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The Vulnerability, Impacts, Adaptation and Climate Services Advisory Board (VIACS AB v1.0) contribution to CMIP6
2016, Ruane, Alex C., Teichmann, Claas, Arnell, Nigel W., Carter, Timothy R., Ebi, Kristie L., Frieler, Katja, Goodess, Clare M., Hewitson, Bruce, Horton, Radley, Kovats, R. Sari, Lotze, Heike K., Mearns, Linda O., Navarra, Antonio, Ojima, Dennis S., Riahi, Keywan, Rosenzweig, Cynthia, Themessl, Matthias, Vincent, Katharine
This paper describes the motivation for the creation of the Vulnerability, Impacts, Adaptation and Climate Services (VIACS) Advisory Board for the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6), its initial activities, and its plans to serve as a bridge between climate change applications experts and climate modelers. The climate change application community comprises researchers and other specialists who use climate information (alongside socioeconomic and other environmental information) to analyze vulnerability, impacts, and adaptation of natural systems and society in relation to past, ongoing, and projected future climate change. Much of this activity is directed toward the co-development of information needed by decision-makers for managing projected risks. CMIP6 provides a unique opportunity to facilitate a two-way dialog between climate modelers and VIACS experts who are looking to apply CMIP6 results for a wide array of research and climate services objectives. The VIACS Advisory Board convenes leaders of major impact sectors, international programs, and climate services to solicit community feedback that increases the applications relevance of the CMIP6-Endorsed Model Intercomparison Projects (MIPs). As an illustration of its potential, the VIACS community provided CMIP6 leadership with a list of prioritized climate model variables and MIP experiments of the greatest interest to the climate model applications community, indicating the applicability and societal relevance of climate model simulation outputs. The VIACS Advisory Board also recommended an impacts version of Obs4MIPs and indicated user needs for the gridding and processing of model output.
Historical greenhouse gas concentrations for climate modelling (CMIP6)
2017, Meinshausen, Malte, Vogel, Elisabeth, Nauels, Alexander, Lorbacher, Katja, Meinshausen, Nicolai, Etheridge, David M., Fraser, Paul J., Montzka, Stephen A., Rayner, Peter J., Trudinger, Cathy M., Krummel, Paul B., Beyerle, Urs, Canadell, Josep G., Daniel, John S., Enting, Ian G., Law, Rachel M. Law, Lunder, Chris R., O'Doherty, Simon, Prinn, Ron G., Reimann, Stefan, Rubino, Mauro, Velders, Guus J.M., Vollmer, Martin K., Wang, Ray H.J., Weiss, Ray
Atmospheric greenhouse gas (GHG) concentrations are at unprecedented, record-high levels compared to the last 800000 years. Those elevated GHG concentrations warm the planet and – partially offset by net cooling effects by aerosols – are largely responsible for the observed warming over the past 150 years. An accurate representation of GHG concentrations is hence important to understand and model recent climate change. So far, community efforts to create composite datasets of GHG concentrations with seasonal and latitudinal information have focused on marine boundary layer conditions and recent trends since the 1980s. Here, we provide consolidated datasets of historical atmospheric concentrations (mole fractions) of 43 GHGs to be used in the Climate Model Intercomparison Project – Phase 6 (CMIP6) experiments. The presented datasets are based on AGAGE and NOAA networks, firn and ice core data, and archived air data, and a large set of published studies. In contrast to previous intercomparisons, the new datasets are latitudinally resolved and include seasonality. We focus on the period 1850–2014 for historical CMIP6 runs, but data are also provided for the last 2000 years. We provide consolidated datasets in various spatiotemporal resolutions for carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), as well as 40 other GHGs, namely 17 ozone-depleting substances, 11 hydrofluorocarbons (HFCs), 9 perfluorocarbons (PFCs), sulfur hexafluoride (SF6), nitrogen trifluoride (NF3) and sulfuryl fluoride (SO2F2). In addition, we provide three equivalence species that aggregate concentrations of GHGs other than CO2, CH4 and N2O, weighted by their radiative forcing efficiencies. For the year 1850, which is used for pre-industrial control runs, we estimate annual global-mean surface concentrations of CO2 at 284.3ppm, CH4 at 808.2ppb and N2O at 273.0ppb. The data are available at https://esgf-node.llnl.gov/search/input4mips/ and http://www.climatecollege.unimelb.edu.au/cmip6. While the minimum CMIP6 recommendation is to use the global- and annual-mean time series, modelling groups can also choose our monthly and latitudinally resolved concentrations, which imply a stronger radiative forcing in the Northern Hemisphere winter (due to the latitudinal gradient and seasonality).
The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6
2016, O'Neill, Brian C., Tebaldi, Claudia, van Vuuren, Detlef P., Eyring, Veronika, Friedlingstein, Pierre, Hurtt, George, Knutti, Reto, Kriegler, Elmar, Lamarque, Jean-Francois, Lowe, Jason, Meehl, Gerald A., Moss, Richard, Riahi, Keywan, Sanderson, Benjamin M.
