Tree rings are a good place to start thinking about how climate researchers get information about past climates. In certain cases, trees can live for many hundreds of years and in an extraordinary case, like the bristlecone pine, thousands of years! Each year trees add growth rings, which can indicate what sort of growing season the tree experienced. Interestingly these rings are more than a temperature indicator, they also tell the researcher about moisture and cloudiness as well. You can refer to some editor on the site :www. scirp.org or refer to journal articles and concieve you theory.

Not very well apparently.

I'm sure you've heard the term "hide the decline", people adamant about mans role in global warming would love to make this issue about deniers claiming scientist are hiding a decline in temperature, because it makes people look stupid when you point out that hide the decline refers to a "divergence problem". Then you can move on and claim the discussion is over, stupid deniers are claiming we are hiding something when all we did was stop using tree ring data because temperature is rising but tree ring proxies say temperature is declining. Well doesn't that put past Temperature reconstruction into question, I mean really you know more about the actual environment now and can't get it right, how do you know you've got it right when most if not all the variables have to be built from reconstructed data?

The divergence problem shows that there are problems determinging temperature in the present using tree rings which to any sane and rational person would put into question the ability to use tree rings to reconstruct past temperature.

There are at least three basic issues that underlie the development of reliable dendroclimatic reconstructions. The first involves stand and sample selection. The second concerns the accurate assignment of calendar dates to a tree-ring chronology. The third set of issues involves the basic numerical transformations of tree-ring series deemed necessary in view of current biological knowledge and the requirements of statistical tests.

The goal in sampling is to obtain tree-ring series with a high degree of common variation that is strongly driven by climate. Strong common variance in trees is frequently found at elevational extremes, often near the lower forest border or upper treeline limits of a species. Moisture related signals are usually found in chronologies from lower forest border settings. Large spatial networks of chronologies from upper treeline and high latitudes (e.g., the sub-arctic) often contain seasonal or annual temperature signals.

Accurately dated chronologies are developed through the process of cross-dating. Confidence in this accuracy is gained in part (1) by experience, (2) by applying multiple laboratory procedures, and (3) by building a repertoire of tree-ring chronologies on a regional scale that evidence similar and synchronous annual changes due to commonly recorded climate signals.

The third set of issues involves the removal of non-stationary variation from individual series that are related to non-climatic factors such as biological growth (aging), competition, and injury. Following this “standardization” process, further transformation may be required if significant autocorrelation (i.e., persistence) remains in the series. This is usually accomplished through ARMA (autoregressive-moving average) modeling procedures.

Linear regression procedures are used to develop (calibrate) statistical models that describe the climate-tree growth relationship. Regression model validation procedures (verification) to determine the consistency of the relationship over the period of instrumental records include (1) establishing a climate-tree growth model based on a subset of data, then (2) if the model proves satisfactory in terms of standard diagnostic regression statistics, (3) a reconstruction of the climate variable is computed over the remaining set of data. Several parametric and nonparametric statistical tests are used to evaluate the quality of a reconstruction.

Finally, all available data are included in a regression analysis to develop the final model for reconstruction. This is done to insure that the most complete range of sample covariance is included in model formulation.

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MIKE L --

Thanks for the most excellent presentation of Denier scientific illiteracy and intellectual buffoonery - but we already have enough examples.

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Moe --

>> because it makes people look stupid when you point out that hide the decline refers to a "divergence problem".<<

When "you" point out? The divergence problem was identified by tree-ring scientists and has been discussed in scientific publications for 20 years. Deniers have never pointed out anything significant that climate scientists had not already reported.

>>The divergence problem shows that there are problems determinging temperature in the present using tree rings which to any sane and rational person would put into question the ability to use tree rings to reconstruct past temperature.<<

Note the term "divergence." That means a departure from a period of coherence with the instrumental record.

On the other hand, I have never been a big fan of tree-ring based temperature reconstructions - even before the divergence problem was identified.

Laddie, don't say "off of". It's bad English. In any case, you should have said "based on".

Thin ring means dry year , thick one wet year .

How they and Micheal Mann gets temperatures out that probably Voodoo or making

it up .

You got to have those government funds to live on .

I am taking an Honors Research Course and my research question is, "Can dendroclimatology confirm 20th century global warming trends?" I'm at the point where I understand tree rings and have multiple journal articles with references to temperature anomalies based off of tree ring data. I have a presentation Tuesday and I'd like to be able to explain how scientists go from the tree ring to making graphs of estimated temperature anomalies. Any help is greatly appreciated.