To understand the scale and scope of a challenge, modelers start with a reference scenario. This is also variously called “business as usual” (as in En-ROADS) or a “baseline scenario.” The purpose of these scenarios is to characterize a dynamic challenge by showing a pattern of behaviors overtime that policy actions can then be compared against. So for example, the Business as Usual (BAU) scenario that appears as the default in En-ROADS was created as a starting point from which to test various changes in policies and assumptions to see the impacts on our global climate. It was not designed as a prediction of the most likely future for our world.


Our Business as Usual scenario was designed to be consistent with the baseline scenario for SSP2. The SSPs, or shared socioeconomic pathways, are a set of scenario narratives developed for the integrated assessment models. SSP2 is called the “Middle of the Road” scenario, as it represents a future with some challenges to climate change mitigation but reflects continued progress in technological development. In SSP2, population growth stabilizes towards the end of the century and the economy continues to grow steadily. Other SSPs represent different future scenarios with some resulting in better outcomes for our climate and some worse.


Each SSP scenario has been run at different radiative forcing levels to see what combination of actions, like a carbon price, would be needed to achieve that radiative forcing level and resulting global temperature change. For the En-ROADS BAU, we used the SSP2 baseline so it doesn’t include added policies to achieve a certain climate outcome. In this regard, we choose to adopt the baseline scenario definition from one of the foundational papers on the SSP scenarios Riahi et al. (2017, – which explains the baseline scenario as "a description of future developments in absence of new climate policies beyond those in place today” and notes that “[t]he baseline SSP scenarios should be considered as reference cases for mitigation, climate impacts and adaptation analyses.” 


In creating the En-ROADS BAU, we first built it up by looking across the research literature for global projections and trends in factors like population (coming from the UN), economic growth (coming from the World Bank), and historic greenhouse gas emissions (coming from the IPCC). This work was done initially at a level of 20 regions for our C-ROADS model and then was aggregated globally for En-ROADS. As we added these data sources and ran the model’s thousands of equations factoring in climate feedbacks, capital stock turnover, market dynamics, and more, we then compared our results to the SSP2 baseline scenarios of the six primary integrated assessment models - GCAM, MESSAGE-GLOBIOM, WITCH-GLOBIOM, IMAGE, AIM, and REMIND-MAGPIE.


The graph below shows the fit of En-ROADS (in blue) to the six IAM Baseline scenarios, as well as its place in between RCP 8.5 and RCP 6.0, in terms of temperature change from preindustrial levels.

There is debate about what many of the underlying parameters should be set at initially. We encourage curious users to vary the wide range of assumptions in En-ROADS about the climate, economy, and energy system to explore how sensitive their results are to uncertainty. We picked one set of assumptions to be our default, but users can select a different suite of sliders in advance of their En-ROADS activities and policy tests to use a different starting point, and then engage their audiences from there. Currently, you cannot change the Business as Usual scenario in En-ROADS.