Archive for the ‘CO2’ Category

The Renewable Energy Transition

July 11, 2019

The Australian Greens’ number one aim in their Climate Change and Energy Policy is:

“Net zero or net negative Australian greenhouse gas emissions by no later than 2040.”

And the Lowy Institute believes that Australia can set an example for the rest of the world.  In their article ‘An Australian model for the renewable-energy transition’ published on 11 March 2019, they assert that across the world “A very rapid transition to renewables is in process” and that “Most countries can follow the Australian path and transition rapidly to renewables with consequent large avoidance of future greenhouse emissions.”

Time for a reality check.

In this assessment I use energy consumption and carbon dioxide emissions data from the 2019 BP Statistical Review of World Energy.

First of all, greenhouse gas emissions.  In the BP Review,

…carbon emissions … reflect only those through consumption of oil, gas and coal for combustion related activities, and are based on ‘Default CO2 Emissions Factors for Combustion’ listed by the IPCC in its Guidelines for National Greenhouse Gas Inventories (2006).  This does not allow for any carbon that is sequestered, for other sources of carbon emissions, or for emissions of other greenhouse gases. Our data is therefore not comparable to official national emissions data.

Excluded sources would include for example cement production and land clearing.  However, given that we are focussing on the transition away from fossil fuels towards renewables, that is not a problem.

Figure 1 shows the growth in carbon dioxide emissions (from fossil fuels) since 1965.

Fig. 1: Global CO2 emissions in millions of Tonnes

CO2 emissions global

The big hitters are China, the USA, and India, who together account for more than half of the world total.

Fig. 2: CO2 emissions by the Big Three and the rest

CO2 emissions top3 rest

Note that America’s emissions peaked in 2007 and have since declined.  China’s emissions rose rapidly from 2002 to 2013.  From a low base, India’s emissions growth rate is practically exponential.

Figure 3 shows how Australia “compares”.

Fig. 3: CO2 emissions by the Big Three and Australia

CO2 emissions top3 Oz

Australia’s emissions from fossil fuels peaked in 2008.

The BP Review’s CO2 emissions data are based on fossil fuel combustion, so I now look at energy consumption since 1965.  Energy units are million tonnes of oil equivalent (MTOE), from the BP Review, “Converted on the basis of thermal equivalence assuming 38% conversion efficiency in a modern thermal power station.”

Fig. 4: Global energy consumption by fuel type in millions of tonnes of oil equivalent

World energy cons 65 to 18

(Note:

Apart from 2009 (the GFC) gas has risen steadily, especially the last five years.

Since the oil shocks of the seventies and early eighties and apart from the GFC, oil has mostly enjoyed a steady rise.

Coal consumption increased rapidly from 2002 to 2013 (mostly due to Chinese expansion) followed by a small decrease to 2016.

Hydro power has seen a steady increase.

Nuclear power peaked in 2006 and declined slightly before increasing over the last six years.

Wind and Solar are in the bottom right hand corner.  Both are increasing rapidly but are dwarfed by other forms of energy.)

How close are we to the renewable energy transition?  Figures 5 to 9 show 1965 – 2018 energy consumption for conventional sources (fossil fuels plus hydro and nuclear) and the total.  The gap between conventional and total energy use is filled by renewables OF ALL TYPES- solar, wind, geothermal, bio-waste (e.g. sugar cane bagasse), and bio-mass used for electricity production, (but excluding firewood, charcoal, and dung).  I have highlighted the gaps with a little green arrow.

Fig. 5: Total and conventional energy consumption in millions of tonnes of oil equivalent

World energy cons 65 to 18 fossil hydro nuclear

In 2018, renewables of all types accounted for just 4.05% of the world’s energy, fossil fuels 83.7%.  So much for rapid transition to renewables.

The next three plots show energy consumption of the big emitters.

Fig. 6: Total and conventional energy consumption- China

CO2 emissions China

4.38% of Chinese energy came from renewables in 2018.  Nuclear and hydro power have increased enormously over the past 15 years and make up 10.35% of usage but fossil fuels (mostly coal) make up 85.3% of energy consumption.

Fig. 7: Total and conventional energy consumption- USA

CO2 emissions USA

Renewables accounted for 4.51% of US energy.  Fossil fuel and total energy consumption peaked in 2007 but has recently started increasing mostly due to gas and oil use.   (Coal has slipped from more than a quarter of the fossil fuel total in 2007 to less than a sixth in 2018.)  Fossil fuels make up 84.3% of energy use.

Fig. 8: Total and conventional energy consumption- India

CO2 emissions India

Only 3.4% of India’s energy comes from renewables.  India’s energy consumption is growing very rapidly, and 91.6% of consumption is from fossil fuels.

