Risk Analysis

Representing socio-economic uncertainty in human system models

Abstract: Future global socio-economic development pathways and their implications for the environment are highly uncertain, as are the technology mixes associated with different global environmental targets.

To develop a range of possible future outcomes, we develop probability distribution estimates for key input parameters of a model of global human activity. Latin Hypercube Sampling is applied to draw 400 samples from the probability distributions for each uncertain input variable, including costs of advanced energy technologies, energy efficiency trends, fossil fuel resource availability, elasticities of substitution, population, and labor and capital productivity. The sampled values are simulated through a multi-sector, multi-region, recursively dynamic model of the world economy.

The results are 400-member ensemble simulations describing future energy and technology mixes as well as GDP and emissions. We find that many patterns of energy and technology development are consistent with various long-term environmental pathways, and that sectoral output for most sectors is little affected through 2050 by the long-term temperature target, but with tight constraints on emissions, emission intensities must fall much more rapidly.

We also combine uncertainty quantification and scenario discovery to investigate scenarios with similar values for one outcome and the range of other outcomes in those scenarios. This analysis illustrates how many combinations of outcomes can be consistent with an outcome of interest. For example, many different technology outcomes can be consistent with high or low economic growth.

A consistent framework for uncertainty in coupled human-Earth system models

Abstract: Addressing climate change is ultimately a challenge of risk management, which requires an understanding of the likelihood of potential outcomes. We provide integrated, probabilistic socio-economic and climate projections obtained using updated estimates of probability distributions for key parameters in both the human and Earth system components of the MIT Integrated Global System Model (IGSM).

The Reference scenario results in median end-of-century warming of 3.5oC and a 90% range of 2.8-4.3oC, which is lower than the median of 5.7oC from a prior study using a previous version of the IGSM. About 0.5oC of the difference is due to updated estimates in the human system and the rest of the difference is explained by changes in Earth system estimates.

Our results show that climate policy lowers the upper tail of temperature change distributions more than the median, and that even relatively modest policies can significantly reduce the likelihood of high global temperature outcomes. Human system uncertainties contribute more to uncertainty in projected CO2 concentrations and total radiative forcing, while Earth system uncertainties have the greatest influence on temperature and precipitation. Including additional uncertain inputs does not automatically increase the outcome range because uncertainties can offset one another.

Results also show how policy costs can vary greatly among regions.  As we improve understanding of underlying technology and economic factors as well as Earth system response to human forcing, further updating of these estimates of uncertainty can make an important contribution to decision-making about mitigation and adaptation.

Many world regions face increasing pressures from global and regional changes in climate, population growth, urban-area expansion, and the socio-economic impacts of fossil-based development. Human interference in the global climate system contributes significantly to changes in regional and local extreme weather and climate patterns.

Navigating the energy transition
Integrated climate-change assessment scenarios and carbon dioxide removal

Abstract: To halt climate change this century, we must reduce carbon dioxide (CO2) emissions from human activities to net zero. Any emission sources, such as in the energy or land-use sectors, must be balanced by natural or technological carbon sinks that facilitate CO2 removal (CDR) from the atmosphere. Projections of demand for large-scale CDR are based on an integrated scenario framework for emission scenarios composed of emission profiles as well as alternative socio-economic development trends and social values consistent with them. The framework, however, was developed years before systematic reviews of CDR entered the literature. This primer provides an overview of the purposes of scenarios in climate-change research and how they are used. It also introduces the integrated scenario framework and why it came about. CDR studies using the scenario framework, as well as its limitations, are discussed. Possible future developments for the scenario framework are highlighted, especially in relation to CDR.

This project supports an overall development strategy toward an integrated, interoperable model system utilizing components developed by PNNL, MIT and the PCHES group to explore regional multi-sectoral dynamics of energy, land and water systems in the US. The project seeks to advance the modeling capabilities, tools and approaches of the research groups in preparation for jointly examining multi-sector, multi-resource responses to multiple forcers.

Multi-Sector, Multi-Resource Interactions with Multiple Forcers

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