Originally published in our May 2021 newsletter (Issue 9)
Researchers and analysts use computer-based mathematical models, such as multisector human-Earth systems models, to explore long-term changes to the energy system and its co-evolution with other systems. These tools support science-based decision-making in a variety of contexts; most studies utilizing multisector models employ scenarios to account for future uncertainty. At the Pacific Northwest National Laboratory’s (PNNL) Joint Global Change Research Institute (JGCRI), an interdisciplinary group of researchers developed a three-part framework to evaluate and update the future energy system scenarios generated by these models. First, model users develop a qualitative description (narrative) of future changes to the energy system which informs choices about model structures and parameters. Second, metrics quantify model outcomes that correspond to key elements of the scenario narrative. Finally, evaluation criteria judge consistency between the numerical model results (metrics) and scenario storyline.
After developing this flexible framework, the research team applied it to the reference scenario in GCAM-USA, a version of the multisector Global Change Analysis Model with state-level detail in the United States, focusing on the electric power sector. With this novel approach, the researchers found that (1) having a well-defined set of criteria both simplified and improved the process of evaluating model developments; (2) it’s possible for model developments to improve scenario consistency for some metrics but decrease it for others; and (3) some outlier results can be explained by unique regional dynamics and thus are not necessarily indicative of issues with model parameters or the scenario narrative. The paper also demonstrated how visualization techniques that simultaneously display results for many regions and automatically flag anomalous results can help streamline the scenario evaluation process.
This study makes several contributions to the MSD community. First, the structured evaluation framework developed by the researchers helps scientists identify and correct model deficiencies, refine their understanding of future changes in the energy system, and highlights interesting exceptions to anticipated trends. Additionally, as the spatial, temporal, and sectoral resolution of multisector models continues to increase, a systematic approach to scenario evaluation helps manage this increased complexity. The Binsted et al. scenario framework was designed to be flexible and can be applied to other regions and sectors. Finally, carefully evaluating multisector models and the scenarios they produce gives users more confidence in the analytical insights they generate and helps maintain their credibility as scientific tools.
The Binsted et al. 2020 paper counts four early-career MSD Community researchers among its co-authors. Matthew Binsted, Kalyn Dorheim, and Zarrar Khan are scientists at the Joint Global Change Research Institute. Ryna Cui is an Assistant Research Professor at the Center for Global Sustainability at the University of Maryland School of Public Policy; she holds a joint appointment at JGCRI and is a member of the MSD Working Group on Professional Development and Education for Early Career Scientists. Each brought unique expertise to the development of this scenario evaluation framework.
Recently, Gokul—along with Neal Graham, Mohamad Hejazi, and Son H. Kim—coordinated the improved representation of water supplies and demands within GCAM-USA. As a result, GCAM-USA now includes state-level representations of energy, state- and basin- level representations of water and land systems, and interactions across them. Since GCAM-USA also represents the rest of the world in the same regions as GCAM, these improvements allow users to run a broad range of multi-decadal scenarios of human and natural systems with subnational details in a consistent, integrated framework that simultaneously accounts for subnational dynamics within the USA while also capturing key interactions in the rest of the globe.
In addition, Gokul led a team of researchers including Marshall Wise, Pralit Patel, Matthew Binsted, Son Kim, Yang Ou, and Zarrar Khan to incorporate improved state-level technology, resource, and socioeconomic assumptions in GCAM-USA. More recently, the team incorporated information about sub-annual (monthly day/night) electricity load profiles, and separate markets for electric capacity and electricity demand in GCAM-USA. In addition, the team implemented dynamically and endogenously changing load profiles in response to future temperature changes and associated investment and operation decisions within GCAM-USA. The improved model also includes representations of key structural elements of the power sector such as electricity trade across multi-state grids and between states within a grid. Ongoing efforts at JGCRI are focused on expanding this capability to the rest of the globe and including representations of electric storage.
Gokul’s current research also focuses on better understanding how regional teleconnections through trade and resource supply networks can affect the co-evolution of energy-water-land systems within the USA and globally. As part of this effort, Gokul is coordinating efforts across JGCRI to improve representation of water resources and energy trade, incorporate mineral resources and trade, and implement forest trade in GCAM. His work is expected to provide a quantification and mapping of regional teleconnections across the globe for energy, water, land systems in the 21st century.
Matthew’s research has explored energy system transitions with a focus on the electric power sector; he is also a lead developer of GCAM-USA and has collaborated with Canadian and Indian researchers working to develop subnational versions of GCAM for their respective countries. Ryna’s current research focuses on energy transitions, global and national low-carbon development pathways, and the interaction between national and subnational policy decisions. Kalyn’s work focuses on developing and using climate emulators to provide computationally inexpensive climate information to the MSD community; recently she has focused on calibrating Hector, an open-source climate model, to emulate more complex Earth System Models. Zarrar’s research focuses on developing tools and methodologies to promote stakeholder engagement and facilitating the analysis of global modeling outputs in the context of local issues. His recent work focuses on the analysis and visualization of global modeling outputs at finer decision relevant spatial and temporal scales. Collectively, their work contributes to advancing the development, evaluation, application, and accessibility of multisector human-Earth system models.
Highlighted articles:
M. Binsted, et al., 2020. Evaluating long-term model-based scenarios of the energy system. https://doi.org/10.1016/j.esr.2020.100551
Cui, R.Y. et al., 2018. Regional responses to future, demand-driven water scarcity. https://doi.org/10.1088/1748-9326/aad8f7
Dorheim, K., Link, R., Hartin, C., Kravitz, B., & Snyder, A. (2020). Calibrating simple climate models to individual Earth system models: Lessons learned from calibrating Hector. https://doi.org/10.1029/2019EA000980
Khan, Z., Wise, M., Patel, P., Kim, S.H., Hejazi, M., Burleyson, C., and Iyer, G., 2021. Impacts of long-term temperature change and variability on electricity investments. https://doi.org/10.1038/s41467-021-21785-1