Posts Tagged ‘climate’

More Evidence That The Australian Temperature Record Is Complete Garbage

December 8, 2021

The Bureau of Meteorology is either incompetent or has knowingly allowed inaccurate data to garble the record.

My colleague Chris Gillham at has alerted me to growing problems with the BOM’s record for Diurnal Temperature Range (DTR).  DTR is the difference between daytime temperature (Tmax) and night-time temperature (Tmin). 

According to Dr Karl Braganza’s paper at , “an index of climate change” is that DTR should decrease as greenhouse gases accumulate. To oversimplify, greenhouse gases will enhance daytime temperature while at night greenhouse gases will slow down cooling.  With increasing greenhouse gas concentration, daytime maxima are expected to increase, certainly, but the effect on night-time minima will be relatively greater.  Thus, minimum temperatures will increase faster than maxima, and DTR will decrease.  While Dr Braganza was referring to global values, Australia is a large dry continent where DTR should show up clearly.

We now have 111 years of temperature data in ACORN-SAT (Australian Climate Observation Reporting Network- Surface Air Temperatures).  In this post I only use Acorn temperature data and corresponding rainfall data.  Skeptics have been bagging Acorn ever since it was introduced, and for good reasons as you will see.

Figure 1 is straight from the Bureau’s climate time series page, and shows how DTR has varied over the years.  There is a centred 15 year running mean overlaid. 

Figure 1: Official plot of annual DTR

Melbourne, We Have A Problem… DTR has been increasing recently.

I have used BOM data to make plots that show this more clearly.  First, Figure 2 shows annual DTR from 1910 to 2020 has no trend.  It should be decreasing.

Figure 2:  Annual DTR

There appears to be a distinct step up around 2000-2002.

Figure 3 shows the same data for the last 70 years, broken into two periods, from 1951 to 2000, and 2001 to 2020.

Figure 3:  DTR since 1951

From 1951 to 2000, DTR behaves as it should, with a long term decrease.  After 2000, DTR steps up well above expected values.  The average from 1981-2000 is -0.12 C.  From 2001-2020 the average is +0.35C.  DTR suddenly increases by nearly 0.5C. Why?

DTR is very much governed by that other greenhouse gas, H2O.  Dry days, months and years produce hot days and cooler nights; wet periods result in cooler than average days and warmer than average nights.  This relationship is shown in Figure 4.

Figure 4:  DTR anomalies plotted against rainfall anomalies- all years 1910-2020

As rainfall increases, DTR decreases.  The effect is more marked in very wet (>100mm above average) and very dry (100mm or more below average) years.

Figure 5 shows time series of DTR (as in Figure 2) and rainfall.  Rainfall has been inverted and scaled down by a factor of 250.

Figure 5:  DTR and Inverted, Scaled Rainfall

There is close match between the two.

Using 10 year averages in Figure 6 makes the change after 2001 much clearer.

Figure 6:  Decadal means of DTR and inverted, scaled rainfall

The 10 year average rainfall to 2020 is about the same as the 1961-1990 average (the period the BOM uses for calculating anomalies).  The 10 year average DTR should be about the same value- not at a record level.

As DTR decrease due to greenhouse gas accumulation is caused by minimum temperatures increasing faster than maximum temperatures, Figure 7 shows 10 year averages of maxima and minima for all years to 2020.

Figure 7:  10 year running means of Tmax and Tmin

Tmax has clearly accelerated in the last 20 years, increasing much faster than Tmin.

This is NOT what should be happening: indeed it is the exact opposite of what greenhouse theory predicts.

Something happened to Australian maximum temperature recording or reporting early this century.  I suspect that the BOM changed from using the highest one-minute average of temperatures recorded in Automatic Weather Systems to the current highest one-second value for the day becoming the reported maximum; or else the design of a significant number of AWS changed, with new, faster-responding probes replacing old ones.

I also suspect I know why this was allowed to happen and continue.

Warmer minimum temperatures at night and in winter are not very scary, but record high temperatures and heatwaves make headlines.

It would suit the Global Warming Enthusiasts in the Bureau for apparently rapidly rising maxima and ever higher records being broken to make headlines, frighten the public, put pressure on governments, and generally support The Narrative.

But someone forgot to tell the left hand what the right hand was doing.

The result is that they are now faced with a contradiction- Diurnal Temperature Range is not decreasing as it should. 

The Bureau is either incompetent or has knowingly allowed inaccurate data to garble the record.

The World’s Biggest Thermometer

August 23, 2021

Are temperatures today unprecedented and dangerously high?  Apparently- the IPCC’s 6th Assessment Report says that current temperatures are higher than at any time in the last 125,000 years

But that is wrong.  Temperatures today are cooler than they were in the past.

In making that statement I am not referring to data from ice cores (as in my previous posts here and here), but a simple and accessible temperature measurement device: the biggest thermometer in the world.

The following statements are uncontroversial:

1 Sea level rise is largely due to melting of glaciers and thermal expansion of the oceans.

2 Thermal expansion and glacial melting are symptoms of temperature increase.

3 Higher sea level indicates warmer conditions, lower sea level indicates colder conditions.

4 Sea levels are currently rising (by a small amount- NOAA says Fort Denison, Sydney, has a rise of 0.65mm per year).

5 This indicates temperatures have been rising.

6 But sea levels and therefore temperatures were higher than now about 4,000 to 7,000 years ago.

If you doubt point 6, you can easily tell whether it was warmer or cooler in the past relative to today.

How?  By looking for evidence of sea level change in areas that are not affected by tectonic rising or falling coastal land, or by large scale water run off or glacial melting, or by very large underground water extraction.

Areas such as the eastern coastline of Australia- the world’s biggest thermometer.

The continent of Australia is very old and flat.  It is in the middle of its continental plate with very little tectonic activity.  Australia’s coastlines are therefore largely stable with little vertical movement, apart from a small tilt down at the northern edge and a small uplift along the southern coast.  Australia is also a very long way from ancient ice sheets.

