Sentences with phrase «different estimates of sensitivity»

Steven Sherwood of the University of New South Wales in Sydney, Australia, and his colleagues looked at why different models give different estimates of sensitivity.

Then another scientist comes up with a different estimate of sensitivity.

Not exact matches

Note that the old GISS model had a climate sensitivity that was a little higher (4.2 ºC for a doubling of CO2) than the best estimate (~ 3ºC) and as stated in previous years, the actual forcings that occurred are not the same as those used in the different scenarios.

It is important to regard the LGM studies as just one set of points in the cloud yielded by other climate sensitivity estimates, but the LGM has been a frequent target because it was a period for which there is a lot of data from varied sources, climate was significantly different from today, and we have considerable information about the important drivers — like CO2, CH4, ice sheet extent, vegetation changes etc..

A combination of circumstances makes model - based sensitivity estimates of distant times and different climates hard to do, but at least we are getting a good education about it.

There are two recent papers on paleo constraints: the already mentioned PALAEOSENS (2012) paper which gives a good survey of existing estimates from paleo - climate and the hierarchy of different definitions of sensitivity.

See: Lockwood, J. R., Daniel F. McCaffrey, Laura S. Hamilton, Brian Stecher, Vi - Nhuan Le, and José Felipe Martinez, «The Sensitivity of Value - Added Teacher Effect Estimates to Different Mathematics Achievement Measures,» Journal of Educational Measurement 44 (1)(2007): 47 - 67.

The sensitivity of value - added teacher effect estimates to different mathematics achievement measures

We should underscore that the concepts of radiative forcing and climate sensitivity are simply an empirical shorthand that climatologists find useful for estimating how different changes to the planet's radiative balance will lead to eventual temperature changes.

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.

Maybe the word «equilibrium» should be omitted from all climate sensitivity estimates, from the shortest term values (TCR) to the longest and most comprehensive (Earth System), since all the different forms of sensitivity estimation seem, in my view, to be looking at somewhat different phenomena and should not necessarily yield the same values.

Trenberth et al. suggest that even the choice of a different data set of ocean heat content would have increased the climate sensitivity estimate of Otto et al. by 0.5 degrees.

Instead, we did an extensive parallel set of sensitivity analyses using an EBM w / different estimates of the forcings, different climate sensitivities, etc. and showed that our key conclusions are quite robust.

Indeed, this was found to be true for any of several different published volcanic forcing series for the past millennium, regardless of the precise geometric scaling used to estimate radiative forcing from volcanic optical depth, and regardless of the precise climate sensitivity assumed.

They want empirical estimates of relatively low sensitivity to be wrong, and think (with no credible rational) that the behavior of a GCM to different applied forcings is somehow a refutation of empirical estimates.

Each SCC estimate is the average of numerous iterations (10,000 in the EPA's assessment, which we reproduce here) of the model using different potential values for climate sensitivity (how much warming a doubling of CO2 will generate).

In reality, climate scientists have used many different lines of evidence to create numerous independent estimates of the planet's climate sensitivity.

(The «I think» was because I was hoping to extricate myself from CE for a while to finish off a paper explaining why climate sensitivity as currently defined can neither be measured nor estimated with an error bar less than 1 C per doubling, and proposing a different definition that shrinks the error bar by an order of magnitude.

How different are estimates of climate sensitivity using a 3D model?

If the two methods do lead to different estimates of climate sensitivity, I find it difficult to believe that the 1D model is more appropriate than 3D to making claims about how much the real average temperature will rise due to a given influence.

Before discussing this, a methodological point affecting estimates of S needs to be mentioned: results from methods estimating a PDF of climate sensitivity depend strongly on their assumptions of a prior distribution from which climate models with different S are sampled [Frame 2005].

Stating the «IPCC position on climate sensitivity is largely based on GCMs» (Montford) is different from «argu [ing] that GCMs are crucial to estimating climate sensitivity (your interpretation of Monford).»

«Today's best estimate of the sensitivity (between 2.7 degrees Fahrenheit and 8.1 degrees Fahrenheit) is no different, and no more certain, than it was 30 years ago.

In particular, two commonly used methods for converting cumulus condensate into precipitation can lead to drastically different climate sensitivity, as estimated here with an atmosphere — land model by increasing sea surface temperatures uniformly and examining the response in the top - of - atmosphere energy balance.

In an essay published this week, President Barack Obama's former climate advisor Steven Koonin said today's best estimate of the sensitivity was no different, and no more certain, than it was 30 years ago despite billions of dollars having been spent.

Way back in 2011 SteveF, using a completely different approach, estimate a climate sensitivity of 1.56 per doubling.

In light of the comments by Craig Loehle and Willis Eschenbach, we decided to update our original draft to include sections, • Discussing the different reconstruction methods used by the 19 proxy - based estimates, and their relative advantages / disadvantages • Providing a more detailed discussion of the lack of consistency between individual proxies, and the importance of carrying out rigorous «sensitivity studies», including a discussion of Willis Eschenbach's cluster analysis.

How many different estimates of CO2 sensitivity are embodied in the IPCC - blessed GCM?

This new NASA paper builds upon those previous studies by better quantifying the efficiencies of different forcings over the historical period and the effect this has on energy budget approach climate sensitivity estimates.

To better assess confidence in the different model estimates of climate sensitivity, two kinds of observational tests are available: tests related to the global climate response associated with specified external forcings (discussed in Chapters 6, 9 and 10; Box 10.2) and tests focused on the simulation of key feedback processes.

We study climate sensitivity and feedback processes in three independent ways: (1) by using a three dimensional (3 - D) global climate model for experiments in which solar irradiance So is increased 2 percent or CO2 is doubled, (2) by using the CLIMAP climate boundary conditions to analyze the contributions of different physical processes to the cooling of the last ice age (18K years ago), and (3) by using estimated changes in global temperature and the abundance of atmospheric greenhouse gases to deduce an empirical climate sensitivity for the period 1850 - 1980.

Barring a dramatic breakthrough in reconciliation of some long - standing differences in the magnitude of paleotemperature estimates for different proxies, the range of paleo - sensitivities will continue to have this uncertainty.

These two different years provide an estimate of the uncertainty in the sensitivity associated with the base state of the atmosphere.

What you have is a different estimate of climate sensitivity to CO2, not «how» the IPCC derived their estimate.