Description: The future climate change projections are essentially based on coupled general circulation model (CGCM) simulations, which give a distinct global warming pattern with arctic winter amplification, an equilibrium land-sea warming contrast and an inter-hemispheric warming gradient. While these simulations are the most important tool of the Intergovernmental Panel on Climate Change (IPCC) predictions, the conceptual understanding of these predicted structures of climate change and the causes of their uncertainties is very difficult to reach if only based on these highly complex CGCM simulations. In the study presented here we will introduce a very simple, globally resolved energy balance (GREB) model, which is capable of simulating the main characteristics of global warming. The model shall give a bridge between the strongly simplified energy balance models and the fully coupled 4-dimensional complex CGCMs. It provides a fast tool for the conceptual understanding and development of hypotheses for climate change studies, which shall build a basis or starting point for more detailed studies of observations and CGCM simulations. It is based on the surface energy balance by very simple representations of solar and thermal radiation, the atmospheric hydrological cycle, sensible turbulent heat flux, transport by the mean atmospheric circulation and heat exchange with the deeper ocean. Despite some limitations in the representations of the basic processes, the models climate sensitivity and the spatial structure of the warming pattern are within the uncertainties of the IPCC models simulations. It is capable of simulating aspects of the arctic winter amplification, the equilibrium land-sea warming contrast and the inter-hemispheric warming gradient with good agreement to the IPCC models in amplitude and structure. The results give some insight into the understanding of the land-sea contrast and the polar amplification. The GREB model suggests that the regional inhomogeneous distribution of atmospheric water vapor and the non-linear sensitivity of the downward thermal radiation to changes in the atmospheric water vapor concentration partly cause the land-sea contrast and may also contribute to the polar amplification. The combination of these characteristics causes, in general, dry and cold regions to warm more than other regions.

Description: According to the IPCC AR4 the geographical patterns of projected surface air temperature warming show greatest temperature increases over land (roughly twice the global average temperature increase) and at high northen latitudes, and less warming over the southern oceans and North Atlantic, consistent with observations during the latter part of the 20th century. The developed simple climate model that only considers simplified representations of central feedback emchanisms in the climate system is indeed able to reproduce the major features of this global surface warming pattern. The global average temperature change lies well within the range suggested by current IPCC models, suggesting that the basic physics explain most of that pattern. Local deviations betwen the simple model result and that of the multi-model mean response of IPCC models lie within the range of single GCMs, since most complex models differ from the ensemble mean as well. Several experiments were undertaken in order to show the effects of single feedback mechanisms in combination with each other. The known effects of positive feedbacks, such as water vapor and ice-albedo feedback, and negative feedbacks, such as the latent heat feedback, are acting amplifying and dampening, respectively. The most important feedback mechanism is the water vapor feedback which is roughly doubling the model's sensitivity to external forcing. The ice-albedo feedback is amplifying the temperature change in those regions that experience seasonally varying ice or snow cover. However, several physical processes had to be parameterized in order to keep the model as simple as possible. This, however, leads to model failures in reproducing all details of the complex climate system in response to climate change conditions. Nevertheless, it was not the aim of this work to develop one more climate model that is reproducing just a global warming response but to come up with a simplified model version that allows experimental tests of physical relations. This goal indeed has been achieved. In conclusion, the developed simple climate model is only appropriate for clearing the most general features of climate change under a global warming scenario with increasing CO2 concentration. But it may be used to study the effect of single feedback processes under very simplified conditions. The low computation time and simple structure of this conceptual model suggest a usage as a 'educational tool'. Further improvement and expansion will certainly lead to more realistic results, which than surely agree to a certain limit with the results of more complex models.