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We derive joint probability density distributions for three key uncertain properties of the climate system, using an optimal fingerprinting approach to compare simulations of an intermediate complexity climate model with three distinct diagnostics of recent climate observations. On the basis of the marginal probability distributions, the 5 to 95% confidence(More)
To aid climate policy decisions, accurate quantitative descriptions of the uncertainty in climate outcomes under various possible policies are needed. Here, we apply an earth systems model to describe the uncertainty in climate projections under two different policy scenarios. This study illustrates an internally consistent uncertainty analysis of one(More)
The MIT Joint Program on the Science and Policy of Global Change is an organization for research, independent policy analysis, and public education in global environmental change. It seeks to provide leadership in understanding scientific, economic, and ecological aspects of this difficult issue, and combining them into policy assessments that serve the(More)
The MIT Joint Program on the Science and Policy of Global Change is an organization for research, independent policy analysis, and public education in global environmental change. It seeks to provide leadership in understanding scientific, economic, and ecological aspects of this difficult issue, and combining them into policy assessments that serve the(More)
This paper presents the probabilistic collocation method as a computationally efficient method for performing uncertainty analysis on large complex models such as those used in global climate change research. The collocation method is explained, and then the results of its application to a box model of ocean thermohaline circulation are presented. A(More)
The MIT Joint Program on the Science and Policy of Global Change is an organization for research, independent policy analysis, and public education in global environmental change. It seeks to provide leadership in understanding scientific, economic, and ecological aspects of this difficult issue, and combining them into policy assessments that serve the(More)
Future emissions of greenhouse gases, their climatic effects, and the resulting environmental and economic consequences are subject to large uncertainties. The task facing the public and their policy-makers is to devise strategies of risk reduction, and they need a clear representation of these uncertainties to inform their choices. Absent this information,(More)
We have derived a parameterization consisting of a set of analytical expressions that approximate the predictions by the CIT Urban Airshed Model for the net export to the environment (i.e., effective emissions) of several chemical species, as functions of fourteen input parameters. For each species, effective emissions are a function of actual urban(More)
Clear and quantitative discussion of uncertainties is critical for public policy making on climate change. The recently completed report of the Intergovernmental Panel on Climate Change assessed the uncertainty in its findings and forecasts. The uncertainty assessment process of the IPCC should be improved in the future by using a consistent approach to(More)
Possible climate change caused by an increase in greenhouse gas concentrations, despite having been a subject of intensive study in recent years, is still very uncertain. Uncertainties in projections of different climate variables are usually described only by the ranges of possible values. For assessing the possible impact of climate change, it would be(More)