Sentences with phrase «climate feedback sensitivities»

Not exact matches

Earlier studies on the sensitivity of tropical cyclones to past climates have only analyzed the effect of changes in the solar radiation from orbital forcing on the formation of tropical cyclones, without considering the feedbacks associated to the consequent greening of the Sahara.

The conclusion that limiting CO2 below 450 ppm will prevent warming beyond two degrees C is based on a conservative definition of climate sensitivity that considers only the so - called fast feedbacks in the climate system, such as changes in clouds, water vapor and melting sea ice.

Using information from pre-historic climate archives, Zeebe calculated how slow climate feedbacks (land ice, vegetation, etc.) and climate sensitivity may evolve over time.

Zeebe uses past climate episodes as analogs for the future, which suggest that so - called slow climate «feedbacks» can boost climate sensitivity and amplify warming.

First that CO2 is the main climate driver, second that in calculating climate sensitivity the GHE due to water vapour should be added to that of CO2 as a feed back effect and third that the GHE of water vapour is always positive.As to the last point the feedbacks can not be positive otherwise we wouldn't be here to talk about it.

Indeed, it is precisely the role of these positive feedbacks that is at the heart of discussions of climate sensitivity.

The climate sensitivity classically defined is the response of global mean temperature to a forcing once all the «fast feedbacks» have occurred (atmospheric temperatures, clouds, water vapour, winds, snow, sea ice etc.), but before any of the «slow» feedbacks have kicked in (ice sheets, vegetation, carbon cycle etc.).

The variation in global climate sensitivity among GCMs is largely attributable to differences in cloud feedbacks, and feedbacks of low - level clouds in particular.

One issue that I have wondered about for some time is to what extent the paleoclimate record supports the distinction between slow - feedback and fast - feedback climate sensitivity.

From the paper...» These results provide enhanced confidence in the range of climate sensitivity in climate simulations, which are based on a positive uppertropospheric water vapor feedback.

Climate is not different, as can be seen in the fact that a broad range of cloud feedbacks (compensated by other parameters...) or a range of combined aerosol / CO2 sensitivities is able to fit the temperature of the past century.

I'm not even an amateur climate scientist, but my logic tells me that if clouds have a stronger negative feedback in the Arctic, and I know (from news) the Arctic is warming faster than other areas, then it seems «forcing GHGs» (CO2, etc) may have a strong sensitivity than suggested, but this is suppressed by the cloud effect.

Sure, there might be a few papers that take climate sensitivity as a given and somehow try to draw conclusions about the impact on the climate from that... But, I hardly think that these are swamping the number of papers trying to determine what the climate sensitivity is, studying if the water vapor feedback is working as expected, etc., etc..

Thus in summary, a change in sensitivity of one of the primary actors in climate variation has only effect for the general sensitivity of climate, if all the feedbacks are essentially similar for all primary actors involved, which is highly probably not the case...

Temperature sensitivity of soil carbon decomposition and feedbacks to climate change.

Stowasser, M., K. Hamilton, and G.J. Boer, 2006: Local and global climate feedbacks in models with differing climate sensitivity.

That's the same value for climate sensitivity I've seen from the string theory physics site and from knowledgeable climate sites as well — it's the number people get this way: calculated in the absence of any feedback, on the hypothetical twinning of each molecule of CO2 in the atmosphere to make two where there were one, instantly, and having nothing else happen.

(where T = temperature, f = feedback factor and F a Flux or Forcing and C is the baseline climate sensitivity i.e. for a clear atmosphere)

A sensitivity which is too low will be inconsistent with past climate changes - basically if there is some large negative feedback which makes the sensitivity too low, it would have prevented the planet from transitioning from ice ages to interglacial periods, for example.

A 2008 study led by James Hansen found that climate sensitivity to «fast feedback processes» is 3 °C, but when accounting for longer - term feedbacks (such as ice sheet disintegration, vegetation migration, and greenhouse gas release from soils, tundra or ocean), if atmospheric CO2 remains at the doubled level, the sensitivity increases to 6 °C based on paleoclimatic (historical climate) data.

