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Modeling Uncertainty in Integrated Assessment of Climate Change: A Multimodel Comparison

Abstract: The economics of climate change involves a vast array of uncertainties, complicating our understanding of climate change. This study explores uncertainty in baseline trajectories using multiple integrated assessment models commonly used in climate policy development. The study examines model and parametric uncertainties for population, total factor productivity, and climate sensitivity. It estimates the probability distributions of key output variables, including CO2 concentrations, temperature, damages, and social cost of carbon (SCC). One key finding is that parametric uncertainty is more important than uncertainty in model structure. Our resulting distributions provide a useful input into climate policy discussions.

To avoid the most serious and permanent damage from climate change, from catastrophic sea-level rise to devastating droughts, and do so at the least cost, the world will need to reduce net human-caused carbon dioxide (CO₂) emissions to zero ASAP. Getting to net-zero emissions in a timely manner will require the development of technologies and policies aimed at decarbonizing human activities rapidly and economically, with ambition far exceeding that of the initial pledges of the Paris Agreement.

Handicapping the High-Stakes Race to Net-Zero

The future of the Earth’s energy, water and land resources will depend, in part, on how the climate will change in coming decades. To generate meaningful projections of global climate change, one must take into account two major sources of uncertainty—first, in the level of external forcings to the climate system; and second, in the magnitude of the climate system’s response to those forcings.

Description and Evaluation of the MIT Earth System Model (MESM)

On first glance, it could be a tall order for Turkey to fulfill its Paris Agreement pledge, which targets a reduction in the nation’s greenhouse gas (GHG) emissions by 21 percent in 2030 below business-as-usual levels. Fossil fuels comprise nearly all of Turkey’s energy mix, and low-carbon options have not yet gained traction. Wind and solar accounts for about five percent of energy generation and nuclear power plants are only in the planning stages.

The price of the pledge
Ecological control of nitrite in the upper ocean

Microorganisms oxidize organic nitrogen to nitrate in a series of steps. Nitrite, an intermediate product, accumulates at the base of the sunlit layer in the subtropical ocean, forming a primary nitrite maximum, but can accumulate throughout the sunlit layer at higher latitudes. We model nitrifying chemoautotrophs in a marine ecosystem and demonstrate that microbial community interactions can explain the nitrite distributions. Our theoretical framework proposes that nitrite can accumulate to a higher concentration than ammonium because of differences in underlying redox chemistry and cell size between ammonia- and nitrite-oxidizing chemoautotrophs. Using ocean circulation models, we demonstrate that nitrifying microorganisms are excluded in the sunlit layer when phytoplankton are nitrogen-limited, but thrive at depth when phytoplankton become light-limited, resulting in nitrite accumulation there. However, nitrifying microorganisms may coexist in the sunlit layer when phytoplankton are iron- or light-limited (often in higher latitudes). These results improve understanding of the controls on nitrification, and provide a framework for representing chemoautotrophs and their biogeochemical effects in ocean models.

Seasonal resource conditions favor a summertime increase in North Pacific diatom–diazotroph associations

In the North Pacific Subtropical Gyre (NPSG), an annual pulse of sinking organic carbon is observed at 4000 m between July and August, driven by large diatoms found in association with nitrogen fixing, heterocystous, cyanobacteria: Diatom–Diazotroph Associations (DDAs). Here we ask what drives the bloom of DDAs and present a simplified trait-based model of subtropical phototroph populations driven by observed, monthly averaged, environmental characteristics. The ratio of resource supply rates favors nitrogen fixation year round. The relative fitness of DDA traits is most competitive in early summer when the mixed layer is shallow, solar irradiance is high, and phosphorus and iron are relatively abundant. Later in the season, as light intensity drops and phosphorus is depleted, the traits of small unicellular diazotrophs become more competitive. The competitive transition happens in August, at the time when the DDA export event occurs. This seasonal dynamic is maintained when embedded in a more complex, global-scale, ecological model, and provides predictions for the extent of the North Pacific DDA bloom. The model provides a parsimonious and testable hypothesis for the stimulation of DDA blooms.

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