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Head shot of Zachary Labe

Zachary Labe

Postdoctoral Research Associate
Atmospheric and Oceanic Sciences, Princeton University
Geophysical Fluid Dynamics Laboratory (GFDL), Seasonal-to-Decadal Variability and Predictability Division
Email: zachary.labe@noaa.gov

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RESEARCH INTERESTS

My current work explores the intersection of large-scale climate variability and change, extreme events, large ensembles, decadal prediction, and data science methods. In addition to academic research, I am very passionate about improving science communication, accessibility, and outreach through engaging data visualizations.

EDUCATION

  • Ph.D. in Earth System Science – University of California, Irvine – May 2020
  • M.Sc. in Earth System Science – University of California, Irvine – September 2017
  • B.Sc. in Atmospheric Science – Cornell University – May 2015 (Distinction in Research)

ACADEMIC APPOINTMENTS

  • 2022-Present: Postdoctoral Research Associate
    • Program in Atmospheric and Oceanic Sciences, Princeton University, NJ
    • NOAA Geophysical Fluid Dynamics Laboratory, Princeton, NJ
  • 2020-2022: Postdoctoral Researcher
    • Department of Atmospheric Science, Colorado State University, CO
  • 2015-2020: Graduate Research Assistant
    • Department of Earth System Science, University of California, Irvine, CA
  • 2014-2015: Undergraduate Research Assistant
    • Department of Earth and Atmospheric Science, Cornell University, NY

SERVICE

  • Member – Diversity, Equity, Inclusivity, and Accessibility Committee (NOAA GFDL)
  • Member – Fresh Eyes on CMIP (WCRP Working Group)
  • Associate Editor – Journal of Climate
  • Contributing Editor – Carbon Brief
  • Guest Editor – Special Issue for Atmospheric Science Letters
  • Board Member – United States Association of Polar Early Career Scientists (USAPECS)
  • Board Member – GFDL Employees Association (GFDLEA)
  • Board of Advisors – NCAR Climate Data Guide

PUBLICATIONS

(GFDL Bibliography)