Govindasamy, B., et al., 2005: Increase of the carbon cycle feedback with climate sensitivity: results from a coupled and carbon climate and carbon cycle model.

All this discussion of the Schmittner et al paper should not distract from the point that Hansen and others (including RichardC in # 40 and William P in # 24) try to make: that there seems to be a significant risk that climate sensitivity could be on the higher end of the various ranges, especially if we include the slower feedbacks and take into account that these could kick in faster than generally assumed.

For instance, the sensitivity only including the fast feedbacks (e.g. ignoring land ice and vegetation), or the sensitivity of a particular class of climate model (e.g. the «Charney sensitivity»), or the sensitivity of the whole system except the carbon cycle (the Earth System Sensitivity), or the transient sensitivity tied to a specific date or period of time (i.e. the Transient Climate Response (TCR) to 1 % increasing CO2 aftersensitivity only including the fast feedbacks (e.g. ignoring land ice and vegetation), or the sensitivity of a particular class of climate model (e.g. the «Charney sensitivity»), or the sensitivity of the whole system except the carbon cycle (the Earth System Sensitivity), or the transient sensitivity tied to a specific date or period of time (i.e. the Transient Climate Response (TCR) to 1 % increasing CO2 aftersensitivity of a particular class of climate model (e.g. the «Charney sensitivity»), or the sensitivity of the whole system except the carbon cycle (the Earth System Sensitivity), or the transient sensitivity tied to a specific date or period of time (i.e. the Transient Climate Response (TCR) to 1 % increasing CO2 after 70 climate model (e.g. the «Charney sensitivity»), or the sensitivity of the whole system except the carbon cycle (the Earth System Sensitivity), or the transient sensitivity tied to a specific date or period of time (i.e. the Transient Climate Response (TCR) to 1 % increasing CO2 aftersensitivity»), or the sensitivity of the whole system except the carbon cycle (the Earth System Sensitivity), or the transient sensitivity tied to a specific date or period of time (i.e. the Transient Climate Response (TCR) to 1 % increasing CO2 aftersensitivity of the whole system except the carbon cycle (the Earth System Sensitivity), or the transient sensitivity tied to a specific date or period of time (i.e. the Transient Climate Response (TCR) to 1 % increasing CO2 afterSensitivity), or the transient sensitivity tied to a specific date or period of time (i.e. the Transient Climate Response (TCR) to 1 % increasing CO2 aftersensitivity tied to a specific date or period of time (i.e. the Transient Climate Response (TCR) to 1 % increasing CO2 after 70 Climate Response (TCR) to 1 % increasing CO2 after 70 years).

In some sense, though, almost any known forcing is useful in inferring climate sensitivity, since the same feedbacks that determine the response to Milankovic also determine response to CO2, though the relative weightings of the different feedbacks are likely to be different.

So the reference system climate sensitivity parameter is based on a negative feedback due to Stefan's law.

Note that the observational approach needs to assume a constant climate sensitivity between different states, whereas perturbed physics ensembles don't (though you still need to understand what feedback processes are important between different climate states to have confidence in the results).

Webb, M.J., et al., 2006: On the contribution of local feedback mechanisms to the range of climate sensitivity in two GCM ensembles.

They got 10 pages in Science, which is a lot, but in it they cover radiation balance, 1D and 3D modelling, climate sensitivity, the main feedbacks (water vapour, lapse rate, clouds, ice - and vegetation albedo); solar and volcanic forcing; the uncertainties of aerosol forcings; and ocean heat uptake.

At its present temperature Earth is on a flat portion of its fast - feedback climate sensitivity curve.

The goal of the paper under review, as I take it, is an attempt to put an upper bound on the Charney climate sensitivity feedback by considering the LCM paleoclimate.

