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Regional Environmental Change

, Volume 13, Supplement 1, pp 101–110 | Cite as

Evaluating the fidelity of downscaled climate data on simulated wheat and maize production in the southeastern US

  • Davide Cammarano
  • Lydia Stefanova
  • Brenda V. Ortiz
  • Melissa Ramirez-Rodrigues
  • Senthold Asseng
  • Vasubandhu Misra
  • Gail Wilkerson
  • Bruno Basso
  • James W. Jones
  • Kenneth J. Boote
  • Steven DiNapoli
Original Article

Abstract

Crop models are one of the most commonly used tools to assess the impact of climate variability and change on crop production. However, before the impact of projected climate changes on crop production can be addressed, a necessary first step is the assessment of the inherent uncertainty and limitations of the forcing data used in these crop models. In this paper, we evaluate the simulated crop production using separate crop models for maize (summer crop) and wheat (winter crop) over six different locations in the Southeastern United States forced with multiple sources of actual and simulated weather data. The paper compares the crop production simulated by a crop model for maize and wheat during a historical period, using daily weather data from three sources: station observations, dynamically downscaled global reanalysis, and dynamically downscaled historical climate model simulations from two global circulation models (GCMs). The same regional climate model is used to downscale the global reanalysis and both global circulation models’ historical simulation. The average simulated yield derived from bias-corrected downscaled reanalysis or bias-corrected downscaled GCMs were, in most cases, not statistically different from observations. Statistical differences of the average yields, generated from observed or downscaled GCM weather, were found in some locations under rainfed and irrigated scenarios, and more frequently in winter (wheat) than in summer (maize). The inter-annual variance of simulated crop yield using GCM downscaled data was frequently overestimated, especially in summer. An analysis of the bias-corrected climate data showed that despite the agreement between the modeled and the observed means of temperatures, solar radiation, and precipitation, their intra-seasonal variances were often significantly different from observations. Therefore, due to this high intra-seasonal variability, a cautious approach is required when using climate model data for historical yield analysis and future climate change impact assessments.

Keywords

Crop simulation models Climate variability Global circulation models Reanalysis Wheat Maize 

Notes

Acknowledgments

The authors would like to thank two anonymous reviewers for constructive comments.

Supplementary material

10113_2013_410_MOESM1_ESM.docx (140 kb)
Supplementary material 1 (DOCX 141 kb)

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Davide Cammarano
    • 1
  • Lydia Stefanova
    • 2
  • Brenda V. Ortiz
    • 3
  • Melissa Ramirez-Rodrigues
    • 1
  • Senthold Asseng
    • 1
  • Vasubandhu Misra
    • 2
    • 4
    • 5
  • Gail Wilkerson
    • 6
  • Bruno Basso
    • 7
  • James W. Jones
    • 8
  • Kenneth J. Boote
    • 1
  • Steven DiNapoli
    • 2
  1. 1.Department of Agricultural and Biological EngineeringUniversity of FloridaGainesvilleUSA
  2. 2.Center for Ocean-Atmospheric Prediction Studies, College of Arts and SciencesFlorida State UniversityTallahasseeUSA
  3. 3.Agronomy and SoilsAuburn UniversityAuburnUSA
  4. 4.Earth, Ocean and Atmospheric Sci and Center for Ocean-Atmospheric Prediction Studies, College of Arts and SciencesFlorida State UniversityTallahasseeUSA
  5. 5.Florida Climate InstituteFlorida State UniversityTallahasseeUSA
  6. 6.Department of Crop ScienceNorth Carolina State UniversityRaleighUSA
  7. 7.Department of Geological Sciences and WK Kellogg Biological StationMichigan State UniversityEast LansingUSA
  8. 8.Florida Climate InstituteUniversity of FloridaGainesvilleUSA

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