Contribution of crop model structure, parameters and climate projections to uncertainty in climate change impact assessments

Tao, Fulu, Rötter, Reimund, Palosuo, Taru, Hernández Díaz-Ambrona, Carlos Gregorio ORCID: https://orcid.org/0000-0003-1452-8757, Minguez Tudela, Maria Ines ORCID: https://orcid.org/0000-0002-1966-0653, Semenov, Mikhail A., Kersebaum, K.C., Nendel, Claas, Specka, Xenia, Hoffmann, Holger, Ewert, Frank, Dambreville, Anaelle, Martre, Pierre, Rodríguez Fernández, Lucía, Ruiz Ramos, Margarita ORCID: https://orcid.org/0000-0003-0212-3381, Gaiser, Thomas, Höhn, Jukka, Salo, Tapio, Ferrise, Roberto, Bindi, Marco, Cammarano, Davide and Schulman, Alan H, (2018). Contribution of crop model structure, parameters and climate projections to uncertainty in climate change impact assessments. "Global Change Biology", v. 24 (n. 3); pp. 1291-1307. ISSN 1354-1013. https://doi.org/10.1111/gcb.14019.

Description

Title: Contribution of crop model structure, parameters and climate projections to uncertainty in climate change impact assessments
Author/s:
  • Tao, Fulu
  • Rötter, Reimund
  • Palosuo, Taru
  • Hernández Díaz-Ambrona, Carlos Gregorio https://orcid.org/0000-0003-1452-8757
  • Minguez Tudela, Maria Ines https://orcid.org/0000-0002-1966-0653
  • Semenov, Mikhail A.
  • Kersebaum, K.C.
  • Nendel, Claas
  • Specka, Xenia
  • Hoffmann, Holger
  • Ewert, Frank
  • Dambreville, Anaelle
  • Martre, Pierre
  • Rodríguez Fernández, Lucía
  • Ruiz Ramos, Margarita https://orcid.org/0000-0003-0212-3381
  • Gaiser, Thomas
  • Höhn, Jukka
  • Salo, Tapio
  • Ferrise, Roberto
  • Bindi, Marco
  • Cammarano, Davide
  • Schulman, Alan H,
Item Type: Article
Título de Revista/Publicación: Global Change Biology
Date: March 2018
ISSN: 1354-1013
Volume: 24
Subjects:
Freetext Keywords: barley; climate change; Europe; impact; super-ensemble; uncertainty
Faculty: E.T.S. de Ingeniería Agronómica, Alimentaria y de Biosistemas (UPM)
Department: Producción Agraria
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Climate change impact assessments are plagued with uncertainties from many sources, such as climate projections or the inadequacies in structure and parameters of the impact model. Previous studies tried to account for the uncertainty from one or two of these. Here, we developed a triple-ensemble probabilistic assessment using seven crop models, multiple sets of model parameters and eight contrasting climate projections together to comprehensively account for uncertainties from these three important sources. We demonstrated the approach in assessing climate change impact on barley growth and yield at Jokioinen, Finland in the Boreal climatic zone and Lleida, Spain in the Mediterranean climatic zone, for the 2050s. We further quantified and compared the contribution of crop model structure, crop model parameters and climate projections to the total variance of ensemble output using Analysis of Variance (ANOVA). Based on the triple-ensemble probabilistic assessment, the median of simulated yield change was 4% and +16%, and the probability of decreasing yield was 63% and 31% in the 2050s, at Jokioinen and Lleida, respectively, relative to 1981–2010. The contribution of crop model structure to the total variance of ensemble output was larger than that from downscaled climate projections and model parameters. The relative contribution of crop model parameters and downscaled climate projections to the total variance of ensemble output varied greatly among the seven crop models and between the two sites. The contribution of downscaled climate projections was on average larger than that of crop model parameters. This information on the uncertainty from different sources can be quite useful for model users to decide where to put the most effort when preparing or choosing models or parameters for impact analyses. We concluded that the triple-ensemble probabilistic approach that accounts for the uncertainties from multiple important sources provide more comprehensive information for quantifying uncertainties in climate change impact assessments as compared to the conventional approaches that are deterministic or only account for the uncertainties from one or two of the uncertainty sources.

Funding Projects

Type
Code
Acronym
Leader
Title
Government of Spain
CGL2012-38923-C02-02
Unspecified
Unspecified
Variabilidad climática multiescalar. Impactos agrícolas y económicos. II evaluación integrada de riesgos climáticos y económicos: adaptación de sistemas agrícolas en España
FP7
613556
WHEALBI
Unspecified
Wheat and barley Legacy for Breeding Improvement

More information

Item ID: 54937
DC Identifier: https://oa.upm.es/54937/
OAI Identifier: oai:oa.upm.es:54937
DOI: 10.1111/gcb.14019
Official URL: https://onlinelibrary.wiley.com/doi/abs/10.1111/gc...
Deposited by: Memoria Investigacion
Deposited on: 04 Jun 2019 11:56
Last Modified: 04 Jun 2019 11:56
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