Saturday, January 16, 2010

Climatology 2 - Response #1

Nice post. Interesting. I'll look into it. Here are a few notes after a quick (NOT in depth) review of the IPCC chapter 8.pdf you referenced...

1. “Some models used for projections of tropical cyclone changes can simulate successfully the observed frequency and distribution of tropical cyclones.”

Really? Then why have they missed the boat in the number and severity of Atlantic hurricanes for the last several years? Or are cyclones and hurricanes really that different (from a climate model perspective)?

2. “The possibility that metrics based on observations might be used to constrain model projections for climate change has been explored for the first time... a proven set of model metrics that might be used to narrow the range of plausible climate projections has yet to be developed.”

Am I reading this wrong - aren't they admitting they DO NOT use Real World observations to refine the models? If they haven't been doing this (i.e., “explored for the first time”), just what criteria have they been used to validate the models? And just who defines what is “plausible”?

3. “Eighteen modelling groups performed a set of coordinated, standard experiments, and the resulting model output, analysed by hundreds of researchers worldwide, forms the basis for much of the current IPCC assessment of model results.”

What's wrong with just comparing the model predictions against observed Real World data? And as for noting it was reviewed by "hundreds", how many folks does it take to disprove a theory? (answer: ONE) Were these folks TRYING to find problems, or looking justify the conclusion?

4. “The response to global warming of deep convective clouds is also a substantial source of uncertainty in projections... and it is not yet possible to determine which estimates of the climate change cloud feedbacks are the most reliable.”

Doesn't this say they DO NOT fully understand - and the models do not agree on - what they admit is a key component of accurate climate change prediction?

5. [section]

This appears to be a caveat claiming that if there are differences between the models and observations, the differences are 'insignificant' and can be ignored. It also explicitly avoids doing one of the tests I suggested, e.g., predict the 20th century based on the preceding 500 years of raw data. Is that such a bad idea? Why?

* * * * *

It's a long report, but I'll continue looking in depth - I've looked at others from IPCC and was not impressed with the science, but was stunned at the numerous justifications for why I should accept the conclusions anyway.

The graph you supplied is impressive, but I don't see a disclosure on where the models got their raw data, e.g., if you're predicting 1965 based on 1964 (or 1920!) measurements, that's one thing. But to 'simulate' 1965 based on 'estimates' is something completely different. To properly evaluate the process that defines where you finished, you need to know precisely where you started.

*sigh* I cannot concede your point (yet), but I am open to the idea. Caveat: I must admit that - given the nature and scope of the manipulated data by CRU - I have doubts about the accuracy of models used by the IPCC report, simply because the integrity of the DATA is now in question. And I'm less concerned about the content of the CRU emails than I am about the accuracy of the raw data that has been made available to researchers. My simplistic review of source code segments *clearly* shows the input to the underlying model code was 'tweaked' in order to generate a specific result. Not good.

BTW - According to the IPCC, carbon dioxide causes 1.1 degress C of warming if it DOUBLES. The real key to defining the cause of climate change is feedback based on water (vapor) - and as I pointed out in #4 above, they admit they don't have a good handle on it.

More to come.

- Steve


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  2. *sigh* I guess I was unclear on what I constitute as an indication of 'accuracy'.

    The graph clearly shows a relationship between the models and observed measurements. There, I said it.

    But is the graph relevant? What starting data was used? Are those measurements authentic? (There is a REAL problem with the East Anglia data.) A good model can be 'accurate' but still be ultimately useless.

    Second, where is the base level for the input data compared to the prediction range? It's easier to predict next year based on last year's data. But to predict conditions 100 years from now, your model should ONLY use the data from over 100 years ago to predict conditions NOW... THAT is what I mean by accuracy: define the data range, predict the future, and compare the prediction against Real World. Is that what the IPCC did? I don't think so.

    Third, the graph has some 'accuracy' for predicting temperature. But, the AGW theory is very specific on man-made CO2 being the culprit in warming. Global CO2 levels are being monitored very closely and we have slowed the rate of increase over the last decade, but temperatures are not tracking along. A key component - some say THE KEY component - of AGW is that CO2 is a LEADING indicator of temperature rise: i.e., CO2 levels go up, followed by temperature and controlling man-made CO2 levels will positively affect global temperature. We all know that premise directly contradicts the geological record (CO2 is a TRAILING indicator if any). The AGW theory (and models) better be able to accurately explain CO2 in the historical record for the model to be relevant.

    Fourth, remember that just because two events happen within the same time frame does NOT mean one 'causes' the other. *BY ANALOGY* - I have a study which compares the rate of increase in heroin addiction against the relative numbers of mothers who breast-feed their children. A graph shows ups and downs over years, from societal pressures and desires. The graph implicates human actions - choosing to breast feed as opposed to using manufactured baby formula - in a cause-effect relationship. I provide peer-reviewed articles by respected researchers around the world who validate the data. There is no opposing mechanism defined by those who disagree with me. Following in the footsteps of the IPCC, I conclude that mother's milk leads to drug addiction and propose that a world-wide organization be set up to control and monitor such: We need to rigidly enforce regulations on people in industrialized nations while allowing Third World mothers to continue as before until a transfer of wealth - distributed 'fairly' by current regimes - provide 'poorer' people with access to 'proper' baby nutrition... Yes, yes, I drove off the road there with the absurd aspects, but you see my point.

    Fifth, there are published graphs which show the IPCC predictions of temperature - based on the same pre-2000 models you cited - for the last decade, 2000-2009, predicting RISE in temperature. In fact, measurements show the trend going DOWN. This is happening in spite of the fact that CO2 levels continued to rise (although not as fast) during the period. An obvious conclusion is: (1) there is more to temperature ranges than CO2 level, (2) the models don't include it, and (3) they completely MISSED predicting global temperatures just 10 years down the road.

    HOWEVER - I can say, YES, the IPCC appears to have some nice models. But, in my recent post, I pointed out situations where *my* models were similarly accurate, but STILL not able to yield a CORRECT conclusion. I cannot say the IPCC models cited are relevant in supporting the IPCC conclusion on CO2. Saying the same thing over and over don't make it True. But those graphs are Very Pretty.

    More to come.

    - Steve