Sentences with phrase «model temperatures seem»

As you can clearly see, the 60 - month UAH alignment shifts the entire record down, artificially offsetting the satellite temps and making surface and model temperatures seem much higher.

Not exact matches

The flaring of M - dwarfs seems to die down over time, and new climate models suggest that even a locked planet could be habitable because its atmosphere would help even out the temperatures.

Regional trends are notoriously problematic for models, and seems more likely to me that the underprediction of European warming has to do with either the modeled ocean temperature pattern, the modelled atmospheric response to this pattern, or some problem related to the local hydrological cycle and boundary layer moisture dynamics.

Several models see a positive feedback of clouds when the temperatures increase, but this seems to be wrong, at least in the tropics and the Arctic, where clouds form a strong negative feedback.

Their model certainly doesn't explain all of the features of the temperature record, but since it was never their claim to have done so, such criticisms seem misplaced.

This seems to be associated with particular patterns of change in sea surface temperature in the Atlantic and Pacific oceans, a teleconnection which is well - captured in climate models on seasonal timescales.

By the 2030s, the modeling showed this year's coral bleaching temperatures could become average and after that they may start to seem cool.

This is based on one model, and that model has flaws (especially its temperature sensitivity that seems too great (David Galbraith's work), and its rainfall that seems to low (our PNAS paper PDF).

Jacob (and many, many others) seem to think that if model A, when run from 1900 to present, predicts the relatively flat, global average surface temperature record over the past decade, is a better match to reality than model B which does not.

Most models seem to have a very large margin of error, so that almost any recent temperature result can be said to fall within the M of E and validate the model.

It is quite strange that this paper seems to review future of tropical rainforest in the face of rising CO2 and rising temperature — unfortunately, it completely lacks to mention change in precipitation, which is just - another - very - important (climate change) metric — and it completely fails to mention modelling work of Peter Cox group — that predicts decline in rain forest productivity and growth due to decline in precipitation..

So the problem has been principally with MSU 2LT, which despite a strong surface temperature trend did not seem to have been warming very much — while models and basic physics predict that it should be warming at a slightly larger rate than the surface.

The two most common arguments against warming theories seem to be (1) local temperature variations (or mutually - inconclusive data) disprove global warming itself; and (2) models aren't real science, anyway, so we don't need to worry about them.

If this heat has been lost to space, and the models have not accounted for it, it would seem to me that it must have an effect on the model «projections» because the non-equalibrium forcing has changed (the system has been reset at a lower temperature).

The argument that larger sensitivity for natural (mainly solar and volcanic) goes at the cost of the sensitivity for natural and man - made greenhouse gases, or enhanced variability during pre-industrial times, would result in a redistribution of weight towards the role of natural factors in forcing temperature changes, seems to rely on a model like the following: T = a * ANTHRO + b * NAT

RE # 24, Ferdinand you state, «Several models see a positive feedback of clouds when the temperatures increase, but this seems to be wrong, at least in the tropics and the Arctic, where clouds form a strong negative feedback.»

Several models see a positive feedback of clouds when the temperatures increase, but this seems to be wrong, at least in the tropics and the Arctic, where clouds form a strong negative feedback.

Right now, we know that there is a solar cycle, that this cycle is parallel to the CO2 cycle and that the volcano signals (as interpreted by the models) seem to be almost invisible in the temperature data (Foukal picture).

A couple of years ago, when it was starting to become obvious that the average global surface temperature was not rising at anywhere near the rate that climate models projected, and in fact seemed to be leveling off rather than speeding up, explanations for the slowdown sprouted like mushrooms in compost.

In short, whatever the initial climate sensitivity is to a doubling of CO2, I just can't buy off on this positive feedback loop idea that says that temperatures are going to spin out of control once we pass over some «tipping point» that only seems to exists in some scientist's theoretical model.

It is the case that Hansens first models came out in 1988 and he did seem to correctly predict the spiking temperatures up until 1998 and the El Nino seemed to show the scary Scenario A behavior he described.

If we do not apply any physical modelling to the problem of finding the global average temperature, it seems to me that for each point on the Earth we can make no better temperature estimate than by interpolation based on triangles.

It seems as though the magnitude of the model biases in global average temperature do have some relationship with the magnitude of modeled future warming.

In «panel a» there appears to be quite a bit of agreement between modeled and observed global temperature from 1861 to the present and thus this seems to provide compelling visual support for climate models» ability to simulate / project global average temperature in the future.

