Jonathan M King
Jonathan King is a Mendenhall Post-doc in the Landslide Hazards Program at the Geologic Hazards Science Center in Golden, Colorado. His work focuses on software tools for post-fire debris-flow hazard assessments and research.
Jonathan M. King is a Mendenhall postdoc at the USGS who is currently developing tools for post-fire debris-flow hazard assessments. Previously, he completed a doctorate in climatology at the University of Arizona, where he specialized in paleoclimate data assimilation. Jonathan is the author of several geoscientific software libraries - these include the USGS's pfdf, wildcat packages, and the DASH Matlab toolbox. Jonathan King's interests include natural hazards, climate change, and supporting open science.
Professional Experience
2023-present: Mendenhall Postdoctoral Fellow, USGS Landslide Hazards Program
2015-2016: Hydrologic Technician, USGS Water Resources Division
Education and Certifications
Ph.D. Geoscience, 2022, University of Arizona
M.S. Geoscience, 2018, University of Arizona
B.A. Chemistry, 2015, Dartmouth College
Honors and Awards
2024: USGS Star Award
2023: USGS Mendenhall Fellowship
2022: Graduate Student Scholarship Award, University of Arizona College of Science
2021: Andrew Douglas Memorial Scholarship, University of Arizona Laboratory of Tree-Ring Research
2020: Data Science and Digital Scholarship Fellowship, University of Arizona Libraries
2020: Galileo Circle Scholar, University of Arizona College of Science
Science and Products
Multireaction equilibrium geothermometry: A sensitivity analysis using data from the Lower Geyser Basin, Yellowstone National Park, USA Multireaction equilibrium geothermometry: A sensitivity analysis using data from the Lower Geyser Basin, Yellowstone National Park, USA
A multireaction chemical equilibria geothermometry (MEG) model applicable to high-temperature geothermal systems has been developed over the past three decades. Given sufficient data, this model provides more constraint on calculated reservoir temperatures than classical chemical geothermometers that are based on either the concentration of silica (SiO2), or the ratios of cation...
Authors
Jonathan King, Shaul Hurwitz, Jacob Lowenstern, D. Nordstrom, R. McCleskey
Non-USGS Publications**
Tierney, J., Judd, E., Osman, M., King, J., Truax, O., Steiger, N., Amrhein, D., and Anchukaitis, K. (2025). Advances in Paleoclimate Data Assimilation. Annual Review of Earth and Planetary Sciences, 53. https://doi.org/10.1146/annurev-earth-032320-064209
Tierney, J., King, J., Osman, M., Abell, J., Burls, N., Erfani, E., Cooper, V., and 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., and 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., and 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., and 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., and Poulsen, C. J. (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., and 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., and Poulsen, C. (2020). Glacial cooling and climate sensitivity revisited. Nature, 584(7822), 569-573. https://doi.org/10.1038/s41586-020-2617-x
Zhu, F., Emile‐Geay, J., Hakim, G., King, J., and 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
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
Post-Wildfire Debris-Flow Hazard Assessment (PWFDF) Collection Post-Wildfire Debris-Flow Hazard Assessment (PWFDF) Collection
Wildfire can substantially alter the hydrologic response of watersheds to rainfall, and debris-flow activity is among the most destructive consequences of these events. To assist federal, state, and local agencies in planning for postfire hazards, the U.S. Geological Survey conducts debris-flow hazard assessments for recent wildfires. This collection contains the results of those...
STATSGO Cloud Optimized GeoTIFFs for the Continental US STATSGO Cloud Optimized GeoTIFFs for the Continental US
This data release reformats data fields from the STATSGO soil characteristics dataset (Schwarz and Alexander, 1995) as cloud-optimized GeoTIFFs (COGs). The COG format allows standard software tools to efficiently access the datasets over an internet connection. Please refer to the documentation of the source archive (Schwarz and Alexander, 1995) for additional details on the underlying...
ocelote 1.0.0 ocelote 1.0.0
This release introduces the ocelote package. The package includes routines to run assessments, manage assessment metadata, and upload assessments to Amazon S3 and ScienceBase. The package consists of the following commands: * authenticate s3: Acquires, tests, and stores credentials for S3 uploads * authenticate sciencebase: Acquires, tests, and stores credentials for ScienceBase uploads...
