气候变化对小麦生物量影响的概率预测和不确定性分析

doi:10.11821/xb201203005

摘要/Abstract

摘要： 气候变化对农业生产的影响和适应一直是学界关注的重点。但是,由于气候模式输出、排放情景、尺度转换、模型参数化等研究过程中存在的不确定性,往往导致研究结果也存在较大的不确定性。为减少研究结果的不确定性,本研究综合了IPCC 四个排放情景(A1FI、A2、B1、B2) 以及5 个全球气候模式(HadCM3, PCM, CGCM2, CSIRO2, ECHAM4) 的输出结果,基于英国CRU 气候中心的20 个未来情景数据库,生成全球平均温度升高1℃(GMT+1D)、2℃ (GMT+2D)、3℃ (GMT+3D) 下研究站点的气候日值中值情景数据,利用过程模型CERES-Wheat 和概率预测方法研究CO₂肥效作用和GMT+1D、GMT+2D、GMT+3D对我国小麦主产区小麦生物量的影响。研究结果表明:CO₂肥效作用可以补偿由于温度升高而造成的小麦生物量减产且补偿作用随着温度的升高而增加。当有CO₂肥效作用时,灌溉小麦和雨养小麦生物量均增加,且随着温度的升高生物量的增长程度增大,相同情景下,雨养小麦生物量的增高概率大于灌溉小麦。当不考虑CO₂肥效作用时,灌溉小麦和雨养小麦生物量均降低,且灌溉小麦生物量减产的概率大于雨养小麦减产概率。

关键词: 温度升高, CO₂浓度, 小麦, 生物量, 概率预测

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

刘玉洁, 陶福禄. 气候变化对小麦生物量影响的概率预测和不确定性分析[J]. 地理学报, 2012, 67(3): 337-345.

LIU Yujie, TAO Fulu. Probabilistic Assessment and Uncertainties Analysis of Climate Change Impacts on Wheat Biomass[J]. Acta Geographica Sinica, 2012, 67(3): 337-345.

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