WUWT reader Tom O’Hara writes in a question that seemed worthwhile to discuss. Paleo specialists can weigh in on this. It seems to me that he has a point, but like him, I don’t know all the nuances of calibrating a proxy. (Graphic at right by Willis Eschenbach, from another discussion.)
O’Hara writes:
[This] is a puzzle to me.
Everything we know about past climate is based on “proxies.” As I understand the concept, science looks at “stuff” and finds something that tends to mirror the changes in temperature, or whatever, and uses that as a means to determine what the likely temperature would have been at an earlier time. This is, I am sure, an oversimplified explanation.
So what we have, in essence, is a 150 year or so record of temperature readings to use to determine our proxy’s hopeful accuracy.
Now my question would be, if we are continuously adjusting the “readings” of that record, how does that affect the usefulness of the proxy information?
If I have correlated my proxy to a moving target, doesn’t that effect the likelihood that the proxy will yield useful information?
It would seem to me that this constant massaging of the database used to define and tune my proxy, would, in the end, destroy the utility of my proxy to deliver useful information. Or have I got it all wrong?
A few primers for discussion:
1.Detecting instabilities in tree-ring proxy calibration
Abstract. Evidence has been found for reduced sensitivity of tree growth to temperature in a number of forests at high northern latitudes and alpine locations. Furthermore, at some of these sites, emergent subpopulations of trees show negative growth trends with rising temperature. These findings are typically referred to as the “Divergence Problem” (DP). Given the high relevance of paleoclimatic reconstructions for policy-related studies, it is important for dendrochronologists to address this issue of potential model uncertainties associated with the DP. Here we address this issue by proposing a calibration technique, termed “stochastic response function” (SRF), which allows the presence or absence of any instabilities in growth response of trees (or any other climate proxy) to their calibration target to be visualized and detected. Since this framework estimates confidence limits and subsequently provides statistical significance tests, the approach is also very well suited for proxy screening prior to the generation of a climate-reconstruction network.
Two examples of tree growth/climate relationships are provided, one from the North American Arctic treeline and the other from the upper treeline in the European Alps. Instabilities were found to be present where stabilities were reported in the literature, and vice versa, stabilities were found where instabilities were reported. We advise to apply SRFs in future proxy-screening schemes, next to the use of correlations and RE/CE statistics. It will improve the strength of reconstruction hindcasts.
Citation: Visser, H., Büntgen, U., D’Arrigo, R., and Petersen, A. C.: Detecting instabilities in tree-ring proxy calibration, Clim. Past, 6, 367-377, doi:10.5194/cp-6-367-2010, 2010.
2.
From WUWT August 16, 2013 A new paper now in open review in the journal Climate of the Past suggests that “modern sample bias “has “seriously compromised” tree-ring temperature reconstructions, producing an “artificial positive signal [e.g. ‘hockey stick’] in the final chronology.”
Basically, older trees grow slower, and that mimics the temperature signal paleo researchers like Mann look for. Unless you correct for this issue, you end up with a false temperature signal, like a hockey stick in modern times. Separating a valid temperature signal from the natural growth pattern of the tree becomes a larger challenge with this correction. More here
3.
Calibration trails using very long instrumental and proxy data
Esper et al. 2008
Introduction
The European Alps are one of the few places that allow comparisons of natural climate proxies, such as tree-rings, with instrumental and documentary data over multiple centuries. Evidence from local and regional tree-ring analyses in the Alps clearly showed that tree-ring width (TRW) data from high elevation, near treeline environments contain substantial temperature signals (e.g., Büntgen et al. 2005, 2006, Carrer et al. 2007, Frank and Esper 2005a, 2005b, Frank et al. 2005). This sensitivity can be evaluated over longer timescales by comparison with instrumental temperature data recorded in higher elevation (>1,500 m asl) environments back to the early 19th century, and, due to the spatially homogenous temperature field, back to the mid 18th century using observational data from stations surrounding the Alps (Auer et al. 2007, Böhm et al. 2001, Casty et al. 2005, Frank et al. 2007a, Luterbacher et al. 2004). Further, the combination of such instrumental data with even older documentary evidence (Pfister 1999, Brázdil et al. 2005) allows an assessment of temporal coherence changes between tree-rings and combined instrumental and documentary data back to AD 1660. Such analyses are outlined here using TRW data from a set of Pinus cembra L. sampling sites from the Swiss Engadin, and calibrating these data against a gridded surface air temperature reconstruction integrating long-term instrumental and multi-proxy data (Luterbacher et al. 2004).
paper here: Esper_et_al_TraceVol_6 (PDF)
Kurt,
Several of the reconstructions split up the instrumental record into a “calibration period” and a “verification period”, as you say – in particular the Mann et al. studies. However, as we mention in Section 2.1 of our paper (link in my first comment above), many of the reconstructions don’t bother with a “verification period”.
You are correct to point out that changing the “calibration period” can substantially alter the reconstruction. For instance, if you look at Fig S10 in the Supplementary Information on Mann’s website for Mann et al., 2008 (http://www.meteo.psu.edu/holocene/public_html/supplements/MultiproxyMeans07/SuppInfo.pdf), there are recognisable differences between the 1850-1949-calibrated vs 1896-1995-calibrated reconstructions.