What of Australia, supposedly setting an example for the rest of the world to follow?

Fig. 9: Total and conventional energy consumption- Australia

CO2 emissions Australia

After years of building solar and wind farms, and at enormous expense, renewable energy of all types accounts for just 5% of Australia’s energy use- and the Greens aim to have zero net emissions in 21 years from now.

In the past 10 years, renewable consumption has increased by 5.5 million tonnes of oil equivalent- but fossil fuels have increased by 6.4 million tonnes.  While coal use has dropped by 12 million tonnes, this has been more than replaced by 18.4 million tonnes of oil and gas.  That’s not much of a rapid transition.

Figure 10 shows in order renewables consumption in all countries.  Remember, this includes all types including geothermal energy and bio-mass.

Fig. 10: Comparative penetration of renewables

Renewable cons %

Australia at 5 % renewable consumption is 19th and ahead of the big emitters, the USA, China, and India.

Perhaps the Extinction Rebellion activists who are unhappy with lack of action against climate change in Germany, the UK, and Australia, could glue themselves to the roadways in China, India, or Russia.

There is no rapid renewable energy transition.   Oil, coal, and gas are cheap and readily available and are powering growth in developing economies.  At some time in the future there will not be enough accessible fossil fuel to sustain the world’s economies alone; uranium too will one day be in short supply.  However, necessity and technological innovation, not legislation, will drive the adoption of alternative fuels.

Rumours of the imminent death of fossil fuels appear to be greatly exaggerated (with apologies to Mark Twain).

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More Footprint Comparisons

June 18, 2019

In my previous post I showed different ways of comparing carbon dioxide emissions.

Here are some more, unashamedly with an Australian focus, in different formats.

As in my last post I use data from the Global Carbon Atlas for fossil fuel emissions for 2017 (the most recent data available), and Gross Domestic Product (GDP) data from the World Bank, also for 2017. GDP for each nation is calculated in current US dollars.

Percentages

Figure 1 shows cumulative percentages of 2017 fossil fuel emissions for all 202 countries with available data.

Fig. 1:  Cumulative CO2 emissions 2017 expressed as percentages

Globalco2 cum %

China, the USA, and India are the big hitters.  China produces 28.5% on its own.  Australia, in 16th place, produces 1.2% of global emissions, a bit behind Canada at 1.66%, and just ahead of the UK at 1.12%.  France and Italy are just over 1% each.  The remaining 183 countries each produce less than 1% – many much less.

Earth Hours

Earth Hour, where some people show how virtuous they are by switching off their lights for an hour in order to reduce emissions, might provide another way of comparing emissions.  I next compare emissions by units of “Earth Hours”.  One Australian Earth Hour is the amount of CO2 emissions reduced when:

Across Australia, all lights powered by fossil fuels; all stoves, fridges, air conditioners, and other appliances; all battery chargers; all street lights, traffic lights, and emergency lighting; all hospitals, schools, shopping centres, and telecommunications including computers; all mining operations; all transport- cars, trucks, trains, and aircraft; all farming operations; all water pumping; all manufacturing industry small and large, including steel and aluminium; all building and construction:  are shut down for one hour.

That is one Australian Earth Hour.

One Chinese Earth Hour is equal to 23.82 Australian Earth Hour units- Australia could run for 23 hours and 48 minutes on the equivalent amount of emissions. The value for America in Australian Earth Hours is 12 hours and 45 minutes; India, 6 hours; Russia, 4 hours; Japan, 2 hours 54 minutes. The value for the UK is 55 minutes and 53 seconds worth of Australian emissions output.

At the other end of the scale, El Salvador’s hourly emissions would last Australia for one minute.  Tuvalu’s total emissions are the equivalent of one tenth of one second of Australia’s emissions.

Efficiency

Here’s another idea.  Australia is the world’s 13th largest economy, and achieves this with emissions per dollar of GDP that put us in 105th place.  For all nations the average CO2 emissions per US dollar of GDP is 485 grams per dollar.  What if all countries were as efficient as Australia?  That is, they all had the same amount of emissions as Australia: 312 grams of CO2 per dollar of GDP.

Figure 2 shows what global emissions would look like if all nations were as efficient as Australia.

Fig. 2:  Global fossil fuel emissions currently and at Australia’s rate per dollar GDP

Global Oz efficiency

Or, to put it another way, Figure 3 shows the effect on the global economy for the same level of emissions.

Fig. 3:  Global GDP currently and at Australia’s emissions rate per dollar GDP

Global GDP Oz efficiency

That’s a potential increase of 37.7%.

