This paper presents a set of energy and resource intensive scenarios based on the concept of Shared Socio-Economic Pathways (SSPs). The scenario family is characterized by rapid and fossil-fueled development with high socio-economic challenges to mitigation and low socio-economic challenges to adaptation (SSP5). A special focus is placed on the SSP5 marker scenario developed by the REMIND-MAgPIE integrated assessment modeling framework. The SSP5 baseline scenarios exhibit very high levels of fossil fuel use, up to a doubling of global food demand, and up to a tripling of energy demand and greenhouse gas emissions over the course of the century, marking the upper end of the scenario literature in several dimensions. These scenarios are currently the only SSP scenarios that result in a radiative forcing pathway as high as the highest Representative Concentration Pathway (RCP8.5). This paper further investigates the direct impact of mitigation policies on the SSP5 energy, land and emissions dynamics confirming high socio-economic challenges to mitigation in SSP5. Nonetheless, mitigation policies reaching climate forcing levels as low as in the lowest Representative Concentration Pathway (RCP2.6) are accessible in SSP5. The SSP5 scenarios presented in this paper aim to provide useful reference points for future climate change, climate impact, adaption and mitigation analysis, and broader questions of sustainable development.
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-phase-3/#/downloads. 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. 3.3 (7 October 2022) Correction notice: In this version of the NGFS Phase 3 data set, V3.3, the updates for the NiGEM model were not included due to a processing error. This has been rectified is the next version, V3.4 (10.5281/zenodo.7198430). For reasons of transparency and continuity we have chosen to keep the release notes below regarding NiGEM even though they are not correct. The rest of the updates were included correctly. General: Included all years in the data set, including years passed. NiGEM: (not included due to processing error) Removed incorrect "index; 2017=100" from NiGEM units. Units affected are (updated unit in bold): index; 2017=100 US$ per barrel index; 2017=100 US$ per barrel(equiv) % difference, index; 2017=100 US$ per barrel % difference, index; 2017=100 US$ per barrel(equiv) Transition effects now refer to the combined carbon pricing and recycling shocks rather than the carbon price only. Transition effects have been removed for "Current Policies" which only experiences chronic physical impacts (no carbon pricing under current policies). Combined effects now equal transition + physical. A further combined data row has been added to the disorderly scenarios ("Delayed transition", "Divergent Net Zero") to show the output of an additional business confidence shock applied to the combined shock (see scenario description). These data are denoted by the "|Combined plus business confidence" suffix in the variable name. Acute physical risk data have been added for the scenarios "Delayed transition", "Current Policies", "Net Zero 2050" for the world level. As these data are model independent, they have been added under "NiGEM NGFS v1.22" only (without any input model information). Country specific currency information for units labelled as "local currency" has been added to the downloadable data under the "unit" column. It is added as a suffix e.g. "2017 prices; local currency ( US$ Bn)", when before it was "2017 prices; local currency ( US$ Bn)". REMIND integrated damage runs: Added the variables "GDP|PPP|Counterfactual without Damage" and "GDP|PPP|including chronic physical risk damage estimate" for the for the regions "TWN", "MAC" and "CHN". About the data set This dataset contains a set of climate scenario that have been developed for the Network for Greening the Financial System (NGFS). The NGFS is a group of 83 central banks and supervisors and 12 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. The scenarios in this dataset were produced by NGFS Workstream 3 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), the Eidgenössische Technische Hochschule Zürich (ETH) and the National Institute of Economic and Social Research (NIESR). The Phase 3 bespoke scenarios are generated by state-of-the-art well-established integrated assessment models (IAMs), namely GCAM, MESSAGEix-GLOBIOM and REMIND-MAgPIE. These models allow the estimation of global and regional mitigation costs, the analysis of energy system transition characteristics, the quantification of investments required to transform the energy system, and the identification of synergies and trade-off of sustainable development pathways. Technical documentation is available to help users access the datasets. The documentation describes the models and variables, as well as provides detailed guidance for database users. Scenario presentation materials and the user guide are also available at the NGFS portal.