Having said that, Mann et al. used roughly 2/3 of their instrumental record for their calibration period, and made sure it was over a continuous period. So, there’s not an awful lot of room for “cherry-picking” there.
Have you seen McShane & Wyner, 2011, though? They did an interesting analysis where they studied the effects of systematically varying the “verification”/”calibration” periods for the Mann et al., 2008 dataset. Their paper is paywall, but if you don’t have access, there’s a pre-print available from ArXiV here: http://arxiv.org/abs/1104.4002
Kurt says:
June 15, 2014 at 7:34 pm
“Maybe before you get snarky with someone, you should first take the time to understand what they are saying.”
———
Kurt, this is the statement you made and the one I responded to, to wit:
================
Kurt says: June 13, 2014 at 5:20 pm “My understanding (which may be wrong) is that the proxy data is initially calibrated or trained against a first subset of the instrumental record ………..”
——————-
Kurt, please cite me one (1) example of specific proxy data that WAS ever “initially calibrated against the instrument (thermometer) record”. Just one (1).
Here is a graph of “Holocene Temperature Variations” which shows 12K years of plotted data from eight (8) different proxies, …… with an inset graph showing the most recent 2K years of plotted data from four (4) more different proxies. The “data sources” for all twelve (12) separate proxies are specified at the bottom of the article. To wit: http://commons.wikimedia.org/wiki/File:Holocene_Temperature_Variations.png
Kurt, the proxy data …. is the proxy data.
And the “instrument records” are just more of the same, ….. more per se proxy data.
Why are you so damn sure that you are now “right” …. when you initially stated you “may be wrong”?
Ronan Connolly,
“However, for the non-USHCN component of the GHCN, the net adjustments are much less.”
This raises the problem of the definition of adjustments. For example, BEST doesn’t adjust in this sense. This does not prevent BEST to adjust massively in the aggregation stage.
Quantification of adjustments depends greatly on the average length of the series. With short (GHCN) or cut (BEST) series, the very real adjustments at the aggregation stage are not recorded.
We can give another definition of adjustments : the average shift operated relative to absolute temperatures. This definition obviously has a weakness related to a possible bias in altitudes. However, in cases using preferentially long series, adjustments lead to an artificial warming of about 0.5 ° C per century (see eg Begert et al fig. 4.29 p. 87 and Böhm et al. 2001).
On the subject of “the instrument (thermometer) record” …. I would like to see a plotted graph that depicts the number of “points” or places on the earth’s surface where thermometers were being used to record “daily surface temperatures” …. for each year … for the years from say 1650 to present.
In other words, a graph that depicts the “# of” per se, active Temperature Stations …. per each year …. for the past 360 years.
Such a graph would be excellent reference material for any one that is curious of the “data sources” that are used for calculating Global Average Surface Temperatures for each of the years inclusive of the aforementioned “time period”.
And also would be excellent reference material for discussions on “adjustments to the instrument (thermometer) record”.
Cheers
Phi,
That’s actually one of the main reasons why the net adjustments for the GHCN are so small relative to the USHCN. The USHCN records are relatively long: ~93 yrs compared to ~44 yrs for the GHCN.
As a result, the overlap between target stations and their neighbours is much less for the GHCN than the USHCN – see Table 5 (p28) of our Urbanization bias III paper.
Also, the average distances between target stations and their neighbours is much greater for the GHCN.
For these reasons, the Menne & Williams, 2009 algorithm is less effective at identifying potential breakpoints in the GHCN, and so the net adjustments are much less.
Also NCDC never collected station history files/time-of-observation changes for the non-USHCN component, so they don’t bother with TOB adjustments.
As for the Berkeley Earth (BEST) adjustments, we found in Section 4.8 of our Urbanization bias I paper that their “Scalpel” technique seems to introduce a warming trend of about +0.43°C/century relative to using the “Common Anomaly Method” (see Figure 30, p41). We suspect this is a consequence of them shortening the records too much. If so, it may be that their adjusted records are problematic for studying long-term trends.
Samuel,
Have a look at Section 2 (p2-5) of our “Urbanization bias III” paper (link above) for the GHCN dataset. This is the main one used by NOAA, NASA and the Japan Meteorological Agency and is fairly similar to the CRU’s dataset.
For the Berkeley Earth dataset (BEST), have a look at Figure 27 of our “Urbanization bias I” paper (link also above) on p40.
Is that of any help?
Samuel C Cogar says:
June 16, 2014 at 8:27 am
“Kurt, please cite me one (1) example of specific proxy data that WAS ever initially calibrated against the instrument (thermometer) record.”
Every tree ring series would have to be calibrated against the thermometer record in order to associate any given width of a tree ring with some average temperature for the season. You have to calibrate width against something, after all, to figure out how to get temperature from a ring width. You don’t have to take my word for it – many of the posts in this thread confirm that proxy data is calibrated against the thermometer record. Willis Eschenbach says on June 16, 2014 at 2:02 am for example that in the “’calibration procedure’ used for most of the global temperature proxy reconstructions . . . proxy series are simply re-scaled to have the same mean (“average”) value and variance (“range”) as the instrumental record over the calibration period.'” There is a calibration period where proxy data overlaps the instrumental record and that the instrumental record is used to determine a relationship between tree ring width and temperatures. I’m not sure about the exact procedure – I’d guess that the ring widths are mapped to some kind of a temperature- width curve to account for declining growth in tree rings as the tree ages, with the instrumental record for the region that the tree was in used to figure out the best coefficients and/or exponents to minimize a mean square error or some other criterion like a mean that Willis Eschenbach mentions above, but one thing for certain you have to do is use the thermometer record in some way to figure out how to correlate a tree ring width to temperature.
