Özet:
The human induced climate change is the most serious and difficult environmental issue to manage that has emerged in the recent decades. The complexity of this problem lies in the fact that if the increase in atmospheric greenhouse gas concentrations continue in an uncontrolled manner, its potential damage can be very severe but the costs associated with the mitigation activities are very high. Although the severity of the problem and the need for urgent action are unquestionable today, people usually prefer "wait and see" policies instead of prompt action. One reason of this tendency is inherent difficulties of understanding the dynamics of anthropogenic climate change and anticipating the possible future results of today's actions. Climate change is a good example of a dynamic systems problem. It embodies several delays, feedbacks, nonlinearities and uncertainties in its dynamically complex structure. Therefore, the need for and the usefulness of descriptive and simpler models that explain these dynamic complexities are undisputed. The aim of this study is to construct such a dynamic simulation model. The method used is system dynamics, which is a powerful approach to model and analyze complex dynamic systems to create hypotheses on structure and to predict future behavior. The model integrates several components of the climate system. It includes the carbon cycle, radiative forcing of CO2, CH4, N2O and induced temperature change as well as the temperature feedback affecting terrestrial carbon absorption rates. It also proposes a representation of the permafrost melting and methane feedback process. The model aims at enabling the user to test the effects of these feedbacks, the emission scenarios and parameter uncertainty on greenhouse gas concentrations and average surface temperature change. The simulation length is 240 years from 1860 to 2100. Model structure is validated with indirect structure tests. Historical emissions and temperature change data are used to calibrate the model behavior. Model reference behavior is based on IS92a emission scenario of IPCC. The model can be transformed to an interactive learning environment and be used as a tool to improve the public understanding about dynamics of climate change and to increase awareness. It is also possible to develop it and to transform to a web application that enables the users to test different policy options and observe the results.
