Article 2 of the UN Framework Convention on Climate Change (UNFCCC) states that: "The ultimate objective of this Convention and any related legal instruments that the Conference of the Parties may adopt is to achieve, in accordance with the relevant provisions of the Convention, stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system". The Framework Convention on Climate Change further suggests that "Such a level should be achieved within a time frame sufficient

• to allow ecosystems to adapt naturally to climate change,

• to ensure that food production is not threatened and

•to enable economic development to proceed in a sustainable manner."

Thus, the phrase "dangerous anthropogenic interference" (DAI) may be defined or characterized in terms of the consequences (or impacts) of climate change outcomes, which can be related to the levels and rates of change of climate parameters. These parameters will, in turn, be determined by the evolution of emissions and consequent atmospheric greenhouse gas concentrations. In addition, scenarios of social and economic development influence adaptive capacity of various sectors and regions, which, in turn, influences impact magnitudes and climate change thresholds that might be labeled "DAI". Evaluating the consequences of climate change outcomes to determine those that may be considered "dangerous" is a complex undertaking, involving substantial uncertainties as well as value judgments. Probabilistic estimation is an important method to treat such uncertainties. This task inevitably involves a mix of objective and subjective probability measures. What can integrated assessment modeling do to help explicate this important scientific and policy question?