“Why are you so damn sure that you are now “right” …. when you initially stated you “may be wrong”?”
You ellipsed out the relevant potion of the quote from my original post. What I wasn’t sure about was whether the period during which a proxy series overlapped the instrumental record was divided into a calibration period and a verification period, and more particularly whether the person doing the reconstruction gets to just pick where to set the boundary between the calibration period and the verification period. Apparently I was only partially right as
Ronan Connoly just noted (thanks for that – I’ll be sure to read the article you linked when I have the chance) in that this procedure is only sometimes used, and when for example Mann et al. used it they selected a dividing line that left a full 1/3 as the verification period with 2/3 as the calibration period – which means that there is significant data to both calibrate and verify the reconstruction.
Ronan Connolly says:
June 16, 2014 at 2:33 pm
Ronan, on another thread this week we discussed the fact that if you take a number of trendless sawtooth waves of different frequencies, and you subject them to the “scalpel” method, you’ll end up with a trend, despite the fact that you started with trendless data.
I’ve been a long-time supporter of the “scalpel” method, so this was a great surprise to me. I asked Mosher and Zeke for a comment, but they evaporated …
w.
Ronan Connolly says:
June 16, 2014 at 2:33 pm
“Samuel,
Have a look at Section 2 (p2-5) of our “Urbanization bias III” paper (link above) for the GHCN dataset. This is the main one used by NOAA, NASA and the Japan Meteorological Agency and is fairly similar to the CRU’s dataset. Is that of any help?”
—————-
Ronan,
Thanks, but “No”, I have no interest in the above cited “data sets”. My request was for a “plotted graph” of the original “source locations” from which the thermometer records were obtained, …. not the massaged and manipulated “data sets” that were created from the recorded and reported thermometer “readings”.
It is foolish for anyone to calculate the “average” of twenty-four (24) surface temperatures that were recorded in 1870 ….. and then compare it to the calculated “average” of 2,000+- surface temperatures that were recorded in 2012 ….. and then claim the former is “the highest ever recorded Yearly Average Surface Temperature for the entire US of A”.
Especially given the fact that the “accuracy” of the recorded data being used to create your above cited “data sets” is highly questionable to say the least. And a “reading” of the history of the NWS should enlighten you on that fact.
Ronan, here are a few excerpts from one of said histories, to wit:
Evolution to the Signal Service Years (1600-1891)
Source link: http://www.nws.noaa.gov/pa/history/signal.php
“By the end of 1849, 150 volunteers throughout the United States were reporting weather observations to the Smithsonian regularly. By 1860, 500 of Henry’s stations were furnishing daily telegraphic weather reports to the Washington Evening Star, and as Henry’s network of volunteer observers grew, other existing systems were gradually absorbed, including several state weather services.
At 7:35 a.m. on November 1, 1870, the first systematized and synchronous meteorological reports were taken by observer-sergeants at 24 stations in the new agency. These observations, which were transmitted by telegraph to the central office in Washington, D.C., commenced the beginning of the new division of the Signal Service.
Since the original congressional resolution covered only the Gulf and Atlantic coasts, and the Great Lakes, the early forecasts were made only for these areas. On June 10, 1872, an act of Congress extended the service throughout the United States, “for the benefit of commerce and agriculture.” However, a sample forecast of 1872 reflects the lack of data west of the Mississippi River.
The Signal Service’s field stations grew in number from 24 in 1870 to 284 in 1878. Three times a day (usually 7:35 a.m., 4:35 p.m., and 11:35 p.m.), each station telegraphed an observation to Washington, D.C. These observations consisted of:
1. Barometric pressure and its change since the last report.
2.Temperature and its 24-hour change.
3.Relative humidity.
4.Wind velocity.
5.Pressure of the wind in pounds per square foot.
6.Amount of clouds.
7.State of the weather
…………on October 1, 1890, an act transferring the weather service to the Department of Agriculture was signed into law by President Benjamin Harrison.”
=======================
Now Ronan, what is the source “location” data for the recorded temperatures that are used to calculate the Yearly Average Global Surface Temperatures for the years of 1650 thru to 2014? What percentage of the earth’s surface was actually being monitored during each of those years? Curious minds would like to know.
Kurt says:
June 16, 2014 at 3:04 pm
“You have to calibrate width against something, after all, to figure out how to get temperature from a ring width.”
—————–
Kurt, I know a little about tree rings, …. and xylem and phloem and cambium layers and apical meristems, etc., etc. I am learned in biology, including botany. And in my learned opinion one has to do a lot of “hard squeezing” to extract an average “yearly” near surface air temperature out of tree ring growth.
