific software engineering, developing tools to facilitate efficient and reproducible research and open science.

Research Interests

  • Earth System Modeling
  • Data Assimilation
  • Machine Learning
  • Scientific Software Engineering

Funding History

  • Emulating Water Isotopes in Fully-coupled Global Climate Models using Knowledge-guided Machine Learning. NSF, Collaborations in Artificial Intelligence and Geosciences (CAIG), Led the Proposal, 10/1/2025 - 9/30/2028
  • Enhancing Safety, Security, and Privacy in the Community Earth System Model (CESM) Ecosystem. NSF, Safety, Security, and Privacy of Open-Source Ecosystems (Safe-OSE), Co-led the Proposal, 1/1/2026 - 12/31/2027
  • deepGreen: A deep learning based tree-ring width data model for paleoclimatic data assimilation. NSF, Paleo Perspectives on Present and Projected Climate (P4CLIMATE), Led the Proposal, 7/1/2023 - 6/30/2026
  • x4c: Xarray for efficient CESM postprocessing, analysis, and visualization. NCAR/CGD Strategic Initiative Fund (SIF), PI, 1/1/2025 - 9/30/2025

Scientific Datasets

pseudoPAGES2k: A pseudoproxy emulation of the PAGES 2k database using a hierarchy of proxy system models

Scientific Software Projects

cfr: a Python package for climate field reconstruction
x4c: Xarray for CESM
Pyleoclim: utilities for paleoclimate data analysis and visualization
pens: utilities for comparing paleoclimate reconstruction ensembles

Selected Publications

  • Zhu, F., Zhu, J., Si, W., Nirenberg, J., Herbert, T., Tierney, J., Acosta, R.P., Burls, N., Evans, D., 2025. Model-data synthesis of benthic isotopes suggests a warmer Miocene Climatic Optimum. Nature Communications (In Revision). Preprint
  • Zhu, F., Emile-Geay, J., Anchukaitis, K.J., Hakim, G.J., Wittenberg, A.T., Morales, M.S., Toohey, M., King, J., 2022. A re-appraisal of the ENSO response to volcanism with paleoclimate data assimilation. Nature Communications 13, 747. https://doi.org/10.1038/s41467-022-28210-1 Poster
  • Zhu, F., Emile-Geay, J., McKay, N.P., Hakim, G.J., Khider, D., Ault, T.R., Steig, E.J., Dee, S., Kirchner, J.W., 2019. Climate models can correctly simulate the continuum of global-average temperature variability. PNAS 201809959. https://doi.org/10.1073/pnas.1809959116
  • Zhu, F., Emile-Geay, J., Hakim, G.J., King, J., Anchukaitis, K.J., 2020. Resolving the Differences in the Simulated and Reconstructed Temperature Response to Volcanism. Geophysical Research Letters 47, e2019GL086908. https://doi.org/10.1029/2019GL086908
  • Zhu, F., Emile-Geay, J., Hakim, G.J., Guillot, D., Khider, D., Tardif, R., Perkins, W.A., 2024. cfr (v2024.1.26): a Python package for climate field reconstruction. Geoscientific Model Development 17, 3409-3431. https://doi.org/10.5194/gmd-17-3409-2024 Poster
  • Zhu, F., Emile-Geay, J., Anchukaitis, K.J., McKay, N.P., Stevenson, S., Meng, Z., 2023. A pseudoproxy emulation of the PAGES 2k database using a hierarchy of proxy system models. Scientific Data 10, 624. https://doi.org/10.1029/2019GL086908
  • Khider, D., Emile-Geay, J., Zhu, F., James, A., Landers, J., Ratnakar, V., Gil, Y., 2022. Pyleoclim: Paleoclimate Timeseries Analysis and Visualization With Python. Paleoceanography and Paleoclimatology 37, e2022PA004509. https://doi.org/10.1029/2022PA004509
  • Emile-Geay, J., Cobb, K.M., Cole, J.E., Elliot, M., Zhu, F., 2020. Past ENSO Variability: Observations, Models, and Implications, in: El Niño Southern Oscillation in a Changing Climate. American Geophysical Union (AGU), pp. 87-118. https://doi.org/10.1002/9781119548164.ch5
  • Power, S., Lengaigne, M., Capotondi, A., Khodri, M., Vialard, J., Jebri, B., Guilyardi, E., McGregor, S., Kug, J.-S., Newman, M., McPhaden, M.J., Meehl, G., Smith, D., Cole, J., Emile-Geay, J., Vimont, D., Wittenberg, A.T., Collins, M., Kim, G.-I., Cai, W., Okumura, Y., Chung, C., Cobb, K.M., Delage, F., Planton, Y.Y., Levine, A., Zhu, F., Sprintall, J., Di Lorenzo, E., Zhang, X., Luo, J.-J., Lin, X., Balmaseda, M., Wang, G., Henley, B.J., 2021. Decadal climate variability in the tropical Pacific: Characteristics, causes, predictability, and prospects. Science 374, eaay9165. https://doi.org/10.1126/science.aay9165
  • PAGES 2k Consortium, 2019. Consistent multidecadal variability in global temperature reconstructions and simulations over the Common Era. Nature Geoscience 12, 643-649. https://doi.org/10.1038/s41561-019-0400-0
  • King, J.M., Anchukaitis, K.J., Tierney, J.E., Hakim, G.J., Emile-Geay, J., Zhu, F., Wilson, R., 2021. A data assimilation approach to last millennium temperature field reconstruction using a limited high-sensitivity proxy network. Journal of Climate 1, 1-64. https://doi.org/10.1175/JCLI-D-20-0661.1