One Example of Domestic Electricity Costs

October 25, 2018

During a clean up I found a package of old electricity bills, going back to 2006.  I entered the data into Excel to see what has happened to our costs over the last 13 years.

We live in regional Queensland where the sole provider is Ergon Energy.  Ergon provides on each bill a handy comparison chart showing our electricity usage is very similar to that of other households like ours.  In 2012 we moved to Rockhampton, which is hotter and drier than Mackay, and the house has a different energy use pattern, but electricity prices are the same in both areas.

While our usage has actually declined by about 5.8 kWhrs per quarter over 13 years as we have become more careful, our annual electricity bill has increased by 138%.  We are being good global citizens, so why are we being punished?  The reasons are as shown in the following figures.

Figure 1:  Nett cost per kWhr of electricity

Nett price

The average annual price of electricity delivered (free of other charges) has increased by about 129%.  This was achieved mainly by a series of ever larger increases on an annual basis to 2014 (113% over 8 years), followed by a drop of about 16% over two years, then another increase of 22% over three years.

However the total cost of electricity supply (all charges divided by kWhrs consumed) has increased by 170%.

Figure 2:  Cost of electricity plus other charges per kWhr

Total price

Note the quarterly costs are very close to the trend line, with larger variation from about 2014.  How can this be achieved?  By increasing daily service fees and quarterly metre reading charges.

Figure 3:  Daily service fees and quarterly metre reading charges

Other costs

The average annual costs of these other charges has increased by 544%!

The unintended consequence is that if we use more electricity, the average price per kWhr decreases.  This is actually a disincentive to decrease carbon dioxide emissions, and an incentive to consume more electricity, and in effect, consumers who use less electricity are subsidising those who use more.

So what is driving these steep increases?

According to the Queensland Times on 20 February 2018,

“Energy Queensland – Energex and Ergon – returned a profit of $881 million in 2017, a decrease of $61 million, due to increased borrowings and transmission charges.”

However, “Queensland’s government-owned energy corporations posted a massive $1.9 billion profit last year.

That was a 45 per cent increase on the $1.3 billion in profits recorded in 2016.”

This was mainly from the power generating corporations CS Energy and Stanwell selling to the National Energy Market.

This embarrassment of riches has led the Queensland government to return $50 each to consumers this year, with another $50 next year- taking with one hand and giving back with the other.  This is very little help to business, industry, and agriculture.

So our retail supplier Ergon buys electricity from the wholesalers on the National Energy Market, with our local generator Stanwell selling to this market at the highest price they can get.  Ergon has to return dividends to the state government.  Their only way to ease the squeeze is to increase the return from consumers.

What is happening in capital cities and other states?  How do others compare?  I have no idea.

I will be interested to see whether the Federal government’s promise of lower power prices really eventuates.

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Why are Australian Sea Levels Rising?

October 22, 2018

The answer, my friend, is blowin’ in the wind…. literally.

In brief…

  • At Sydney, the long term sea level rise is about 1 mm per year, with short periods of rapid increase and a long plateau of very small or zero trend in the second half of last century.  As Australia is geologically stable, it is likely that a similar pattern occurred all around the coast.
  • This gradual sea level rise is consistent with oceanic warming since the Little Ice Age, with fluctuations resulting from El Nino-Southern Oscillation (ENSO) changes.
  • Tide gauge data since 1990 from different locations show rises varying from 2.4 mm to 7.2 mm per year.  A significant proportion of this is due to ENSO wind circulation changes.
  • There is no sign of any unusual acceleration in Australian tide gauge data.

The Bureau of Meteorology maintains the Australian Baseline Sea Level Monitoring Project, with a number of tide gauges around the coastline, shown here:

Fig. 1:  Australian Baseline Sea Level Monitoring Project

MSL map

These sites have monthly data only from 1990, mostly later, and two (Thursday Island and Port Stanvac) have very limited data and were not used in this study.   I have used data for Mean Sea Level for all sites on the Australian coastline to find the current situation with sea level rise, and use the much longer dataset from Fort Denison in Sydney Harbour as well for a longer term perspective.  Figure 2 is a plot of all monthly data from all sites.

Fig. 2: Australian Mean Sea Levels

MSL plot abs

Points to note:

  • The mean is a measure of central tendency: the full tidal range is at least twice the values shown for each site.  Broome’s range is well over 11 metres.  Portland has a very small range.
  • An Australian average of these means is meaningless.
  • Each site has a seasonal signal which is not regular.
  • It is difficult to make any meaningful comparison.

However if we look at sites individually, we can at least compare any trends.  Figures 3 and 4 show MSL at sites with the greatest and least trends.

Fig. 3:  MSL at Hillarys

MSL plot abs Hillarys

Fig. 4:  MSL at Stony Point

MSL plot abs StonyPt

According to this very short record, the rate of Australian sea level rise varies in different locations, from a low of 2.4 mm per year in Bass Strait to 7.2 mm per year at Hillarys in Western Australia.  Why is this?

Australia is very stable geologically, and these tide gauges are carefully checked with levelling connections between them and Global Navigation Satellite System (GNSS) sites maintained by State land and survey departments.  Therefore differing rates of land movement are unlikely to be responsible.

We need to compare all sites, and as well remove the seasonal signal.  To do this I calculate monthly anomalies for each site, then plot the results in Figure 5.

Fig. 5:  Monthly anomalies for all Australian sites:

MSL plot all anoms

With the seasonal signal removed, the data show some roughly similar patterns for all sites.  I now plot the mean of these anomalies, to find an “average” Australian sea level trend.

Fig. 6:  Average of all MSL anomalies

MSL anoms trend

All sites show marked dips in 1997-98 and 2015-16, clearly shown in the average.  The influence of El Nino perhaps?  Figure 7 shows the mean of all MSL anomalies with the scaled Southern Oscillation Index (SOI).

Fig. 7:  Average of all MSL anomalies and SOI/200

Aust MSL and soi

My first response was “Wow!”  Next, sea level plotted against SOI:

Fig. 8: MSL as a function of SOI

MSL scatterplot all v soi

For every one point increase in the SOI, Australian sea level rises an average of 3.2 mm, and SOI change can account for more than a third of sea level rise.  Now we check how the SOI has behaved over the last 27 years.

Fig. 9:  Trend in SOI, 1991-2018

SOI plot trend

In this short record, the SOI has increased by about 8 points.

From this, we can deduce that a portion of the perceived sea level rise since 1991 is due to the influence of the El Nino- Southern Oscillation (ENSO), of which SOI is a strong indicator.

