Sentences with phrase «sensitivity uncertainty estimates»

A brief analysis based on multi-gas emission pathways and several climate sensitivity uncertainty estimates», Avoiding dangerous climate change, in H.J. Schellnhuber et al. (eds.)

Using available climate sensitivity uncertainty estimates (pdfs by Murphy et al., Gregory et al., Forest et al., Wigley & Raper, Knutti et al., etc...), the probability of overshooting 2 °C global mean temperature rise above pre-industrial levels for a stabilization at 550ppm CO2eq are between 70 % -99 %.

A brief analysis based on multi-gas emission pathways and several climate sensitivity uncertainty estimates.

Not exact matches

95 % UI = uncertainty interval around the cost and DALY estimates, derived from multivariate sensitivity analysis propagating uncertainty around cost inputs, elasticity estimates, relative risks of disease outcomes and the prevalence of alcohol consumption.

It tries to turn a major factor in the uncertainty in climate sensitivity estimates — the behavior of clouds — into a strength.

Indeed, the main quandary faced by climate scientists is how to estimate climate sensitivity from the Little Ice Age or Medieval Warm Period, at all, given the relative small forcings over the past 1000 years, and the substantial uncertainties in both the forcings and the temperature changes.

Only a few estimates account for uncertainty in forcings other than from aerosols (e.g., Gregory et al., 2002a; Knutti et al., 2002, 2003); some other studies perform some sensitivity testing to assess the effect of forcing uncertainty not accounted for, for example, in natural forcing (e.g., Forest et al., 2006; see Table 9.1 for an overview).

(in general, whether for future projections or historical reconstructions or estimates of climate sensitivity, I tend to be sympathetic to arguments of more rather than less uncertainty because I feel like in general, models and statistical approaches are not exhaustive and it is «plausible» that additional factors could lead to either higher or lower estimates than seen with a single approach.

This sensitivity estimate is not the last word on the subject, because of uncertainties in the approximate formulae used to compute the terms in the energy balance, and neglect of possible effects of water vapor feedback on the surface budget.

Probabilistic estimates of transient climate sensitivity subject to uncertainty in forcing and natural variability.

This is also a good recent presentation of the various estimates of climate sensitivity and of the amount of uncertainty associated with them — found by doing a Google image search on the terms:

This is enough to matter, but it's no more scary than the uncertainty in cloud feedbacks for example, and whether they could put us on the high end of typical climate sensitivity estimates.

The IPCC range, on the other hand, encompasses the overall uncertainty across a very large number of studies, using different methods all with their own potential biases and problems (e.g., resulting from biases in proxy data used as constraints on past temperature changes, etc.) There is a number of single studies on climate sensitivity that have statistical uncertainties as small as Cox et al., yet different best estimates — some higher than the classic 3 °C, some lower.

Regarding ECS («equilibrium climate sensitivity»), I think there are difficulties estimating anything truly resembling a Charney - type ECS from data involving OHC uptake and forcing estimates, because these estimates are fraught with so many uncertainties, and because the values that are calculated, even if accurate, bear an uncertain relationship to how the climate would behave at equilibrium.

Indeed, the main quandary faced by climate scientists is how to estimate climate sensitivity from the Little Ice Age or Medieval Warm Period, at all, given the relative small forcings over the past 1000 years, and the substantial uncertainties in both the forcings and the temperature changes.

Here as with CO2 sensitivity, most of the uncertainty is on the high - side of the best guess, but we are mainly concerned with the best estimate.

Schneider, T., 2007: Uncertainty in climate - sensitivity estimates.

Sensitivity of the climate to carbon dioxide, and the level of uncertainty in its value, is a key input into the economic models that drive cost - benefit analyses, including estimates of the social cost of carbon.

Can you say if this work changes our understanding of the central estimate or uncertainty of climate sensitivity?

It is well known that the ERFaero, the sum of direct aerosol forcing (ERFari) and ERFaci is by far the greatest source of uncertainty when it comes to observationally based estimates about the transient sensitivity (TCR) and the expected warming in this century.

Using a global energy budget approach, this paper seeks to understand the implications for climate sensitivity (both ECS and TCR) of the new estimates of radiative forcing and uncertainty therein given in AR5.

It is hoped that providing these 100 realisations in a form identical to the median estimate will encourage users to explore the sensitivity of their analysis to observational uncertainty with little extra effort.

Yeah, they're keeping that a huge secret: Section 8.6.3.2 of AR4 is called «Clouds,» and contains the statement «cloud feedbacks remain the largest source of uncertainty in climate sensitivity estimates.»

Because of the many uncertainties involved, any estimate of climate sensitivity comes with a range, a lower and upper limit within which the real value could reasonably lie.

«uncertainty» (in the IPCC attribution of natural versus human - induced climate changes, IPCC's model - based climate sensitivity estimates and the resulting IPCC projections of future climate) is arguably the defining issue in climate science today.

