Publications

You can also find a list of publications on Google Scholar.

  1. Kalashnikov, D. A., F. V. Davenport, Z. M. Labe, P. C. Loikith, J. T. Abatzoglou, and D. Singh (2024) . Predicting Cloud‐To‐Ground Lightning in the Western United States From the Large‐Scale Environment Using Explainable Neural Networks, Journal of Geophysical Research: Atmospheres, https://doi.org/10.1029/2024JD042147

  2. Trok, J. T., E. A. Barnes, F. V. Davenport, and N. S. Diffenbaugh (2024) . Machine learning–based extreme event attribution, Science Advances, https://doi.org/10.1126/sciadv.adl3242 | PDF

  3. Davenport, F. V., E. A. Barnes, and E. M. Gordon (2024) . Combining Neural Networks and CMIP6 Simulations to Learn Windows of Opportunity for Skillful Prediction of Multiyear Sea Surface Temperature Variability, Geophysical Research Letters, https://doi.org/10.1029/2023GL108099 | PDF

  4. Gordon, E. M., E. A. Barnes, and F. V. Davenport (2023) . Separating internal and forced contributions to near term SST predictability in the CESM2-LE, Environmental Research Letters, https://doi.org/10.1088/1748-9326/acfdbc | PDF

  5. Trok, J. T., F. V. Davenport, E. A. Barnes and N. S. Diffenbaugh (2023) . Using Machine Learning with Partial Dependence Analysis to Investigate Coupling Between Soil Moisture and Near-surface Temperature, Journal of Geophysical Research: Atmospheres, https://doi.org/10.1029/2022JD038365 | PDF

  6. Ly, A., F. V. Davenport, and N. S. Diffenbaugh (2023) . Exploring the Influence of Summer Temperature on Human Mobility During the COVID-19 Pandemic in the San Francisco Bay Area, GeoHealth, https://doi.org/10.1029/2022GH000772 | PDF

  7. Yu, G., D. B. Wright, and F. V. Davenport (2022) . Diverse Physical Processes Drive Upper-Tail Flood Quantiles in the US Mountain West, Geophysical Research Letters, https://doi.org/10.1029/2022GL098855 | PDF
    See media coverage in: Desert Research Institute, CSU News, NSF

  8. Diffenbaugh, N. S., and F. V. Davenport (2021) . On the impossibility of extreme event thresholds in the absence of global warming, Environmental Research Letters, https://doi.org/10.1088/1748-9326/ac2f1a | PDF

  9. Johnston, E. C., F. V. Davenport, L. Wang, J. K. Caers, S. Muthukrishnan, M. Burke, and N. S. Diffenbaugh (2021) . Quantifying the effect of precipitation on landslide hazard in urbanized and non-urbanized areas, Geophysical Research Letters, https://doi.org/10.1029/2021GL094038
    See media coverage in: AGU News

  10. Davenport, F. V., and N. S. Diffenbaugh (2021) . Using Machine Learning to Analyze Physical Causes of Climate Change: A Case Study of U.S. Midwest Extreme Precipitation, Geophysical Research Letters, https://doi.org/10.1029/2021GL093787 | PDF
    See media coverage in: Stanford News, Stanford Woods Institute (video)

  11. Diffenbaugh, N. S., F. V. Davenport, and M. Burke (2021) . Historical warming has increased U.S. crop insurance losses, Environmental Research Letters, https://doi.org/10.1088/1748-9326/ac1223 | PDF
    See media coverage in: Stanford News, Scientific American

  12. Simpson, I. R., K. A. McKinnon, F. V. Davenport, M. Tingley, F. Lehner, A. Al Fahad, and D. Chen (2021) . Emergent constraints on the large scale atmospheric circulation and regional hydroclimate: do they still work in CMIP6 and how much can they actually constrain the future?, Journal of Climate, https://doi.org/10.1175/JCLI-D-21-0055.1 | PDF

  13. Davenport, F. V., M. Burke, and N. S. Diffenbaugh (2021) . Contribution of historical precipitation change to US flood damages, Proceedings of the National Academy of Sciences, https://doi.org/10.1073/pnas.2017524118 | PDF
    See media coverage in: Washington Post, SF Chronicle, Bloomberg, CBS News, Reuters, CNBC, Earther, Stanford News

  14. Davenport, F. V., J. E. Herrera-Estrada, M. Burke, and N. S. Diffenbaugh (2020) . Flood size increases nonlinearly across the western United States in response to lower snow‐precipitation ratios, Water Resources Research, https://doi.org/10.1029/2019WR025571 | PDF
    See media coverage in: Stanford News

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