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    Reduced Complexity Model Intercomparison Project Phase 2: Synthesizing Earth System Knowledge for Probabilistic Climate Projections
    Nicholls, Z ; Meinshausen, M ; Lewis, J ; Corradi, MR ; Dorheim, K ; Gasser, T ; Gieseke, R ; Hope, AP ; Leach, NJ ; McBride, LA ; Quilcaille, Y ; Rogelj, J ; Salawitch, RJ ; Samset, BH ; Sandstad, M ; Shiklomanov, A ; Skeie, RB ; Smith, CJ ; Smith, SJ ; Su, X ; Tsutsui, J ; Vega-Westhoff, B ; Woodard, DL (AMER GEOPHYSICAL UNION, 2021-06)
    Over the last decades, climate science has evolved rapidly across multiple expert domains. Our best tools to capture state-of-the-art knowledge in an internally self-consistent modeling framework are the increasingly complex fully coupled Earth System Models (ESMs). However, computational limitations and the structural rigidity of ESMs mean that the full range of uncertainties across multiple domains are difficult to capture with ESMs alone. The tools of choice are instead more computationally efficient reduced complexity models (RCMs), which are structurally flexible and can span the response dynamics across a range of domain-specific models and ESM experiments. Here we present Phase 2 of the Reduced Complexity Model Intercomparison Project (RCMIP Phase 2), the first comprehensive intercomparison of RCMs that are probabilistically calibrated with key benchmark ranges from specialized research communities. Unsurprisingly, but crucially, we find that models which have been constrained to reflect the key benchmarks better reflect the key benchmarks. Under the low-emissions SSP1-1.9 scenario, across the RCMs, median peak warming projections range from 1.3 to 1.7°C (relative to 1850-1900, using an observationally based historical warming estimate of 0.8°C between 1850-1900 and 1995-2014). Further developing methodologies to constrain these projection uncertainties seems paramount given the international community's goal to contain warming to below 1.5°C above preindustrial in the long-term. Our findings suggest that users of RCMs should carefully evaluate their RCM, specifically its skill against key benchmarks and consider the need to include projections benchmarks either from ESM results or other assessments to reduce divergence in future projections.
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    It Is Still Possible to Achieve the Paris Climate Agreement: Regional, Sectoral, and Land-Use Pathways
    Teske, S ; Pregger, T ; Simon, S ; Naegler, T ; Pagenkopf, J ; Deniz, O ; van den Adel, B ; Dooley, K ; Meinshausen, M (MDPI, 2021-04)
    It is still possible to comply with the Paris Climate Agreement to maintain a global temperature ‘well below +2.0 °C’ above pre-industrial levels. We present two global non-overshoot pathways (+2.0 °C and +1.5 °C) with regional decarbonization targets for the four primary energy sectors—power, heating, transportation, and industry—in 5-year steps to 2050. We use normative scenarios to illustrate the effects of efficiency measures and renewable energy use, describe the roles of increased electrification of the final energy demand and synthetic fuels, and quantify the resulting electricity load increases for 72 sub-regions. Non-energy scenarios include a phase-out of net emissions from agriculture, forestry, and other land uses, reductions in non-carbon greenhouse gases, and land restoration to scale up atmospheric CO2 removal, estimated at −377 Gt CO2 to 2100. An estimate of the COVID-19 effects on the global energy demand is included and a sensitivity analysis describes the impacts if implementation is delayed by 5, 7, or 10 years, which would significantly reduce the likelihood of achieving the 1.5 °C goal. The analysis applies a model network consisting of energy system, power system, transport, land-use, and climate models.
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    Country-resolved combined emission and socio-economic pathways based on the Representative Concentration Pathway (RCP) and Shared Socio-Economic Pathway (SSP) scenarios
    Gutschow, J ; Jeffery, ML ; Gunther, A ; Meinshausen, M (COPERNICUS GESELLSCHAFT MBH, 2021-03-11)
    Abstract. Climate policy analysis needs reference scenarios to assess emission targets and current trends. When presenting their national climate policies, countries often showcase their target trajectories against fictitious so-called baselines. These counterfactual scenarios are meant to present future greenhouse gas (GHG) emissions in the absence of climate policy. These so-called baselines presented by countries are often of limited use, as they can be exaggerated and as the methodology used to derive them is usually not transparent. Scenarios created by independent modeling groups using integrated assessment models (IAMs) can provide different interpretations of several socio-economic storylines and can provide a more realistic backdrop against which the projected target emission trajectory can be assessed. However, the IAMs are limited in regional resolution. This resolution is further reduced in intercomparison studies, as data for a common set of regions are produced by aggregating the underlying smaller regions. Thus, the data are not readily available for country-specific policy analysis. This gap is closed by downscaling regional IAM scenarios to the country level. The last of such efforts has been performed for the SRES (“Special Report on Emissions Scenarios”) scenarios, which are over a decade old by now. CMIP6 (Coupled Model Intercomparison Project phase 6) scenarios have been downscaled to a grid; however they cover only a few combinations of forcing levels and SSP storylines with only a single model per combination. Here, we provide up-to-date country scenarios, downscaled from the full RCP (Representative Concentration Pathway) and SSP (Shared Socio-Economic Pathway) scenario databases, using results from the SSP GDP (gross domestic product) country model results as drivers for the downscaling process. The data are available at https://doi.org/10.5281/zenodo.3638137 (Gütschow et al., 2020).