Conclusion

Australia is punching above its weight in regard to efficiency of fossil fuel emissions per dollar of GDP.  Our carbon footprint is tiny compared with the big three- China, the USA, and India.  While there is always room for us to improve, if every country behaved as well as we do, the world would be a better place.

Carbon Footprints in Perspective

June 16, 2019

According to a Lowy poll before our recent “climate change election”, apparently 89% of Australians were in favour of action on climate change.  They got it wrong of course, but there is still much gnashing of teeth over the size of our carbon footprint, especially in regard to our emissions per capita.   According to the University of Melbourne’s Climate Energy College, “Australia’s per-capita emissions remain the highest among its key trading partners”.

So how does Australia rate in the world of carbon emissions?

In this post I use data from the Global Carbon Atlas for fossil fuel emissions for 2017 (the most recent data available), and population, land area, and Gross Domestic Product (GDP) data from the World Bank, also for 2017. GDP for each nation is calculated in current US dollars.

Figure 1 shows 2017 fossil fuel emissions for all 202 countries with available data, in millions of tonnes of carbon dioxide.

Fig. 1:  Fossil fuel emissions 2017

CO2top5

In 2017 China was way in front with close to 10 billion tonnes of CO2 emitted, distantly followed by the USA, with India, Russia, and Japan well behind.  Australia was in 16th place, following Germany, Iran, Saudi Arabia, South Korea, Canada, Mexico, Indonesia, Brazil, South Africa, and Turkey.  At the other end of the scale the tiny Pacific nation of Tuvalu emitted only 13,000 tonnes of CO2.

In absolute terms our 413 million Tonnes of CO2 emissions are mediocre.  In the 20 years from 1998 to 2017, Australia’s carbon footprint increased by 78.4 million tonnes.  China’s increased by 6,573 million tonnes.  We’re not in the race, and it is blindingly obvious that however much we reduce our emissions we will have almost zero impact on the global total.

That is the reason that global warming enthusiasts in academia and the media promote the idea of per capita emissions- because we look worse that way.

Fig. 2:  2017 emissions per capita

CO2percap

It is certainly true that we emit larger amounts of CO2 per person compared with our major trading partners.  Fossil fuel is dirt cheap in oil rich nations, but in poor African countries each person emits less than a quarter of a Tonne of CO2 from fossil fuels per year.  There, firewood is the fuel of necessity, with severe consequences for health and the environment.  It is interesting that New Caledonia emits more per head than Australia.

Why does Australia hold this position?  The amount of wealth created by fossil fuel use is a measure of productivity and efficiency.  Figure 3 shows how countries rate in efficiency- how much CO2 is emitted for each US dollar in GDP.

Fig. 3:  2017 emissions per US $ GDP

CO2per$

Less is better.  Poorer countries that burn a lot of fossil fuel, and larger nations that do the same- including Russia, India, China, South Korea, and Indonesia- have less efficient economies than western nations including Canada, Australia, and the USA.  Small countries, especially those with nuclear and renewable energy, rich island nations, and poor African nations using very little fossil fuel make up the best.  Australia has a productive economy with historically cheap fossil fuels- but the most important reason for our relatively high emissions per capita is our size.

Figure 4, a comparison of carbon intensity, is an alternative way of comparing emissions, and because it takes into account the natural advantages of other advanced economies, demonstrates our carbon efficiency much better than population or GDP comparisons.

Fig. 4: 2017 emissions per land area

CO2persqkm

Australia, in 144th position, is followed only by countries with much smaller economies, and none of them apart from Iceland and Greenland are European.  All of our major trading partners, and many others, have much higher carbon intensity than Australia.  All Pacific Island nations, except for Papua New Guinea, Vanuatu, and the Solomon Islands, have higher carbon intensity as well.

Why?  Our economy is diffused across a wide brown land.  Even our cities are relatively thinly populated by world standards.  Production centres and markets are vast distances apart.  Russia, China, Canada, the USA, and Brazil are all larger in area than Australia.  Even so, our emissions are much less: Australia- 53.7 Tonnes per square kilometre; Brazil- 61.5; Canada- 63; Russia- 103.4; USA- 576; China- 1,048 Tonnes per square kilometre.

Don’t preach to us- Australia is a carbon sink by comparison with most other countries.

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As an appendix, here are three plots showing Australia’s relative position in the world.

Fig. 5:  2017 population

Poptop5

Fig. 6:  2017 GDP

GDPtop5

Fig. 7:  Land area

Areatop5

Australia is sixth in land area, 13th in GDP, and 53rd in population.  We are a large, under-populated, productive nation.  Naturally we have fossil fuel emissions to match.

