One of these days I'm going to have to sit you folks down and teach you about lube.Yes. The IFQ -- International Fapping Quotient -- is at unprecedented levels.
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One of these days I'm going to have to sit you folks down and teach you about lube.Yes. The IFQ -- International Fapping Quotient -- is at unprecedented levels.
In my case, it isn't that I'm not listening to them; it's that they're talking about one thing and I'm trying to talk about another. This has happened before. It is very frustrating to me, and I'm sure it is frustrating to them, as well, if they truly don't realize we're talking about separate issues.The agenda, then, is politically expedient? I've been here a long time and Joe and FSUreed are the smartest people on this subject by far. Why won't you listen to them? What motive do they have? Are they running for office? Or are they telling you, quite simply, that as a species we are ruining the planet, and must change? That's the explain like I'm five part. Why do you refuse to listen to people who have spent their lives studying it? If a guy comes over and fixes your computer, would you argue about processors? No, because you have no idea how it works, but have a lot of ideas about it should work. I don't understand that mentality and probably never will. You specifically seem like the "I got mine, screw everyone else" crowd. Reexamine your religion and morality. I'm an atheist and volunteer for animals in need. I don't get paid for it. I do it because I have the time and they need the help. According to you, they should just die.
Does "model response error" mean "incorrect assumptions used in designing the model"?
Ice Free Arctic predictions:
http://www.theguardian.com/environment/earth-insight/2013/dec/09/us-navy-arctic-sea-ice-2016-melt
I manage a team of 16 people that performs analytics, includes data scientists, and builds predictive analytics models using tools like SAS. My background is in Aerospace Engineering, not Climate Science, but I understand the scientific method, can understand the general climate principles, and have an appreciation for the many different disciplines in play here (statistics; climate; geology; etc).
Given that background, but without seeing the actual models, my sense is that:
1. The models have tons of assumptions in them, and quite frankly I've yet to see a sensitivity analysis (Monte Carlo, et al) done to rank order the assumptions from most sensitive (likely the Feedback Multiplier, as discussed above, but also aerosols and so forth) to least sensitive so we can focus our attention on those at the top. A specific answer to your question can be found at this link, and says "The discrepancy between simulated and observed trends...between 1998 and 2012...can be explained in part by....a tendency for the models to simulate a stronger response to C02 than is consistent with observations", which is the direct response to C02 increases, but it goes on to talk about the Feedback Multiplier caused by a water vapor assumption as well with "Another possible source of model error is the representation of water vapor in the upper atmosphere". This is exactly what I'm talking about in this thread.
https://books.google.com/books?id=jn4mCAAAQBAJ&pg=PA62&lpg=PA62&dq="model+response+error"&source=bl&ots=-UyLeir9Bc&sig=y1gez3OO7MLosKrIVDktRA7EDE0&hl=en&sa=X&ei=_7yKVZ6EJoXzsAXa_JqABQ&ved=0CEkQ6AEwBw#v=onepage&q="model response error"&f=false
2. The scientific method requires you to make a prediction, and then measure to see if it came true in order to corroborate your scientific theory. The climate models are the prediction, but they have failed to accurately predict the last 15 years with reasonable enough accuracy, and therefore something is wrong with the theory/hypothesis - and the most likely culprit is the Feedbacks imo. Again - most definitely not settled science.
3. For all the assumed complexity of the climate models, the results of a few of the key models used by the IPCC can be replicated using very simple equations, indicating they are HEAVILY biased towards C02 and do not include much else that matters (like nature). I've found this type of "black box" analysis very interesting:
http://wattsupwiththat.com/2011/01/17/zero-point-three-times-the-forcing/
Again - just matching historical data by adjusting assumptions like aerosols et al does not make it a good predictive model. That's just goofy.
Yes. The IFQ -- International Fapping Quotient -- is at unprecedented levels.
Climate change was invented by Al Gore and his ilk
I understand that they are constantly "tuning" the models (as they should, and good to know they are starting to incorporate natural factors which should have been in there from the beginning), but every time they do it they are updating their hypothesis and the clock restarts on testing a prediction to confirm whether their new hypothesis (model) is accurate enough to drive policy decisions.
I can accept that. What I have trouble accepting is that Dan is automatically wrong because 97% of scientists agree with Joe and the science is settled.You follow the previous post with this? It reminds me of Adam Corolla's bit about someone that gets their ass kicked in an argument but finishes w/ "yeah, but still . . . ". Joe and Dan's debate demonstrate this issue is (frankly) too complicated for public consumption.
But understand that there is a DIFFERENCE between adjusting an aerosol 'forcing' constant or factor vs. adjusting the AMOUNT that is observationally seen vs. what was surmised MIGHT be there in 2 year or 5 years, looking forward.
You can have an absolutely PERFECT model for the climate, but if the solar TSI changes, or the aerosol concentration changes, or CO2 levels emitting divert from your expected curve, or the PDO reverts to a long El Nino or La Nina phase, you WILL NOT get an output which matches observations. That is not because 'the model is incorrect'; that is because forward-looking estimations/guesses you had to use as annually (or monthly) adjusted inputs (while the model is running, it uses graphical lookup tables, not fixed values for these inputs). So, when the observed and measured values for those 'input' curves is different than your 'best guess', you update your model the next year with more accurate input curves.
No one is able to predict what all of those inputs will look like, so they use variations on them, ALONG WITH tweaks to forcing/feedback mechanisms (like you guys do with your modeling methods) to generate the large scatterplots of runs you see in things like IPCC reports and papers. And they simply make the 'best guess' that an actual scenario for those uncontrolled variables is close enough to one or more of their model runs to 'encapsulate' reality. That is why you see much of the scatter - it is NOT just due to model 'inaccuracy', it is to try and see how any and all of the scenarios of TSI, PDO, aerosols, CO2 levels make the 'best guess' window.
It is not like these 'variable inputs' are just random numbers, either. They have acceptable and expected ranges they will likely follow.
Now, when you are CHANGING the sensitivities of forcings/feedbacks, THAT is a different issue, and that DOES directly relate to the 'accuracy' and predictability of the models. But it is important to not lump it all into one 'the models are inaccurate' bucket, because they are completely different sources of error, and one is simply not error it is random/natural variability.
A lot of that makes sense Joe and I think we would agree on much of it. They may be running a lot of models just to try different variants, and then adjusting as they go based on observations as they come in, but from a Scientific method standpoint if you want to test a Hypothesis (ie: this is how it works) you have to pick one set of assumptions and ride them out - and if the predictions are not true (ie: not accurate enough to be useful) then you can adjust the hypothesis and try again.
What app are you using? I guarantee you've dropped more turds than that around here.My computer just gave me a prediction. It said I will poop twice today and it is a result of global warming.
What app are you using? I guarantee you've dropped more turds than that around here.