Little things can make a big difference in tree ring growth. Like, was the tree “shaded” by another tree? Did the tree receive mostly “morning” Sunshine or mostly “afternoon” Sunshine? Kurt, do you realize that shorter young saplings “leaf out” earlier than the taller older trees? Sure nuff, they do. They gotta get their new Spring growth in before the canopy of the older trees “blocks” all their chances of receiving any direct Sunlight.
Kurt says:
“You don’t have to take my word for it – many of the posts in this thread confirm that proxy data is calibrated against the thermometer record. Willis Eschenbach says on June 16, 2014 at 2:02 am for example that in the “’calibration procedure’ used for most of the global temperature proxy reconstructions . . . proxy series are simply re-scaled to have the same mean (“average”) value and variance (“range”) as the instrumental record over the calibration period.’” ”
—————
Kurt, what Willis E said ….. and what you think he said ….. are two (2) different things.
Stipulating a ’calibration procedure’ …. and actually calibrating something to a known standard are not the same thing.
Me thinks that Willis was simply implying the need for an “adjustment procedure” for aligning two (2) different “scales” to the same “baseline”.
Just like one has to “adjust” Centigrade temperatures if they are to be “aligned” (re-scaled) to a Fahrenheit “baseline”. Or to “adjust” atmospheric CO2 quantities from … “CO2 ppm increases per decade” …. to …. “CO2 ppm increases per year”.
What purpose would it serve to “re-calibrate” the proxy data so that it matched the instrument data? That is, other than to prove or justify one’s “junk science” claims? AKA: “Michael Mann’s “hide the decline“”.
Willis Eschenbach says:
June 16, 2014 at 10:47 pm
Are you referring to this guest essay by Bob Dedekind? http://wattsupwiththat.com/2014/06/10/why-automatic-temperature-adjustments-dont-work/
If so, I agree with a lot of what he says, and we made similar arguments in Section 4.3 of our Urbanization bias III paper – in particular, see the discussion of the schematics in Figures 28 & 29 (p29-30).
However, I disagree with his claim that:
He correctly points out that the growth of trees around a weather station can introduce a gradual “warming” trend (by blocking cooling winds). But, under some conditions, tree growth can also lead to gradual cooling. For instance, trees can also block sunlight and make the area “cooler”, which is why people sometimes lie “in the shade” of a tree on a hot summer’s day!
Have you read Runnalls & Oke, 2006 (open access)? In their conclusions section, they point out that microclimate biases could easily introduce a non-climatic trend if the majority of the biases are of the same sign. But, they are careful to point out that these trends could potentially be of either sign. I’d agree with the conclusions of Runnalls & Oke, 2006.
I do agree with Dedekind that step-change adjustments are not enough when there are also non-climatic trend biases in the data. This was one of our primary conclusions in our Urbanization bias III paper. This applies to both the Menne & Williams algorithm used by NCDC and the “Scalpel” method used by the Berkeley group.
And, if there is a tendency for non-climatic trend biases to be “warming biases”, then what Dedekind said is valid. An automated step-change breakpoint homogenization which only removes step biases and leave the trend biases, will lead to a net warming bias.
When we realise that about half of the current stations are currently urbanized (depending on the metric you use), and wouldn’t have been as urbanized 100 years ago, we can see that this IS a serious problem.
Berkeley Earth attempt to minimise the trend bias problem by reducing the weighting of stations with trends different from their neighbours. But, this just leads to a slightly different version of the “urban blending” problem which we discuss on p30-35. That is, in urbanized areas, the few rural neighbours unaffected by urbanization bias will tend to be in the minority. Therefore, their trends will be the “anomalous” trends that are de-weighted, and the trends of the (already more numerous!) urbanization biased stations will dominate regional trends even more.
For the Menne & Williams algorithm, things are more insidious because:
a) trend biases are adjusted as if they were “step biases” – leading to the problem illustrated in our Fig. 29
b) step change adjustments are based on the trends of the 40 neighbouring stations. In urban areas, this will lead to urban blending, i.e., “homogenization” will introduce a warming bias into the rural neighbours.
If the majority of stations are affected by a similar non-climatic bias, then “homogenization” will spread this bias uniformly amongst all the neighbouring stations, yielding a “homogeneous” blended bias.
Anthony’s Surfacestations project has shown that the majority of USHCN stations are affected by siting biases. Menne et al. imagine their homogenization algorithm somehow “removes” all of these biases. To me, this is kind of like mixing strawberries and bananas in a blender, and expecting your “homogenous”, blended smoothie to consist of pure strawberries…
Samuel,
Ha! Have a proper look at the figures I suggested:
Section 2 (p2-5) of this paper: http://oprj.net/oprj-archive/climate-science/34/oprj-article-climate-science-34.pdf
Figure 15 (p30) and figure 27 (p40) of this paper: http://oprj.net/oprj-archive/climate-science/28/oprj-article-climate-science-28.pdf
Also, have a read of Section 2.4 (p7-8) of this paper: http://oprj.net/oprj-archive/climate-science/19/oprj-article-climate-science-19.pdf
I suspect we’re not in as much disagreement as you think we are! 😉
Ronan Connolly says:
June 17, 2014 at 6:39 am
“He correctly points out that the growth of trees around a weather station can introduce a gradual “warming” trend (by blocking cooling winds). But, under some conditions, tree growth can also lead to gradual cooling.”