Evidence of higher sea level is plain to see in many places around Australia.  For example, at Phillip Island in Victoria, Victorian Resources Online describes raised Holocene beaches at Chambers Point, 0.5m and 3 to 5m above high water mark.  Arrows on this Google Maps image show where to find them.

More evidence at Wooloweyah Lagoon, near Maclean in NSW:

And Bulli, NSW:

There are many, many other locations where you can find Holocene beaches well above current sea level. 

Some of the height of these stranded beaches is probably due to the weight of deeper seawater from the melting ice sheets gradually tilting up continental coastlines as the sea floor deepened leading to an apparent drop in sea level at the coast.  However, as Lewis et al (2013) and Sloss et al (2018) (see Appendix below) show, this was of lesser importance especially in northern Australia.  Sea level fall was largely due to climatic influences- in particular, cooling and drying since the Holocene Optimum.

To conclude:  Sea levels were higher in the past, so temperatures must have been higher. 

Therefore there is no evidence that current temperature rise is anything unusual.  Just check the world’s biggest thermometer.

Appendix:  Here are a few of many references to higher Australian sea levels in the Holocene, and reasons for variation.

Sloss et al (2007)  Holocene sea-level change on the southeast coast of Australia: a review

“Present sea level was attained between 7900 and 7700 cal. yr BP, approximately 700—900 years earlier than previously proposed. Sea level continued to rise to between +1 and +1.5 m between 7700 and 7400 cal. yr BP, followed by a sea-level highstand that lasted until about 2000 cal. yr BP followed by a gradual fall to present. A series of minor negative and positive oscillations in relative sea level during the late-Holocene sea-level highstand appear to be superimposed over the general sea-level trend.”

ABC TV catalyst 19/6/2008

Even the ABC says sea levels were higher in the Holocene!

Lewis et al (2008) Mid‐late Holocene sea‐level variability in eastern Australia

“We demonstrate that the Holocene sea-level highstand of +1.0–1.5 m was reached ∼7000 cal yr bp and fell to its present position after 2000 yr bp.”

Moreton Bay Regional Council, Shoreline Erosion Management Plan for Bongaree, Bellara, Banksia Beach and Sandstone Point (2010)

“Sea levels ceased rising about 6,500 years ago (the Holocene Stillstand) when they reached approximately 0.4 to 1m above current levels. By 3,000 years before present they had stabilised at current levels”

Switzer et al (2010) Geomorphic evidence for mid–late Holocene higher sea level from southeastern Australia

“This beach sequence provides new evidence for a period of higher sea level 1–1.5 m higher than present that lasted until at least c. 2000–2500 cal BP and adds complementary geomorphic evidence for the mid to late Holocene sea-level highstand previously identified along other parts of the southeast Australian coast using other methods.”

Lewis et al (2013) Post-glacial sea-level changes around the Australian margin: a review

“The Australian region is relatively stable tectonically and is situated in the ‘far-field’ of former ice sheets. It therefore preserves important records of post-glacial sea levels that are less complicated by neotectonics or glacio-isostatic adjustments. Accordingly, the relative sea-level record of this region is dominantly one of glacio-eustatic (ice equivalent) sea-level changes. ….Divergent opinions remain about: (1) exactly when sea level attained present levels following the most recent post-glacial marine transgression (PMT); (2) the elevation that sea-level reached during the Holocene sea-level highstand; (3) whether sea-level fell smoothly from a metre or more above its present level following the PMT; (4) whether sea level remained at these highstand levels for a considerable period before falling to its present position; or (5) whether it underwent a series of moderate oscillations during the Holocene highstand.”

Leonard et al (2015) Holocene sea level instability in the southern Great Barrier Reef, Australia: high-precision U–Th dating of fossil microatolls

“RSL (relative sea level) was as least 0.75 m above present from ~6500 to 5500 yr before present (yr BP; where “present” is 1950). Following this highstand, two sites indicated a coeval lowering of RSL of at least 0.4 m from 5500 to 5300 yr BP which was maintained for ~200 yr. After the lowstand, RSL returned to higher levels before a 2000-yr hiatus in reef flat corals after 4600 yr BP at all three sites. A second possible RSL lowering event of ~0.3 m from ~2800 to 1600 yr BP was detected before RSL stabilised ~0.2 m above present levels by 900 yr BP. While the mechanism of the RSL instability is still uncertain, the alignment with previously reported RSL oscillations, rapid global climate changes and mid-Holocene reef “turn-off” on the GBR are discussed.”

Sloss et al (2018) Holocene sea-level change and coastal landscape evolution in the southern Gulf of Carpentaria, Australia

“ By 7700 cal. yr BP, sea-level reached present mean sea-level (PMSL) and continued to rise to an elevation of between 1.5 m and 2 m above PMSL. Sea level remained ca. + 1.5 between 7000 and 4000 cal. yr BP, followed by rapid regression to within ± 0.5 m of PMSL by ca. 3500 cal. yr BP. When placed into a wider regional context results from this study show that coastal landscape evolution in the tropical north of Australia was not only dependent on sea-level change but also show a direct correlation with Holocene climate variability….  Results indicate that Holocene sea-level histories are driven by regional eustatic driving forces, and not by localized hydro-isostatic influences. “

Dougherty et al (2019)  Redating the earliest evidence of the mid-Holocene relative sea-level highstand in Australia and implications for global sea-level rise

“The east coast of Australia provides an excellent arena in which to investigate changes in relative sea level during the Holocene…. improved dating of the earliest evidence for a highstand at 6,880±50 cal BP, approximately a millennium later than previously reported. Our results from Bulli now closely align with other sea-level reconstructions along the east coast of Australia, and provide evidence for a synchronous relative sea-level highstand that extends from the Gulf of Carpentaria to Tasmania. Our refined age appears to be coincident with major ice mass loss from Northern Hemisphere and Antarctic ice sheets, supporting previous studies that suggest these may have played a role in the relative sea-level highstand. Further work is now needed to investigate the environmental impacts of regional sea levels, and refine the timing of the subsequent sea-level fall in the Holocene and its influence on coastal evolution.”

