Sentences with phrase «model estimates of climate sensitivity»

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.

«The authors demonstrate that model estimates of climate sensitivity can be strongly affected by the manner through which cumulus cloud condensate is converted into precipitation in a model's convection parameterization, processes that are only crudely accounted for in GCMs.

Not exact matches

To estimate how much the sensitivity varies, Gary Russell of the NASA Goddard Institute for Space Studies in New York and colleagues ran a climate model repeatedly.

In addition, past data can be used to provide independent estimates of climate sensitivity, which provide a reality check on the models.

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.

In the end, Archibald concludes that the warming from the next 40 ppm of CO2 rise (never mind the rest of it) will only be 0.04 degrees C. Archibald's low - ball estimate of climate change comes not from the modtran model my server ran for him, but from his own low - ball value of the climate sensitivity.

Whether the observed solar cycle in surface temperature is as large as.17 K (as in Camp and Tung) or more like.1 K (many previous estimates) is somewhat more in doubt, as is their interpretation in terms of low thermal inertia and high climate sensitivity in energy balance models.

This is a 0.9 ºC reduction from the sensitivity of 2.5 °C estimated in that predecessor study, which used the same climate model.

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.

But to reiterate: the difference between climate sensitivity estimates based on land vs. ocean data indicates that something is seriously wrong, either with the model, or the data, or some of both.

Using Mg / Ca paleothermometry from the planktonic foraminifera Globigerinoides ruber from the past 500 k.y. at Ocean Drilling Program (ODP) Site 871 in the western Pacific warm pool, we estimate the tropical Pacific climate sensitivity parameter (λ) to be 0.94 — 1.06 °C (W m − 2) − 1, higher than that predicted by model simulations of the Last Glacial Maximum or by models of doubled greenhouse gas concentration forcing.

A number of subsequent publications qualitatively describe parameter values that allow models to reproduce features of observed changes, but without directly estimating a climate sensitivity probability density function (PDF).

Another way to estimate climate sensitivity from both models AND observations is to calculate the ratio of observed warming to forecast warming... then multiply that by the ECS value used in the model.

Climate model studies and empirical analyses of paleoclimate data can provide estimates of the amplification of climate sensitivity caused by slow feedbacks, excluding the singular mechanisms that caused the hyperthermal Climate model studies and empirical analyses of paleoclimate data can provide estimates of the amplification of climate sensitivity caused by slow feedbacks, excluding the singular mechanisms that caused the hyperthermal climate sensitivity caused by slow feedbacks, excluding the singular mechanisms that caused the hyperthermal events.

(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.

Using Mg / Ca paleothermometry from the planktonic foraminifera Globigerinoides ruber from the past 500 k.y. at Ocean Drilling Program (ODP) Site 871 in the western Pacific warm pool, we estimate the tropical Pacific climate sensitivity parameter (λ) to be 0.94 — 1.06 °C (W m − 2) − 1, higher than that predicted by model simulations of the Last Glacial Maximum or by models of doubled greenhouse gas concentration forcing.

As stated last year, the Scenario B in that paper is running a little high compared with the actual forcings growth (by about 10 %)(and high compared to A1B), and 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).

David's comments reminded me of something that Suki Manabe and I wrote more than 25 years ago in a paper that used CLIMAP data in a comparative evaluation of two versions of the 1980s - vintage GFDL model: «Until this disparity in the estimates of LGM paleoclimate is resolved, it is difficult to use data from the LGM to evaluate differences in low latitude sensitivity between climate models.»

The best estimates of climate sensitivity (around 3 deg.C per doubling of CO2) indicate that that's too much — in agreement with the conclusion from the model - data comparison.

A detailed reanalysis is presented of a «Bayesian» climate parameter study (Forest et al., 2006) that estimates climate sensitivity (ECS) jointly with effective ocean diffusivity and aerosol forcing, using optimal fingerprints to compare multi-decadal observations with simulations by the MIT 2D climate model at varying settings of the three climate parameters.

In addition, past data can be used to provide independent estimates of climate sensitivity, which provide a reality check on the models.

But 3,2 °C is the best estimate for equilibrium climate sensitivity (that is when the runs of models consider all the feedbacks).

Could some aspect of our situation, e.g. the extreme rapidity of the forcing change, be sufficiently novel to make Earth's climate respond differently than it has in the past, and could this cause divergence from models based on paleoclimate sensitivity estimates?

IPCC makes all sorts of calculations on the deleterious effects of NOT halting CO2 emissions, based on the same climate sensitivity estimate and a bunch of model «scenarios» on CO2 increase.

Using the IPCC model - based estimate for climate sensitivity and the same logarithmic calculation as for the UK alone, we will have averted 1.2 °C of warming by 2100 by shutting down the world carbon - based economy.

The reports for which you provided links are interesting, but do not provide any empirical evidence in support of the Myhre et al. model - based estimate of CO2 climate sensitivity (clear sky, no feedbacks).