——————-
Ronan, when I read your above statement about “trees n’ warming” ….. it reminded me of a “puzzling” question that has been bugging me since February 08, 2012.
Now I’m pretty good at figuring out “oddities” that one often sees in nature …. but here is one that I observed that I have a couple “maybes” that might explain it, but not a factual scientific reason that I am positive of. Therefore I would appreciate your expert opinion on the matter.
Following are “links” to three (3) pictures I took around 9:30 AM on the morning after a brief snowfall the night before …. and are pictures of what I have labeled as being “tree circles” or “snow circles”. One can see six (6) different “circles” in said 3 pictures.
The pictures are self-explanatory ….. but my tired ole brain is not. (a case of CRS, maybe.)
Ronan, my question for you is, ….. why no snow underneath those “naked” trees?
Or, …. why did the snowfall underneath those “naked” trees melt so much quicker than the other snowfall?
See pictures @ur momisugly:
http://i1019.photobucket.com/albums/af315/SamC_40/1treecircle.jpg
http://i1019.photobucket.com/albums/af315/SamC_40/2treecircles.jpg
http://i1019.photobucket.com/albums/af315/SamC_40/3treecircles.jpg
Samuel C Cogar says:
June 18, 2014 at 3:35 am
Samuel, that is an excellent example of how trees can alter the local microclimate, and your photos illustrate the phenomenon perfectly! Thanks!
There are several factors that could be involved. I think the standard explanation is as follows:
Snow is “white” because it reflects ~90% of visible (and also UV) light (in climate science, we say snow has a high “albedo”). This is why there is often a “glare” from the snow, and also why you can sometimes get sunburnt from the reflected light of snow. However, snow (like all forms of water) easily absorbs infrared light.
On the other hand, tree trunks (which are “dark”) absorb quite a lot of the sunlight. They also emit infrared light, and as the trees heat up they emit more infrared light.
So, in the morning, most of the sunlight falling on the open ground is reflected, while most of the sunlight falling on the tree trunk is absorbed, heating the trees up. The trees emit infrared light to the surroundings, and some of this is absorbed by the snow nearest the tree, causing the snow to melt quicker.
—
There are other possible explanations, however. For instance, at night the ground cools by emitting infrared light to the sky (particularly on a clear, cloudless night). Even though the branches were “leafless”, they would still “block” some of the escaping infrared light, and thus the ground nearer the trees wouldn’t cool as much as the open ground. This would keep the ground a bit warmer, and cause the snow to melt quicker.
[By the way, this is thought to be one of the factors in the so-called “urban heat island” phenomenon. Tall buildings block some of the outgoing infrared light, and thereby reduce the rate of “infrared cooling” at night. This means that those urban areas cool less at night than rural open spaces, leading to higher night-time minimum temperatures (“Tmin”).]
Another possibility is that if the root structure is near the ground, it could be respiring enough to slightly heat the surrounding soil – thus melting the snow slightly quicker. The root structure would be densest closer to the trees (and also the tree trunk would be warmer as mentioned above).
—
Do you know were your “tree circles” there before sunrise, or did only they form once the sun started shining?
If they only started forming once the sun had risen, then the first explanation seems likely. However, if the “tree circles” were there at night, then one of the other explanations would seem more likely.
Ronan Connolly:
Thankyou for your superb post at June 18, 2014 at 12:54 pm.
It is clear, interesting and informative. I enjoyed it, and I think it to be the best post of this day on WUWT.
Richard
Thanks, Richard!
Ronan Connolly says:
June 18, 2014 at 12:54 pm
“Samuel, that is an excellent example of how trees can alter the local microclimate, and your photos illustrate the phenomenon perfectly! Thanks!”
———————
Ronan, my thoughts EXACTLY, …. but I didn’t know EXACTLY how or why, ….. and thus the reason I took those pictures because there was no way in ell I could have adequately described said “event” in verbal only terms.
And Ronan, thank you for your response, ….. but, …… and I don’t know how to tell you this other than to say, ….. it was of absolutely no value to me in resolving my quandary. Thus I will ignore all of it except for your question of …. “Do you know were your “tree circles” there before sunrise, or did only they form once the sun started shining?”
Ronan, I do not know if said “tree circles” were there before sunrise (daylight). But in my opinion, it is highly likely that they were.
Anyway, I would like to reiterate the fact(s) that those pictures were taken during the “wintertime” on February 08, 2012, around 9 to 9:30 AM …. under heavily overcast skies.
And being “wintertime 2-8-12”, …. those trees are dormant …. and I could not see that clearly before “daylight” …. which does not occur here until like 7:45 to 8:00 AM EST. Thus, no Sunshine, no IR radiation from the soil, no IR from the root structure, no IR from the tree trunks or limbs, …. but potentially a wee bit of IR radiation from the “overcast” cloud layer.
Now the roadway, sidewalks and rooftops are “snow free” because of the “heat island” effect …. but their IR emission could not be, would not be, “directed” to a circular area underneath the “circumference” of the out-stretched tree limbs.
And the trees are of three (3) different species. One (1) huge “pignut” Hickory tree, 1 large and 2 smaller Sugar Maple (Acer saccharum) and the other 2 are a “flowering” tree that I do not know the name of because they are not “native” to this locale.
