Constraining total feedback of the climate system by observations and models

Assessing global warming projections on the basis of various future emission scenarios is difficult because a number of key variables in climate change are poorly quantified. In particular, the feedbacks of the climate system when greenhouse-gas concentra tions and aerosols are changing are not well constrained, leading to large uncertainties. The proposed project aims at constraining the total feedback of the climate system by combining improved historic radiative forcing development, Monte Carlo simulat ions with an energy balance climate model, and observations of climate change. A major part of the project is to apply global models to calculate improved estimates of trends in concentrations of short-lived gases and aerosols. The radiative forcing will be calculated based on these trend estimates and a novel apprach to estimate the RF of indirect cloud effects of aerosols will be applied. The uncertainties in the input parameters and in the energy balance model itself are taken into account, and past ob servations of oceanic and atmospheric warming are used to constrain the feedback parameter. The end result will be a probability density function for the feedback parameter that should have less uncertainty than pervious estimates. Improved knowledge of t he total feedback of the climate system will reduce the uncertainty that currently makes it difficult for policy makers to develop emission mitigation strategies consistent with long-term limitations to acceptable global warming.