Archive for the ‘anthropogenic CO2’ Category


Barack Obama: Glaciologist

September 6, 2015

The avid outdoors-man and eminent scientist, Barack Obama, has been trekking through Alaska lately.  He is lamenting the demise of the great glaciers of the North.  He is surely grieving over the harm that man is inflicting on the planet by spewing his toxic CO2.  The Washington Post reports

Standing near the foot of the Exit Glacier, which has receded 1.25 miles since 1815 and 187 feet last year alone, Obama said “this is as good of a signpost of what we’re dealing with it comes to climate change as just about anything.”

The man certainly has a way with words – a true poet.

I guess we are supposed to be alarmed because 187 feet per year is a lot faster than 1.25 miles per 200 years.  After all, 1.25 miles in 200 years averages out to only 33 feet per year.  The message we are supposed to get is that the Exit Glacier is receding about 6 times faster now than its average over the last 200 years.  This, of course, is due to the CO2 that vile humans use to poison the atmosphere and it means endless and escalating disaster unless we socialize the economy of the world.

But what does the National Park service say about the retreat rate of Exit Glacier? The following table of retreat distances and rates comes from the National Park Service’s “The Retreat of Exit Glacier.” Annotation in red was added by me.

Exit glacier retreat annotatedSo, this data confirms Obama’s assertion that the Exit Glacier has retreated 1.25 miles in the last 200 years.  But it also makes it quite clear that it was retreating as fast, or faster, 100 years ago.

If CO2 is the culprit today, what was the culprit 100 years ago?  The following graph shows the amount of anthropogenic CO2 in the atmosphere as a function of time going back to 1750.  The data comes from Oak Ridge National Laboratory.  I made the plot and added the annotation. It’s kind of hard to explain why the retreat rate was so much greater in the past when there was less than 10% of the anthropogenic atmospheric CO2 than there is today.  Perhaps Professor Obama will elucidate.

anthro atmos carbonMy wife and I were up in Alaska a few years ago, and we also visited some some of those receding glaciers.  At Glacier Bay National Park, which is several hundred miles southeast of Exit Glacier, I happened to pick up a park pamphlet that had the following series of illustrations showing the glacier extents in the park going back to 1680.

glacier bay extents v3The first thing that jumps out at you is the rapid ice advance between 1680 and 1750 and the subsequent retreat between 1750 and 1880.  The pamphlet said

“The Little Ice Age came and went quickly by geologic measures.  By 1750 the glacier reached its maximum, jutting into Icy Strait.  But when Capt. George Vancouver sailed here 45 years later, the glacier had melted back five miles into Glacier Bay – which it had gouged out.”

As an aside, a co-worker once told me that the Little Ice Age was not a global phenomenon, but rather, local to Europe.  He cited the Union of Concerned Scientists as the source of this insight.  But there it is, in Alaska!

It is hard to argue with the Union of Concerned Scientists because they’re, well, scientists.  Not just anybody can be a Concerned Scientist.  You have to send a check first.  My wife used to send a check years ago, but it was from our joint account so I figure I was only half a Concerned Scientist then.  Now I guess I am just a wholly unconcerned scientist.

IMG_1546 v2Anyway, Obama was getting excited about 1.25 miles of glacier recession since 1815, and a whopping 187 feet in the last year.  That pamphlet that I mentioned also had a large map of the Glacier Bay area marking the location of the various glaciers back to 1760. It’s easy to string the locations together and calculate the recession rate of these glaciers.  The image at the left  shows the map as I marked it out for Grand Pacific Glacier. (Click to enlarge.)

I have plotted the distance as a function of time for three glacier routes using this crude method.   As you can see below, these glaciers have receded at a much faster rate than Exit Glacier.  But Exit Glacier and the Glacier Bay National Park glaciers have one thing common:  they all retreated at their maximum rate back when anthropogenic atmospheric CO2 levels were very low compared to today.

Glacier retreatLet’s take a closer look at the Grand Pacific Glacier.  John J. Clague and S. G. Evans (J. of Glaciology)  used various data sources to plot the retreat of the Grand Pacific Glacier.  I have converted their data to miles and overlaid it with my coarser data from the map. The Clague data and the map data agree nicely, but the Clague data fills in some of the gaps.  The most interesting point is that like Exit Glacier, the retreat rate for the Grand Pacific Glacier was greatest around the last part of the 19th century. In fact, the Clague data may indicate that the Grand Pacific Glacier was slightly progressing, not retreating, during most of the 20th century.