Helfensdorfer et al (2020) Atypical responses of a large catchment river to the Holocene sea-level highstand: The Murray River, Australia

“Three-dimensional numerical modelling of the marine and fluvial dynamics of the lower Murray River demonstrate that the mid-Holocene sea-level highstand generated an extensive central basin environment extending at least 140 kilometres upstream from the river mouth and occupying the entire one to three kilometre width of the Murray Gorge. This unusually extensive, extremely low-gradient backwater environment generated by the two metre sea-level highstand….”

Climate Change in Context

August 17, 2021

In my last post I showed some plots of temperature data derived from ice cores at Vostok base in Antarctica, which indicate we are close to the end of the Holocene.

Here are some more plots from the same data so we can put present concerns about warming in some context.  Please remember- temperatures calculated from ice cores have a resolution of from 20 years recently to 40 to 50 years in the mid-Holocene, to 80 to 85 years in the glacial maximum.  Temperatures shown may be regarded as a rough average of conditions over those intervals.  Also note this dataset is for one point on the earth’s surface, not a global average.  Nevertheless it is a very important dataset as it shows polar conditions over a very long period.

Figure 1:  Vostok temperatures relative to 1999 over the last 20,000 years

The previous glacial maximum had temperatures in the Antarctic about 9 degrees colder than now.  This was followed by a strong warming, the Termination of glacial conditions, resulting in 11,000 years of warm conditions, the Holocene.  The Holocene was not uniformly warm but featured fluctuations of up to 2 degrees above and below current temperatures.  I will look at this later, but first I shall take a closer look at the Termination.  

Figure 2:  Vostok temperatures during the Termination

Point A marks the start of the Termination warming.  Temperatures rose from A to B (by about 6.5 degrees in 3,000 years- about 0.2 degrees per 100 years- so not exactly “rapid” warming).  Temperatures then fell about 2 degrees, before rising even more sharply from C to D, the start of the Holocene.  Figure 3 shows temperatures in this final part of the Termination.

Figure 3:  Vostok temperatures in the steepest part of the Termination

Temperatures increased by about 5 degrees over a bit more than 1,100 years.  Yes, the warming rate was indeed steeper- 0.44 degrees per 100 years on average.  However, the temperature rose 1 degree in less than 50 years at the end of this period.

During the Termination, long term temperature rise was gradual, but punctuated by short periods of much more rapid rise.

Now let’s look at temperature change in the Holocene.

Figure 4:  Vostok temperatures 7,000 to 9,000 years ago

Conditions were not uniformly warm, with fluctuations from -1 to +.5C relative to 1999 over hundreds of years.  But there was one episode with a rise of 2.93 degrees in less than 100 years- now that’s rapid warming.

Figure 5:  Vostok temperatures in the last 2,020 years

More recently, temperatures rose 1.94 degrees in 155 years to 1602, and again 2.2 degrees in 44 years to 1809.

You will notice I have shown 3 datapoints showing 21 year mean annual surface air temperatures at Vostok (1970, 1990, and 2010, with zero at 1990).  This is merely for interest- instrumental air temperatures should never be appended to ice core data.  What it does show is that the rate of present temperature change is well within the range of natural variation.

This is also evident when a Greenland ice core series is compared with modern surface air temperatures.

Figure 6:  Greenland (GISP2) temperatures in the last 4,000 years

I have inserted the decadal average of -29.9 C at the GISP borehole from 2001-2010.  Notice how unremarkable that is.

As the fluctuations at GISP and Vostok have been occurring for thousands of years something other than carbon dioxide emissions must be responsible.

So what about carbon dioxide? Data in the next figure is from Dome Fuji, also in Antarctica.

Figure 7:  Insolation, temperature, and CO2 in the last 350,000 years

Notice that at no time in previous interglacials did carbon dioxide concentration exceed 300ppm, (and despite the higher temperatures than now there was no “runaway” warming.)    And as the Carbon Dioxide Information Analysis Centre says

There is a close correlation between Antarctic temperature and atmospheric concentrations of CO2 (Barnola et al. 1987). The extension of the Vostok CO2 record shows that the main trends of CO2 are similar for each glacial cycle. Major transitions from the lowest to the highest values are associated with glacial-interglacial transitions. During these transitions, the atmospheric concentrations of CO2 rises from 180 to 280-300 ppmv (Petit et al. 1999). The extension of the Vostok CO2 record shows the present-day levels of CO2 are unprecedented during the past 420 kyr. Pre-industrial Holocene levels (~280 ppmv) are found during all interglacials, with the highest values (~300 ppmv) found approximately 323 kyr BP. When the Vostok ice core data were compared with other ice core data (Delmas et al. 1980; Neftel et al. 1982) for the past 30,000 – 40,000 years, good agreement was found between the records: all show low CO2 values [~200 parts per million by volume (ppmv)] during the Last Glacial Maximum and increased atmospheric CO2 concentrations associated with the glacial-Holocene transition. According to Barnola et al. (1991) and Petit et al. (1999) these measurements indicate that, at the beginning of the deglaciations, the CO2 increase either was in phase or lagged by less than ~1000 years with respect to the Antarctic temperature, whereas it clearly lagged behind the temperature at the onset of the glaciations. (My emphasis).

Therefore, carbon dioxide did not drive, but followed, temperature change in the past; past rapid warming did not lead to positive feedbacks and runaway warming; and the instrumental record is far too short to draw any definitive conclusion about recent warming, which cannot be differentiated from past Antarctic and Greenland temperature fluctuations.

There is no climate crisis.

Global Warming or Global Cooling: Keep an Eye on Greenland

July 30, 2021

Here are four graphs that governments should think about.

