Jonathan King
Publications
Use the tabs below to view my papers and software projects.
A complete list of my journal articles and data releases.
Postfire Debris Flows
  • Graber, A., Selander, B., Barnhart, K., Gorr, A., Kean, J., King, J., Kostelnik, J., Rengers, F., & Thomas, M. (2026). Regional Models for Postfire Debris‐Flow Likelihood and Rainfall Thresholds Across the Western United States. Earth Surface Processes and Landforms, 51(9), e70393. https://doi.org/10.1002/esp.70393
  • Graber, A., Thomas, M., Kean, J., King, J., & Kostelnik, J. (2026). Characterizing changes in postfire debris-flow hazard as burned areas recover. Geosphere, 22(3), 494-515. https://doi.org/10.1130/GES02936.1
  • King, J., & Graber, A. (2026). Precipitation intensity estimates for a one-year recurrence interval for the continental United States. U.S. Geological Survey Data Release. https://doi.org/10.5066/P1499TUY
  • Barnhart, K., Belair, G., Kean, J., King, J., Graber, A., Kostelnik, J., Rengers, F., & Thomas, M. (2026). Post-Wildfire Debris-Flow Runout Hazard Assessment (PWFDF-R) Collection. U.S. Geological Survey Data Release. https://doi.org/10.5066/P18RMZBB
  • King, J., Kostelnik, J., Kean, J., Barnhart, K., Graber, A., Rengers, F., & Thomas, M. (2025). Post-Wildfire Debris-Flow Hazard Assessment (PWFDF) Collection. U.S. Geological Survey Data Release. https://doi.org/10.5066/P14EWYME
  • King, J. (2025). PWFDF Data Specification. U.S. Geological Survey Software. https://doi.org/10.5066/P13KUWCO
  • King, J., Kostelnik, J., & Kean, J. (2025). 2024 Post-Wildfire Debris-Flow Hazard Assessments. U.S. Geological Survey Data Release. https://doi.org/10.5066/P13GTMAX
  • Staley, D., Kean, J., Kostelnik, J., King, J., Jones, E., Schmitt, R., Rengers, F., Thomas, M., & Negri, J. (2026). 2013-2023 Post-Wildfire Debris-Flow Hazard Assessments. U.S. Geological Survey Data Release. https://doi.org/10.1016/j.geomorph.2016.10.019
  • King, J. (2025). STATSGO Cloud Optimized GeoTIFFs for the Continental United States. U.S. Geological Survey Data Release. https://doi.org/10.5066/P13WAPYV
Climate Data Assimilation
  • Allen, K., Freund, M., Anchukaitis, K., Palmer, J., English, N., Evans, R., Adrianaase-Tucker, A., King, J., Cook, E., Buckley, B., Krusic, P., & Baker, P. (2026). Common Era temperature variability for two seasons in Tasmania, southern Australia. Proceedings of the National Academy of Sciences, in press.
  • Tierney, J., Judd, E., Osman, M., King, J., Truax, O., Steiger, N., Amrhein, J., & Anchukaitis, K. (2025). Advances in paleoclimate data assimilation. Annual Review of Earth and Planetary Sciences, 53(1), 625-650. https://doi.org/10.1146/annurev-earth-032320-064209
  • Tierney, J., King, J., Osman, M., Abell, J., Burls, N., Erfani, E., Cooper, V., & Feng, R. (2025). Pliocene warmth and patterns of climate change inferred from paleoclimate data assimilation. AGU Advances, 6(1), e2024AV001356. https://doi.org/10.1029/2024AV001356
  • King, J., Tierney, J., Osman, M., Judd, E., & Anchukaitis, K. (2023). DASH: A MATLAB toolbox for paleoclimate data assimilation. Geoscientific Model Development, 16(19), 5653-5683. https://doi.org/10.5194/gmd-16-5653-2023
  • King, J., Anchukaitis, K., Allen, K., Vance, T., & Hessl, A. (2023). Trends and variability in the Southern Annular Mode over the Common Era. Nature Communications, 14(1), 2324. https://doi.org/10.1038/s41467-023-37643-1
  • Zhu, F., Emile-Geay, J., Anchukaitis, K., Hakim, G., Wittenberg, A., Morales, M., Toohey, M., & King, J. (2022). A re-appraisal of the ENSO response to volcanism with paleoclimate data assimilation. Nature communications, 13(1), 747. https://doi.org/10.1038/s41467-022-28210-1
  • Osman, M., Tierney, J., Zhu, J., Tardif, R., Hakim, G., King, J., & Poulsen, C. (2021). Globally resolved surface temperatures since the Last Glacial Maximum. Nature, 599(7884), 239-244. https://doi.org/10.1038/s41586-021-03984-4
  • King, J., Anchukaitis, K., Tierney, J., Hakim, G., 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, 34(17), 7091-7111. https://doi.org/10.1175/JCLI-D-20-0661.1
  • Tierney, J., Zhu, J., King, J., Malevich, S., Hakim, G., & Poulsen, C. (2020). Glacial cooling and climate sensitivity revisited. , 584(7822), 569-573. https://doi.org/10.1038/s41586-020-2617-x
  • Zhu, F., Emile‐Geay, J., Hakim, G., King, J., & Anchukaitis, K. (2020). Resolving the differences in the simulated and reconstructed temperature response to volcanism. Geophysical Research Letters, 47(8), e2019GL086908. https://doi.org/10.1029/2019GL086908
Other
  • King, J., Hurwitz, S., Lowenstern, J., Nordstrom, D., & McCleskey, R. (2016). Multireaction equilibrium geothermometry: A sensitivity analysis using data from the Lower Geyser Basin, Yellowstone National Park, USA. Journal of Volcanology and Geothermal Research, 328, 105-114. https://doi.org/10.1016/j.jvolgeores.2016.10.010.
  • Burnin, A., Poggio, S., King, J., & BelBruno, J. (2016). Direct growth by arc discharge and computational study of zinc sulfide nanotubes. Journal of materials science, 51(21), 9716-9722. https://doi.org/10.1007/s10853-016-0205-0.
  • Poggio, S., King, J., & BelBruno, J. (2015). Properties of transition metal doped cadmium sulfide hexamers and dodecamers. Chemical Physics Letters, 640, 106-111. https://doi.org/10.1016/j.cplett.2015.10.007.
A curated list of my software projects. Also check out my Github profile for more information.
Postfire Debris Flows
Python packages that form the USGS's postfire debris-flow software stack.
  • pfdf: Numerical Python library to faciliate postfire debris-flow hazard assessments and research
  • wildcat: Command line tool to assess and map postfire debris-flow hazards
  • ocelote: USGS production pipeline to produce and publish postfire debris-flow hazard assessments
  • pwfdf-api: Search, query, and download hazard assessments from the PWFDF Collection
  • pwfdf-ids: Python utility classes for parsing PWFDF assessment IDs
  • flowalert: Monitor synoptic gages for rainfall events that cross critical thresholds
Climate Data Assimilation
Matlab packages used for climate data assimilation research.
  • DASH: MATLAB toolbox to design and implement paleoclimate data assimilation workflows
  • pdsi: Functions to efficiently compute the Palmer Drought Severity Index for instrumental and/or climate model data
  • scaleColorMap: Utility functions to scale colorbars when plotting divergent datasets.
Developer Utilities
Python utilities to improve the developer experience.
  • pytest-issues: Decorators for testing errors and warnings with pytest
  • logset: Convenience functions for quickly configuring Python loggers
  • logindent: Utility class for implementing structurally indented log messages
© 2026 Jonathan King