Process, Forcing, and Signal Analysis of Global Mean TemperatureVariations by Means of a Three-Box Energy Balance Model

An analytic solution of an energy balance model (EBM) is presented which can beused as a recursive filter for time series analysis. It is shown that the EBM can reproduce the solution of a coupled atmosphere-ocean general circulation model (AOGCM) experiment. Contrary to the AOGCM, the EBM easily allows for variations in climate sensitivity to satisfy the full range of uncertainty concerned with this parameter. The recursive filter is applied to two natural and two anthropogenic forcing mechanisms which are expressed in terms of heating rate anomaly time series: volcanism, solar activity, greenhouse gases (GHG), and anthropogenic tropospheric aerosols. Thus, we obtain modelled global mean temperature variations as a response to the different forcings and with respect to the uncertainty in the forcing approximations and climate sensitivity. In addition, it is shown that the observed (ENSO-corrected) global mean temperature time series within the period from 1866 to 1997 can be explained by the external forcings which have been considered and an additional white noise forcing. In this way we are able to separate different signals and compare them. As a result, global anthropogenic climate change due to GHG forcing can be detected at a high level of significance without considering spatial patterns of climate change but including natural forcing, which is usually not done. Furthermore, it is shown that solar forcing alone does not lead to significantclimate change, whereas solar and volcanic forcing together lead to a significant natural climate change signal. Anthropogenic climate change due to GHG forcing may partly be masked by anthropogenic aerosol cooling.