Publications
You can also find a list of publications on Google Scholar.
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Trok, J. T., E. A. Barnes, F. V. Davenport, and N. S. Diffenbaugh
(2024)
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Machine learning–based extreme event attribution,
Science Advances,
https://doi.org/10.1126/sciadv.adl3242
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Davenport, F. V., E. A. Barnes, and E. M. Gordon
(2024)
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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
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Gordon, E. M., E. A. Barnes, and F. V. Davenport
(2023)
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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
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Trok, J. T., F. V. Davenport, E. A. Barnes and N. S. Diffenbaugh
(2023)
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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
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Ly, A., F. V. Davenport, and N. S. Diffenbaugh
(2023)
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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
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Yu, G., D. B. Wright, and F. V. Davenport
(2022)
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Diverse Physical Processes Drive Upper-Tail Flood Quantiles in the US Mountain West,
Geophysical Research Letters,
https://doi.org/10.1029/2022GL098855
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See media coverage in: Desert Research Institute, CSU News, NSF -
Diffenbaugh, N. S., and F. V. Davenport
(2021)
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On the impossibility of extreme event thresholds in the absence of global warming,
Environmental Research Letters,
https://doi.org/10.1088/1748-9326/ac2f1a
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Johnston, E. C., F. V. Davenport, L. Wang, J. K. Caers, S. Muthukrishnan, M. Burke, and N. S. Diffenbaugh
(2021)
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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 -
Davenport, F. V., and N. S. Diffenbaugh
(2021)
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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
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See media coverage in: Stanford News, Stanford Woods Institute (video) -
Diffenbaugh, N. S., F. V. Davenport, and M. Burke
(2021)
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Historical warming has increased U.S. crop insurance losses,
Environmental Research Letters,
https://doi.org/10.1088/1748-9326/ac1223
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See media coverage in: Stanford News, Scientific American -
Simpson, I. R., K. A. McKinnon, F. V. Davenport, M. Tingley, F. Lehner, A. Al Fahad, and D. Chen
(2021)
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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
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Davenport, F. V., M. Burke, and N. S. Diffenbaugh
(2021)
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Contribution of historical precipitation change to US flood damages,
Proceedings of the National Academy of Sciences,
https://doi.org/10.1073/pnas.2017524118
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See media coverage in: Washington Post, SF Chronicle, Bloomberg, CBS News, Reuters, CNBC, Earther, Stanford News -
Davenport, F. V., J. E. Herrera-Estrada, M. Burke, and N. S. Diffenbaugh
(2020)
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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
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See media coverage in: Stanford News