Another Inconvenient Pause

January 15, 2019

The Pause in global temperatures may be past, but here is another, longer Pause, and one that is much more difficult to explain: at ideal Australian sites, increasing greenhouse gas concentrations have led to a decrease in downwelling longwave radiation- the very opposite of expectations.

Basically, the theory behind the enhanced greenhouse effect is that the increase in concentrations of anthropogenic greenhouse gases leads to an increase in downwelling infra-red (IR) radiation, which causes surface warming.

Is there evidence for increasing downwelling IR in recent years, as atmospheric concentration of carbon dioxide has been rapidly rising?

The authors of Skeptical Science think so:

Surface measurements of downward longwave radiation

A compilation of surface measurements of downward longwave radiation from 1973 to 2008 find an increasing trend of more longwave radiation returning to earth, attributed to increases in air temperature, humidity and atmospheric carbon dioxide (Wang 2009). More regional studies such as an examination of downward longwave radiation over the central Alps find that downward longwave radiation is increasing due to an enhanced greenhouse effect (Philipona 2004).

Time for a reality check.

The links in the above quote do not work for me, so I use data available for Australia.

Greenhouse gas concentrations are measured at Cape Grim in north-west Tasmania.  According to the CSIRO,

The Cape Grim station is positioned just south of the isolated north-west tip (Woolnorth Point) of Tasmania. It is in an important site, as the air sampled arrives at Cape Grim after long trajectories over the Southern Ocean, under conditions described as ‘baseline’. This baseline air is representative of a large area of the Southern Hemisphere, unaffected by regional pollution sources (there are no nearby cities or industry that would contaminate the air quality).

Fig. 1:  Cape Grim Baseline Air Pollution Station (looking almost directly south)

c grim photo

Fig. 2:  CO2 concentration, Cape Grim.

co2 c grim

Fig. 3:  Methane concentration, Cape Grim.

ch4 graph

Fig. 4:  Nitrous oxide concentration, Cape Grim.

n2o graph

There is no doubt that concentrations of greenhouse gases have been increasing.  We should therefore expect to see some increase in downwelling longwave radiation.

Downwelling IR data are available from the Bureau of Meteorology which maintains a database of monthly 1 minute solar data from a network of stations around Australia, including Cape Grim.

What better location than Cape Grim to study the effects of greenhouse gas concentrations from month to month on readings of downwelling IR.  The instruments are within metres of each other under “baseline” conditions at a pristine site.

The data include 1 minute terrestrial irradiance (i.e. downwelling IR striking a horizontal surface) from which I calculated mean daily IR for each month.  To remove the seasonal signal, I calculate anomalies from monthly means.

Fig. 5:  Downwelling longwave radiation anomalies, Cape Grim.

ir over time capegrim

Oops! IR has been decreasing for the full length of the record, 20 years (May 1998 to June 2018).   And monthly IR anomalies plotted against monthly CO2 anomalies show a similar story:

Fig. 6:  Downwelling longwave radiation anomalies, Cape Grim.

ir vs co2 cgrim

In the most suitable location in Australia, from May 1998 to June 2018 there has been no increase in downwelling infra-red radiation, despite an increase of 41.556 ppm atmospheric concentration of carbon dioxide, 104.15 ppb of methane, and 14.472 ppb of nitrous oxide.

So what factors do influence downwelling IR and thus surface warming or cooling?  Together with solar radiation, that other greenhouse gas, H2O.  Gaseous H2O (humidity) and clouds formed of liquid and ice H2O are by far the major players in returning heat to the surface.

We see this in a plot of downwelling IR against cloudiness (from nearby Marrawa).

Fig. 7:  Downwelling IR anomalies vs Cloudiness, Cape Grim.

ir vs cloud capegrim

Daytime cloudiness (an average of observations at 9.00 a.m. and 3.00 p.m.) increases downwelling IR.  We have no data for night time cloudiness unfortunately.

To illustrate the irrelevance of carbon dioxide, here is a plot of anomalies of solar radiation (global irradiance), downwelling infra-red radiation, daytime cloudiness, and carbon dioxide concentration at Cape Grim over the past 20 years.

Fig. 8:  Anomalies of IR, Global Irradiance, CO2, and Daytime Cloud at Cape Grim 1998-2018

98 to 18 full range capegrim ir global co2 cloud anoms

And zooming in on 2008 to 2010:

Fig. 9:  Anomalies of IR, Global Irradiance, CO2, and Daytime Cloud at Cape Grim 2008-2010

98 to 18 2008 2010 capegrim ir global co2 cloud anoms

There is a feedback mechanism: cloudiness inhibits daytime temperature and increases IR and nighttime temperature; decreased cloudiness means decreased IR; but less cloud and higher daytime temperature will increase IR as well if sustained; and higher IR also increases daytime temperature.  Further, sustained decrease in global radiation due to increased cloud cools the surface, thus decreasing IR.