What mechanism could there be for this?  The SOI is calculated from the difference in atmospheric pressure between Tahiti and Darwin.  Darwin’s sea level is compared with the SOI in Figure 10.

Fig. 10:  Darwin MSL anomalies and SOI/100

MSL plot Darwin SOI

The match is very close, as the plot of MSL vs SOI shows:

Fig. 11:  Darwin MSL as a function of SOI

MSL plot Darwin vs SOI

SOI has about twice the effect on MSL at Darwin as it has on the Australian average, and more than half sea level rise can be accounted for by change in SOI.  Here’s my explanation:

During La Nina, when SOI is high, the northwest monsoon is strengthened, the monsoon trough penetrates further into northern Australia in summer with lower atmospheric pressure and stronger northwest winds.  This combination pushes the sea up against the northwest coast, raising the sea level.  In winter, the monsoon disappears and winds are predominantly from the east.  During El Nino, the monsoon is weakened and may fail completely.  Thus northwest winds are weaker and the sea level is markedly lower.

That’s all very well for Darwin and other sites in northern Australia, but take a look at Figure 12, which compares seal level at Darwin with Spring Bay, in southern Tasmania, and about as far from Darwin as you can get without a passport.

Fig. 12: MSL at Darwin and Spring Bay

MSL plot Darwin Springbay all

Note that in some (but not all) El Ninos (marked) Spring Bay sea level is also strongly affected.  Note also that sea level at Spring Bay appears to start rising again several months before Darwin, in other words before the SOI starts rising.

The 2015-16 comparison of anomalies shows the Spring Bay sea level at its lowest in September 2015, rising strongly and four months before Darwin’s.

Fig. 13: MSL at Darwin and Spring Bay 2015-16

Darwin SpringBay anoms 20152016

To understand this we need to consider circulation patterns as they change through the year and with ENSO events, and their effect on local sea levels.  The following plots show the absolute 2015-2016 monthly mean sea levels and the long term average for each month.

Fig. 14: MSL at Darwin 2015-16 compared with average monthly levels

Darwin abs 20152016

Darwin’s long term average sea level is highest at the peak of the Wet season (February – March) and lowest in the Dry (July – August).  In 2015, the high was reached in January and the low in July- both one month earlier- and the 2016 high was in March- one month later.  Below normal sea levels lasted from April 2015 to April 2016.

In contrast, Spring Bay’s average sea level is highest in the southern wet season (Winter-July) and lowest in the summer dry season (November to February).  In 2015 the high was reached in May and the low in September, and the 2016 high in May.

Fig. 15: MSL at Spring Bay 2015-16 compared with average monthly levels

Spring Bay abs 20152016

This happens at other sites in the southeast of Australia (from Portland to Port Kembla including Tasmania).

Fig. 16:  Australian sea level at sites in the north and southeast.

MSL plot Nth SE

Note that the same pattern applies: sea level is lower in strong El Ninos and rises before the north (in 1997-98 and 2015-16 but not so clearly in 2006-07).

A possible explanation is that circulation changes associated with the ENSO are not restricted to the tropics, although that is where the effects are largest and most visible. In normal (non-El Nino) years, the sub-tropical ridge moves north over the continent in winter, and the winter storms around the lows to its south bring rain and winds from the south-west quarter to the southern coast, particularly South Australia, Victoria, and Tasmania.  These winds cause the sea to pile up (by a few centimetres) against the southern coast.  In summer, the sub-tropical ridge moves south, rain bearing storms mostly pass to the south of the Australian region, and blocking highs in the Tasman Sea bring strong north-west winds across the south-east of Australia.  This causes sea level to fall.

In a strong El Nino, these conditions occur earlier, with a rapid retreat south of the sub-tropical ridge so that winter storms with south-westerly winds are fewer and weaker and sea level is lower in winter and spring.  Summer sea levels (November to January) are close to normal.

Figure 17 tests the response of sea level to barometric pressure at Spring Bay.

Fig. 17:  Spring Bay MSL anomalies as a function of barometric pressure anomalies

SpringBay MSL vs Press.jpg

The result is clear.  More than half of sea level change is due to pressure variation, which causes winds to change.

The effect is much greater at Darwin.

Fig. 18:  Darwin MSL anomalies as a function of barometric pressure anomalies

Darwin MSL vs Press

By the way, how much does increase in sea temperature affect sea level?

Fig. 19:  Spring Bay MSL anomalies as a function of temperature anomalies

SpringBay MSL vs SST

At Spring Bay, very little.  An increase of one degree could raise sea level by 17 mm, but R-squared of 0.033 is tiny compared with 0.527 for air pressure.

Whatever causes El Nino also causes the southern seasonal weather cycle to occur earlier, and sea levels rebound several months before they do in the tropics.

What of the longer term?

The Australian Baseline Sea Level Monitoring Project data are limited to sea levels since 1990, so the record is too short to make assumptions about long term sea level rise, and certainly not about the future.  There are longer datasets available however.  Sydney Harbour (Fort Denison) has data from 1914.

Fig. 20: MSL anomalies at Fort Denison (Sydney)

Sydney 1914 to 2018

That’s a long term sea level rise of 1 mm per year, or 104 mm in 100 years- a bit over 4 inches.  Now there has been an apparent “acceleration” since 1991, matching the data at nearby Port Kembla:

Fig. 21: MSL anomalies at Fort Denison (Sydney) 1991-2018

Sydney 19912018

But once again note the correspondence with the SOI:

Fig. 22: MSL anomalies and scaled SOI Sydney 1991-2018

Sydney 19912018 soi

A significant portion of the recent sea level rise at Sydney can be attributed to a short term rise in the SOI.

So is this recent rapid rise unique?  By calculating the trend in sea level over 10 year periods, we can see periods when sea level rise has accelerated or slowed in the past:

Fig. 23:  10 year running trend in MSL at Sydney

10yr trends MSLSydney

The most recent rise in sea level of 7 to 8 mm per year over 10 years is less than that of the rise to 1953, when sea level rose by 10 mm per year.

If you think 10 year trends are too short, Figure 21 shows 30 year trends at Sydney:

Fig. 24:  30 year running trend in MSL at Sydney

30yr trends MSL Sydney

The current 30 year trend is exactly the same as the trend to 1965:  2.4 mm per year.  For the 30 year period to the mid-1990s the trend was zero.

Conclusion:

Across all tide gauges of the Australian Baseline Sea Level Monitoring Project, a significant proportion of sea level rise since 1990 is due to circulation changes associated with the El Nino- Southern Oscillation.  The effect is much greater in the north and west, where sea level rise is highest, but also is evident in the south-east.

