Posts Tagged ‘CO2’

“Well mixed” Carbon Dioxide Part 2: Sources and Sinks

June 26, 2016

Following from Part 1 (North vs South), this post looks at current sources and sinks for CO2.

Here are some images of surface CO2 concentration for today (June 26 in Australia) from nullschool.

Darker areas show lower CO2, lighter areas are higher.  I recommend the nullschool site!

Europe:

Europe

The industrialised Ruhr valley appears to have the highest CO2 concentration.  Paris Berlin and London are difficult to identify however.

South America (Argentina):

Buenos Aires

The high concentration appears to be from Buenos Aires- perhaps the satellite image of the CO2 is 200 km off target?

China, Korea, and Japan:

China Korea Japan

The highest concentration appears to be close to Japan’s larger cities.  Eastern China, including Shanghai and Beijing, is around 402ppm.

Southern Africa:

S Africa

Kinshasa and Johannesburg are close to the high concentrations, but dry season fires could also be the cause.

Indochina:

Indochina

Oddly, the high concentration is to the south west and west of Hanoi in a rural region.

USA:

USA

A large part of the USA seems to be one vast carbon sink at the moment.  New York and Chicago areas could be associated with some higher CO2, and there are those two areas in California, one of which I identified as Los Angeles in the previous post.  Now I’m not so sure.  More later.

Kamchatka yesterday:

high co2 kamchatchka peninsula

And today:

kamchatchka peninsula 26 june

The Kamchatka Peninsula features many active volcanoes and that’s what I think we are seeing here.  Yesterday afternoon the concentration peaked at 509ppm and today is down a lot but the “hot spots” are still distinct.

Australia:

Australia

Again inland eastern Australia is a carbon sink with large areas under 390ppm.  Melbourne may be the cause of a 408ppm area, but where is Sydney? Brisbane? Perth? Adelaide?

Southern California:

California

Note San Francisco does not appear to have over high CO2.  One of the high areas is indeed over the Los Angeles area, but the other is in the mountains to the north:  Kern County to be precise, where a bushfire has broken out.  The other ‘haze’ appears to be from the Santa Barbara fire.  See this map of fire locations.

firemap usa

It seems to me that it is hard to identify strong sources of CO2 associated with the world’s large cities and industrial areas.  However, it is the weekend, so perhaps this will change during the coming week.  We shall see.

On the other hand, very strong sources of CO2 can be traced to volcanoes and bushfires, and also decaying vegetation in the dry season.  Sinks as we have seen are clearly associated with rapidly growing crops, grasslands, and forests.

And today the Equatorial Pacific sink appears to match the cooler water being pushed westwards by the strengthening trade winds.  See for yourself at nullschool.

I will continue to monitor these sources and sinks as the seasons progress.

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“Well Mixed” Carbon Dioxide Part 1: North vs South

June 24, 2016

This post addresses the question: How “well mixed” is carbon dioxide in Earth’s atmosphere?

Here are some images of surface CO2 concentration for yesterday (June 23 in Australia) from nullschool.

Darker areas show lower CO2, lighter areas are higher.  Very nifty.

Fig. 1:  Northern Hemisphere CO2:

co2 image NH

The dark areas with low CO2 are the northern forests and farm land, now growing strongly.  Note the cold, dry North Pole has high CO2.

Fig. 2: Southern Hemisphere:

co2 image SH

Cold, dry Antarctica has high CO2, whereas a broad area of inland Eastern Australia, which recently has had some decent rain, has lower CO2.

Fig. 3:The East:

co2 image EH

Fig. 4: The West:

co2 image WH

The contrast in South America is interesting!

Fig. 5:  The Pacific (a hemisphere on its own):

co2 image Pacific

Note the northern Pacific (north of 5 degrees north) is predominantly above 400ppm, while a broad band from about 5 degrees north to about 20 degrees south is about 395ppm.

Note also a tiny area in southern California pluming into the Pacific with a very high reading of 437ppm.  Los Angeles.