Grand Pacific Glacier retreatIt is pretty clear that the Grand Pacific Glacier was retreating fastest around 1860.  Where is that on the anthropogenic atmospheric CO2 timeline?  The graph below shows that the anthropogenic atmospheric CO2 level was only about 2% of today’s level when the Grand Pacific Glacier was retreating at its fastest by far!

CO2 and Grand PacificHow is that possible???????  I thought it was high CO2 levels that caused the glaciers to recede.


The Guardian: “China is slowing its carbon emissions.” Huh?

November 27, 2013

Left-wingers in the US have a need to see everything European as superior to American.  But it may be a necessity of left-wingers in general see some other culture as preferable to their own.  So if you are a European left-winger, who do you look up to?  Certainly not the United States!  That’s what China is for!

So a few days ago Jennifer Duggan, in her Guardian column said “China’s action on air pollution is slowing its carbon emissions.”  Maybe Duggan doesn’t know the difference between first and second derivatives and meant to say “China is reducing its acceleration of carbon emissions,” but even that wouldn’t be true.

Duggan tells us…

The latest Climate Change Performance Index published by Germanwatch and Climate Action Network Europe suggests that China is taking action to clean up its act as it tries to deal with its hazardously high levels of air pollution.

The report states:

“Recent developments indicate a slower growth of CO2 emissions and a decoupling of CO2 growth and GDP growth. Both, its heavy investments in renewable energies and a very critical debate on coal in the highest political circles, resulting from the heavy smog situation in many towns, give hope for a slower emission growth in the future.”

OK, sure, “slower growth of CO2 emissions.” Whatever you say Jennifer.

There is rhetoric – and there is reality.  Here is some reality.


BEIJING — China’s coal consumption is expected to hit 4.8 billion metric tons by 2020, the China National Coal Association (CNCA) forecast on Sunday.

CNCA data showed that China’s coal output increased to 3.65 billion tons last year from 2.35 billion tons in 2005, representing an annual increase of 190 million tons. Consumption in 2012 stood at 3.52 billion tons.

So, going from 3.65 billion tons this year to 4.8 billion tons in 2020 represents neither a decrease in usage (first derivative) nor a decrease in the rate of increase (second derivative).


From Trends in Global CO2 Emissions: 2012 Report from PBL Netherlands Environmental Assessment Agency, here are the CO2 emissions per region from 1990 to 2012…

Global CO2 emissions per region

By the way, how does Chinese emission acceleration compare to US emissions acceleration?

China vs US


From the 2014 China International Electric Power & Electric Engineering Technology Exhibition webpage

China’s five-year plan ending in 2015 envisions adding 520 GW to its current power production, expanding its capacity by 54%. Coal will be the primary source of energy in this increase…Coal-fired plants will contribute 58% of the increase in 2015 to remain the largest contributor to China’s power generation.


From Reuters, October 14th 2012

Coal, propelled by rising use in China and India, will surpass oil as the key fuel for the global economy by 2020 despite government efforts to reduce carbon emissions, energy consultancy firm Wood Mackenzie said on Monday…

The two Asian powerhouses will need the comparatively cheaper fuel to power their economies, while demand in the United States, Europe and the rest of Asia will hold steady.

“China’s demand for coal will almost single-handedly propel the growth of coal as the dominant global fuel,” said William Durbin, president of global markets at Woodmac…

China – already the top consumer – will drive two-thirds of the growth in global coal use this decade. Half of China’s power generation capacity to be built between 2012 and 2020 will be coal-fired, said Woodmac…

“If you take China and India out of the equation, what is more surprising is that under current regulations, coal demand in the rest of the world will remain at current levels,” Durbin said.

In Southeast Asia, coal will be the biggest winner in the region’s energy mix. Coal will generate nearly half of Southeast Asia’s electricity by 2035, up from less than a third now, the International Energy Agency said in early October…

This will contribute to a doubling of the region’s energy-related carbon dioxide emissions to 2.3 gigatonnes by 2035, according to the IEA.


The United Stages’ Energy Information Administration’s evaluation of China’s energy consumption (2012) shows us the breakdown of the fuel types for China’s electricity production for the last two decades.  Do you see the difference in trends for “Total Fossil Fuels” and “Other Renewables?”  You may need a magnifying glass to see it.

2010 china electricity by type from EIA

Air Pollution is out of control in China.

There is no doubt that simply breathing in many Chinese cities can be hazardous to your health.  But CO2 is not the source of that hazard – it is other gasses and particulates that are destroying people’s lungs.  There is also no doubt that China will continue full-bore toward energy-consuming industrialization.

I expect that improvement (if any) in Chinese air quality in the near future will come in the form of particulate removal.   But CO2 emissions will grow and grow and grow in China.


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,, (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