ecological modelling 213 ( 2 0 0 8 ) 365–380 available at www.sciencedirect.com journal homepage: www.elsevier.com/locate/ecolmodel A crop model cross calibration for use in regional climate impacts studies Wei Xiong a,b,* , Ian Holman c , Declan Conway d , Erda Lin a,b , Yue Li a,b a Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing 100081, China b The Key Laboratory for Agro-Environment & Climate Change, Ministry of Agriculture, Beijing 100081, China c Natural Resources Department, Cranfield University, Bedfordshire MK43 0AL, United Kingdom d University of East Anglia, Norwich NR4 7TJ, United Kingdom article info Article history: Received 12 December 2006 Received in revised form 23 December 2007 Accepted 9 January 2008 Published on line 7 March 2008 Keywords: Calibration Crop model Climate change abstract Crop simulation models are widely used to assess the impacts of and adaptation to climate change in relation to agricultural production. However, a substantial mismatch often exists between the spatial and temporal scale of available data and the requirements of crop sim- ulation models. Conventional model calibration methods which concentrate on a model’s performance at plot scale cannot be used for large scale regional simulation (especially for climate change impacts assessments), given the limited observed data and the iterative cal- ibration needed. One primary purpose of regional simulation is to predict the spatial yield variation and temporal yield fluctuation. This purpose could be fulfilled through model input calibration in which the objective of the calibration focuses on spatial or temporal agreement between simulated and observed values. This study examines the performance of CERES-Rice at the regional scale across China using a cross calibration process based on limited experiment data, agroecological zones (AEZ) and 50 km × 50 km grid scale geograph- ical database. Model performance is evaluated using rice yields from experimental sites at the plot scale, and/or observed yield data at the county scale. Results suggest: the CERES-Rice model was able to simulate the site-specific rice production with good performance in most of China, with a root mean square error (RMSE) = 991 kg ha -1 and a relative RMSE = 14.9% for yield across China. The cross calibration process, in which AEZ-scale parameter val- ues were derived, gave a relative bigger bias to yield estimation, with a RMSE = 1485 kg ha -1 and a relative RMSE = 22.5%, but achieved a reasonable agreement with observed maturity day and yield at spatial scale. The bias rose further if this cross calibrated model was used to simulate the real farmer rice yields at a regional scale, with a RMSE = 2191 kg ha -1 and relative RMSE = 34% across China. The pattern of yield variation was captured spatially by the model in most of the rice planting areas, but not temporally. The sources of uncer- tainties were analyzed for both plot scale and regional scale simulation. This calibration process could be incorporated into climate change integrated assessment and adaptation assessment, especially for those developing counties with limited observed data. © 2008 Elsevier B.V. All rights reserved. ∗ Corresponding author at: Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing 100081, China. Tel.: +86 10 68919571 3606; fax: +86 10 62116981. E-mail address: Xiongw@ami.ac.cn (W. Xiong). 0304-3800/$ – see front matter © 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.ecolmodel.2008.01.005