The IPCC and climate scientists generally refer to data from Mauna Loa in Hawaii.  The CSIRO in Australia also measures CO2 concentration at Cape Grim in Tasmania.  The next few charts compare Cape Grim data with that of Mauna Loa.

Fig. 6:  Comparison Mauna Loa and Cape Grim CO2 1976-2016

ML v CG co2

Here is a closer look at the most recent years:

Fig. 7:  Comparison Mauna Loa and Cape Grim CO2 2010-2016

ML v CG co2 2010-16

There are several points to note:

Cape Grim CO2 concentration is increasing at the same rate as Mauna Loa.

There are massive swings in Mauna Loa’s data, while Cape Grim fluctuates gently.  In 2016 there was no “bottom” at all.

Cape Grim is much lower- in fact the annual high points are at about the same level as Mauna Loa’s low points.

The records are out of phase.  Mauna Loa peaks in northern spring and bottoms out in northern autumn, whereas Cape Grim peaks in southern Spring and “bottoms out” in southern Summer.

Now I look at the seasonal change in concentration.

Fig. 8:  Seasonal rises and falls at Cape Grim

Inc decr CG

Fig. 9:  Seasonal rises and falls at Mauna Loa

Inc decr ML

Notice at Mauna Loa the annual rises from bottoms to peaks are getting larger, but so are the falls, while at Cape Grim there are slower rises but falls are lessening.  I compare rises and falls separately in the next two plots:

Fig. 10:  Seasonal increases compared

Incr ML v CG

Fig. 11:  Seasonal decreases compared

Decr ML v CG

I would interpret this as follows:

As emissions increase, carbon dioxide sinks (mainly growing plants) consume more and more.  However this is not enough to remove all of the additional CO2, so each year the growth continues.

In the Northern Hemisphere, sinks completely overwhelm sources in summer.

In the Southern Hemisphere there is a much less pronounced annual peak in spring, perhaps because there is less land, especially from 30 to 70 degrees south, and much of it is dry.  CO2 concentration has increased to the level at which vegetation CO2 sinks are becoming unable to make an impression (at least in El Nino years).

The bulk of CO2 increase originates in the Northern Hemisphere.  In northern winter as the Inter-Tropical Convergence Zone shifts south of the Equator, the north east trade winds move CO2 to the Southern Hemisphere where it is gradually mixed.  In northern summer (now), the ITCZ is north of the Equator, and the image of the Pacific in Figure 5 above shows trade winds crossing the Equator with less CO2 concentration than just to the north.

We know there are large changes to CO2 concentration following ENSO events.  This may be due to the changing circulation over the tropical Pacific as more or less CO2 is shifted by trade winds north and south. Or perhaps changing ocean currents, upwelling, or downwelling warm or cool large ocean areas.

Drier areas of the globe (deserts, Polar regions) have higher CO2 concentration than wetter areas.  Few growing plants, more CO2.  More and greener plants, less CO2.

And finally: CO2 is not “well mixed” globally, and an average concentration is as elusive as an average temperature.  There is a range of concentrations between areas of sources and sinks approaching 80ppm.

Theory and Reality- Part 1: DTR

February 2, 2016

It was two years ago in 2013 that I last posted on the difference between climate scientists’ expectations and reality, so in this series of posts I bring these points up to date, and add a couple of related points.

What the climate scientists tell us:

Dr Karl Braganza in The Conversation on 14/06/2011 lists the “fingerprints” of climate change (my bold).

These fingerprints show the entire climate system has changed in ways that are consistent with increasing greenhouse gases and an enhanced greenhouse effect. They also show that recent, long term changes are inconsistent with a range of natural causes…..
…Patterns of temperature change that are uniquely associated with the enhanced greenhouse effect, and which have been observed in the real world include:
• greater warming in polar regions than tropical regions
• greater warming over the continents than the oceans
• greater warming of night time temperatures than daytime temperatures
• greater warming in winter compared with summer
• a pattern of cooling in the high atmosphere (stratosphere) with simultaneous warming in the lower atmosphere (tropopause).

and later

Similarly, greater global warming at night and during winter is more typical of increased greenhouse gases, rather than an increase in solar radiation.