The first graph is of ice core temperature data from Vostok in Antarctica for the past 422,000 years.  Temperatures are shown as variation from surface temperature in 1999 of -55.5 degrees Celsius.

(From:- Petit, Jean-Robert; Jouzel, Jean (1999): Vostok ice core deuterium data for 420,000 years. PANGAEA,

 We are living in an inter-glacial period of unusual warmth, the Holocene, but previous interglacials were 2 to 3 degrees warmer than the present.  Between these brief interglacials are 100,000 year long glacial periods.  As the US National Climatic Data Centre says, “Glacial periods are colder, dustier, and generally drier than interglacial periods.”

We are lucky to be living now- life would be pretty hard for the small population the world could support in a glacial period.

Graph 2 shows just the last 12,000 years.  We are at the extreme right hand end.

Note that Vostok temperatures have fluctuated between +2 and -2 degrees relative to 1999.

There are several ways of identifying the start and end of interglacials.  I have chosen points when Antarctic temperatures first rise above zero and permanently fall below zero relative to 1999.  Graph 3 shows the length of time between these points for the previous three interglacials compared with the Holocene.

The Holocene has lasted longer than the previous three interglacials: and is colder.

Many scientists think glacial periods start when summer insolation at 65 degrees North decreases enough so that winter snowfall is not completely melted and therefore year by year snow accumulates.  Eventually the area of snow (which has a high albedo i.e. reflects a lot of sunlight) is large enough to create a positive feedback, and this area becomes colder and larger.  Ice sheets form, and a glacial period begins.  This is a gradual process that may take hundreds of years.

Well before global temperatures decrease, the first sign of a coming glacial inception will be an increasing area of summer snow in north-eastern Canada, Baffin Island, and Greenland.

I could find no data for northern Canada or Baffin Island, but it is possible to deduce summer snow area for Greenland.

Graph 4 shows the minimum area of snow at the end of summer in Greenland.  (Data from Rutgers University, calculated from North America including Greenland minus North America excluding Greenland.)

The area of unmelted snow at the end of summer in Greenland has grown by about 100,000 square kilometres in the past 30 years.  At this rate Greenland will be completely covered in snow all year round in about 45 years.

Caution: there was no glacial inception in the Little Ice Age- other factors may be involved, cloudiness being one.  Further, a 30 year trend is just weather, and may or may not continue- but with the Holocene already longer and colder than previous interglacials, summer snow cover is one indicator we ignore at our peril.

Cold is not good for life.

How Accurate Is Australia’s Temperature Record? Part 1

January 7, 2021

In my last post I showed that maximum temperature (Tmax) as reported by ACORN-SAT (Australian Climate Observations Reference Network-Surface Air Temperature) appears to be responsible for the growing divergence of the difference between Tmax and tropospheric temperatures from Australia’s rainfall.

In this post I show how Tmax is related to rainfall, and show that while this relationship holds for discrete periods throughout the last 110 years, Tmax has apparently diverged from what we would expect.  In other words, the Acorn Tmax record is faulty and unreliable.

For much of this analysis I am indebted to Dr Bill Johnston who has posted a number of papers at Bomwatch using the relationship between Tmax and rainfall.

At any land based location annual maximum temperature varies with rainfall: wet years are cooler, dry years are warmer.  More rainfall (with accompanying clouds that reflect solar radiation) brings cooler air to the ground; provides more moisture in the air, streams, waterholes, and the soil which cools by evaporation; causes vegetation to grow, the extra vegetation shading the ground and retaining moisture, with transpiration providing further cooling; and in moist conditions deep convective overturning moves vast amounts of water and heat high into the troposphere- especially evident in thunderstorms.  Less rainfall means the opposite: more solar radiation reaches the ground with fewer clouds and less vegetation; there is less moisture available to evaporate; less vegetation growth and transpiration; and much less heat is transferred to the troposphere through convective overturning.

While more rainfall than the landscape can hold results in runoff in rivers and streams, thus removing some moisture from the immediate area, this affects large regions only in tropical coastal catchments- the Kimberleys, the Gulf rivers, the Burdekin and Fitzroy.  Across the bulk of Australia there is very little discharge of water to the oceans.  In the Murray-Darling Basin, on average less than 0.005% of rainfall is discharged from the Murray mouth. (BOM rainfall data and 1891-1985 discharge data from Simpson et al (1993))

This temperature ~ rainfall relationship is particularly evident in desert areas far from any marine influence.  Alice Springs provides a good example.  Figure 1 shows how annual maximum temperatures at Alice Springs Airport vary with rainfall since 1997.  Data are from ACORN.

Fig. 1: Tmax and Rainfall, Alice Springs

The slope of the trend line shows that for every extra millimetre of rain, Tmax falls by 0.0047 of a degree Celsius, which is about half a degree less for every 100 mm.  The R-squared value shows that there is a good fit for the data- 79% of temperature change is due to rainfall.

I said above that this relationship holds for land locations.  An island, with a little land surrounded by water, is mostly affected by sea temperature and wind direction.  Locations near the coast are also affected by marine influence.  At Amberley in south-east Queensland daily maximum temperature can be moderated by the time of arrival of a sea breeze or whether it arrives at all.  (Site changes also can change Tmax recorded.)

Fig. 2: Tmax and Rainfall, Amberley

Further inland, the relationship is strong: at Bathurst, there is 0.4C temperature variation per 100mm of rainfall and 61% of temperature change is due to rainfall alone.

Fig. 3: Tmax and Rainfall, Bathurst

The BOM has sophisticated algorithms for area averaging temperature and rainfall across Australia and provide national climate records back to 1900 for rainfall and 1910 for maxima.  Averaged across Australia individual station idiosyncrasies are submerged so that the 1997 to 2019 relationship between Tmax and rainfall is very strong (and similar to that of Alice Springs):

Fig. 4: Tmax and Rainfall, Australia 1997-2019

However, the relationship is not strong throughout the whole record:

Fig. 5: Tmax and Rainfall, Australia 1910-2019

The relationship from 1910 to 2019 is poor.

