Laws and Symmetry

Fraassen, Bas C. van

doi:10.1093/0198248601.001.0001

Cited by 1,564 publications

(235 citation statements)

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“…This is an instance of Bertrand's paradox, one of the classic paradoxes of probability theory [van Fraassen, 1989;Bertrand, 1889;Rosenkrantz, 1977]. The solution, in this instance, is to make clear to the forecast user the relative roles of untestable prior assumptions versus observational or physical constraints.…”

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confidence: 99%

Constraining climate forecasts: The role of prior assumptions

Frame

Booth

Kettleborough

et al. 2005

Geophysical Research Letters

152

167

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[1] Any attempt to estimate climate sensitivity using observations requires a set of models or model-versions that simultaneously predict both climate sensitivity and some observable quantity(-ies) given a range of values of unknown climate system properties, represented by choices of parameters, subsystems or even entire models. The choices researchers make with respect to these unknown properties play a crucial role in conditioning their climate forecasts. We show that any probabilistic estimate of climate sensitivity, and hence of the risk that a given greenhouse gas stabilisation level might result in a ''dangerous'' equilibrium warming, is critically dependent on subjective prior assumptions of the investigators, not simply on constraints provided by actual climate observations. This apparent arbitrariness can be resolved by focussing on the intended purpose of the forecast: while uncertainty in long-term equilibrium warming remains high, an objectively determined 10 -90% (5 -95%) range of uncertainty in climate sensitivity that is relevant to forecasts of 21st century transient warming under nearly all current emission scenarios is 1.4-4.1°C with a median of 2.4°C, in good agreement with the ''traditional'' range. [2] Climate sensitivity, or equilibrium warming due to a doubling of carbon dioxide (CO 2 ), is a key determinant of climate change [Intergovernmental Panel on Climate Change (IPCC), Morgan and Keith, 1995]. Studies [Andronova and Schlesinger, 2000;Forest et al., 2002;Knutti et al., 2002;Gregory et al., 2002;Murphy et al., 2004;Stainforth et al., 2005] attempting to constrain climate sensitivity by comparing models with recent observations report a wide range of distributions. Here we show that much of this variation arises from different prior assumptions regarding climate sensitivity before any physical or observational constraints are applied, suggesting fundamental reasons why a universal consensus on longterm equilibrium warming consistent with any given stabilisation level for greenhouse gases may prove impossible to achieve.[3] We demonstrate our point with a simple global energy balance model (EBM) and diffusive ocean [Hansen et al., 1985], although the reasoning applies to any model in which atmospheric feedbacks scale linearly with surface warming and in which effective oceanic heat capacity is approximately constant under 20th century climate forcing. The diamonds in Figures 1a and 1b show the average warming trend caused by greenhouse gas increase over the 20th century (vertical axis) as a function of effective heat capacity of the troposphere-land-ocean system (horizontal) and the climate sensitivity S (colours) for a range of different settings of model parameters. The black contour encloses the region consistent (at the 5% level) with observations of 20th century greenhouse warming and the effective heat capacity.[4] We isolate the greenhouse warming signal using a pattern-based attribution analysis [Stott and Kettleborough, 2002] allowing for uncertainty in both greenhouse and oth...

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confidence: 99%

Constraining climate forecasts: The role of prior assumptions

Frame

Booth

Kettleborough

et al. 2005

Geophysical Research Letters

152

167

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“…3 The concept of a shadow is not very clearly demarcated. (van Fraassen, 1989), ch. 9, indicates that it may be uncertain, in some cases, whether a certain shadowed area is a shadow of any object.…”

Section: Terminologymentioning

confidence: 99%

The Shadow Knows: A Primer on the Informational Structure of Cast Shadows

Casati

2004

Perception

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“…Despite having some attractive features, the maximum entropy approach is rather complicated to apply, and has the further disadvantage of being dependent on the partition of possible world over which entropy is assessed (cf. [20]). …”

Section: System Zmentioning

confidence: 99%