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-phase-3/#/downloads. 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. 3.2 (9 September 2022) Added "Baseline" scenario for NiGEM Moved MESSAGEix-GLOBIOM 1.1-M-R12 variables that were wrongly filed under "Downscaling [MESSAGEix-GLOBIOM 1.1-M-R12]" back to model native. About the data set This dataset contains a set of climate scenario that have been developed for the Network for Greening the Financial System (NGFS). The NGFS is a group of 83 central banks and supervisors and 12 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. The scenarios in this dataset were produced by NGFS Workstream 3 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), the Eidgenössische Technische Hochschule Zürich (ETH) and the National Institute of Economic and Social Research (NIESR). The Phase 3 bespoke scenarios are generated by state-of-the-art well-established integrated assessment models (IAMs), namely GCAM, MESSAGEix-GLOBIOM and REMIND-MAgPIE. These models allow the estimation of global and regional mitigation costs, the analysis of energy system transition characteristics, the quantification of investments required to transform the energy system, and the identification of synergies and trade-off of sustainable development pathways. Technical documentation is available to help users access the datasets. The documentation describes the models and variables, as well as provides detailed guidance for database users. Scenario presentation materials and the user guide are also available at the NGFS portal.
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 where you find 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 V4.0 An effort has been made to keep the NGFS Phase 4 data model as much as possible in line with Phase 3 as possible. Nonetheless, there are a few changes: The MESSAGE model (IAM and Downscaling) does not report GDP for the Low demand scenario because the demand projections are developed bottom-up uncoupled from the GDP feedbacks in the MESSAGEix framework. The *Divergent net Zero* scenario was dropped. Two new scenarios were introduced: Fragmented World Low Demand There's now a full set of From the MAGICC climate model, we now report more percentiles ranging from 5th to 95th instead of just the previously only the 50th percentile. The in Phase 3 from REMIND and GCAM model-reported temperature variable Temperature|Global mean has been dropped. The replacement variable is the more accurate AR6 climate diagnostics|Surface Temperature (GSAT)|MAGICCv7.5.3|50.0th. In addition we also report atmospheric concentrations from MAGICC for CO2, CH4, and N2O. The Damages post processing was moved under the Downscaling model as it reports country level data. Previously it was filed under the native IAM models.The variables affected are: GDP|PPP|including medium chronic physical risk damage estimate GDP|PPP|including high chronic physical risk damage estimate Post-processed|high GDP change|KW panel population-weighted|GMT AR6 climate diagnostics|Surface Temperature (GSAT)|MAGICCv7.5.3|5.0th Percentile Post-processed|high GDP change|KW panel population-weighted|GMT AR6 climate diagnostics|Surface Temperature (GSAT)|MAGICCv7.5.3|50.0th Percentile Post-processed|high GDP change|KW panel population-weighted|GMT AR6 climate diagnostics|Surface Temperature (GSAT)|MAGICCv7.5.3|95.0th Percentile Post-processed|median GDP change|KW panel population-weighted|GMT AR6 climate diagnostics|Surface Temperature (GSAT)|MAGICCv7.5.3|5.0th Percentile Post-processed|median GDP change|KW panel population-weighted|GMT AR6 climate diagnostics|Surface Temperature (GSAT)|MAGICCv7.5.3|50.0th Percentile Post-processed|median GDP change|KW panel population-weighted|GMT AR6 climate diagnostics|Surface Temperature (GSAT)|MAGICCv7.5.3|95.0th Percentile net GDP|PPP|high damage|KW panel population-weighted|GMT AR6 climate diagnostics|Surface Temperature (GSAT)|MAGICCv7.5.3|5.0th Percentile net GDP|PPP|high damage|KW panel population-weighted|GMT AR6 climate diagnostics|Surface Temperature (GSAT)|MAGICCv7.5.3|50.0th Percentile net GDP|PPP|high damage|KW panel population-weighted|GMT AR6 climate diagnostics|Surface Temperature (GSAT)|MAGICCv7.5.3|95.0th Percentile net GDP|PPP|median damage|KW panel population-weighted|GMT AR6 climate diagnostics|Surface Temperature (GSAT)|MAGICCv7.5.3|5.0th Percentile net GDP|PPP|median damage|KW panel population-weighted|GMT AR6 climate diagnostics|Surface Temperature (GSAT)|MAGICCv7.5.3|50.0th Percentile net GDP|PPP|median damage|KW panel population-weighted|GMT AR6 climate diagnostics|Surface Temperature (GSAT)|MAGICCv7.5.3|95.0th Percentile Country Temperature|Downscaling|5.0th Percentile Country Temperature|Downscaling|50.0th Percentile Country Temperature|Downscaling|95.0th Percentile In Phase 3 for the integrated damage runs of REMIND (REMIND-MAgPIE 3.0-4.4 IntegratedPhysicalDamages (95th-high) and REMIND-MAgPIE 3.0-4.4 IntegratedPhysicalDamages (median)) the variable GDP|PPP|Counterfactual without damage was reported erroneously. It has been removed for this release. Due to limitation in Excel data size the Downscaling data have now been split into three files, one for each IAM. In addition, due to a processing error, NiGEM data for the MESSAGE model, for scenarios Net Zero 2050, Below 2C and Fragmented World are currently not published. Work is being done to fix this as soon as possible. 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.
