Mark

Mark

The tendency in these observations posted to a blog are that they can be over simplistic and with that precaution in mind I will attempt to summarize what I find lacking in Wilson and company’s approach. The item with which I believe most here would agree is that Wilson and company do not strictly adhere to when applying the scienticfic method of inquiry is:

Another basic expectation is to document, archive and share all data and methodology so it is available for careful scrutiny by other scientists, thereby allowing other researchers the opportunity to verify results by attempting to reproduce them. This also allows statistical measures of the reliability of these data to be established.

What I see as a perhaps a lacking to which posters are in less agreement is:

Scientific researchers propose specific hypotheses as explanations of natural phenomena, and design experimental studies that test these predictions for accuracy.

Here, I think the lacking involves using hypotheses that would provide criteria for selecting trees, months, lags, TRs, MXD, QC indexes, etc. for temperature reconstructions prior to testing and then using all the data to test whether a model can predict temperatures in the instrumental time period using both calibration and validation. What bothers me about the current approach as I understand it (I will stand corrected if someone provides better information) are that the criteria selected are based on the results of the testing after the fact and the dangers of data snooping are completely ignored. In my view, if these dangers were well understood the dendros would be making a major effort to compare the calibration and validation periods for a reduction in correlation on going from calibration to validation, and finally, since data snooping can always look ahead to validation performance, they would want to be making every effort to look at out-of-sample periods using the same criteria that was applied to the original calibration and validation periods.

A central concept in a science and the scientific method is that all evidence must be empirical, or empirically based, that is, dependent on evidence that is observable by the senses. It is differentiated from the philosophic usage of empiricism by the use of the adjective “empirical” or the adverb “empirically”. Empirical is used in conjunction with both the natural and social sciences, and refers to the use of working hypotheses that are testable using observation or experiment. In this sense of the word, scientific statements are subject to and derived from our experiences or observations.

In a second sense “empirical” in science may be synonymous with “experimental”. In this sense, an empirical result is an experimental observation. The term semi-empirical is sometimes used to describe theoretical methods which make use of basic axioms, established scientific laws, and previous experimental results in order to engage in reasoned model building and theoretical inquiry.

http://en.wikipedia.org/wiki/Empiricism

Although procedures vary from one field of inquiry to another, there are identifiable features that distinguish scientific inquiry from other methods of developing knowledge. Scientific researchers propose specific hypotheses as explanations of natural phenomena, and design experimental studies that test these predictions for accuracy. These steps are repeated in order to make increasingly dependable predictions of future results. Theories that encompass wider domains of inquiry serve to bind many specific hypotheses together in a coherent structure. This in turn aids in the formation of new hypotheses, as well as in placing groups of specific hypotheses into a broader context of understanding.

Among other facets shared by the various fields of inquiry is the conviction that the process must be objective to reduce a biased interpretation of the results. Another basic expectation is to document, archive and share all data and methodology so it is available for careful scrutiny by other scientists, thereby allowing other researchers the opportunity to verify results by attempting to reproduce them. This also allows statistical measures of the reliability of these data to be established.

http://en.wikipedia.org/wiki/Scientific_proof

the trick is in bending the response curve the way it’s supposed to be

Benders are capable of bending anything, even unbendable bars! John Brognell (is that spelled right?) of numberwatch calls himself “your bending author.” Maybe there’s a connection.

Mark