Lewis says that «CLARREO's contribution of more accurate and comprehensive data is likely to speed up the reduction in uncertainty,» in estimates of climate sensitivity.

from the pdf: Using a global energy budget approach, this paper seeks to understand the implications for climate sensitivity (both ECS and TCR) of the new estimates of radiative forcing and uncertainty therein given in AR5.

She said climate sensitivity and estimates of its uncertainty were important to establishing the cost benefit of taking action to limit greenhouse gas emissions.

To the contrarian, it is just a matter of time before other uncertainties will yield even lower estimates of sensitivity, until eventually it will fall to the point that it is nothing significant.

The bottom line is that spatial averaging of temperature data introduces yet another layer of uncertainty into climate sensitivity estimates.

The point is that using the IPCC's own estimates of forcings and associated uncertainties, the estimated sensitivity PDF falls far below the «distribution» of sensitivities diagnosed by GCM's.

Given current uncertainties in representing convective precipitation microphysics and the current inability to find a clear obser - vational constraint that favors one version of the authors» model over the others, the implications of this ability to engineer climate sensitivity need to be considered when estimating the uncertainty in climate projections.»

Nic invited me to coauthor this paper, and I was delighted to given my concerns about ignoring uncertainties in external forcing in attribution arguments and climate sensitivity estimates (which I discussed in the Uncertainty Monster paper).

The estimate of climate sensitivity and its associated uncertainty -LRB-!)

I again used the variance in our estimate of climate sensitivity as an indicator of uncertainty — if you are unclear about what that means, refresh your memory here.

In context of the way climate sensitivity is defined by the IPCC, uncertainty in climate sensitivity is decreasing as errors in previous observational estimates are identified and eliminated and model estimates seem to be converging more.

Climate science has been thrown into disarray by the hiatus, disagreement between climate model and instrumental estimates of climate sensitivity, uncertainties in carbon uptake by plants, and diverging interpretations of ocean heating (in the face of a dearth of observations).

This bias may be explained by a misrepresentation of mixed - phase extratropical clouds, often pinpointed as playing a key role in driving global - cloud feedback and uncertainties in climate sensitivity estimates (e.g., Tan et.

Using 72 - day averages resulted in a sensitivity ~ 1.0 C during the Pinatubo years, although there's a lot of noise and uncertainty around all the estimates.

It is worth noting that inferences of climate sensitivity from energy budget estimates suggest low ECS values, i.e., ~ 2 K, but their uncertainty is so large that they can not exclude much higher ECS (Forster 2016).

The problem with sensitivity estimates based on ancient data is the great uncertainty of the input data (solar activity, land albedo, etc), which creates very fuzzy numbers.

These uncertainties may partly explain the typically weak correlations found between paleoclimate indices and climate projections, and the difficulty in narrowing the spread in models» climate sensitivity estimates from paleoclimate - based emergent constraints (Schmidt et.

and «no data or computer code appears to be archived in relation to the paper» and «the sensitivity of Shindell's TCR estimate to the aerosol forcing bias adjustment is such that the true uncertainty of Shindell's TCR range must be huge — so large as to make his estimate worthless» and the seemingly arbitrary to cherry picked climate models used in Shindell's analysis.

When they define sensitivity or human contribution only with respect to their estimated forcings, it is implied that these are correct, but we know that the uncertainty with respect to clouds, aerosols, etc is large.

Changes in cloudiness in a warmer climate can be either a negative or positive feedback and the uncertainty in this feedback is the major source of uncertainty in the IPCC's estimate of climate sensitivity.

Gabi Hegerl did publish an estimate of climate sensitivity in 2006 based on a new proxy temperature reconstruction (only the last 700 years due to excessive uncertainty in forcings before then), which was cited in AR4 (Ch 9 of WG1).

While climate contrarians like Richard Lindzen tend to treat the uncertainties associated with clouds and aerosols incorrectly, as we noted in that post, they are correct that these uncertainties preclude a precise estimate of climate sensitivity based solely on recent temperature changes and model simulations of those changes.

Energy budget estimates of equilibrium climate sensitivity (ECS) and transient climate response (TCR) are derived based on the best estimates and uncertainty ranges for forcing provided in the IPCC Fifth Assessment Scientific Report (AR5).

The wide range of estimates of climate sensitivity is attributable to uncertainties about the magnitude of climate feedbacks (e.g., water vapor, clouds, and albedo).

Energy budget estimates of equilibrium climate sensitivity (ECS) and transient climate response (TCR) are derived using the comprehensive 1750 — 2011 time series and the uncertainty ranges for forcing components provided in the Intergovernmental Panel on Climate Change Fifth Assessment Working Group I Report, along with its estimates of heat accumulation in the climate system.