This post will examine “greater global warming at night” and whether it can be attributed to increased greenhouse gases.

If night time temperatures (minima) increase faster than day time temperatures (maxima), then the difference between these, the Diurnal Temperature Range (DTR) will decrease.

I use BEST global land temperature data,

http://berkeleyearth.lbl.gov/auto/Global/Complete_TMAX_complete.txt
http://berkeleyearth.lbl.gov/auto/Global/Complete_TMIN_complete.txt

and annual CO2 concentration data from NOAA.

ftp://aftp.cmdl.noaa.gov/products/trends/co2/co2_annmean_mlo.txt

Fig. 1: Global DTR (derived from BEST Land Tmax and Tmin)

DTR globe

Yes, the long term linear trend shows globally DTR has decreased, at a rate of more than half a degree Celsius per century.

Case closed! That is, if you ignore the sudden turnaround in the early 1980s. Since then DTR has been increasing at +1.1C per 100 years.

The plot showing the relationship with CO2 concentration is even more revealing:

Fig. 2: Global DTR vs CO2 concentration

globe dtr v co2 all

If we break the series in two at the dogleg, we get the following plots:

Fig. 3: Global DTR vs CO2 concentration to 1982

globe dtr v co2 1

Fig. 4: Global DTR vs CO2 concentration 1982 to 2015

globe dtr v co2 2

Calling Global Warming Enthusiasts! I am puzzled:

Is DTR decreasing at 1.14 C/ 100 ppm CO2 or increasing at 0.61 C/ 100 ppm?
Can there be any logical explanation for this distinct turnaround?
Is there a problem with (a) the CO2 concentration data? (b) BEST data? (c) the theory behind decreasing DTR being an indicator of enhanced greenhouse warming? (d) all of these?

I now turn to the Australian context, with Australian surface data.

Fig. 5: Annual DTR Australia (from ACORN)

DTR Aust

While averaged across Australia, DTR has decreased since 1910, there has been a marked increase recently. As well, the pattern is different in different regions.

Fig. 6: DTR North Australia

DTR Aust nth

Fig. 7: DTR Southwest Australia

DTR Aust SW

Fig. 8: DTR South Australia

DTR Aust SA

Fig. 9: DTR Victoria

DTR Aust Vic

Fig. 10: DTR Tasmania

DTR Aust Tas

The effect is strongest in the tropical northwest and northeast, and weakest in the southwest and South Australia, Victoria, and Tasmania.

Moreover, the dominant influence on DTR is rainfall:

Fig. 11: DTR vs Rainfall

DTR Aust vs rain

Definitely not CO2!

Fig. 12: DTR vs CO2 concentration

DTR Aust vs CO2

Assessment of decreased DTR as evidence for the enhanced greenhouse effect: Fail.

Other factors- especially rainfall- overwhelm the enhanced greenhouse effect.

UPDATE:

Perhaps I should be more blunt:  If Global Warming Enthusiasts stick to decreasing DTR as an indicator of greenhouse warming, then this shows BEST and ACORN surface data are completely unreliable.  If they stick to claiming ACORN and BEST are “world’s best practice” then they must accept that DTR as an indicator of greenhouse warming is a dead duck.

Energy, Carbon Dioxide, and The Pause

December 16, 2015

Here’s an alternative way to view The Pause. Rather than analysing temperature trends over time, here I compare temperature with carbon emissions and carbon dioxide concentration, and on the way look at a couple of interesting facts that need highlighting.

I use energy data from the BP Statistical Review of World Energy 2015, CO2 data from NOAA, and Temperature data from UAH.

I need to get two important issues out of the way.

Firstly, total energy consumption. Figure 1 shows global energy consumption from all sources for 2014.

Fig. 1: Global Energy Consumption in Million Tonnes of Oil Equivalent
energy 1965 2014

I aggregated coal, oil, and gas into one fossil fuel category. It is plainly obvious that fossil fuels are going to be around for a long time, unless there is a massive multiplication of (a) nuclear energy production, which may not appeal to some environmentalists, or (b) hydro-electricity dams, but that may not appeal either, and are there enough rivers?, or (c) windfarms and large scale solar, with storage, to produce 30 times what they produce now just to meet current demand. Cheap, reliable energy supply is going to depend on technological breakthroughs in the next 100 years and fossil fuels in the meantime.