Sydney’s long term record tells us that sea level has been rising at an average rate of about 1 mm per year.  There have been short periods of rapid increase and a long plateau of very small or zero trend in the second half of last century.  As Australia is geologically stable, it is likely that a similar pattern occurred all around the coast.

This gradual sea level rise is consistent with oceanic warming since the Little Ice Age, with fluctuations resulting from ENSO changes.

There is no sign of any unusual acceleration in Australian tide gauge data.  In 100 years from now sea level could be expected to be 100 mm to 200 mm higher.  A sea level rise of 5 to 10 times this amount is purely speculative and not based on empirical data, but instead is based on the worst case scenario of computer models.

Tropical Cyclones and Global Warming: A Reality Check

September 15, 2018

Recently there was widespread media reporting of Queensland Emergency Services Minister Craig Crawford’s release of “a plan designed to help first responders get ready for future weather extremes.”

In the ABC Online report, these quotes from Mr Crawford are emphasised:

“There are plenty of people out there who are climate change sceptics… but the consensus is our fire seasons are getting hotter and longer and our flood and cyclone seasons are certainly getting stronger and more frequent.”

“If we’re going to have cyclones happening in parts of Queensland that they don’t normally happen right now it means that we’re going to have to expand all the areas where we have response training, capability and everything like that,” Mr Crawford said.

Cyclone seasons getting stronger and more frequent?  Cyclones happening in parts of Queensland that they don’t normally happen right now?  Time for a reality check.

The Bureau of Meteorology has a useful resource in its Southern Hemisphere Tropical Cyclone Data Portal  which shows the tracks of all cyclones since the 1969-1970 season.  By clicking on each track you find details of each.   This is the 2017/18 season:

Fig. 1:  Cyclones of the 2017/18 season

Cyclone portal

I have used it to look at all cyclones that have crossed the coast of Australia (and I have included TC Nancy which came very close and whose impact was strongly felt without actually crossing the coast.)  I have counted the cyclones that crossed the coast in every month from October 1969 to now, allocating them to those parts of the northern coastline that they predominantly affected- the north-west, Northern Territory, Gulf of Carpentaria and northern Cape York, north-east Queensland, south-east Queensland (south of the Tropic of Capricorn), and New South Wales.

So here are some facts to annoy our Global Warming Enthusiast friends, and to demonstrate how ill-informed our Emergency Services Minister is.

Fig. 2: Total number of cyclones per season

All cyclones Aust

There has been a decrease in the number of cyclones over the past 48 years, a rate of five less in 100 years.  There has been little change in Western Australian cyclones:

Fig. 3: Total number of cyclones per season hitting North-West Australia

All cyclones NW

Whereas there has been a very noticeable decrease on the east coast (Queensland and NSW):

Fig. 4: Total number of cyclones per season hitting the east coast

All cyclones East coast

which is well illustrated by this plot of cyclones crossing the Queensland coast south of the Tropic of Capricorn:

Fig. 5: Total number of cyclones per season hitting south-east Queensland

All cyclones SEQ

And these images of cyclone tracks are instructive:

Fig. 6: Cyclones of south-east Queensland 1969-1992

SEQ cyclones to 92

Fig. 7: Cyclones of south-east Queensland 1992-2018

SEQ cyclones since 92

Oswald, Marcia and Debbie crossed the coast north of the Tropic of Capricorn and were rain depressions by the time they reached the south-east.

The difference is obvious.  No cyclone has crossed the coast south of Yeppoon since TC Fran in 1992.  26 years without a cyclone- people (and Mr Crawford) forget we had three in 1971.  If we do get another one no doubt it will be blamed on climate change.

So what connection is there between temperature and cyclones?

Fig. 8:  Australian tropical cyclones as a function of sea surface temperature

All cyclones Aust vs sst trop

As temperatures go up, cyclones go down!

Fig. 9:  Australian tropical cyclones as a function of Southern Oscillation Index

All cyclones Aust vs soi

The SOI is an indicator of El Nino, La Nina, or neutral conditions.  According to the BOM, consistently below -7 indicates El Nino, and above +7 indicates La Nina.  It is obvious that there have been very few cyclones in seasons with El Nino conditions, with the vast majority in neutral or La Nina conditions, and higher SOI indicates greater likelihood of cyclones crossing the coast.  This is not new, and the Bureau makes this clear.

Fig. 10:  Tropical cyclones in La Nina years

BOM map la Nina

Fig. 11:  Tropical cyclones in El Nino years

BOM map el nino

Future trends:

The Bureau discusses future trends at length at http://www.bom.gov.au/cyclone/climatology/trends.shtml

but seems to base its conclusions entirely on climate models:

There remains uncertainty in the future change in tropical cyclone frequency (the number of tropical cyclones in a given period) projected by climate models, with a general tendency for models to project fewer tropical cyclones in the Australia region in the future climate and a greater proportion of the high intensity storms (stronger wind speeds and heavier rainfall).

This is the BOM plot of severe and non-severe cyclones, which includes all tropical cyclones from 90E to 160E south of the Equator, many of which remained well offshore.

Fig. 12: Severe and non-severe tropical cyclones

BOM graph

Is there any evidence for cyclones becoming stronger, if fewer?  According to the BOM’s history of cyclones, no.  This graph plots the number of cyclones rated as severe by the Bureau (<970 hPa central pressure at peak intensity- low pressure is a good predictor of wind speed).  Interestingly, Marcia and Debbie are not listed as severe, but are described as severe in their reports, and definitely were, so I have included them in the tally.

Fig. 13: Severe land-falling tropical cyclones

Severe cyclones Aust

And showing how the proportion of severe tropical cyclones as a percentage of all land-falling cyclones has changed:

Fig. 14: Proportion of land-falling tropical cyclones rated as severe

Severe cyclones Aust %

Tropical cyclones in the past 48 years have decreased in number and intensity, and the proportion of severe tropical cyclones has also decreased, although it is entirely likely that this situation could reverse due to natural variability.

The Government’s Response

The Queensland Government is concerned cyclones may strike further south than they currently do.  They have records of cyclones going back 150 years.  Many, many of them have affected south-east Queensland and NSW.

The worst natural disaster in recorded Australian history was in March 1899 when TC Mahina (the Bathurst Bay cyclone) killed 307 people.

Here are some other significant tropical cyclones recorded by the Bureau:

February 1893 a cyclone crossed near Yeppoon.  This led to the Brisbane River floods.

