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How global computer models work, and how they are tested for accuracy...
A climate model is actually a collection of models - typically an atmosphere model, an ocean model, a land model, and a sea ice model. Some GCMs split up the sub-models (let's call them components) a bit differently, but that's the most common arrangement.
So how do we know the models are working? Should we trust the predictions they make for the future? It's not reasonable to wait for a hundred years to see if the predictions come true, so scientists have come up with a different test: tell the models to predict the past. For example, give the model the observed conditions of the year 1900, run it forward to 2000, and see if the climate it recreates matches up with observations from the real world.
This 20th-century run is one of many standard tests to verify that a GCM can accurately mimic the real world. It's also common to recreate the last ice age, and compare the output to data from ice cores.
History has shown us that when climate models make mistakes, they tend to be too stable, and underestimate the potential for abrupt changes. Take the Arctic sea ice: just a few years ago, GCMs were predicting it would completely melt around 2100. Now, the estimate has been revised to 2030, as the ice melts faster than anyone anticipated: How do Climate Models Work?
How global computer models work, and how they are tested for accuracy...
A climate model is actually a collection of models - typically an atmosphere model, an ocean model, a land model, and a sea ice model. Some GCMs split up the sub-models (let's call them components) a bit differently, but that's the most common arrangement.
So how do we know the models are working? Should we trust the predictions they make for the future? It's not reasonable to wait for a hundred years to see if the predictions come true, so scientists have come up with a different test: tell the models to predict the past. For example, give the model the observed conditions of the year 1900, run it forward to 2000, and see if the climate it recreates matches up with observations from the real world.
This 20th-century run is one of many standard tests to verify that a GCM can accurately mimic the real world. It's also common to recreate the last ice age, and compare the output to data from ice cores.
History has shown us that when climate models make mistakes, they tend to be too stable, and underestimate the potential for abrupt changes. Take the Arctic sea ice: just a few years ago, GCMs were predicting it would completely melt around 2100. Now, the estimate has been revised to 2030, as the ice melts faster than anyone anticipated: How do Climate Models Work?
What happened when they plugged the ice cores into the model? Crash and burn. Error of 0.9C in 100 years. Oops.
. Take the Arctic sea ice: just a few years ago, GCMs were predicting it would completely melt around 2100. Now, the estimate has been revised to 2030, as the ice melts faster than anyone anticipated: How do Climate Models Work?
ok and????
no one is questioning or denying climate change...as it has happened many many times
but its NOT man made...its natural
a warmer earth would be better..longer and better growing seasons
no one is questioning or denying climate change...as it has happened many many times
but its NOT man made...its natural
a warmer earth would be better..longer and better growing seasons
no more freezing to death
I say lets get rid of all the freaking snow...
No, it is not natural this time, and this is why....A natural cycle requires a forcing, and no known forcing exists that fits the observed warming - except anthropogenic greenhouse gases.
Listen, you are so quick to put labels on people and posts that do not fit with your agenda . I said the weather has been breaking all records , everywhere. So soon you forget this Summer, and the last 3 winters which were much warmer than normal We normally get a lot of snow, sometimes 300 inches, not happened for several winters so, when I say that's happened, well it was . I do not make any conclusions, just stating a fact in this area near the Canadian border. We get our weather directly from the NWT, so what goes on in Yellowknife will come to us in short order.
Now when I talk about air and water , I do know of what I say. I spent over 40 years in logistics distributing environmental equip. I have seen my business go up and down, a lot blamed on politics . I am aware of many Coal fired power plants that remain without proper clean up.I think these things are well kown, just what's wrong with other than what I have experienced ?
I make no conclusions or no long term effects , just what's public knowledge I would like to know your reason for dismissing 40 years of experience. I could just as easy talk about Alaska and the Yukon. They got hammered this past winter. We have a gold claim in the Yukon, this year everyone had to be lifted in by air because of the long winter with more than normal snow. It was a late summer with all the access roads impassable.
We still are distributing the power plant clean up of their smokestacks.. So many have bought a lot of time, when now they have run out of time.. The claim is that the cost could be greater than the value of some Plants, or so they say. Same goes for the nuke Plants here in Michigan, way too many spent fuel rods and no place to put them..... I have said more than intended, so I exit Stage left. The show goes on with out your "facts" , or mine. I just wanted everyone to know what's going on in the field., been there done that many times.
That is why I responded as I did. We have not being breaking "all" records "everywhere". That is a sensationalized claim and why I see no point in even attending to your comments. You start off with a false premise.
If I am speculating as if it was conclusive then you are doing the exact same thing.
???
I am speculating that it is inconclusive? That makes no sense at all. Either there is a consistency that validates a given assumption or there is not. There is not, this is a fact as models are not conclusive means of validation. They are not a process of the scientific method. So, when I take the position that you can't conclude on that because you can not properly validate the position through scientific process, I am right... and you are wrong. I am not speculating, I am stating a fact. /boggle
Quote:
Originally Posted by dv1033
Ah, now you are modifying your defintion to mostly unknowns. LOLZ. You do realize models can analyze the interaction between knowns?
Um, yes, but without accounting for the unknowns (ie you have no idea how they work or what their contribution is because you can not isolate them), then you can not state that such interaction (ie the correlation of signals) is what you think it is, noise, or some other unknown. this isn't an issue of having all the variables except one accounted for and you pop it into a nifty little equation solver to come up with the answer. As the unknowns are increased, so is the lack of certainty of their interactions and if you have read anything about models, there is A TON of unknowns.