Secondly, the recent increase in carbon dioxide concentrations is almost entirely anthropogenic.

Figure 2: CO2 concentration as a function of global energy consumption from 1965 to 2014:
Energy vs co2

99% of CO2 increase can be explained by energy use in all forms.

Now, before Global Warming Enthusiasts drool all over their keyboards, let’s look at how this relates to temperature.
I have calculated 12 month running means of CO2 concentration and TLT anomalies. From November 1979 to November 2015- CO2 concentration increased from 336.6 ppm to 400.57 ppm. What happened in this period to global lower troposphere temperatures- arguably a better indicator of global warming than surface temperatures because they show what the bulk of the atmosphere is doing?

Fig. 3: Tropospheric temperature anomalies vs CO2 concentration:
TLT vs CO2 78-15

43.5% of the temperature increase over the satellite era can be explained by/ is associated with the increase of about 64 ppm of CO2. The relationship is anything but linear, however the linear trend indicates, if warming continues at the same rate while CO2 increases by 100 ppm, that temperature anomalies will increase by about 0.63C. By this estimate, doubling CO2 concentration from 280 ppm (what many believe to be pre-industrial concentration) will result in a temperature increase from whatever the global temperature was 250 years ago, of 1.76C. According to HadCruT4, we’ve already seen about 0.8C increase since 1850, so we’re nearly halfway there! Not only that, but we’ll stay below 2 degrees of warming without the need for any emissions reductions!

But the temperature increase is not linear. The next plot shows the tropospheric temperature/ CO2 relationship while temperatures have paused.

Fig. 4: TLT vs CO2, from 363 ppm to 400 ppm:
TLT vs CO2 Pause

That, my friends is the true indicator of The Pause: while CO2 has increased by almost 37 ppm (out of 64 ppm), temperature has remained flat. The trend is +0.01C per 100 ppm CO2.

Finally, I’ve separated the record into three phases: before, during, and after the large step change in the 1990s culminating in the 1997-98 El Nino and the following La Nina.

Fig. 5: Temperature vs CO2 during the first phase, when CO2 increased by 20 ppm:
Phase 1

Fig. 6: Temperature vs CO2 during the second phase, when CO2 increased by about 14 ppm:
Phase 2
Fig. 7: Temperature vs CO2 during the last phase, when CO2 increased by about 29.3 ppm:
Phase 3

Therefore I conclude:

Barring a miraculous breakthrough, renewable energy has no hope of replacing cheap, reliable fossil fuels in the foreseeable future- thankfully!
Greenhouse gas increase is anthropogenic;

CO2 increase has probably caused some small temperature increase;

The relationship between CO2 and temperature in the satellite era is weak, with 58% of the CO2 increase occurring while temperatures have paused;

Therefore temperature change is probably caused mainly by natural factors;

Even if the long term “linear” trend continues, this rate is not alarming, and would lead to a temperature increase during a doubling of CO2 of less than 1.8C.

I find it amusing that Global Warming Enthusiasts pin their hopes for an end to The Pause on a strong El Nino- in other words, on natural variability, the very thing that is supposed to have been overwhelmed by greenhouse warming.

The end of the scam is nigh!

Adjustments vs CO2

August 3, 2014

Steven Goddard has posted about the remarkable correlation between USHCN adjustments and atmospheric carbon dioxide concentrations:

goddard co2

Here’s my plot of Australian adjustments to minima, Acorn minus raw vs CO2 data (downloaded from NASA GISS at

http://data.giss.nasa.gov/modelforce/ghgases/Fig1A.ext.txt ):

acorn vs co2

R2= 0.777 not as impressive as 0.988, so not proof of anything except past cooling adjustments which we already knew.  Interesting all the same.

No Evidence of Greenhouse Warming for 67 Years!