January 1918. The Mackay cyclone, which caused many deaths.  There was a large storm surge and a barometric pressure reading of 932.6 hPa in a private barometer, and less than 944.8 hPa at the Post Office as the flange on the instrument prevented the needle from going lower.  Inland rainfall caused the highest recorded flood in the Fitzroy River.

March 1918. The Innisfail cyclone.  The pressure dropped to 926 hPa at Mourilyan Sugar Mill.  There was a large storm surge.  Almost all buildings in the town were destroyed or badly damaged.

March 1949.  A cyclone struck Rockhampton and Gladstone.

1967 TC Dinah affected southern Queensland and NSW.  The pressure dropped to 944.8 hPa at Sandy Cape.

In Queensland, counting only those cyclones that have actually crossed the coast, not just approached, here is a list of tropical cyclones since 1970 (see Figure 6) that have struck south of the Tropic of Capricorn (Rockhampton or Yeppoon.)

February 1971 TC Dora

February 1972 TC Daisy

March 1972 TC Emily

January 1974 TC Wanda

March 1974 TC Zoe

February 1976 TC Beth

March 1976 TC Dawn

February 1981 TC Cliff

March 1992 TC Fran

TC Nancy (January 1990) came close but did not actually cross the coast.

TC Marcia in February 2015 crossed the coast near Shoalwater Bay before moving south over Rockhampton.

There is also an impressive list of cyclones which have caused deaths and wind, wave, and flooding damage in NSW.   These include cyclones from 1892.  Included are:

March 1939, TC crossed the coast at Cape Byron.

January 1950   The Sydney cyclone of 1950, when the pressure dropped to 988 hPa in Sydney.

February 1954, TC crossed the coast at Tweed Heads, where the pressure dropped to 973 hPa.

February 1957 TC crossed the coast south of Port Macquarie.

January 1967 TC Dinah caused a large storm surge in the Tweed River.

February 1967 TC Barbara crossed the coast near Lismore.

March 1974 TC Zoe crossed the coast just north of the border and travelled through northern NSW.

January 1990  TC Nancy did not cross the coast but passed about 50km east of Cape Byron.

The Reality

Contrary to Minister Crawford’s claim, and the media’s breathless and uncritical reporting, tropical cyclones in the past 48 years have decreased in number and intensity, and the proportion of severe tropical cyclones has also decreased.  Predictions of future trends are purely speculative.  The current 26 year lull in tropical cyclones hitting the south of Queensland and northern NSW is unusual.  In the past it was normal for cyclones to strike much further south than they do now.  We should not become complacent.

Drought and Climate Change Part 2: Rainfall deficiency

September 7, 2018

In my last post, I looked at long term rainfall trends across Southern, South Eastern, and South Western Australia, and found no cause for alarm at recent rainfall decline.  Droughts can occur at any time and cause much hardship across wide parts of the country.  Global Warming Enthusiasts are gnashing their teeth, believing man-made climate change is making droughts worse.  Greg Jericho in the Guardian wrote last Thursday 30th August, “If you are a prime minister going out to the rural areas and you’re not talking about climate change, and you’re not suggesting that droughts are more likely to occur and thus farmers need to take greater responsibility, then you are failing in your job.”

Are droughts really “more likely to occur” with climate change, and is there any evidence they are becoming more frequent, more intense, and more widespread with global warming?

The Bureau of Meteorology says:

Drought in general means acute water shortage.

The Bureau’s drought maps highlight areas considered to be suffering from a serious or severe rainfall deficiency…. for three months or more….

……

  • Serious rainfall deficiency: rainfall lies above the lowest five per cent of recorded rainfall but below the lowest ten per cent (decile range 1) for the period in question,
  • Severe rainfall deficiency: rainfall is among the lowest five per cent for the period in question.”

This map of meteorological drought (areas in the lowest ten and five percent of 12 months rainfall to 31 August) shows the extent across Australia:

Fig. 1:  Recent 12 month Rainfall Deficiency Australia

12m drought map

Parts of central and southern inland Queensland, parts of eastern South Australia, many parts of New South Wales, and small areas of Victoria are in drought.  Notice that the droughted areas are separated by areas that are not in drought.

But, but… all of NSW is in drought, isn’t it?

100% of NSW has been drought declared, and 54.7% of Queensland, and indeed some parts are in a very bad way.   But “drought declaration” is the term the media, politicians, and general public don’t understand.  They assume that because 100% of NSW is drought declared, this means all of NSW is in drought.  Not so.  Drought declaration is a political or at best administrative instrument for giving drought assistance to farmers and communities.  Some areas of Queensland that have not yet been drought declared really are in the grip of drought; some “drought declared” areas of NSW are not in drought, as this map of NSW (6 months March to August) shows:

Fig. 2: 6 month Rainfall deficiency NSW

NSW map 6m

Of course the blank areas have had below average rainfall, which may turn into full blown drought, so the NSW government is being proactive.  However, they are not at this time in meteorological drought with serious or severe rainfall deficiency.

Trends in Drought Incidence

In the bigger picture, how widespread, how intense, how long lasting, and how frequent are droughts becoming in Australia?  For this analysis I use monthly rainfall data from 1900 to July 2018 from the Bureau of Meteorology at their Climate Change page, and calculate the number of months where the rainfall total of the previous 12, 18, 24, or 36 months shows severe deficiency (in the lowest 5 percent of all months since 1900) or serious deficiency (in the lowest 10 percent).  (I am looking at droughts that last at least 12 months, not just short dry spells, and 12 months total rainfall includes rain in all seasons.)

I do this for various regions, as shown on the map below.

Fig. 3:  Australian Regions

Climate regions

I have plotted the number of consecutive months where the 12, 18, 24, and 36 month totals are in the lowest 5% and 10% of their respective values since 1900, and calculated the trend in months per century of increase or decrease. There are 96 plots, so I will only show a couple of examples, and summarise the results in Table 1 below.

Table 1:  Trends in Drought Incidence (Months per 100 Years) for various Australian Regions

Trend table

A negative trend indicates decreasing drought incidence, shaded green; a positive trend indicates increasing incidence, shaded pink.

Australia wide, and in the regions of Northern and Southern Australia and the Murray Darling Basin, and South Australia as a whole, since 1900 droughts of all lengths have become less frequent, and because these are broad regions, less widespread.  There is no evidence that climate change is making droughts more likely to occur, except for smaller areas (Victoria, Tasmania, and SW Australia) which have an increasing frequency of droughts of all lengths.

36 month dry periods are more frequent in SW Australia, SE Australia, Eastern Australia, Tasmania, Victoria, (and interestingly Queensland, but only for <10% deficiency).

Some examples will illustrate the complexity of the picture.

