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Last month, the Intergovernmental Panel on Climate Change (IPCC) released the first part of its sixth assessment report (AR6), making headlines around the world for its stark portrayal of future climate change. The report (otherwise known as the Working Group I contribution or Climate Change 2021: The Physical Science Basis) serves as an aggregation of the latest climate science, compiling and synthesizing the work of thousands of scientific publications from across the world. The IPCC’s AR6 utilizes the latest climate model data and analytical techniques, which will now become standard for evaluating the impacts of climate change. In this post, we will explore the key differences between this report and previous iterations, and outline how we plan to incorporate advancements made to the underlying data into our assessments of climate risk.
One of the key differences between the previous IPCC report (AR5) and AR6 is the climate model data underlying many of the findings and projections. AR6 uses the latest generation of climate models, coordinated by the World Climate Research Programme’s Coupled Model Intercomparison Project, version 6 (CMIP6). This project is a collection of models from scientific institutions around the world, implementing the latest science and technology to produce projections of future climate. In total, more than 30 institutions contributed to over 40 models ultimately used in the IPCC’s assessment.
The CMIP6 climate models are based on updated emissions pathways. In CMIP5 (the previous set of models), Representative Concentration Pathways (RCPs) were used as sample trajectories of radiative forcing which relate to the greenhouse gas effect and trapping of heat in the Earth’s atmosphere ultimately resulting in global temperature increases. While useful approximations for understanding a range of climate impacts under different emissions pathways, it was difficult to link RCPs with real-world scenarios for emissions, land use and change and political interventions. As a result, the new climate models use RCPs coupled with Shared Socioeconomic Pathways (SSP-RCPs) which include more robust “storylines” of factors intrinsically linked to climate change, such as population growth, urbanization, and technologic advancements to mitigate climate change. These generally relate to the RCPs used in CMIP5, with RCP8.5 and RCP4.5 still being used (in addition to new RCPs), but now in conjunction with SSPs to provide additional context. SSP-RCPs also more closely align with certain end-of-century temperature targets, such as the 1.5° set forth in the Paris Agreement and provide insight into the timing of crossing certain thresholds. With these new pathways, it becomes easier to understand how different actions could manifest in the form of future climate impacts. In total, five SSP-RCPs will be available for use in climate risk assessments, as shown in Table 1.
While generally comparable to CMIP5 generation models, CMIP6 has taken a step forward by improving the overall quality of climate projections. Due to advancements in computing, the spatial resolution of the models is generally finer. However, the granularity of 1-2° latitude x longitude grid cells (~100-200km) is still relatively coarse for the purpose of impact assessments prior to any downscaling efforts. The performance of models in simulating past conditions has also improved, in part due to better understanding of complex physical processes (such as modeling clouds and aerosols) and due to the availability of a more robust observational record used to tune the models. As a result, climate scientists have refined the expected range of the Earth’s response to emissions, an important step in understanding how drastically global temperature may increase over the course of the next century. Together, these advancements point to more reliable models with a reduced range of possible outcomes within a given SSP-RCP (Figure 1), helping us to better model future climate change.
Projected end-of-century temperature anomalies within SSP-RCPs have a narrower uncertainty range than in AR5, but generally also run slightly hotter compared to previous models. AR6 also evaluates when we may cross key temperature thresholds, such as the Paris Agreement 1.5°C (which is during the 2030s in most SSP-RCPs). Other key improvements help refine estimates for particularly complex variables which have direct impacts on society. For instance, a better understanding of Greenland and Antarctic ice sheet processes have helped address uncertainty surrounding sea level estimates, particularly towards the end of the century. While the confidence intervals vary by region and hazard, it is becoming increasingly clear which impacts are most likely to affect certain areas around the globe.
The arrival of the IPCC’s AR6 and its use of CMIP6 and SSP-RCPs marks an important milestone in the climate risk space. Going forward, we plan to integrate this latest generation of climate models into our analytics. We will also leverage the latest thinking in climate science as we develop new products, for instance by incorporating SSP-RCPs into our scenario analysis offerings. By utilizing the latest data from CMIP6 and key methodologies identified by the IPCC, we can continue to ensure our analyses use the latest science to best capture future climate risk.
Even with the tremendous depth of this report, there is still more to come from the IPCC. Working Group II and III contributions (Climate Change 2022: Impacts, Adaptation, and Vulnerability and Climate Change 2022: Mitigation of Climate Change) are scheduled to be released next year and will explore how the findings from this report will impact society and how the worst-case scenarios may be avoided. These compendiums are an invaluable resource for understanding the latest climate science and they highlight the urgency of responding to climate change. Climate risk assessments can leverage the work of the IPCC and CMIP to bring a refined understanding of climate risk to global stakeholders, informing the increasingly critical efforts to build effective climate resilience where most needed.
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