NGFS Climate Scenarios Data Set

Download information Please do not request a data download here. Rather, the data is available for download at the NGFS Scenario Explorer under this download link: https://data.ece.iiasa.ac.at/ngfs/#/downloads. In order to download click on Guest login. You will be forwarded to the downloads page. At the bottom of the downloads page you can download the data. The license permits use of the scenario ensemble for scientific research and commercial use, but restricts redistribution of substantial parts of the data. Please refer to the FAQ and legal code for more information. Release Notes for Version 5.1 Changes IAMs REMIND-MAgPIE: For scenarios o_1p5c and o_lowdem, the variables "Policy Cost|GDP Loss" and similar variables are slightly off The variable "Capacity|Hydrogen" was twice as high as it was supposed to be, this is now fixed (All IAMs) MAGICC: atmospheric concentrations of CO2, CH4 and N2O were erroneously not published in version 5.0, they are now part of the data set Downscaling Governance indicators are improved NiGEM A number of variables that NiGEM re-reported from Downscaling have now been removed for clarity. The variables can still be found as part of the Downscaling data. The following is a list of the variables dropped from NiGEM on the left and the corresponding Downscaling variables on the right: Revenue from CB or BCA tax -> Revenue|Government|Tax|Carbon Quarterly consumption of oil ; MnToe -> Primary Energy|Oil Quarterly consumption of gas ; MnToe -> Primary Energy|Gas Quarterly consumption of coal ; MnToe -> Primary Energy|Coal Quarterly consumption of non-carbon ; MnToe-> Sum of: Primary Energy|Biomass, Primary Energy|Geothermal, Primary Energy|Hydro, Primary Energy|Solar, Primary Energy|Wind, Primary Energy|Nuclear Energy consumption (total) ; MnToe -> This is a summation of NiGEM variables, there is not direct Downscaling correspondance, removed because all components have been removed Carbon pricing ; $ per Tn CO2 -> Price|Carbon Notice to users of NGFS long-term climate scenarios The NGFS informs users that the academic paper underpinning the physical risk estimates in Phase V of its long-term scenarios, Kotz et al. (2024), has received critiques in a post-publication review at Nature. The authors have revised their analysis, with limited impacts on results. The updated paper still has to undergo peer-review. The NGFS closely monitors the academic process and will incorporate any necessary updates in future iterations of its long-term scenarios. Users are reminded that neither the NGFS, nor its member institutions, nor any person acting on their behalf, is responsible or liable for any reliance on, or for any use of the NGFS scenarios and/or supplementary documentation. This also applies to the use of the data produced under the scenarios – see section 5 in https://data.ene.iiasa.ac.at/ngfs/#/license. Thus, while the NGFS climate scenarios are certainly a helpful tool, they do not alleviate the responsibility of users, including banks and other (financial) organisations, to