In the next figure I compare the Tmax – rainfall relationships for the first 10 years of the record with the last 10 years.

Fig. 6: Tmax and Rainfall, Australia, first and last decades

The trendlines are almost exactly parallel, with tight fits, showing strong relationships 100 years apart- but the trendline for 2010 to 2019 is about 1.7 degrees above that for 1910 – 1919.  How can that be?

It is possible to compare rainfall and temperature throughout the last 110 years.  In the next figure, rainfall is inverted and scaled down so as to match Tmax at 1910.

Fig. 7: Tmax and Inverted Scaled Rain, Australia

Running 10 year means allow us to see long term patterns of rainfall and temperature more easily:

Fig. 8: Tmax and Inverted Scaled Rain, Decadal Means, Australia

Rainfall has increased over the last 110 years (despite what you might hear in the media), and so apparently have maximum temperatures.  In the above figures Tmax and rainfall track roughly together until the mid-1950s, then Tmax takes off.

I calculated an “index” of temperature ~ rainfall variation by subtracting scaled, inverted rainfall from Tmax, commencing at zero in 1919.  This allows us to identify when temperature appears to diverge markedly from inverted rainfall:

Fig. 9: Index of Temperature ~ Rainfall Variation: Tmax minus Inverted Scaled Rain, Decadal Means, Australia

There is a small increase from the mid-1950s, but the really large divergence commences in the 1970s, with the decade from 1973 to 1982 about 0.6 units above the decade to 1972.  The index decreases to 1995, then there is another steep increase to 2007, and a final surge to 2019.

This index alone shows how poorly the official temperature record represents the temperature of the past.

 While there are other times, in the next figures I compare four periods: 1910 to 1972, 1973 to 1995, 1996 to 2007, and 2008 to 2019.  Here I use annual data.

Fig. 10: Tmax and Rainfall, Australia, four periods

Again, trendlines are almost parallel with similar slopes, showing that the Tmax ~ rainfall relationship is fairly constant for all periods- (about 0.5C per 100mm after 1995 and about 0.4C per 100mm before 1995).  However, the lines are separated.  Temperature for each later period is higher than the ones preceding, such that the temperature recorded now is about 1.5 degrees Celsius higher than it would have been for similar rainfall before 1973. And rainfall has increased in that time.

Global Warming Enthusiasts and apologists for the BOM will claim that these breaks between separate periods are real and caused by changes in circulation patterns due to climate change- in particular the Southern Annular Mode.  That will be the subject of Part 2.

Whatever the reasons, Australia wide the Tmax ~ rainfall relationship has remained constant for the past 110 years (as it should) but the temperatures reported in the Acorn dataset have increased by more than 1.5 degrees Celsius relative to rainfall.


The ACORN-SAT temperature dataset is an unreliable record of Australia’s maximum temperatures.

CO2vid Watch: August

September 10, 2020

I have been wondering whether the largest real-life science experiment in history will show whether atmospheric carbon dioxide concentrations will decrease as a result of the Covid19-induced economic slowdown.

Earlier I concluded:  “I expect there may be a small decrease in the rate of CO2 concentration increase, but it won’t be much, and I will be surprised if it turns negative.  A large La Nina later this year will lead to a CO2 increase a few months later, in which case there will be a larger downturn in annual CO2 change in 2021.

However, if the major cause of CO2 increase is fossil fuel consumption, there will be an extra large decrease in CO2 change in 2020 and 2021- and a noticeable jump if the global economy rebounds.”

The CO2 concentration number for August is now published: 412.55 p.p.m. (parts per million).  The seasonal drawdown of CO2 has begun, but CO2 concentration is still 2.61 ppm above the figure for August last year.  Figure 1 shows the 12 month change in CO2 at Mauna Loa since 2015-that is, January to January, February to February, March to March.

Fig. 1:  12 month change in CO2 concentration since 2015 to August 2020- Mauna Loa

Figure 2 is a monthly update for 2020 I will show as each month’s CO2 figures become available (and 2021 if necessary):

Fig. 2:  Updated 12 month changes in CO2 concentration for 2020- Mauna Loa

Figure 3 shows the 12 month change in CO2 concentration since the record began.

Fig. 3:  12 month change in CO2 concentration since 1958 to August 2020- Mauna Loa

Annual growth has been above zero since the mid 1970s, and has not been below 1 ppm since 2011. The annual rate of change is increasing, in other words CO2 concentration growth is accelerating.

Note that so far this year, 12 month changes continue to remain firmly in the normal or even upper range, and there is no sign of any slow down. And there won’t be!

This paper by J. Reid explains why.

CO2 growth appears to be an entirely natural process.

Unless something dramatic happens, I don’t think I will continue this series any longer. There’s nothing to see.

CO2vid Watch: July

August 7, 2020

I have been wondering whether the largest real-life science experiment in history will show whether atmospheric carbon dioxide concentrations will decrease as a result of the Covid19-induced economic slowdown.

Earlier I concluded:  “I expect there may be a small decrease in the rate of CO2 concentration increase, but it won’t be much, and I will be surprised if it turns negative.  A large La Nina later this year will lead to a CO2 increase a few months later, in which case there will be a larger downturn in annual CO2 change in 2021.

However, if the major cause of CO2 increase is fossil fuel consumption, there will be an extra large decrease in CO2 change in 2020 and 2021- and a noticeable jump if the global economy rebounds.”

The CO2 concentration number for July is now published: 414.38 p.p.m. (parts per million).  The seasonal drawdown of CO2 has begun, but CO2 concentration is 2.61 ppm above the figure for July last year.  Figure 1 shows the 12 month change in CO2 at Mauna Loa since 2015-that is, January to January, February to February, March to March.

Fig. 1:  12 month change in CO2 concentration since 2015 to July 2020- Mauna Loa

Notice the amount of 12 month change has increased a bit more.

