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Are tree-rings a good proxy for temperature reconstruction?

October 10, 2015

Guest post by Neil Catto


Are tree-rings a good proxy for temperature reconstruction?

To start this essay I would like you to think a bit about basic logic.

The very first form of life on Earth would have been stimulated by gases, heat, light (photons), water and pressure. Do you think this very first form of life needed a mechanism to cope with continuously changing levels of gases, hot/cold, light/dark, wet/dry and high/low pressure?

Every form of life since its start has been and is stimulated by the same continuously changing levels of these elementary parameters. I suggest this “weather-coping” mechanism is a fundamental protection and survival mechanism for all life.

As part of my research into weather impact on living organisms (including humans) I developed a measurement of photosynthesis; the N-Index. Without divulging the exact algorithm due to IP constraints, the N-Index is a (daytime) combination of gases, heat, radiation (photons), water and pressure.

Trees use photosynthesis to grow. This growth can be seen in the tree-rings produced during each season. There are a huge variety tree species indigenous to different areas of the globe and their growth rings vary according to the above stimuli and the specific nutrients in their local environment.

Now, if we compare real temperature data with real N-Index data perhaps we can start asking questions. I have used Birmingham data for representation.



Fig 1 daily maximum temperatures for Birmingham UK Oct1998-Sep2015



Fig 2 daily N-Index measurements for Birmingham UK Oct1998-Sep2015


Both plots have similarities, they show seasonality, both are higher in the summer and lower in the winter.

There is lot amount of data (>6,000 days) in fig 1 and 2 plots. For this essay in order to see more clearly I have used a full year in isolation from 01Oct2014 to 30Sep2015.



Fig 3 Birmingham daily maximum temperature (Tx) vs N-Index latest 12 months


Whilst both show variability the NI is considerably more variable than Tx. The green line is a figure representing the on/off switching of biological signalling molecules which start or stop photosynthesis. 6.9 NI has been shown to be consistent over many empirical experiments [mitochondria in mammalian retinal ganglion cells]. There are perhaps some species of life which have evolved to enact photosynthesis at slightly higher or lower levels than this 6.9NI.

When perusing Fig 3 I’d like you to imagine two scenarios. 1) Think about mowing the lawn. 2) Think about BBQ’s.

In scenario one, the grass probably had its last cut at the end of October (30th) 2014 with the first cut around the 6th April (although there was one day growth on the 6th March). As the N-Index is an average figure for a day, there are often occasions when photosynthesis may occur for shorts periods during a day.

The second scenario, there were about 5 days when you may have had a BBQ. 4th/11th/30th June, and the 3rd/10th July 2015.

Of course both these scenarios only apply to locations around Birmingham.

If we look at these same data but sorted by maximum temperature (Tx) lowest to highest we can start observing some interesting points.



Fig 4 Birmingham daily Tx (low-high) vs N-Index for latest 12 months


We can see, in Fig 4 that there is potentially no photosynthesis when the temperature is less than 6.9 Deg C. The 6.9 Deg C is coincidence with the 6.9 NI for photosynthesis, I think.



Fig 5 NI (low-high), equivalent temperature and highlight of when photosynthesis (growth) can occur


Analysis of the whole year data of 365 days shows there were 244 days when no growth would have taken place in Birmingham even with temperatures as high as 23 Deg C.

You can now make up your own mind if you think tree-ring data is a good proxy for temperature reconstruction.

  1. robinedwards36 permalink
    October 10, 2015 1:40 pm

    Very interesting! I’d like to get the Birmingham max t starting around 1980, and corresponding NIs if they are available, I could look for consistent (or otherwise) features. I am almost sure that the temperatures in Birmingham will have had a step change in late 1987 and a comparison with NI for that period would be intriguing.
    Cheers, Robin

    • NeilC permalink
      October 11, 2015 10:18 am

      I am sure you would be able to obtain max temperatures for Birmingham from 1980. However, as far as the NI, I have not been able to locate accurate measurements of a couple of elements needed to build the NI.

  2. October 10, 2015 1:45 pm

    Tree ring dating, or dendrochronology, is a very useful tool for certain situations. However, there is a lot of “noise” which cannot be adequately determined with environmental factors. The main use is to show ages and environmental trends. For example, dendrochronology was used at Mesa Verde, CO. By overlapping the cores, from posts in the 800-1300 A.D. cliff-dwelling structures, forward to living trees, it was possible to determine the ages of the Mesa Verde construction. Dendrochronology also was useful in determining abandonment due to a long drought of 69 years followed by cold temperatures. It also showed that the last tree felled for construction was in 1281. This summer I got one of the “Roof Tour” tickets for Lincoln Cathedral, UK. Dendrochronology was used to determine when the oak beams used in the reconstruction of Lincoln Cathedral in ca. 1200 were cut.

    So, when you are dealing with specific environmental factors, it has severe limitations. You need a large data base of trees over a long period of time to show trends in climate factors, not specifics.

    • October 10, 2015 10:02 pm

      Very interesting. Thanks!

    • NeilC permalink
      October 11, 2015 10:21 am

      I can understand the use of tree-ring data to obtain dating information. What I was suggesting is tree-ring data is not accurate enough to build temperature reconstructions.

  3. Ben Vorlich permalink
    October 10, 2015 4:32 pm

    This is a model for plant growth, where is the data from the field for matching model to reality? Without the field data I have no idea how well the model did and therefore am no better informed than I was when I started reading vis-a-viz tree thermometers.

    For example
    Analysis of the whole year data of 365 days shows there were 244 days when no growth would have taken place in Birmingham even with temperatures as high as 23 Deg C.

    So what happened in the field?

    BTW I don’t think trees do make reliable thermometers.

    • NeilC permalink
      October 11, 2015 10:31 am

      The N-Index is an indicator of when a specific biological molecule, common to all life forms, changes its structure based on the weather stimuli it is recieving.

      There are two structures to the molecule, in one mode its releases a signalling hormone (we’ll call H1) and in the the other mode it releases a different signalling hormone (H2).

      If you want field data ask Paul and he’ll give you me contact details. There are a few IP issues with data.

  4. Joe Public permalink
    October 10, 2015 5:03 pm

    Michael thought so ……

    • NeilC permalink
      October 10, 2015 5:32 pm

      Made me smile

  5. Svend Ferdinandsen permalink
    October 11, 2015 11:48 pm

    Tree rings are excellent to determine the growing conditions for trees, but to infer single climatic conditions it does not work. Trees reponds to the whole package, temperature, rain, draught, sunshine, gowing days, forest fires, a man with an axe, an animal chewing on the leaves or insects, you name it.

  6. Chris Walcek permalink
    October 13, 2015 8:09 pm

    It is my understanding that there are some raw correlations (r^2) approaching 0.8 for correlations between some local temperatures and tree ring widths. However, with only limited browsing of literature, I only find r^2’s in the range 0.2 or so. What is the correlation coefficient for your Ni and Temperature? Go ahead and torture the data (average it for different times, lag/lead, season adjustments) What is the BEST r^2 you can obtain? My bets it is comparable to the real world correlation coefficients?

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