Carbon dioxide concentration changes have no detectable effect.

A desert location, where humidity is typically very low and rain and cloudiness very infrequent, would also be ideal for checking on downwelling IR from carbon dioxide.  Alice Springs in the central desert is such a location with available irradiance data.

At Alice Springs as well, since March 1995 downwelling IR has been decreasing.

Fig. 10:  Downwelling longwave radiation anomalies, Alice Springs.

ir over time alice

The relationship between cloud and IR is even more evident.

Fig. 11:  Anomalies of IR, Global Irradiance, CO2, and Daytime Cloud at Alice Springs 2008-2010

2008 2010 alice ir global co2 cloud anoms

Fig. 12:  Downwelling IR anomalies vs Cloudiness, Alice Springs.

alice ir v cloud

Cloudiness has an even greater influence on IR in desert than maritime locations.

TAKE AWAY FACT:-  For over 20 years, at what are arguably the most suitable sites in Australia, increasing greenhouse gas concentrations have had no detectable effect on downwelling longwave radiation.  Natural factors including cloudiness changes have vastly overwhelmed any such effect and have instead led to a decrease in downwelling longwave radiation.

That is indeed a most inconvenient pause.

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To replicate these findings:

Go to http://reg.bom.gov.au/climate/reg/oneminsolar/index.shtml

You will need to register with a username and password.  Then click on an irradiance observation station.  Select year and month.  Download the zip file, and open in your preferred application.  (I use Excel).  IR data are in Column W- the values are wattminutes of IR striking a horizontal surface of area one square metre.

My method:  Order the data in ascending order to remove null values.  Count the minutes of valid data and calculate the percentage valid of all possible minutes in that month.  (I discard months with less than 80% valid data.)   Divide the total minutes by 1,440 to convert to days.  Sum the valid data and divide by 60,000 to find kilowatthours; divide by the number of days to find the mean daily value; then multiply by 3.6 to convert to Megajoules.  Plot monthly values against time or carbon dioxide concentration.

The Chicken or the Egg?

May 3, 2018

Climate scientists assert that increasing concentrations of carbon dioxide and other greenhouse gases in the atmosphere have caused and will continue to cause global temperature to increase.  Real world evidence to support this is sadly lacking.

I use CO2 data from NOAA at Mauna Loa and HadSST3  Sea Surface data to compare both over the same period, as oceans cover most of global surface.

There have been 60 years of continued and accelerating CO2 increase.

Figure 1: 60 years of carbon dioxide concentration

CO2 abs trend

Ocean temperatures have also increased:

Figure 2:  HadSST3 Sea Surface Temperature from 1958

Hadsst3

While you may note the distinct lack of warming before the mid 1970s, and that although a quadratic trend line fits the data, the increase is not smooth but a series of steps with some large spikes at about the time of ENSO events, climate scientists insist that it is the overall trend that is important.

The following plot appears to support the greenhouse warming theory.

Figure 3:  Global Sea Surface Temperature anomalies as a function of CO2 concentration

SST vs CO2

It seems that nearly three quarters of the temperature change since 1958 can be explained by the increase in CO2 concentration.  This accords with the theory.

But what if we reverse the axes in Figure 3?

Figure 4:  CO2 concentration as a function of Sea Surface Temperature anomalies

CO2 vs SST

It is equally valid to propose that nearly three quarters of the increase in carbon dioxide concentration can be explained by increasing sea surface temperatures, although that is not the point of this exercise.

To determine if CO2 is the cause of increasing temperature, or vice versa, we need to compare SST anomalies and CO2 concentration as a function of time.  If SST and CO2 both change at the same time, we are no further advanced, but if CO2 changes before SST (due to thermal inertia of the oceans), then that would be evidence for CO2 increase being the driver of temperature increase.

Both CO2 concentration and SST anomalies have pronounced trends, so for comparison both datasets are detrended, and the large seasonal signal is removed from CO2 data to calculate monthly “anomalies”.

Remember, it is increasing CO2 which is supposed to cause increasing temperature, not a static amount, so change in CO2 and SST must be our focus.

My measure of change in SST and CO2 is 12 monthly difference: for example January 2000 minus January 1999.  The next plot shows 12 monthly difference in both SST and CO2 anomalies from 1959 to 2018.  (SST is scaled up for comparison).

Figure 5:  12 monthly change in detrended SST and CO2 anomalies

12m chg Hadsst3 co2

SST appears to spike before CO2.  In the next plot, SST data have been lagged by seven months:

Figure 6:  12 monthly change in detrended SST (lagged 7 months) and CO2 anomalies

lagged 7m 12m chg Hadsst3 co2

There appear to be differences in some decades- the lag time varies from four months to eight or nine months.