Figure 2 is a monthly update for 2020 I will show as each month’s CO2 figures become available (and 2021 if necessary):

Fig. 2:  Updated 12 month changes in CO2 concentration for 2020- Mauna Loa

Note that so far this year, 12 month changes continue to remain firmly in the normal or even upper range, and there is no sign of any slow down.

Watch for next month’s update, and enjoy the ride!

CO2vid Watch: June

July 13, 2020

I have been wondering whether the largest real-life science experiment in history will show whether atmospheric carbon dioxide concentrations will decrease as a result of the Covid19-induced economic slowdown.

Earlier I concluded:  “I expect there may be a small decrease in the rate of CO2 concentration increase, but it won’t be much, and I will be surprised if it turns negative.  A large La Nina later this year will lead to a CO2 increase a few months later, in which case there will be a larger downturn in annual CO2 change in 2021.

However, if the major cause of CO2 increase is fossil fuel consumption, there will be an extra large decrease in CO2 change in 2020 and 2021- and a noticeable jump if the global economy rebounds.”

(In a coming post I will update my expectations for the end of the year and next year.) 

The CO2 concentration number for June is now published: 416.39 p.p.m. (parts per million).  The seasonal drawdown of CO2 has begun, but CO2 concentration is 2.47 ppm above the figure for June last year.  Figure 1 shows the 12 month change in CO2 at Mauna Loa since 2015-that is, January to January, February to February, March to March.

Fig. 1:  12 month change in CO2 concentration since 2015 to June 2020- Mauna Loa

Notice the amount of 12 month change has increased a little.

Figure 2 is a monthly update for 2020 I will show as each month’s CO2 figures become available (and 2021 if necessary):

Fig. 2:  Updated 12 month changes in CO2 concentration for 2020- Mauna Loa

Note that so far this year, 12 month changes are in the normal or even upper range, and there is no sign of any slow down.

Watch for next month’s update, and enjoy the ride!

Covid-19 and Global Warming: Two Problems, Two Responses

June 24, 2020

Skeptics have often faced the argument, “You trust medical experts, so you should trust the climate experts”.  The science, after all, is settled.

That argument is nonsense- there is no comparison between them.

Medical researchers, in the fight against Covid-19, are using the time honoured scientific method used for decades in the search for treatments, vaccines, or cures for a host of crippling and deadly diseases- cancer, diabetes,  HIV, to name a few.

This usually involves years of careful examination of patient data and all existing information and literature, forming an hypothesis to test, designing studies, writing protocols, implementing and evaluating laboratory trials, designing and conducting animal trials, designing and conducting clinical trials, analyzing results, and then reporting findings.  It is a continuous process built on past and current evidence. 

The sought-after treatment or vaccine must pass the tests of safety and efficacy.  Doctors are enjoined: First, do no harm.  As well, the treatment must be effective.  There are many examples of trials that were stopped because they were causing higher risk of harm or were showing no benefit. 

It would be too much to expect automatic success from any of the programs under way around the world to find a safe and effective Covid-19 vaccine.

The same approach is not used in climate science:-

It is assumed that the patient (the world) has an unusually high and increasing temperature, even though patient records indicate periods of higher temperature in the past.

It is assumed that this will continue and will worsen.

It is assumed that this is dangerous and must be treated.

It is assumed that we know the cause, because of an untested hypothesis that increasing concentrations of greenhouse gases in the atmosphere, caused by the burning of fossil fuels, lead to increasing temperatures.

It is assumed that “the science is settled”, (and, even more dangerously, conflicting opinions have been actively suppressed.)

Based on these assumptions, all manner of treatments have been rushed into service, with no testing and no thought for safety or efficacy.   Unwanted and dangerous side-effects have been ignored.  Enormously expensive treatments with no proven or even possible benefit have been implemented, while other treatments (e.g. nuclear energy) are beyond consideration.

Why do I trust medical experts?

When discussing a cancer diagnosis, I trusted my specialist because he showed me the evidence, welcomed a second opinion, discussed the benefits and side-effects of different treatments (and none), gave me research papers on the safety and efficacy of the recommended treatment, and gave me time to think about it.  Nearly three years later the treatment is (so far) successful.

Thank God climate experts are not involved in the search for a Covid-19 vaccine- or cancer treatment.

A Closer Look at CO2 Growth

June 11, 2020

For a while I have been looking at atmospheric carbon dioxide data from stations around the world.  This post draws together some observations, many of which are pretty much common knowledge- but some of what I’ve found is surprising.

So I’ll start by listing some of this common and not so common knowledge:-

-The often quoted figures for global CO2 levels are not at all global, but are the local readings at Mauna Loa in Hawaii.

-The long term carbon dioxide record shows continuing increase at all stations, indicating greater output than sinks can absorb. 

-Southern Hemisphere CO2 concentration is increasing but more slowly than the Northern Hemisphere.  Their trends are diverging.

-Seasonal peaks in CO2 concentration occur in late winter and spring in both hemispheres.

-There is very great inter-annual variation in the seasonal cycle of CO2, which can be even more than the average annual increase.

-This inter-annual variation occurs at the same time in both hemispheres, even though the seasonal cycles are 6 months apart.  This implies a global cause, such as the El Nino Southern Oscillation (ENSO).  Large volcanic eruptions also have an impact.  There are likely to be other factors.

-Sea surface temperature change precedes CO2 change by 12 to 24 months.  It is difficult to reconcile this with ocean out-gassing as a cause of the inter-annual CO2 changes.  It is nonsense to claim that CO2 change leads to sea surface temperature change.

-ENSO changes occur at about the same time as CO2 changes.

-CO2 concentration increases during La Ninas. 

-El Ninos precede higher sea temperatures by 4 to 6 months.

-Because of the “oscillation” part of ENSO events, strong events are followed by opposite conditions 16 to 24 months later.  In this way a strong El Nino will lead to strong ocean warming often followed by La Nina conditions and higher CO2 concentration.