Quote:
Originally Posted by dv1033
My goodness, you've already tried this Drake Equation argument before. You really need to take your Namenda to help with memory. Remeber the Drake Equation is used to estimate the number of technological civilizations in the milky way galaxy.
Wow, did you google that really quick so you could sound like you know something? The point was, the entire equation is based on unknowns. You can not get something out of nothing which is why the equation is just nonsense pseudoscience. In relation to the models we were talking about, it points out the problem with having numerous unknown variables and then thinking because you see some correlation in the signal, it somehow validates it as your assumption. This defies proper scientific process as "correlation != causation".
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Originally Posted by dv1033
Blah blah blah. So going back to your well used Drake Equation, that equation is based on the BEST INFORMATION AVAILABLE. That's what models use, the best information available. Therefore, the Drake Equation gives us the best answer possible with the best information available.
Stop starting with the premise that models are based on unknowns, that is false.
It is based on NO information! It is based on stacking one assumption on top of another. Stop being obtuse.
Quote:
Originally Posted by dv1033
Why do you assume that only models are used to explore and study climate change?
I don't assume, but the basis of CAGW is entirely based on models. I didn't state only models are used, where did you get that idea? Oh wait... fallacy. NM.
Quote:
Originally Posted by dv1033
No I'm not arguing that. You just can't comprehend how models are used in today's science.
I can't? I have a degree in Computer Science (math/science option) and a degree in mathematics (applied). Tell me again now how I just can't comprehend?
Quote:
Originally Posted by dv1033
Then how do you validate to your standard that humans are causing climate change then? Or not causing it.
Your ignorance of scientific process is astounding. It doesn't work like that. What you are purposing is a fallacy, that you make a claim and I have to prove it wrong and until I do so, your claim is valid. That is absurd and such a belief would fail you out of any fist semester physics course.
The scientific method is a process of observation, then trying to come up with an explanation of what is happening (hypothesis). That hypothesis is then tested, if it passes the tests and does not fail (or if the failure can be accounted for, identified and shows consistently that it causes the fail, then it is passed to review and replication by another. If they are able to achieve the same passing results and consistency, then that explanation is considered to be a correct explanation of the observation. If anytime it fails and it can not be determined exactly why it failed, then the explanation is scrapped and a new one is developed to which the process is repeated until such is achieved.
The models can not explain why they fail. they can not account for the various divergence in their results and so, the assumption (ie the explanation to which the model designer programs the model to follow) must be changed.
You ask me to validate my position, but you fail to understand that your inability to validate yours, validates mine. When you can properly validate your claims concerning CAGW through proper scientific process, then my position will be invalid. Though my position is not based on a movement or an entirety, it is based on you properly establishing your position through scientific process. Until you do so, your inability to validate your position will continue to validate mine.
This is not a difficult concept, this used to be taught in first year physics courses. Heck, I think even the non-calc conceptual courses cover this if they aren't a waste of effort. Even some undergrad mathematics courses cover this concept, how is it that you have no understanding of it?
Hmm, I looked up your degree in bio chemistry and I can not see much mathematics and it appears your physics courses are specialized with less math than the traditional physics courses. It all makes sense now.
Um, yes, but without accounting for the unknowns (ie you have no idea how they work or what their contribution is because you can not isolate them), then you can not state that such interaction (ie the correlation of signals) is what you think it is, noise, or some other unknown. this isn't an issue of having all the variables except one accounted for and you pop it into a nifty little equation solver to come up with the answer. As the unknowns are increased, so is the lack of certainty of their interactions and if you have read anything about models, there is A TON of unknowns.
What unknowns are missing?
Quote:
I don't assume, but the basis of CAGW is entirely based on models. I didn't state only models are used, where did you get that idea? Oh wait... fallacy. NM.
Really? Where do you get that idea from? If you say an extreme statement, you should back it up with evidence.
Quote:
I can't? I have a degree in Computer Science (math/science option) and a degree in mathematics (applied). Tell me again now how I just can't comprehend?
Neither degree is actually science, though.
Quote:
Your ignorance of scientific process is astounding. It doesn't work like that. What you are purposing is a fallacy, that you make a claim and I have to prove it wrong and until I do so, your claim is valid. That is absurd and such a belief would fail you out of any fist semester physics course.
Vague generalities about the scientific process are good, but without applying them to the specific subject the discussion is rather meaningless. You give statement (often not backed up), why should I believe it?
The list is numerous and it depends on whatever specific aspect you are evaluating as to the number of assumptions they make about its interaction and influence.
Quote:
Originally Posted by nei
Really? Where do you get that idea from? If you say an extreme statement, you should back it up with evidence.
What would you like me to back up?
Quote:
Originally Posted by nei
Neither degree is actually science, though.
Computer science, not in the traditional science, no. Mathematics, well... try doing complex physics without it. Considering we are talking about models which rely heavily on both, I would say that saying I don't "comprehend" the models would be a rather silly statement. In fact, note that the problems with Hansen's models, the problems with the hockey stick and the numerous issues with many other areas of the field have been primarily focused on the poor methodology of mathematical evaluation. Also note the poster was going on about how I don't understand and yet his degree has very little if any mathematics and he is arguing with me over mathematical relevance. Seriously Nei, your response doesn't seem to serve any meaningful point.
Quote:
Originally Posted by nei
Vague generalities about the scientific process are good, but without applying them to the specific subject the discussion is rather meaningless. You give statement (often not backed up), why should I believe it?
I don't ask for belief. Are you objecting to the scientific method? Are you saying that scientific process does not require verification, validation and replication? Feel free to step in and make your position. There was no need to cite the scientific method, it is common knowledge to anyone who proclaims themselves to be educated.
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