Ronan, just so you know …. “where I am coming from”, …. I am Degreed (AB) in both the Physical and Biological Sciences (which includes Botany) …. and the only “reason” I could think up that might be responsible for creating those “tree circles” is, to wit:
It was a “wet” snowfall, with no wind or breeze blowing ….. and thus the “snowflakes” stuck to the tree limbs as well as covering the entire surface (grass, sidewalks, roadway and roof tops). But then, after the snowfall ceased …. but before daylight, ….. a “warm” air mass moved in underneath the over-cast skies …. and that “warm” air “conducted” some of its energy to the snowfall that was “stuck” to all the limbs of those trees. And that absorbed energy caused the snow to “melt” …. and the melt-water “dripped” down to the surface thus exacerbating the surface “melting”.
Anyway, I wanted another (author original) learned “opinion” or explanation before I started “touting” and/or “claiming” my above “solution” is a factuality that is based in/on logical reasoning, intelligent deductions and factual science.
Cheers, Sam C
Samuel C Cogar says:
June 19, 2014 at 6:28 am
Well, what are you basing your opinion on? Did you make any observations before sunrise, or is it just that this better suits your explanation? Not having been there, or knowing anything about your examples other than what you have told me, both possibilities seem likely.
If you did observe the circles before sunrise, we could then rule out any explanations which required sunlight for the circle formation. But, if you didn’t make any pre-sunrise observations, then we have to consider both possibilities. It’s not a matter of “opinion” – you either made the observations or you didn’t. If you did, then that’s great and we can use the information. But, if you didn’t, it’s not a big deal – we just have to consider both possibilities.
Infrared cooling of the ground is certainly greater on clear, cloudless nights (e.g., more likely to have ground frost after a “starry” night), however it still occurs on cloudy nights – all solid materials with a temperature greater than -273°C (i.e., 0K) emit infrared light.
I agree with you that the trees would have been dormant. However, “dormant” does not mean all metabolic activity completely stops. It just slows down dramatically. As a general rule of thumb for most organisms (plants/animals/bacteria/etc), biological activity roughly halves with a 7°C drop (provided the organism remains alive that is!).
In trees that have a winter dormancy period, the root structure still continues to grow during winter (absorbing water & nutrients and respiring) – just at a much slower rate. To be honest, I don’t think soil heating from root activity would be a major factor in your case, but it is a possible factor which we need to consider. One way to check would be to compare soil temperatures near the roots and away from the roots.
Your theory might well explain the circles, but so far I don’t think we’ve ruled out the other explanations. So I would be reluctant to choose one of the 4 proposed explanations (or some other explanation) over the others, until we had more information. Indeed, it may be that several factors are involved.
Did you actually see the snowfall “stuck” on the limbs before daylight? If you did, this would be an important bit of information, as the branches are bare in the photographs. So, if we knew that there had been snow “stuck” on the limbs during the night, but it was gone by 9am, this would definitely be relevant. But, if it’s just a guess, then we still don’t know.
If melt-water drips from the branches were responsible for the circles, I would expect the melting to be mostly confined to underneath the branches. It’s hard to tell from the photos – did the branches completely cover the “tree circle” regions? The circles seem to be more uniform in nature and cover a larger area, but that could just be the angles the photos are taken from.
Of course, if the branches did exactly cover the circles, that still wouldn’t rule out the other explanations, but it would at least provide us more information…
Ronan Connolly says:
June 21, 2014 at 3:43 am
“If you did observe the circles before sunrise, we could then rule out any explanations which required sunlight for the circle formation. But, if you didn’t make any pre-sunrise observations, then we have to consider both possibilities.”
————–
I have to assume that you are intentionally ignoring the IR absorption, emission and/or reflectivity properties of atmospheric H2O vapor in/of the specific form of “heavy cloud cover”.
And secondly, even if there were no heavy cloud cover …. the trees and surface area in question are not subject to any direct Sunlight within the stipulated “time frame” ….. and will not be subjected to said until like two (2) +- hours after “1st light” each morning because of the surrounding hills which “blocks” said direct solar energy.
And thirdly, even if the branches and trunks of the trees in question were subjected to direct Sunlight at the specified hour(s) of the morning in question, …. then >50% of their surface area would be subject to any solar “warming”…. and that surface area would be at 90 degrees perpendicular to the “rising” Sun, ….. thus there is no way in hell the “warmed” or “heated” surface area of said trees could possibly radiate their IR energy around to the “back” or “dark” side of said trees, ….. nor is it possible for said IR energy to have been radiated directly toward the surface area surrounding each of said trees.
Therefore, way less than 50% of the surface area of each tree would have been “warmed” …… and way less than 5% of said “warmth” (IR energy) would have been radiated directly toward the surface underneath the branch “canopy” of each of said trees.
“In trees that have a winter dormancy period, the root structure still continues to grow during winter (absorbing water & nutrients and respiring) – just at a much slower rate. To be honest, I don’t think soil heating from root activity would be a major factor in your case, but it is a possible factor which we need to consider.”
Ronan, …. “Give it up”, …. you don’t have a clue what you are talking about and your above obfuscations are little more than a silly CYA attempt to “bedazzle” me into thinking you are learned in/on the subject matter.
