Posts Tagged ‘Australia’

Covid in Context

January 24, 2022

With the recent surge in Covid-19, here is a progress report without the hype from the media, and without the commentary from those who doubt the impact of the disease.

I am attempting to show how Covid-19 compares with other major diseases in one important aspect: mortality.  How deadly is it?

I use data from the Australian Bureau of Statistics reports Provisional Mortality Statistics, Australia, Jan 2020 – Oct 2021 and Covid-19 Mortality, released 22 December 2021, and Our World in Data.  

To be certified as a Covid-19 fatality, Covid-19 must be the underlying cause of death- not dying of another condition while being positive for Covid.  According to Covid-19 Mortality, 71.2% of people dying from Covid had pre-existing chronic conditions.  The overall Case Fatality Rate (CFR) for Australia for COVID-19 as of 31 October 2021 was 1.0%, but while the CFR for those aged under 60 years was 0.1%, the CFR for males aged 90 years and over was close to 50%.   83% of people who died of Covid were over 70.  It is therefore a relatively mild disease for younger people, but very severe for elderly and sick Australians.

I shall now tease out mortality statistics to show Covid in context.

Figure 1 shows weekly death tallies of deaths in which doctors certified Covid as being the underlying cause of death, and from November weekly death tallies from Our World in Data.

Figure 1:  Weekly Covid Deaths from January 2020

Those who doubt the severity of Covid-19 often say that deaths from Covid are far less than from other causes.  Figure 2 shows total deaths for the past two years to October as well as the average from 2015-2019 (as 2020 was very unusual), together with Covid deaths.

Figure 2:  Covid-19 compared with all deaths per week

They have a point- to a point.  Weekly deaths from Covid in 2020 and 2021 were tiny in comparison, but in 2022 have risen to be a fifth of the average number for this time of year.  Breaking down the death toll to show separate diseases shows a different picture again.

Figure 3:  Covid-19 and other major diseases

Clearly, Covid’s weekly death toll is already greater than all other major killers except cancer, and may overtake cancer in another couple of weeks.  Thankfully we are close to the peak in eastern states.

Covid is a respiratory disease, but counted separately.  How does it compare with other respiratory diseases?  The next figure tracks Covid and total respiratory deaths, together with the average weekly deaths from respiratory illness from 2015 to 2019.

Figure 4:  Covid-19 and respiratory disease mortality

Covid already not only exceeds the weekly respiratory deaths for any time in the last two years (which had very little influenza), but also the highest average for 2015-2019.

I used to think Covid-19 was just another nasty infectious flu.  Not anymore.  Here’s a comparison of Covid deaths with deaths due to influenza leading to pneumonia.

Figure 5:  Covid-19 and influenza mortality

Already Covid-19 deaths are nine times the average for this time of year, and are also more than three times higher than the average in the peak of the winter flu season.

And WA has yet to open its border!

To compare mortality from diseases, the ABS calculates age-standardised death rates (SDRs) which “enable the comparison of death rates between populations with different age structures”.  Rates are calculated per 100,000 population.  Figure 2 shows death rates for the major diseases causing fatalities, including approximate (caution: not age- standardised) figures for Covid. 

Figure 6:  Death rates for Covid-19 and other major killers

Deaths will not stay at this high level for much longer.  There are signs we are close to the peak of new cases, and deaths will peak a week or two after that.  With Covid endemic in the community, mortality will fall to an unknown rate, and hospitalisations will become more easily manageable.

Make no mistake:  this is a deadly disease!  Take care!

Post Script: Here is another excellent resource:

https://www.covid19data.com.au/deaths

Diurnal Temperature Range and the Australian Temperature Record: More Evidence

January 19, 2022

In an earlier post, I demonstrated through analysing Diurnal Temperature Range (DTR) that the Bureau of Meteorology is either incompetent or has knowingly allowed inaccurate data to garble the record.

A couple of readers suggested avenues for deeper analysis. 

Siliggy asked, “Is the exaggerated difference now caused by the deletion of old hot maximums and or whole old long warmer records?”

Graeme No. 3 asked, “Is there any way of extracting seasonal figures from this composition?”

