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Coordinating AgMIP data and models across global and regional scales for 1.5°C and 2.0°C assessments

机译:协调全球和区域范围内的AgMIP数据和模型以进行1.5°C和2.0°C评估

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摘要

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has developed novel methods for Coordinated Global and Regional Assessments (CGRA) of agriculture and food security in a changing world. The present study aims to perform a proof of concept of the CGRA to demonstrate advantages and challenges of the proposed framework. This effort responds to the request by the UN Framework Convention on Climate Change (UNFCCC) for the implications of limiting global temperature increases to 1.5°C and 2.0°C above pre-industrial conditions. The protocols for the 1.5°C/2.0°C assessment establish explicit and testable linkages across disciplines and scales, connecting outputs and inputs from the Shared Socio-economic Pathways (SSPs), Representative Agricultural Pathways (RAPs), Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) and Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble scenarios, global gridded crop models, global agricultural economics models, site-based crop models and within-country regional economics models. The CGRA consistently links disciplines, models and scales in order to track the complex chain of climate impacts and identify key vulnerabilities, feedbacks and uncertainties in managing future risk. CGRA proof-of-concept results show that, at the global scale, there are mixed areas of positive and negative simulated wheat and maize yield changes, with declines in some breadbasket regions, at both 1.5°C and 2.0°C. Declines are especially evident in simulations that do not take into account direct CO2 effects on crops. These projected global yield changes mostly resulted in increases in prices and areas of wheat and maize in two global economics models. Regional simulations for 1.5°C and 2.0°C using site-based crop models had mixed results depending on the region and the crop. In conjunction with price changes from the global economics models, productivity declines in the Punjab, Pakistan, resulted in an increase in vulnerable households and the poverty rate.This article is part of the theme issue ‘The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'.
机译:农业模型比对和改进项目(AgMIP)开发了新颖的方法,用于在不断变化的世界中对农业和粮食安全进行协调的全球和区域评估(CGRA)。本研究旨在对CGRA进行概念验证,以证明所提出框架的优势和挑战。这项工作是对《联合国气候变化框架公约》(UNFCCC)提出的要求的回应,该要求是将全球温度限制在工业化前的温度之上1.5°C和2.0°C的影响。 1.5°C / 2.0°C评估的协议建立了跨学科和规模的明确且可测试的链接,将共享的社会经济途径(SSP),代表性农业途径(RAP)的输出和输入连接起来,半度附加变暖,预后和预计影响(HAPPI)和耦合模型比对项目第5阶段(CMIP5)集成方案,全球网格化作物模型,全球农业经济学模型,基于站点的作物模型和国家内部区域经济学模型。 CGRA始终将学科,模型和规模联系在一起,以跟踪复杂的气候影响链,并确定管理未来风险的关键脆弱性,反馈和不确定性。 CGRA概念验证结果表明,在全球范围内,模拟小麦和玉米单产变化的正负混合区域,在1.5°C和2.0°C的某些面包篮区域均有下降。在不考虑直接CO2对作物的影响的模拟中,下降尤为明显。这些预计的全球单产变化主要导致两种全球经济学模型中小麦和玉米的价格和面积增加。使用基于站点的作物模型对1.5°C和2.0°C进行的区域模拟根据区域和作物的不同而得出的结果也不尽相同。结合全球经济学模型的价格变化,巴基斯坦旁遮普邦的生产力下降,导致脆弱家庭的增加和贫困率的增加。本文是主题“巴黎协定:了解物质和社会挑战”的一部分使其温度比工业化前的水平高1.5°C。

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