Archive for the ‘Mann’ Category

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Tree-rings: Proxies for Temperature or CO2?

February 15, 2010

Recall step 2 of the  five super-simple steps for building a hockey stick:

Step 2. Select those time series that fit the instrumental (measured) temperature record of choice. Assume that since these time series match the measured temperature in some way, then they are, in fact, temperature proxies.

This step begs the question (in the classical logical sense) about the usefulness of tree-rings as proxies for temperature.  Surely tree-ring width is not solely dependent on temperature, is it? 

What about drought conditions?  Usually we think of droughts as coinciding with high temperatures.  Would higher temperatures cause tree-rings to be thicker even when the tree is being stressed or dying due to lack of water?  Of course not.

What about the abundance of CO2? 

Back when I was a college student I worked at Phytofarms of America in DeKalb, Illinois, USA, which grew the highest quality leafy vegetables in a giant indoor,  innovative, artificially lighted, hydroponic facility.  One of the keys to this industrial sized facility was elevated CO2.  Huge tanks of CO2 pumped up the indoor level to about 1000 ppm, or about 4 times the pre-industrial level.  The resulting veggies were expensive, but they were the best money could buy.

Is it possible that tree-rings are better proxies for atmospheric CO2 than for temperature?   As a simple test, I selected all the tree-ring proxies used for Mann’s 2008 version of the hockey stick and did a simple correlation to the Northern Hemisphere instrumental temperature record and to the atmospheric CO2 record.  The tree-ring data and the instrumental temperature record came from the NCDC archive for Mann’s paper

 The CO2 data is a combination of Mauna Loa data (1959 to present) and the Siple Station ice Core (1744 to 1953).  The Siple data was not in yearly increments, so I interpolated.   I also interpolated between the end of the Siple data (1953) and the beginning of the Mauna Loa date (1959).  The Mauna Loa data was truncated beyond 2006 so that the CO2 data would cover the same time domain as the instrumental record used by Mann.

Results

The first graph below (click to enlarge) shows the 30 tree-ring time series with the best correlations to the instrumental temperature record.  Each of these correlations has been matched with the correlation to the CO2 level.  The first thing to jump out is that for 23 out of 30 cases, the CO2 correlation is better than the temperature correlation!

The next graph is the reverse situation.  It shows the 30 tree-ring time series with the best correlations to CO2 in descending order.  As above, each of these correlations is matched with the correlation to the instrumental temperature record.  This time the thing that jumps out is that the correlation to CO2 is better in every single case.  And these correlations to CO2 are not just a little better, they are a lot better.

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Amazing multiplying hockey stick proxies

February 3, 2010

In my previous post I wrote about the five super-simple steps for building a hockey stick:   

Step 1. Gather time series.
Step 2. Select those time series that fit the instrumental (measured) temperature record of choice. Assume that since these time series match the measured temperature in some way, then they are, in fact, temperature proxies.
Step 3. Combine the chosen proxies in some fashion and note, not surprisingly, that the combined proxies match the temperature record. (duh) Call this your temperature reconstruction.
Step 4. Call this thing made from the combined proxies your temperature reconstruction, and therefore assume that the combined proxies are also a match for the temperature that occurred prior to the temperature measurement records.
Step 5. Note that the reconstruction shows that the temperature prior to the instrumental data is relatively flat, and conclude that the temperature prior to the instrumental record changed very little.   

This post is about a little subplot in gathering of time series for the Michael Mann’s 2008 version of the hockey stick (Proxy based reconstructions of hemispheric and global surface temperature variations over the past two millenia, PNAS, 2008)   

Mann used 1209 proxies for this reconstruction.  He explains the breakdown as follows…   

We made use of a multiple proxy (‘‘multiproxy’’) database consisting of a diverse (1,209) set of annually(1,158) and decadally (51) resolved proxy series … including tree-ring, marine sediment, speleothem, lacustrine, ice core, coral, and historical documentary series. All 1,209 series were available back to at least A.D. 1800, 460 extend back to A.D. 1600, 177 back to A.D. 1400, 59 back to A.D. 1000, 36 back to A.D. 500, and 25 back to year ‘‘0’’ (i.e., 1 B.C.).   

Figure 1. Northern Hemisphere proxies in alphabetical order

 

Mann split his analysis between the Northern and Southern hemispheres.  I am going to talk about the 1,036 of the 1,209 proxies that applied to the North.  The following two images show the plots of the these 1,036 proxies, just click on them to enlarge.  The file sizes are less than a megabyte each and should open quickly in your browser.  Figure 1 is the plots arranged in alphabetical order.  If you scroll through this image you will see a lot of proxies that don’t look much like a hockey stick, and a few scattered here and there that do.  However, there is a series of 71 proxies named lutannt1 through lutannt71 that look very much like hockey sticks.    

These lutannt# proxies are from Pauling A Luterbacher, the researcher who “provided” them.  More on this important point later   

Figure 2. All Northern Hemisphere proxies in order of correlation with Northern Hemisphere instrumental temperature record.

 

As explained in the five easy steps for hockey stick construction, the proxies that look much like a hockey stick are likely to be weighted heavily in the final hockey stick construction.  If all the 1,036 proxies are correlated (For the math inclined: see correlation formula below) with the northern hemisphere instrumental temperature record, and the plots laid out from the worst correlation to the best, it will look like figure 2.  Scroll through this figure from top to bottom.  You will see the worst correlations at the top and the best on the bottom.  Note that the Luterbacher proxies are among the best correlated, and show up near the bottom.   

