That isn't how modeling works...models test hypotheses, ranking them relative to the information in the data. Models are data driven. Saying models generate hypotheses is a false statement just like it isn't true when you have said that models generate data. Where can you point to the mis-statement you have made having ever been in anyway proven since hypotheses are not model generated?
If you limit the scope of the hypotheses you exclude modeling all available data. Ranking models becomes meaningless if you have introduced a bias by excluding some hypotheses or data from an analysis. Which brings us back to the original disagreement between Ryan and Ronny.
"All the clouds turn to words
All the words float in sequence
No one knows what they mean
Everyone just ignores them"
Brian Eno, 1975
Rusty, you are confused, I will attempt to assist in your confusion however, I feel it is in vain.
I will start out with computer models, the sole purpose of a model or simulator is to output data, thats what computer models and simulators do, period. The data that goes into the model is variable and the data that comes out is the result of the models process[s] or formula[s] executed on the variables inputted.
The models generate the data that will help to prove or disprove a particular hypothesis as well as to help steer the hypothesis moving forward based on the data gleaned from the model.
The hypothesis that our environment is steadily warming at a catastrophic pace due to humans releasing C02 is based almost entirely on data derived from faulty computer models that could never be accurate. As I have stated previously we humans are incredibly far from possessing the technology to create an accurate computer model of our climate here on earth, thats a fact plain and simple. All of the media hyperbole and fear mongering is also based on the data, or outcome, if you like, of these models that have puked out data indicating that our climate is going to warm catastrophically based on our release of C02.
I dont know how much simpler I can state that.
As far as pointing out inaccurate models of the climate? Pick one! I would challenge you to find one that can be proven accurate.
I will not debate about semantics.
Climate models: Garbage in, garbage out.
The hypothesis that humans are causing unprecedented, catastrophic, irreversible, global warming is based on climate models that can't accurately model historical climate or predict current climate and therefore can't predict any future climate.
The catastrophic warming that AlGore predicted in his docudrama failed the test of empirical data; it didn't happen.
Regardless of one's beliefs, what really matters is what one does to reduce their impact on the planet.
Well actually models generate parameter estimates and effect size based on the data...they don't generate data
Again, model parameters estimate effect size and inform us of the relative contribution of the different variables in the data set to the model. Models don't generate data. The model fit is how the best models sort themselves out.
The models can then be objectively ranked by how well each represents the signal in the data. This allows objective comparisons between models. A model for no effect of CO2 on global temperatures is always within the model set (one of the hypotheses being tested)...it just doesn't rank higher than models that include CO2 because it doesn't capture the information in the data as well
No fair...i asked you to back up your broad over generalization first but i am patiently waiting
Actually the climate models are in pretty close agreement. When you pick the extreme high point of a 95% confidence interval as your expected value you will be wrong most of the time.
Sounds fair enough...please get back to us when you have some practice with modeling
Rusty, My concern of my comments being in vain were well founded. It is pointless to debate this as your simply 'out there'.
Please get back to us when you understand what data is and what the function of a model is.
And what broad over generalization would that be? I have made nothing of the sort.
From the GWPF and Dr. Benny Peiser
News Media No Longer Interested In Climate Hysteria
2013 marks the 17th year of no warming on the planet.
Global sea ice area is the second highest on record for Dec 16th, and the highest since 1988. For most of this year, it has been above the 1979-2008 mean. –Paul Homewood, Not A Lot Of People Know That, 19 December 2013
Almost everything that could go wrong did go wrong for the cause of global warming. 2013 was the best of years for climate skeptics; the worst of years for climate change enthusiasts for whom any change – or absence of change — in the weather served as irrefutable proof of climate change. That governments and the public would abandon the duty to stop climate change was in their minds no more thinkable than Hell freezing over. Which the way things are going for them, may happen in 2014. –Lawrence Solomon, Financial Post, 20 December 2013
As the Anthropogenic Global Warming boondoggle continues to collapse, the Greens and others complicit in the warming alarmist industry are busily looking for reasons for their failure to convince people of the validity of their message. It’s called crying Wolf, repeatedly, the Greens simply don’t comprehend that after decades of failed predictions of looming environmental holocaust, people are bored of the CO2 wolf that never comes. Like all good scams and totalitarian ideologies the suppression of dissent and discussion was of a paramount importance to keep the public with the Green message. The Greens and warmists always knew that their story would never stand up to public scrutiny and debate which is why they worked so hard to suppress dissent and smear the opponents with labels like “Denier”. –Tory Aardvark, 17 December 2013
The maps in Figure 1 show the modeled and observed linear trends for the full term of the GISS data, from 1880 to 2012. The CMIP5-archived simulations indicate stronger-than-observed polar-amplified warming at high latitudes in the Northern Hemisphere. The models also show a more uniform warming of the tropical Pacific, while the observations show little warming. There are a number of other regional modeling problems.