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    Climate model projections from the Scenario Model Intercomparison Project (ScenarioMIP) of CMIP6
    Tebaldi, C ; Debeire, K ; Eyring, V ; Fischer, E ; Fyfe, J ; Friedlingstein, P ; Knutti, R ; Lowe, J ; O'Neill, B ; Sanderson, B ; van Vuuren, D ; Riahi, K ; Meinshausen, M ; Nicholls, Z ; Tokarska, KB ; Hurtt, G ; Kriegler, E ; Lamarque, J-F ; Meehl, G ; Moss, R ; Bauer, SE ; Boucher, O ; Brovkin, V ; Byun, Y-H ; Dix, M ; Gualdi, S ; Guo, H ; John, JG ; Kharin, S ; Kim, Y ; Koshiro, T ; Ma, L ; Olivie, D ; Panickal, S ; Qiao, F ; Rong, X ; Rosenbloom, N ; Schupfner, M ; Seferian, R ; Sellar, A ; Semmler, T ; Shi, X ; Song, Z ; Steger, C ; Stouffer, R ; Swart, N ; Tachiiri, K ; Tang, Q ; Tatebe, H ; Voldoire, A ; Volodin, E ; Wyser, K ; Xin, X ; Yang, S ; Yu, Y ; Ziehn, T (COPERNICUS GESELLSCHAFT MBH, 2021-03-01)
    Abstract. The Scenario Model Intercomparison Project (ScenarioMIP) defines and coordinates the main set of future climate projections, based on concentration-driven simulations, within the Coupled Model Intercomparison Project phase 6 (CMIP6). This paper presents a range of its outcomes by synthesizing results from the participating global coupled Earth system models. We limit our scope to the analysis of strictly geophysical outcomes: mainly global averages and spatial patterns of change for surface air temperature and precipitation. We also compare CMIP6 projections to CMIP5 results, especially for those scenarios that were designed to provide continuity across the CMIP phases, at the same time highlighting important differences in forcing composition, as well as in results. The range of future temperature and precipitation changes by the end of the century (2081–2100) encompassing the Tier 1 experiments based on the Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) and SSP1-1.9 spans a larger range of outcomes compared to CMIP5, due to higher warming (by close to 1.5 ∘C) reached at the upper end of the 5 %–95 % envelope of the highest scenario (SSP5-8.5). This is due to both the wider range of radiative forcing that the new scenarios cover and the higher climate sensitivities in some of the new models compared to their CMIP5 predecessors. Spatial patterns of change for temperature and precipitation averaged over models and scenarios have familiar features, and an analysis of their variations confirms model structural differences to be the dominant source of uncertainty. Models also differ with respect to the size and evolution of internal variability as measured by individual models' initial condition ensemble spreads, according to a set of initial condition ensemble simulations available under SSP3-7.0. These experiments suggest a tendency for internal variability to decrease along the course of the century in this scenario, a result that will benefit from further analysis over a larger set of models. Benefits of mitigation, all else being equal in terms of societal drivers, appear clearly when comparing scenarios developed under the same SSP but to which different degrees of mitigation have been applied. It is also found that a mild overshoot in temperature of a few decades around mid-century, as represented in SSP5-3.4OS, does not affect the end outcome of temperature and precipitation changes by 2100, which return to the same levels as those reached by the gradually increasing SSP4-3.4 (not erasing the possibility, however, that other aspects of the system may not be as easily reversible). Central estimates of the time at which the ensemble means of the different scenarios reach a given warming level might be biased by the inclusion of models that have shown faster warming in the historical period than the observed. Those estimates show all scenarios reaching 1.5 ∘C of warming compared to the 1850–1900 baseline in the second half of the current decade, with the time span between slow and fast warming covering between 20 and 27 years from present. The warming level of 2 ∘C of warming is reached as early as 2039 by the ensemble mean under SSP5-8.5 but as late as the mid-2060s under SSP1-2.6. The highest warming level considered (5 ∘C) is reached by the ensemble mean only under SSP5-8.5 and not until the mid-2090s.