Reply to Roe and Baker's comment on &amp;quot;Another look at climate sensitivity&amp;quot; by Zaliapin and Ghil (2010)

Zaliapin, Ilya; Ghil, Michael

doi:10.5194/npg-18-129-2011

Cited by 5 publications

(5 citation statements)

References 11 publications

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“…However, these have not sufficed to produce narrow estimates of S, because of the difficulty in reproducing and parameterizing the complex processes involved (Bony et al 2006). Since several of these processes correspond to positive feedbacks, even small uncertainties can be amplified and lead to large uncertainties in S (Roe and Baker 2007; discussed in Ghil 2010, 2011;Roe and Baker 2011). Observational data are also used in the hope to constrain S, but success has been rather limited to date (Hegerl et al 2007;Knutti and Hegerl 2008).…”

Section: The Estimation Of Climate Sensitivitymentioning

confidence: 96%

Solution to the paradox of climate sensitivity

Pueyo

2011

Climatic Change

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Most countries endorse a limit of either 2°C or 1.5°C global warming above preindustrial levels. However, for several reasons, there is still a significant uncertainty in the climate sensitivity parameter, which relates greenhouse gas concentration (or other forcings) to steady-state temperature. One key source of uncertainty is the disagreement about the appropriate prior for Bayesian estimation. A common choice is the uniform distribution, often thought to contain no information. However, when used to estimate sensitivity it leads to paradoxical results, which have been interpreted as revealing an inherent indeterminacy in the prior of choice. If this were the case, part of the uncertainty would be irreducible. Here I develop an objective Bayesian approach to this problem. I show that both Jaynes' invariant groups criterion and a new criterion based on information theory lead to the conclusion that there is a uniquely defined non-informative prior of climate sensitivity, which is distinct from the uniform and solves the paradox. This prior distribution is the log-uniform. Furthermore, this result is supported empirically by the observation that other comparable non-equilibrium parameters display a scale-invariant, log-uniform-like frequency distribution. Rather than advocating a direct use of this prior, I recommend to refine it with a limited use of expert elicitation or other methods. A sound prior is a key ingredient in the process to reach a consensus low-uncertainty estimate of climate sensitivity to inform climate policy.

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Section: The Estimation Of Climate Sensitivitymentioning

confidence: 96%

Solution to the paradox of climate sensitivity

Pueyo

2011

Climatic Change

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“…Traditionally, the attention of the climate research community is focused on investigation of perturbations caused by F T 0 response on the shift of the radiation heat balance. North et al (1981) review and the very recent Zaliapin and Ghil (2010) insightful analysis are just two examples of such a work. Contrary, the system heat capacity, C, has not received much attention.…”

Section: Bulk Planetary Boundary Layer Effect On the Climate Systemmentioning

confidence: 99%

On the role of the planetary boundary layer depth in the climate system

Esau

Zilitinkevich

2010

Adv. Sci. Res.

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Abstract.The planetary boundary layer (PBL) is a part of the Earth's atmosphere where turbulent fluxes dominate vertical mixing and constitute an important part of the energy balance. The PBL depth, h, is recognized as an important parameter, which controls some features of the Earth's climate and the atmospheric chemical composition. It is also known that h varies by two orders of magnitude on diurnal and seasonal time scales. This brief note highlights effects of this variability on the atmospheric near-surface climate and chemical composition. We interpret heat capacity parameter of a Budyko-type energy balance model in terms of quasi-equilibrium h. The analysis shows that it is the shallowest, stably-stratified PBL with the smallest h that should be of particular concern for climate modelling. The reciprocal dependence between the PBL depth and temperature (concentrations) is discussed. In particular, the analysis suggests that the climate characteristics during stably stratified PBL episodes should be significantly more sensitive to perturbations of the Earth's energy balance as well as emission rates. On this platform, h from ERA-40 reanalysis data, the CHAMP satellite product and the DATABASE64 data were compared. DATABASE64 was used to assess the Troen-Mahrt method to determine h through available meteorological profile observations. As it has been found before, the shallow PBL requires better parameterization and better retrieval algorithms. The study demonstrated that ERA-40 and CHAMP data are biased toward deeper h in the shallow polar PBL. This, coupled with the scarcity of in-situ observations might mislead the attribution of the origins of the Arctic climate change mechanisms.

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“…Zaliapin and Ghil 201 also study co-existence of multiple solutions for fixed model parameters and describe the basins of attraction of the stable solutions in a onedimensional space of constant initial model histories 201 .…”

Section:  Delay Differential Modeling For El Nino/southern Oscillatimentioning

confidence: 99%

Nonlinear Dynamics and Chaos: Applications in Atmospheric Sciences

Selvam¹

2012

Journal of Advanced Mathematics and Applications

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Atmospheric flows, an example of turbulent fluid flows, exhibit fractal fluctuations of all space-time scales ranging from turbulence scale of mmsec to climate scales of thousands of kilometers -years and may be visualized as a nested continuum of weather cycles or periodicities, the smaller cycles existing as intrinsic fine structure of the larger cycles. The power spectra of fractal fluctuations exhibit inverse power law form signifying long -range correlations identified as self -organized criticality and are ubiquitous to dynamical systems in nature and is manifested as sensitive dependence on initial condition or 'deterministic chaos' in finite precision computer realizations of nonlinear mathematical models of real world dynamical systems such as atmospheric flows. Though the selfsimilar nature of atmospheric flows have been widely documented and discussed during the last three to four decades, the exact physical mechanism is not yet identified. There now exists an urgent need to develop and incorporate basic physical concepts of nonlinear dynamics and chaos into classical meteorological theory for more realistic simulation and prediction of weather and climate. A review of nonlinear dynamics and chaos in meteorology and atmospheric physics is summarized in this paper. Dynamical systems and fractal space-time fluctuationsDynamical systems in nature, i.e., systems that change with time, such as fluid flows, heartbeat patterns, spread of infectious diseases, etc., exhibit nonlinear (unpredictable) fluctuations. Conventional mathematical and statistical theories deal only with linear systems and the exact quantification and description of nonlinear fluctuations was not possible till the identification in the 1970s by Mandelbrot 6,12 , of the universal symmetry of self-similarity, i.e., fractal geometry underlying the seemingly irregular fluctuations in space and time 13,14 . Fractals, as the name implies, describe non-Euclidean objects generic to nature such as tree

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Reply to Roe and Baker's comment on "Another look at climate sensitivity" by Zaliapin and Ghil (2010)

Cited by 5 publications

References 11 publications

Solution to the paradox of climate sensitivity

Solution to the paradox of climate sensitivity

On the role of the planetary boundary layer depth in the climate system

Nonlinear Dynamics and Chaos: Applications in Atmospheric Sciences

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