Presenting the trends over the full term of the GISS data actually tends to make the models look as though they perform reasonably well. But when we break the observations and model outputs into the 4 periods shown in Figure 2, the models do not fare as well. In fact, the trend maps will help to show how poorly the models simulate observed temperature trends during the early cooling period (1880 to 1917), the early warming period (1917 to 1944), the mid-20th century flat temperature period (1944 to 1976) and the late warming period (1976 to 2012).
Pretty ambitious statement there...please post your points of repeated proof (one will do)
But here is a good starter to help develop a deeper understanding of the topic.
Please note that past estimates bound the most recent estimates...which is expected with larger sample sizes (since it reduces variation confidence intervals are smaller).
RECENT WARMING PERIOD – 1976 TO 2012
Figure 3 compares the observed and modeled linear trends in global land plus sea surface temperature anomalies for the period of 1976 to 2012. The models have overestimated the warming by about 28%. The divergence between the models and the data in recent years is evident. It’s no wonder James Hansen, now retired from GISS, used to hope for another super El Niño.
Figure 4 compares the modeled and observed surface temperature trend maps for 1976 to 2012. The models show warming for all of the East Pacific, while the data indicates little warming to cooling there. For the western and central longitudes of the Pacific, the models fail to show the ENSO-related warming of the Kuroshio-Oyashio Extension (KOE) east of Japan and the warming in the South Pacific Convergence Zone (SPCZ) east of Australia. The models also underestimate the warming in the mid-to-high latitudes of the North Atlantic. Modeled land surface temperature anomaly trends also show very limited abilities on regional bases, but that’s not surprising since the models simulate the sea surface temperature trends so poorly.
What part of
"The models have overestimated the warming by about 28%. The divergence between the models and the data in recent years is evident."
was difficult to understand?
That's NOT an accurate prediction at all. See fig 3 above.
The graph posted above http://bobtisdale.files.wordpr...013/04/figure-34.png clearly demonstrated the 28% inaccurate over-prediction of warming by the modeling in the recent warming period, nothing else was implied.
Changing the averaging time frame doesn't change that inescapable conclusion. The models are wrong.
Pick a different time frame and the perspective shifts yet again. see graph on previous page
The current warming is not unusual, unprecedented nor alarming; the human contribution is small.
The amount of toxic pollution emitted by humans is huge and unprecedented and should be alarming. It's too bad that many are easily distracted from those real problems undeniably caused by humans.
Not that ambitious at all Rusty, like I said, just pick one of the projections of climate based on data puked out by a computer model and show me how accurate its been...
When you put variables that are not understood and that have been derived by hypothesis and theory in, guess what comes out? More of the same, not proven hard facts, hence all the debating.
I am not looking for a deeper understanding, understanding the function of a model and how data is utilized and created with one is a pretty basic concept... Your not seeing the forest due to all the trees... wink wink
Callum, Your putting words in my mouth, you have a comprehension problem read my post slowly and repeat it back to yourself, perhaps it will help with your comprehension.
I am not interested in your fishing expedition.
The example you requested is right there...your skating on thin ice my friend (must be the weather)
Who is skating?
Thats a report for the IPCC full of all kinds of inaccurate data produced by models, as yet to be proven inaccurate by the test of time, like the last one...
Actually, models don't produce data, they estimate parameters and effect size.
Remember the 95% confidence intervals overlap in all the IPCC reports and the variance is getting smaller...good modeling there.
Merry Christmas to you too.
LOL, thats funny.
Now your being silly
This graph can not be real can it? If it is then what more proof do people need that an increase in CO2 leads to an increase in temperature?
For those who are concerned about CO2 and warming, this
provides a good reality check to evaluate where the human produced CO2 is coming from.
For the most recent year tabulated , China produced 29% of the world's total human CO2 [most of that from toxic coal], the US produced 15% [about half from toxic coal] and if one adds 6% for India then those top three emitters produce half of the world's GHGs. Other countries contribute very little by comparison to the Gold and Silver winners in the world's GHG Olympics. Like #4 Russia 5.1%, #5 Japan 3.8%, #6 Germany 2.3% and #8 Canada 1.6%, then Mexico, Indonesia, and the UK each at 1.4%, next Saudi Arabia or Brazil at 1.3%, Australia at 1.2% and everyone else less than that.
So if you don't want to be contributing to the world's GHG soup don't buy stuff from the top emitters, buy locally produced products where possible.
Know where the energy and the products you consume comes from. Be an informed consumer, regardless of your beliefs.
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