The projections of climate impacts that are visualised on the PROVIDE climate risk dashboard were computed with climate models. These models describe the evolution of human or natural systems under different global warming scenarios by solving a range of mathematical equations. One characteristic of the PROVIDE project is that it largely makes use of emulators, that is, relatively simple models that imitate the behaviour of more complex ones. Their simplicity also means that they require less computing power, thus allowing us to explore more scenarios, or to conduct multiple runs of the models to better distinguish actual climate impacts from natural variation. Below we explain what models we have selected and their characteristics.


FaIR is a climate model emulator, replicating the warming behaviour of more complex climate models without the computational complexity. It simplifies the Earth system to consist of four locations that each store carbon, which may be interpreted as the Earth’s crust, the atmosphere and surface, the ocean mixing layer and the deep ocean. The levels of carbon in each layer are influenced by emissions, both human and natural. FaIR then calculates how these emissions translate into concentrations of greenhouse gas and aerosols using simple relationships, and combines them with estimates of other climate change drivers (such as cloud-formation from aviation, solar variability and land use reflectiveness changes) to give a model of the total strength of the forcing imposed on the climate system. This is then used to calculate the change in the average Earth’s temperature. The outputs are constrained to match both historic warming and the expected levels of future warming as set out by the Intergovernmental Panel on Climate Change (cross-chapter box 7 of WG1 chapter 5). We used FaIR version 1.6.4. For more details see Smith et al. 2018.


The Modular Earth System Model Emulator with spatially Resolved output (MESMER) is a statistical model that simulates the possible evolution of key climate variables over land areas for a given Global Mean Temperature (GMT) trajectory, by emulating the behaviour from more computationally expensive Earth System Models (ESMs). Calibrated on existing scenario projections produced by ESMs, it combines estimates of the local forced response of the climate to increasing emissions, as well as of the impact of natural climate variability. Its simplicity and flexibility allow it to produce very robust estimates of future possible climate outcomes within minutes, even for GMT trajectories it hasn't been trained on. The current MESMER analyses are based on Beusch et al. (2020) and Beusch et al. (2022); for a full description of the data see Schwaab et al. (in preparation). For further information see here.

More information about MESMER


The future impacts from climate change are associated with scenarios defined by the amount of greenhouse gas emissions or concentrations trajectories. While the change in global mean temperature (GMT) in these scenarios is a more direct driver of climate impacts, depending on the employed climate model there is considerable uncertainty on how GMT responds to emissions (a measure called climate sensitivity). Also, scenarios used for impact assessments are often not related to implemented climate policies, nor to policy objectives, like the goals of the Paris Agreement.

Temperature overshoot scenarios, where temperatures would exceed the 1.5°C limit temporarily, but are able to fall back below it before 2100, feature prominently in the literature on mitigation pathways, but their implications for the impacts of climate change have so far been under researched. Because climate and climate impact models are often complex and therefore expensive to run, impacts are commonly calculated for a limited number of scenarios, and few runs can be conducted to assess the influence of natural variability for one single scenario.

In the PROVIDE project, we try to address some of these limitations. A core idea of the scenario design is that GMT is the defining feature for assessing climate impacts. This means that we select scenarios that span a range of GMT outcomes with regard to near-term warming (until about 2050), peak warming, and overshoot, according to our best understanding of climate sensitivity and the associated uncertainty. We make sure to include some scenarios that reflect currently implemented or formulated policies, or that align with the long term temperature goal of the Paris Agreement. We consider scenarios that remain below the 1.5°C warming limit of the Paris Agreement or overshoot it by various extents, with some exhibiting a decrease in GMT after reaching peak warming, or not. Finally, because impact assessment in the PROVIDE project mostly relies on a suite of lightweight climate or climate impact model emulators, we can explore up to ten scenarios.

Eventually, the 10 PROVIDE scenarios for which resulting climate impacts can be explored in the Climate Risk Dashboard can help address the following research questions, which were kept in mind during the scenario selection and design process:

  • What is the difference between (a) permanently exceeding 1.5°C and stabilising at a higher level, (b) stabilising at 1.5°C of warming, (c) peaking above 1.5°C and returning to 1.5°C in either 2100 or 2300?
  • What is the difference between following current trends until 2100 and a 1.5°C-compatible world?
  • Assuming current policies until 2100, how much can temperatures be reversed until 2300?
  • What are the differences in societal risk for similar 1.5°C compatible pathways?
  • What can be said about the emergence of avoided climate risks in the near-term? What’s the range of different climate risks outcomes in 2050 – a timescale relevant for climate adaptation?
  • What are long-term (multi-century) climate outcomes from achieving and sustaining net zero greenhouse gas emissions? Is climate change fully reversible?
  • How does impact and overshoot reversibility depend on different levels of peak warming?