This post seeks to answer both, and the short answer is “Yes”.

Using BOM Time Series data (from the thoroughly adjusted Acorn dataset) I have looked at data for Spring, Summer, Autumn, and Winter (although those seasons lose their meaning the further north you go).

DTR is very much governed by rainfall differences as shown by this plot.

Figure 1:  Winter DTR anomalies plotted against rainfall anomalies- all years 1910-2020

This shows that in winter DTR decreases with increasing rainfall.  The R squared value of 0.79 means that for the whole period, rainfall explained DTR 79% of the time on average.  However, the average conceals the long term changes in the relationship.

To show this, I simply calculated running 10 year correlations between DTR and Rainfall anomalies for each season, and squared these to show the “R squared” value.  This is a good rule of thumb indicator for how well DTR matches rainfall over 10 year periods.  A value of 0.5 indicates only half of the DTR for that decade can be explained by rainfall alone.  As you will see in the following figures, there are plenty of 10 year periods when the relationship was 0.9 or better, meaning it is ideally possible for 90% of DTR variation to be explained by rainfall.  Here are the results.

Figure 2:  Spring Running R-squared values: DTR vs Rain

There was a good relationship before 1930.  In the decades from then to the mid-1970s it was much worse, and very poor in the decade to 1946. It was poor again in the decade to 2001, and the 10 years to 2020 shows another smaller dip, showing something not quite right with 2020.

Figure 3: Summer Running R-squared values: DTR vs Rain

Summer values were very poor before the 1960s, especially the decades to 1944 and 1961, and dipped again in the 1990s.

Figure 4:  Autumn Running R-squared values: DTR vs Rain

The DTR/Rain relationship was very poor in the decades to 1928, and again before 2001.  The recent decade has also been poor- less than half of DTR to 2020 can be explained by rainfall.

Figure 5:  Winter Running R-squared values: DTR vs Rain

The DTR/rainfall relationship was fairly good, apart from two short episodes, until the 1990s.

I now turn to the northern half of the continent.

A large area of Northern Australia is dominated by just two seasons, wet and dry.  Here is the plot of northern DTR vs Rain for the wet season (October to April).

Figure 6:  Northern Australia Wet Season Running R-squared values: DTR vs Rain

Apart from the 1950s, the late 1970s-early 1980s, and 1998 to 2020, the DTR : Rainfall relationship is very poor, with a long period in the 1930s and 1940s in which rainfall explains less than half of DTR variation (only 13% in the decade to 1943). 

Because the northern half of Australia accounts for the bulk of Australian rainfall, and the wet season is from October to April, this perhaps explains the problems in spring, summer, and autumn for the whole country.

We can get some clues as to the reasons by comparing long term average maximum temperatures with inverted rain (as wet years are cool and dry years are warm).

Figure 7:  Northern Australia Wet Season Decadal Maxima and Rain

The divergence before 1972 and after 2001 is obvious.

The above plots show how poorly DTR (and therefore temperature, from which it is derived) has matched rainfall over the past 111 years.  Low correlations indicate something other than rainfall was influencing temperatures.

In reply to Siliggy, who asked “Is the exaggerated difference now caused by the deletion of old hot maximums and or whole old long warmer records?” the answer appears to be: both, however Figure 7 shows old temperatures (before 1972) appear incorrect, but recent temperatures are at fault too.

The mismatch shows that the Acorn temperature record is not to be trusted as an indicator of past temperatures- and even recent ones.

Tonga Volcano Shock Wave

January 17, 2022

The volcano that erupted near Tonga (and I won’t pretend I can spell let alone pronounce its name) sent a shock wave racing around the world.

It was detected at weather stations across Australia as a sudden spike followed by sharp drop about half an hour afterwards, as in this screenshot from Rockhampton.   

I used Google Maps to plot the course of the shock wave from the volcano across the widest part of Australia.

Showing just Australia:

I used BOM’s Weather Graphs of weather stations close to that line and found the times of the spikes and dips as the wave passed over.

It took roughly 3 hours and 24 minutes to cross the country.  That’s 3,953km at about 1,160 kph.

Here’s a quick plot of the speed of the shock wave as it crossed Australia.