wildcat 1.1.0 wildcat 1.1.0
This release allows users to select the CRS of exported files, and to specify alternate configuration files. The release also updates wildcat’s backend for compatibility with pfdf 3+. Documentation: https://ghsc.code-pages.usgs.gov/lhp/wildcat/ Release Notes: https://ghsc.code-pages.usgs.gov/lhp/wildcat/resources/release-notes/1.1.0.html
pfdf 3.0.0 pfdf 3.0.0
This release adds the `data` package, which provides routines to download commonly used datasets from the internet. The release also provides pfdf tutorials as Jupyter Notebooks, improves array broadcasting in the `gartner2014` and `staley2017` modules, and introduces the `RasterMetadata` class (which manages raster metadata without loading data arrays to memory). Documentation: https:/...
wildcat 1.0.0 wildcat 1.0.0
Wildcat is a software tool to assess and map post-wildfire debris-flow hazards. The package can be run from the command line or within Python. This 1.0.0 release includes the core routines to: * Preprocess input datasets, * Design stream segment networks, * Estimate debris-flow hazards and rainfall thresholds, and * Export results to common GIS formats (such as Shapefiles and GeoJSON)...
statsgo-cog 1.0.0 statsgo-cog 1.0.0
This release introduces the core statsgo-cog package. This package provides functions to convert soil data fields in the STATSGO archive from shapefiles to cloud optimized GeoTiffs (COGs). The package contains 3 main commands: * download: Downloads the STATSGO shapefile archive from ScienceBase * merge: Merges the shapefile archive into a single shapefile spanning all of the continental...
pfdf 2.0.0 pfdf 2.0.0
This release substantially improves support for working with datasets in a mix of coordinate reference systems. The release also introduces new classes for working with spatial metadata, adds confidence intervals to the Gartner 2014 volume model, adds support for additional unit systems, and improves the user experience when filtering the stream segments in a network.
pfdf 1.1.0 pfdf 1.1.0
This release add the following major features to pfdf: * Comprehensive documentation * Raster preprocessing * Parallelization options when locating outlet basins * Windowed raster reading The release also provides minor improvements, as follows: * Raster data/nodata masks, * Improved model broadcasting options, * The Segments.in_mask and Segments.in_perimeter methods
pfdf 1.0.0 pfdf 1.0.0
pfdf: A Python library to facilitate post-wildfire debris-flow hazard assessments and research. This release provides the core functionality needed to implement operational hazard assessments. This includes tools to: * Analyze watersheds * Delineate and filter stream segment networks * Compute earth-system variables for stream segments in a network * Assess debris-flow probabilities...
Science and Products
Multireaction equilibrium geothermometry: A sensitivity analysis using data from the Lower Geyser Basin, Yellowstone National Park, USA Multireaction equilibrium geothermometry: A sensitivity analysis using data from the Lower Geyser Basin, Yellowstone National Park, USA
A multireaction chemical equilibria geothermometry (MEG) model applicable to high-temperature geothermal systems has been developed over the past three decades. Given sufficient data, this model provides more constraint on calculated reservoir temperatures than classical chemical geothermometers that are based on either the concentration of silica (SiO2), or the ratios of cation...
Authors
Jonathan King, Shaul Hurwitz, Jacob Lowenstern, D. Nordstrom, R. McCleskey
Non-USGS Publications**
Tierney, J., Judd, E., Osman, M., King, J., Truax, O., Steiger, N., Amrhein, D., and Anchukaitis, K. (2025). Advances in Paleoclimate Data Assimilation. Annual Review of Earth and Planetary Sciences, 53. https://doi.org/10.1146/annurev-earth-032320-064209
Tierney, J., King, J., Osman, M., Abell, J., Burls, N., Erfani, E., Cooper, V., and 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., and 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., and 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., and 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., and Poulsen, C. J. (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., and 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., and Poulsen, C. (2020). Glacial cooling and climate sensitivity revisited. Nature, 584(7822), 569-573. https://doi.org/10.1038/s41586-020-2617-x
Zhu, F., Emile‐Geay, J., Hakim, G., King, J., and 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
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
Post-Wildfire Debris-Flow Hazard Assessment (PWFDF) Collection Post-Wildfire Debris-Flow Hazard Assessment (PWFDF) Collection
Wildfire can substantially alter the hydrologic response of watersheds to rainfall, and debris-flow activity is among the most destructive consequences of these events. To assist federal, state, and local agencies in planning for postfire hazards, the U.S. Geological Survey conducts debris-flow hazard assessments for recent wildfires. This collection contains the results of those...
