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Description:
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Spectral properties of global surface temperature and uncertainties of global climate sensitivity are explored in this work through the medium of Energy Balance Climate Models (EBCMs ) and observational surface temperature data . In part I , a complete series of 2D time -dependent non -orthogonal eigenmodes of global surface temperature are analytically derived and their geographic patterns are presented . The amplitudes of these modes have temporal characteristics and present exponentially decaying patterns . Theoretically , if the energy balance model is forced by white noise forcing in time , the autocorrelation functions of the mode amplitudes should present the same exponentially decaying patterns . When observed surface temperature data are projected onto these theoretical modes , the autocorrelation time scales of the mode amplitudes exhibit similar exponential decaying patterns . These modes are believed to be useful for surface temperature studies and model intercomparison . In part II , an objective means of deriving the probability density function (PDF ) of global climate sensitivity is investigated . The method constrains the PDF by its fit to the present climate in terms of surface temperature . We found that a wide range of parameter combinations , which corresponds to a broad range of the sensitivity , shows equally good fits to the present climate . It means that the uncertainties in global climate sensitivity are very difficult to eliminate if climate models are tuned to fit observations of surface temperature alone . The origin of the skewness of the PDF is found in very simple terms . |