It’s not often you get to see such a phenomenon.

The Challenge Ahead For Renewables: Part 3

January 16, 2022

In Part 1 I showed how the low Capacity Factors of wind and solar mean enormous wastage of resources and money has been incurred over the past 20 years. 

In part 2, I showed the impact of the policies of the major parties, with the costs of replacing fossil fuels in electricity generation, and the enormous cost of using renewables for all our energy use.

However, Net Zero is the goal of the whole developed world, not just Australia.  There are many, and not just the Greens, who say that replacing fossil fuel for all energy is not enough.  We must also ban all exports of coal and gas.

We produce far more energy than we consume- mainly coal (cue wailing and gnashing of teeth).  Most is exported.

According to the Department of Industry, Science, Energy and Resources (2021) total energy production (for domestic consumption plus exports of coal and gas) in 2019-2020 was 20,055 PetaJoules. 

Figure 1:  Australian energy production 2019-2020

All renewables and hydroelectricity amounted to a little over 2% of energy produced in Australia.

Figure 2:  Relative share of energy production

Therefore if we are to maintain our role as an energy exporter (of electricity or hydrogen), and thus our standard of living, then just to keep up with our 2019-2020 production, renewables will have to produce 48 times current production- an EXTRA 19,636 PJ. 

Figure 3: All renewables compared with energy consumption and production

Can this be achieved?

19,636 PJ is 5.45 billion MegaWattHours, which will need 622,227 MW generation (at 100% capacity).

If the extra generation is to come from solar (wind would require far too much land- over 6% of Australia’s land area), we will need an extra 4.149 million MW- 290 times 2020 solar capacity.

Therefore the cost would be at least

$7.47 TRILLION (if all solar).

And that figure doesn’t include storage, extra infrastructure like transmission lines and substations, charging points for vehicles, building hydrogen plants, and losses involved in electrolysis of water, conversion to ammonia and back again, and conversion of hydrogen to motive power.  Neither does it include the costs of decommissioning and replacement, safe burial of non-recyclable solar panels, turbine blades, and used batteries, nor the human costs of child labour in Congolese mines supplying cobalt for batteries.

(Australia’s nominal GDP will be around $2.1 trillion in 2022.)

Figure 4 shows the comparison between Australian GDP and the cost of solar generation needed.

Figure 4:  Cost of extra solar generation needed for Net Zero compared with the whole of the economy

So can it really be achieved?

In the minds of some, yes.

The report from the Australian Energy Market Operator (AEMO) containing the Draft 2022 Integrated System Plan (ISP) makes interesting (and scary) reading.  The favoured scenario is called “Step Change” which involves a rapid transformation of the Australian energy industry (rather than “Slow Change” or “Progressive Change”), which relates more to my analysis in Part 2.

However the scenario called “Hydrogen Superpower” received 17% of stakeholder panellists’ votes in November 2021 and must be considered a possible political goal.

Here is a summary of the Step Change and Hydrogen Superpower scenarios:

• Step Change – Rapid consumer-led transformation of the energy sector and co-ordinated economy-wide action. Step Change moves much faster initially to fulfilling Australia’s net zero policy commitments that would further help to limit global temperature rise to below 2° compared to pre-industrial levels. Rather than building momentum as Progressive Change does, Step Change sees a consistently fast-paced transition from fossil fuel to renewable energy in the NEM. On top of the Progressive Change assumptions, there is also a step change in global policy commitments, supported by rapidly falling costs of energy production, including consumer devices. Increased digitalisation helps both demand management and grid flexibility, and energy efficiency is as important as electrification. By 2050, most consumers rely on electricity for heating and transport, and the global manufacture of internal-combustion vehicles has all but ceased. Some domestic hydrogen production supports the transport sector and as a blended pipeline gas, with some industrial applications after 2040.

• Hydrogen Superpower – strong global action and significant technological breakthroughs. While the two previous scenarios assume the same doubling of demand for electricity to support industry decarbonisation, Hydrogen Superpower nearly quadruples NEM energy consumption to support a hydrogen export industry. The technology transforms transport and domestic manufacturing, and renewable energy exports become a significant Australian export, retaining Australia’s place as a global energy resource. As well, households with gas connections progressively switch to a hydrogen-gas blend, before appliance upgrades achieve 100% hydrogen use.

