Rosenzweig Cynthia, Ruane Alex C, Antle John, Elliott Joshua, Ashfaq Muhammad, Chatta Ashfaq Ahmad, Ewert Frank, Folberth Christian, Hathie Ibrahima, Havlik Petr, Hoogenboom Gerrit, Lotze-Campen Hermann, MacCarthy Dilys S, Mason-D'Croz Daniel, Contreras Erik Mencos, Müller Christoph, Perez-Dominguez Ignacio, Phillips Meridel, Porter Cheryl, Raymundo Rubi M, Sands Ronald D, Schleussner Carl-Friedrich, Valdivia Roberto O, Valin Hugo, Wiebe Keith
Goddard Institute for Space Studies, National Aeronautics and Space Administration, 2880 Broadway, New York, NY 10025, USA
Center for Climate Systems Research, Columbia University, 2880 Broadway, New York, NY 10025, USA.
Philos Trans A Math Phys Eng Sci. 2018 May 13;376(2119). doi: 10.1098/rsta.2016.0455.
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 CO 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'.
农业模式相互比较与改进项目(AgMIP)开发了新方法,用于对变化世界中的农业和粮食安全进行全球与区域协调评估(CGRA)。本研究旨在对CGRA进行概念验证,以展示所提议框架的优势与挑战。这项工作回应了《联合国气候变化框架公约》(UNFCCC)关于将全球气温升幅限制在比工业化前水平高1.5°C和2.0°C的影响的要求。1.5°C/2.0°C评估的方案在各学科和尺度之间建立了明确且可检验的联系,将共享社会经济路径(SSP)、代表性农业路径(RAP)、半度额外升温、预测与预估影响(HAPPI)以及耦合模式相互比较计划第5阶段(CMIP5)集合情景、全球网格化作物模型、全球农业经济模型、基于站点的作物模型和国内区域经济模型的输出与输入联系起来。CGRA持续地将各学科、模型和尺度联系起来,以追踪气候影响的复杂链条,并识别管理未来风险中的关键脆弱性、反馈和不确定性。CGRA概念验证结果表明,在全球尺度上,模拟的小麦和玉米产量变化在一些地区呈正负混合态势,在1.5°C和2.0°C时,一些产粮区的产量有所下降。在未考虑二氧化碳对作物直接影响的模拟中,产量下降尤为明显。这些预估的全球产量变化在两个全球经济模型中大多导致了小麦和玉米价格上涨以及种植面积增加。使用基于站点的作物模型对1.5°C和2.0°C进行的区域模拟结果因地区和作物而异。结合全球经济模型中的价格变化,巴基斯坦旁遮普邦的生产力下降导致了脆弱家庭数量和贫困率上升。本文是主题为“《巴黎协定》:理解比工业化前水平高1.5°C的变暖世界所面临的自然和社会挑战”的一部分。