Gary Strand (15:44:41) :

hotrod (14:12:57) :
“The easiest metric to use would be to show they perform better in a statistically significant degree from a naive forecast that simply forecasts more of the same we had last year or the last few years.”

As I asked Kurt, have you exploited the CMIP3 climate model data archive versus your favorite obs data and made this examination?

And just why should I do someone else’s job? It is up to the model developers to show they have a clue what is going on, not the people that are paying them to do the job.

If they care so little about the validity of their product that they will not even invest a small fraction of their time showing it has value why should I pay the slightest attention to their projections.

Do you think it is the shoppers job to verify prices in a store?
Do you think it is the patients job to certify his doctors?
Do you think it is the buyers job to crash test cars?

Larry

As I asked Kurt, have you exploited the CMIP3 climate model data archive versus your favorite obs data and made this examination?

Have you done this test using the available data for the CMIP3 archive for the model runs for the 20th century compared against your favorite observational data, for surface temperature?

That would be an interesting test.

Gary Strand (05:35:37) :

To the folks requesting validation of a climate model before they accept them as reasonable tools – what are your metrics, and why?

The National Weather Service recognizes the need to formally validate flood forecasts due to their impact on public planning and expenditures.

http://www.nws.noaa.gov/oh/rfcdev/docs/Final_Verification_Report.pdf

Why should we not expect a similar formal review of the climate model projections?
Can you give any rational that supports the idea that a similar organized effort to evaluate and improve climate models in unwarranted?

Public costs incurred due to faulty flood forecasts would be counted in the multimillion dollar range. Public costs due to faulty climate forecasts would tally in the hundreds of billions of dollars to multiple trillion dollar range.

The Nuclear Regulatory Commission requires formal evaluation of a nuclear plant and the possible impact of its maximum credible accident, and formal testing and evaluation of the adequacy of emergency response planning due to the high public costs and impacts a nuclear plant accident would have.

The EPA requires similar impact studies on major industrial plants that might impact the public, and emergency response activities in communities.

It is the climate modeling community that has the burden of proof to show why their models should not be held to similar standards of formal validation and review.
To base public policy on untested computer models in pure idiocy! They are either competent and useful, or if incompetent and harmful, or statistically meaningless. Until we know which of those 3 options is true, given the costs involved we should assume they are useless or harmful (first do no harm).

The easiest metric to use would be to show they perform better in a statistically significant degree from a naive forecast that simply forecasts more of the same we had last year or the last few years.

There are two simple variations of this, one is that the future conditions will be the same as the historical climatic variation (for example will fall within some error of the 1971-2000 average).

The other is persistence — ie that the future conditions will be essentially identical to today’s conditions.

To have merit the model projection would have to beat both those metrics by a statistically significant margin.

http://www.forecastadvisor.com/blog/

If their forecasts (projections) are within the range of historical natural variation, then they also need to prove that they are predicting something that would not have happened without increasing CO2.

If the climate change forecast makes some projection about sea surface temperature rise over the next century for example, then unless they can show a scientifically valid reason to the contrary, they should be tested against 1/10 that rise over 10 years. Likewise on other major features of their forecasts. If they are scientifically valid, the authors of the model should be able to state ahead of time what the error bars are for their bench marks on key events and the window of performance they must fly through to be meaningful.

Larry

To the folks requesting validation of a climate model before they accept them as reasonable tools – what are your metrics, and why?”

As of today, there are no metrics by which models can be validated. That’s why many don’t believe they can be relied upon. Perhaps after about 75 years or so, a computer model in existence today could be validated with respect to a forecast in a climate variable (e.g., temperature) If, say, it’s running 10 year mean predicted temperatures were within 95% of the measured running 10-year mean of temperarures over 70 of those 75 years. That woud be impressive, but I would add that important part is that you collect empirically the metrics to quantify how reliable the model is. If it turned out to be within 75% of the actual 10-year mean in 70 of 75 years, you still would have an objective way of measuring how reliable of a tool the model is. But right now, there is nothing.

I understand you’re an empiricist, not a rationalist.

When I said published, I meant in a journal, not a website. After all, if you can convincingly show that “Arrhenius was wrong also regarding his underlying premise because the carbon dioxide would work as a coolant if its mass in the atmosphere increases and the load of energy incoming to the Earth doesn’t increases, i.e. if the intensity of solar radiation doesn’t increase”, then you’re going to overturn more than a century of understanding.

There is not need of writing an article about Arrhenius’ mistakes; take any book on heat transfer and you’ll find those errors. If the source of heat doesn’t change its intensity, and the mass of carbon dioxide increases, the carbon dioxide will act as a coolant:

dT = q / m (Cp)

It’s a basic formula for calculating the change of temperature caused by any substance.

When I said published, I meant in a journal, not a website. After all, if you can convincingly show that “Arrhenius was wrong also regarding his underlying premise because the carbon dioxide would work as a coolant if its mass in the atmosphere increases and the load of energy incoming to the Earth doesn’t increases, i.e. if the intensity of solar radiation doesn’t increase”, then you’re going to overturn more than a century of understanding.

Your ideas have been published, then – in what journal(s)?

Nope, they’re not ideas; I didn’t invented natural processes. They’re what scientists have observed in nature and experimented in labs, when it is possible. AGW is an idea.

Every article submitted, didactic, theoretical or informative, is peer reviewed for its publication in Biocab.org. Some of my articles have been published by Universities; for example, Astrobiology, Heat Transfer, Heat Stored by Atmospheric Gases, The Abiotic Origin of Life, etc.

20 years minimum.

Your ideas have been published, then – in what journal(s)?