Using the business - as - usual scenario for GHG radiative forcing (RCP8.5) and their novel estimate of Earth's warm - phase climate sensitivity the authors find that the resulting warming during the 21st century overlaps with the upper range of the Coupled Model Intercomparison Project Phase 5 (CMIP5) climate simulations.

So the two estimates (with and without solar forcing) give me a range of 0.7 C to 1.4 C for the 2xCO2 climate sensitivity, based on actually observed CO2 and temperature records, rather than model simulations and assumptions.

This Nature Climate Change paper concluded, based purely on simulations by the GISS - E2 - R climate model, that estimates of the transient climate response (TCR) and equilibrium climate sensitivity (ECS) based on observations over the historical period (~ 1850 to recent times) were biasClimate Change paper concluded, based purely on simulations by the GISS - E2 - R climate model, that estimates of the transient climate response (TCR) and equilibrium climate sensitivity (ECS) based on observations over the historical period (~ 1850 to recent times) were biasclimate model, that estimates of the transient climate response (TCR) and equilibrium climate sensitivity (ECS) based on observations over the historical period (~ 1850 to recent times) were biasclimate response (TCR) and equilibrium climate sensitivity (ECS) based on observations over the historical period (~ 1850 to recent times) were biasclimate sensitivity (ECS) based on observations over the historical period (~ 1850 to recent times) were biased low.

Anyone reading our paper may or may not agree with our choice of parameters and hence with our revised estimates of climate sensitivity, which are very much lower and very much closer to observed reality than those of the more complex models.

We already looked at how climate skeptics rely on a selective reading of the literature to highlight low estimates of climate sensitivity and use the divergence between climate models and measured temperatures to make conjectural statements about climate models being too sensitive to CO2, without considering other factors that could account for such divergence.

These values have been estimated using relatively simple climate models (one low - resolution AOGCM and several EMICs based on the best estimate of 3 °C climate sensitivity) and do not include contributions from melting ice sheets, glaciers and ice caps.

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.

Nevertheless, an estimate of total climate sensitivity that considers all feedbacks is crucial for checking these model results.

However, because climate scientists at the time believed a doubling of atmospheric CO2 would cause a larger global heat imbalance than today's estimates, the actual climate sensitivities were approximatly 18 % lower (for example, the «Best» model sensitivity was actually closer to 2.1 °C for doubled CO2).

However, as in the FAR, because climate scientists at the time believed a doubling of atmospheric CO2 would cause a larger global heat imbalance than current estimates, the actual «best estimate» model sensitivity was closer to 2.1 °C for doubled CO2.

The most popular observationally - constrained method of estimating climate sensitivity involves comparing data whose relation to S is too complex to permit direct estimation, such as temperatures over a spatio - temporal grid, with simulations thereof by a simplified climate model that has adjustable parameters for setting S and other key climate properties.

[7] Each individual estimate of the SCC is the realization of a Monte Carlo simulation based on a draw from an equilibrium climate sensitivity distribution to model the impact of CO2 emissions on temperature.

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).

Estimates of climate sensitivity predate both the IPCC and the development of computer models.

As these figures show, estimates from both models and observational data consistently find that the most likely climate sensitivity value is approximately 3 °C for a doubling of CO2.

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

If you know of anyone who has used the 3D model described in the paper I linked above (or a more complex one) to estimate this climate sensitivity parameter, please just share the link so I can see what they do and how they derive it.

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.

The three successive IPCC reports (1991 [2], 1996, and 2001 [3]-RRB- concentrated therefore, in addition to estimates of equilibrium sensitivity, on estimates of climate change over the 21st century, based on several scenarios of CO2 increase over this time interval, and using up to 18 general circulation models (GCMs) in the fourth IPCC Assessment Report (AR4)[4].

These are based on the IPCC model - derived 2xCO2 climate sensitivity of 3.2 °C, so let's stick with that estimate for now.

First, instead of using an ensemble of models to calculate the 66th percentile of runs that result in 1.5 C warming, they use a range of possible climate sensitivity values that ends up providing a more conservative estimate of what it would take to exceed 1.5 C.

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].

There appear to be upwards of 15 estimates below 1.5 C. Incorporating the numerous lower climate sensitivity estimates would need to rephrase to something like: «Climate sensitivity is likely to be in the range 0.5 °C to 4 °C with a best estimate of 0.6 °C for measurements and 3 °C for climate sensitivity estimates would need to rephrase to something like: «Climate sensitivity is likely to be in the range 0.5 °C to 4 °C with a best estimate of 0.6 °C for measurements and 3 °C for Climate sensitivity is likely to be in the range 0.5 °C to 4 °C with a best estimate of 0.6 °C for measurements and 3 °C for models.

«Lewis & Crok perform their own evaluation of climate sensitivity, placing more weight on studies using «observational data» than estimates of climate sensitivity based on climate model analysis.»