Sentences with phrase «much about climate models»

Griffith knows that all these speculations are mostly for shits and giggles, but there is a value in roping in those who might not think much about climate models and how they work.

Not exact matches

By improving the understanding of how much radiation CO2 absorbs, uncertainties in modelling climate change will be reduced and more accurate predictions can be made about how much Earth is likely to warm over the next few decades.

But early on Jenkins realized that the global climate models are too coarse to tell much about what's going to happen in the Sahelian zone.

The impact of these results is wide - reaching, and Dr Pullen suggests that it may even change how we think about global climate data: «Climate models need to incorporate genetic elements because at present most do not, and their predictions would be much improved with a better understanding of plant carbon demand.climate data: «Climate models need to incorporate genetic elements because at present most do not, and their predictions would be much improved with a better understanding of plant carbon demand.Climate models need to incorporate genetic elements because at present most do not, and their predictions would be much improved with a better understanding of plant carbon demand.»

Using climate models and data collected about aerosols and meteorology over the past 30 years, the researchers found that air pollution over Asia — much of it coming from China — is impacting global air circulations.

As can be seen your graph, our climate models make a wide range of predictions (perhaps 0.5 - 5 degC, a 10-fold uncertainty) about how much «committed warming» will occur in the future under any stabilization scenario, so we don't seem to have a decent understanding of these processes.

With about half of climate models predicting a return to «neutral» conditions, there's even a fair chance the much - hyped La Niña won't materialise at all.

They do, however, raise serious questions about the validity of climate models (which are, of course, used to predict future warming and are used to set public policy and sway public opinion) and how much we are actually warming.

This point might become clearer once it's realised that climate models are not developed just to the climate change problem, but as much more general tools to quantify the net effects of all the different processes we know about.

A new study shows that the climate simulated by a numerical climate model can depend surprisingly much of what is assumed about the snow grain shapes when computing the reflection of solar radiation by the snowpack.

As global methane levels have increased, the impact has been felt twice as much in the Arctic, about a half a degree Celsius more of Arctic warming, according to climate models.

John Christy and Roy Spencer of the University of Alabama published a series of papers starting about 1990 that implied the troposphere was warming at a much slower rate than the surface temperature record and climate models indicated Spencer and Christy (1992).

This point might become clearer once it's realised that climate models are not developed just to the climate change problem, but as much more general tools to quantify the net effects of all the different processes we know about.

When you think about the uncertainties of economic models and how much money is invested using those models as a basis, the idea that we don't know enough about climate change is laughable.

An equatorial volcano occurring during that period would allow much better model calibration, for example, settling questions about transient climate response.

We used it heavily as part of a Global Climate Processes course at UW - Madison for later undergrad and grad students, so it has a good deal of flexibility in what you can test (though the model blows up for extreme forcings like snowball Earth, I used CO2 at about 140 ppm and couldn't get much lower than that).

However, that his statement can be quoted in a major US newspaper says much about the level of public knowledge concerning climate change and the models used to try and understand it.

All in all the science of hurricanes does appear to be much more fun and interesting than the average climate change issue, as there is a debate, a «fight» between different hypothesis, predictions compared to near - future observations, and all that does not always get pre-eminence in the exchanges about models.

The pace of ice loss — both its extent and the amount of the older, thicker ice that survives from summer to summer — has been faster than most models predicted and clearly has, as a result, unnerved some polar researchers by revealing how much is unknown about ice behavior in a warming climate.

John, On the «Presentation: Precautionary Principle...» thread you told me that you think it's «unhelpful to conflate discussion of climate - science issues like the modelling of SO2, about which none of us here know very much, with discussion of economic projections, where we can have a useful discussion.»

Psychologists studying climate communication make two additional (and related) points about why the warming - snow link is going to be exceedingly difficult for much of the public to accept: 1) people's confirmation biases lead them to pay skewed attention to weather events, in such a way as to confirm their preexisting beliefs about climate change (see p. 4 of this report); 2) people have mental models of «global warming» that tend to rule out wintry impacts.

It has already been demonstrated climate models, the Holy Relic of AGW, are merely paramterized engineering code that thus far can not predict much of anything correctly, so what is the argument about?

Brad DeLong expresses qualified Skepticism Toward the Skeptical Environmentalist I think there's a much more fundamental problem in Lomborg's argument about global warming, as I argue here The Intergovernmental Panel on Climate Change cites a range of model estimates of the costs of implementing Kyoto using market mechanisms.

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 climate scientists that worry about these issues don't post here (much - Jeff made a single post) so you aren't really going to see a meaningful discussion on the role of chaos or stochastic processes on climates, how that is handled in model building, and what that means in terms of model verification.

Either WUWT has wrongly concluded what the IPCC's models show, or the constant ululating about the fast left - wing / socialist / eco-Nazi / climate scientist conspiracy is much ado about nothing.