Your ability to accurately measure the “warming” effect that root activity contributes to the “warming” of the soil is no better than your ability to accurately measure the “warming” effect that atmospheric CO2 molecules contributes to the “warming” of the near surface atmosphere via direct absorption of radiated IR energy. Which, by the way, said “ability” is zero, nada, zilch, none …. whatsoever.
Ronan, here is a url “link” which I thinks originates from your own “backyard”, ….. so best you read the 1st paragraph therein …… and pay close attention to what it is telling you.
http://www.forestry.gov.uk/pdf/GrowingGreenActivityPack-Roots.pdf/$FILE/GrowingGreenActivityPack-Roots.pdf
“Did you actually see the snowfall “stuck” on the limbs before daylight?”
Ronan, I don’t have to actually see the Rabbit that left its “tracks” in the snow …. to know damn well that a Rabbit had been there prior to my observing of said “tracks”. And please don’t infer that it might have been a Weasel, Raccoon, deer, Chipmunk or dog that left said “tracks” in the snow.
If it had been a “dry” snowfall that had not “stuck” to the limbs, ….. then the area around the trunk of the trees would have had the same amount of “snow cover” as the rest of the surface area.
Your reliance on the possible interference by the Flying Spaghetti Monster does little to bolster or confirm your expertise or credibility on such matter of science.
Samuel,
In your June 18, 2014 at 3:35 am comment, you asked me for my opinion on a “puzzling” question that has been bugging me since February 08, 2012.
I gave you several plausible explanations, including one of the “standard explanations” for “tree circles”, e.g., see here, or here.
Apparently, there are many different reasons why “tree circles” will form, depending on the circumstances, e.g., some flowering trees can produce heat to help speed up melting. This obviously doesn’t apply to your case as the trees hadn’t started to bud. However, the point is there doesn’t seem to be a single, universal answer to the phenomenon. Yet, it seems because I didn’t include the one you wanted to hear (i.e., your favoured explanation), that you didn’t like my reply.
I have to admit, I’m now the puzzled one! If you were already convinced you knew “the answer”, why did you ask me in the first place?
To be honest, you haven’t convinced me that your explanation is “the answer”. It’s one possible explanation, but there are several reasons why “tree circles” form, and I don’t think you’ve satisfactorily shown that the others are “wrong”, and that yours is “right”. But, if you’ve already convinced yourself you have “the answer”, why do you need my approval to start ‘ “touting” and/or “claiming” [your] above “solution” is a factuality’?
At any rate, I do think your tree circle photos are a great example of how trees can significantly alter the local microclimate (regardless of what specific factors are involved in your particular case). So, I do appreciate you posting them and, before you started insulting me, I was finding the discussion interesting. So, thanks for sharing the photos.
Yeah, I found that exchange a little puzzling myself, “hey, got a question which I’d like to hear your thoughts on” turning into “ha ha, you’re wrong because I already had an answer I liked and you didn’t give it to me, take that!” is a bit out there.
Ronan Connolly says:
June 21, 2014 at 11:23 am
“and, before you started insulting me, I was finding the discussion interesting. So, thanks for sharing the photos.”
———-
Ronan, ……. (and also for Max™’s reading pleasure)
In all you’re previous postings/commentary to this article you inferred that you were quite knowledgeable and/or learned on the subjects of climate, weather, temperatures, thermal energy transfers, etc. … and thus the reason I specifically ask for your expertise and/or expert opinion on my “tree circle” pictures.
But what I got in reply from you, via your June 21, 2014 at 3:43 am posting, … was little more than patronizing crapolla with the implication that you were responding to a question posited by a dim-witted High School student.
And that highly irritated me …. and confirmed the fact that you surely thought likewise about all my other posted commentary. And now you are “crying-the-pity-party-blues” about me insulting you. GIMME A BREAK
And after I jumped your arse about the contents of your “3:43 am” post you did some quickie “searching” and posted a bunch of paraphrased and mimicked commentary in your above “11:23 am” posting, thus doing little more than “adding insult to your injury”.
Try again, Ronan, there is nothing in your above “11:23 am” posting that explains the “cause” of my pictured “tree rings” formation given the known environmental criteria that existed at the time of their formation. I specifically stated what said “known environmental criteria” were, … yet you come back with your 2nd post with more BS about flowering plants & trees, spring growth of bulbs & tubers and bright Sunshine heating up different parts of the environment. The next time, “write down” said controlling criteria ….. and eliminate everything that doesn’t conform to said ….. before you start with your mimicry of “what ifs” and “maybes”.
I’m too damn old to worry about someone getting “hurt feelings”, p-faced and/or pouty just because I point out their ignorance in/of/on a subject matter being discussed. One never learns a damn thing ….. if every one is nice to them and never contradicts anything they say or do. If one has been miseducated in the Sciences ……. then they have to be consciously “willing” to correct their problem …… but they have to be told what their “problem” is before there is any chance or hope of them ever correcting it. It is their conscious “choice” to make. No one can make it for them.
Thanks for the support, Max™
Hi Samuel,
I’ve re-read my June 21, 2014 at 3:43 am comment, and I’m not sure which bits you felt were patronising. But, I’m sorry if you perceived them as such. I try to be as clear, specific and straightforward as I can when I’m commenting & to try and document my reasoning as well as I can. Perhaps this approach can sometimes come across as “patronising”, but if so, it’s unintended.