The ten emissions scenarios fall into three categories:

  • Seven of them were defined for the contribution of the Working Group III of the IPCC (focusing on mitigation of climate change) to its Sixth Assessment Report (AR6);
  • Two were defined as part of phase six of the Coupled Model Intercomparison Project (CMIP6), designed to provide multi-model climate projections that constituted the basis for many scientific assessments included in AR6;
  • One – the ‘Stabilisation at 1.5°C’ scenario – is designed by the PROVIDE consortium.

In the case of the first nine scenarios, they were selected from the AR6 database or other published datasets, and the GMT evolutions resulting from their greenhouse gas emissions trajectories were derived using the climate model emulator FaIR version 1.6.4 (see Models). For further information on the scenarios, please refer to the white paper describing them (Lamboll et al., 2022). The scenario data are publicly available via Zenodo.

Scenarios defined by the IPCC Working Group III for AR6

Most information included in this section is adapted from Section 1.5 of Chapter 1 of the IPCC Working Group III (WG3) contribution to AR6 (IPCC AR6 WG3 Ch1 | 2022, Grubb et al., 2022).

For AR6, the IPCC WG III considered more than 2500 model-based scenarios published in the scientific literature. Drawing from this database, five so-called Illustrative Mitigation Pathways (IMPs) were defined for the report to illustrate different possible global mitigation strategies that are recurrent across the entire WG III assessment. Additionally, two scenarios were selected from the database that illustrate the consequences of current climate policies and pledges. Originally defined for their characteristics with regard to global mitigation, these seven scenarios are re-used in the PROVIDE project so that resulting impacts can be assessed and compared. More information on them is provided in this section.

The PROVIDE scenarios based on the five Illustrative Mitigation Pathways are:

  • 1.5 - Shifting Pathway (short, SP)
  • 1.5 - High Renewables (Ren)
  • 1.5 - Low Demand (LD)
  • High Negative Emissions (Neg)
  • Delayed Action (DA)

In AR6 these were originally called IMP-SP, IMP-Ren, IMP-LD, IMP-Neg, and IMP-GS, respectively. The five IMPs are organised around two dimensions: the level of ambition consistent with meeting the Paris Agreement goals and key characteristics of the scenario related to mitigation strategies (for example, high levels of renewables deployment).

Apart from the IMPs, Current Policies (CurPol) was designed to investigate the outcomes of climate policies implemented in 2020, in case they only get gradually strengthened after 2030. The NDCs Pathway (NDC), originally called Moderate Action by the IPCC, explores the consequences of the implementation of the Nationally Determined Contributions to 2030 and no further reinforcement of climate policies thereafter. Both scenarios result in Global Mean Temperature levels above 2°C.

Delayed Action exhibits the lowest level of ambition of the five IMPs; it follows current policies until 2030 but could stay below 2°C if followed by very fast emissions cutbacks. The High Negative Emissions scenario is characterised by somewhat higher emission reductions by 2030, and a significant decrease in GMT in the second half of the 21st century achieved through the large-scale deployment of Carbon Dioxide Removal technologies in the energy and industry sectors leading to net global emissions. According to the best estimate of the calculations conducted with the FaIR climate model emulator, this decrease in GMT would bring global warming back to below 1.5°C after significant overshoot.

1.5 - Shifting Pathway, 1.5 - High Renewables and 1.5 - Low Demand illustrate other key characteristics related to mitigation strategies and all achieve rapid emission reductions in the short-term, which would keep global warming close to the 1.5°C limit of the Paris Agreement without large overshoot. A key mitigation strategy featured in 1.5 - Low Demand is exploiting opportunities for demand reduction. 1.5 - High Renewables shows how transforming energy systems through upscaling electrification and renewable energy penetration can also achieve massive emission reductions. In contrast, 1.5 - Shifting Pathway explores how shifting development pathways to achieve sustainable development goals can also result in deep emission reductions. These seven scenarios are meant to illustrate a range of climate futures linked to future emissions reductions. They also show that there are several ways to achieve the long-term temperature goal of the Paris Agreement. However, these scenarios are not intended to be comprehensive, and do not aim at illustrating the range of possible themes in the IPCC WG3 contribution to AR6. They are primarily scenarios of technological evolution and demand shifts that echo various global trends in societal choice. This means that they do not aim at capturing the whole range of possible future socioeconomic pathways and their consequences for mitigation, at reflecting regional variations in development and climate action, nor do they explore issues around income distribution and environmental justice.