Here’s the plot of CO2 vs lagged SST:

Figure 7:  12 month change in CO2 as a function of 12 month change in SST, lagged 7 months

lagged 12m SST vs CO2

Correlation co-efficient of 0.57 is not bad considering we are comparing all ocean basins and the atmosphere.

As SST change generally precedes CO2 change by about seven months (sometimes less, sometimes more), there is NO evidence that CO2 increase causes temperature increase.

But we are still left with the increase in CO2 from 1958 while SST paused or decreased for 19 years.

Figure 8:  Sea Surface Temperature and CO2 concentration, 1958-1976

Hadsst and CO2 58 76

While it is difficult to attribute decadal CO2 increase to non-existent SST rise, there is no evidence for CO2 driving temperature increase in this period.

However, plotting 12 month change of CO2 and SST clearly reveals their relationship.

Figure 9: 12 month change in detrended CO2 and SST anomalies

12m chg Hadsst and CO2 58 76

Figure 10: 12 month change in detrended CO2 and SST anomalies, lagged 7 months

lagged 12m chg Hadsst and CO2 58 76

It is clear that 12 monthly change in temperature drives 12 monthly change in CO2 concentration.

The continual rise in CO2 from 1958 to 1976 while SST declined indicates there must be an underlying increase in CO2 unrelated to immediately preceding temperature, but there is definitely no evidence that it causes sea surface temperature increase at any time.

Summary:

  1. Increase in CO2 concentration is supposed to be the cause of the increase in temperature we see in the SST data (and satellite data).
  2. However, analysis shows that CO2 changes about four to seven months (and longer) after sea surface temperature changes.
  3. Therefore, atmospheric CO2 increase cannot be the cause of surface temperature increase. Real world data disproves the theory.

Fingerprints of Greenhouse Warming: Poles Apart

February 26, 2018

If global warming is driven by the influence of carbon dioxide and other man made greenhouse gases, it will have certain characteristics, as explained by Karl Braganza in his article for The Conversation (14 June 2011).

As water vapour is a very strong greenhouse gas, it will tend to mask the influence of man made greenhouse gases, and because solar radiation is such a powerful driver of temperature, this also must be taken into account.  Therefore, the characteristic greenhouse warming fingerprints are best seen where solar and water vapour influences can be minimised: that is, at night time, in winter, and near the poles.  So we would look for minimum temperatures rising faster than maxima; winter temperatures rising faster than summer, and polar temperatures rising faster than the tropics.  Indeed, polar temperature change in winter should be an ideal metric, as in Arctic and Antarctic regions the sun is almost completely absent in winter, and the intense cold means the atmosphere contains very little water vapour.  We can kill three birds with one stone, as winter months in polar regions are almost continuously night.

So let’s look at the evidence for greater winter and polar warming.

Figure 1: North Polar Summers:

NP summers

Figure 2:  North Polar Winters:

arctic all winters

Yep, North Polar winters are warming very strongly, at +2.58C/100 years, and much faster than summers (+1.83C/100 years)- strong evidence for anthropogenic global warming.  And warming is much faster than the Tropics (+1.023C/100 years):

Figure 3: Tropics

Tropics TLT

Unfortunately for the theory, the opposite happens in the South Polar region:

Figure 4: South Polar Summers

SP summers

Figure 5:  South Polar Winters:

antarctic all winters

While summers are warming (+0.58C/100 years), winters are cooling strongly at -1.66C/100 years.  Over land areas, with little influence from the ocean, very low moisture, and very little solar warming, winters are cooling even faster:

Figure 6:  Antarctic winters over land:

antarctic land winters

This is the exact opposite of what is supposed to happen in very dry, cold, and dark conditions- at night, in winter, at the poles.  Can this be because carbon dioxide and other greenhouse gases are NOT well mixed, and are in fact decreasing in concentration near the South Pole?

Figure 7: Carbon Dioxide concentration at Cape Grim (Tasmania):

C Grim CO2

Figure 8:  South Polar region TLT (all months) as a function of CO2 concentration:SP vs co2

No, while Cape Grim data show CO2 concentration to be increasing in the Southern Hemisphere, but without the marked seasonal fluctuations of the Northern Hemisphere, there is NO relationship between CO2 and temperature in the South Polar region.

Is it because the oceans around Antarctica are cooling?

Figure 9: South Polar Ocean TLT:

SP ocean

Nope- -0.01C/100 years (+/- 0.1C).  Neither cooling nor warming.

