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    REMIND2.1: transformation and innovation dynamics of the energy-economic system within climate and sustainability limits
    (Katlenburg-Lindau : Copernicus, 2021) Baumstark, Lavinia; Bauer, Nico; Benke, Falk; Bertram, Christoph; Bi, Stephen; Gong, Chen Chris; Dietrich, Jan Philipp; Dirnaichner, Alois; Giannousakis, Anastasis; Hilaire, Jerome; Klein, David; Koch, Johannes; Leimbach, Marian; Levesque, Antoine; Madeddu, Silvia; Malik, Aman; Merfort, Anne; Merfort, Leon; Odenweller, Adrian; Pehl, Michaja; Pietzcker, Robert C.; Piontek, Franziska; Rauner, Sebastian; Rodrigues, Renato; Rottoli, Marianna; Schreyer, Felix; Schultes, Anselm; Soergel, Bjoern; Soergel, Dominika; Strefler, Jessica; Ueckerdt, Falko; Kriegler, Elmar; Luderer, Gunnar
    This paper presents the new and now open-source version 2.1 of the REgional Model of INvestments and Development (REMIND). REMIND, as an integrated assessment model (IAM), provides an integrated view of the global energy–economy–emissions system and explores self-consistent transformation pathways. It describes a broad range of possible futures and their relation to technical and socio-economic developments as well as policy choices. REMIND is a multiregional model incorporating the economy and a detailed representation of the energy sector implemented in the General Algebraic Modeling System (GAMS). It uses non-linear optimization to derive welfare-optimal regional transformation pathways of the energy-economic system subject to climate and sustainability constraints for the time horizon from 2005 to 2100. The resulting solution corresponds to the decentralized market outcome under the assumptions of perfect foresight of agents and internalization of external effects. REMIND enables the analyses of technology options and policy approaches for climate change mitigation with particular strength in representing the scale-up of new technologies, including renewables and their integration in power markets. The REMIND code is organized into modules that gather code relevant for specific topics. Interaction between different modules is made explicit via clearly defined sets of input and output variables. Each module can be represented by different realizations, enabling flexible configuration and extension. The spatial resolution of REMIND is flexible and depends on the resolution of the input data. Thus, the framework can be used for a variety of applications in a customized form, balancing requirements for detail and overall runtime and complexity.
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    Reduced Complexity Model Intercomparison Project Phase 1: introduction and evaluation of global-mean temperature response
    (Katlenburg-Lindau : Copernicus, 2020) Nicholls, Zebedee R. J.; Meinshausen, Malte; Lewis, Jared; Gieseke, Robert; Dommenget, Dietmar; Dorheim, Kalyn; Fan, Chen-Shuo; Fuglestvedt, Jan S.; Gasser, Thomas; Golüke, Ulrich; Goodwin, Philip; Hartin, Corinne; Hope, Austin P.; Kriegler, Elmar; Leach, Nicholas J.; Marchegiani, Davide; McBride, Laura A.; Quilcaille, Yann; Rogelj, Joeri; Salawitch, Ross J.; Samset, Bjørn H.; Sandstad, Marit; Shiklomanov, Alexey N.; Skeie, Ragnhild B.; Smith, Christopher J.; Smith, Steve; Tanaka, Katsumasa; Tsutsui, Junichi; Xie, Zhiang
    Reduced-complexity climate models (RCMs) are critical in the policy and decision making space, and are directly used within multiple Intergovernmental Panel on Climate Change (IPCC) reports to complement the results of more comprehensive Earth system models. To date, evaluation of RCMs has been limited to a few independent studies. Here we introduce a systematic evaluation of RCMs in the form of the Reduced Complexity Model Intercomparison Project (RCMIP). We expect RCMIP will extend over multiple phases, with Phase 1 being the first. In Phase 1, we focus on the RCMs' global-mean temperature responses, comparing them to observations, exploring the extent to which they emulate more complex models and considering how the relationship between temperature and cumulative emissions of CO2 varies across the RCMs. Our work uses experiments which mirror those found in the Coupled Model Intercomparison Project (CMIP), which focuses on complex Earth system and atmosphere–ocean general circulation models. Using both scenario-based and idealised experiments, we examine RCMs' global-mean temperature response under a range of forcings. We find that the RCMs can all reproduce the approximately 1 ∘C of warming since pre-industrial times, with varying representations of natural variability, volcanic eruptions and aerosols. We also find that RCMs can emulate the global-mean temperature response of CMIP models to within a root-mean-square error of 0.2 ∘C over a range of experiments. Furthermore, we find that, for the Representative Concentration Pathway (RCP) and Shared Socioeconomic Pathway (SSP)-based scenario pairs that share the same IPCC Fifth Assessment Report (AR5)-consistent stratospheric-adjusted radiative forcing, the RCMs indicate higher effective radiative forcings for the SSP-based scenarios and correspondingly higher temperatures when run with the same climate settings. In our idealised setup of RCMs with a climate sensitivity of 3 ∘C, the difference for the ssp585–rcp85 pair by 2100 is around 0.23∘C(±0.12 ∘C) due to a difference in effective radiative forcings between the two scenarios. Phase 1 demonstrates the utility of RCMIP's open-source infrastructure, paving the way for further phases of RCMIP to build on the research presented here and deepen our understanding of RCMs.
