@article{HarmsenKrieglervanVuurenetal.2021,
  author    = {Harmsen, Mathijs and Kriegler, Elmar and van Vuuren, Detlef P. and van der Wijst, Kaj-Ivar and Luderer, Gunnar and Cui, Ryna and Dessens, Olivier and Drouet, Laurent and Emmerling, Johannes and Morris, Jennifer Faye and Fosse, Florian and Fragkiadakis, Dimitris and Fragkiadakis, Kostas and Fragkos, Panagiotis and Fricko, Oliver and Fujimori, Shinichiro and Gernaat, David and Guivarch, C{\´e}line and Iyer, Gokul and Karkatsoulis, Panagiotis and Keppo, Ilkka and Keramidas, Kimon and K{\"o}berle, Alexandre and Kolp, Peter and Krey, Volker and Kr{\"u}ger, Christoph and Leblanc, Florian and Mittal, Shivika and Paltsev, Sergey and Rochedo, Pedro and van Ruijven, Bas J. and Sands, Ronald D. and Sano, Fuminori and Strefler, Jessica and Arroyo, Eveline Vasquez and Wada, Kenichi and Zakeri, Behnam},
  title     = {Integrated assessment model diagnostics},
  series = {Environmental research letters},
  volume    = {16},
  journal   = {Environmental research letters},
  number    = {5},
  publisher = {IOP Publishing},
  address   = {Bristol},
  issn      = {1748-9326},
  doi       = {10.1088/1748-9326/abf964},
  pages     = {13},
  year      = {2021},
  abstract  = {Integrated assessment models (IAMs) form a prime tool in informing about climate mitigation strategies. Diagnostic indicators that allow comparison across these models can help describe and explain differences in model projections. This increases transparency and comparability. Earlier, the IAM community has developed an approach to diagnose models (Kriegler (2015 Technol. Forecast. Soc. Change 90 45-61)). Here we build on this, by proposing a selected set of well-defined indicators as a community standard, to systematically and routinely assess IAM behaviour, similar to metrics used for other modeling communities such as climate models. These indicators are the relative abatement index, emission reduction type index, inertia timescale, fossil fuel reduction, transformation index and cost per abatement value. We apply the approach to 17 IAMs, assessing both older as well as their latest versions, as applied in the IPCC 6th Assessment Report. The study shows that the approach can be easily applied and used to indentify key differences between models and model versions. Moreover, we demonstrate that this comparison helps to link model behavior to model characteristics and assumptions. We show that together, the set of six indicators can provide useful indication of the main traits of the model and can roughly indicate the general model behavior. The results also show that there is often a considerable spread across the models. Interestingly, the diagnostic values often change for different model versions, but there does not seem to be a distinct trend.},
  language  = {en}
}
@article{KikstraNichollsSmithetal.2022,
  author    = {Kikstra, Jarmo S. and Nicholls, Zebedee R. J. and Smith, Christopher J. and Lewis, Jared and Lamboll, Robin D. and Byers, Edward and Sandstad, Marit and Meinshausen, Malte and Gidden, Matthew J. and Rogelj, Joeri and Kriegler, Elmar and Peters, Glen P. and Fuglestvedt, Jan S. and Skeie, Ragnhild B. and Samset, Bj{\o}rn H. and Wienpahl, Laura and van Vuuren, Detlef P. and van der Wijst, Kaj-Ivar and Al Khourdajie, Alaa and Forster, Piers M. and Reisinger, Andy and Schaeffer, Roberto and Riahi, Keywan},
  title     = {The IPCC Sixth Assessment Report WGIII climate assessment of mitigation pathways},
  series = {Geoscientific model development},
  volume    = {15},
  journal   = {Geoscientific model development},
  number    = {24},
  publisher = {Copernicus},
  address   = {Katlenburg-Lindau},
  issn      = {1991-959X},
  doi       = {10.5194/gmd-15-9075-2022},
  pages     = {9075 -- 9109},
  year      = {2022},
  abstract  = {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.},
  language  = {en}
}