Statistical analysis versus computer modeling

In summary, scientists have found that there is a strong statistical correlation between greenhouse gas emissions and temperature, but that does not mean that human activity is to blame for global warming.
  • #1
Johan de Vries
22
0
http://physicsworld.com/cws/article/news/30711

Also here

New statistical analysis confirms human role in climate change

The idea that global warming is caused by changes in solar output rather than human activity has been dealt a further blow by a new analysis of temperature, volcanic and solar-radiation data by a physicist in Germany. The research, carried out by Pablo Verdes from the Heidelberg Academy of Sciences in Germany, does not rely on climate models, which cannot account for all global-warming mechanisms. Instead, the work reveals a strong statistical link between rising temperatures and greenhouse gas emissions (Phys. Rev. Lett. 99 048501).

Most of the evidence for human-induced or “anthropogenic” climate change has come from climate models, which simulate the dynamics of the atmosphere using complex fluid-flow equations. Given inputs of temperature and other climate data from instruments and older proxy records, such as tree rings, these equations are solved numerically using short time increments.

Although all climate models indicate that the Earth’s temperature will continue to rise, some climate-change sceptics have suggested that the anthropogenic influences are exaggerated. For example, because the simulations divide the atmosphere into a 3D lattice with a coarse resolution, they cannot take into account the effects of clouds, which can both reduce or enhance warming.


Rather than trying to simulate the atmosphere as climate models do, Verdes has used statistics to assess man’s role in climate change.
 
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  • #2
Don't underestimate the skeptics and their capacity for denial.
 
  • #3
You do realize that statistics do not count as proof, they can only help indicate a possible solution which may or may not be correct?
Furthermore, 150 years (the reported time period of the statistical analysis) is a pathetically short time for testing a particular model. Try thousands or millions of years.
Lastly, the scientist who performed this analysis is not claiming that his report in any way is conclusive proof that anthropogenic global warming exists (atleast according to the news reports). All he said is that his report should “enrich the continuing debate on the future of our climate.”

There is a strong statistical correlation between the number of pirates in the world and the average temperature but that does not mean that the amount of pirates determines the average temperature of the world!

If statistics were so powerful, then scientists wouldn't spend their entire lives looking for explanations of natural phenomenon.
 
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  • #4
sid_galt said:
You do realize that statistics do not count as proof, they can only help indicate a possible solution which may or may not be correct?

That is true, however the significance of this is that an alternate approach supports the existing conclusions.

Furthermore, 150 years (the reported time period of the statistical analysis) is a pathetically short time for testing a particular model. Try thousands or millions of years.

This seems to ignore the nature of the evidence. The test was to identify a forcing function that agrees with the data over that span of time.

...Verdes used a theory known as nonlinear time-series analysis, whereby the existence of a slowly-varying driving force can be deduced without any knowledge of internal dynamics

If we have a forcing function that runs in 100 year cycles, for example, it would not be necessary to look at millions of years of data to see it. Also, if we have an irregular function that has uniquely identifiable characteristics, it might easily be identified when compared to the observed variations in the data.

There is a strong statistical correlation between the number of pirates in the world and the average temperature but that does not mean that the amount of pirates determines the average temperature of the world!

Oh really?
http://en.wikipedia.org/wiki/Image:1000_Year_Temperature_Comparison.png
http://img523.imageshack.us/img523/4919/piratesarecooluw5.jpg

Conversely
Verdes found that the driving-force profile that produced the best fit almost exactly matched records of greenhouse gas and aerosol emissions (see Driving force).

Not only do I doubt that the pirates graph is accurate, there is serious doubt that the profile would match the required forcing function. :wink:

Oh yes, many scientists and engineers use statistics successfully on a daily basis.
 
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  • #5
Math and Global Warming

Math always has a place in the universe and vice versa. If anything can be predicted without direct physical observation of the factors involved, then math can do it. Of course, anything that is predicted by math remains as theory unless proven physically. The same goes for statistical data that can lead to conclusions to possible outcomes.