Fig. 4:  Number of consecutive months per calendar year of 12 months severe rain deficiency: Australia

12m 5% Aust

Fig. 5:  Periods of 36 months serious rain deficiency: Australia

36m 10% Aust

In the past droughts of all lengths and severity were more widespread across Australia.

Fig. 6:  Periods of 36 months severe rain deficiency: Southern Australia

36m 5% Sthn Aust

Similarly, multi-year periods of severe rain deficiency were much more frequent and widespread across Southern Australia before 1950.  In the last 50 years there has been only one month where the 36 month total was in the lowest 5th percentile.

Fig. 7:  Periods of 12 months severe rain deficiency: New South Wales

12m 5% NSW

Fig. 8:  Periods of 36 months severe rain deficiency: New South Wales

36m 5% NSW

Fig. 9:  Periods of 12 months serious rain deficiency: New South Wales

12m 10% MDB

Fig. 10:  Periods of 36 months serious rain deficiency: New South Wales

36m 10% NSW

Across NSW, 4 months of 2018 had 12 month totals in the serious deficiency range, but none in the severe range.  Droughts of all severity and duration have become less frequent and widespread.  The Millennium Drought lasted longer but was less severe than the Federation Drought.

The Murray-Darling Basin lies across four states including most of NSW, and is Australia’s premier food and fibre producing region.  The current drought is affecting many areas in this region.

Fig. 10:  Periods of 12 months severe rain deficiency: Murray-Darling Basin

12m 5% MDB

Fig. 11:  Periods of 12 months serious rain deficiency: Murray-Darling Basin

12m 10% MDB

Fig. 12:  Periods of 36 months serious rain deficiency: Murray-Darling Basin

36m 10% MDB

We can conclude from these plots of the Murray-Darling Basin that this drought is patchy, and while nasty, is not the most intense or long lasting even in living memory, let alone on record, and that droughts are becoming less frequent and less widespread.

Fig. 13:  Periods of 36 months severe rain deficiency: Queensland

36m 5% Qld

Fig. 14:  Periods of 36 months serious rain deficiency: Queensland

36m 10% Qld

Queensland has little trend in frequency of drought with severe deficiency over three years but less severe droughts have been more frequent- due to the droughts of the 1990s and the Millennium drought.

Fig. 15:  Periods of 36 months serious rain deficiency: Victoria

36m 10% Vic

The Millennium Drought stands out as the longest period of widespread serious rain deficiency.

Fig. 16:  Periods of 36 months serious rain deficiency: South-West Australia

36m 10% SW Oz

Here we see that all but one month of all the 36 month periods of serious rain deficiency have occurred since 1970, reflecting the marked drying trend.  This really is an example of climate changing.

Winter rainfall

Fig. 17:  Winter Rainfall Deciles across Australia, 2018

winter rain 2018

According to the Climate Council, “Climate change has contributed to a southward shift in weather systems that typically bring cool season rainfall to southern Australia.”  However the usual areas affected by this southwards shift, Tasmania, south-west Victoria, southern South Australia, and most of the south-west of Western Australia, have had an average to above average winter.  Droughted areas are to the north.   The southwards shift of weather systems caused by Climate Change cannot be claimed to have any part in this drought.

Drought is a dreadful calamity wherever and whenever it occurs.  And on top of other difficulties in Queensland is the bureaucratic approval process under Vegetation Management regulations before graziers can push mulga to feed starving stock.

This drought may get worse if a full El Nino develops.  It is unlikely to break before six months or even 18 months.  By then it will be much more severe and widespread.  However, climate change has not caused this drought.  While there is evidence for increasing drought frequency and thus likelihood of more drought in the future in Tasmania, southern Victoria, southern South Australia, and the south-west of Western Australia, across the rest of Australia there is strong evidence that droughts have become less frequent, less severe, less widespread, and shorter.  If climate change is claimed as the cause of increasing droughts in the far southern regions, then climate change must also be causing less frequent droughts across the vast bulk of Australia, where droughts are always “likely to occur”, but not “more likely”.

Drought and Climate Change Part 1: Long Term Rainfall

September 1, 2018

The current drought conditions in New South Wales and large parts of Queensland are getting a lot of media attention, and of course the usual suspects are linking it to climate change and our apparently “unambitious” emissions targets in the NEG.  But are droughts really becoming “the new normal”, and are they becoming more frequent, more intense, and more widespread with global warming?

There are two aspects to consider: long term rainfall trends in various regions, and periods of rainfall deficiency.  In this post I will look at long term rainfall, and Part 2 will look at rainfall deficiency i.e. drought incidence.

Long term rainfall trends

Everyone “knows” southern Australia is getting drier.  Paul West in Feeding Australia Pt 2 on the ABC says there has been a 28% decrease in rainfall over the past 30 years.  The Climate Council says “Over the past 30 years, there has been a discernible decrease in rainfall across southern Australia.” That’s their headline; in the details the Climate Council’s June 2018 Fact Sheet says:

“Climate change has contributed to a southward shift in weather systems that typically bring cool season rainfall to southern Australia. Since the 1970s late autumn and early winter rainfall has decreased by 15 percent in southeast Australia, and Western Australia’s southwest region has experienced a 15 percent decline in cool season rainfall.”

Both are true, but both are only half true, and in fact the ABC and the Climate Council as usual lie by omission.

The whole story is more complex but shows a completely different, and much less dramatic picture.  Using data for cool season (April- September) rainfall from the Bureau of Meteorology we can check on different time periods.

Fig. 1:  Cool season rainfall, Southern Australia, 1988-2017

Cool rain Sth Oz 19882017

Yes, if this is what Paul West based his statement on, 2017 had about 28% less rain than in 1988.  I hope he didn’t- comparing single years would be pretty bad science.  However there has been a marked decrease in cool season rainfall over this period, so the Climate Council is quite correct.

However, Figure 2 shows the big picture- since 1900.

Fig. 2: Cool season rainfall, Southern Australia, 1900-2017

Cool rain Sth Oz 19002017

Oops! Rainfall has in fact increased over southern Australia.

The reason for the current gnashing of teeth is that “living memory” only goes back about 70 years, and we are comparing current conditions with those of a few decades ago.  Figure 3 shows the average rainfall for the 10 year periods up to 2017.

Fig. 3: 10 year average Cool season rainfall, Southern Australia, 1900-2017

Cool rain Sth Oz 19002017 10yrs

As you can see, the average rainfall of the 10 years 2008 to 2017 was about 7% less than in the 1950s, 1970s, 1980s, and 1990s, but more than the 1920s and 1930s, and nearly 10% more than the 10 years to 1947.  Of the 10 decades before this one, five had less rain and five had more.  Southern Australian cool season rainfall is not “the new normal”, it is in fact “the old normal”.

