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Frances V Davenport

Biographic Data

ID7999775
NAMEFrances V Davenport
GIVEN NAMESFrances V
FAMILY NAMEDavenport
SIGNATUREDAVENPORT F V
AFFILIATIONSStanford University
ORCID0000-0002-3061-2062
VERIFIEDYes
TOTAL WORKS3
TOTAL CITATIONS0
WORKS AS AUTHOR3
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2021
LATEST PUBLICATION YEAR2023
H-INDEX0
  • Separating internal and forced contributions to near term SST predictability in the Cesm2-LE

    Open Access•Emily M Gordon, Elizabeth A Barnes et al.•ARTICLE•Environmental Research Letters•2023

    An open question in the study of climate prediction is whether internal variability will continue to contribute to prediction skill in the coming decades, or whether predictable signals will be overwhelmed by rising temperatures driven by anthropogenic forcing. We design a neural network that is interpretable such that its predictions can be decomposed to examine the relative contributions of external forcing and internal variability to future re…

  • On the impossibility of extreme event thresholds in the absence of global warming

    Open Access•Noah S Diffenbaugh, Frances V Davenport•ARTICLE•Environmental Research Letters•2021

    The exceptional severity of recent climate extremes has raised the question of whether some events would have been impossible in the absence of global warming. This question is critical for climate adaptation, but is challenging to answer given the length and non-stationarity of the observational record. The large single-model ensemble climate simulations archived in the Coupled Model Intercomparison Project (CMIP6) offer a unique opportunity to …

  • Historical warming has increased U.S. crop insurance losses

    Open Access•Noah S Diffenbaugh, Frances V Davenport et al.•ARTICLE•Environmental Research Letters•2021

    Quantification of the sector-specific financial impacts of historical global warming represents a critical gap in climate change impacts assessment. The multiple decades of county-level data available from the U.S. crop insurance program—which collectively represent aggregate damages to the agricultural sector largely borne by U.S. taxpayers—present a unique opportunity to close this gap. Using econometric analysis in combination with observed an…

No prominent works on this page.

  • On the impossibility of extreme event thresholds in the absence of global warming

    Open Access•Noah S Diffenbaugh, Frances V Davenport•ARTICLE•Environmental Research Letters•2021

    The exceptional severity of recent climate extremes has raised the question of whether some events would have been impossible in the absence of global warming. This question is critical for climate adaptation, but is challenging to answer given the length and non-stationarity of the observational record. The large single-model ensemble climate simulations archived in the Coupled Model Intercomparison Project (CMIP6) offer a unique opportunity to …

  • Historical warming has increased U.S. crop insurance losses

    Open Access•Noah S Diffenbaugh, Frances V Davenport et al.•ARTICLE•Environmental Research Letters•2021

    Quantification of the sector-specific financial impacts of historical global warming represents a critical gap in climate change impacts assessment. The multiple decades of county-level data available from the U.S. crop insurance program—which collectively represent aggregate damages to the agricultural sector largely borne by U.S. taxpayers—present a unique opportunity to close this gap. Using econometric analysis in combination with observed an…

  • Separating internal and forced contributions to near term SST predictability in the Cesm2-LE

    Open Access•Emily M Gordon, Elizabeth A Barnes et al.•ARTICLE•Environmental Research Letters•2023

    An open question in the study of climate prediction is whether internal variability will continue to contribute to prediction skill in the coming decades, or whether predictable signals will be overwhelmed by rising temperatures driven by anthropogenic forcing. We design a neural network that is interpretable such that its predictions can be decomposed to examine the relative contributions of external forcing and internal variability to future re…

Climate change (3 works) · Environmental Science (3 works) · Climate model (2 works) · Climate variability and models (2 works) · Climatology (2 works) · Forcing (mathematics (2 works) · Geography (2 works) · Geology (2 works) · Global warming (2 works) · Meteorological Phenomena and Simulations (2 works)

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