I believe that math can and does give a fairly accurate way of predicting things if the factors involved remain constant for a period of time beyond the expected outcome. However, there are likely too many variables in this global warming phenomenon that are unaccounted for.

You might want to read about this item from TheNewsRoom on how math is used to assess climate change: http://www.thenewsroom.com/details/561532?c_id=wom-bc-ar

I'm writing from TheScienceDesk at TheNewsRoom. We have a group of users into global warming who have found great news from us which they have used for their sites. If you're interested, email mail jtowns@voxant.com. We'll be glad to entertain your inquiries.

- Alvin from TheScienceDesk at TheNewsRoom.com
 
  • #6
It's proven scientific fact that the temperature has been on a rising trend. It is proven scientific fact that CO2 levels have increased in the atmosphere. We don't need some complex statistical analysis to see these things. The debate isn't over whether or not a global warming trend exists or whether or not humans have led to an increase in CO2 in the atmosphere, etc. the debate is over whether or not this issue even matters.

There is a strong statistical correlation between the number of pirates in the world and the average temperature but that does not mean that the amount of pirates determines the average temperature of the world!

Yes, quite absurd. Everyone knows that the average temperature of the world is determined mainly by the mating patterns of penguins.
 
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  • #7
Use of Debates

Renge's right. Debates are beside the point. Whether or not global warming is caused by natural fluctuations or anthropogenic, there's still the fact that weather patterns are changing and ice is melting. Global warming aside, I still would want the pumping of carbon dioxide into the air, along with other hydrocarbon emissions that constitute air pollution, to cease. I also would want the harvesting of forest trees stopped and that people just resort to tree farming. I'd rather have a world with clean air and trees than one that's foul and bare.

Interestingly, here's news item link from the Investor's Business Daily, courtesy of TheNewsRoom about trees and global warming from the critic's point of view:
http://www.thenewsroom.com/details/219407?c_id=wom-bc-ar

- Alvin from TheScienceDesk at TheNewsRoom.com
 

What is the difference between statistical analysis and computer modeling?

Statistical analysis involves the use of mathematical calculations and techniques to analyze and interpret data in order to make conclusions. It is typically used to identify patterns, trends, and relationships within a dataset. On the other hand, computer modeling involves the creation of computer programs or simulations to represent real-life systems or processes. It allows for the prediction or estimation of outcomes based on input parameters and assumptions.

Which method is more accurate, statistical analysis or computer modeling?

Both methods have their own strengths and limitations. Statistical analysis is based on real data and can provide precise and unbiased results if the data is collected and analyzed correctly. However, it is limited to the data that is available and may not always be able to accurately predict future outcomes. Computer modeling, on the other hand, allows for the manipulation of variables and can provide insights into complex systems. However, it relies on assumptions and may not always reflect real-world scenarios accurately.

When should I use statistical analysis and when should I use computer modeling?

The choice between statistical analysis and computer modeling depends on the research question and the type of data available. Statistical analysis is best suited for analyzing and interpreting existing data, while computer modeling is useful for predicting outcomes and understanding complex systems. In some cases, a combination of both methods may be used to get a more comprehensive understanding of the data and its implications.

What are the potential drawbacks of using statistical analysis?

One of the main drawbacks of statistical analysis is that it requires a large amount of data to be accurate. In addition, the results may be influenced by outliers or biased data. It also assumes that the data follows a specific distribution, which may not always be the case. Furthermore, statistical analysis cannot account for all variables and may not be able to capture the full complexity of a system.

What are the benefits of using computer modeling?

Computer modeling allows for the manipulation of variables and can provide insights into complex systems that may be difficult to study in real life. It also allows for the testing of different scenarios and parameters, which can help in decision-making and planning. Additionally, computer modeling can save time and resources compared to conducting experiments in real life. It also provides a way to visualize and communicate complex data and concepts to a wider audience.

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