2024
  • Bushuk, M., S. Ali, D. Bailey, Q. Bao, L. Batte, U.S. Bhatt, E. Blanchard-Wrigglesworth, E. Blockley, G. Cawley, J. Chi, F. Counillon, P. Goulet Coulombe, R. Cullather, F.X. Diebold, A. Dirkson, E. Exarchou, M. Gobel, W. Gregory, V. Guemas, L. Hamilton, B. He, S. Horvath, M. Ionita, J. E. Kay, E. Kim, N. Kimura, D. Kondrashov, Z.M. Labe, W. Lee, Y.J. Lee, C. Li, X. Li, Y. Lin, Y. Liu, W. Maslowski, F. Massonnet, W.N. Meier, W.J. Merryfield, H. Myint, J.C. Acosta Navarro, A. Petty, F. Qiao, D. Schroder, A. Schweiger, Q. Shu, M. Sigmond, M. Steele, J. Stroeve, N. Sun, S. Tietsche, M. Tsamados, K. Wang, J. Wang, W. Wang, Y. Wang, Y. Wang, J. Williams, Q. Yang, X. Yuan, J. Zhang, and Y. Zhang (2024). Predicting September Arctic sea ice: A multi-model seasonal skill comparison. Bulletin of the American Meteorological Society, DOI:10.1175/BAMS-D-23-0163.1
  • Zhang, Y., B.M. Ayyub, J.F. Fung, and Z.M. Labe (2024). Incorporating extreme event attribution into climate change adaptation for civil infrastructure: Methods, benefits, and research needs. Resilient Cities and Structures, DOI:10.1016/j.rcns.2024.03.002
  • Labe, Z.M., N.C. Johnson, and T.L. Delworth (2024). Changes in United States Summer Temperatures Revealed by Explainable Neural Networks. Earth’s Future, DOI:10.1029/2023EF003981
2023
  • Timmermans, M.-L. and Z.M. Labe (2023). Sea surface temperature [in “Arctic Report Card 2023”], NOAA, DOI:10.25923/e8jc-f342
  • Timmermans, M.-L. and Z.M. Labe (2023). [The Arctic] Sea surface temperature [in “State of the Climate in 2022”]. Bull. Amer. Meteor. Soc., DOI:10.1175/BAMS-D-23-0079.1
  • Eischeid, J.K., M.P. Hoerling, X.-W. Quan, A. Kumar, J. Barsugli, Z.M. Labe, K.E. Kunkel, C.J. Schreck III, D.R. Easterling, T. Zhang, J. Uehling, and X. Zhang (2023). Why has the summertime central U.S. warming hole not disappeared? Journal of Climate, DOI:10.1175/JCLI-D-22-0716.1
  • Witt, J.K., Z.M. Labe, A.C. Warden, and B.A. Clegg (2023). Visualizing uncertainty in hurricane forecasts with animated risk trajectories. Weather, Climate, and Society, DOI:10.1175/WCAS-D-21-0173.1
  • Labe, Z.M., E.A. Barnes, and J.W. Hurrell (2023). Identifying the regional emergence of climate patterns in the ARISE-SAI-1.5 simulations. Environmental Research Letters, DOI:10.1088/1748-9326/acc81a
2022
  • Timmermans, M.-L. and Z.M. Labe (2022). Sea surface temperature [in “Arctic Report Card 2022”], NOAA, DOI:10.25923/p493-2548
  • Po-Chedley, S., J.T. Fasullo, N. Siler, Z.M. Labe, E.A. Barnes, C.J.W. Bonfils, and B.D. Santer (2022). Internal variability and forcing influence model-satellite differences in the rate of tropical tropospheric warming. Proceedings of the National Academy of Sciences, DOI:10.1073/pnas.2209431119
  • Witt, J.K., Z.M. Labe, and B.A. Clegg (2022). Comparisons of perceptions of risk for visualizations using animated risk trajectories versus cones of uncertainty. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, DOI:10.1177/1071181322661308
  • Timmermans, M.-L. and Z.M. Labe (2022). [The Arctic] Sea surface temperature [in “State of the Climate in 2021”]. Bull. Amer. Meteor. Soc., DOI:10.1175/BAMS-D-22-0082.1
  • Labe, Z.M. and E.A. Barnes (2022), Comparison of climate model large ensembles with observations in the Arctic using simple neural networks. Earth and Space Science, DOI:10.1029/2022EA002348
  • Labe, Z.M. and E.A. Barnes (2022), Predicting slowdowns in decadal climate warming trends with explainable neural networks. Geophysical Research Letters, DOI:10.1029/2022GL098173
2021
  • Timmermans, M.-L. and Z.M. Labe (2021). Sea surface temperature [in “Arctic Report Card 2021”], NOAA, DOI:10.25923/2y8r-0e49
  • Timmermans, M.-L. and Z.M. Labe (2021). [The Arctic] Sea surface temperature [in “State of the Climate in 2020”]. Bull. Amer. Meteor. Soc., DOI:10.1175/BAMS-D-21-0086.1
  • Labe, Z.M. and E.A. Barnes (2021), Detecting climate signals using explainable AI with single-forcing large ensembles. Journal of Advances in Modeling Earth Systems, DOI:10.1029/2021MS002464
  • Peings, Y., Z.M. Labe, and G. Magnusdottir (2021), Are 100 ensemble members enough to capture the remote atmospheric response to +2°C Arctic sea ice loss? Journal of Climate, DOI:10.1175/JCLI-D-20-0613.1
2020
  • Timmermans, M.-L. and Z.M. Labe (2020). Sea surface temperature [in “Arctic Report Card 2020”], NOAA, DOI:10.25923/v0fs-m920
  • Timmermans, M.-L., Z.M. Labe, and C. Ladd (2020). [The Arctic] Sea surface temperature [in “State of the Climate in 2019”], Bull. Amer. Meteor. Soc., DOI:10.1175/BAMS-D-20-0086.1
  • Labe, Z.M., Y. Peings, and G. Magnusdottir (2020). Warm Arctic, cold Siberia pattern: role of full Arctic amplification versus sea ice loss alone, Geophysical Research Letters, DOI:10.1029/2020GL088583
2019
  • Thoman, R.L., U. Bhatt, P. Bieniek, B. Brettschneider, M. Brubaker, S. Danielson, Z.M. Labe, R. Lader, W. Meier, G. Sheffield, and J. Walsh (2019): The record low Bering Sea ice extent in 2018: Context, impacts and an assessment of the role of anthropogenic climate change [in “Explaining Extreme Events of 2018 from a Climate Perspective”]. Bull. Amer. Meteor. Soc, DOI:10.1175/BAMS-D-19-0175.1
  • Labe, Z.M., Y. Peings, and G. Magnusdottir (2019). The effect of QBO phase on the atmospheric response to projected Arctic sea ice loss in early winter, Geophysical Research Letters, DOI:10.1029/2019GL083095
2018
  • Labe, Z.M., Y. Peings, and G. Magnusdottir (2018), Contributions of ice thickness to the atmospheric response from projected Arctic sea ice loss, Geophysical Research Letters, DOI:10.1029/2018GL078158
  • Labe, Z.M., G. Magnusdottir, and H.S. Stern (2018), Variability of Arctic sea ice thickness using PIOMAS and the CESM Large Ensemble, Journal of Climate, DOI:10.1175/JCLI-D-17-0436.1
2017
  • Labe, Z.M., T.R. Ault, and R. Zurita-Milla (2017), Identifying Anomalously Early Spring Onsets in the CESM Large Ensemble Project, Climate Dynamics, DOI:10.1007/s00382-016-3313-2

OTHER SELECTED WRITINGS

PHD THESIS

CONTACT INFORMATION

  • Office Email: zachary.labe@noaa.gov
  • Office Phone: +1-609-452-6571
  • Mailing/Courier Address: GFDL, 201 Forrestal Rd. Princeton, NJ 08540-6649 USA