Abstract In Paris in 2015, the global community agreed to limit global warming to well below 2 $${}^{\circ }$$ ∘ C, aiming at even 1.5 $${}^{\circ }$$ ∘ C. It is still uncertain whether these targets are sufficient to preserve marine ecosystems and prevent a severe alteration of marine biogeochemical cycles. Here, we show that stringent mitigation strategies consistent with the 1.5 $${}^{\circ }$$ ∘ C scenario could, indeed, provoke a critical difference for the ocean’s carbon cycle and calcium carbonate saturation states. Favorable conditions for calcifying organisms like tropical corals and polar pteropods, both of major importance for large ecosystems, can only be maintained if CO $${}_{2}$$ 2 emissions fall rapidly between 2025 and 2050, potentially requiring an early deployment of CO $${}_{2}$$ 2 removal techniques in addition to drastic emissions reduction. Furthermore, this outcome can only be achieved if the terrestrial biosphere remains a carbon sink during the entire 21st century.
Abstract To achieve the Paris climate target, deep emissions reductions have to be complemented with carbon dioxide removal (CDR). However, a portfolio of CDR options is necessary to reduce risks and potential negative side effects. Despite a large theoretical potential, ocean-based CDR such as ocean alkalinity enhancement (OAE) has been omitted in climate change mitigation scenarios so far. In this study, we provide a techno-economic assessment of large-scale OAE using hydrated lime (‘ocean liming’). We address key uncertainties that determine the overall cost of ocean liming (OL) such as the CO2 uptake efficiency per unit of material, distribution strategies avoiding carbonate precipitation which would compromise efficiency, and technology availability (e.g., solar calciners). We find that at economic costs of 130–295 $/tCO2 net-removed, ocean liming could be a competitive CDR option which could make a significant contribution towards the Paris climate target. As the techno-economic assessment identified no showstoppers, we argue for more research on ecosystem impacts, governance, monitoring, reporting, and verification, and technology development and assessment to determine whether ocean liming and other OAE should be considered as part of a broader CDR portfolio.
Many countries have implemented national climate policies to accomplish pledged Nationally Determined Contributions and to contribute to the temperature objectives of the Paris Agreement on climate change. In 2023, the global stocktake will assess the combined effort of countries. Here, based on a public policy database and a multi-model scenario analysis, we show that implementation of current policies leaves a median emission gap of 22.4 to 28.2 GtCO2eq by 2030 with the optimal pathways to implement the well below 2 °C and 1.5 °C Paris goals. If Nationally Determined Contributions would be fully implemented, this gap would be reduced by a third. Interestingly, the countries evaluated were found to not achieve their pledged contributions with implemented policies (implementation gap), or to have an ambition gap with optimal pathways towards well below 2 °C. This shows that all countries would need to accelerate the implementation of policies for renewable technologies, while efficiency improvements are especially important in emerging countries and fossil-fuel-dependent countries. To evaluate the effectiveness of current national policies in achieving global temperature targets is important but a systematic multi-model evaluation is still lacking. Here the authors identified a reduction of 3.5 GtCO2 eq of current national policies relative to a baseline scenario without climate policies by 2030 due to the increasing low carbon share of final energy and the improving final energy intensity.