The cold, dry, dark skies over Antarctica are getting colder in winter.  Summers show a small warming trend.

Conclusion:  The fingerprints of man made greenhouse warming are completely absent from the South Pole, and differences between North and South Polar regions must, until shown otherwise, be due to natural factors.

Data sources:

https://www.nsstc.uah.edu/data/msu/v6.0/tlt/uahncdc_lt_6.0.txt

http://www.csiro.au/en/Research/OandA/Areas/Assessing-our-climate/Latest-greenhouse-gas-data

Mandated disclaimer:-

“Any use of the Content must acknowledge the source of the Information as CSIRO Oceans & Atmosphere and the Australian Bureau of Meteorology (Cape Grim Baseline Air Pollution Station) and include a statement that CSIRO and the Australian Bureau of Meteorology give no warranty regarding the accuracy, completeness, currency or suitability for any particular purpose and accept no liability in respect of data.”

“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.

“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.

Trending Trends Continued: An Alternative View

February 26, 2016

No matter how much and how well we explain the methods for calculating the length of The Pause, Global Warming Enthusiasts will accuse us of cherry picking the start date.

In this post I will replicate the IPCC’s predicted estimates for temperatures, and show alternative scenarios with a range of trends to the end of 2035, through using an alternative  view which will be sure to please our friends on the other side of the fence- but will demonstrate the limited extent of the joy they should feel at the expected demise of The Pause. As well,  I will also demonstrate what temperatures will need to do before we skeptics can claim victory (our opponents will never admit defeat- that would be heresy).

In these figures I plot running trends of 12 month means of Temperatures of the Lower Troposphere (TLT) anomalies from UAH (Version 6 Beta 5), but starting from the beginning of the record (12 month means from November 1979).  Running trends will be used in this post to demonstrate the effects of changing data values over time.

Fig. 1: Running trends for global TLT to the present

Trend to 2016 all

Fig. 2: Running trends for global TLT to the present, closer view.

trend to 2016 closeup

Note to GWEs: there is no cherry picking: the start is from the start of the record. Each new month’s data point will either increase or decrease the long term trend, but with decreasing effect as the record grows in length. Peaks correspond to warming events, troughs to cooling events. Note also that the recent long term trend is near the lowest it has been since 1998. With the expected increase in temperatures following the El Nino, I anticipate the long term trend to the end of 2016 will be about +1.2C per 100 years.

What of the future? Now according to the IPCC Assessment Report 5, warming for the next 20 years is locked in, no matter what emissions scenario.

“The global mean surface temperature change for the period 2016–2035 relative to 1986–2005 is similar for the four RCPs and will likely be in the range 0.3°C to 0.7°C (medium confidence). This assumes that there will be no major volcanic eruptions or changes in some natural sources (e.g., CH4 and N2O), or unexpected changes in total solar irradiance.”

( https://www.ipcc.ch/pdf/assessment-report/ar5/syr/AR5_SYR_FINAL_SPM.pdf p8)

If I am still around in 2035, this prediction will not be a huge priority for me. However, to illustrate various possibilities, I shall calculate possible TLTs for the next 20 years. (Yes, I know the IPCC is talking about surface temperatures. However if tropospheric temperature change doesn’t reflect surface temperature change for another 20 years there are going to be some serious arguments in climate science circles!)

First, let’s replicate the IPCC predictions for 2016-2035- and in so doing, show The Pause in all its glory. The next figures plot running 12 month mean Temperatures of the Lower Troposphere (TLT) anomalies in degrees Celsius versus global atmospheric carbon dioxide concentration in parts per million (ppm), data from NOAA.  The global record commences in 1980.

Fig. 3: Running trend of Degrees C per 100 ppm CO2

Trend TLT v co2

Note again the peaks and troughs, and that the current trend is the lowest it has been since 1996.  The long term trend to December 2015 is +0.65C/ 100 ppm CO2. This is confirmed in the following plot:

Fig. 4: TLT anomalies vs CO2

tlt vs co2 1980-2015

Now let’s break the record in two: the first half of the CO2 rise and the second half.

Fig. 5:  TLT vs CO2: 1st 30.32ppm

tlt vs co2 1st half

Fig. 6:  TLT vs CO2: last 30.32ppm

tlt vs co2 2nd half

There you have The Pause: entirely un-cherry picked, as we are using exactly equal portions of the record: the first and last 30.32 ppm of the CO2 growth from 1980 to 2015.

The next graphs plot CO2 increase over time, from 2001 to 2015.

