In the original climate context, leaving out one of the presumed contributors to the (additive) parameter of interest (and I suppose we are still talking about local or areal or global temperatures) There should not be any “interaction effects” I guess, so the problem should not arise.

However, I’d be grateful for some instruction about the fundamental reason for being so fixated on tree ring data. Several references have been made to the hoped-for correlation between tree ring information of whatever sort, (or varve thickness data) and the temperature/climate prevailing at particular times of the year in the same region. What I gather is that the tree ring stuff is being assessed by its (linear) correlation with local summer temperatures JJA, perhaps MJJAS, or whatever the growing season is. However, in my book annual temperatures – the things that determine our way of life – are not just those existing in the growing months. There are several other months in which temperatures remain of interest to those living in them. What will happened to our assessment of climate if we choose to ignore the majority of the available instrumental data?

In my studies of instrumental readings for polar regions I’ve noticed that many stations do not record data from the depth of winter. Specifically, temperatures below -20C seem to have been widely replaced by missing values. I can readily sympathise with the people charged with measuring them, but surely it would be very useful to know whether the cold extremes have been getting more or less extreme. These big negative numbers ought to play their part in our estimation of global temperatures.

Am I missing something here?

Robin

If (as is very likely) the nature of the errors change over time there can be a structural break in the correlation of sediment data and temperatures. (I.e., it is likely that the modern era has affected sediments in a substantially different way than the agricultural/wild period prior to the modern era.) The structural break can lead to widely erroneous and biased results.

There are, of course, ways to statistically test for a structural break in forecast modeling. I have little doubt that a structural break is present in the relationship between sediments and temperature around the early/mid 20th century.

A milk shake maker produced a wonderful pink milkshake which was delicious. Moreover, because it was pink it had health giving properties. It contained milk, cream, yoghurt, sugar and raspberries. He concluded that all 5 ingredients were needed to give the drink its pink coloration. Then along came an amateur scientist who disputed the claim. He performed a simple series of experiments in which he removed one ingredient at a time from the mix. He discovered that it was, in fact, only the raspberries that were responsible for the pink colour; the rest of the ingredients had no influence on the colour.

The Shaker (for that was his title) was upset at this assertion, an assertion from a man who wasn’t even a fellow Shaker, but he did not waste too much time as he’d moved on. For he was both a mover and a shaker. He now had a drink that was even pinker and, therefore, even more beneficial to health. This drink contained milk, cream, yoghurt, sugar and strawberries. Again, he asserted that all 5 ingredients were needed to get the pink colour. The amateur scientist performed the same series of experiments as before and this time he discovered that only the strawberries give the shake its pink colour.

The shaker was angry that this “amateur” was making these wild assertions but he did not waste too much time as he’d moved on again. His latest drink was the pinkest yet. It contained milk, cream, yoghurt, sugar, raspberries and strawberries. In order to prove his assertion that all the ingredients were needed, he performed his own series of experiments, based on those performed by the amateur scientist, in which he removed one ingredient at a time. In every case he still ended up with a pink milkshake. He was thus able to rubbish the amateur scientist’s claim that some of the ingredients weren’t necessary for the pink colour.

I think his logic is flawed. What do you think? Could you falsify his hypothesis if you were allowed to remove, say, two ingredients from the mix or would this be unreasonable for scientific reasons? Off the top of your head, which 2 would you start with?

Andymc

Dean P, that’s an interesting observation. Looking again at the graph, I actually can see a distinct negative slope in the data between about 1875 and about 1960 (ie, cooling). So, why the sudden change trend reversal around 1960?

Can you extend it to more recent dates? Also, can we all remember (I’m an offender too) to label both axes of graphs accurately and concisely please? Thanks, Geoff.

There is this very special tree in Russia….