Modeling Uncertainty in Climate Change: A Multi-Model Comparison

The economics of climate change involves a vast array of uncertainties, complicating both the analysis and development of climate policy. This study presents the results of the first comprehensive study of uncertainty in climate change using multiple integrated assessment models. The study looks at model and parametric uncertainties for population, total factor productivity, and climate sensitivity. It estimates the pdfs of key output variables, including CO2 concentrations, temperature, damages, and the social cost of carbon (SCC). One key finding is that parametric uncertainty is more important than uncertainty in model structure. Our resulting pdfs also provide insights on tail events

Priority for the Worse Off and the Social Cost of Carbon

The social cost of carbon (SCC) is a monetary measure of the harms from carbon emission. Specifically, it is the reduction in current consumption that produces a loss in social welfare equivalent to that caused by the emission of a ton of CO2. The standard approach is to calculate the SCC using a discounted-utilitarian social welfare function (SWF)—one that simply adds up the well-being numbers (utilities) of individuals, as discounted by a weighting factor that decreases with time. The discounted-utilitarian SWF has been criticized both for ignoring the distribution of well-being, and for including an arbitrary preference for earlier generations. Here, we use a prioritarian SWF, with no time-discount factor, to calculate the SCC in the integrated assessment model RICE. Prioritarianism is a well-developed concept in ethics and theoretical welfare economics, but has been, thus far, little used in climate scholarship. The core idea is to give greater weight to well-being changes affecting worse off individuals. We find substantial differences between the discounted-utilitarian and non-discounted prioritarian SCC

Systematic sensitivity analysis of the full economic impacts of sea level rise

The potential impacts of sea level rise (SLR) due to climate change have been widely studied in the literature. However, the uncertainty and robustness of these estimates has seldom been explored. Here we assess the model input uncertainty regarding the wide effects of SLR on marine navigation from a global economic perspective. We systematically assess the robustness of computable general equilibrium (CGE) estimates to model’s inputs uncertainty. Monte Carlo (MC) and Gaussian quadrature (GQ) methods are used for conducting a Systematic sensitivity analysis (SSA). This design allows to both explore the sensitivity of the CGE model and to compare the MC and GQ methods. Results show that, regardless whether triangular or piecewise linear Probability distributions are used, the welfare losses are higher in the MC SSA than in the original deterministic simulation. This indicates that the CGE economic literature has potentially underestimated the total economic effects of SLR, thus stressing the necessity of SSA when simulating the general equilibrium effects of SLR. The uncertainty decomposition shows that land losses have a smaller effect compared to capital and seaport productivity losses. Capital losses seem to affect the developed regions GDP more than the productivity losses do. Moreover, we show the uncertainty decomposition of the MC results and discuss the convergence of the MC results for a decomposed version of the CGE model. This paper aims to provide standardised guidelines for stochastic simulation in the context of CGE modelling that could be useful for researchers in similar settings

Modeling Uncertainty in Climate Change: A Multi‐Model Comparison

The economics of climate change involves a vast array of uncertainties, complicating both the analysis and development of climate policy. This study presents the results of the first comprehensive study of uncertainty in climate change using multiple integrated assessment models. The study looks at model and parametric uncertainties for population, total factor productivity, and climate sensitivity. It estimates the pdfs of key output variables, including CO 2 concentrations, temperature, damages, and the social cost of carbon (SCC). One key finding is that parametric uncertainty is more important than uncertainty in model structure. Our resulting pdfs also provide insights on tail events

Global economic impacts of climate variability and change during the 20th century

