Sentences with phrase «clouds on climate sensitivity»

Scientists have revealed the impact of clouds on climate sensitivity.

Not exact matches

Climate sensitivity depends on a number of properties of the earth's climate system, such as the composition of clouds and cloudClimate sensitivity depends on a number of properties of the earth's climate system, such as the composition of clouds and cloudclimate system, such as the composition of clouds and cloud cover.

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.

The research also appears to solve one of the great unknowns of climate sensitivity, the role of cloud formation and whether this will have a positive or negative effect on global warming.

Note that the last remark can go either way, as the solar signal can even be more enhanced at the cost of the sensitivity for the greenhouse signal... And from Hansen ea.: «Solar irradiance change has a strong spectral dependence [Lean, 2000], and resulting climate changes may include indirect effects of induced ozone change [RFCR; Haigh, 1999; Shindell et al., 1999a] and conceivably even cosmic ray effects on clouds [Dickinson, 1975].

A 2015 USDA report (Brown et al. 2015) on how climate affects agriculture delineates the sensitivities of specialty crops to many climate components (e.g., temperatures, atmospheric CO2 levels, water supply, cloud and light conditions, high winds and other extreme conditions).

Given that clouds are known to be the primary source of uncertainty in climate sensitivity, how much confidence can you place in a study based on a model that doesn't even attempt to simulate clouds?

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.

We'll also dig into some of his peer reviewed work, notably the recent paper by Spencer and Braswell on climate sensitivity, and his paper on tropical clouds which is widely misquoted as supporting Lindzen's IRIS conjecture regarding stabilizing cloud feedback.

And now, work on clouds will narrow the climate sensitivity range.

It is my understanding that the uncertainties regarding climate sensitivity to a nominal 2XCO2 forcing is primarily a function of the uncertainties in (1) future atmospheric aerosol concentrations; both sulfate - type (cooling) and black carbon - type (warming), (2) feedbacks associated with aerosol effects on the properties of clouds (e.g. will cloud droplets become more reflective?)

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.

I haven't seen anything that very strongly supports the IRIS idea, but I do concur with one idea buried in the paper: that the parameterization of fractional cloud cover in GCM's is not based on very clear physical principles, and could operate in many different ways — some of which, I think, could make climate sensitivity considerably greater than the midrange model of the current crop.

On the real planet, there are multitudes of feedbacks that affect other greenhouse components (ice alebdo, water vapour, clouds etc.) and so the true issue for climate sensitivity is what these feedbacks amount to.

If you altered the rate of conversion from cloud ice to snow instead / in addition could this have a larger effect on upper - level cloud, and therefore a larger effect on climate sensitivity?

This «climate sensitivity» not only depends on the direct effect of the GHGs themselves, but also on natural «climate feedback» mechanisms, particularly those due to clouds, water vapour, and snow cover.

Read more «Constraints on Climate Sensitivity From Space - Based Measurements of Low - Cloud Reflection»»

Alec Rawls, on the other hand, points out that if his criticism of Chapter 7 of the AR5 is valid, and it has been accepted by the authors of Chapter 7, then the value of climate sensitivity estimated by Nic Lewis is a MAXIMUM value, which could be less depending on the effect of clouds.

Based on evidence from Earth's history, we suggest here that the relevant form of climate sensitivity in the Anthropocene (e.g. from which to base future greenhouse gas (GHG) stabilization targets) is the Earth system sensitivity including fast feedbacks from changes in water vapour, natural aerosols, clouds and sea ice, slower surface albedo feedbacks from changes in continental ice sheets and vegetation, and climate — GHG feedbacks from changes in natural (land and ocean) carbon sinks.

(Note: the biggest issue is climate sensitivity, with a secondary issue being the magnitude of modes of natural internal variability on multi-decadal time scales, and tertiary issues associated model inadequacies in dealing with aerosol - cloud processes and solar indirect effects.)

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.

On the other hand the projected positive feedbacks you support, which are COMPLETELY theoretical, depend on the LEAST understood aspects of the affect of water vapor and cloud formation, so the strong feedbacks PROJECTED are the least dependable, while the «OBSERVATIONS» used by Lindzen, Spencer, and others, support the lower estimates of climate sensitivitOn the other hand the projected positive feedbacks you support, which are COMPLETELY theoretical, depend on the LEAST understood aspects of the affect of water vapor and cloud formation, so the strong feedbacks PROJECTED are the least dependable, while the «OBSERVATIONS» used by Lindzen, Spencer, and others, support the lower estimates of climate sensitiviton the LEAST understood aspects of the affect of water vapor and cloud formation, so the strong feedbacks PROJECTED are the least dependable, while the «OBSERVATIONS» used by Lindzen, Spencer, and others, support the lower estimates of climate sensitivity.

Of course, there could be a (Thomas Kuhn) «paradigm shift» resulting from the CLOUD experiment at CERN, which would put the whole current paradigm of high «climate sensitivity» on its head.

But in a given model you can often find ways of altering the model's climate sensitivity through the sub-grid convection and cloud schemes that affect cloud feedback, but you have to tread carefully because the cloud simulation exerts a powerful control on the atmospheric circulation, top - of - atmosphere (TOA) and surface radiative flux patterns, the tropical precipitation distribution, etc..

Given the importance of changes in boundary layer clouds to climate sensitivity, it would make more focus on predictors from areas where boundary layer clouds are important.

BH: Some of them are talking about climate sensitivity at 1.2 C, at 1.5 C. I think this is completely implausible because the basic energetics of the climate system responding to the additional greenhouse gas emissions almost from simple physics, has to be at least 1.2 C and possibly more before you begin to take into account any of the feedbacks in the system from water vapour in clouds and so on.

The MIT model permits one to systematically vary the model's climate sensitivity (by varying the strength of the cloud feedback) and rate of mixing of heat into the deep ocean and determine how the goodness - of - fit with observations depends on these factors.

Merging realistic estimates of low - cloud amount, high - cloud amount, and extratropical optical depth feedbacks would likely increase our confidence in constraints on climate sensitivity from climate models.

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.

[~ 17 model years](Motivation: Variation in the climate response across models will be a function of (a) different climate sensitivity in the GCMs, (b) different impact of aerosols on climate (due to location with respect to clouds, water uptake, natural aerosols, mixing, etc), and (c) different 3D constituent fields from the composition models.

That increased atmospheric water vapor will also affect cloud cover, though impacts of changes in cloud cover on climate sensitivity are much more uncertain.

The impact on the 2xCO2 climate sensitivity (p. 633): +1.9 °C ± 0.15 °C — including all feedbacks, except clouds +3.2 °C ± 0.7 °C — including all feedbacks, including clouds

On the other hand, in the SMEs with relatively high climate sensitivity (about 4 — 10 K), or the SMEs with relatively low climate sensitivity (about 2 — 3 K) compared to the studies in the literature, SW and LW radiation and cloud radiative forcing are not reliable.

Later on (p 163) the derivation of climate sensitivity omits clouds completely — does that additional simplification introduce non-negligible inaccuracy?

But I also believe it is reasonable to conclude, based on all the recent data out there, that the net feedback from clouds (LW+SW) is very likely to be negative (rather than strongly positive, as assumed by all the models cited by IPCC), and that the 2xCO2 climate sensitivity is very likely to be below 1.5 C (probably closer to 1C).