-The slowing Southern Hemisphere trend and flattening curve at the South Pole lacks satisfactory explanation.

CO2 measuring stations

Geoffrey Sherrington has shown differences existing between NOAA and Scripps daily CO2 data at Mauna Loa, and that uncertainty in daily data must be much greater than the claimed 0.2 part per million.  His article confirmed my decision to use Scripps instead of NOAA data.  In this post I use Scripps monthly data from many stations across the Pacific, and data from the CSIRO station at Cape Grim in Tasmania, to compare observations from different locations.

Figure 1 shows the locations of stations in the Scripps network, and Cape Grim.

Figure 1:  Scripps stations and Cape Grim

Point Barrow is the most northerly part of the USA, and Alert is the most northerly part of Canada.

The often quoted figures for global CO2 levels are not at all global.  They are not the global average, nor are they representative of other locations.  They are in fact the local CO2 concentration from the slopes of Mauna Loa in Hawaii.  The trend in CO2 increase is similar to, but not the same as, those in other locations.

Figure 2 shows monthly CO2 concentrations from all of the Scripps stations.

Figure 2:  Monthly CO2 at all locations

It is clear that all stations show a similar rising trend, and all show seasonal variation of varying degrees.  However, few stations have long term records, and most have periods of missing data. 

Differences, similarities, and divergence

Figure 3 shows monthly differences from the Mauna Loa record of stations with fairly complete records. 

Figure 3:  Six stations’ difference from Mauna Loa

Monthly differences show huge seasonal variation, so Figure 4 shows 12 month average differences.

 Figure 4:  Six stations’ difference from Mauna Loa, 12 month averages

Clearly, there are major differences between the different records: 

-La Jolla has too many gaps for further analysis. 

-There are differences between Cape Grim and South Pole from about 1980 to the early 1990s.

-Southern Hemisphere stations (American Samoa, Cape Grim, and South Pole) are diverging from Mauna Loa, and from Barrow Point and Alert.  Figure 5 shows these trends more clearly.

Figure 5:  Barrow Point and South Pole difference from Mauna Loa, 12 month averages

While South Pole and Mauna Loa are strongly diverging, Barrow Point and Mauna Loa are becoming slightly more similar.

In Figure 6, the divergence of South Pole data is evident in monthly readings.

Figure 6:  Monthly CO2 concentrations, Mauna Loa, Barrow Point, and South Pole

Note how much larger the Barrow Point seasonal range is.  More importantly, note how South Pole data begin well within the Mauna Loa range, but 50 years later barely reach the bottom of the Mauna Loa range, as Figures 7 and 8 show.

Figure 7:  Monthly CO2 concentrations, Mauna Loa and South Pole 1965-1975

Figure 8:  Monthly CO2 concentrations, Mauna Loa and South Pole 2010 -2020

Why the divergence?  How can a well-mixed gas show a lower trend at the South Pole?  Why is it that the South Pole summer draw down has decreased and is now a plateauing?

Seasonal change

Now zooming in to look at seasonal swings in just two years, 2011 and 2012:

Figure 9:  Monthly CO2 concentrations, Mauna Loa, Barrow Point and South Pole

The Barrow Point range from low to high is nearly three times the size of the Mauna Loa range, and the South Pole range is tiny.  The peak concentrations at Barrow Point and Mauna Loa are in late spring, with a sharp drop at Barrow Point to August and a smoother curve at Mauna Loa to lows in autumn; while at the South Pole the annual curve is better described as a shallow rise in winter followed by a “peak” in spring and a long plateau over summer, with a very small decrease in late summer.  The next three plots show the timing of highs and lows at these three stations for the whole record.

Figure 10:  Timing of seasonal high and low CO2 concentrations, Mauna Loa

Annual lows are in September or October, and highs are almost always in May.

Figure 11:  Timing of seasonal high and low CO2 concentrations, Barrow Point

Lows are always in August, while highs are spread across late winter to late spring, with a plateau from February to May (and extending twice into June).

Figure 12:  Timing of seasonal high and low CO2 concentrations, South Pole

At the South Pole, seasonal highs are reached in spring or early summer, with lows in late summer and early autumn, with one instance in June.

Inter-annual changes

While the seasonal cycles appear to be regular, the timing and size of seasonal changes can vary considerably from year to year.

The next plots show detrended data since 1985 for several locations (few have good data before 1985).  Detrending allows us to compare inter-annual variation more easily.  We do this for each record by subtracting the trend.

Figure 13:  Detrended monthly CO2, Mauna Loa

Figure 14:  Detrended monthly CO2, Barrow Point and Alert

Figure 15:  Detrended monthly CO2, South Pole and Cape Grim

While the seasonal range is different for each location, there is remarkable similarity in timing of changes, for example the late 1980s- early 1990s and 2009-2013.  Note how close Cape Grim and South Pole are, although Cape Grim is at 40.68 degrees South, 49 degrees north of the South Pole.  The South Pole data appear to be representative of a large part of the Southern Ocean.

Because the detrended data retain enormous seasonal variations, it is necessary to show the detrended data (this time from 1979) with monthly means subtracted, for Barrow Point in the far north, Mauna Loa in the middle, and South Pole at the extreme south.  Here are the seasonal signals:

Figure 16: Seasonal signals of monthly CO2 data

As an example, Figure 17 compares detrended data from Barrow Point with monthly means:

Figure 17:  Detrended monthly CO2 with monthly means, Barrow Point

Subtracting the monthly means shows the residual variation in carbon dioxide for Barrow Point:

Figure 18:  Detrended monthly CO2 with seasonal signal removed, Barrow Point

Figure 19 combines the three stations:

All three records follow the same pattern, with a large increase from 1979 to the late 1980s, followed by decrease in the 1990s.  There appears to be another steep increase from 2012 to the present.  Notice that Mauna Loa and South Pole values can be from 1 ppm below to 2 ppm above the trend, while at Barrow Point the range can be from 4ppm below to 5 ppm above the trend, which is about 2.5 ppm per year. 