Household gas switching to 100% hydrogen? What could possibly go wrong?

Here are the AEMO projections:

“The ISP forecasts the need for ~122 GW of additional VRE by 2050 in Step Change, to meet demand as coal-fired generation withdraws (see Section 5.1). This means maintaining the current record rate of VRE development every year for the decade to treble the existing 15 GW of VRE by 2030 – and then double that capacity by 2040, and again by 2050.”  (VRE= Variable Renewable Energy)

 “In Hydrogen Superpower, the scale of development can only be described as monumental. To enable Australia to become a renewable energy superpower as assumed in this scenario, the NEM would need approximately 256 GW of wind and approximately 300 GW of solar – 37 times its current capacity of VRE. This would expand the total generation capacity of the NEM 10-fold (rather than over three-fold for the more likely Step Change and Progressive Change scenarios). Australia has long been in the top five of energy exporting nations. It is now in the very fortunate position of being able to remain an energy superpower, if it chooses, but in entirely new forms of energy. “ (p.36)

Figure 5:  Projections of different renewable needs from the draft report

And capacity factors have not been considered!

And here are the “future technology and innovation” ideas for reducing emissions:

Figure 6: How to achieve emissions reductions

I’m glad I won’t be around to see this play out.

The Challenge Ahead For Renewables: Part 2

January 13, 2022

In Part 1 I showed how the low Capacity Factors of wind and solar mean enormous amounts of wastage of resources and money have been incurred over the past 20 years. 

I also said that the wastage can only get worse.  Here’s how.

In Part 1, I only looked at historical electricity generation.  What of the future according to the major political parties? (The Greens don’t count because they can’t count.)

The major parties are committed to Net Zero emissions by 2050, which will require massive changes to our energy use.

I use data from the BP Statistical Review of World Energy 2021, the National Energy Market website, and the report of the Department of Industry, Science, Energy and Resources (2021).

To replace 2020 fossil fuel electricity with renewable electricity will require an extra 200.6 TeraWattHours:

Figure 1:  Total Electricity Generation

That’s an extra 22,884 MegaWatts of renewable capacity at 100% capacity factor.  Remember, wind’s capacity factor is about 32%, and solar is about 15%.  At $1.8 million per MW, that will cost somewhere between 129 and 275 billion dollars. 

That is of course entirely achievable.  Costly, but achievable.

However, electricity makes up only a small part of Australia’s total energy use.  Transport alone uses much more.  That is why there is a push for more electric vehicles: the ALP wants 89% of new car sales to be electric vehicles by 2030.

Australia’s 2020 energy consumption was 5,568.59 PetaJoules, a decrease of 5.25% on 2019.  One PetaJoule is the equivalent of 0.278 TeraWattHours, or 277,778 MegaWattHours, which is the power generated by 31.7 MW over one year.

Figure 2:  Total Energy Consumption in Australia

Renewables of all sorts accounted for just 8% of energy consumed in Australia in 2020.  Include hydro and that rises to 10.4%.  Figure 2 shows the amount for each.

Figure 3:  Energy Consumption by Type

Note the complete absence of nuclear energy.

If Australia is to be completely fossil fuel free (with no increase on 2020 consumption, which was reduced because of Covid), renewables will have to produce an extra 4,990.9 PetaJoules.  Our consumption will look like this:

Figure 4:  Energy Consumption without Fossil Fuels

4,990.9 PJ is 1.387 billion MegaWattHours, which will need 158,152 MW generation (at 100% capacity)- only 27.8 times 2020 generation.

If this is to be supplied by wind alone, we will need an additional 494,225 MW of installed capacity in wind farms- 52 times 2020 wind capacity- at 24 Hectares per MW.  An extra 118,600 square kilometres of suitable land for wind farms will be difficult to find.

Solar at 2-3 Hectares per MW would probably be a better proposition.  If the extra generation is to come from solar, we will need an extra 1,054,357 MW- 60 times 2020 solar capacity.

