Adapting wheat ideotypes for climate change: accounting for uncertainties in CMIP5 climate projections
Adapting wheat ideotypes for climate change: accounting for uncertainties in CMIP5 climate projections
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DOI：
10.3354/cr01297
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发表时间：
2015-01-01
期刊：
影响因子：
1.1
通讯作者：
Stratonovitch, Pierre
中科院分区：
文献类型：
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作者：
Semenov, Mikhail A.;Stratonovitch, Pierre
本研究介绍了从耦合模式相互比较项目第5阶段（CMIP 5）多模式集合与LARS-WG天气发生器，它提供了一个有吸引力的选择，从全球气候模型（GCMs）的大尺度气候预测降尺度到当地规模的气候情景的影响评估气候变化预测的集成。来自CMIP 5集合的18个GCM子集和2个代表性浓度途径（RCP）RCP4.5和RCP8.5与LARS-WG集成。对于需要计算的影响评估，如果不可能探索GCM x RCP的所有可能组合，则可以使用气候敏感性指数来选择保留CMIP中发现的不确定性范围的GCM子集5。这将使我们能够通过进行更少的模拟实验来量化CMIP 5集合产生的影响预测的不确定性。在一个案例研究中，我们描述了使用天狼星小麦模拟模型来设计针对欧洲未来气候进行优化的计算机小麦ideotypes，GCM中的采样不确定性，排放情景，时间段和欧洲地区的气候对比。选择了两种对比的GCM进行分析，“热”HadGEM 2-ES和“冷”GISS-E2-R-CC。尽管未来气候预测存在很大的不确定性，但我们能够确定小麦改良的目标性状，这可能有助于培育产量稳定性更高的高产小麦品种。
This study describes integration of climate change projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model ensemble with the LARS-WG weather generator, which delivers an attractive option for the downscaling of large-scale climate projections from global climate models (GCMs) to local-scale climate scenarios for impact assessments. A subset of 18 GCMs from the CMIP5 ensemble and 2 Representative Concentration Pathways (RCPs), RCP4.5 and RCP8.5, were integrated with LARS-WG. For computationally de manding im pact assessments, where it is not practical to explore all possible combinations of GCM x RCP, a climate sensitivity index could be used to select a subset of GCMs which preserves the range of uncertainty found in CMIP5. This would allow us to quantify uncertainty in predictions of impacts resulting fromthe CMIP5 ensemble by conducting fewer simulation experiments. In a case study, we describe the use of the Sirius wheat simulation model to design in silico wheat ideotypes that are optimised for future climates in Europe, sampling uncertainty in GCMs, emission scenarios, time periods and European locations with contrasting climates. Two contrasting GCMs were selected for the analysis, 'hot' HadGEM2-ES and 'cool' GISS-E2-R-CC. Despite large uncertainty in future climate projections, we were able to identify target traits for wheat improvement which may assist breeding for high-yielding wheat cultivars with increased yield stability.