January 8, 2014

The release of 2013 data by the BOM has provided me with plenty to work on.  Various commentators are busily alarming people by claiming that the hottest year on record is an indication that global warming due to the enhanced greenhouse effect is already impacting Australia.  What is most disappointing is that the BOM has done nothing to report the truth: that while Australia has definitely been warming, and breaking records, the data show no evidence of greenhouse warming.

One of the key indicators of warming uniquely associated with the enhanced greenhouse effect is night time temperatures (minima) increasing faster than daytime temperatures (maxima).  The difference between the two is called the Diurnal Temperature Range, or DTR.  So, decreasing DTR would be evidence of greenhouse warming.

Here is Australian DTR since 1947:dtr1947-2013

That’s dead flat or slightly rising for 67 years!

I couldn’t believe it either, and double checked.  There’s no mistake- DTR shows no evidence of greenhouse warming in Australia, with a flat trend for 67 years.

Still No Evidence of Greenhouse Warming!

January 8, 2014

This morning I noticed at Jennifer Marohasy’s post http://jennifermarohasy.com/2014/01/last-year-2013-a-hot-year-for-australia/

a comment from “Luke” (who else) objecting to my use of 2nd order polynomials in yesterday’s post.  Strictly I should stick to linear trends for a 35 year timescale, and use polynomials only for much longer periods.   Therefore, here is a plot of Australian annual minima and maxima for the 104 years from 1910 to 2013, using data straight from the BOM.minvmax poly2

Note that the red 2nd polynomial curve (maxima) shows a fairly flat trend until the 1950s, with an increasing rise since then. (Yes! It’s getting hotter!)

Note how the blue (minima ) curve also gradually rises over the years and apparently continues to do so.

However I have circled the graphs in the 1980s and the last few years.   I have blown this up so you can see more clearly what is happening.minvmax blownup

Since the mid 1980s there is a divergence in trends.  Daytime temperatures are rising faster than night time temperatures.

This is a problem because increasing CO2 and other greenhouse gases should be slowing back radiation, which should be evident in night time temperatures increasing faster.

Something else is happening.

 

2013 Minimum Temperatures Released

January 2, 2014

Ken Stewart, 2 January 2014

UPDATE 3 January: BOM has updated it’s time series graph, but not the raw data, which still finishes at 2012! See below.

I have calculated the annual 2013 minimum temperature anomaly for Australia, well before the Bureau of Meteorology.

Not including the 8 sites acknowledged as having anomalous warming due to the Urban Heat Island (UHI) effect, I calculate the straight mean (without area averaging) to be +0.82 C.  This puts 2013 as second warmest after 1998, and just ahead of 1973 and 1988.

I expect that the BOM will publish a figure of around +1.2C, and claim 2013 as the warmest on record for minima.

I calculated this by using daily Acorn data for 1910 to 2012 from http://www.bom.gov.au/climate/change/acorn-sat/  , plus daily minima for 2013 for these same sites from Climate Data Online.  I used Acorn data from 1961-1990 to recalculate monthly means for each site, and then calculated running centred 31 day means to estimate daily means for the same period.

Then I calculated daily anomalies for each site, and amalgamated these into a straight mean for Australia.

The result is as follows:

Fig. 1:  365 day running mean of daily data.acorn 365d 1910-13 no uhi

I will analyse Fig. 1 in some detail later.  But first, how does my calculation stack up against the BOM super computer?

Fig. 2: Annual (31 December each year) means of minima 1910 to 2012.Acorn ann v me 1910-12

My calculation is in green, BOM in red.  As you can see, the match is pretty close, and of course I have not used any area averaging.  But you would expect the results to be close, as I have used exactly the same data.  You will notice that the major differences occur in years of higher or lower than normal minima.  These appear to have become larger in the last 40 years.  The official annual figures show greater extremes, as shown above.

I have also calculated trends for the 1910 to 2013 period, and hope that this will persuade you of the futility of using linear trends for temperatures, and that if you cherry pick you can prove just about anything.  The next graph is a plot of the continuous running trend from 31 December 2013 all the way back to 1 January 1910.  That is, the linear trend through datapoints between any selected date and 31 December 2013.