«Willis builds a strawman Willis makes a logical fallacy known as the strawman fallacy here, when he says: The current climate paradigm says that the surface air temperature is a linear function of the «forcing»... Change in Temperature (∆ T) = Change in Forcing (∆ F) times Climate Sensitivity What he seems to have done is taking an equation relating to a simple energy balance model (probably from this Wikipedia entry) and applied it to the much more complex climtemperature is a linear function of the «forcing»... Change in Temperature (∆ T) = Change in Forcing (∆ F) times Climate Sensitivity What he seems to have done is taking an equation relating to a simple energy balance model (probably from this Wikipedia entry) and applied it to the much more complex climTemperature (∆ T) = Change in Forcing (∆ F) times Climate Sensitivity What he seems to have done is taking an equation relating to a simple energy balance model (probably from this Wikipedia entry) and applied it to the much more complex climate system.

«We can't think of anything else» is not very good as an answer and, according to him (I have no idea), predictive models of temperature - vs - CO2 concentration seem to be lacking.

The entire idea of using a climate model to «determine» the true influence of eastern Pacific temperatures seems to me a bit of a stretch..

It seems to me that the key issue is not to say whether current models accout for 40 % or 60 % of the observed variance in temperature but to generate falsifiable hypotheses from the models.

Much of the transfer from surface to upper troposphere occurs during non-equilibrium conditions that are hard to model, but it would seem that a small surface temperature increase ought to accompany a larger upper troposphere temperature increase.

Kininmonth seems to suggest that models can't handle temperature increases properly in terms of evaporation.

They claim that aerosols will significantly affect temperatures in the future and models will be inaccurate if this is not considered (seems obvious enough to me).

soundly based in actual temperature observations of the real world... while yours seems to be largely dreamt up as a consequence of untried and unproven models.

Also the importance of (temperature) measurement errors on the long term predictibility of non linear time series (= temperature records and proxies) seems to be key to me for an eventual validation of any predicitve model.

An ingenious theory, but the model set out in that paper seems to make predictions about what would happend to surface temperature if CO ₂ concentration were to vary which are out of kilter with empirical measurements by several orders of magitude in timescale and at least one order of magnitude and possibly the wrong sign in temperature.

For large scale quantities like global temperature, climate models seem to do this well.

It now seems clear that we are not modelling future global temperature with anything like the precision the IPCC claims and that the models are very substantially overestimating the rate of global temperature change: basically they are «wrong».

Seems to disprove my theory above... they are perhaps just doing the usual «here is a proxy temperature record, now please look over here at the model «projections»..

They don't seem to realize anywhere in the paper that the temperature data they are relying of for input to their models used for permafrost thaw comes from the little white box at the edge of the tarmac.

Considering the recent evidence that climate models have failed to predict the flattening of the global temperature curve, and that global warming seems to have ended some 15 years ago, the work of the NIPCC is particularly important.»

And the climate models seem to get the warming rate of sea surface temperatures just right for the smallest portion of the global oceans, the extratropical Northern Hemisphere (24N - 90N).

Although there have been jumps and dips, average atmospheric temperatures have risen little since 1998, in seeming defiance of projections of climate models and the ever - increasing emissions of greenhouse gases.»

But what with evidence somewhat lacking on positive CO2 feed backs, the present temperature plateau continuing, model projections of warming way out with observation, the analogy appears a bit, well, Ehrlichean, seems to me.And then there's the bleeding of economies by costs of CO2 reduction measures and subsidizing ineffectual, (evidence indicates even un-environmental) renewable energy policies, no gain for lotsa» pain.

In particular, the satellite temperature models seem more sensitive to the ENSO cycles.

Current GCM models may have realistic - seeming weather patterns, but are totally incapable of producing phenomena that look like the Holocene (Little Ice Age, Medieval Warm Period, Roman Warm Period, Holocene Optimum, the steady decline of temperature on average over the last 3,000 years, etc.) The Climate Science community has, instead, taken the path of trying to claim that these swings didn't occur (Michael Mann's «Hockey Stick», etc.) This does not give me a lot of confidence in the rest of their «science».

In terms of having anything useful to say about the likely temperature profile over the coming century, climate models seem to me to have too many weak links.

This casts some doubt on projections of global warming in as much as there seems to be a built - in bias in the models to overestimation of temperatures.

This seems to be an even greater blow than the failure of the global temperature to follow the models trend lines projected from the warming from 1970 to 1998.

This is important because the CAGW now seems to centre around CO2 causing «extreme weather» and the suggested activity by the different agencies to move the global temperature up to the models rather than the other way round.

This hardly seems to fit the IPCC description that «[m] odels reproduce observed continental - scale surface temperature patterns and trends over many decades» or is grounds for having «very high confidence» that the «model simulations show a trend in global - mean surface temperature from 1951 to 2012 that agrees with the observed trend.»

And, because the planet hasn't reached boiling point (in bitter defiance of the IPCC's models), the once concrete relationship between CO2 emissions and increasing global temperature now seems murky, at best.