Fig. 7: CO2 growth (12 month running mean)

co2 to 2015 formula

Using this trend equation it is possible to estimate CO2 for the next 20 years, and from that, using (A) the trend of the first half of TLT vs CO2, i.e. rapid warming; (B) that of the whole 1980-2015 period, i.e. continuing the present long term trend; and (C) that of the second half of the CO2 growth, i.e. The Pause, calculate three theoretical estimates for the TLT in the best way- from observations. Here are series A and B.

Fig. 8:  Theoretical trends calculated from observations

Series A B calcs

Note that series A approximately tracks the observed TLTs until about 2002, when the disparity begins. This shows clearly why The Pause is so inconvenient, and why so much effort has been made to eradicate it.

Amazingly, the 2016-35 high mean of 0.7 above 1986-2005, and the low mean of +0.3, as predicted by the IPCC, have been replicated almost exactly by series A and B. (The UAH 1986-2005 mean is +0.02C).  It appears that the temperature trend for the rapidly warming phase up to 2001 exactly matches the trend needed to create the upper limit of their prediction for 2016-35, and the trend overall to 2015 is very close to that of the lower limit. The IPCC is banking on the warming trend from now to 2035 being at least as much as the 1980-2015 trend, and as much as that of the rapid warming to about 2001. Any continuation of a slowdown makes that much harder.

Obviously these series are imaginary, showing the theoretical TLT calculated from CO2 concentration, and without any of the bumps and dips caused by natural variation- volcanoes, ENSO events, and the like. However, they can be used to simulate what temperatures might do over the next 20 years.

I illustrate this with these scenarios, and a fourth, below.

Scenario A allows the 2016-2035 mean to be 0.7C above the 1986-2005 mean and necessitates temperatures sharply rising then continuing at the rate of the higher of the theoretical series (A). Scenario B very slightly exceeds the lower IPCC expectation of +0.3C, and represents a continuation of the current trend. Scenario C is calculated by multiplying expected CO2 concentration by the TLT per CO2 trend for the second half of CO2 growth, indexed to the 1996-2015 mean. As expected it is virtually flat with the 2016-35 mean at +0.14C. This represents an extension of The Pause by another 20 years. Scenario D shows a sharp drop to a 20 year plateau (shown as flat as we have no idea how temperatures may fluctuate) at -0.11C, the lowest 12 month mean of the last 20 years, and about the same average as the 1980-95 period. I have smoothed the beginning months of all four scenarios.

I repeat- these scenarios are entirely imaginary and represent approximate calculated values IF TLT responds to CO2 concentration as it has to now, and nothing else.

Fig. 9: Four scenarios to 2035

Scenarios to 2035

I have marked in the trend line for UAH to now.  Scenario A shows what would happen if The Pause came to an abrupt end, with temperatures rising to a record high for 2016, and then keeping on rising at the theoretical rate as if The Pause had never happened. I’m sure there are some Global Warming Enthusiasts who expect temperatures will do just that.

But the IPCC has an out clause- Scenario B. If the current long term trend continues, TLTs will reach IPCC expectations. Which is why GWEs are desperate for The Pause to end and warming to resume at (at least) the slow if not steady +1.1 to 1.2C per 100 years. If it doesn’t they’re in trouble.

Temperatures will need to trend below this to falsify the predictions- and not even as much as Scenario C, which represents an extension of The Pause. Scenario D represents a significant decrease.

The next plot compares the trends under these four scenarios.

Fig. 10: Trends in degrees Celsius per 100 years to 2035 under four TLT scenarios.

Trend scenarios to 2035

Ignore the artificial shape of the curves. At December 2035 the trend for each scenario will be about:
Scenario A: 2.1C/ 100 years
Scenario B: 1.2C
Scenario C: 0.6C
Scenario D: 0.0C

The IPCC expects trends to be between those of Scenarios A and B. A small step up (to a new 20 year mean of say +0.25C) and a new pause- which is entirely possible- would probably still be claimed to be “the hottest decade ever” and “consistent with global warming projections”. We need to emphasise that a pause doesn’t have to be completely flat. A 30 year period with a trend of +0.3C per 100 years should be enough to bring the global warming models into question. However, there will need to be a significant drop in temperatures, or a much longer plateau, for us to claim victory. A 57 year pause would be most embarrassing- but then they would probably blame it on volcanoes!

Finally, even if this El Nino is followed by a strong La Nina, as suggested by NOAA,  it is unlikely The Pause will return until the beginning of 2018, perhaps a little earlier. However, that is not important. The important thing is what happens next. Watch the next two or three ENSO cycles- especially the La Nina dips.

Global Warming Enthusiasts are desperate for rapid warming to resume at least as much as Scenario B. The long term trend must rise above the current rate if they are to feel vindicated. But then, who knows what the actual temperatures will do.

Time will tell.

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.