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Drought assessment has been outpaced by climate change: empirical arguments for a paradigm shift

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  • Zachary H. Hoylman

    (University of Montana
    University of Montana)

  • R. Kyle Bocinsky

    (University of Montana
    Crow Canyon Archaeological Center)

  • Kelsey G. Jencso

    (University of Montana
    University of Montana)

Abstract

Despite the acceleration of climate change, erroneous assumptions of climate stationarity are still inculcated in the management of water resources in the United States (US). The US system for drought detection, which triggers billions of dollars in emergency resources, adheres to this assumption with preference towards 60-year (or longer) record lengths for drought characterization. Using observed data from 1,934 Global Historical Climate Network (GHCN) sites across the US, we show that conclusions based on long climate records can substantially bias assessment of drought severity. Bias emerges by assuming that conditions from the early and mid 20th century are as likely to occur in today’s climate. Numerical simulations reveal that drought assessment error is relatively low with limited climatology lengths (~30 year) and that error increases with longer record lengths where climate is changing rapidly. We assert that non-stationarity in climate must be accounted for in contemporary assessments to more accurately portray present drought risk.

Suggested Citation

  • Zachary H. Hoylman & R. Kyle Bocinsky & Kelsey G. Jencso, 2022. "Drought assessment has been outpaced by climate change: empirical arguments for a paradigm shift," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-30316-5
    DOI: 10.1038/s41467-022-30316-5
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    References listed on IDEAS

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    Cited by:

    1. Hrozencik, R. Aaron & Perez-Quesada, Gabriela & Bocinsky, Kyle, 2024. "The Stocking Impact and Financial-Climate Risk of the Livestock Forage Disaster Program," Economic Research Report 340568, United States Department of Agriculture, Economic Research Service.

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