Acta Geographica Sinica ›› 2012, Vol. 67 ›› Issue (3): 337-345.doi: 10.11821/xb201203005

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Probabilistic Assessment and Uncertainties Analysis of Climate Change Impacts on Wheat Biomass

LIU Yujie, TAO Fulu   

  1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • Received:2011-10-24 Revised:2011-12-20 Online:2012-03-20 Published:2012-05-14
  • Supported by:
    National Natural Science Foundation of China, No.41071030

Abstract: Impacts of climate change on agriculture and adaptation are of key concern of scentific research. However, vast uncertainties exist among the global climate models (GCMs)output, emission scenarios, scale transformations, crop model parameteration-simulated outputs. In this study, a probabilistic approach is used to reduce the uncertainties, from 20 climate scenarios output (including four emissions scenarios of A1FI, A2, B1 and B2, and five GCMS of HadCM3, PCM, CGCM2, CSIRO2 and ECHAM4) from the Intergovernmental Panel on Climate Change Data Distribution Centre. We adapt the median values of projected changes in daily mean climate variables for representative stations and drive the CERES (Crop Environment Resource Synthesis)-Wheat model to simulate wheat biomass under baseline condition and global warming scenarios of global mean temperature (GMT) increase of 1 ℃ (GMT+1D), 2 ℃ (GMT+2D) and 3 ℃ (GMT+3D), with and without consideration of CO2 fertilization effects, respectively. Our study results show that elevated CO2 concentration generally compensate for the negative effects of warming temperatures on wheat biomass and the positive effects of elevated CO2 concentration on wheat biomass increase with warming temperatures. There is a high probability of increasing wheat biomass under higher temperature scenarios in consideration for CO2 fertilization effect and rain-fed wheat biomass increase are higher than rain-fed wheat biomass under the same temperature rising scenarios. Due to increase in temperature, projected wheat biomass for GMT + 1D, GMT+2D and GMT+3D would reduce without consideration of CO2 fertilization effects and irrigated wheat biomass would reduce more than rain-fed wheat biomass under the same temperature rising scenarios.

Key words: rising temperature, CO2 concentration, wheat, biomass, probabilistic projection