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温度升高和CO_2浓度增加对冬小麦生物量的影响和不确定性分析(英文) 被引量:1

Impacts and uncertainty analysis of elevated temperature and CO_2 concentration on wheat biomass
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摘要 Impacts of climatic change on agriculture and adaptation are of key concern of scientific research. However, vast uncertainties exist among global climates model output, emission scenarios, scale transformation and crop model parameterization. In order to reduce these uncertainties, we integrate output results of four IPCC emission scenarios of A1FI, A2, B1 and B2, and five global climatic patterns of HadCM3, PCM, CGCM2, CSIRO2 and ECHAM4 in this study. Based on 20 databases of future climatic change scenarios from the Climatic Research Unit (CRU) , the scenario data of the climatic daily median values are generated on research sites with the global mean temperature increase of 1 ℃(GMT+1D), 2 ℃ (GMT+2D) and 3 ℃(GMT+3D). The impact of CO2 fertilization effect on wheat biomass for GMT+1D, GMT+2D and GMT+3D in China's wheat-producing areas is studied in the process model, CERES-Wheat and probabilistic forecasting method. The research results show the CO2 fertilization effect can compensate reduction of wheat biomass with warming temperature in a strong compensating effect. Under the CO2 fertilization effect, the rain-fed and irrigated wheat biomasses increase respectively, and the increment of biomass goes up with temperature rising. The rain-fed wheat biomass increase is greater than the irrigated wheat biomass. Without consideration of CO2 fertilization effect, both irrigated and rain-fed wheat biomasses reduce, and there is a higher probability for the irrigated wheat biomass than that of the rain-fed wheat biomass. Impacts of climatic change on agriculture and adaptation are of key concern of scientific research. However, vast uncertainties exist among global climates model output, emission scenarios, scale transformation and crop model parameterization. In order to reduce these uncertainties, we integrate output results of four IPCC emission scenarios of A1 FI, A2, B1 and B2, and five global climatic patterns of HadCM3, PCM, CGCM2, CSIRO2 and ECHAM4 in this study. Based on 20 databases of future climatic change scenarios from the Climatic Research Unit (CRU) , the scenario data of the climatic daily median values are generated on research sites with the global mean temperature increase of 1℃(GMT+ID), 2℃(GMT+2D) and 3℃(GMT+3D). The impact of CO2 fertilization effect on wheat biomass for GMT+I D, GMT+2D and GMT+3D in China's wheat-producing areas is studied in the process model, CERES-Wheat and probabilistic forecasting method. The research results show the CO2 fertilization effect can compensate reduction of wheat biomass with warming temperature in a strong compensating effect. Under the CO2 fertilization effect, the rain-fed and irrigated wheat biomasses increase respectively, and the increment of biomass goes up with temperature rising. The rain-fed wheat biomass increase is greater than the irrigated wheat biomass. Without consideration of CO2 fertilization effect, both irrigated and rain-fed wheat biomasses reduce, and there is a higher probability for the irrigated wheat biomass than that of the rain-fed wheat biomass.
出处 《Journal of Geographical Sciences》 SCIE CSCD 2012年第6期1002-1012,共11页 地理学报(英文版)
基金 National Natural Science Foundation of China, No.41071030
关键词 不确定性分析 CO2浓度 平均温度 生物量 小麦 未来气候变化 全球气候模型 概率预报方法 rising temperature CO2 concentration wheat, biomass probabilistic projection
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