STATSGO Cloud Optimized GeoTIFFs for the Continental US STATSGO Cloud Optimized GeoTIFFs for the Continental US
This data release reformats data fields from the STATSGO soil characteristics dataset (Schwarz and Alexander, 1995) as cloud-optimized GeoTIFFs (COGs). The COG format allows standard software tools to efficiently access the datasets over an internet connection. Please refer to the documentation of the source archive (Schwarz and Alexander, 1995) for additional details on the underlying...
ocelote 1.0.0 ocelote 1.0.0
This release introduces the ocelote package. The package includes routines to run assessments, manage assessment metadata, and upload assessments to Amazon S3 and ScienceBase. The package consists of the following commands: * authenticate s3: Acquires, tests, and stores credentials for S3 uploads * authenticate sciencebase: Acquires, tests, and stores credentials for ScienceBase uploads...
wildcat 1.1.0 wildcat 1.1.0
This release allows users to select the CRS of exported files, and to specify alternate configuration files. The release also updates wildcat’s backend for compatibility with pfdf 3+. Documentation: https://ghsc.code-pages.usgs.gov/lhp/wildcat/ Release Notes: https://ghsc.code-pages.usgs.gov/lhp/wildcat/resources/release-notes/1.1.0.html
pfdf 3.0.0 pfdf 3.0.0
This release adds the `data` package, which provides routines to download commonly used datasets from the internet. The release also provides pfdf tutorials as Jupyter Notebooks, improves array broadcasting in the `gartner2014` and `staley2017` modules, and introduces the `RasterMetadata` class (which manages raster metadata without loading data arrays to memory). Documentation: https:/...
wildcat 1.0.0 wildcat 1.0.0
Wildcat is a software tool to assess and map post-wildfire debris-flow hazards. The package can be run from the command line or within Python. This 1.0.0 release includes the core routines to: * Preprocess input datasets, * Design stream segment networks, * Estimate debris-flow hazards and rainfall thresholds, and * Export results to common GIS formats (such as Shapefiles and GeoJSON)...
statsgo-cog 1.0.0 statsgo-cog 1.0.0
This release introduces the core statsgo-cog package. This package provides functions to convert soil data fields in the STATSGO archive from shapefiles to cloud optimized GeoTiffs (COGs). The package contains 3 main commands: * download: Downloads the STATSGO shapefile archive from ScienceBase * merge: Merges the shapefile archive into a single shapefile spanning all of the continental...
pfdf 2.0.0 pfdf 2.0.0
This release substantially improves support for working with datasets in a mix of coordinate reference systems. The release also introduces new classes for working with spatial metadata, adds confidence intervals to the Gartner 2014 volume model, adds support for additional unit systems, and improves the user experience when filtering the stream segments in a network.
pfdf 1.1.0 pfdf 1.1.0
This release add the following major features to pfdf: * Comprehensive documentation * Raster preprocessing * Parallelization options when locating outlet basins * Windowed raster reading The release also provides minor improvements, as follows: * Raster data/nodata masks, * Improved model broadcasting options, * The Segments.in_mask and Segments.in_perimeter methods
pfdf 1.0.0 pfdf 1.0.0
pfdf: A Python library to facilitate post-wildfire debris-flow hazard assessments and research. This release provides the core functionality needed to implement operational hazard assessments. This includes tools to: * Analyze watersheds * Delineate and filter stream segment networks * Compute earth-system variables for stream segments in a network * Assess debris-flow probabilities...