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    The IPCC Sixth Assessment Report WGIII climate assessment of mitigation pathways: from emissions to global temperatures
    (Katlenburg-Lindau : Copernicus, 2022) Kikstra, Jarmo S.; Nicholls, Zebedee R. J.; Smith, Christopher J.; Lewis, Jared; Lamboll, Robin D.; Byers, Edward; Sandstad, Marit; Meinshausen, Malte; Gidden, Matthew J.; Rogelj, Joeri; Kriegler, Elmar; Peters, Glen P.; Fuglestvedt, Jan S.; Skeie, Ragnhild B.; Samset, Bjørn H.; Wienpahl, Laura; van Vuuren, Detlef P.; van der Wijst, Kaj-Ivar; Al Khourdajie, Alaa; Forster, Piers M.; Reisinger, Andy; Schaeffer, Roberto; Riahi, Keywan
    While the Intergovernmental Panel on Climate Change (IPCC) physical science reports usually assess a handful of future scenarios, the Working Group III contribution on climate mitigation to the IPCC's Sixth Assessment Report (AR6 WGIII) assesses hundreds to thousands of future emissions scenarios. A key task in WGIII is to assess the global mean temperature outcomes of these scenarios in a consistent manner, given the challenge that the emissions scenarios from different integrated assessment models (IAMs) come with different sectoral and gas-to-gas coverage and cannot all be assessed consistently by complex Earth system models. In this work, we describe the "climate-assessment"workflow and its methods, including infilling of missing emissions and emissions harmonisation as applied to 1202 mitigation scenarios in AR6 WGIII. We evaluate the global mean temperature projections and effective radiative forcing (ERF) characteristics of climate emulators FaIRv1.6.2 and MAGICCv7.5.3 and use the CICERO simple climate model (CICERO-SCM) for sensitivity analysis. We discuss the implied overshoot severity of the mitigation pathways using overshoot degree years and look at emissions and temperature characteristics of scenarios compatible with one possible interpretation of the Paris Agreement. We find that the lowest class of emissions scenarios that limit global warming to "1.5 ° C (with a probability of greater than 50 %) with no or limited overshoot"includes 97 scenarios for MAGICCv7.5.3 and 203 for FaIRv1.6.2. For the MAGICCv7.5.3 results, "limited overshoot"typically implies exceedance of median temperature projections of up to about 0.1 ° C for up to a few decades before returning to below 1.5 ° C by or before the year 2100. For more than half of the scenarios in this category that comply with three criteria for being "Paris-compatible", including net-zero or net-negative greenhouse gas (GHG) emissions, median temperatures decline by about 0.3-0.4 ° C after peaking at 1.5-1.6 ° C in 2035-2055. We compare the methods applied in AR6 with the methods used for SR1.5 and discuss their implications. This article also introduces a "climate-assessment"Python package which allows for fully reproducing the IPCC AR6 WGIII temperature assessment. This work provides a community tool for assessing the temperature outcomes of emissions pathways and provides a basis for further work such as extending the workflow to include downscaling of climate characteristics to a regional level and calculating impacts.
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    Global emissions pathways under different socioeconomic scenarios for use in CMIP6: a dataset of harmonized emissions trajectories through the end of the century
    (Katlenburg-Lindau : Copernicus, 2019) Gidden, Matthew J.; Riahi, Keywan; Smith, Steven J.; Fujimori, Shinichiro; Luderer, Gunnar; Kriegler, Elmar; van Vuuren, Detlef P.; van den Berg, Maarten; Feng, Leyang; Klein, David; Calvin, Katherine; Doelman, Jonathan C.; Frank, Stefan; Fricko, Oliver; Harmsen, Mathijs; Hasegawa, Tomoko; Havlik, Petr; Hilaire, Jérôme; Hoesly, Rachel; Horing, Jill; Popp, Alexander; Stehfest, Elke; Takahashi, Kiyoshi
    We present a suite of nine scenarios of future emissions trajectories of anthropogenic sources, a key deliverable of the ScenarioMIP experiment within CMIP6. Integrated assessment model results for 14 different emissions species and 13 emissions sectors are provided for each scenario with consistent transitions from the historical data used in CMIP6 to future trajectories using automated harmonization before being downscaled to provide higher emissions source spatial detail. We find that the scenarios span a wide range of end-of-century radiative forcing values, thus making this set of scenarios ideal for exploring a variety of warming pathways. The set of scenarios is bounded on the low end by a 1.9 W m−2 scenario, ideal for analyzing a world with end-of-century temperatures well below 2 ∘C, and on the high end by a 8.5 W m−2 scenario, resulting in an increase in warming of nearly 5 ∘C over pre-industrial levels. Between these two extremes, scenarios are provided such that differences between forcing outcomes provide statistically significant regional temperature outcomes to maximize their usefulness for downstream experiments within CMIP6. A wide range of scenario