The Paris Agreement was a historic milestone in global efforts to combat climate change. The countries agreed to take action to keep the global average temperature rise well below 2°C and to make efforts to limit warming to 1.5°C. The researchers studied what happens when climate models are performed with an emissions scenario rather than concentration scenarios to partially account for these feedbacks, and found that CO2 concentrations and the resulting warming were significantly higher than predicted by a concentration trajectory analysis. This agreement assumed that greenhouse gas emissions would quickly peak and begin to decline almost immediately, but that did not happen. While emissions remained stable in 2015 and 2016, they increased in 2017, reaching a record high of 53.5 gigatonnes of CO2 equivalent, which includes emissions from fossil fuels, industry and land use changes such as deforestation. Another record followed in 2018. When characterizing climate change projections, it is considered whether the RCP 8.5 climate change scenario represents a “business as usual”, a “high emissions” scenario, or a “worst-case” scenario. In addition, it is questioned whether RCP 8.5 is compatible with the current emission trajectory and whether RCP 8.5 is the alternative route offered by world leaders engaged in the use of fossil fuels. The creators of RCP8.5 did not intend this to be the most likely outcome of the “status quo”, pointing out that “no probability or preference is associated with any of the specific scenarios”. Its subsequent use as such represents a kind of break in communication between energy system modellers and the climate modelling community.
Instead of starting with detailed socio-economic scenarios to generate emissions and climate scenarios, as was the case with SRES scenarios, the energy system modelling community decided to first create future “radiative forcing” scenarios for climate modelling that are not associated with a specific single socio-economic or emission scenario. Radiative forcing is a measure of the combined effect of greenhouse gases, aerosols and other factors that can affect the climate to capture additional heat. PCRs can be combined with SSPs to derive emission and concentration scenarios that take up the socio-economic assumptions underlying SSPs, and then impose climate policies to achieve the radiative forcing values defined by THE PCRs by the end of the century. Therefore, SSPs and RCPs can be organized into a matrix of climate propulsion outcomes (in rows) and socio-economic development assumptions (in columns). This matrix scenario architecture provides a powerful tool for exploring the space of climate change response options. The scenarios and pathways that populate individual cells are referred to in the literature as SSP x–y (x = SSP number; y = radiative forcing level). It also distinguishes them from the original PCRs used to advance climate change projections in the fifth Climate Model Intercomparison Project (CMIP5). These original PCRs were not derived from SSPs, as SSPs were only developed a few years later. However, emissions projections and forced to advance the next round of climate change projections, CMIP6, will use the new scenarios based on the SSP, e.B.
SSP 1-2.6 instead of the original RCP 2.6. Climate modelers have slightly different needs than energy system modelers in future emission scenarios. While energy system modelers want to look at a number of different outcomes under different socioeconomic assumptions – such as future population and economic growth – climate modelers want outcomes that lead to significantly different levels of warming in order to effectively assess and compare the results. In RCP 8.5, emissions continue to increase into the 21st century. [13] Since AR5, this is considered very unlikely, but still possible, as feedbacks are not well understood. [17] RCP8.5, which was generally used as a basis for worst-case climate change scenarios, was based on an overestimation of projected coal production. The RCP8.5 scenario has therefore become a challenge ground, with one report describing it as “implausible with each passing year”. [18], while another argues for its usefulness, based on its relevance to other pathways, both for tracking cumulative cumulative CO2 emissions and for predicting mid-century emissions based on current and stated policies. [19] Climate change management is essentially a matter of risk management, and it is therefore important to know the projected impacts in high and low emission scenarios, regardless of the probability of each scenario. .