Nevertheless, selecting these scenarios on the PROVIDE climate risk dashboard offers a good basis to explore impacts resulting from the GMT outcomes they would lead to, ultimately linked to the ability of the world’s individuals and societies to cut back greenhouse gas emissions. Because they span a range of possible climate futures, they are also helpful to approximate impacts from other scenarios defined by other characteristics with regard to global mitigation, but leading to similar outcomes in terms of emissions and resulting global warming.

Scenarios defined as part of phase six of the Coupled Model Intercomparison Project (CMIP6)

Most information included in this section is adapted from the paper by O’Neill et al., 2016. For more extensive information, please refer to this document.

The scenarios ssp1-1.9 and ssp5-3.4-OS were defined as part of Phase 6 of the Coupled Model Intercomparison Project (CMIP6). This numerical experiment was designed to compare climate projections of various climate models for a common set of greenhouse gas emissions or concentration scenarios. The resulting climate and climate impact projections have been described in many peer-reviewed studies. Given their prominence in the climate and climate impact modelling community, they are being considered under the PROVIDE project to provide an easy way to compare our results to previously published ones.

Both ssp1-1.9 and ssp5-3.4-OS are driven by emissions and land use trajectories produced with integrated assessment models (IAMs) based on future pathways of societal development, the shared socioeconomic pathways (SSPs, see Riahi et al., 2016). There are five SSPs in total, which follow distinct broad narratives and describe potential futures in which challenges for adaptation and mitigation vary from low to high:

  • SSP1: Sustainability (taking the green road, low challenges to mitigation and adaptation)
  • SSP2: Middle of the road (medium challenges to mitigation and adaptation)
  • SSP3: Regional rivalry (a rocky road, high challenges to mitigation and adaptation)
  • SSP4: Inequality (a road divided, low challenges to mitigation, high challenges to adaptation)
  • SSP5: Fossil-fueled development (taking the highway, high challenges to mitigation, low challenges to adaptation)

The narratives of SSP1 and SSP5 were used as a basis to derive the emissions trajectories for ssp1-1.9 and ssp5-3.4-OS, respectively.

ssp1-1.9 and ssp5-3.4-OS are also related to representative concentration pathways (RCPs; van Vuuren et al., 2011), a set of pathways of land use emissions and emissions of air pollutants and greenhouse gases that span a wide range of future outcomes through 2100 and have commonly been used in the climate modelling community.

Produced within the Phase 5 of CMIP (CMIP5) using IAMs, their use was central for climate science research conducted during the IPCC Fifth Assessment Report (AR5) cycle. The change in energy flux in the atmosphere due to human activities (called radiative forcing and expressed in W/m2) achieved at the end of the 21st century and relative to pre-industrial levels, define the RCPs as well as the SSP-RCP combinations: for example 1.9 W/m2 for ssp1-1.9 and 3.4 W/m2 for ssp5-3.4-OS.

Because it doesn’t exceed relatively low radiative forcing values along the 21st century, ssp1-1.9 is considered as being compatible with the long-term temperature goal of the Paris Agreement (keeping the global mean temperature increase compared to pre-industrial levels well below 2°C, and bringing it back down to below 1.5°C by 2100).

ssp5-3.4-OS investigates the implications of a substantial 21st century overshoot in radiative forcing relative to a longer-term target. This scenario follows SSP5-8.5 through 2040, at which point aggressive mitigation is undertaken to rapidly reduce emissions to zero by about 2070 and to net negative levels thereafter. Such a level of mitigation would be more ambitious than what is happening in most high-ambition scenarios simulated with IAMs, and is thus deemed unfeasible. However, ssp5-3.4-OS provides a way to explore the consequences of such colossal variations for the climate system.

The ‘Stabilisation at 1.5°C’ scenario

This scenario has been designed through the PROVIDE project. It is meant to assess climate impacts if global mean temperature is held constant at 1.5°C above pre-industrial levels, and how these would differ from other scenarios where global mean temperature would exceed and potentially be brought back down to below this global warming level.