In as much as none of the model scenarios can be validated, all predictions about future climate conditions amount to nothing more that, «Wait to see if our predictions come true; you'll see then.

As others have noted, the IPCC Team has gone absolutely feral about Salby's research and the most recent paper by Dr Roy Spencer, at the University of Alabama (On the Misdiagnosis of Surface Temperature Feedbacks from Variations in Earth's Radiant Energy Balance), for one simple reason: both are based on empirical, undoctored satellite observations, which, depending on the measure required, now extend into the past by up to 32 years, i.e. long enough to begin evaluating real climate trends; whereas much of the Team's science in AR4 (2007) is based on primitive climate models generated from primitive and potentially unreliable land measurements and proxies, which have been «filtered» to achieve certain artificial realities (There are other more scathing descriptions of this process I won't use).

«Uncertainty» about whether or not something (very costly), which we do (in the «uncertain» attempt to change our climate from an «uncertain» model - generated threat) will have «uncertain» unintended negative consequences, which could be much more severe than the «uncertain» threat we are attempting to mitigate against in the first place, seems to ba a reasonable justification for NOT doing this mitigating action.

I found the climate models unconvincing (they help us learn about climate but I don't think have predictive capability) but I accepted IPCC without giving it much thought.

This is not too surprising because (a) CO2 concentrations didn't actually increase much until about the 1950s, and (b) the current climate models don't include many mechanisms to account for natural global warming.

The rapid melting of the Arctic sea ice, then, illuminates the difficulty of modelling the climate — but not in a way that brings much comfort to those who hope that fears about the future climate might prove exaggerated.

Much of what we know and conclude about climate change is based on computer models, which have proven to be inaccurate over the years, and the Antarctic sea ice growth is another example of where the model went wrong.

Miller observed that estimates from CMIP5 climate models were much lower — about 1.1 deg C — from which he deduced that things were worse than we thought.

Based on temperature records from 1864 to 2002, the odds of such a heatwave occurring are about 1 in 10 million.4 An event like the 2003 heatwave becomes much more likely after factoring in the observed warming of 2 °F over Europe and increased weather variability.5 In addition, comparing computer models of climate with and without human contribution shows that human influence has roughly quadrupled the odds of a European summer as hot as or hotter than the summer of 2003.6

The disagreement is not so much about observational evidence, but rather about the epistemic status of climate models, the logics used to link the observational evidence into arguments, the overall framing of the problem and overconfident conclusions in the face of incomplete evidence and understanding.

Klapper seems to feel that the models need some fixing to better match past climates, and seems unwilling to accept that there may be not much that can be done about it, due to inaccuracies.

A new study shows that the climate simulated by a numerical climate model can depend surprisingly much of what is assumed about the snow grain shapes when computing the reflection of solar radiation by the snowpack.

That we tend to see much more discussion about global warming is I think because of the limitations of the climate models when they go to more regional and seasonal predictions and refinements of max versus min temperature trends.

Translating the above to climate science, if you tell me that in 100 years earth inhabited by your children is going to hell in a handbasket, because our most complicated models built with all those horrendously complicated equestions you can find in math, show that the global temperatures will be 10 deg higher and icecaps will melt, sea will invade land, plant / animal ecosystem will get whacked out of order causing food supply to be badly disrupted, then I, without much climate science expertise, can easily ask you the following questions and scrutinize the results: a) where can I see that your model's futuristic predictions about global temp, icecaps, eco system changes in the past have come true, even for much shorter periods of time, like say 20 years, before I take this for granted and make radical changes in my life?

Neither approach is likely to help them much if for no other reason than that both approaches will drive the debate into complex arguments about whose climate or economic modelling is using the best assumptions, data etc..

The failure by man and model to fully understand and explain them reflects that neither man nor model really knows all of that much about climate mechanisms at this time.

Everyone interested in global warming climate change 7 maths and physics should read about «Climate as a random walk» as a model fit its much much better than anythinclimate change 7 maths and physics should read about «Climate as a random walk» as a model fit its much much better than anythinClimate as a random walk» as a model fit its much much better than anything else.

Much of the controversy about uncertainties comes from these areas, most notably from climate modeling.

You would get much better results lowering the tone and being less hyperbolicsesquedalimiystic about climate models.

However, statistical analysis very clearly support the theory, which also imply that the climate sensitivity to CO2 doubling is about 1.5 K. And models made using this hypothesis are able to explain the temperature patterns since 1850 very well, much better than any IPCC CMIP5 models.

By consulting climate records and modeling extreme events with and without added greenhouse gases, scientists can talk about how much global warming has increased the chances of extreme events — without blaming any one event on warming.

Tests of models using those estimates of climate sensitivity predict about twice as much warming as actually occurred.

«I said that the models don't tell us much about how the jet stream is affected by climate change.

Collins, yesterday on Twitter: «I said that the models don't tell us much about how the jet stream is affected by climate change.