Fig. 3: Continuous running trend, daily minima anomaliescont trend Oz no uhi

The vertical axis measures trend in degrees Celsius at particular points in time.  Note the rapid fluctuations at the right hand end.  I’m sure no one would be silly enough to calculate trends of only a few years’ data.

As the time period increases (moving from right to left) the fluctuations smooth out.  Note that Australia has had zero trend in daily minima since 21 July 1997.  Interesting, but no predictor of the future.

Moving further back in time, the plot shows the temperature trend increasing until the early 1940s.  Up until then the long term trend is fairly stable.  Since 1910 the trend is about 1.1C per 104 years.  The maximum trend can be calculated from 1922. Therefore, a cheerful cherrypicker can choose whatever time frame they like to produce a linear trend that suits.

Back to my graph of the 365 day running means of daily temperatures. Figure 1 again:acorn 365d 1910-13 no uhi

Note that the 365 day mean peaked in early November 2013 and has dropped since then.  The peak was at +0.94C, which is still below that of 1998 and 2006.

But also note that the rise of about +1.1C over 104 years is by no means steady.  There are several sharp rises and falls along the way.  Let’s have a closer look at these.

Fig. 4: Step changes in temperatureacorn 365d 1910-13 no uhi stepups

I have shown (starting in 2014) how the minimum temperature record of Australia features a series of sharp step ups, followed by slow declines.  I have indicated the start of these periods and the linear trend lines of each one.  There may have been one in 1926, and 2013 may (or may not) be the start of another such period.  They are more frequent and more pronounced in the past 40 years than in the first 60 years.  This appears to show a link to natural climate forces, such as the El Nino- Southern Oscillation.

I will analyse these results further in future posts, and may do the same for maxima as well.  (People are interested in maxima because “that’s how hot it is”.  I like minima because they tell you more about climate e.g. if they increase faster than maxima this may indicate greenhouse warming.)

Watch for the official 2013 minimum temperature anomaly:  probably +1.2C.

Update 3 January:

Here is the official BOM graph to 2013:

timesereis tmin to 2013

and it looks like a bit over +0.9C  +0.94 C, so less than I expected and closer to mine.

No Warming in North Australia for 31 Years

December 23, 2013

I’m nearly a year late with this, but I’ve only just noticed.

According to the Bureau of Meteorology’s official temperature records, for all of the Northern Australian region- the half of the continent north of 26 degrees South- the minimum temperatures are steadfastly refusing to rise.  From 1982 to 2012, the linear trendline for minima is on the decreasing side of dead flat.

Acorn tmin Nth Oz 82-12

This is longer than the 3o years regarded as the minimum period for analysing climate trends, and in spite of the massive increase in amount of CO2 emissions.  Note that 1982 and 2011-2012 were almost equally cooler than normal.

Remember  that one of the fingerprints of greenhouse warming is that minima should be increasing more than maxima.

Here is the 365 day running mean of daily minima anomalies of all Acorn sites in Northern Australia (more about this next year) up to early December this year:

tmin nth aust 1910-13a

Rather than a smoothly rising trend, the record is characterised by 10 to 15 year rapid rises and falls, responding to events in the Pacific and Indian Oceans.

This is a diagram of Australia’s climate regions:summer1213  regions

After New Year I will post about minima for other regions and Australia as a whole.

Merry Christmas to all.

Inter-annual change in SOI and Carbon Dioxide

March 23, 2012

Ken Stewart, March 2012

Last April I demonstrated that changes in temperature precede changes in the concentration of atmospheric carbon dioxide.

Here I look at the increase in CO2 concentration more closely, and how it relates to atmospheric temperature and the Southern Oscillation Index (SOI).

There is no doubt that CO2 concentration has been rising, certainly since 1959, and that isotopic analysis shows this is largely due to fossil fuel burning.

But there’s more to the story.

This is a graph of CO2 concentration for the past 5 years, 2007-2011.

Fig.1

Some points to note:

The regular seasonal wave shows fluctuations.

