An Assessment of Earth's Climate Sensitivity Using Multiple Lines of Evidence.

We assess evidence relevant to Earth's equilibrium climate sensitivity per doubling of atmospheric CO2, characterized by an effective sensitivity S. This evidence includes feedback process understanding, the historical climate record, and the paleoclimate record. An S value lower than 2 K is difficult to reconcile with any of the three lines of evidence. The amount of cooling during the Last Glacial Maximum provides strong evidence against values of S greater than 4.5 K. Other lines of evidence in combination also show that this is relatively unlikely. We use a Bayesian approach to produce a probability density function (PDF) for S given all the evidence, including tests of robustness to difficult-to-quantify uncertainties and different priors. The 66% range is 2.6-3.9 K for our Baseline calculation and remains within 2.3-4.5 K under the robustness tests; corresponding 5-95% ranges are 2.3-4.7 K, bounded by 2.0-5.7 K (although such high-confidence ranges should be regarded more cautiously). This indicates a stronger constraint on S than reported in past assessments, by lifting the low end of the range. This narrowing occurs because the three lines of evidence agree and are judged to be largely independent and because of greater confidence in understanding feedback processes and in combining evidence. We identify promising avenues for further narrowing the range in S, in particular using comprehensive models and process understanding to address limitations in the traditional forcing-feedback paradigm for interpreting past changes.

Greenhouse gas induced climate change.

Simulations using global coupled climate models predict a climate change due to the increasing concentration of greenhouse gases and aerosols in the atmosphere. Both are associated with the burning of fossil fuels. There has been considerable debate if this postulated human influence is already evident. This paper gives an overview on some recent material on this question. One particular study using optimal fingerprints (Hegerl et al., 1996) is explained in more detail. In this study, an optimal fingerprint analysis is applied to temperature trend patterns over several decades. The results show the probability being less than 5% that the most recently observed 30 year trend is due to naturally occurring climate fluctuations. This result suggests that the present warming is caused by some external influence on climate, e.g. by the increasing concentrations of greenhouse gases and aerosols. More work is needed to address the uncertainties in the magnitude of naturally occurring climate fluctuations. Also, other external influences on climate need to be investigated to uniquely attribute the present climate change to the human influence.

Articulatory representation and speech technology.

In this paper we demonstrate the feasibility and usefulness of articulation-based approaches in two major areas of speech technology: speech recognition and speech synthesis. Our articulatory recognition model estimates probabilities of categories of manner and place of articulation, which establish the articulatory feature vector. The transformation from the articulatory level to the symbolic level is performed by hidden Markov models or multi-layer perceptions. Evaluations show that the articulatory approach is a good basis for speaker-independent and speaker-adaptive speech recognition. We are now working on a more realistic articulatory model for speech recognition. An algorithm based on an analysis by synthesis model maps the acoustic signal to 10 articulatory parameters which describe the position of the articulators. EMA (electro-magnetic articulograph) measurements recorded at the University of Munich provide good initial estimates of tongue coordinates. In order to improve articulatory speech synthesis we investigated an accurate physical model for the generation of the glottal source with the aid of a numerical simulation. This model takes into account nonlinear vortical flow and its interaction with sound-waves. The simulation results can be used to improve the articulatory synthesis model developed by Ishizaka and Flanagan (1972).