Estimates of the global economic impacts of observed climate change during the 20th century obtained by applying five impact functions of different integrated assessment models (IAMs) are separated into their main natural and anthropogenic components. The estimates of the costs that can be attributed to natural variability factors and to the anthropogenic intervention with the climate system in general tend to show that: 1) during the first half of the century, the amplitude of the impacts associated with natural variability is considerably larger than that produced by anthropogenic factors and the effects of natural variability fluctuated between being negative and positive. These non-monotonic impacts are mostly determined by the low-frequency variability and the persistence of the climate system; 2) IAMs do not agree on the sign (nor on the magnitude) of the impacts of anthropogenic forcing but indicate that they steadily grew over the first part of the century, rapidly accelerated since the mid 1970's, and decelerated during the first decade of the 21st century. This deceleration is accentuated by the existence of interaction effects between natural variability and natural and anthropogenic forcing. The economic impacts of anthropogenic forcing range in the tenths of percentage of the world GDP by the end of the 20th century; 3) the impacts of natural forcing are about one order of magnitude lower than those associated with anthropogenic forcing and are dominated by the solar forcing; 4) the interaction effects between natural and anthropogenic factors can importantly modulate how impacts actually occur, at least for moderate increases in external forcing. Human activities became dominant drivers of the estimated economic impacts at the end of the 20th century, producing larger impacts than those of low-frequency natural variability. Some of the uses and limitations of IAMs are discussed

Coastal lagoons and rising sea level: a review

Sea-level rise (SLR) poses a particularly ominous threat to human habitations and infrastructure in the coastal zone because 10% of the world's population lives in low-lying coastal regions within 10 m elevation of present sea level. There has been much discussion about projected (and the sources of projection) vs. measured SLR rates. Which rates should coastal scientists and managers apply in their studies, and what is the degree of confi- dence of such forecasts, are still open questions. This paper reviews the patterns and effects of relative SLR (RSLR) in coastal lagoons. Three main components are presented in the review: (a) a summary of the main approaches used in predicting medium- to long-term trends in RSLR, (b) a summary of the main evolutionary trends of coastal lagoons and the tools used to examine such trends, and (c) an identification of future research needs. The review reveals that the major source of uncertainty is how and when RSLR will manifest itself at different spatio-temporal scales in coastal lagoon systems, and how its effects can be mitigated. Most of the studies reviewed herein articulate a natural ‘defence’ mechanism of barriers in coastal lagoons by landward barrier retreat through continuous migration, and a gradual change in basin hypsometry during the retreat process. So far, only a relatively small number of detailed studies have integrated and quantified human impacts and coastal lagoon evolution induced by RSLR. We conclude that much more research about adaptation measures is needed, taking into consideration not only the physical and ecological systems but also social, cultural, and economic impacts. Future challenges include a downscaling of SLR approaches from the global level to regional and local levels, with a detailed application of coastal evolution prediction to individual coastal lagoon systemsinfo:eu-repo/semantics/publishedVersio

The importance of health co-benefits under different climate policy cooperation frameworks

Reducing greenhouse gas emissions has the 'co-benefit' of also reducing air pollution and associated impacts on human health. Here, we incorporate health co-benefits into estimates of the optimal climate policy for three different climate policy regimes. The first fully internalizes the climate externality at the global level via a uniform carbon price (the 'cooperative equilibrium'), thus minimizing total mitigation costs. The second connects to the concept of 'common but differentiated responsibilities' where nations coordinate their actions while accounting for different national capabilities considering socioeconomic conditions. The third assumes nations act only in their own self-interest. We find that air quality co-benefits motivate substantially reduced emissions under all three policy regimes, but that some form of global cooperation is required to prevent runaway temperature rise. However, co-benefits do warrant high levels of mitigation in certain regions even in the self-interested case, suggesting that air quality impacts may expand the range of possible policy outcomes whereby global temperatures do not increase unabated

Main assumptions for energy pathways

© The Author(s) 2019. The aim of this chapter is to make the scenario calculations fully transparent and comprehensible to the scientific community. It provides the scenario narratives for the reference case (5.0 °C) as well as for the 2.0 °C and 1.5 °C on a global and regional basis. Cost projections for all fossil fuels and renewable energy technologies until 2050 are provided. Explanations are given for all relevant base year data for the modelling and the main input parameters such as GDP, population, renewable energy potentials and technology parameters