There is a marked slowdown in February and March 2008 (following the temperature drop in the previous year), and another blip in March 2009 (resulting from the drop in energy consumption in late 2008.)

There is another slowdown in February, March, and April 2011.

The difference between consecutive peaks, and between troughs, varies each year.

These inter-annual differences interest me.

Here is a graph of the inter-annual monthly differences- the difference between the same months in consecutive years, e.g. January 2010 and January 2011.

Fig. 2

2010 was a very good year for CO2 increase.

Note the huge slump in the rate of increase in April 2008, and the even bigger and longer slump around April 2011.  In fact, April 2011 had the lowest inter-annual difference since July 2000.

The recent State of the Climate report claims that “Global CO2 concentrations in the atmosphere increased from 2009 to 2011 at 2 ppm per year” which is correct- the concentration in December of each year has risen by 2ppm. This was entirely due to 2010 however- by December 2011 the annual mean rise in concentration was down to 1.8ppm. 2011 was a below average year for CO2 increase. The BOM and CSIRO failed to mention this, I notice!

By comparison, here’s the same inter-annual rate of change for 1997 to 2001:

Fig. 3

There’s no comparison, is there?

Here’s a graph (2007- 2011 again) showing the relationship between rate of change of temperature and rate of change of CO2.  The temperature change has been doubled, and brought up to the same scale as CO2 change (2 is average).

Fig. 4

Notice once again that rapid temperature change precedes CO2 change by a couple of months. However, other factors may be involved.  Notice mid-2009.

Let’s zoom out and look at the 25 years from 1987 to 2011- actually, these plots show data up to February 2012.

Fig 5.  Temperature change vs CO2

I have marked in the eruption of Pinatubo, and the El Nino event of 1997-1998.  CO2 change can still be seen lagging temperature change.

Now compare temperature change with SOI change. Note that SOI values are inverted.

Fig. 6 Temperature change vs SOI change

Note: temperature change clearly lags SOI change by many months.

It has long been known that there is a link between ENSO events and CO2 concentration.  So can we see a relationship between inter-annual change in SOI and CO2?

Fig. 7 SOI change vs CO2 change

There is at least 10 months lag between SOI and CO2 change.

Now, smoothing with 12 month means:

Fig. 8: CO2, UAH, SOI changes

Applying 10 months lag to the SOI and 4 months lag to temperature:

Fig. 9: lagged SOI and UAH:

A pretty good match. El Ninos cause rapid CO2 increase. La Ninas and volcanoes are associated with slower CO2 increase.

Removing UAH shows the closer relationship between SOI and CO2.  Here the 12 month mean of SOI change has been advanced 10 months.

Fig. 10

Notice that in strong ENSO events the inter-annual change in CO2 can vary by more than 2 ppm per year.

Fig. 11

The 12 month mean of raw SOI (scaled: /20, +2) shows El Ninos occurring nearly a year before CO2 increase; La Ninas have a weaker match.

Here are graphs of SOI vs CO2 since 1959:  There are gaps in the CO2 mean because of missing months of data, after which 12 month means cannot be calculated.

Fig. 12

Notice the same pattern: CO2 change lags SOI change by nearly a year.

Fig. 13: SOI change advanced 10 months. ENSO events are shown as well.

Notice the very close match.

We can conclude that:

  • CO2 concentration is increasing, and the rate of increase has doubled from 1 to 2 ppm per year in the past 50 years
  • There is seasonal fluctuation in concentration
  • CO2 concentration responds not only to temperature change but also to changes in the La Nina- El Nino cycle, nearly a year later.

The ENSO cycles strongly influence changes in CO2 concentration- not enough to overwhelm it, but enough to double or halve the rate of increase. Much more study is needed.

 

Data used:

http://vortex.nsstc.uah.edu/data/msu/t2lt/uahncdc.lt
ftp://ftp.cmdl.noaa.gov/ccg/co2/trends/co2_mm_mlo.txt
ftp://ftp.bom.gov.au/anon/home/ncc/www/sco/soi/soiplaintext.html