The North Central Climate Adaptation Science Center (NC CASC) provides climate science support for resource managers, researchers, and stakeholders navigating climate-related challenges. As part of this effort, we offer resources and expertise to help interpret and apply climate data to decision-making.

Imtiaz Rangwala, lead climate scientist, helped review one of these efforts: the Coupled Model Intercomparison Project Phase 6 (CMIP6) to ensure its scientific robustness and relevance. CMIP6 is an international collaboration that compiles global climate projections from numerous modeling centers across the world. These models use standardized scenarios, which include scenarios of future greenhouse gas emissions, to simulate past and future climate conditions, aiding research and adaptation planning. CMIP6 models generally offer higher spatial resolution and complexity compared to CMIP5 (the previous compilation), and also include a broader range of emissions scenarios and more simulations per scenario. While CMIP6 shows overall improvements, the advancements don't render CMIP5 obsolete; the choice between them depends on specific use cases. 

Approximately 25% of CMIP6 models project greater future warming than previous iterations, sometimes exceeding observed historical warming trends. This raises concerns about their physical plausibility. Methods have been developed to screen or weight these "hot" models, but their projections shouldn't be entirely discounted, especially for regional analyses of variables like precipitation. CMIP6 utilizes eight emissions scenarios, known as Shared Socioeconomic Pathways (SSPs), representing various future trajectories of greenhouse gas emissions and land-use changes. Four of these (SSP1-2.6, SSP2-4.5, SSP4-6.0, SSP5-8.5) are comparable to the Representative Concentration Pathways (RCPs) used in CMIP5. 

Selecting SSPs depends on factors such as the likelihood of scenarios, data availability, planning timeframe, and system vulnerability. SSP2-4.5 and SSP4-6.0 are frequently recommended as they align with current policies and emissions trends. However, data availability differs, and for analyses with longer time horizons, the choice of scenario may have a greater impact.

In the most recent Intergovernmental Panel on Climate Change Report (IPCC AR6), the scientific community promoted a relatively new approach for framing the risk of climate change that uses Global Warming Levels (GWLs). The GWL approach facilitates assessments of regional climate changes and impacts for specific global temperature increases (e.g., +2°C or +3°C global warming), independent of exact timing or emissions scenarios. This method provides a promising and versatile framework for risk assessment but may require adaptation for traditional planning approaches which are typically centered on specific time horizons. 

For the United States, CMIP6 and CMIP5 projections show similar spatial patterns in future temperature and precipitation changes. However, CMIP6 models generally indicate slightly greater warming, even after accounting for "hot" models. These differences could influence assessments of temperature-related vulnerabilities and, potentially, hydrological and ecological impacts. The range of uncertainties in CMIP6 projections is comparable to that in CMIP5, when considering factors like emissions scenarios, model differences, and natural variability. Consulting a larger number of models typically reveals greater uncertainty, emphasizing the importance of considering multiple projections in planning. 

For new analyses, utilizing CMIP6 is advisable if suitable data are accessible. However, existing CMIP5-based analyses do not necessarily require updating solely to incorporate CMIP6 data. The decision should be based on the specific context and data needs. CMIP6 datasets are available through various platforms, including the Earth System Grid Federation (ESGF) and cloud-based services. While these platforms offer extensive data, they may require advanced data handling skills. More user-friendly options with visualization tools are also available but may provide access to only a subset of the full dataset. 

Several CMIP6 downscaling projects are underway to provide higher-resolution data and new capabilities, such as additional variables and improved simulation of fine-scale processes. These efforts aim to enhance the applicability of CMIP6 data for regional and local analyses. Communities with limited resources, including in the North Central region of the United States, may benefit from focusing on understanding their specific vulnerabilities and accessing existing climate assessments and resources. Collaborating with organizations like the North Central Climate Adaptation Science Center, that provide regional climate adaptation support can also provide valuable assistance in interpreting and applying CMIP6 data to resource management decisions. For a comprehensive understanding and detailed answers to these topics, refer to the full CMIP6 FAQs document provided by the Water Utility Climate Alliance here.