Figure 3. All Northern Hemisphere proxies, except Luterbacher proxies, in order of correlation with Northern Hemisphere instrumental temperature record.

 

Figure 3 is the same as figure 2, but with the Luterbacher proxies removed.  Scroll through, and it is quite clear that there are far fewer hockey stick-like proxies now.   

The Amazing Multiplying Proxies

Remember, the point of a hockey stick is not that it goes up in the 20th century – this is a given because the hockey stick is deliberately constructed from proxies that go up in the 20th century.  The real point is that it is more or less flat prior to the 20th century. (See step 5 of the super-simple steps for building a hockey stick.)  The 71 Luterbacher time series are tailor-made for this purpose, because they tend to show temperature rising in the 20th century but flat prior to that.  The problem with the 71 Luterbacher proxies is that they are actually not 71 separate proxies at all.    

Luterbacher, et.al., (European Seasonal and Annual Temperature Variability, Trends, and Extremes Since 1500, Science, 2004) used about 150 “predictors” spread out over Europe to reconstruct European surface temperature fields.  These predictors consisted of “instrumental temperature and pressure data and documentary proxy evidence.”    Figure 4, taken from Luterbacher’s  supplemental material, shows the geographical distribution of these predictors.   

Figure 4. Luterbacher's original caption: (A) station pressure locations (red triangles) and surface temperature sites (B, red circles) used to reconstruct the monthly European temperature fields (25°W-40°E; 35°N-70°N given by the rectangular blue box). Blue circles indicate documentary monthly-resolved data, blue dots represent documentary information with seasonal resolution back to 1500. Green dots stand for seasonally resolved temperature proxy reconstructions from tree-ring and ice core evidence.

 

 Lutenbacher used combinations of the predictors to interpolate the data to…   

“a new gridded (0.5° x 0.5° resolution) reconstruction of monthly (back to 1659) and seasonal (from 1500 to 1658) temperature fields for European land areas (25°W to 40°E and 35°N to 70°N).”    

Each of these grid points in the reconstruction is like one of the lutannt# graphs that show up in the list of proxies for Mann’s 2008 version of the hockey stick.  Mann ends up with 71 lutannt# “proxies” by simply taking 71 points using 5° x 5° resolution from Luterbacher’s temperature field reconstruction.   

Here’s  the rub: Not all the predictors used to make Luterbacher’s temprature field reconstruction go all the way back to 1500.  In fact, prior to about 1760 only about 10 of the total 150 predictors are used, and these predictors are primarily “documentary information.”  Prior to about 1660, only about 7 are used.   Figure 5, which also comes from Luterbacher’s supplementary material, shows the number of predictors used for each year to reconstruct his surface temperature fields.   

Figure 5. Luterbacher's original caption: Number of predictors through time.

 

Figure 6 shows the location of Mann’s 71 selected “proxies” and the location of the “documentary information” sources.  Not the best match in the world, is it?  Amazingly, the construction of some of the proxies prior to 1750 is based on data from sources over 1000 kilometers away!  

Figure 6. Blue dot show the location of Mann lutannt# "proxies." Red dots show the location of Luterbachers early "documentary information" sources.

 

 The important point is that all the data for Mann’s 71 lutannt# “proxies” prior to about 1760 is made up of some combination of the same 10 or so “documentary information” predictors.  This short list of predictors are the “Amazing Multiplying Hockey Stick Proxies.”  These 10 predictors are multiplied into 71 proxies, and these proxies all rank high for correlation to the instrumental temperature record from 1850 to the present.  Consequently, these 71 “proxies” likely weigh heavily in Mann’s 2008 hockey stick, and these 10 “documentary information” predictors, sometimes folded into “proxies” over a thousand kilometers away, have an undeserved multiplied effect in making the flat part of the hockey stick prior to the instrumental temperature record. 

****************************************** 

correlation coefficient: 

 

where P is the proxy, and Pi is the ith year of the proxy
T is the temperature, and Ti is the ith year of the temperature

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Super-simple hockey stick explanation.

January 31, 2010

I have been reading over the blog posts of Steve McIntryre and Jeff Id and others about the nuances of various constructions of the hockey stick.  I’ve been examining the archived Mann08 data at the NCDC.  This is my attempt to boil down hockey stick construction to its bare-bones, expressed as five essential steps:

Step 1. Gather time series.
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Step 2. Select those time series that fit the instrumental (measured) temperature record of choice. Assume that since these time series match the instrumental temperature record in some way, then they are, in fact, temperature proxies.
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Step 3. Combine the chosen proxies in some fashion and note, not surprisingly, that the combined proxies match the temperature record (duh!).
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Step 4. Call this thing made from the combined proxies your temperature reconstruction, and therefore assume that the combined proxies are also a match for the temperature that occurred prior to the temperature measurement records.
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Step 5.  Note that the reconstruction shows that the temperature prior to the instrumental data is relatively flat.  Make the important conclusion that the temperature prior to the instrumental record changed very little.

Defenders of hockey stick constructions will point out my naïvety with an endless list of nuances and subtleties involved in each of these steps.  But keep your eye on the puck.  The following picture illustrates the difference between my simple steps and their more nuanced approaches…

It’s important to examine those details and nuances at some time and place.  But sometimes they are simply a smokescreen.  Keep your eye on the hockey puck.

Coming soon to ClimateSanity: the Amazing Multiplying Proxies.