Let’s now look at South-East Australia, below 33 degrees South and east of 135 degrees East.

Fig. 4: Cool season rainfall, South-Eastern Australia, 1988-2017

Cool rain SE Oz 19882017

Again there is an obvious decrease in rain over the last 30 years.

Fig. 5: Cool season rainfall, South-Eastern Australia, 1900-2017

Cool rain SE Oz 19002017

There has been a small decrease in cool season rainfall over the whole 118 years.  Again there was a marked step up in rainfall from the mid-1940s.  The plot of 10 year averages shows this more clearly:

Fig. 6: 10 year average cool season rainfall, South-Eastern Australia, 1900-2017

Cool rain SE Oz 19002017 10yrs

There was a decreasing trend up to the 1940s, and a decreasing trend from the 1950s to now.  The current 30 to 40 year decrease is nothing new.

However, rainfall records for individual sites go back much longer.  What do these show?  Here is a plot of monthly rainfall for all months at Penola, in South Australia, starting in 1863:

Fig. 7: Monthly rainfall (all months January 1863 – December 2017) at Penola, S.A.

Penola rain monthly

A very long term decreasing trend.  Running 12 month totals show wetter and drier periods:

Fig. 8: 12 month running total rainfall (all months January 1863 – December 2017) at Penola, S.A.

Penola rain 12m

There were very severe droughts around World War 1 and the late 1960s, but a big step up in the 1950s.  This is more obvious in a plot of 10 year totals:

Fig. 8: 120 month running total rainfall (all months January 1863 – December 2017) at Penola, S.A.

Penola rain 120m

This site shows a very long term rainfall decrease, complicated by droughts and strings of wetter years, and a huge step up in the middle of last century.  This site is one of many of varying lengths in the High Quality Rainfall dataset.  Nearly all show the mid-century step up, some show a small long term increase, some show a small long term decrease.

I amalgamated all 84 stations, and here are the plots for all months. Firstly, the number of stations reporting:

Fig. 9: Count of all stations in S.E. Australia reporting, all months

All SE sites Count

There are a number of long term sites.  There were 50 sites in 1898, as in 2017 (several had not yet reported January 2018).

Note: the following plots are of naïve means: there is no area averaging.

Fig. 10: S.E. Australia monthly rainfall (all months)

SE Oz all months

Note a small increase.  Now 12 month running totals of these means:

Fig. 11:  S.E. Australia 12 month rainfall (all months)

SE Oz 12 months

Now the 10 year running total of monthly means, but since 1898 when the number of stations was the same as now:

Fig. 12:  S.E. Australia 120 month rainfall (all months)

SE Oz 120 months 1898

The mid-century step up is obvious, with a decline since then.  The 10 year rainfall to December 2017 is about what it was a century ago.

I now turn to South West Australia.

Fig. 13: Cool season rainfall, South-Western Australia, 1988-2017

Cool rain SW Oz 19882017

A very serious decline since 1988.

Fig. 14: Cool season rainfall, South-Western Australia, 1900-2017

Cool rain Sw Oz 19002017

As you can see, the decline has been around since 1900, but with a marked step down starting in 1968, with a steep but uneven decline since then.  10 year averages show this clearly.

Fig. 14: 10 year average cool season rainfall, South-Western Australia, 1900-2017

Cool rain SW Oz 19002017 10yrs

Conclusion:

The long term data show a complex picture of long term cool season rainfall decline in south-west and some parts of south-east Australia, while southern Australia as a whole shows a very small increase.  It is true that rainfall has declined, as the Climate Council and ABC claim, over the past 30 and 40 years in many parts, but that is only half the story.  The whole story is much less dramatic.  Rainfall has been declining for a long time in WA, and in south-east Australia has been declining in two stages, separated by a large step up in rainfall in the middle of last century.

The current low rainfall is not “the new normal” but entirely consistent with “the old normal” and should be seen as just plain “normal”.  This is Australia.  Get used to it.

Solar Exposure

June 6, 2018

The Bureau of Meteorology publishes many useful datasets on its Climate Data Online portal, including one minute solar exposure data for selected sites around Australia.  You have to register to receive monthly data here.

(In contrast with their one minute temperature data which are not available at CDO but must be requested and purchased, and are really “final second of each minute”, their solar exposure data are (a) free, and (b) include for each minute, maximum 1 second irradiance, minimum 1 second irradiance, and THE MEAN IRRADIANCE FOR THE PREVIOUS 60 SECONDS.  Why not temperature?  We can only wonder.  But I digress.)

I am naturally curious and enjoy finding out new stuff, so in this post I’ll show a number of plots for the months of July 2017, December 2017, and February 2018 to illustrate some things I’ve found about summer and winter solar exposure for Rockhampton.  Why Rocky?  It’s where I live, and is just a few kilometres north of the Tropic of Capricorn.  At the end of December the sun is directly overhead, so December shows interesting information.  February is typically the wettest and cloudiest month, and July usually the coldest and driest.

One minute solar exposure data have several components:  direct (normal) irradiance (rate of energy from the direct beam of the sun tracked throughout the day); direct horizontal irradiance (the amount striking a horizontal surface); diffuse irradiance (radiation scattered from the atmosphere including dust and clouds striking a horizontal surface); and “global” irradiance which is the sum of the horizontal and diffuse components.  Also measured is “terrestrial” irradiance, which is downwards infra-red radiation on a horizontal surface, and related to the temperature of the atmosphere, including from clouds and humidity (not just at ground level, but throughout the troposphere).

Figure 1:  Irradiance for February 2018

rocky all feb 18

Note that terrestrial (infra-red) irradiance is fairly constant at around 350-450 watts per square metre, while direct irradiance on a horizontal surface fluctuates from zero to ~1000 W/sq.m., and diffuse irradiance fluctuates from zero to ~900 W/sq.m.  For a closer look here are the same data for one day, 1st February:

Figure 2:  Irradiance for 1 February 2018

rocky all 1 feb 18

Mean horizontal irradiance (the direct beam from the sun on a horizontal surface) is zero in the absence of direct sunlight- at night, but also when clouds are thick enough, and also is greatly reduced even by thinner cloud; at other times, it rises rapidly to ~900 W/sq.m. at noon.

Diffuse irradiance is zero until a few minutes before sunrise, with radiation reflecting from clouds, dust, and other atmospheric particles; similarly just after sundown.  It is much higher in cloudy conditions.