Therefore the cost of meeting our current energy consumption- transport, domestic, commercial, and industrial- with no allowance for growth, and ignoring the cost of converting our entire domestic, commercial, industrial, mining, and air transport capacity to some form of electric vehicles, would be between:-

$ 889.6 BILLION  (if all wind)

and

$1.898 TRILLION (if all solar).

(Australia’s nominal GDP will be around $2.1 trillion in 2022.)

That’s up to $73,700 for every man, woman, and child in Australia.

Figure 5 shows the comparison between Australian GDP and the cost of solar generation needed.

Figure 5:  Cost of extra solar generation compared with the whole of the economy

How much of that investment would be in wasted capacity? Between 68% and 85%-from $605 Billion to $1.613 Trillion.

Moreover, the life of a wind turbine is 20 to 25 years, and 25 years for solar panels, so we can look forward to more expense in decommissioning and replacement in the future.

(By the way- do you think that “future technology and innovation” will be any cheaper?)

That’s just what would be the result of the major parties’ commitment to Net Zero.

But wait- there’s more. Stand by for Part 3.

The Challenge Ahead For Renewables: Part 1

January 11, 2022

As we are committed by all major parties to the goal of Net Zero emissions by 2050 perhaps we need to reflect on the scale of the challenge ahead.

I shall first deal with electricity, as that is the only thing that renewables such as wind and solar can produce (except perhaps for a warm inner glow in those who love them.)

Being less of a romantic, I prefer facts and figures.  In this post I use data from the BP Statistical Review of World Energy 2021, the National Energy Market website, and by tracking down opening and closing dates for various facilities.

Figure 1 shows the total generating capacity for coal, wind, and solar electrical generation for the last 20 years.  (Gas is excluded as it makes up less than 8% of generation over a year.)  This is the maximum possible output if all plants are operating at 100% of their rated capacity.

Figure 1: Generating Capacity 2021 – 2020

Note how coal fired electrical capacity fell below 25,000 MegaWatts (MW) with the closure of power stations in SA, WA, and Victoria.  Meanwhile from a very low base wind capacity rose steadily and accelerated from 2018.  Solar generating capacity has exceeded wind since 2012 and really took off in 2019 and 2020.  Wind and solar combined now exceed coal generating capacity.

Now let’s look at how much electricity was actually produced

Figure 2: Coal Capacity and Generation 2021 – 2020

Note how coal generation is falling steadily.  The gap between generation and capacity may be regarded as wasted resources (and money).  This has remained fairly constant over the years.

Figure 3: Wind Capacity and Generation 2021 – 2020

Despite the large increase in capacity, generation is not increasing as fast.  The gap is widening.

Figure 4: Solar Capacity and Generation 2021 – 2020

Again, the gap (i.e. waste) is increasing even faster.  More on this later.

Here’s another way of looking at this problem, for solar.

Figure 5: Solar Generation as a Factor of Installed Capacity 2021 – 2020

Over the last 20 years there has been a fairly constant and close relationship between the amount of electricity generated and the installed capacity it is produced from.  This illustrates the low capacity factor of renewables.  Capacity factor is average actual generation divided by the nameplate capacity, usually expressed as a percentage. 

Figure 6: Capacity Factor 2021 – 2020

Coal has a capacity factor of between 65% and 80%.  Hydro depends on rainfall and has averaged 21% over the last 10 years.  Wind averaged 32% over the last 10 years, but solar struggles to get above 15%- mainly because it sits idle at night, there are large losses in conversion from DC to AC, and also because it produces more than the grid can handle in the middle of the day so supply is curtailed. 

Investors take heed: for every MegaWatt of solar electricity you may wish to generate, you will need to install 6.7 MW.  Every 1 MW of wind electricity needs 3.125 MW installed.  But wind takes up about 24 Hectares of land per Megawatt as against 2-3 Hectares for solar.

Figure 7 shows how much investment has been wasted over the years.

Figure 7: Wasted Capacity

Waste costs money.  In the case of wind and solar, $1.8 MILLION per MW.

I hate waste- but it can only get worse. 

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 http://www.waclimate.net/ 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 https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2004GL019998 , “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….”