I did ask you to back up your opinions with the experimental data/observations that you used for reaching your conclusions. But, this is the approach I would take when peer reviewing a paper. If I felt you were just a “a dim-witted High School student”, I probably wouldn’t have bothered.
I maintain science should be based on experimental data, not just opinions. Indeed, this is one of my main criticisms of much of modern “climate science”. Many climate scientists (who should know better) seem more interested in silly “scientific consensus” claims, or making sure their conclusions give the “right” answer than in critically checking the data for themselves!
I had assumed you shared this data-based approach to science & were genuinely interested in reaching a scientifically rigorous & robust explanation. Was I wrong?
P.S. As far as I’m concerned you still haven’t answered my June 21, 2014 at 3:43 am comment. If you genuinely want to continue the discussion, I don’t mind (although I’m not sure what the other commenters on this thread think??).
But, if you just want to claim people who are unimpressed by your opinion-based theories are “ignoran[t] in/of/on a subject matter being discussed” & just saying “crapolla” and/or “BS”, then go ahead…
Ronan Connolly says:
June 23, 2014 at 3:05 pm
“I did ask you to back up your opinions with the experimental data/observations that you used for reaching your conclusions.
I maintain science should be based on experimental data, not just opinions.”
—————
Ronan,
That means that you discredit 80+% of all science, ….. is that correct?
All opinions voiced by Stephen Hawking.
All opinions voiced by Einstein.
90+% of all opinions voiced by Astronomers.
And 95+% of all opinions voiced by psychiatrists, psychologists and neural research scientists.
RIGHT? All discredited by you.
And last but not least, you discredited Arthur C. Clarke for his silly opinion concerning a geostationary satellite, …… right?.
Ronan, , why in hell are you asking for my “experimental data” when it should have been plainly obvious to you that none was need or required? I dun told yu, …. the pictures “speak for themselves”.
Ronan, the “funny” thing about an “original thinker” ….. is the fact that it usually “takes one to know one”, …… and those that are “not one” are highly prone to DISCREDIT those that “are one”.
Ronan, me thinks you have been “brainwashed”, badly nurtured and/or miseducated with a “religious belief” that Degree status and/or employment title/position automatically and selectively ……. “trumps” common sense, logical reasoning, intelligent deductions and/or “original thinking”.
Science does not bow to any Monarch or Titled gentry.
Fer shame, fer shame, … because those who ascribe to the aforesaid will never be as smart as, … or smarter than, ….. their mentors are.
Ronan, here is a “link” to some “original thinking” commentary which is solely the result of “my learned opinion” ….. and which was not based in/on any data resulting from my doing of any “experimental research” of the subject matter ….. and which maybe you would care to offer your … discrediting critique of said, to wit:
http://snvcogar.newsvine.com/_news/2013/04/24/17899899-biology-of-a-cell-genetic-memory-verses-environmental-memory
Hi Samuel,
I suspect we might be talking at cross purposes (or perhaps shouting at cross purposes!)
I never said opinions were irrelevant for science! I said,
(highlighted for emphasis)
There are apparently many different approaches to “doing science”. However, my approach to science is a strongly empirical one – I have always favoured the “data is king” approach, similar to what Feynman suggested in his classic 1964 lecture:
[youtube http://www.youtube.com/watch?v=OL6-x0modwY&w=420&h=315%5D
I also agree with a lot of what Karl Popper said in his 1963 “falsification” essay.
But, other scientists take other approaches. For instance, a number of philosophers (Kuhn, Feyerabend, etc.) have strongly criticised Popper’s “falsification” approach, and said it’s not how science is usually done, e.g., here.
So, when I said ”I maintain science should be…”, I wasn’t saying “science is…” – different scientists take different approaches to “doing science”. I was explaining that I personally favour the “data is king” approach.
It sounds like you prefer the “theory is king” approach – is that right? If so, you’re not alone. A lot of scientists seem to prefer the “theory is king” approach… and these days, even the “computer model is king” approach (particularly popular in climate science, it seems!)
I’m not sure where you got this impression. But, nothing could be further from the truth. As I mentioned above, I favour the “data is king” approach to science.
“Nature” doesn’t care what we happen to think, what degrees we got, who our parents were, etc. That’s actually why I’m more interested in what the data says, than in people’s opinions of what the data should say.
I’m definitely interested in people’s opinions… but when it comes to drawing conclusions, I always try to go back to the data, and figure out what “Nature” is saying…
On your article on how the brain stores memory, it’s a good article. I think your concept of distinguishing between “genetic memory” and “environmental memory” is useful.
Have you heard of the studies of London cab drivers by Eleanor Maguire (and others)? There’s a short summary here.
Apparently, the hippocampus part of the brain is much larger than average in London cab drivers because they have to develop a very strong spatial memory of the city – although, perhaps it’s not as important now that cab drivers have GPS machines. It seems that the size of the hippocampus increases the longer the cab drivers have been driving and before training their hippocampus is average in size. So, this indicates that we can & do alter our physical brain structure depending on our mental activity. Does this fit into your “environmental memory” concept?