IR irradiance, relatively constant before sunrise at ~400 W/sq.m., rises during the day as the atmosphere warms.  It also fluctuates with cloudy conditions, more noticeably at night.  Clouds are composed of water droplets and emit IR radiation- a natural greenhouse effect.

The next plot shows how irradiance varies over four days as clouds and rain increase.

Figure 3:  Irradiance for 1 – 4 February 2018

rocky all 1 to 4 feb 18

The effect of cloud on horizontal irradiance is obvious.  Diffuse irradiance is maximised on the 3rd; on the 4th, clouds reflect most solar radiation, the surface is cool, and IR irradiance which had increased due to cloudiness on the 2nd and 3rd, returns to ~400 W/sq.m.

By contrast, Figure 4 shows irradiance during the hottest week of February with maxima above 39.1C (41.1C on the 12th).

Figure 4:  Irradiance for 11 – 15 February 2018

rocky all 11 to 15 feb 18

Note the smooth curves of horizontal and diffuse irradiance on 11th and 12th; early morning cloud on 13th – 15th with diffuse and IR increasing; and IR increases with surface temperature, peaking in the late afternoon- with little surges as clouds pass overhead.

Figure 5 shows the variation of IR irradiance during February.

Figure 5:  IR Irradiance for February 2018

rocky IR feb 18

The diurnal fluctuation typically of 60-70 W/sq.m. is obvious, as is the change over time.  The bottom of the daily fluctuation occurs in the early morning.  Notice the effect on the minimum temperature:

Figure 6:  Minima for February 2018

Tmin Feb 18

The last plot for February shows the irradiance from the direct beam of the sun tracked throughout the day:

Figure 7:  Direct Irradiance for February 2018

rocky direct feb 18

It’s interesting that the irradiance of the direct beam is not constant, even on clear sunny days.  It is possible that the rain of the first four days removed suspended particles; from 5th to 9th the wind was from the east or south-east (from the sea); from the 11th to 15th it was from the north west to north, blowing dust and smoke from the land, resulting in slightly dimmer conditions.

I now turn to July 2017.  July is usually the coolest and driest month in Rockhampton.

Figure 8:  Irradiance for July 2017

rocky all july 17

Due to the much lower solar angle, horizontal irradiance is much lower than February, mostly from 600 to 700 W/sq.m.  IR irradiance is more variable, so needs a closer look.

Figure 9:  Irradiance for 6 – 10 July 2017

rocky all 6 to 10 july 17

These were cloudy days, with wind from the north-west on the 6th to 8th, with a south-east change on the 9th with light rain on 9th and 10th.

19th to 22nd shows more of this atypical winter weather.

Figure 10:  Irradiance for 19 – 22 July 2017

rocky all 19 to 22 july 17

Overcast and 90% Relative Humidity in the morning of the 19th, then RH fell rapidly, with the lowest 3:00 p.m. reading for the month (16%) and 9:00 a.m. (36%) on the afternoon of the 21st and the morning of the 22nd– when IR, and minimum temperature, were lowest for the month.  The 20th and 21st were clear sunny days.   Some cloud arrived on the afternoon of the 22nd.

Figure 11:  Irradiance for 25 – 28 July 2017

rocky all 25 to 28 july 17

This is typical winter weather- clear skies, cool nights followed by warm sunny days.  Note the smooth curves for horizontal and diffuse irradiance, both much less than February.  This indicates cloudless skies and low humidity.  There is a little early morning fog or mist as indicated by small wiggles in IR irradiance, but not enough to affect diffuse irradiance.  IR irradiance again peaks in mid afternoon.

Figure 12:  IR Irradiance for July 2017

rocky IR july 17

Due to less direct irradiance, cooler temperatures, and lower humidity, IR irradiance is much lower than in February, and rarely exceeds 400 W/sq.m.  IR fluctuates less in clear dry conditions.   Again, IR is reflected in minima:

Figure 13:  Minima for July 2017

Tmin July 17

Figure 14:  Direct Irradiance for July 2017

rocky direct july 17

Note that direct irradiance is not much less than in February, even for being soon after aphelion: it is the sun’s lower angle in the sky that makes most of the difference.  The clear dry days on the 20th and 21st have the highest irradiance.

The next plots are for December, around summer solstice and close to perihelion, when days are typically hot and sultry.

Figure 15:  Irradiance for December 2017

rocky all dec 17

The first four days, and the 9th, were cloudy, with rain on 3rd and 4th, as you can see from the horizontal irradiance.  On the remaining days irradiance was close to 1000 W/sq.m.

Figure 16:  IR Irradiance for December 2017

rocky IR dec 17

Heavy cloud, swept in from the Coral Sea, on the first four days, and hotter maxima on the last two, pushed IR well above 400W/sq.m.

And the plot for minima:

Figure 17:  Minima for December 2017

Tmin Dec 17

Last one!

Figure 18:  Direct Irradiance for December 2017

rocky direct dec 17

You will notice that with the sun virtually directly overhead around noon each day (from 1.56 degrees from zenith on 1st December to 0.01 degrees from zenith on Christmas Day), sun tracking direct irradiance is almost the same as the horizontal irradiance.

What have I learnt?  The variability of solar exposure, which is strongly affected by what’s in the atmosphere: dust, smoke, gaseous water, liquid water (clouds); as well as time of year and time of day.  The extent that downwards infra-red irradiance, which is an indicator of atmospheric temperature, is increased by daytime surface temperature and also very noticeably by clouds, and decreased by lower humidity.  How IR strongly influences minima- the greenhouse effect.

Nothing new probably, but I hope you found it as interesting as I did.

Finally:  why, oh why, can’t the Bureau make one minute temperature data freely available, and why does it persist with one second temperature readings rather than the mean over the previous minute, which it calculates with solar exposure?

My next post will look at different factors influencing temperature, including solar exposure.

The Chicken or the Egg?

May 3, 2018

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

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

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

Figure 1: 60 years of carbon dioxide concentration

CO2 abs trend

Ocean temperatures have also increased:

Figure 2:  HadSST3 Sea Surface Temperature from 1958

Hadsst3

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

The following plot appears to support the greenhouse warming theory.

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

SST vs CO2

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

But what if we reverse the axes in Figure 3?