How Accurate Is Australia’s Temperature Record? Part 2

January 19, 2021

In my last post I showed that Australia wide the Tmax ~ rainfall relationship has remained constant for the past 110 years (as it should) but Tmax reported in the Acorn dataset has increased by more than 1.5 degrees Celsius relative to rainfall.  Consequently, the ACORN-SAT temperature dataset is an unreliable record of Australia’s maximum temperatures.

Of course there are other aspects of climate besides rainfall.   In this post I will compare annual ACORN-SAT Tmax data with:

Rainfall

Sea Surface Temperatures (SST)

The Southern Annular Mode (SAM)

Cloudiness

Evaporation

all for the Australian region.

I have sourced all data from the Bureau of Meteorology’s Climate time Series pages

except for SAM data from Marshall, Gareth & National Center for Atmospheric Research Staff (Eds). Last modified 19 Mar 2018. “The Climate Data Guide: Marshall Southern Annular Mode (SAM) Index (Station-based).” 

Tmax, Rainfall, and SST data are from 1910; SAM and Daytime Cloud from 1957, and Pan Evaporation from 1975.  Cloud observations apparently ceased after 2014, and Evaporation after 2017, possibly because of staffing cuts.

Because Pan Evaporation data are only available from 1975 and are reported as anomalies from 1975 to 2004 means, I have recalculated Tmax, Rainfall, SST, SAM, and Daytime Cloud anomalies for the same period so all data are directly comparable.

As in the previous post, I have calculated decadal averages for all indicators to show broad long term climate changes.  Decadal averages show how indicators perform over longer periods.  Each point in the figures below shows the average of the 10 years to that point.  This can then indicate times of sudden shifts or questionable data. (For example in Figure 1 SAM (the green line) makes a sudden jump in 2015.  Was this a climate shift or a data problem?)

Figure 1 shows the 10 year means for all climate indicators.  I have scaled Rain and SST to match Tmax at 2019, Cloud and SAM to match Tmax at 1966, and Evaporation to match Tmax in 1984.  Rain and Cloud are inverted as they have an inverse relationship with temperature.

Figure 1:  10 Year Means of Climate Indicators

Tmax has stayed close to SST until 2001.  Clearly Tmax has increased far more than any of the others, especially since 2001.

The next plots show the difference between decadal averages of Tmax and the other indicators.  Zero difference means an excellent relationship with Tmax.

Figure 2:  Difference: 10 Year Means of Tmax minus Rain and SSTs.

Starting from 1919 (zero difference), Rainfall is close to Tmax until 1957, after which Tmax takes off until it is 1.6 degrees Celsius greater than expected in the 10 years to 2020.  Tmax diverges from SST values in 2001 and in 2020 is 0.7 degrees greater than expected.

In Figure 3, Rain, SST, SAM, and Cloudiness are scaled to match Tmax at 1966.

Figure 3:  Difference: 10 Year Means of Tmax minus Rain, SST, SAM, and Cloud

Figure 3 shows how closely Rain and Cloud are related: differences from Tmax are almost identical.  Compared with 1966, Tmax is 1.3 degrees more than rainfall would suggest in the 10 years to 2020.  SST and the SAM index are less different from Tmax but Tmax divergence is still clear.  You may notice that Tmax differences from all climate indicators seem to change at similar times, apart from SAM in 2015.

In Figure 4, all indicators are scaled to match Tmax at 1984.

Figure 4:  Difference: 10 Year Means of Tmax minus Rain, SST, SAM, Cloud and Evaporation

Differences increase rapidly after 2001, so in Figure 5 indicators match Tmax at 2001.

Figure 5:  Difference: 10 Year Means of Tmax minus Rain, SST, SAM, Cloud and Evaporation

There appears to be a problem with SAM in 2015, and it’s a shame that the BOM have discontinued Cloud and Evaporation observations.  In the last 20 years, it is obvious that Tmax has diverged from other indicators.

Conclusion:

All factors- Rainfall, SAM, SST, Clouds, and Pan Evaporation- point to a clear divergence of temperature nationwide, especially in the last 20 years.  In other words, ACORN-SAT, our official record of temperatures, is unreliable.

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.

Conclusion:

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