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International Journal of Biometeorology

, Volume 60, Issue 7, pp 935–944 | Cite as

Dynamically downscaling predictions for deciduous tree leaf emergence in California under current and future climate

  • David MedvigyEmail author
  • Seung Hee Kim
  • Jinwon Kim
  • Menas C. Kafatos
Original Paper

Abstract

Models that predict the timing of deciduous tree leaf emergence are typically very sensitive to temperature. However, many temperature data products, including those from climate models, have been developed at a very coarse spatial resolution. Such coarse-resolution temperature products can lead to highly biased predictions of leaf emergence. This study investigates how dynamical downscaling of climate models impacts simulations of deciduous tree leaf emergence in California. Models for leaf emergence are forced with temperatures simulated by a general circulation model (GCM) at ~200-km resolution for 1981–2000 and 2031–2050 conditions. GCM simulations are then dynamically downscaled to 32- and 8-km resolution, and leaf emergence is again simulated. For 1981–2000, the regional average leaf emergence date is 30.8 days earlier in 32-km simulations than in ~200-km simulations. Differences between the 32 and 8 km simulations are small and mostly local. The impact of downscaling from 200 to 8 km is ~15 % smaller in 2031–2050 than in 1981–2000, indicating that the impacts of downscaling are unlikely to be stationary.

Keywords

Leaf emergence California Dynamical downscaling Valley oak Climate change 

Notes

Acknowledgments

This work was supported by the Agriculture and Food Research Initiative of the US Department of Agriculture National institute of Food and Agriculture grant 2011-67004-30224. The observed budburst data were provided by the USA National Phenology Network (http://www.usanpn.org) and the many participants who contribute to its Natures Notebook program. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modeling, which is responsible for CMIP, and we thank the climate modeling groups for producing and making available their model output. For CMIP, the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development for software infrastructure in partnership with the Global Organization for Earth System Science Portals. We thank two anonymous reviewers for their helpful comments.

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Copyright information

© ISB 2015

Authors and Affiliations

  • David Medvigy
    • 1
    Email author
  • Seung Hee Kim
    • 2
  • Jinwon Kim
    • 3
  • Menas C. Kafatos
    • 2
  1. 1.Department of GeosciencesPrinceton UniversityPrincetonUSA
  2. 2.Center for Earth Systems Science and Observations, Schmid College of ScienceChapman UniversityOrangeUSA
  3. 3.Joint Institute for Regional Earth System Science and EngineeringUniversity of California, Los AngelesLos AngelesUSA

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