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

CO2 vs SST

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

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

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

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

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

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

12m chg Hadsst3 co2

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

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

lagged 7m 12m chg Hadsst3 co2

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

Here’s the plot of CO2 vs lagged SST:

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

lagged 12m SST vs CO2

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

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

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

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

Hadsst and CO2 58 76

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

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

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

12m chg Hadsst and CO2 58 76

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

lagged 12m chg Hadsst and CO2 58 76

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

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

Summary:

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

UAH, ACORN and Rainfall: Something’s Wrong

April 4, 2018

Tom Quirk had an interesting article posted by Jo Nova this week, at

http://joannenova.com.au/2018/04/bom-homogenization-errors-are-so-big-they-can-be-seen-from-space/

questioning the large number of adjustments coincident with the changeover to automatic weather stations in the 1990s, which appear to have had a large impact on the correlation between BOM’s monthly ACORN mean temperatures and UAH’s Lower Troposphere data for the Australian region.

However, using a different comparison something very strange appears.

For me, his killer plot was this one, showing a huge drop in centred running 13 month correlations between UAH and BOM mean anomalies:

Figure 1: Tom’s plot of monthly correlations:

Tom Q correl plot

Using the same methodology, but with maxima instead of mean temperature anomalies (as tropospheric data better reflect daytime temperatures when there is deep convective overturning), I have replicated his findings.  Note that BOM maxima and rainfall are converted to anomalies from 1981 to 2010, the same as UAH.

Figure 2 is my plot of the running centred 13 month correlations between BOM maxima anomalies and UAH Australian region anomalies for all months of data from December 1978 to February 2018.

Figure 2:  Centred running 13 month correlation between BOM maxima and UAH:

BOM max v uah correl

There are some differences, but like Tom, I find a distinctly low, in fact, negative, correlation in the mid-nineties, centred on April 1996.

However, as I showed in my post “Why are surface and satellite temperatures different?”  in 2015, most of the difference between UAH and BOM maxima can be explained by rainfall variation alone.

Figure 3 is a plot of the monthly difference between UAH and BOM data plotted against rainfall anomalies (also calculated from 1981-2010 means).

Figure 3:

Diff v rain plot

R-squared of 0.54 means a correlation coefficient of 0.73.

This is how the correlation varies over time:

Figure 4:

Diff v rain correl

I have a problem.

There is a major drop in July 1995, but other big ones- October 1998, July 2003, December 2009, September 2015, and the most recent figure, August 2017.   Correlations are much more variable from 1995.  What can be the reason for these poor correlations?

There is also a general decrease in correlation over the years since 1978.

What’s wrong?  Surely rain gauges can’t be faulty?

Has there been a drift in accuracy of the UAH data?

Or has there been a drift in accuracy of BOM temperature measurement?

Any suggestions would be most welcome.

Post Script:

The major drops may occur at about the same time as major ENSO changes, though not always.  This graph plots the above correlations and 13 month centred averages of the SOI (scaled down) together.

Figure 5:

SOI and correlations

The SOI has not been lagged in this plot.  Perhaps the major changes in trade winds, monsoons, and the sub-tropical ridge affect tropospheric temperatures differently from surface temperatures at these times.  But that doesn’t explain the gradual decrease over time.

 

 

Pretty Patterns

March 13, 2018

Most people like pretty patterns.  They are pleasing to the eye.  But that’s no reason to create them when homogenising data, as the Bureau of Meteorology does when creating its ACORN-SAT datasets for a number of sites.

I am indebted to Bob Fernley-Jones, who noticed this and has been trying without success to point out to the Bureau that they need to address this issue.

For example, the Bureau found problems with maximum data from Darwin, especially before the Post Office and its thermometer were blown to bits by a Japanese bomb in February 1942.  Adjustments were needed as the data source moved from the town to the RAAF base.  Before this, apparently the Stevenson screen had become partially shaded by vegetation.  The problem is that the only other stations available for comparison for identifying and adjusting for discontinuities in the data were hundreds of kilometres away- Port Keats Police Station is 243 km away, Katherine is 270 km away, and Wyndham Port is 446 km away.  Port Keats and Katherine have monthly data from 1938 and 1937 respectively (but with many months of data missing from Katherine), and Wyndham Port has daily data available for the whole 1910-1942 period.  So these three distant sites were used to adjust Darwin’s raw data before 02/02/1941, but only Wyndham Port was used to make adjustments for all data before 01/01/1937 and 01/01/1916.

Here is the result.

Figure 1:  Adjustments to Darwin’s daily maxima 1910 to 1942

Darwin daily adj 1910 1942

Now isn’t that a very pretty and pleasing pattern?  The red line shows the difference between Darwin Acorn Tmax and Darwin raw Tmax, for every day from 01/01/1910 to 31/01/1942, revealing a repeating oscillation in values.  Note that from 2 February 1941 there are no adjustments.

The next plots analyse the three distinct periods by month of the year.

Figure 2:  Daily adjustments to Darwin’s maxima 01/01/1937 to 31/01/1941

Darwin daily adj 1937 to 41 max

Note that these are not mean values:  every single day in each month was adjusted by exactly the same amount as every other day in that month.  Every day in June 1937 was cooled by -0.5 degrees C, and likewise every day in June 1938, 1939, and 1940.  Days in April and December were not adjusted, while the Wet months were warmed and the Dry and Build-up months were cooled.  So much for the Bureau’s explanation that only Winter (-0.47) and Spring (-0.57) were adjusted.

Figure 3:  Daily adjustments to Darwin’s maxima 01/01/1916 to 31/12/1936

Darwin daily adj 1916 to 36 max

Again, every single day in each month has been adjusted by exactly the same amount as every other day in that month.  Days in the Wet were cooled by from -0.2C to -1.2C, while days in the Dry and Build-up months were cooled by -1.2C to -2.2C.  That’s some pretty savage adjusting, and does not vary from the first to the last day of each month.

Figure 4:  Daily adjustments to Darwin’s maxima 01/01/1910 to 31/12/1915

Darwin daily adj 1910 to 15 max

Note again that while the adjustments are not as large as 1916-1936, only February has no adjustment to raw data, and all other months have daily cooling adjustments which are the same from the start to the finish of the month.

Unbelievable.

Time for a clean out.

 

 

 

Fingerprints of Greenhouse Warming: Poles Apart

February 26, 2018

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

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

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

Figure 1: North Polar Summers:

NP summers

Figure 2:  North Polar Winters:

arctic all winters

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

Figure 3: Tropics

Tropics TLT

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

Figure 4: South Polar Summers

SP summers

Figure 5:  South Polar Winters:

antarctic all winters

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

Figure 6:  Antarctic winters over land:

antarctic land winters

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

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

C Grim CO2

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

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

Is it because the oceans around Antarctica are cooling?

Figure 9: South Polar Ocean TLT:

SP ocean

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

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

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

Data sources:

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

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

Mandated disclaimer:-

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