DOI: 10.1007/s10584-015-1518-8
Scopus记录号: 2-s2.0-84951569418
论文题名: Comparing correction methods of RCM outputs for improving crop impact projections in the Iberian Peninsula for 21st century
作者: Ruiz-Ramos M. ; Rodríguez A. ; Dosio A. ; Goodess C.M. ; Harpham C. ; Mínguez M.I. ; Sánchez E.
刊名: Climatic Change
ISSN: 0165-0009
EISSN: 1573-1480
出版年: 2016
卷: 134, 期: 2018-01-02 起始页码: 283
结束页码: 297
语种: 英语
Scopus关键词: Climate change
; Crops
; Climate change impact
; Correction method
; Correction performance
; Growth and development
; Impact assessments
; Modeling variability
; Postprocessing methods
; Regional climate models
; Climate models
; agricultural management
; agricultural modeling
; agrometeorology
; climate change
; climate modeling
; comparative study
; crop yield
; cropping practice
; data set
; error correction
; maize
; orography
; phenology
; Iberian Peninsula
; Zea mays
英文摘要: 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. © 2015, Springer Science+Business Media Dordrecht.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/84421
Appears in Collections: 气候减缓与适应 气候变化事实与影响
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作者单位: CEIGRAM-Agricultural Systems Group from Technical University of Madrid, Madrid, Spain; European Commission Joint Research Centre, Institute for Environment and Sustainability, Ispra, Italy; Climatic Research Unit, School of Environmental Sciences, University of East Anglia, Norwich, United Kingdom; Facultad de Ciencias del Medio Ambiente, University of Castilla-La Mancha, Avda. Carlos III s/n, Toledo, Spain
Recommended Citation:
Ruiz-Ramos M.,Rodríguez A.,Dosio A.,et al. Comparing correction methods of RCM outputs for improving crop impact projections in the Iberian Peninsula for 21st century[J]. Climatic Change,2016-01-01,134(2018-01-02)