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.

Carpal tunnel decompression in the super-elderly: functional outcome and patient satisfaction are equal to those of their younger counterparts.

There is conflicting evidence about the functional outcome and rate of satisfaction of super-elderly patients (≥ 80 years of age) after carpal tunnel decompression. We compiled outcome data for 756 patients who underwent a carpal tunnel decompression over an eight-year study period, 97 of whom were super-elderly, and 659 patients who formed a younger control group (< 80 years old). There was no significant difference between the super-elderly patients and the younger control group in terms of functional outcome according to the mean (0 to 100) QuickDASH score (adjusted mean difference at one year 1.8; 95% confidence interval (CI) -3.4 to 7.0) and satisfaction rate (odds ratio (OR) 0.78; 95% CI 0.34 to 1.58). Super-elderly patients were, however, more likely to have thenar muscle atrophy at presentation (OR 9.2, 95% CI 5.8 to 14.6). When nerve conduction studies were obtained, super-elderly patients were more likely to have a severe conduction deficit (OR 12.4, 95% CI 3.0 to 51.3). Super-elderly patients report functional outcome and satisfaction rates equal to those of their younger counterparts. They are more likely to have thenar muscle atrophy and a severe nerve conduction deficit at presentation, and may therefore warrant earlier decompression.

Efficient estimation and ensemble generation in climate modelling.

In this paper, we review progress towards efficiently estimating parameters in climate models. Since the general problem is inherently intractable, a range of approximations and heuristic methods have been proposed. Simple Monte Carlo sampling methods, although easy to implement and very flexible, are rather inefficient, making implementation possible only in the very simplest models. More sophisticated methods based on random walks and gradient-descent methods can provide more efficient solutions, but it is often unclear how to extract probabilistic information from such methods and the computational costs are still generally too high for their application to state-of-the-art general circulation models (GCMs). The ensemble Kalman filter is an efficient Monte Carlo approximation which is optimal for linear problems, but we show here how its accuracy can degrade in nonlinear applications. Methods based on particle filtering may provide a solution to this problem but have yet to be studied in any detail in the realm of climate models. Statistical emulators show great promise for future research and their computational speed would eliminate much of the need for efficient sampling techniques. However, emulation of a full GCM has yet to be achieved and the construction of such represents a substantial computational task in itself.