Projections of future climate change play a fundamental role in improving understanding of the climate system as well as characterizing societal risks and response options. The Scenario Model Intercomparison Project (ScenarioMIP) is the primary activity within Phase 6 of the Coupled Model Intercomparison Project (CMIP6) that will provide multi-model climate projections based on alternative scenarios of future emissions and land use changes produced with integrated assessment models. In this paper, we describe ScenarioMIP's objectives, experimental design, and its relation to other activities within CMIP6. The ScenarioMIP design is one component of a larger scenario process that aims to facilitate a wide range of integrated studies across the climate science, integrated assessment modeling, and impacts, adaptation, and vulnerability communities, and will form an important part of the evidence base in the forthcoming Intergovernmental Panel on Climate Change (IPCC) assessments. At the same time, it will provide the basis for investigating a number of targeted science and policy questions that are especially relevant to scenario-based analysis, including the role of specific forcings such as land use and aerosols, the effect of a peak and decline in forcing, the consequences of scenarios that limit warming to below 2°C, the relative contributions to uncertainty from scenarios, climate models, and internal variability, and long-term climate system outcomes beyond the 21st century. To serve this wide range of scientific communities and address these questions, a design has been identified consisting of eight alternative 21st century scenarios plus one large initial condition ensemble and a set of long-term extensions, divided into two tiers defined by relative priority. Some of these scenarios will also provide a basis for variants planned to be run in other CMIP6-Endorsed MIPs to investigate questions related to specific forcings. Harmonized, spatially explicit emissions and land use scenarios generated with integrated assessment models will be provided to participating climate modeling groups by late 2016, with the climate model simulations run within the 2017–2018 time frame, and output from the climate model projections made available and analyses performed over the 2018–2020 period.
Implications of potentially lower climate sensitivity on climate projections and policy
2014, Rogelj, Joeri, Meinshausen, Malte, Sedláček, Jan, Knutti, Reto
Climate sensitivity, the long-term temperature response to CO2, has been notoriously difficult to constrain until today. Estimates based on the observed warming trends favor lower values, while the skill with which comprehensive climate models are able to simulate present day climate implies higher values to be more plausible. We find that much lower values would postpone crossing the 2 °C temperature threshold by about a decade for emissions near current levels, or alternatively would imply that limiting warming to below 1.5 °C would require about the same emission reductions as are now assumed for 2 °C. It is just as plausible, however, for climate sensitivity to be at the upper end of the consensus range. To stabilize global-mean temperature at levels of 2 °C or lower, strong reductions of greenhouse gas emissions in order to stay within the allowed carbon budget seem therefore unavoidable over the 21st century. Early reductions and the required phase-out of unabated fossil fuel emissions would be an important societal challenge. However, erring on the side of caution reduces the risk that future generations will face either the need for even larger emission reductions or very high climate change impacts.
Historic and future increase in the global land area affected by monthly heat extremes
2013, Coumou, Dim, Robinson, Alexander
Climatic warming of about 0.5 ° C in the global mean since the 1970s has strongly increased the occurrence-probability of heat extremes on monthly to seasonal time scales. For the 21st century, climate models predict more substantial warming. Here we show that the multi-model mean of the CMIP5 (Coupled Model Intercomparison Project) climate models accurately reproduces the evolution over time and spatial patterns of the historically observed increase in monthly heat extremes. For the near-term (i.e., by 2040), the models predict a robust, several-fold increase in the frequency of such heat extremes, irrespective of the emission scenario. However, mitigation can strongly reduce the number of heat extremes by the second half of the 21st century. Unmitigated climate change causes most (>50%) continental regions to move to a new climatic regime with the coldest summer months by the end of the century substantially hotter than the hottest experienced today. We show that the land fraction experiencing extreme heat as a function of global mean temperature follows a simple cumulative distribution function, which depends only on natural variability and the level of spatial heterogeneity in the warming.
Half a degree additional warming, prognosis and projected impacts (HAPPI): Background and experimental design
2017, Mitchell, Daniel, AchutaRao, Krishna, Allen, Myles, Bethke, Ingo, Beyerle, Urs, Ciavarella, Andrew, Forster, Piers M., Fuglestvedt, Jan, Gillett, Nathan, Haustein, Karsten, Ingram, William, Iversen, Trond, Kharin, Viatcheslav, Klingaman, Nicholas, Massey, Neil, Fischer, Erich, Schleussner, Carl-Friedrich, Scinocca, John, Seland, Øyvind, Shiogama, Hideo, Shuckburgh, Emily, Sparrow, Sarah, Stone, Dáithí, Uhe, Peter, Wallom, David, Wehner, Michael, Zaaboul, Rashyd
The Intergovernmental Panel on Climate Change (IPCC) has accepted the invitation from the UNFCCC to provide a special report on the impacts of global warming of 1.5°C above pre-industrial levels and on related global greenhouse-gas emission pathways. Many current experiments in, for example, the Coupled Model Inter-comparison Project (CMIP), are not specifically designed for informing this report. Here, we document the design of the half a degree additional warming, projections, prognosis and impacts (HAPPI) experiment. HAPPI provides a framework for the generation of climate data describing how the climate, and in particular extreme weather, might differ from the present day in worlds that are 1.5 and 2.0°C warmer than pre-industrial conditions. Output from participating climate models includes variables frequently used by a range of impact models. The key challenge is to separate the impact of an additional approximately half degree of warming from uncertainty in climate model responses and internal climate variability that dominate CMIP-style experiments under low-emission scenarios. Large ensembles of simulations (> 50 members) of atmosphere-only models for three time slices are proposed, each a decade in length: the first being the most recent observed 10-year period (2006–2015), the second two being estimates of a similar decade but under 1.5 and 2°C conditions a century in the future. We use the representative concentration pathway 2.6 (RCP2.6) to provide the model boundary conditions for the 1.5°C scenario, and a weighted combination of RCP2.6 and RCP4.5 for the 2°C scenario.