Researcher Highlight: Jennifer Morris

Originally published in our May 2020 newsletter (Issue 4)

By Jennifer Morris

I am a research scientist at the MIT Joint Program on the Science and Policy of Global Change, where an integrated team of natural scientists, economists, engineers and political scientists studies the complex interactions among co-evolving human and natural systems. Prior to this role, I earned my PhD in Engineering Systems and a M.S. in Technology and Policy from MIT, and a B.A. in Public Policy from UNC Chapel Hill. This interdisciplinary background draws me to the Multi-Sector Dynamics (MSD) community, which aligns well with my research. I am excited to serve as a member of the MSD Scientific Steering Committee.

My research focuses on energy-economic modeling, coupled human-natural systems, and uncertainty and risk analysis. I contribute to the development of the MIT Integrated Global System Model (IGSM), focusing on the human system component, the Economic Projection and Policy Analysis (EPPA) model. I employ this modeling framework for a wide range of studies. I design and conduct large ensembles of the model to investigate uncertainties, explore energy transitions and economic development pathways for meeting long-term societal goals, examine regional and sectoral interactions, and investigate avenues for capturing important dynamics in the model (such as climate impacts on human systems, the speed of energy transitions, and changing consumer preferences). 

A large part of my research focuses on uncertainty— quantifying key uncertainties, assessing risks and their coevolution, and applying different methodological approaches to models in order to formally represent uncertainties and explore how they impact near-term decisions. A key focus is evaluating risks to different investment options in energy, water and coastal adaptation.

Recent work has focused on representing uncertain influences and stressors in human and natural systems. I have quantified key socio-economic uncertainties (e.g. economic and population growth, the cost of technologies, resource availability, etc.) and conducted probabilistic ensembles with the EPPA model. I have worked closely with the climate scientists undertaking parallel tasks with the MIT Earth System Model (MESM). Together, we developed integrated ensembles for various climate stabilization futures (see figure below of our framework), and use the results in a wide variety of studies of coupled human-natural systems. We take a telescopic approach from global to regional to sectoral or sub-regional, harmonizing scenarios and assumptions across models of different levels of resolution and coupling. 

I aim to continue this type of work that combines human and natural systems models of different scales in a consistent framework to inform more local decision-making under uncertainty. To that end, my group at the MIT Joint Program has started an exciting a new DOE-funded project focused on the Mississippi River Basin region. We will explore compounding risks in the region (including those related to extreme events, demographics, economic and energy transitions, etc.), resilience and tipping points in the face of co-evolving natural, built and human systems, teleconnections between sub-regions, and local vs. system-level decision-making.

My work fits well with the MSD themes of adaptive human actions, model coupling, sectoral interactions and dependencies, and stressors and uncertainties. I very much look forward to helping to grow the MSD community and expanding collaborations in these important research areas.

Highlighted articles:
Chen, Y.-H.H. et al. (2016): Long-term economic modeling for climate change assessment. Economic Modelling, 52 (Part B): 867–883.
Monier, E. et al.(2018): Toward a consistent modeling framework to assess multi-sectoral climate impacts
Morris, J.F. et al. (2019): Advanced Technologies in Energy-Economy Models for Climate Change Assessment. Energy Economics, 80 (476-490)
Morris, J. et al. (2018): Hedging Strategies: Electricity Investment Decisions under Policy Uncertainty. Energy Journal, 39(1)  

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