The relative contributions of the various feedbacks that make up climate sensitivity need not be the same going back to the LGM as in a world warming relative to the pre-industrial climate.

New paper mixing «climate feedback parameter» with climate sensitivity... «climate feedback parameter was estimated to 5.5 ± 0.6 W m − 2 K − 1» «Another issue to be considered in future work should be that the large value of the climate feedback parameter according to this work disagrees with much of the literature on climate sensitivity (Knutti and Hegerl, 2008; Randall et al., 2007; Huber et al., 2011).

The regional climate feedbacks formulation reveals fundamental biases in a widely - used method for diagnosing climate sensitivity, feedbacks and radiative forcing — the regression of the global top - of - atmosphere radiation flux on global surface temperature.

Beckage tells us that the uncertainty from human feedback comes close to the uncertainty scientists still have in the physical systems (things like permafrost melt, climate sensitivity, and all that).

A few other things — Mann et al. does not «get rid» of a MWP and LIA — «weaker TSI forcing would imply the presence of a stronger climatic feedback to TSI variation and / or a stronger climate sensitivity to other solar changes» — What about non-solar changes?

This empirical fast - feedback climate sensitivity allows water vapor, clouds, aerosols, sea ice, and all other fast feedbacks that exist in the real world to respond naturally to global climate change.

However, in view of the fact that cloud feedbacks are the dominant contribution to uncertainty in climate sensitivity, the fact that the energy balance model used by Schmittner et al can not compute changes in cloud radiative forcing is particularly serious.

Water vapour feedback is the most important feedback enhancing climate sensitivity.

They find a climate feedback parameter of 2.3 ± 1.4 W m — 2 °C — 1, which corresponds to a 5 to 95 % ECS range of 1.0 °C to 4.1 °C if using a prior distribution that puts more emphasis on lower sensitivities as discussed above, and a wider range if the prior distribution is reformulated so that it is uniform in sensitivity (Table 9.3).

Although the strength of this feedback varies somewhat among models, its overall impact on the spread of model climate sensitivities is reduced by lapse rate feedback, which tends to be anti-correlated.

Some of these papers also used other priors for climate sensitivity as alternatives, typically either informative «expert» priors, priors uniform in the climate feedback parameter (1 / S) or in one case a uniform in TCR prior.

It is even incompatible with the low climate sensitivities you would get in a so - called «no - feedback» response (i.e just the Planck feedback — apologies for the terminological confusion).

It seems to me we should use the higher values for climate sensitivity, including the slower feedbacks, for a complete assessment of risks upto the seventh generation, so to speak.

It's also another piece of evidence that is consistent with fast feedback climate sensitivity of around 0.75 °C / W / m ².

Absent understanding of cloud feedback processes, the best you can really do is mesh it into the definition of the emergent climate sensitivity, but I think probing (at least some of) the uncertainties in effects like this is one of the whole points of these ensemble - based studies.

Plotting GHG forcing (7) from ice core data (27) against temperature shows that global climate sensitivity including the slow surface albedo feedback is 1.5 °C per W / m2 or 6 °C for doubled CO2 (Fig. 2), twice as large as the Charney fast - feedback sensitivity.»

[Response: Computed cloud feedbacks would mainly have the potential to affect the results by changing the asymmetry between the climate sensitivity going into the LGM vs. going into a 2xCO2 world.

Abstract:» The sensitivity of global climate with respect to forcing is generally described in terms of the global climate feedback — the global radiative response per degree of global annual mean surface temperature change.

These models all suggest potentially serious limitations for this kind of study: UVic does not simulate the atmospheric feedbacks that determine climate sensitivity in more realistic models, but rather fixes the atmospheric part of the climate sensitivity as a prescribed model parameter (surface albedo, however, is internally computed).

Then on page 9.5 we read «There is very high confidence that the primary factor contributing to the spread in equilibrium climate sensitivity continues to be the cloud feedback.