However, there is still a large amount of variation in the monthly figures.  A centred 13 month rolling mean makes comparison much easier.

Figure 20:  Centred 13 month mean of detrended monthly CO2 with seasonal signal removed

The similar pattern followed by stations from north to south, from the Arctic Ocean, across the Pacific, to the Antarctic, far from any industrial or cropping contamination, is immediately obvious.  The Barrow Point record appears to lag behind Mauna Loa and South Pole data by from one to five months.  South Pole can be a few months ahead to a few months behind Mauna Loa, even though South Pole absolute monthly concentration peaks are from four to seven months later.

Ocean temperature effects

In Figure 14 of my post on 2nd May, Will Covid-19 Affect Carbon Dioxide Levels? I showed that CO2 change lags one year behind sea surface temperatures (SSTs).  The next plot shows the centred 13 month mean of HadSST4 data, scaled up to compare with CO2 data.

Figure 21:  Scaled, centred 13 month mean of detrended monthly HadSST4 and CO2 data with seasonal signal removed

Now the same data with SSTs lagged 12 months…

Figure 22:  Scaled, centred 13 month mean of detrended monthly HadSST4 and CO2 data with seasonal signal removed, HadSST4 lagged 12 months

Large change in CO2 concentrations appears closely linked with sea surface temperature a year before- (or even two years, as between 2002 and 2010).  Sea surface temperatures have a global effect.

ENSO effects

Another cause of CO2 variation is the El Nino- Southern Oscillation (ENSO) which appears in the swings between El Nino and La Nina conditions.  ENSO has a great effect on weather conditions globally, affecting winds, clouds, rainfall and temperature.  Figure 18 shows how CO2 levels respond to the Southern Oscillation Index (SOI), which is a good indicator of ENSO conditions.

Figure 23:  Centred 13 month means, scaled SOI and detrended CO2 levels

CO2 increases in La Ninas.  The pattern becomes more intriguing when we plot inverted SOI levels with sea surface temperatures, as in Figure 19.

Figure 24:  Scaled, centred 13 month mean of detrended monthly HadSST4 with seasonal signal removed and scaled inverted SOI

Inverted SOI data indicate SST data 4 to 6 months later.  (The early 1980s and early 1990s don’t match because of the huge volcanic eruptions of El Chichon and Pinatubo.)  In other words, an El Nino will raise ocean temperatures, and a La Nina will lower ocean temperatures, 6 months later.  Because of the oscillating nature of ENSO, El Ninos and La Ninas approximately reflect each other 16 to 24 months later, as Figure 20 shows.  (Again, El Chichon and Pinatubo have a large impact.)

Figure 25:  Scaled SOI, normal and inverted

That pattern recurs, with varying lag times, throughout the whole 144 year SOI history.

Which is why SSTs will probably increase to about February of 2021…

Figure 26:  Scaled SOI, normal and inverted, and detrended HadSST4

…and with them, CO2 concentration.

Figure 27:  Scaled SOI, normal and inverted, and detrended HadSST4, with South Pole CO2 data

This image has an empty alt attribute; its file name is soi-inv-sst-co2-1.jpg


The long term carbon dioxide record shows continuing increase at all stations, indicating greater output than sinks can absorb. 

CO2 concentrations and trends, while similar, have discernible differences at different locations, notably between the hemispheres.

CO2 concentrations at Southern Hemisphere stations are increasing, but more slowly than those in the Northern Hemisphere, such that their trends are diverging.

On the long term CO2 rise are seasonal rises and falls, most likely due to seasonal vegetation, crop, and phytoplankton growth and decay. 

Peaks in CO2 concentration occur after winter and spring in both hemispheres- February to May at Barrow Point, April and May at Mauna Loa, and September-December at the South Pole.  This is not due however to a six month delay in CO2 mixing from sources in the Northern Hemisphere to the Southern, otherwise the South Pole trend would be the same.  It is lower, and becoming more so. 

There is great variety in seasonal range of CO2 at different locations, with greatest variation in the Arctic and the least in the Southern Hemisphere.

The amount and timing of these seasonal rises and falls varies from year to year.  These inter-year changes in CO2 concentrations can be as much as or greater than the normal annual increase.

Even though the South Pole station is far from the Southern Ocean, especially in winter when sea ice extends further, and even further from any vegetated land areas, its data appear representative of a great part of the Southern Hemisphere.

Small inter-annual changes in sea surface temperatures have a large impact on these changes in CO2 concentrations at South Pole and Mauna Loa about 12 to 24 months later.  There can be a further delay of up to five months in the effect at Point Barrow. 

This is not controversial.  According to the CSIRO, these variations “have been shown to correlate significantly with the regular El Niño-Southern Oscillation (ENSO) phenomenon and with major volcanic eruptions. These variations in carbon dioxide are small compared to the regular annual cycle, but can make a difference to the observed year-by-year increase in carbon dioxide.”

While sea surface temperature rise precedes CO2 concentration increase, there is no evidence at all of CO2 concentration change preceding sea surface temperature change.

With an apparent approximate 12 – 24 month delay between ocean temperature change and inter-annual CO2 change, changes in ocean out-gassing and absorption rates appears to be an unlikely mechanism.  Changes in land vegetation, forests, crops, and oceanic phytoplankton, moderated by the changing circulation, rainfall, cloud, and temperature patterns of ENSO events, appears to be a more likely mechanism, with the much smaller land area of the Southern Hemisphere accounting for the much smaller changes. 

The unresolved problem

This does not however explain the decreasing amount of summer draw down at the South Pole, and the divergence from Northern Hemisphere data.   Perhaps Southern Ocean phytoplankton are not decreasing as much during winter, so the CO2 sink is slightly increasing, slowing the CO2 growth trend a little and smoothing the CO2 growth curve.  Who knows?  I have yet to see a satisfactory- or any- explanation.