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Comparing correction methods of RCM outputs for improving crop impact projections in the Iberian Peninsula for 21st century

Author

Listed:
  • M. Ruiz-Ramos
  • A. Rodríguez
  • A. Dosio
  • C. Goodess
  • C. Harpham
  • M. Mínguez
  • E. Sánchez

Abstract

Assessment of climate change impacts on crops in regions of complex orography such as the Iberian Peninsula (IP) requires climate model output which is able to describe accurately the observed climate. The high resolution of output provided by Regional Climate Models (RCMs) is expected to be a suitable tool to describe regional and local climatic features, although their simulation results may still present biases. For these reasons, we compared several post-processing methods to correct or reduce the biases of RCM simulations from the ENSEMBLES project for the IP. The bias-corrected datasets were also evaluated in terms of their applicability and consequences in improving the results of a crop model to simulate maize growth and development at two IP locations, using this crop as a reference for summer cropping systems in the region. The use of bias-corrected climate runs improved crop phenology and yield simulation overall and reduced the inter-model variability and thus the uncertainty. The number of observational stations underlying each reference observational dataset used to correct the bias affected the correction performance. Although no single technique showed to be the best one, some methods proved to be more adequate for small initial biases, while others were useful when initial biases were so large as to prevent data application for impact studies. An initial evaluation of the climate data, the bias correction/reduction method and the consequences for impact assessment would be needed to design the most robust, reduced uncertainty ensemble for a specific combination of location, crop, and crop management. Copyright Springer Science+Business Media Dordrecht 2016

Suggested Citation

  • M. Ruiz-Ramos & A. Rodríguez & A. Dosio & C. Goodess & C. Harpham & M. Mínguez & E. Sánchez, 2016. "Comparing correction methods of RCM outputs for improving crop impact projections in the Iberian Peninsula for 21st century," Climatic Change, Springer, vol. 134(1), pages 283-297, January.
  • Handle: RePEc:spr:climat:v:134:y:2016:i:1:p:283-297
    DOI: 10.1007/s10584-015-1518-8
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    References listed on IDEAS

    as
    1. Enrique Sánchez & Marta Domínguez & Raquel Romera & Noelia López de la Franca & Miguel Gaertner & Clemente Gallardo & Manuel Castro, 2011. "Regional modeling of dry spells over the Iberian Peninsula for present climate and climate change conditions," Climatic Change, Springer, vol. 107(3), pages 625-634, August.
    2. Fredrik Boberg & Jens H. Christensen, 2012. "Overestimation of Mediterranean summer temperature projections due to model deficiencies," Nature Climate Change, Nature, vol. 2(6), pages 433-436, June.
    3. Marc Stéfanon & Nicolas Martin-StPaul & Paul Leadley & Sophie Bastin & Alessandro Dell’Aquila & Philippe Drobinski & Clemente Gallardo, 2015. "Testing climate models using an impact model: what are the advantages?," Climatic Change, Springer, vol. 131(4), pages 649-661, August.
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    Cited by:

    1. Rodríguez, Alfredo & Pérez-López, David & Centeno, Ana & Ruiz-Ramos, Margarita, 2021. "Viability of temperate fruit tree varieties in Spain under climate change according to chilling accumulation," Agricultural Systems, Elsevier, vol. 186(C).
    2. Bin Wang & De Li Liu & Cathy Waters & Qiang Yu, 2018. "Quantifying sources of uncertainty in projected wheat yield changes under climate change in eastern Australia," Climatic Change, Springer, vol. 151(2), pages 259-273, November.
    3. Heiko Paeth & Daniel Schönbein & Luzia Keupp & Daniel Abel & Freddy Bangelesa & Miriam Baumann & Christian Büdel & Christian Hartmann & Christof Kneisel & Konstantin Kobs & Julian Krause & Martin Krec, 2023. "Climate change information tailored to the agricultural sector in Central Europe, exemplified on the region of Lower Franconia," Climatic Change, Springer, vol. 176(10), pages 1-24, October.
    4. Alessandro Dosio & Christopher Lennard & Jonathan Spinoni, 2022. "Projections of indices of daily temperature and precipitation based on bias-adjusted CORDEX-Africa regional climate model simulations," Climatic Change, Springer, vol. 170(1), pages 1-24, January.

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