Previously published work using satellite observations of the clear sky infrared emitted radiation by the Earth in 1970, 1997 and in 2003 showed the appearance of changes in the outgoing spectrum, which agreed with those expected from known changes in the concentrations of well-mixed greenhouse gases over this period. Thus, the greenhouse forcing of the Earth has been observed to change in response to these concentration changes. In the present work, this analysis is being extended to 2006 using the TES instrument on the AURA spacecraft. Additionally, simulated spectra have been calculated using LBLRTM with inputs from the HadGEM1 coupled model and compared to the observed satellite spectra.

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[1] The global and tropical means of clear-sky outgoing longwave radiation (hereinafter OLRc) simulated by the new GFDL atmospheric general circulation model, AM2, tend to be systematically lower than ERBE observations by about 4 W m 2, even though the AM2 total-sky radiation budget is tuned to be consistent with these observations. Here we quantify the source of errors in AM2-simulated OLRc over the tropical oceans by comparing the synthetic outgoing IR spectra at the top of the atmosphere on the basis of AM2 simulations to observed IRIS spectra. After the sampling disparity between IRIS and AM2 is reduced, AM2 still shows considerable negative bias in the simulated monthly mean OLRc over the tropical oceans. Together with other evidence, this suggests that the influence of spatial sampling disparity, although present, does not account for the majority of the bias. Decomposition of OLRc shows that the negative bias comes mainly from the H2O bands and can be explained by a too humid layer around 6–9 km in the model. Meanwhile, a positive bias exists in channels sensitive to near-surface humidity and temperature, which implies that the boundary layer in the model might be too dry. These facts suggest that the negative bias in the simulated OLRc can be attributed to model deficiencies, especially the large-scale water vapor transport. We also find that AM2-simulated OLRc has 1Wm 2 positive bias originating from the stratosphere; this positive bias should exist in simulated total-sky OLR as well.

The science of climate is at the intersection of a number of science disciplines and sub-disciplines. At its heart are physics, chemistry, biology and mathematics – each with their sub-disciplines of atmospheric physics and chemistry, oceanography, hydrology, geology etc – and each of which can be considered as mature within the framework required to discuss climate. It is at this intersection of the disciplines where uncertainty can and will arise, both because of the yet poorly understood feedbacks between the different components of the climate system and because of the difficulty of bringing these components together into a single descriptive and predictive model.