design and implement their own risk management frameworks. About NGFS The Network for Greening the Financial System (NGFS) is a group of 127 central banks and supervisors and 20 observers committed to sharing best practices, contributing to the development of climate– and environment–related risk management in the financial sector and mobilising mainstream finance to support the transition toward a sustainable economy. This Scenario Explorer is a web-based user interface for NGFS Scenarios. This provides intuitive visualizations & display of time series data and download of the data in multiple formats. NGFS scenarios were produced by NGFS Workstream on Scenarios Design and Analysis in partnership with an academic consortium from the Potsdam Institute for Climate Impact Research (PIK), International Institute for Applied Systems Analysis (IIASA), University of Maryland (UMD), Climate Analytics (CA), and the National Institute of Economic and Social Research (NIESR). This work was made possible by grants from Bloomberg Philanthropies and ClimateWorks Foundation. The bespoke scenarios developed in Phase 4 of this project are generated by state-of-the-art well-established integrated assessment models (IAMs), namely GCAM, MESSAGE-GLOBIOM and REMIND-MAgPIE, as well as the NiGEM macroeconomic model.下载说明 请勿在此处请求数据下载。 相关数据可通过NGFS情景探索器（NGFS Scenario Explorer）的以下下载链接获取：https://data.ece.iiasa.ac.at/ngfs/#/downloads。下载时请点击"访客登录"，随后将跳转至下载页面，在该页面底部即可下载数据。 本许可协议允许将情景集合用于科学研究与商业用途，但禁止对数据的实质性部分进行重新分发。详细信息请参阅常见问题解答（FAQ）与法律条款。 5.1版更新说明 更新内容 ### 综合评估模型（Integrated Assessment Models，IAMs） #### REMIND-MAgPIE： 针对o_1p5c与o_lowdem情景，"政策成本|GDP损失"及类似变量存在小幅偏差。 "装机容量|氢能"变量此前数值为预期值的两倍，现已修复该问题。 #### （所有综合评估模型）MAGICC模块： 5.0版本中未包含二氧化碳（CO₂）、甲烷（CH₄）与一氧化二氮（N₂O）的大气浓度数据，现已将其纳入数据集。 ### 降尺度处理 治理指标已优化。 #### NiGEM： 为提升可读性，已移除NiGEM中部分此前从降尺度模块重复上报的变量，这些变量仍可在降尺度数据中找到。以下为NiGEM中被移除的变量（左侧）与对应降尺度模块变量（右侧）的对应列表： - 碳边境机制（CB）或碳边境调整机制（BCA）税收收入 → 政府收入|税收|碳税 - 季度石油消费量（单位：百万吨油当量（MnToe）） → 一次能源|石油 - 季度天然气消费量（单位：百万吨油当量） → 一次能源|天然气 - 季度煤炭消费量（单位：百万吨油当量） → 一次能源|煤炭 - 季度非化石能源消费量（单位：百万吨油当量） → 以下能源之和：一次能源|生物质能、一次能源|地热能、一次能源|水能、一次能源|太阳能、一次能源|风能、一次能源|核能 - 总能源消费量（单位：百万吨油当量） → 该变量为NiGEM内变量的加总，无直接对应降尺度变量，因所有组成变量已被移除，故一并删除 - 碳定价（单位：美元/吨二氧化碳（$ per Tn CO2）） → 碳定价 NGFS长期气候情景用户须知 NGFS在此提醒用户，支撑其长期情景第五阶段物理风险估算的学术论文《Kotz et al. (2024)》在《自然》（Nature）期刊发表后受到了同行评议批评。作者已对分析内容进行修订，对结果影响有限；修订后的论文仍需通过同行评审。 NGFS将密切跟进该学术流程，并将在长期情景的后续版本中纳入必要更新。 请用户注意，NGFS、其成员机构及任何代表其行事的个人均不对因使用或依赖NGFS情景及/或补充文档所导致的任何后果承担责任，该条款同样适用于基于情景生成的数据的使用——详见https://data.ene.iiasa.ac.at/ngfs/#/license 中的第5节。因此，尽管NGFS气候情景无疑是一项实用工具，但并不能免除包括银行及其他金融机构在内的用户自行设计并实施自身风险管理框架的责任。 关于NGFS 绿色金融系统网络（Network for Greening the Financial System，NGFS）由127家中央银行与监管机构及20家观察员机构组成，致力于分享最佳实践、推动金融领域气候与环境相关风险管理体系的发展，并调动主流金融资源以支持向可持续经济转型。 本情景探索器是面向NGFS情景的网页端用户界面，可实现时序数据的直观可视化展示，并支持以多种格式下载数据。 NGFS情景由NGFS情景设计与分析工作组与来自波茨坦气候影响研究所（PIK）、国际应用系统分析研究所（IIASA）、马里兰大学（UMD）、气候分析机构（CA）及英国国家经济与社会研究所（NIESR）的学术联盟合作开发。本项目得到了布隆伯格慈善基金会（Bloomberg Philanthropies）与气候工作基金会（ClimateWorks Foundation）的资助。 本项目第四阶段开发的定制化情景由当前主流且经过验证的综合评估模型（IAMs）生成，包括GCAM、MESSAGE-GLOBIOM与REMIND-MAgPIE，以及NiGEM宏观经济模型。